Willamette Water 2100

The Willamette Water 2100 project was a collaborative effort of faculty from Oregon State University (OSU), the University of Oregon (UO), Portland State University (PSU), and the University of California - Santa Barbara. It was funded primarily by grants from the National Science Foundation with additional support from the National Oceanic and Atmospheric Administration.

Collaborating universities and primary project funding agency.

About

Click on the links below for background information about the Willamette Water 2100 project.

Shaded relief map of the Willamette River Basin, looking to the west and the Pacific Ocean.  Image credit: Charles Preppernau, OSU.  Photo credits (left to right): USACE, OSU, OSU.

Project Overview

The Willamette River Basin in western Oregon spans nearly 12,000 square miles (30,000 square kilometers), from its snowy, forested headwaters in the Oregon Cascades to its green valley floor. It serves the water needs of 70% of Oregon’s population while supplying ecosystems and an economy that depend on its abundant water supplies throughout the year. Currently, the Willamette River Basin is a water-rich region, but with a warming climate and increasing socio-economic pressures that may not always be the case. Such pressures raise a number of important questions:

  • Will we have enough water to satisfy future needs?

  • Where, when and under what conditions might water scarcity emerge in the coming decades?

  • What policy actions might reduce the potential for water scarcity?

These questions motivated the Willamette Water 2100 project (WW2100), a collaborative research project led by faculty from Oregon State University (OSU), the University of Oregon (UO), Portland State University (PSU) and the University of California-Santa Barbara. The project was funded by the National Science Foundation and the National Oceanic and Atmospheric Administration and ran from October 2010 through September 2016.

Project Purpose

The primary project objectives were to:

  • identify and quantify the linkages and feedbacks among human, hydrologic, and ecologic dimensions of the water system,

  • make projections about where and when human activities and climate change will impact future water scarcities,

  • evaluate how biophysical and human system uncertainties affect these projections, and 

  • evaluate how policy changes or other interventions might affect future water scarcities.

We recognize that the Willamette River Basin is a complex coupled system, one that includes both a natural system (the biophysical components) and a human system (the socio-economic components). The interactions, feedbacks, and evolving characteristics of these different components will control when and where water is abundant or scarce. Modeling such a system has to be selective: it would be impossible to model all aspects of such a complex system in great detail and high resolution. We therefore chose to focus on the elements, relationships, and feedback mechanisms that were most important to the key objectives described above. Fig. 1 describes at a general level the main components of the Willamette River Basin that we modeled in detail. The components include “external drivers” (factors outside the control of people in the basin), including the climate, population growth, and growth in income levels. This conceptual model identifies components related primarily to water supply and demand. Water supply is mainly determined by the biophysical system. Water demand includes human demands for water that are both direct (urban use) and indirect (water allocated by law to protect fish). At a general level, human decisions influence how land and water is used as a result of laws, regulations, and policies, and these in turn influence how individual decisions are made (farmers, consumers), and how society’s representatives (public officials) act to allocate land and water (e.g., reservoir management).

Conceptual diagram of Willamette Envision and its modeling components.

Figure 1. Conceptual diagram of the Willamette water system showing the human and natural system elements that Willamette Envision represents.

Given the complexity of the system, and the detailed spatial and temporal scales at which these different components interact and influence each other, an explicit and quantitative representation of this system requires a computer model to incorporate the many processes and relationships in time and space between and among the natural and human system components, so that we are able to predict how those processes are likely to change over time. As a result, we developed Willamette Envision, a computer model that includes sub-models for each of the biophysical and economic components indicated in Fig. 1. The model captures key biophysical and socioeconomic elements of the system that allow us to address the first two objectives. In addition, the model can be used to ask “What if?” questions of interest to applied scientists, policymakers, and the general public. These questions explore the interactions between land and water use, law and policy, and public management of land and water resources. A more detailed description of Willamette Envision is contained in the model overview section.

Website Purpose

As a companion to the project’s scientific publications, this website provides an overview of project methods and findings, and a portal to access publications, data products, and unpublished project materials. It also contains sections describing the project’s broader impacts activities such as engagement with regional stakeholders, and training provided to university students and K-12 students and teachers. This website is intended for use by scientists, water and land managers, policy and decision makers, and educators.

 

Project Setting

The Willamette River flows north, draining 29,728 square kilometers (11,478 square miles) of diverse landforms and ecology. To the east, High Cascades volcanoes create the basin’s headwaters, with alpine peaks ranging up to 3,426 meters (11,239 feet). To the west, weathered volcanic and sedimentary rocks of the Coast Range bound the basin. Coniferous forests predominate in both mountain ranges and cover about 70% of the basin. Agriculture and city landscapes predominate in the Willamette Valley, with many cities including Eugene, Salem, and Portland clustered along the Willamette River mainstem. The basin’s river systems are home to diverse aquatic species including 36 native fish species, seven of which are listed by the federal or state government as species of concern.

Shaded relief map of the Willamette River Basin, looking to the west and the Pacific Ocean.  Map credit: Charles Preppernau, OSU.  Photo credits (left to right): Al Levno, USFS; OSU; USACE.

Figure 1. Shaded relief map of the Willamette River Basin, looking to the west and the Pacific Ocean. Image credit: Charles Preppernau, OSU. Photo credits (left to right): Al Levno, OSU, USACE.

Water in the Willamette Basin

Seasonal patterns strongly influence water supply and demand in the Willamette River Basin. Winters are cool and wet with abundant precipitation that swells the rivers, recharges soil moisture and groundwater, and creates snowpack in the basin’s Cascade mountain headwaters. In contrast, summers are warm and dry, with little precipitation to meet the warm-weather water demands of forests, agriculture, and cities. A system of 13 federal reservoirs managed by the U.S. Army Corp of Engineers (USACE), called the Willamette Project, also exert a strong influence on hydrology by reducing winter flood peaks and augmenting summer flows in the Willamette River mainstem and major tributaries draining the Cascade mountains. The reservoirs were built primarily to reduce flooding in the Willamette Valley, however they also serve other purposes such as power generation, recreation, and water supply for irrigation. Interest in the reservoirs as a water supply source has grown in recent years, and in 2016 the USACE and Oregon Water Resources Department re-initiated a study to consider how stored water is allocated for summer water needs.

Monthly mean precipitation in the Willamette Basin.

Figure 2. Mean monthly precipitation in the Willamette Basin.

Project Team

 

Photo of participants in the December 4, 2015, WW2100 Learning and Action Network Workshop. Photo credit:  Kayla Martin, OSU

Project researchers and Learning and Action Network team members gathered in Salem in December 2015 for a capstone workshop. Photo credit: Kayla Martin, OSU

Researchers

Lead Principal Investigators

  • Jeffrey McDonnell, Oregon State University (OSU) College of Forestry, now at University of Saskatchewan, Global Institute for Water Security (2010-2012) 
  • Roy Haggerty, OSU College of Earth, Ocean, and Atmospheric Sciences (2012-2015) 
  • Anne Nolin, OSU College of Earth, Ocean, and Atmospheric Sciences (2015-2016) 

Executive Committee (alphabetical)

  • John Bolte, OSU Biological & Ecological Engineering
  • Barbara Bond, OSU Forest Ecosystems & Society (2010-2012)
  • Samuel Chan, Oregon Sea Grant
  • Roy Haggerty, OSU College of Earth, Ocean, and Atmospheric Sciences (2015-2016)
  • David Hulse, University of Oregon, Landscape Architecture
  • William Jaeger, OSU Applied Economics (2013-2016)
  • Philip Mote, Oregon Climate Change Research Institute
  • Anne Nolin, OSU College of Earth, Ocean, and Atmospheric Sciences (2012-2015)
  • Andrew Plantinga, UC Santa Barbara - Bren School of Environmental Science & Management (2010-2013)
  • Project Coordinator: Maria Wright, OSU Institute for Water and Watersheds

Other Research Team Members (alphabetical) 

  • Adell Amos, UO School of Law
  • Meagan Atkinson, MS Student, OSU Environmental Science (Graduated: 2014)
  • Chris Berger, PSU Civil & Environmental Engineering
  • Joe Bernert, Institute for Natural Resources
  • Dan Bigelow, PhD Student, OSU Applied Economics
  • Heejun Chang, PSU Geography
  • David Conklin, Oregon Freshwater Simulations
  • Matt Cox, OSU Biological & Ecological Engineering
  • Kathie Dello, Oregon Climate Change Research Institute
  • Laura Ferguson, MS Student, OSU Marine Resource Management (Graduated: 2015)
  • Elizabeth Garcia, PhD Student, UCSB (Graduated: 2014)
  • Kelly Gleason, PhD Student, Water Resources Science (Graduated: 2015)
  • Stephanie Graham, MS Student (Graduated: 2012)
  • Gordon Grant, USDA Forest Service
  • Stan Gregory, OSU Fisheries and Wildlife
  • Alexey Kalinin, MS Student, OSU Applied Economics (Graduated: 2013)
  • Andrea Laliberte, Earthmetrics
  • Stephen Lancaster, OSU College of Earth, Ocean, and Atmospheric Sciences
  • Christian Langpap, OSU Applied Economics
  • Sarah Lewis, OSU College of Earth, Ocean, and Atmospheric Sciences
  • Maria Lewis Hunter, MS Student, OSU Water Resources Policy and Management (Graduated: 2013)
  • Kayla Martin, Oregon Sea Grant
  • Myrica McCune, Institute for Natural Resources
  • Linda Modrell, Former Benton County Commissioner
  • Kathleen Moore, PhD Student, OSU Geography (Graduated: 2015)
  • Hamid Moradkhani, PSU Civil & Environmental Engineering
  • Anita Morzillo, OSU Forest Ecosystems & Society
  • Phil Neumann, MS Student, OSU Water Resources Science (Graduated: 2012)
  • Anne Nolin, OSU College of Earth, Ocean, and Atmospheric Sciences
  • Beau Olen, MS Student, OSU Applied Economics (Graduated: 2012)
  • Charles Preppernau, OSU Geography (Graduated: 2015)
  • Travis Roth, PhD Student, Water Resources Science 
  • David Rupp, Oregon Climate Change Research Institute
  • Mary Santelmann, OSU Water Resources Graduate Program
  • Cynthia Schwartz, OSU Biological & Ecological Engineering
  • Eric Sproles, PhD Student, Water Resources Science (Graduated: 2012)
  • Adam Stebbins, Benton County
  • Dan Stephens, OSU Geography (Graduated: 2016)
  • James Sulzman, OSU Biological & Ecological Engineering
  • Christina (Naomi) Tague, UC-Santa Barbara
  • Desiree Tullos, OSU Biological & Ecological Engineering
  • David Turner, OSU Forest Ecosystems and Society
  • Kellie Vache, OSU Biological & Ecological Engineering
  • Eric Watson, PSU Geography (Graduated: 2016)
  • Scott Wells, Portland State University (PSU) Civil & Environmental Engineering
  • Josh Williams, MS Student, OSU Fisheries and Wildlife (Graduated: 2014)
  • Junjie Wu, OSU Applied Economics

 

Technical Advisory Group (TAG) (alphabetical)

Beginning in project year 5 (fall 2014), we invited a core group of 25 citizen stakeholders to participate in a series of meetings to define the assumptions for two stakeholder scenarios and provide feedback on communicating project findings.  TAG members included: 

  • Rick Bastasch, Straub Environmental Center
  • Jason Bradford, Vitality Farms
  • Kevin Brannan, Oregon Department of Environmental Quality
  • Stephanie Eisner, City of Salem
  • Bob Heinith, Columbia River Inter-Tribal Fish Commission
  • Johan Hogervorst, USDA Forest Service
  • Gary Horning, Horning Farm
  • Allison Inouye, City of Hillsboro
  • Niki Iverson, City of Hillsboro
  • John Harland, Pacific Northwest Pollution Prevention Resource Center
  • Margaret Matter, Oregon Department of Agriculture
  • Matt McRae, City of Eugene
  • Jim Meierotto, Tualatin Valley Water District
  • Linda Modrell, Benton County
  • Karl Morgenstern, Eugene Water and Electric Board
  • Alyssa Mucken, Oregon Water Resources Department
  • Laurie Nicholas, US Army Corps of Engineers
  • Dan Obrien, Greenberry Irrigation District
  • Michelle Plambeck, Multnomah County
  • Kimberley Swan, Clackamas Water Providers
  • Gregory Taylor, US Army Corps of Engineers
  • Tom VanderPlaat, Clean Water Services

 

Learning and Action Network (LAN)

Throughout the project, the science team met with regional water managers, stakeholders, and educators.  This group was called the Learning and Action Network (LAN) and grew to include county commissioners, managers, and scientists from state and federal natural resource agencies, farmers, K-12 educators, and representatives from water utilities, conservation organizations, and industry.  Over 120 people participated in at least one LAN event over the project's six years.  LAN events consisted of fieldtrips, workshops, and webinars, where we encouraged dialogue about water issues in the basin and introduced and received feedback on WW2100 modeling approaches and analysis. 

Project Outcomes

The goal of the Willamette Water 2100 project was to develop tools and understanding that will help anticipate water scarcity and inform integrated water system management. Here we highlight some of the key outcomes from the project:

Outcome 1: Development of Willamette Envision

The Willamette Water 2100 project team developed Willamette Envision, a computer model of human and natural controls on water supply and demand across the Willamette River Basin.

Some of the unique aspects of the model include:

  • Landscape modeling at a fine spatial and temporal resolution,
  • A process-based hydrologic model that incorporates human influences such as dam operations, water diversions, and the water rights system, and
  • The ability to run alternative scenarios to explore uncertainty and the affect of changes in land and water management policies.

Outcome 2: Development of a quantitative water budget for the Willamette Basin

The water budget illustrates some of the key characteristics of Willamette water system and how it might respond to coming pressures from climate change and populations growth.

Related findings:

  • In a system where water supply and demand are strongly seasonal and asynchronous, natural and built reservoirs play an important role in sustaining summer flows.
  • Warmer conditions caused by climate change will reduce winter snowpack, stress forests, and could increase the land area burned by wildfires. In model simulations the net effect of these changes and increases in winter precipitation was an increase in annual streamflow.
  • Climate warming could lead to earlier planting dates and an earlier start and end to the irrigation season for annual crops. This shift could reduce out of stream water demands in late summer in some sub-basins.
  • Population growth will increase water demand for cities, while water demand for agriculture may remain relatively constant. Growing cities will displace irrigated farmland, while legal and economic constraints limit the development of new irrigation projects. The trajectory of urban water demand will depend on factors such as population and income growth, development density, water price, and the availability of major water sources outside the Willamette Basin.

Outcome 3: Development of a framework for understanding water scarcity

The framework provides context for understanding water scarcity in the Willamette River Basin and beyond.

Related findings:

  • Water scarcity can be described along a continuum, determined by the value of providing additional water at specific times and places. For example, high water scarcity occurs when and when the value of providing additional water is high. For a more complete discussion of the concept of water scarcity, refer to Jaeger et. al. (2013).
  • Water scarcity has spatial, temporal and qualitative dimensions. Water scarcity in the Willamette River Basin illustrates all of these dimensions:
    • Water is annually abundant but seasonally scarce in summer when demand peaks but little rain falls. 
    • Water may be available regionally, but can be scarce at specific locations in the basin because of legal constraints or the lack of infrastructure. 
    • Water may be abundant, but not of use if it does not meet desired or required water quality standards. In the Willamette, many native fish species require cold water habitats, habitats that may be degraded by climate warming and land development. 
  • Water scarcity can be driven by human decisions, costs, laws and regulations, as much as by a lack of physical abundance. In the Willamette system, summer water storage by the federal dams in the Willamette River Basin provides the biggest single mechanism to mitigate potential water scarcity for humans and ecosystems. However, access to this water is limited by an array of water laws, regulations, and competing needs. Two examples include:
    • Trade-offs between flood risk reduction and water storage for summer use. Reducing spring flood risks requires maintaining reservoirs empty longer, yet that also reduces the time available to fill reservoirs for summer use.
    • Restrictions imposed by federal environmental laws. Rules to mitigate the impact of federal dams on threatened and endangered fish strongly influence dam operations and summer flow releases. In quantitative terms, minimum regulatory instream flow requirements established by ESA-related Biological Opinions are a major summer water use, one that exceeds basinwide agricultural and urban water demands, and will likely limit future access to stored water.

Outcome 4: Capacity building

Adopting a transdisciplinary approach that involved regional water managers and stakeholders in all stages of the research process helped build capacity for integrated water system management.

Related findings:

  • Extensive stakeholder engagement throughout the project helped foster relationships and learning between scientists and stakeholders, and between stakeholders in different sectors.
  • As a university led project with a wide scope, the project provided a neutral forum for learning among water sectors. Interviewed stakeholders valued the opportunity to build relationships with diverse water users, regulators, and researchers, and to discuss possible water availability constraints of the future.

Funding & Disclaimer

WW2100 was funded predominantly by research grants from the National Science Foundation (NSF) with additional support from the US National Oceanic and Atmospheric Administration (NOAA).  Grants included:

 

  • NSF-EAR 1039192 to Oregon State University
  • NSF-EAR 103889 to University of Oregon
  • NSF-EAR 1038925 to Portland State University, and
  • NOAA NA10OAR4310218 to Oregon State University and the University of Oregon

The project was affiliated with the NSF Water Sustainability and Climate (WSC) program, an effort to enhance understanding of the Earth's water system and interactions between human activity, climate change, and ecosystem functions.  NSF's WSC program supported place-based modeling projects at universities across the United States. The OSU Institute for Water and Watersheds provided administrative support for the project, and the Institute for Natural Resources assisted with data management.

Any opinions, findings, conclusions or recommendations expressed on this website are those of the authors and do not necessarily reflect the views of the National Science Foundation or the National Oceanic and Atmospheric Administration. 

Contact Information

Principal Investigator:

Dr. Anne Nolin, Professor
College of Earth, Ocean, and Atmospheric Sciences
Oregon State University
Phone: 541-737-8051
Email: nolina@geo.oregonstate.edu

 

Project Coordinator:

Maria Wright, Faculty Research Assistant
Institute for Water and Watersheds
Oregon State University
Phone: 541-737-6148
Email: maria.wright@oregonstate.edu

Model Overview

Click on the links below to learn more about Willamette Envision, the human and natural systems model created by the WW2100 project, and to read about WW2100 modeling scenarios.

Conceptual diagram of the modeling process within Willamette Envision.

Model Introduction

The Willamette Water 2100 (WW2100) project developed an integrated model of the Willamette River Basin (WRB) to explore how climate change, population growth, and economic growth will alter water availability and use in the WRB. Called Willamette Envision, the model is based on Envision, a modeling framework developed at Oregon State University (J. Bolte and colleagues). The diagram below illustrates the modeling process within Willamette Envision (Fig. 1). Model inputs such as daily weather conditions and annual population growth, drive component models that operate within the modeling framework. These sub-models are called “plug-ins” because they run independently but share data with each other through the modeling framework. As a simulation runs, the plug-in models store and retrieve information from a shared database — output from one model becomes input for others as each steps through time. At the end of a run, spatial and tabular outputs summarize changes in the landscape, water, and economic systems over the 90 years of the simulation. Based on project goals and input from regional stakeholders, we created and then compared alternative future scenarios by varying model inputs and elements for different runs. For example, WW2100 explored the effects of population growth on the water system by comparing several scenarios that each adopted a different population growth rate while holding all other model elements constant.

Conceptual diagram of the modeling process within Willamette Envision.

Figure 1. Conceptual diagram of the modeling process in Willamette Envision (diagram by M. Wright).

Modeling Approach

The Willamette River Basin (WRB) is a complex coupled system, one that includes both a natural system (the biophysical components) and a human system (the socio-economic components). The interactions, feedbacks, and evolving characteristics of these different components will control when and where water is abundant or scarce. Given the complexity of the system, and the detailed spatial and temporal scales at which these different components interact and influence each other, an explicit and quantitative representation of this system requires a computer model to incorporate the many processes and relationships in time and space between and among the natural and human system components. This allows us to predict how those processes are likely to change over time. As a result, we developed Willamette Envision. The model enables us to explore the interactions between land and water use, law and policy, and public management of land and water resources.

Willamette Envision includes modeling components that represent water supply, water allocation, and water demand (Fig. 2). We model water supply in the basin using a hydrologic model that translates daily values of meteorological conditions into a spatially distributed estimate of snow, soil moisture, and streamflow conditions. We model water allocation by incorporating the operating rules for the 13 federal Willamette Project reservoirs, and a model of water use constraints imposed by Oregon water law. We model water demand for four sectors: urban areas, agriculture, upland forests, and instream ecosystems (fish). We estimate water demand for urban areas as a function of factors such as water price and population, and simulate urban growth by relating land use changes to land characteristics and economic returns. We model water demand for agricultural and forested lands by estimating evaporative water loss from different crop and forest cover types. Connected modeling components determine farmer planting and irrigation decisions, and forest succession and disturbance by wildfire and harvest. We represent instream ecological water needs by modeling instream water rights and also federally required ESA-related minimum flows that are integrated into reservoir management rules.

Conceptual diagram of Willamette Envision and its modeling components.

Figure 2. Conceptual diagram of the Willamette water system showing how human and natural system modeling components link together within Willamette Envision (diagram by M. Wright).

Model Components

Willamette Envision incorporates:

  • Hydrologic, ecological, and economic system sub-models called "plug-ins" – Willamette Envision incorporates a suite of sub-models to simulate processes that affect the distribution, movement, supply of, and demand for water in the WRB. Each sub-model was developed or adapted for the project by researchers with expertise in that field. Some sub-models are based on new empirical analyses, while others are process-based models originally developed for other purposes and adapted for this project. For example, the land use transitions model is an economic model developed for this project using historical parcel-level land value data, while the reservoir operations model was adapted from code in ResSim, a model developed by the US Army Corp of Engineers. The plug-in models within Willamette Envision represent both socioeconomic and biophysical components of the water system. Fig. 2 is a conceptual diagram showing those components of the regional human-natural system that have been developed into quantitatively modeled plug-ins, and linked together within Willamette Envision.

  • Modeling frameworks that enable sub-models to run simultaneously and share data – The framework allows output from one modeling component to become input for others as they step through time. For example, hydrology is modeled within a modeling framework called FLOW that was developed for this project (Vaché et al., in review). FLOW models the movement of water through the stream network, while also allowing water to be added or removed at specific points where the model links to other plug-ins. This linkage allows economic processes such as the irrigation decision model, which determines the timing and amount of groundwater pumping and surface irrigation diversions, to be linked to the hydrologic model.

  • A geographic information system (GIS) – Willamette Envision contains a spatial database that stores information about the WRB in map polygons called Integrated Decision Units (IDUs) and in a line network representing the river system. As the component models run, they store and retrieve data from this spatial database. At the end of a Willamette Envision model run, results are available as data, tables, and maps, which can be exported for further analysis.

  • Alternative scenarios – model inputs and other model elements have been varied to create alternative scenarios with Willamette Envision. For example, we developed different scenarios that varied assumptions about fire suppression in the forest disturbance sub-model. That change then affected the distribution of forest types predicted by the forest state and transition sub-model, and consequently stream flows predicted by the hydrology sub-model. By comparing the reference case scenario with alternative scenarios, we can evaluate how sensitive the model is to particular assumptions.  We can also ask “What if?” questions that may help inform policy analysis. 

Technical Details

  • Code – Willamette Envision consists of several hundred thousand lines of C++ code and runs as a 64-bit Windows application.

  • Spatial representation – Data are stored in ESRI shapefiles representing the stream network and landscape polygons called Integrated Decision Units (IDUs). The polygons are meaningful spatial units, representing for example agricultural fields, forest stands, or developed areas.

    • The stream network and associated catchments were taken from the National Hydrography Dataset version 2 (NHD+V2) found at http://www.horizon-systems.com/NHDPlus/NHDPlusV2_home.php.

    • The IDU layer was developed by intersecting the catchment shapefile with a composite dataset representing landuse and landcover in the WRB. This catchment shapefile provides information needed by the hydrology model to connect the landscape to individual stream reaches. The land use/land cover dataset was developed by combining information from two sources: (1) a US Forest Service dataset (GNN) representing the forested portions of the basin and (2) as US Department of Agriculture datasets (NASS CDL) representing all other portions of the basin. The NASS data is derived from LANDSAT imagery and is designed to closely capture the crops grown as part of the agricultural system.

    • There are 164,892 polygons in the IDU layer, covering the nearly 30,000 square kilometer (11,500 square mile) extent of the WRB. Most IDUs cover an area of between 2 and 700 hectares (5 and 1730 acres).Climate data is gridded at a resolution of 2.5 arc-minutes (about 4 km).Refer to the stream layer and IDU metadata for more details about spatial geometry.

  • Time step – Some processes are simulated at a daily timestep and others at an annual timestep.

    • The daily time step includes many processes such as:

      • stream flow
      • snow and canopy evaporation
      • infiltration and percolation
      • evapotranspiration
      • Irrigation decisions
      • Urban water use
      • exercise and enforcement of water rights
         
    • The annual time step includes many landscape change processes such as:
      • spatial distribution of population and income changes
      • expansion of urban growth boundaries
      • urban water price
      • crop choices
      • agricultural land value
      • forest wildfire
      • forest harvest
      • land use transition (for example from agricultural or forest uses to developed uses)
         
  • Simulation period – Most WW2100 modeling scenarios simulate the period from January 1, 2010 through December 31, 2099. However, we also ran two scenarios with a simulation period from January 1, 1950 - December 31, 2009 to allow comparisons of modeled future conditions to a modeled past. These scenarios used simulated historical climate data as a model forcing and held population and land cover constant with conditions at the end of 2010. Refer to the scenarios page from more details.
  • Run time – A single run of Willamette Envision takes about 48 wall clock hours. Up to six scenarios can be run at the same time without increasing elapsed time appreciably.

Related Links & Publications

  • Envision website - http://envision.bioe.orst.edu

  • Recorded lectures about hydrologic modeling, with a focus on Envision and hydrologic models utilized in Willamette Water 2100, taught Spring 2013.

  • Vache, K. Bolte, J, Schwartz, C., Sulzman, J. (2016). A flexible framework to support socio-hydrological scenario analysis. Manuscript submitted for publication.

  • Jaeger et. al. (2016). Scarcity amid abundance: Water, climate change, and the policy role of regional system models [Supplemental material]. Manuscript in preparation.

Developers of Willamette Envision

Willamette Envision is based on Envision, a modeling framework developed at Oregon State University by John Bolte and colleagues (http://envision.bioe.orst.edu/). The following individuals contributed to the design and coding of modeling components within Willamette Envision -

Overall framework -

  • John Bolte, Oregon State University
  • David Conklin, Oregon Freshwater Simulations

Hydrologic modeling -

  • Kellie Vaché, Oregon State University
  • John Bolte, Oregon State University
  • Anne Nolin, Oregon State University
  • Cynthia Schwartz, Oregon State University

Reservoir modeling -

  • Kellie Vaché, Oregon State University
  • Matt Cox, Oregon State University
  • Desiree Tullos, Oregon State University

Hydrologic model calibration -

  • Phase 1:
    • Kellie Vache, Oregon State University
  • Phase 2:
    • Heejun Chang, Portland State University
    • Eric Watson, Portland State University
  • Phase 3:
    • Anne Nolin, Oregon State University
    • David Conklin, Oregon Freshwater Simulations
    • John Dalrymple, Oregon Freshwater Simulations

Upland forest modeling -

  • John Bolte, Oregon State University
  • David Turner, Oregon State University
  • David Conklin, Oregon Freshwater Simulations
  • James Sulzman, Oregon State University

Water rights modeling -

  • John Bolte, Oregon State University
  • James Sulzman, Oregon State University
  • Adell Amos, University of Oregon
  • William Jaeger, Oregon State University
  • David Conklin, Oregon Freshwater Simulations
  • Andrea Laliberte, Earthmetrics

Lowland land use change modeling -

  • Andrew Plantinga, University of California, Santa Barbara
  • Daniel Bigelow, Oregon State University
  • David Conklin, Oregon Freshwater Simulations

Agricultural land and water use modeling -

  • William Jaeger, Oregon State University
  • Dan Bigelow, Oregon State University
  • Cynthia Schwartz, Oregon State University
  • David Conklin, Oregon Freshwater Simulations

Urban and rural residential water use modeling -

  • Christian Langpap, Oregon State University
  • William Jaeger, Oregon State University
  • David Conklin, Oregon Freshwater Simulations

 

Web page authors: M. Wright, W. Jaeger, D. Conklin
Web page last updated: September 22, 2016

Scenarios

While there are multiple ways to design and compare future scenarios, this project adopted a method commonly used for policy analysis. In this approach, the first step was to model a Reference Case scenario, or baseline scenario for the future. For Willamette Water 2100, this scenario modeled future conditions through the year 2099 and adopted mid-range assumptions about climate change, population, and income growth; it also assumes that institutions such as water rights, the land-use planning system, reservoir operating rules, forest practices, and urban water pricing continue to operate in their present form. This base case then became a reference for comparison with alternative scenarios.

This page describes data sources, assumptions, and model settings that we incorporated into the Reference Case scenario. It also describes the main categories of alternative scenarios, and links to tables that describe model settings in detail for each scenario. Eighteen scenarios vary a single element or assumption, and hold all others the same as in the Reference Case scenario. Three scenarios vary multiple elements relative to the Reference Case scenario. Their purpose is to explore the effect of multiple, simultaneous, and plausible changes to the modeled social-ecological system. We developed two of these scenarios in collaboration with our Technical Advisory Group (TAG), a group with diverse expertise in Willamette Basin land and water management. The TAG developed two overarching themes for their scenarios, and with input from the modeling team, selected model settings consistent with each theme.

Table showing the 22 scenarios modeled by the Willamette Water 2100 project.

Figure 1. The 22 scenarios modeled by the Willamette Water 2100 project. The left column lists the ten scenario elements that vary between scenarios. In the Reference Case scenario, these elements match mid-range assumptions about climate change, population, and income growth, and reflect existing management practices, policies and institutions. The 18 “Single Variable Alternative Scenarios” isolate the influence of individual model settings or policy choices, and each varies one scenario element at a time. The last three columns depict the “Multiple Variable Alternative Scenarios” that vary multiple scenario elements to align with a scenario theme. We developed two of these scenarios (highlighted in green) in collaboration with the WW2100 Technical Advisory Group, a group with regional water expertise.

Methods

The Reference Case scenario addresses the first two of the four overarching objectives of the Willamette Water 2100 project: (1) to identify and quantify the linkages and feedbacks among human, hydrologic, and ecologic dimensions of the water system, and (2) to make projections about where and when human activities and climate change will impact future water scarcities. We then developed alternative scenarios to address the third and fourth objectives of the project: (3) to evaluate how biophysical and human system uncertainties affect these projections and (4) to evaluate how policy changes or other interventions might affect future water scarcities. This page provides details about the assumptions and model settings that are part of the Reference Case and alternative scenarios.

Reference Case Scenario

The Reference Case scenario modeled future conditions through the year 2099 and adopted mid-range assumptions about climate change, population and income growth; it also assumed that institutions such as water rights, the land-use planning system, reservoir operating rules, forest practices, and urban water pricing continue to operate in their present form, or with expectations for change that are most likely to occur (e.g., expansion of the urban growth boundaries). The lists below describe some of the specific data sources and model settings in the Reference Case scenario:

External Drivers
  • Climate - Climate inputs from the regionally downscaled projections from the MIROC5 global climate model with the RCP 8.5 emissions scenario. Projections are in the middle of the range of possible changes predicted by a suite of global climate models that perform well for the Pacific Northwest. Annual mean temperature in the Willamette River Basin (WRB) increases ~4°C (~7.5°F) over the century. Climate input data was selected and downscaled through a multi-step process.

  • Population - County population projections to 2050 from the Oregon Office of Economic Analysis (2011), linear extrapolation 2050-2100. County projections downscaled to cities and areas zoned for rural residential use in proportion to 2010 Census block population counts. Example population totals: WB as a whole in 2010 = 2.41M; 2050 = 3.73M; 2100 = 5.37M; within Portland UGB in 2010 = 1.43M ; 2050 = 2.20M; 2100 = 3.16M.

  • Income - County level total household personal income forecasts to 2040 from Woods and Poole (2011); linear extrapolation 2040-2100. The annual projected growth rate in mean household income for WB counties 2012-2100 is 1.13%, a rate that is lower than the average historical growth rate for 1930-2013 of 1.63%. Mean household income in 2010 is $87,900 and reaches $242,000 (in 2005 dollars) in 2100. Income at the city level is assumed to be the same as at the county level. Note that the Woods and Poole measure of income is more inclusive of sources and types of income than the definition of “money income” used by the US Census Bureau and other government agencies; it includes all money income plus “exclusions to income” such as food stamps, agricultural payments-in-kind, and imputed rental value of owner-occupied housing. It also includes certain interest payments, other labor income, and a number of other measures that are not included as part of money income. The mean value for household income that we are using will typically be 30% or 40% higher than the median value.

Economic Policy and Public Management Assumptions
  • Forest management - The level of wildfire suppression is held at historical rates throughout the simulation. But because of changing climate and forest conditions, the area of forest burned per year rises over the simulation from 0.2% per year in 2010 to 0.6% per year in 2100. Harvest by clear cut is maintained at historical rates (8,000 acres per year on public lands + 29,000 acres per year on private lands). There is no harvest of protected areas. Harvest only occurs on stands older than 40 years on private lands, and between 40-80 years on public lands.

  • Urban development - All future development occurs within Urban Growth Boundaries (UGBs); UGBs expand when 80% developed (72% for Eugene-Springfield). No development of parks, wetlands, or other protected areas. Land zoned for Exclusive Farm Use is added to UGBs when all other contiguous areas are exhausted. Growth of the Portland Metro UGB confined to urban reserves through 2060.

  • Reservoirs operations - Operations of the 13 federal reservoirs that are part of the Willamette Project modeled according to rule curves implemented as of 2011 and recommendations from the Biological Opinion as of 2009 except the selective withdrawal structure at Cougar Dam. Reservoirs begin refilling Feb 1, with a target to fill reservoirs by May. Smaller, non-federal reservoirs are not modeled. Pulse flows in sub-basins are not implemented.

  • Urban water demand and pricing - Water demand estimated for UGBs as a whole based on residential and commercial income shares, water price, population, income, housing density, and season. Bull Run (water source for Portland Metro) is modeled according to the municipal water right, which limits diversions to 636 cfs, and in the model is allowed to contribute not more than two-thirds of the Portland Metro municipal demand. Baseline information on water rates and price structure obtained from Water Management and Conservation Plans for Portland (2010), Salem (2009), Corvallis (2005), and Eugene (2012), and through personal communication for Springfield (2012). Example baseline residential prices: Portland UGB= $2.44 per ccf; Eugene-Springfield UGB= $1.25 per ccf; rural residential areas= $0.3 per ccf (reflects pumping cost). Reference Case scenario assumes an increase in water price 2011-2015 (6% per year) and 2016-2025 (1.5% per year; in real, inflation-adjusted dollars); actual and anticipated cost increases to cover infrastructure backlogs, seismic upgrades, etc., then prices held constant in inflation-adjusted terms for a given city population size; resulting average per capita municipal use = 95 gal per day in 2100.

  • Crop choice and irrigation - Crop types are set annually based on land characteristics, water rights and irrigation decision, crop prices, and climate. Crop types are limited to hay, grass seed, corn, pasture, wheat, clover, fallow, and other crops. Lands in orchards, vineyards and tree farms remain in those land cover types and do not change throughout the simulation and are largely not irrigated. On lands with water rights, the decision to irrigate is made annually based on land characteristics, climate (including June precipitation), and energy price. The price of wheat ($64 per ton), grass seed ($5 per bushel), and energy are held constant (in real terms). Irrigation diversions are limited by water right and constrained to legal limits including a max irrigation rate 1/80th cfs per acre and duty 2.5 acre-feet per acre. About two thirds of acres with water rights are irrigated in an average year; the result is that about 280,000 acres are irrigated at the simulation start. Crop and irrigation models are interdependent. Some crops are always irrigated and some crops are never irrigated.

  • Water rights - Modeling includes surface and groundwater rights for irrigation, municipal, and instream uses as documented in the Oregon Water Resources Department Water Rights Information System as of July 2012. Priority is determined by seniority among all rights within the Willamette Basin. For municipal and irrigation rights to surface water, when requested water cannot be allocated due to insufficient water in the stream, junior water rights in upstream reaches may be regulated off for the rest of the season. Tallies are kept by modeling polygon of the frequency of water shortages lasting at least seven consecutive days. The Reference Case scenario assumes that groundwater wells tap an unlimited source. No new water rights or contracts for stored water from the Willamette Project are added over the length of the simulation. The scenario includes instream water rights implemented as of 2010. When more than one instream water right applies at the same time to the same reach, the water rights model applies both water requirements.

Alternative Scenarios

We evaluated 21 alternative scenarios in this project. Fig. 1 depicts the Reference and the 21 alternative scenarios grouped by scenario element and purpose. The Reference Case (shaded grey) modeled future conditions (2010-2099) and set the baseline assumptions for each scenario element. Eighteen scenarios (shaded orange, red, blue, and purple) then varied a single element or assumption, and held all others the same as in the Reference Case scenario. For example, the LateRefill scenario explored the effect of making a specific change in federal reservoir operating rules while all other biophysical and human systems operated as in the Reference Case scenario. Table 1 details specific assumptions of the Reference Case scenario and identifies how those assumptions were changed in the single variable alternative scenarios.

Table showing the 22 scenarios modeled by the Willamette Water 2100 project.

Figure 1. The 22 scenarios modeled by the Willamette Water 2100 project. The left column lists the ten scenario elements that vary between scenarios. In the Reference Case scenario, these elements match mid-range assumptions about climate change, population, and income growth, and reflect existing management practices, policies and institutions. The 18 “Single Variable Alternative Scenarios” isolate the influence of individual model settings or policy choices, and each varies one scenario element at a time. The last three columns depict the “Multiple Variable Alternative Scenarios” that vary multiple scenario elements to align with a scenario theme. We developed two of these scenarios (highlighted in green) in collaboration with the WW2100 Technical Advisory Group, a group with regional water expertise.

 

The color coding in Fig. 1 further identifies the alternative scenarios and their purposes. Tables 1 and 2 list specific assumptions and model settings for each of these scenarios. Orange shading indicates the two scenarios that modeled a 60-year time span from the past (1950-2009). These “simulated historical” scenarios were used to compare the simulated future to the model’s own simulated past. They each used simulated historical climate data that was generated by the same global climate models used to develop future climate conditions for the other scenarios.

Blue shading indicates the future climate scenarios. These scenarios include different assumptions about future climate, but left all other assumptions the same as in the Reference Case scenario. The purpose of the future climate scenarios was to compare the range of possible outcomes, given uncertainty about future climate conditions. Along with the mid-range assumptions of the Reference Case, the HighClim and LowClim scenarios represent the range of possible future climates projected by a suite of global climate models determined to perform well for the Pacific Northwest (Rupp et. al., 2013).

Red shading in Fig. 1 identifies the human dimensions scenarios. These each vary one assumption about the human system, and most explore the effect of specific policy interventions such as changes in water prices, water law, or reservoir management rules. These scenarios explore the direction and magnitudes of change in relation to specific management interventions, so as to be able to differentiate between associated outcome sets, their costs and consequences. One advantage of running these policy scenarios with a single change or intervention relative to the Reference Case scenario is that it allowed us to attribute changes in outcomes to individual changes in policy.

Purple shading identifies the “counterfactual” scenarios. The term “counterfactual” means intentionally modeling a situation that will not occur – i.e., counter to the facts. These scenarios help us measure the impact of changes in the model by comparing the Reference Case scenario with a scenario that omits one source of change. For example, we have included one scenario of this kind where the climate does not change (but the population grows), and also one scenario where there is no change in population or personal income (but where climate change does occur). Comparing these counterfactual scenarios to the Reference Case scenario provides insights into the magnitude of the effects on future water scarcity due to one of these elements versus the other. In one other case we have modeled a scenario with no agricultural production (all fallow). This is clearly counter to the facts; comparison of this scenario to the Reference Case or other alternative scenarios provides evidence of the impact of agriculture on water use and stream flows.

The last three columns shown in Fig. 1 (red and green shading) show scenarios that vary multiple elements relative to the Reference Case scenario. Their purpose is to explore the effect of multiple, simultaneous, and plausible changes to the modeled social-ecological system. We developed two of these scenarios in collaboration with our Technical Advisory Group (TAG), a group with diverse expertise in Willamette Basin land and water use and management. The TAG developed two overarching themes for their scenarios, and with input from the modeling team, selected model settings consistent with each theme (Table 2). The Extreme scenario combined High Climate Change with high population growth and other model settings designed to maximize resource use and water demand for cities and agriculture. It also included a mechanism to take individual federal reservoirs “offline” occasionally for maintenance. The Managed scenario is similar to the Reference Case scenario in that it adopted the mid-range assumptions about climate change and population growth. However it also included several management choices that the TAG felt reflected recent trends in resource management. These included differential rates of fire suppression on private and public forest lands, a per-capita constraint on future municipal water use, and the establishment of new contracts for future use of water stored in federal reservoirs. Assumptions in the Worst Case scenario were selected to maximize water scarcity. Scenario elements include mid-range climate warming and high population growth, combined with increased fire suppression and high utilization of irrigation and instream flow rights.

Table 1. Detailed assumptions for the 18 single element alternative scenarios that were designed to isolate the influence of individual model settings or policy choices. Each varies one scenario element and holds all others the same as in the Reference Case scenario.



Scenario Element

Single Element Alternative Scenarios

Time Period

Historic Mid-Range Climate (HistoricRef) – historical time period (1950-2009); simulated historical climate based on MIROC5 global climate model; landcover held constant with 2010 conditions

Historic High Climate (Historic-HadGEM) – simulated historical climate based on HadGEM2-ES global climate model; landcover held constant with 2010 conditions

Climate

Low Climate Change – GFDL (LowClim) – GFDL-ESM2M RCP 4.5; ~1°C (2°F) increase in WRB annual mean temps. over century

High Climate Change – HadGEM (HighClim) - HadGEM2−ES RCP 8.5; 6°C (~10.5°F) increase in WRB annual mean temps. over century

Stationary Climate (StatClim) - 21st century climate inputs based on random water years drawn from simulated historical MIROC5 1950-2009

Population & Income Growth

High Population Growth (HighPop) - population growth rates within UGBs doubled relative to Reference Case; basinwide pop. in 2100 = 8.25M; within Portland UGB in 2100 = 4.89M.

Zero Population & Income Growth (NoGrow) - population and household income remain at 2011 levels throughout century

Zero Population Growth (NoPopGrowth) - population remains at 2011 levels throughout century; income rises as in in the Reference Case

Zero Income Growth (NoIncGrowth) - income remains at 2011 levels throughout century; population rises as in the Reference Case

Reservoir Operations

Late Reservoir Refill (LateRefill) - reservoir refill begins March 1, ramps up to Reference Case. rule curves between March and May

No Reservoirs (NoReservoirs) - modeled without federal reservoirs, run of the river

Forest Management

Upland Wildfire Suppression (FireSuppress) - fire suppression efforts increase to hold area burned per year to historical rates

Urban Development

Relaxed Urban Expansion (UrbExpand) - UGBs expand when 70% developed; no urban reserves

Agricultural Water Demand

Limited Irrigation Rates & Duties (LowIrrig) - legal maximum irrigation rate reduced from 1/80 cfs/acre to 1/100 cfs/acre; duty also reduced from 2.5 to 2.0 acre-feet/acre

Higher Irrigation Usage (HighIrrig) - average fraction of irrigation rights utilized in a given year increased from 2/3rds (Reference Case) to 5/6th

All Fallow (AllFallow) - crop choice set to “fallow” for all agricultural lands (including trees and orchards); no irrigation

Water Claims

New Irrigation Rights (NewIrrig) - new irrigation contracts to stored water in the Willamette Project and related rights introduced 2015-2044; the probability of adding new rights reflects their profitability and account for pumping and conveyance costs and contract fees ($9/acre); crop choice as in the Reference Case

Environmental Flows

New Instream Flow Rights (NewInstream) - introduced in 2010 (with priority dates as early as 1965) to protect “recommended minimum flows for fish life.” (Hutchison et al. 1966, Hutchison et al. 1964, Oregon State Game Commission 1963)

 

Table 2. Assumptions for the three Multiple Variable Alternative Scenarios that each differ from Reference Case scenario in multiple ways. The assumptions for the Extreme and Managed scenarios were developed in collaboration with the WW2100 Technical Advisory Group (TAG), a group with diverse expertise in Willamette Basin land and water use and management.

Scenario Element

Worst Case Scenario
(EconExtreme)

Extreme Scenario
(Extreme)

Managed Scenario
(Managed)

Scenario Theme

Future scenario (2010-2099) where external drivers and other assumptions were selected to maximize water scarcity.  Scenario elements include mid-range climate warming and high population growth, combined with increased fire suppression and high utilization of irrigation and instream flow rights. 

Future scenario (2010-2099) that assumes extreme changes in climate and population combined with policies that emphasize resource use over conservation

Future scenario (2010-2099) that assumes mid-range changes in climate and population combined with a continuation of recent trends in resource use and management

Climate

Same as Reference Case; middle range climate change; 4° C (7.5° F) warming in mean annual temperatures over century; conditions derived from the global climate model called MIROC5 RCP 8.5

Same as HighClim scenario; 6° C (10.5° F) warming in mean annual temperatures over century; conditions derived from the global climate model HADGEM2-ES RCP 8.5

Same as Reference Case; middle range climate change; 4° C (7.5° F) warming in mean annual temperatures over century; conditions derived from the global climate model called MIROC5 RCP 8.5

Population & Income Growth

Population growth same as HighPop scenario; pop. growth rates within UGBs doubled relative to Reference Case; pop. in 2100 = 8.25M.

Income assumptions same as Reference Case, mean household income in 2010 = $87.9K and 2100 = $242K (in 2005 dollars)

Population growth same as HighPop scenario; pop. growth rates within UGBs doubled relative to Reference Case; pop. in 2100 = 8.25M

Income assumptions same as Reference Case, mean household income in 2010 = $87.9K and 2100 = $242K (in 2005 dollars)

Same as Reference Case; pop. in 2010 = 2.41M; 2100 = 5.37M; mean household income in 2010 = $87.9K and 2100 = $242K (in 2005 dollars)

Forest Management

Same as FireSuppress scenario, fire suppression efforts increase to hold area burned per year to historical rates

Increase in wildfire suppression so that forest area burned per year increases from 0.2%/year in 2010 to 0.8%/year in 2100 (without an increase in fire suppression, area burned per year in the High Climate Change scenario increases to 2%/year). Harvest by clear cut at historical rates (8,000 ac/year on public lands + 29,000 acres/year on private lands); no harvest of protected areas; stand age for harvest >= 40 years on private and public lands

Differential increase in wildfire suppression on private and public lands; resulting increase in forest area burned on private lands from 0.2%/year in 2010 to 0.3%/year in 2100 and on public lands from 0.2%/year in 2010 to 0.8%/year in 2100; harvest by clear cut at historical rates (8000 acres/year on public lands + 29,000 acres/year on private lands); no harvest of protected areas; stand age for harvest >= 40 years on private and 40-80 years on public lands

Reservoir Operations

Same as Reference Case; federal reservoirs operated by rule curves implemented as of 2011; reservoirs begin refilling Feb 1, with a target to fill reservoirs by May

Reservoir refill begins March 1, ramps up to existing rule curves between March and May; 1% chance each year for one of the five biggest reservoirs to go offline for one calendar year; reservoirs treated as “Run of the River” when offline

Same as Reference Case; federal reservoirs operated by rule curves implemented as of 2011; reservoirs begin refilling Feb 1, with a target to fill reservoirs by May

Urban Development

Same as Reference Case; UGBs expand when 80% developed (72% for Eugene-Springfield); growth of Portland Metro UGB constrained to urban reserves through 2060

Same as the UrbExpand scenario; UGBs expand when 70% developed; no urban reserves

Same as Reference Case; UGBs expand when 80% developed (72% for Eugene-Springfield); growth of Portland Metro UGB constrained to urban reserves through 2060

Urban Water Demand

Same as Reference Case

Assumes the non-residential sector of the economy grows between 2015-2030 to the highest levels (relative to personal income) observed in any location in the WB in recent years. This assumption raises municipal water demand by increasing the ratio of non-residential to residential water demand. All other urban water assumptions as in Reference Case.

Municipal use declines to 100 gal/day/person by 2050 then held at that rate to 2100.

Agricultural Water Demand

Combination of HighIrrig and NewIrrig scenarios; avg. fraction of irrigation rights utilized in a given year is 5/6th; new irrigation contracts and related rights introduced 2015-2044; probability of adding new rights reflects their profitability and account for pumping and conveyance costs which are assumed to be half of those estimated for NewIrrig scenario; contract fees set to zero; crop choice as in Ref

New irrigation contracts and related rights introduced 2015-2044, similar to NewIrrig scenario; conveyance costs are assumed to be half of those estimated for NewIrrig scenario; contract fees set to zero; crop choice and irrigation limits as in Reference Case

Same as Reference Case; crop mixes similar to today; crop and energy prices do not rise in real terms; legal limits include max irrigation rate 1/80th cfs/acre and duty 2.5 acre-feet/acre; about 2/3 of acres with water rights irrigated in an average year; result is about 280,000 acres irrigated initially

Water Claims

new contracts from Willamette Project added to satisfy demand for new irrigation demand

New claims of stored water (May-October) of up to 233,060 acre-feet/year for municipal uses and 550,000 acre-feet for irrigation (limits based on Willamette Basin Reservoir Study Interim Report (OWRD and USACE, 2000) and 1994 Application for Reservation (OLCD et al, 1994)

New claims of stored water (May-October) of up to 133,060 acre-feet/year for municipal uses and up to 385,000 acre-feet for agriculture

Environmental Flows

Same as NewInstream; new instream water rights introduced as of 2010 (but with original priority dates as early as 1965) to protect “recommended minimum flows for fish life.” (Hutchison et al. 1966, Hutchison et al. 1964, Oregon State Game Commission 1963)

Same as Reference Case; includes instream water rights implemented as of 2012

Same as Reference Case; includes instream water rights implemented as of 2012

Related Links

  • Scenarios Table (PDF iconPDF format) - Summary of data sources and assumptions for the Reference Case and alternative scenarios in a single table

Contributors to Scenario Development

References

Hutchison, J. M., K. E. Thompson, and J. D. Fortune Jr. (1966). The fish and wildlife resources of the upper Willamette basin, Oregon, and their water requirements. Salem, Oregon: Basin Investigations Section, Oregon State Game Commission.

Hutchison, J. M., and W. W. Aney. (1964). The fish and wildlife resources of the Lower Willamette Basin, Oregon, and their water use requirements. Salem, Oregon: Oregon State Game Commission.

Oregon Office of Economic Analysis. (2011). Forecasts of Oregon's County Populations and Components of Change, 2010 – 2050, Salem, Oregon.

Oregon State Game Commission, Basin Investigations Section. (1963). The fish and wildlife resources of the middle Willamette basin, Oregon, and their water use requirements. Report to the State Water Resources Board. Salem, Oregon.

Rotmans, J., and M. Van Asselt. (1996). Integrated assessment: a growing child on its way to maturity, Climatic Change, 34, 3-4, 327-336.

Rupp, D. E., J. T. Abatzoglou, K. C. Hegewisch, & P. W. Mote. (2013). Evaluation of CMIP5 20th century climate simulations for the Pacific Northwest USA, Journal of Geophysical Research: Atmospheres (188), http://dx.doi.org/10.1002/jgrd.50843

 

Webpage authors: M. Wright, W. Jaeger, D. Hulse
Last updated: September 22, 2016

Key Findings

To understand where and when water scarcity is likely to increase, the Willamette Water 2100 project team developed a computer model of human and natural controls on water supply and demand across the WRB. The model, called Willamette Envision, represents key aspects of the water cycle, from precipitation, evapotranspiration and streamflow, to reservoir operations, water rights and water withdrawals. The team used the model to explore connections and feedbacks between parts of the water system, and to anticipate how climate change, population growth and income growth might affect water scarcity in the 21st century. Below are key findings.

Photo sources, left to right: Anne Nolin; Al Levno, USFS, Al Levno, USFS

Finding 1: Water Scarcity in the Uplands

In the mountains that are the source area for water supply, climate change is the primary driver of water scarcity. Warmer conditions caused by climate change will reduce winter snowpack, stress forests, and increase wildfires by as much as ninefold.

  • Our analysis of global climate models suggests that by 2100, mean annual temperatures in the WRB are projected to be 1°C (2°F) to 7°C (13°F) warmer than today. Over the 90-years simulated by WW2100, temperatures consistently rise while winters become slightly wetter and summers slightly drier.

Differences in annual temperature for 1950-2100 from a historical baseline (mean of 1950-2005).

The graph above shows projected temperature changes from a historical baseline (mean of 1950-2005) for the Willamette Basin. The red and orange shaded areas indicate the range of projections derived from 40 global climate simulations. While the amount of warming varies between models and global carbon emissions scenarios, all project a warming climate. For modeling in Willamette Water 2100, we selected three climate scenarios to span the range of climate projections for the basin. We used output from these three scenarios to drive watershed modeling in Willamette Envision, and explore the effect of a changing climate on the water system. The heavy pink and blue lines indicate the amount of warming in these three climate scenarios: low change (pink; called the LowClim Scenario) and moderate change (bright blue; called the Reference Scenario) and high change (dark blue; called the HighClim Scenario). For more information about climate change projections for the Willamette Basin, link to the Future Climate page on this website.

Box plots showing decadal changes in January-April maximum snow water equivalent for the HighClim scenario, above 1200 m.

Modeling with Willamette Envision illustrates the sensitivity of snowpack to climate warming. The figure above shows the decline in maximum winter snow water equivalent (SWE), the amount of water stored as snow, for the WW2100 scenario with the most climate warming (the HighClim Scenario). Snowpack is a natural reservoir that stores a proportion of winter precipitation, and releases water into streams (and federal reservoirs) during the spring. To read more about snowpack modeling in Willamette Envision, link to the Snow page. You can also view an interactive map showing projected changes in maximum SWE for different WW2100 scenarios.

  • In WW2100 simulations, low snowpack and hotter, drier summers lead to a two- to nine-times increase in land area burned by forest wildfires. The fires reduce the availability of mature forests for timber harvest and open up lands to transition to new forest types better suited to the changing climate. The reduction in forest leaf area associated with more wildfires also tends to reduce evapotranspiration from upland forests, despite the warmer climate conditions. The net effect of decreases in evapotranspiration and slight increases in winter precipitation, is an increase in annual streamflow from the uplands.

Illustration of land cover projections for the WW2100 HighClim scenario.

The maps above show the changes in forest composition simulated by Willamette Envision for the WW2100 scenario with the most climate warming (the HighClim Scenario). Stand replacing disturbances, either harvests or fire, induces a change in vegetation cover type. To read more about forest modeling in Willamette Envision, link to the Upland Forest Change page. You can also view an interactive version of this map.

Water Management Implications:

Both loss of snowpack and changes in upland forests have the potential to affect water supply from Willamette Basin headwaters. The potential loss of snowpack has important implications for spring and early summer high elevation soil moisture, forest health, spring streamflow, and reservoir management. The projected increase in the risk of forest fire and resulting changes in water consumption by upland forests, highlight the need for management strategies to ensure healthy forests in a time of increasing moisture stress.

 NWS/USACE, USACE, OSU

Finding 2: Water Scarcity in the Lowlands

In the Willamette valley where water is needed for farms, cities, and ecosystems, future scarcity depends predominantly on human factors such as population growth, land use practices, and water law.

  • Our simulations suggest that with a doubling of population, urban water demand could rise by 88% over the century; the rate of this increase is sensitive to factors such as changes in water prices and urban density. In WW2100 scenarios, urban areas in general were able to meet water needs with existing water rights, including important sources from outside the basin (i.e. water from Bull Run watershed that supplies the city of Portland).
  • Our simulations suggest that water demand for irrigation may remain relatively stable over the 21st century. Because “live flow” sources of irrigation water are now essentially fully appropriated, any increase in irrigation must come from groundwater sources or stored water in federal reservoirs. In the latter case, incentives to contract for stored water will be limited by the costs of delivering that water to a given farm field. In our simulations that introduced new water rights tied to stored water, the increase in irrigated acreage was very limited due to the high cost of conveyance. In addition, our simulations suggest that two factors could reduce water use from agriculture and urban sectors. First, the warmer spring climate allows earlier planting and harvest, which reduces irrigation demands in late summer. Second, expanding cities will displace at least some irrigated agriculture, and this displacement will likely offset at least some of the increase in urban water demand.

Water allocated for human out of stream water uses in the Reference Case scenario.

The graph above shows water allocated basinwide for human out-of-stream water uses for the WW2100 Reference Case scenario. This scenario included mid-range assumptions about climate change, population, and income growth, and assumes management practices, policies and institutions continue in their present form. Additional WW2100 scenarios explored the sensitivity of these projections to different model settings and policy choices. Read more about WW2100 water demand modeling on the Urban Water Use and Agricultural Land & Water Use pages.

  • The array of water laws, water rights, and regulations, play a major role in determining access to water. For example, rules to mitigate the impact of federal dams on threatened and endangered fish strongly influence dam operations and summer flow releases. In quantitative terms, minimum regulatory instream flow requirements established by ESA-related Biological Opinions are a major summer water use, one that exceeds basinwide water demand for irrigation and municipal use.

Water Management Implications:

Changes in prices or other factors that might reduce urban water demand, or lead to changes in the level of agricultural water use, would have relatively small effects on basin-wide water availability compared to changes in the laws and regulations governing instream water requirements. Environmental requirements may limit access to stored water from the federal reservoir system. Policies and management strategies need to adapt to these complex and connected challenges.

 USACE, Adam Stebbins, Stan Gregory

Finding 3: Federal Reservoirs

The 13 federal dams on the Willamette River provide the biggest single mechanism to mitigate water scarcity over the next 90 years; however, with a growing population the importance of the reservoirs for winter flood risk reduction will also rise. Reservoir management will likely need to adapt to changes in seasonal flows and competing downstream water needs.

  • Compared to the historic period, our simulations show increases in winter and spring runoff into reservoirs and decreases in early summer with climate warming. This is due to a shift in precipitation from snow to rain, earlier snowmelt, and reduced upland forest ET in spring due to forest loss from wildfires. Concurrently, the simulations show increasing shortfalls from full reservoir storage during the summer.

Average shortfall from full summer storage by decade for the high climate scenario.

Although the reservoirs were primarily built for flood regulation, they also provide capacity – a combined 1.6 million acre-feet – to store water from abundant winter and spring streamflows for possible use during the summer, when natural flows are low. While flood reduction remains the priority objective of the reservoirs, stored water uses have become increasingly important. Our modeling results indicate increasing shortfalls from full storage at the beginning of summer over time, particularly under warmer climate scenarios, as well as greater summer drawdowns as obligations to release water downstream for conservation flows or contracted stored water are increasingly unmet by natural inflow. Read more about reservoir modeling on the Reservoir Operations and Reservoir Economics pages.

  • In our simulations, lower summer reservoir water levels led to a loss of economic benefits from reservoir recreation. However, that loss was far exceeded by the value of flood mitigation that the dams provide in the Willamette Valley. We estimate current flood mitigation benefits at more than a billion dollars annually and expect these benefits to triple by 2100 with economic growth and urban expansion.

Estimated flood risk reduction benefits from January through May under the reference and high population scenarios.

Estimated flood risk reduction benefits from January through May under the Reference Case and High Population scenarios. Read more about trade offs between flood risk reduction and recreational benefits on the Reservoir Economics page.

  • In addition to sufficient flow, instream habitats in downstream reaches need high quality water, including an optimal temperature. Climate change and land use changes can raise water temperatures, and the cost of providing not only sufficient water but also sufficiently cool water presents a major challenge. Our data suggest that the likelihood of occurrence of native cold-water species, such as juvenile Chinook salmon, would decrease substantially if future river temperature increases by 2° C (3.6° F) or more.

Longitudinal pattern of the likelihood of capturing different fish species.

We do not have modeled estimates of water temperature for 2100, but we projected the consequence of a potential temperature change on the likelihood of capturing representative fish species in our standard field sampling protocol. The graphs above show the longitudinal pattern of the likelihood of capturing different fish species with a standard sampling protocol based on 1) the river temperatures in observed in 2012 and 2013 (green and red lines, respectively) and 2) river temperatures in 2100 if they increase by 2°C compared to the 2012 and 2013 thermal patterns (blue line). Read more about WW2100 fisheries analysis on the Fish & Stream Temperature page.

Water Management Implications:

The federal reservoirs and the storage they provide can play an important role in buffering the effects of climate change in the basin. While flood reduction remains the priority objective of the reservoirs, stored water uses have become increasingly important. Management of those reservoirs and allocation of water behind the dams could become a source of conflict in the future. In addition, any impacts of climate change in areas above the dams (such as the after-effects of wildfires) that could impair dam operations or storage could have significant impact on water scarcity in the valley.

Photo credits (left to right): Abby Metzger, Abby Metzger, Jack Larson

Finding 4: Spatial Variability

Water scarcity will not occur uniformly across the basin. The tributary basins may respond to climate change, population, and income growth differently depending on local differences in both human and natural dynamics.

  • Our model results highlight how water availability varies with geography. Tributaries that drain the Coast Range have a more muted response to climate change than those that are fed by spring snowmelt or abundant groundwater, most of which are located in the High Cascades. Sub-basins with built reservoirs and/or significant groundwater can maintain higher summer flows than those without such water storage. Water scarcity in upland basins is mainly driven by climate change while changes in water scarcity in the valley are affected not only by climate change but also by economic decisions about land use and water use.

Change in summer hydrologic drought for Willamette sub-basins.

Change in summer hydrologic drought for Willamette River tributary basins over the 90 years simulated for the Reference Case scenario. Each plot corresponds to the underlying tributary basin and shows changes in the number of drought days determined for each year of the simulation. The grey shaded area indicates the range of estimates for different modeling scenarios. The red and blue line indicates results for the Reference Case scenario. In several of the sub-basins draining the Cascades, hydrologic drought increases over the century in the more extreme scenarios (show in grey shading). However, in the sub-basins draining the Coast Range, hydrologic drought does not increase as much. The difference between these trends is probably due to the Cascades losing snow over the century, while the Coast Range has not historically had much snow. Consequently, the loss of snow generates more frequent summer drought in these sub-basins. One day of hydrologic drought is defined as a day in which the 30-day running mean discharge is below the 10th percentile of 30-day mean discharges. The water years 2019 and 2020 are two of the lowest-precipitation years in the simulated Reference Case scenario, and so the early century shows significant drought. This particular drought is due to randomness and not climate change.

Water Management Implications:

While the WRB overall may see relatively small changes in scarcity, some sub-basins may experience significant increases in scarcity, especially those without water storage in the form of snowpack, groundwater, or reservoirs. The Willamette Envision model provides a tool to help quantify the system response to potential management strategies that can help facilitate mitigation and adaptation where it may be needed most.

 Sam Chan, Adam Stebbins, Kayla Martin

Finding 5: Stakeholder Involvement

By providing a forum for learning and fostering relationships between water managers, the project helped build capacity in the basin to address future water scarcity.

  • One of the key aspects of this project was the committed engagement of a diverse group of stakeholders, who provided feedback on model design and informed scenario development. Interviews with participants found that individuals were motivated to participate by previous positive experiences with members of the project team, the project’s transdisciplinary approach, and to gain knowledge about water resources, especially under scenarios of future change.

Motivations of participants in the the Learning and Action Network.  Graph from Ferguson 2015.

Motivations of participants in the the Learning and Action Network, based on a survey described in Ferguson et. al. (2016). Read more about the WW2100 stakeholder involvement process and surveys and interviews with participants on the Stakeholder Engagement page.

  • An important factor related to the continued participation of stakeholders during the project was the experience or perception of being heard and valued as contributors.
  • As a university led project with a wide scope, the project provided a neutral forum for learning among diverse water users. Interviewed stakeholders valued the process for the opportunity to build relationships with diverse water users, regulators, and researchers and to begin a constructive dialogue about planning now for possible water availability constraints in the future.

Water Management Implications:

The Willamette River Basin has an engaged stakeholder community, with scientists, citizens, and resource managers willing to work together and plan for water scarcity.

Analysis by Topic

Future Climate

Climate change is one of the external drivers in Willamette Envision. Daily weather data, such as temperature and precipitation, become input variables for biophysical and human systems modeling components as they simulate land and water system changes over the 21st century. Although every projection made by global climate models indicates a warmer climate, the range of plausible projections is wide, and how they will play out in the Willamette River Basin climate is unknown. To account for the large uncertainty in projected climate, the WW2100 project selected three representative scenarios (High Climate Change, Reference, and Low Climate Change) spanning the range of projections in temperature while including variability in precipitation changes. The WW2100 team then used the daily weather conditions predicted by these three scenarios as model forcings for WW2100 simulations. This page describes the process that we, as the WW2100 climate team, used to select and process data from global climate models so that it could be used as input variables for Willamette Envision. It also summarizes key characteristics of future climate conditions predicted by these models.

Our approach involved the following steps:

  • Assessment of the best available climate models for the Pacific Northwest.
  • Selection of greenhouse gas emissions scenarios.
  • Selection of three representative climate scenarios using a sensitivity approach.
  • Tailoring resulting data to the Willamette River Basin by employing an approach called downscaling.

Our analysis indicates that by 2100, the Willamette River Basin will be between 1° C (2° F) to 7° C (13° F) warmer than today. WW2100’s three representative climate scenarios closely span the spread of this uncertainty and range from 6° C (10.5° F) warming for the High Climate Change scenario, to 1° C (2° F) warming for the Low Climate Change scenario. The Reference Case scenario represents the middle of this range with 4° C (7.5° F) warming over the century.

Climate Methods in Brief

Climate Model Evaluation

The World Climate Research Programme’s Coupled Model Intercomparison Project (CMIP) is a worldwide effort to establish a set of standard experimental protocols for the use of general circulation computer models (also called global climate models), or GCMs, in the development of climate scenarios. Essentially, the CMIP project is an attempt by the world’s climate modelers to improve the performance of GCMs, standardize methods of model evaluation, and make GCM outputs directly comparable.

Results from the CMIP project’s latest phase (Phase 5 or CMIP5) began to be available around the time of the launch of WW2100. CMIP5 ushered in a new wave of GCMs and resulting climate data, and was seen by the WW2100’s climate modeling team as an opportunity to both use the new CMIP5 GCMs in WW2100’s work and assess the performance of the CMIP5 models for the United States Pacific Northwest as a whole.

To that end, the WW2100 climate team assessed 41 GCMs from CMIP5 for their ability to simulate various aspects of climate in the Pacific Northwest. The team’s results were published in the Geophysical Research Letters: Atmospheres, where the researchers’ full results and methods can be reviewed. What follows is a summary of the methods employed and how it aided WW2100.

As the WW2100 team stated in their paper, their goal in evaluating the CMIP5 models was “to evaluate model performance in order to make informed recommendations to those who may use these model outputs” (Rupp et al., 2013). The researchers determined these “downstream” users, including resource managers and other scientists assessing climate impacts, would be best served by GCMs that gave the best statistical fit to the observed climate of the Pacific Northwest. (The team defined the Pacific Northwest as the area within longitude 124.5° and 110.5° W and in latitude 41.5° and 49.5° N, or roughly Oregon, Washington, Idaho, and western Montana.)

To find the best fit, the team evaluated the CMIP5 GCMs according to their ability to re-create in computer simulations the observed historical climate of the 20th century. This hindcasting ran from 1850-2005 and focused on temperature and precipitation. Observed climate data were taken from five gridded datasets of monthly means. A suite of statistics, or metrics, were calculated from both the hindcasts and observations and then compared. These metrics included mean seasonal values, interannual variability, amplitude of the seasonal cycle, consistency in spatial patterns, and sensitivity to the El Niño Southern Oscillation, among others. The researchers used two methods for ranking the performance of the GCMs based on these metrics: The first method assigned equal weight to each of the metrics. The second method excluded those metrics that were not considered robust. This involved ranking the metrics under the assumption that certain metrics might be more important in the assessment process. It also included an attempt to avoid redundancy, given that not all metrics are independent of one another.

The result was a ranking of the models according to metrics that led to a subset of GCMs that the team’s methods determined were the best statistical fit for the climate of the Pacific Northwest.

Illustration of CMIP5 Climate Models for the PNW.

Figure 1. A depiction of the climate model assessment work done for WW2100. Models are listed at the bottom. On the left are meteorological measures, including temperature and precipitation. The graph depicts a relative error, in this case how well the models compare relative to each other when matched against actual historical measures for the Northwest. Here warm colors depict higher degrees of error and cooler colors less error. The models are organized from left (least error) to right (most error). (Image Source: Rupp et al., 2013)

Emissions Scenarios Selection

The biggest certainty in climate science is that increasing greenhouse gas (GHG) concentrations, especially carbon dioxide, are heating the Earth’s atmosphere. Precisely how much regional climate temperatures will increase in response to a given rise in GHGs is not known, which is why climate researchers examine more than one GCM. However, the biggest uncertainty about future climate by the end of the 21st century stems from not knowing just how much GHG human industry will continue to emit.

With their chosen models, the WW2100’s climate team used GCM output (available from the CMIP5 project) for two emission scenarios to incorporate a range of GHG concentration uncertainty. These emission scenarios are known as Representative Concentration Pathways, or RCPs, a category created by researchers convened to support the work of the United Nation’s Intergovernmental Panel on Climate Change (IPCC).

RCPs are the new standard for modeling emission uncertainty. There are four RCPs representing different concentrations of greenhouse gases, or different possible futures based on how much GHGs human industry might emit. These scenarios are: RCP 8.5, RCP 6, RCP 4.5, and RCP 2.6. Here, higher numbers represent a greater degree of radiative forcing (in terms of W m2 over preindustrial levels; e.g., 8.5 = 8.5 W m2) that the scenarios are expected to produce by 2100 (RCP 8.5 is bigger than RCP 6 and so on) and, hence, represents a future scenario with more emissions.

For WW2100,  we employed two RCPs: RCP 8.5 (the high emissions scenario that assumes human industry will continue to emit greenhouse gases at a growing rate) and RCP 4.5 (a middle-of-the-road scenario in which emissions will be curbed starting in the middle of this century).

Selecting Representative Climate Scenarios Using a Sensitivity Approach

Resource managers and other downstream users of GCM data often lack the ability to process data from multiple climate models and scenarios, which requires considerable computing resources. This is especially true when considering other types of future scenarios in their impacts work, such as economics, demographics, and land uses, which require still more computing resources. What is often done instead is to select a subset of representative models and scenarios. For WW2100,  we selected a subset of three “representative” scenarios, that is scenarios that are representative of GCMs run with the RCPs, the data from which could then be fed into WW2100’s latter modeling.

To find their subset of scenarios, the team conducted a sensitivity analysis in the Willamette River Basin that allowed them to select three representative GCMs from the 33 CMIP5 climate models for which future climate scenarios were available (from the 41 GCMs evaluated in the first step).

The sensitivity analysis used simple perturbation experiments to estimate how changes in temperature and precipitation affect summertime streamflow in the Willamette River Basin. More specifically, using the Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model, we simulated streamflow using historical weather data from 1975-2004. Then, we ran a perturbation: Using the same set up, we ran the hydrologic model again, but with incremental increases in temperature. The percent in which summertime streamflow changes in these perturbation experiments provides an estimate for how sensitive it will be in a warmer climate. The same type of perturbation experiments were then repeated, but this time for incremental precipitation increases and decreases.

From this, we then used these derived sensitivities to draw contours of constant summertime streamflow change on a scatter plot of temperature and precipitation changes in GCM output. With the contours as guides, the team selected GCMs and accompanying RCPs with the objective of spanning a wide range of warming (high, middle, and low) while also spanning a wide range of hydrological impact. Where multiple models were available to choose from in each category (high, middle, low), the team chose one of the better performing GCMs according to the model ranking discussed above.

Representative scenarios selection plot for summertime streamflow change in the Willamette River basin.

Figure 2. Representative scenarios selection plot for summertime streamflow change in the Willamette River Basin. Contours represent constant change in streamflow calculated from perturbation experiments. GCM precipitation and temperature changes are based on differences between 1970-1999 and projected changes for the period 2041-2070. Climate models are listed on the right. Models were run using the emissions scenarios RCP 4.5 (low scenario) and RCP 8.5 (high scenario), shown in blue and red respectively. (Image Source: Vano et al., 2015)

From this analysis, three scenarios, now a combination of GCMs that had been run with the two separate RCPs, were ultimately selected.

The final representative selections are: the High Climate Change scenario (the HadGEM2−ES climate model run with RCP 8.5); the Reference Case scenario (the MIROC5 climate model run with RCP 8.5); and the Low Climate Change scenario (the GFDL−ESM2M climate model run with RCP 4.5). Note: GFDL-ESM2M was not ranked highly by performance, but it was selected nonetheless to represent the Low Climate Change scenario, as none of the lowest-warming models were ranked highly. Hereafter the scenarios will be referred to as HighClim, Reference, and LowClim.

The LowClim scenario represents a small temperature increase and small decrease in summertime streamflow (lowest impact). The HighClim scenario represents a large temperature increase and large decrease in summertime streamflows (highest projected impacts). The Reference scenario lies between the two extremes.

It’s worth noting that an additional constraint was placed on the selection process: that all requisite data for a given GCM was available for the downscaling procedure (see section on downscaling below). This constraint ultimately limited the team to choosing from among 20 GCMs.

Downscaling

In order to feed data from the HighClim, Reference, and LowClim scenarios into WW2100’s later modeling work, the team performed a process called downscaling. Downscaling is a means to convert or translate the coarse resolution of GCM grids (which are as large as 375 km, roughly 233 miles, to a side) down to a finer resolution, which for WW2100 was about 4 km, roughly 2.5 miles. This is done to account for the details of local topography and local climate. This adjustment is needed in the Pacific Northwest, which has a complex mountainous topography that does not appear in a detailed form in the GCMs.

For the WW2100, we downscaled data from the HighClim, Reference, and LowClim scenarios for the Willamette Valley. The method used was the Multivariate Adaptive Constructed Analogs (MACA), a downscaling method developed by University of Idaho (UI) researcher John Abatzoglou. Resulting data from the downscaling was then fed into the Envision model’s component models.

 

Select Findings from Climate Analysis

By 2100, the Willamette River Basin is projected to be between 1° Celsius (2° Fahrenheit) and 7° C (13° F) warmer than in the recent past (1950-2005). Here we summarize climate projections for the Willamette River Basin determined from analysis and downscaling of global climate models and provide context for the three WW2100 climate scenarios.
 

Temperature

  • By 2100, the Willamette River Basin is projected to be between 1° C (2° F) and 7° C (13° F) warmer than today. This conclusion is based on two greenhouse gas (GHG) concentration pathways, also called emissions scenarios, with output from 20 global climate models (GCM) from the Coupled Model Intercomparison Project Phase 5.

  • WW2100’s three representative climate scenarios closely span the spread of this uncertainty and range from 6° C (10.5° F) warming for the High Change Climate (HighClim) scenario to 4° C (7.5° F) warming for the Reference Case scenario to 1° C (2° F) warming for the Low Change Climate (LowClim) scenario.

  • Warming from increasing anthropogenic GHG concentrations dominates the long-term variability in temperature. Projected temperature increases on the decadal scale (or decades-long scale) exceed natural variability such that the Willamette River Basin does not experience the climate of the latter 20th century during any decade from the present through 2100 (and beyond).

  • The summer months of July through September, already the warmest months of the year, are projected to warm most under climate change, by about 2° C °(3.6° F) more than in winter.

showing the four RCPs and their emissions trajectories over the 21st century

Figure 3. The four RCPs and their emissions trajectories over the 21st century. The largest uncertainty in climate modeling is how much greenhouse gas (GHG) humans will continue to emit into the atmosphere and thus how much trapped energy from the sun will continue to heat the atmosphere. To account for this uncertainty, the United Nation’s Intergovernmental Panel on Climate Change (IPCC) has created four emissions scenarios, called the Representative Concentration Pathways (RCPs), to help streamline climate modeling. (RCPs replace the older Special Report on Emissions Scenarios [SRES].) The RCPs are: RCP 8.5, RCP 6, RCP 4.5, and RCP 2.6. The four RCPs represent different GHG concentrations. Higher numbers represent a greater degree of additional radiative forcing above preindustrial levels by 2100 (RCP 8.5 is bigger than RCP 6 and so on). For WW2100,  we employed two RCPs: RCP 8.5 (the high emissions scenario, which assumes human industry will continue to emit greenhouse gases at a growing rate) and RCP 4.5 (a middle-of-the-road scenario in which emissions will be curbed starting in the middle of the 21st century).

Differences in annual temperature for 1950-2100 from a historical baseline (mean of 1950-2005).

Figure 4. Temperature projections for the Willamette Basin with WW2100 scenarios. Differences in annual temperature for 1950-2100 from a historical baseline (mean of 1950-2005). Results are from 40 downscaled climate simulations, employing 20 CMIP5 GCMs and two GHG concentration pathways (RCP 4.5 and RCP 8.5). The simulated historical temperatures (with known GHG concentrations) are shown in gray. Future projections with assumed GHG concentrations are color-coded: yellow for the lower GHG concentration pathway (RCP 4.5) and red for the high GHG concentration pathway (RCP 8.5); orange denotes where two RCPs intersect. Overlaying this are WW2100’s representative climate scenarios: HighClim, Reference, andLowClim. The representative scenarios are combinations of three climate models (HadGEM2−ES, MIROC5, and GFDL−ESM2M) run with RCP 4.5 and RCP 8.5: The HighClim scenario was run with RCP 8.5; the Reference scenario was run with RCP 8.5; and the LowClim scenario was run with RCP 4.5. (See Fig. 1 for explanation of RCP emissions scenarios.) Note: the three representative scenarios track closely the range of uncertainty resulting from the multi-model ensemble runs.

Changes in mean temperature by month for the period 2050-2099 from the historical period 1950-1999 for the Willamette River basin

Figure 5. Change in mean temperature. Changes in mean temperature by month for the period 2050-2099 from the historical period 1950-1999 for the Willamette River Basin. The October-to-October timeframe shows the water year, which runs from 1 October to 30 September of any given year. Note: WW2100’s representative climate scenarios largely span the range of the uncertainty of the projected temperature changes at the high, medium, and low ends of the temperature distribution. HighClim is represented in blue; Reference Case in represented in purple; LowClim is represented in pink.

Precipitation

  • The majority of climate scenarios show a general trend of wetter winters and drier summers in the Willamette River Basin. However, unlike with temperature projections that uniformly show temperatures will rise, climate models do not unanimously simulate either a drier or wetter future.
  • Increases in winter precipitation stem mainly from heavier precipitation during wet periods, not an increase in the frequency of precipitation.
  • Natural variability will remain large relative to the greenhouse gas response, even at the decadal scale, so that yearly and decadal precipitation both above and below the historical averages should still be expected.
  • Due to rising temperatures, precipitation is increasingly likely to fall as rain instead of as snow, resulting in a decreased snowpack. The snowpack (measured as snow water equivalent: SWE) as a proportion of cumulative water-year precipitation (P) is expected to decline markedly across the region. A parallel study by members of the WW2100 team shows that those sub-basins that historically receive the most snow, such as North Santiam, have projected winter (December, January, and February) declines of one-quarter to two-thirds in SWE/P by about the mid-21st century. Sub-basins with little snow currently, such as Middle Willamette, are projected to receive virtually no snow in the future. The small projected increases in total winter precipitation provide little offset to the loss in snow due to projected warming
  • For every 1° C (~2° F) increase in annual mean temperature, there is a roughly 15 percent decrease in summer flow in the lower Willamette River Basin. However, as temperatures get significantly higher than the historical average, the spring snowpack is essentially absent. Thus, additional temperature increases have only a marginal effect on streamflow.

Projected differences (as percentages) in annual precipitation for 1950-2100 from a historical baseline (mean of 1950-2005).

Figure 6. Projected differences (as percentages) in annual precipitation for 1950-2100 from a historical baseline (mean of 1950-2005). Here the zero line represents historical climate; changes above and below the line represent more or less precipitation respectively. Note: The majority of climate models run for WW2100 are projecting changes to annual precipitation that do not deviate largely from our region’s historical climate. This means natural variability is expected to play a larger role in precipitation trends into the future than forcing from GHGs. However, the majority of models are trending toward wetter winters and drier summers (See Fig. 7). The simulated historical precipitation (with known GHG concentrations) is shown in gray. Future projections with assumed GHG concentrations are color-coded: pale blue for the lower emissions scenario (RCP 4.5) and dark blue for the high emissions scenario (RCP 8.5); medium blue denotes where two RCPs intersect. Overlaying this are WW2100’s representative climate scenarios: HighClim, Reference, and LowClim. The representative scenarios are combinations of three climate models (HadGEM2−ES, MIROC5, and GFDL−ESM2M) run with RCP 4.5 and RCP 8.5: The HighClim scenario was run with RCP 8.5; the Reference scenario was run with RCP 8.5; and the LowClim scenario was run with RCP 4.5. Note that the three representative scenarios include both drier and wetter than average periods.

Changes in mean monthly precipitation for the period 2050-2099 from the period 1950-1999.Figure 7. Changes in mean monthly precipitation for the period 2050-2099 from the period 1950-1999. Output for the majority of climate models run done for WW2100 are showing a tendency toward wetter winters and drier summers. The October-to-October time frame shows the water year, which runs from 1 October to 30 September of any given year. Here, the zero line represents historical climate. Note: the tendency to rise above the zero line (get wetter) in winter and to drop below the zero line in summer (get drier).

 

Related Publications & Links

 

Contributors to WW2100 Climate Research

  • Philip Mote, Oregon State University (OSU) Oregon Climate Change Research Institute (OCCRI) and the Pacific Northwest Climate Impacts Research Consortium (CIRC) (lead)
  • David Rupp, OSU OCCRI/CIRC
  • Anne Nolin, OSU College of Earth, Ocean, and Atmospheric Sciences
  • Kathie Dello, OSU OCCRI/CIRC
  • Julie Vano, OSU OCCRI/CIRC
  • Dennis Lettenmaier, formerly University of Washington CIRC
  • John Abatzoglou, University of Idaho (UI) CIRC
  • Katherine Hegewisch, UI CIRC
  • Hamid Moradkhani, Portland State University Civil & Environmental Engineering

 

Web page authors: P. Mote, D. Rupp, J. Vano, N. Gilles
Last updated: November 2015

 

Population, Income & Land Use

Population and income are key drivers of land value for developed uses. As population and earning potential increase, demand for developed urban land also increases, transitioning land away from agricultural and forest uses while also driving up land value. Understanding future population and income growth is paramount to anticipating shifts in land use and the resulting impacts on water.

The land-use team developed modeling components within Willamette Envision to simulate how land moves among agricultural, forest, and urban uses in the Willamette Valley. Future population and income growth in the region were assumed to be determined by forces outside the model, and thus, like climate change, were external to any actions by individuals or policy makers in the basin. Our model also represented the value of land in agricultural and forest uses, which is determined by site-specific factors such as slope, elevation, and access to water for irrigation. Within the model, relative values of land in different uses determined changes in land use over time. Urban growth boundaries (UGBs), an integral part of the land-use planning system in Oregon, constrained where development can occur and were adjusted periodically as a city’s population grew.  

In the Reference Case scenario, the area of developed land increases by 54% between 2010 and 2100, and the areas of land in agriculture and forest decrease by 8% and 1%, respectively.  Much of the future development is projected to occur in the Portland Metropolitan Area.

 

Land Use Change Modeling in Brief

The land-use team simulated how land moves among agricultural, forest, and urban uses. These transitions are a function of economic returns to alternative uses, which are determined themselves by site characteristics such as farm rents, distances to cities, and population and income of cities. Returns to land and land-use transitions also are influenced by urban growth boundaries (UGBs), the land use planning lines that restrict development. Here we provide a brief explanation of land-use change modeling in Willamette Envision. For a more detailed explanation refer to Jaeger et al. (2016) and Bigelow (2015).

During a model run, Willamette Envision simulates land-use changes annually at the scale of parcels (referred to as Integrated Decision Units or IDUs within Willamette Envision). Growth in population and income increase the returns to developed uses relative to forest and farm uses, while agricultural land values are influenced by the availability of water for irrigation. We derived functions that estimate the economic returns to each land use from historical data for the Willamette Valley (Bigelow, 2015). In response to changes in the relative returns to different uses, IDUs may shift among agricultural, forest, and urban uses as the model runs. Land-use changes in the model are governed by probabilistic equations estimated with historical data from the National Resources Inventory (NRI).

To account for zoning rules under Oregon’s land-use planning system, the model treats land inside and outside of UGBs differently. Land outside of UGBs can move between undeveloped uses (i.e., ag-to-forest and forest-to-ag transitions are allowed), but transitions to developed use are not allowed. For IDUs inside of UGBs, all of the transitions are allowed, but development is treated as irreversible (i.e., once a forest or agricultural IDU is developed, it cannot return to its original use). Given the irreversibility of development, it follows that, over time, the share of developed land within each UGB will increase. To mimic the land-use planning process, we allowed for UGBs to expand once the developed share became sufficiently large. Once a specified threshold is exceeded, a UGB expansion will be triggered. UGB expansions occurred in a way that approximated rules under the land-use planning system. For example, land zoned for Exclusive Farm Use and Forest Conservation will be brought inside of UGBs only when other opportunities are exhausted. In the case of the Portland Metropolitan Area, priority is given to areas designated as urban reserves.

Population and Income Growth

Willamette Envision treats population and income growth as external drivers, forces that are determined outside of the model and can be varied for different modeling scenarios. The population and income projections adopted for the Reference Case and many other WW2100 modeling scenarios, were based on forecasts from the Oregon Office of Economic Analysis (2011; OEA) and Woods and Poole Economics, Inc. (2011). The OEA forecasts population for each county to 2050, while Woods and Poole forecast mean household total personal income to 2040 (in inflation-adjusted dollars). We used linear extrapolation to 2100, which implied diminishing growth rates over time for both variables (Fig.1). Projected county population was allocated to areas within UGBs and rural residential zones based on population percentages in the 2010 Census. Rural residential zones were allowed population growth until they reached a density of one household for every two acres of land. Once these areas were full, all new population was added within UGBs. All cities within a county were assumed to have the projected mean household income.

 

Selected Findings from Land Use Change Analysis

Population and Income

  • Over the period 2010 to 2100, population is projected to increase in every county in the Willamette Basin, although the increases in absolute terms are largest for Washington, Multnomah, and Clackamas counties (Fig. 1). The basin population is projected to increase by 3.05 million people, a gain of 111%.

  • Mean household total person income increases from a basin average of $83,893 in 2010 to an average of $233,479 in 2100 (Fig. 1). These figures are reported in constant 2005 dollars to remove the effects of inflation. Although these changes may seem large, the growth rate in income was much higher over the previous 90-year period (1920 to 2010).

Figure 1a. Population projections to 2100.

Figure 1b. Income projections to 2100.

Figure 1. Willamette Water 2100 population and income projections.

Land Use

  • In the Reference Case scenario, the area of land in developed use increases from 334,921 acres to 516,053 acres between 2010 and 2100, an increase of 54% (Fig. 2). These increases are mirrored by declines in agricultural land (117,751 acres or -8%) and forest land (63,376 acres or -1%).

  • Much of the increase in developed land is projected to occur in the Portland Metropolitan Area (Fig. 3). This reflects the relatively large increases in population forecasted for the three Metro counties.

  • The inflation-adjusted value of land in developed uses increases through the basin, but reaches the highest levels in the Portland Metropolitan Area (Fig. 4). The average value of land in agriculture declines by 8% between 2010 and 2100, and the forest value remains relatively constant.

  • Population densities (the ratio of population to developed land area) are projected to increase in Salem, but remain relatively constant in the other cities in the basin. Population growth has competing effects on densities, raising the level of population but also the area of developed land. In addition, the area of developed land consumed per household increases over time.

  • The projected area of land in developed use is higher in the High Population Growth (HighPop) scenario and the Urban Expansion (UrbExpand) scenario. The HighPop scenario includes population growth rates within UGBs that are doubled relative to the Reference scenario. The UrbExpand scenario relaxes the threshold requirement for UGB expansions and eliminates urban reserves for Portland Metro.

Projected land use change for the Reference scenario.

Figure 2. Projected land-use change in the Willamette Basin for the Reference Case scenario.

Map showing urban expansion in the Reference scenario.

Figure 3. Projected urbanization patterns for the Reference Case scenario.

Developed land values for the Reference scenario.

Figure 4. Projected values of developed land for the Reference Case scenario.

Population density by county/region for the Reference scenario.

Figure 5. Projected population densities for the Reference Case scenario.

Projected growth in developed land area for several WW2100 scenarios.

Figure 6. Projected developed land area for the Reference Case and two alternative scenarios.

Conclusions

Population and income growth in the Reference Case scenario raise the demand for urban land in the Willamette Basin, which raises the value of developed land over agricultural and forest land. This increases the area of developed land by 54% between 2010 and 2100, while decreasing agricultural and forest land areas by -8% and -1%, respectively. The land-use planning system determines where this future urbanization can occur. We project that the largest increases in developed area will occur within the Portland Metropolitan Area.

Notes, Related Links & Publications

  • Bigelow, D.P. (2015). How do population growth, land-use regulations, and precipitation patterns affect water use? A fine-scale empirical analysis of landscape change. PhD Dissertation. Oregon State University.

  • Note: We conducted a statistical analysis of land values using data collected from assessor offices in Benton, Lane, Marion, and Washington counties. Details are provided in Bigelow (2015). The land-use transition model was adapted from the estimates in Lewis et al. (2012). 

Contributors to WW2100 Land Use Research

  • Andrew Plantinga, UC Santa Barbara - Bren School of Environmental Science & Management (lead)

  • Daniel Bigelow, PhD Student, OSU Applied Economics (graduated: 2015)

  • David Conklin, Oregon Freshwater Simulations

References

Bigelow, D.P. (2015). How do population growth, land-use regulations, and precipitation patterns affect water use? A fine-scale empirical analysis of landscape change. PhD Dissertation. Oregon State University.

Jaeger et. al. (2016). Scarcity amid abundance: Water, climate change, and the policy role of regional system models. Manuscript in preparation.

Lewis, D. J., Plantinga, A. J., Nelson, E., & Polasky, S. (2011). The efficiency of voluntary incentive policies for preventing biodiversity loss. Resource and Energy Economics, 33(1), 192-211.

Oregon Office of Economic Analysis. (2011). Forecasts of Oregon's County Populations and Components of Change, 2010 – 2050, Salem, Oregon.

Woods and Poole Economics, Inc. (2011). 2011 Idaho, Washington, and Oregon State Profile. Washington, DC. https://www.woodsandpoole.com

 

Webpage authors: D. Bigelow, A. Plantinga
Last updated: September 2016

Upland Forest Change

Today the Willamette River Basin’s vegetation is predominately a mix of grasslands and croplands in the valley floor and coniferous forest in the uplands. This vegetation mix is expected to change as rising temperatures create a less-favorable climate for existing vegetation and as forest fires increase in frequency and intensity. WW2100 upland forest modeling simulated how climate change is likely to affect forest composition, forest area burned by wildfires, and the resulting impact on timber harvest and evapotranspiration. Our results suggest that climate change will become an increasing influence on forest management decisions throughout the 21st century. In our simulations, low snowpack and hotter, drier summers lead to a two- to nine-times increase in land area burned by forest wildfires. The fires open up lands to transition to new forest types better suited to the changing climate. At high elevations, cool conifer forests replace subalpine forests. At mid-elevations, Douglas-fir and western hemlock forest types shift to mixed forest types. Increases in wildfire reduce the availability of forestland for timber harvest and affect hydrology.

 

Forest Modeling in Brief

The forest modeling team developed component models for Willamette Envision that simulate how upland forests will age and change through time, given forest type, climate conditions, and disturbance by wildfire and harvest. Here we provide a brief explanation of forest modeling in Willamette Envision. For full details on methods and results from WW2100 forest modeling studies, refer to Turner et al. (2015, 2016).

On an annual basis, Willamette Envision determines the forest type and age in each modeling polygon based on information from models of forest growth and succession (called forest state-and-transition models, STMs). The STMs determine the sequence of forest types that occur over time. In the simplest case, the forest progresses from new growth following a disturbance, through different successional stages, and ultimately to an old growth forest state. Depending on the type and timing of disturbances, forest growth and succession can follow alternate pathways specified by different STMs. When a disturbance occurs, the forest can also “reset” to a new forest type better suited to the current climate conditions. These new “potential” vegetation types were determined for the three WW2100 climate scenarios using offline runs of a dynamic global vegetation model called MC2. MC2 simulates wildfire occurrence and simulates the type of vegetation best suited to grow at a location based on climate, soil, elevation, and latitude. 

Willamette Envision simulates forest harvest on the landscape, according to criteria defined for each scenario. For example, a scenario can specify a harvest rate (the total area of forest harvested each year) for specific forest age classes and land ownership categories (e.g., private lands with forests older than 40 years). Over the simulation, Willamette Envision randomly selects modeling polygons that meet the criteria for harvest. Users can also prescribe the extent of wildfire (the forest area burned per year), and Envision places fires randomly on the landscape. In WW2100, the extent of wildfire was determined from historical observations and the offline runs of MC2 for the three WW2100 climate scenarios. MC2 takes into account factors such as air temperature, relative humidity, and ensuing forest moisture conditions, and determines the area of forests that burn each year. Hotter, drier conditions lead to more extensive wildfires.

Additional Modeling Details:

  • The initial condition of the landscape, which classifies different species of vegetation, and state and transition models (STMs) were based on work from the Integrated Landscape Assessment Project (ILAP) (Halofsky et al., 2014; INR, 2013). Boundaries for land ownership and protection status were from the US Geological Survey (GAP, 2014).

  • Harvest rates in the Reference Case scenario were based on the observed harvest rate from 1986-2010 in the Willamette River Basin (Kennedy et al., 2010; Kennedy et al., 2012). These Landsat-based observations suggested a harvest rate of 1.3% per year across all private forestland, equivalent to ~11,740 hectares per year (29,000 acres) and 0.5% per year on public lands, equivalent to ~3,240 hectares per year (8,006 acres). Harvest on public lands was limited to unreserved stands with ages between 40-80 years, since older forests are largely conserved for wildlife on public lands.

  • The initial probability of fire in the Reference Case scenario were based on observations of the Landsat record (Kennedy et al., 2012), and we did not stratify by ownership class. Over the 1986-2010 period, 0.2% per year of forestland area was burned in the Willamette River Basin. The future extent of fire was based on the MC2 results, thus capturing the increasing incidence of fire associated with a warming climate. Annual area burned was input to Willamette Envision, and fires were placed randomly on the landscape. Fire size was 22,500 ha except when only a fraction of that was needed to reach the prescribed total area burned.

  • We assigned values for Leaf Area Index (LAI), a measure of forest canopy cover, for each forest type and stand age class based on off-line runs of the Biome-BGC productivity model (Thornton et al., 2002). LAI is used to estimate forest evapotranspiration in hydrologic modeling.

 

Select Findings from Upland Forest Analysis

From the valley floor east to the crest of the Cascade Range, air temperatures decrease and precipitation increases as elevation rises (Fig. 1). These gradients drive a change from maritime conifer to cool needleleaf forest and ultimately to subalpine conifer forest. This vegetation mix is expected to change as rising temperatures create a less-favorable climate for existing vegetation and as forest fires increase in frequency and intensity. Here we highlight some of the key findings from WW2100 forest modeling. For more detailed analysis, refer to Turner et al. (2015, 2016).

Figure 1. The Willamette River Basin study domain: a) Vegetation cover and conifer age class, b) Elevation.

Figure 1. The Willamette River Basin study domain: a) Vegetation cover and conifer age class, b) Elevation. (Figure from Turner, 2015)

Wildfire

  • Under the various climate scenarios, frequency of wildfires relative to the historical period increases as temperature increases.
  • Under the Low Climate Change (LowClim) scenario, the area burned per year is only slightly below the historical rate.
  • Under the Reference Case (Reference) scenario, the simulated forest area burned per decade in the 2010-2100 period is 0.6% per year (vs. 0.2% per year in recent decades). Fire tends to be concentrated in particular years, with as much as 25% of the forested area burning in a high fire year late in the 21st century (Fig. 2).
  • The High Climate Change (HighClim) scenario (warmest temperatures) induces the largest areas of fire per year, with average area burned per year increasing by a factor of nine relative to the historical period.
  • In the Reference and HighClim scenarios, the proportion of the Willamette River Basin that is recently burned and relatively open increases. (Note: WW2100’s simulations did not include pest and pathogen disturbances, which are also likely to increase with climate warming.) More relatively open areas result in lower mean leaf area. These decreases in leaf area lead to reduced growing season evapotranspiration, despite higher evaporative demand due to higher temperatures.
  • Several of the WW2100 alternative scenarios influence the forest uplands. In the case of the Upland Wildfire Suppression (FireSuppress) scenario, the incidence of fire is maintained at the contemporary rate (0.2% of area per year). This assumption results in an increase in the proportion of the forest area with a difference (disequilibrium) between climate and potential vegetation type. In the Extreme scenario, the average area burned rises to 0.8% per year. Results in terms of vegetation change are similar to the Reference scenario. In the Managed scenario, the assumed fire rate is low relative to the Reference scenario and rotation age is reduced. These assumptions mean that the landscape is able to sustain contemporary rates of harvest on public and private lands.

Figure 2. Area burned per year in the three climate scenarios.

Figure 2. Area burned per year: a) LowClim, b) Reference, c) HighClim.

Harvest

  • Under climate change, the increased prevalence and power of forest fires is expected to affect how and if trees, such as the commercially important Douglas-fir, are harvested. The WW2100 forest team found that as temperatures increase from 2010-2100 (note: all three representative scenarios show some degree of warming), forest fires increase and mature forests available for harvest correspondingly decrease. (Worth noting in these results: Today’s forest age class distribution in the Willamette River Basin differs substantially between public and privately owned forestland. A significantly larger proportion of the forestland in older age classes are on public land, which also tends to be at higher elevations.)
  • Under the LowClim and Reference scenarios, the harvest rate on private land is stable at about 1.5% of the area per year, and the harvest rate on public lands is stable at a rate of about 0.5% per year (Fig. 3).
  • Under the more severe fire regimes in the HighClim scenario, harvestable forest area decreases, such that the harvest rate begins declining towards the end of the century on both private and public forestland (Fig. 3).

Figure 3.  Area harvested per year (public and private):  a) LowClim, b) Reference, c) HighClim.

Figure 3. Area harvested per year (public and private) in three Willamette Water 2100 modeling scenarios: a) LowClim, b) Reference, c) HighClim.  (Figure from Turner, 2015)

Vegetation Shifts

Plant species in the Northern Hemisphere are moving to higher latitudes and elevations in response to climate change. These climate-induced shifts in vegetation are due primarily to rising temperatures, as plant species migrate to areas with temperatures ranges they are adapted to. This shift in vegetation, already observed in the Northwest, is expected to continue under climate change. WW2100’s forest team produced the following findings concerning vegetation shifts and climate change for the Willamette River Basin:

  • The climate-induced shifts in potential vegetation cover type for the Willamette River Basin under the three climate scenarios are proportional to the magnitude of the climate change (Fig. 4). Under the LowClim scenario (least warming), there is little change in potential vegetation type, whereas with the HighClim scenario (highest warming) the potential vegetation cover type changes over the entire Willamette River Basin by the end of the 21st century.
  • Existing forest vegetation types tend to be replaced by other types of forest.
  • Subalpine forests, now dominated by Subalpine fir, are replaced by cool conifer forests, such as the Pacific silver fir.
  • At the mid-elevations, the maritime conifer forest, generally associated with Douglas-fir and western hemlock, shift to more mixed forest types with hardwood species such as the Big Leaf Maple, and conifer species such as the Grand fir increasing in dominance.
  • Potential vegetation cover type in the relatively low elevation Willamette Valley periphery change from maritime conifer to subtropical mixed forest in the Reference and HighClim scenarios, here driven by the coldest month temperature. The most likely broadleaf species to replace the existing Willamette Valley maritime conifer species are the Pacific madrone and tanoak. Both species currently dominate at mid-elevations in the Sierra Nevada Mountains 800 km (500 miles) to the south. These evergreen broadleaf species would benefit from the projected warmer winters and can tolerate drier summers.
  • The change in the actual vegetation type following a disturbance lags the change in potential vegetation type, meaning what vegetation type the climate could support based on the MC2 model runs, in all scenarios. By 2100 in the LowClim scenario, the area of upland vegetation in disequilibrium is 22% of the total forest area. However, that proportion rises in the two warmer climate scenarios (53% in the Reference and 56% in HighClim scenarios) by the end of the century. Much of the speckling in the actual vegetation cover by 2100 (Fig. 5b) is where stand replacing disturbances, either harvests or fire, induces a change in vegetation cover type to the underlying potential vegetation cover type (Fig. 5a).

Figure 4.  Time series for potential vegetation cover type proportions of the Willamette River Basin uplands: a) LowClim, b) Reference, c) HighClim.

Figure 4. Time series for potential vegetation cover type proportions of the Willamette River Basin uplands: a) LowClim, b) Reference, c) HighClim.  (Figure from Turner, 2015)

Figure 5.  Vegetation distribution in 2100 for the Reference Case scenario: a) Potential Vegetation Cover type (from MC2), a) Actual Vegetation Cover type (from Envision).

Figure 5. Vegetation distribution in 2100 for the Reference scenario: a) Potential Vegetation Cover type (from MC2), a) Actual Vegetation Cover type (from Envision).  (Figure from Turner, 2015)

Conclusions

The recent climate in the western U.S. is already warmer than in previous decades, and increases in tree mortality have been linked to climate change. Spatially explicit landscape simulation of potential and actual vegetation could be particularly effective in adaptation efforts. Using climate observations, stands in different locations could be regularly assessed for the degree to which the vegetation type is out of equilibrium with the local climate, and hence at risk for attack by pests and pathogens. The most vulnerable stands could be prioritized for thinning or harvest.

Dynamic global vegetation models (DGVMs) driven by the latest downscaled climate data could provide resource managers with guidance on what type of vegetation to replant after a disturbance. Our results support the conclusion that climate change will become an increasing influence on forest management decisions throughout the 21st century. The projected increase in the risk of fire points to investments in fire management.

Related Links & Publications

Contributors to WW2100 Forest Research

  • David Turner, OSU Forest Ecosystems & Society (lead)
  • David Conklin, Oregon Freshwater Simulations
  • John Bolte, OSU Biological & Ecological Engineering

References

GAP. (2014). US Geological Survey, Gap Analysis Program (GAP).  National Land Cover, Version 2. http://gapanalysis.usgs.gov/gaplandcover/data/

Halofsky, J. E., Creutzburg, M. K., & Hemstrom, M. A. (2014). Integrating social, economic, and ecological values across large landscapes (General Technical Report PNW-GTR-896). Corvallis, Oregon: USDA Pacific Northwest Research Station.

Halofsky, J. E., Hemstrom, M. A., Conklin, D. R., Halofsky, J. S., Kerns, B. K., & Bachelet, D. (2013). Assessing potential climate change effects on vegetation using a linked model approach. Ecological Modelling, 266, 131-143. http://dx.doi.org/10.1016/j.ecolmodel.2013.07.003

INR. (2013). Integrated Landscape Assessment Project. Retrieved October 15, 2015, from http://inr.oregonstate.edu/ilap

Kennedy, R. E., Yang, Z., & Cohen, W. B. (2010). Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr—Temporal segmentation algorithms. Remote Sensing of Environment, 114(12), 2897-2910. http://dx.doi.org/10.1016/j.rse.2010.07.008  

Kennedy, R. E., Yang, Z., Cohen, W. B., Pfaff, E., Braaten, J., & Nelson, P. (2012). Spatial and temporal patterns of forest disturbance and regrowth within the area of the Northwest Forest Plan. Remote Sensing of Environment, 122, 117-133. http://dx.doi.org/10.1016/j.rse.2011.09.024  

Path Landscape Model. (2015). Retrieved October 15, 2015, from http://essa.com/tools/path-landscape-model/

Rogers, B. M., Neilson, R. P., Drapek, R., Lenihan, J. M., Wells, J. R., Bachelet, D., & Law, B. E. (2011). Impacts of climate change on fire regimes and carbon stocks of the US Pacific Northwest. Journal of Geophysical Research: Biogeosciences, 116(G3). http://dx.doi.org/10.1029/2011JG001695

Thornton, P. E., Law, B. E., Gholz, H. L., Clark, K. L., Falge, E., Ellsworth, D. S., … Sparks, J. P. (2002). Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests. Agricultural and Forest Meteorology, 113, 185–222.

Turner, D. P., Conklin, D. R., Vache, K. B., Schwartz, C., Nolin, A. W., Chang, H., ... & Bolte, J. P. (2016). Assessing Mechanisms of Climate Change Impact on the Upland Forest Water Balance of the Willamette River Basin, Oregon. Ecohydrologyhttp://dx.doi.org/10.1002/eco.1776

Turner, D. P., Conklin, D. R., & Bolte, J. P. (2015). Projected climate change impacts on forest land cover and land use over the Willamette River Basin, Oregon, USA. Climatic Change, 133(2), 335-348. http://dx.doi.org/10.1007/s10584-015-1465-4

 

Web page authors: D. Turner, N. Gilles
Page last updated: September 2016

Snow

Each winter, snow accumulates in the higher elevations of the Willamette Valley. This natural reservoir serves to store a proportion of the winter precipitation, releasing into streams (and reservoirs) during the spring. Snow is the most climatically sensitive element of the annual water budget in the basin. Changes in precipitation, temperature, and forest cover will affect snow accumulation, while changes in temperature and forest cover will affect the rate of snowmelt. 

The snow modeling team examined the maximum snow water equivalent (SWE) over the period January 1-April 1 for each year for the Low Climate Change (LowClim), Reference Case (Reference), High Climate Change (HighClim), and Upland Wildfire Suppression (FireSuppress) scenarios. The LowClim scenario, in which temperatures increase only slightly and winter precipitation also slightly increases, shows an increase in seasonal maximum snow water equivalent of about 41% for elevations above 1200 m (3937 ft). Low elevation snow (500-1200 m, or 1640-3937 ft) varies from decade to decade but there is no trend over the 90-year period. The Reference scenario shows a steep decline in seasonal maximum SWE at both high and low elevations (74% and 94% losses, respectively). SWE declines even more steeply in the HighClim scenario with a loss of 90% of SWE above 1200 m (3937 ft) and a loss of 94% of SWE at the 500-1200 meter (1640-3937 ft) elevation zone. Hydrologic impacts indicate that the snowmelt contribution to spring discharge is lost as snowfall converts to rainfall in winter and the remaining snowpack melts earlier. In all but the LowClim scenario, we see an increase in winter flows as a result of these declines in SWE. While the total water storage from SWE is a relatively small proportion of the annual water budget (2.3-10.6%), the loss of snowpack has important implications for the timing of reservoir filling, spring and early summer high elevation soil moisture, forest health, and spring streamflow.

 

Snow Modeling in Brief

In the Willamette River Basin (WRB), most annual precipitation falls between November and March, with snowfall occurring mainly at elevations above about 1200 m (3937 ft). Sub-basins such as the McKenzie, North Santiam, and Middle Fork, whose headwaters contain substantial area above 1200 m (3937 ft), have more snow than those in the Coast range and elsewhere in the WRB.

We simulated the seasonal evolution of the mountain snowpack at a daily timestep within the Willamette Hydrology Model (WHM) portion of Willamette Envision. WHM is a modified version of the HBV model (Seibert, 1997) in which snow is computed using a degree-day model. Melt rate is governed by air temperature in excess of 0° C and moderated by a melt factor. Precipitation is partitioned into rain and snow by incorporating a temperature-based transition “ramp” rather than a single fixed temperature threshold thus allowing for mixed rain-snow events. The model accounts for the effects of canopy interception and snow sublimation from the canopy as a function of leaf area index (LAI), a measure of canopy cover. Last, we included a radiant energy term as a function of LAI, where both convective heat (as a function of air temperature) and radiant energy can affect snowmelt. Snowmelt is constrained by the amount of actual snow available in each IDU, and when snowmelt exceeds the water-holding capacity of the snowpack, melt is routed into the soil.

Analysis Approach

We selected three climate scenarios to examine the effects of climate and changing forest cover on snowpack. As described in the Climate section, the scenarios representing high, medium, and low levels of climate warming are referred to as HighClim, Reference, and LowClim, respectively. For each climate scenario, the WW2100 team examined snowpack across three elevation zones: 500 m (1640 ft) and below, 500-1200 m (1640-3937 ft), and 1200 m (3937 ft) and above. While April 1 SWE is a traditional metric used by streamflow forecasters, we found that under climate warming this metric does not account for snow water equivalent that melts prior to that date. A more hydrologically appropriate metric is the maximum winter snow water equivalent (MaxSWE). We computed MaxSWE for the January-April time period for elevation zones 500-1200 m (1640-3937 ft, or “low elevation snow”) and 1200 m (3937 ft) and above (“high elevation snow”). Because snow cover below 500 m (1640 ft) is only ephemeral and insignificant, we did not analyze changes in snowpack in that zone. Snowpack in individual winters typically varies from year to year, so our temporal analysis examined decadal and 30-year averages of SWE over the 90-year model run. We also analyzed correlations between snowpack, winter temperature, and winter precipitation on a yearly basis for each of the climate scenarios. In addition to the elevation zone analyses of SWE, we examined decadal-averaged SWE for sub-watersheds (HUC-12 level of detail).

Select Findings from Snow Analysis

As temperatures increase in WW2100 future scenarios (2010-2099), snow water equivalent varies in its response to temperature. SWE decreases in both the Reference and HighClim scenario, where temperatures increase 2.3 °C and 4.4 °C from the first to the ninth decade, respectively. However, SWE increases in the LowClim scenario for both low and high elevations because the temperature increase is only 0.05 °C, not enough to shift precipitation from snow to rain. There is also a slight increase in winter precipitation. Spatially, changes in snow cover mainly affect the McKenzie and North Santiam sub-basins, as well as high elevation portions of several other sub-basins (Fig. 1).

Snowpack Trends in the Three WW2100 Climate Scenarios

  • Under the LowClim scenario, snow water equivalent in the high elevation zone there is high interdecadal variability and maximum SWE increases by 41%. In the low elevation zone, there is high decadal variability but no significant increase in SWE. (Figs. 2 and 3).

  • Under the Reference and HighClim scenarios, snow water equivalent in the high elevation zone declines 74% and 90% under the Reference and HighClim scenarios, respectively (Figs. 4 and 5).

  • Snow water equivalent in the low elevation zone declines 94% under both the Reference and HighClim scenarios (Figs. 6 and 7). In the HighClim scenario, low elevation snow essentially disappears by mid-century.

  • Declines in SWE in the Reference and HighClim scenarios are driven by increases in winter temperatures rather than changes in precipitation.

Annual maximum SWE for early, middle and late 21st century decades (Figure by Nolin and Stephens)

Figure 1. Snow cover in early, mid, late decades of the study period for the Reference Case scenario.

Box plots showing decadal changes in January-April maximum snow water equivalent for the LowClim scenario, above 1200 m.

Box plots showing decadal changes in January-April maximum snow water equivalent for the LowClim scenario, 500-1200 m.

Figure 2a-b.  Box plots showing decadal changes in January-April maximum snow water equivalent for the LowClim scenario, above 1200 m or 3937 ft (top) and 500-1200 m or 1640-3937 ft (bottom).

Box plots showing decadal changes in January-April maximum snow water equivalent for the Reference scenario, above 1200 m.

Box plots showing decadal changes in January-April maximum snow water equivalent for the Reference scenario, above 500-1200m.

Figure 3a-b.  Box plots showing decadal changes in January-April maximum snow water equivalent for the Reference Case scenario, above 1200 m or 3937 ft (top) and 500-1200 m or 1640-3937 ft (bottom).

Box plots showing decadal changes in January-April maximum snow water equivalent for the HighClim scenario, above 1200 m.

Box plots showing decadal changes in January-April maximum snow water equivalent for the HighClim scenario, 500-1200 m.

Figure 4a-b.  Box plots showing decadal changes in January-April maximum snow water equivalent for the HighClim scenario, above 1200 m or 3937 ft (top) and 500-1200 m or 1640-3937 ft (bottom).

 

Table 1. Correlations between Jan-Apr Maximum SWE, temperature, and precipitation for the three scenarios. Values with an asterisk are significant at p=-0.05.

  LowClim Reference HighClim
 

>1200 m
(>3937 ft)

500-1200 m
(1640-3937 ft)
>1200 m
(>3937 ft)
500-1200 m
(1640-3937 ft)
>1200 m
(>3937 ft)
500-1200 m
(1640-3937 ft)

T vs. MaxSWE

-0.59* -0.53* -0.46* -0.36* -0.48* -0.38*
P vs. MaxSWE 0.31* 0.22 0.19 0.19 0.18 0.21

Changes in Volumetric Water Storage in Snowpack

We computed the difference in total volumetric water storage in the snowpack using the first and last decades of the model run and combining snow storage in both the high and low elevations zones. The LowClim scenario sees an increase of 324,285 ac-ft (0.40 km3), the Reference scenario sees a decrease of 2,180,818 ac-ft ( 2.70 km3), and the HighClim scenario sees a decrease of 956,642 ac-ft ( 1.17 km3) from the first to the last decade. The larger decline in the Reference scenario is because there is a single outlier year of extremely high snowpack during the first decade of the Reference scenario that doesn’t occur in the other two scenarios.

Because we did not run a counterfactual case controlling for the effects of wildfire, we are not able to tease apart the effects of climate from those of wildfire on snowpack. However, our field measurements indicate that dense, low elevation forests tend to decrease snowpack due to both canopy interception (reducing accumulation on the ground) and thermal effects that lead to faster melt. At the highest elevations, forests are lower density and colder, so canopy interception and thermal effects are lower. In burned areas, our field studies show that decreased canopy increases snow accumulation, but deposition of charred debris on snow leads to earlier snowmelt by several weeks. Thus, we speculate that forest fires will lead to increased snow accumulation but earlier melt. Forest harvest, especially thinning, may allow greater retention of snowpacks, though higher winter temperatures cause considerable declines in total snowpack at all elevations.

Conclusions

Pacific Northwest mountain snowpack is highly temperature sensitive. In recent decades, warm temperature anomalies have led to significant declines in snow water equivalent. Differences between the LowClim, Reference, and HighClim scenarios show that relatively small changes in temperature and precipitation affect both the magnitude and direction of temperature change. In the LowClim scenario, the slight temperature increase is insufficient to convert precipitation from snowfall to rainfall; the 19.5% increase in winter precipitation leads to a 41% increase SWE from the first to the last decade of the 90-year period. In contrast, the Reference and HighClim scenarios see significant increases in winter temperature but no change in winter precipitation, thus driving the large declines in SWE. The SWE decreases are especially substantial at lower elevations, which see a disappearance of nearly all snow. Climate-driven changes in snow hydrology are considerable. Less clear are the impacts of changing forest cover on snowpacks.

Related Links & Publications

  • Cooper, M. G., Nolin, A. W., & Safeeq, M. (2016). Testing the recent snow drought as an analog for climate warming sensitivity of Cascades snowpacks. Environmental Research Letters, 11(8), 084009.

  • Sproles, E. A., T. R. Roth, and A. W. Nolin. (2016). Future Snow? A Spatial-Probabilistic Assessment of the Extraordinarily Low Snowpacks of 2014 and 2015 in the Oregon Cascades, The Cryosphere Discussion, http://dx.doi.org/10.5194/tc-2016-66

  • Nolin, A. W. (2016). Remote sensing of the cryosphere, In The International Encyclopedia of Geography: People, the Earth, Environment, and Technology. D. Richardson, Ed., Wiley and Sons, http://dx.doi.org/10.1002/9781118786352

  • Gleason, K. E. and A. W. Nolin. (2016). Charred forests accelerate snow albedo decay: parameterizing the post-fire radiative forcing on snow for three years following fire, Hydrological Processes, http://dx.doi.org/10.1002/hyp.10897

  • Safeeq, M. S. Shukla, I. Arismendi, G. E. Grant, S. L. Lewis, and A. Nolin. (2015). Influence of winter season climate variability on snow-precipitation ratio in the western United States, International Journal of Climatology, http://dx.doi.org/10.1002/joc.4545

Contributors to WW2100 Snow Research

  • Anne Nolin, OSU College of Earth, Ocean, and Atmospheric Sciences (lead)

  • David Conklin, Oregon Freshwater Simulations

  • Matthew Cooper, MS Student, Geography (Graduate: 2014; now at UCLA Geography)

  • Kelly Gleason, PhD Student, OSU Geography (Graduated: 2015; now at USGS Flagstaff, AZ)

  • Travis Roth, PhD Student, OSU Water Resources Science (Graduated: 2012, now at 

  • Eric Sproles, PhD Student, OSU Geography (Graduated: 2012, now at Centro de Estudios Avanzados en Zonas Áridas, La Serena, Chile)

  • David Turner, OSU Forest Ecosystems and Society

  • Kellie Vache, OSU Biological & Ecological Engineering

References

Seibert, J. (1997) Estimation of parameter uncertainty in the HBV model. Nordic Hydrology, 28 (4/5), 247-262.

 

Web page author: A. Nolin
Last updated: December 2016

Urban Water Use

Willamette River Basin residents and businesses alike depend on a sustainable source of clean water for continued well being and livelihood. To anticipate future urban water demands, the WW2100 economics team developed a modeling component for Willamette Envision that projects residential and nonresidential urban water demand as a function of factors such as water price, income, population, and population density. Demand for each urban area is modeled in aggregate, with models based on empirical economic research studies and data from major urban areas in the basin. As Willamette Envision runs, the estimated water demand is met by diversions of water from surface and groundwater sources, consistent with existing municipal water rights. WW2100 water demand modeling suggest an increase in urban water use within the basin over the century, mainly due to population growth. The projections indicate that per capita consumption, which has been declining for the past 20 years because of price increases and a range of urban water conservation programs, will stabilize at between 80 and 100 gallons per day, before rising gradually due to growth in per capita income.

 

 

Urban Water Use Modeling in Brief

Water in urban areas of the Willamette Basin is put to residential, commercial, and industrial uses. The amount used will depend on a range of factors including population, price, and income, as well as urban population density. This web page provides a brief introduction to urban water demand modeling in Willamette Envision; for a more detailed description, refer to Jaeger et al., 2016.

The urban water demand component of Willamette Envision consists of models of residential and nonresidential urban water demand for the Portland Metropolitan Area, Salem, Corvallis, and Eugene/Springfield, as well as a separate model for smaller urban areas. We selected model variables based on a review of the economics literature on urban water demand and on the need to use variables that could be forecasted over the entire study period as exogenous drivers (income and population growth) or as variables generated within the Willamette Envision framework (population density). The economics literature suggests that a water demand function must include marginal price of water, pricing structure, and income (Olmstead et al., 2007; Olmstead, 2009; Olmstead, 2010; Bell & Griffin, 2011; Mansur & Olmstead, 2012). Given the specific forecasting needs of the urban water component for WW2100, we also included population and population density in the model. We collected the most current information available (at the time the project was begun) on each of these variables for Portland, Salem, Corvallis, Eugene, and Springfield. We used coefficients from the literature and the averages of water quantity, price, income, population, and density for the five cities to calibrate a log-linear model and calculate the intercept term corresponding to the baseline averages. Finally, we adjusted the demand models to reflect seasonal variations in demand. Our baseline scenario, called the Reference Case (1) assumes initial prices that are commensurate with the basin’s major cities in 2010, (2) includes price increases comparable to what occurred on average from 2010-2015, and (3) assumes a 1.5% annual increase from 2016-2025 (in real, inflation-adjusted dollars), in recognition of the existing backlog of infrastructure needs and system maintenance and upgrades expected for western Oregon. After the year 2025, the Reference Case assumes prices remain constant in inflation-adjusted terms for a given size city. For more information about urban demand modeling in Willamette Envision refer to Jaeger et al. (2016).

Additional Modeling Details:

  • Many Willamette Basin metropolitan areas have multiple water providers that divert water from multiple sources. Many water providers also buy and sell water between municipalities. Willamette Envision does not model these complex arrangements and instead models water demand for each metro area in aggregate. We used water-use reports from recent years to apportion urban water demand among water rights that have been used most by each metro area. As demand grows, the model allows for additional water to be made available by diverting water from the Willamette mainstem.

  • Water supply for the Portland Metro area also includes water sources that are outside of the Willamette Basin including Bull Run (the major source for the city of Portland) and Barney and Scoggins Reservoirs (that serves Metro area customers in the Tualatin River Basin). In the case of Bull Run, we have restricted our model so that no more than two-thirds of total Portland Metro water demand comes from this dominant water right (based on recent water use data). However, the Bull Run water right has a maximum legal rate of 636 cfs, which is 50% above the highest rate of withdrawal in the reference run model (in 2100) with this restriction in place. In addition, our model does not include the mid-Willamette water supply source currently under development by the Tualatin Valley Water District. That source, to be completed in 2026, will have a capacity of 100 million gallons per day, or more than 36,000 acre-feet during the four peak summer months.

  • We adjust residential demand for seasonality by decomposing daily water use into outdoor and indoor use components, based on 24 years of daily data from Portland Water Bureau. Total predicted yearly water demand from above is divided by 365 to obtain daily use, and then multiplied by indoor and outdoor fractions to reflect seasonality. Water demands in rural residential zones, relying on groundwater, is also included in our model. It is predicted using the cost of pumping as a measure of the price of water, the population of the rural-residential area, income per household, and population density.

Select Findings from Urban Water Demand Analysis

Water Demand

  • The demand model produces an estimate of the total annual urban water demand of about 330,000 ccf/day (272 million gallons) in 2015, or 305,000 acre-feet per year. Model projections show these levels rising in coming decades for the entire basin, and especially for the Portland Metro Area, mainly due to population growth (Fig. 1).

  • Consumption per capita will stabilize at between 80 and 100 gallons per person per day, before rising gradually due to growth in per capita income (Fig. 2).

  • If urban water prices throughout the basin were 25% higher than in our Reference Case scenario, urban water demand would be 12% lower. For a 50% price hike, or a 75% price increase, the reductions in urban water demand would be 25% and 37%, respectively (Fig. 3). With these price increases, water consumption in the Portland Metro area would be expected to decline to about 70, 62, and 55 gallons per person per day, respectively.

  • In an alternative scenario with higher population growth than in the Reference Case scenario (called HighPop), urban water demand increases by almost 20% by 2030, 36% by 2060, and almost 50% by the end of the century relative to baseline projections.

  • In an alternative scenario in which income is assumed to remain constant (called NoIncGrowth), basinwide urban water demand is 3.7% lower than in the Reference Case scenario by 2030, 9% lower by 2060, and almost 14% lower by the end of the century.

  • We also considered a scenario in which both income and population are kept constant (called NoGrow). Compared to the Reference Case scenario, basinwide urban water demand is 24% lower by 2030, 44% lower by 2060, and almost 59% lower by the end of the century.

Projected basinwide water demand.

Figure 1. Projected basinwide water demand.

 

Projected per capita water demand.

Figure 2. Projected per capita water demand.

 

Projected basinwide water use for different price paths.

Figure 3. Projected basinwide water demand for different price paths.

Metro water use per capita, with additional price increases.

Figure 4. Projected per capita water demand for Metro under different price paths.

 

Expenditures on Water

  • Expenditures on water represent a small share (less than 0.5%) of household income, and this share is projected to decrease over time (Fig. 4). For low-income households, however, the cost of water will represent a more significant share of income.

  • Price increases of 25% to 75% have little effect on expenditures as a share of income because the rise in price will have an offsetting effect on consumption, resulting in a small effect on total expenditures (Fig. 5).

Expenditures on water as a share of income.

Figure 5. Expenditures on water as a share of income.

 

Expenditures on water as a share of income for different price increases over the Reference scenario.

Figure 6. Expenditures on water as a share of income for different price increases over the Reference Case scenario.

Net Change in Irrigation with Urban Expansion

As cities in the basin grow, they will to some extent displace agriculture as they expand, and this will include displacing some irrigated lands. Hence, reduced irrigation could occur as a result of urban expansion and displacement of these irrigated areas.

  • Our model predicts an increase in urban water use (summer outdoor) of 36,800 acre-feet for the six largest metropolitan areas in the basin.

  • Due to the land-use changes accompanying growth, displacement of irrigated farmland offsets forty percent of this increase. The net increase is estimated to be 21,400 acre-feet.

  • These effects vary significantly across cities in the basin, depending on the extent and direction of urban expansion, as well as on the proximity of the city boundaries to surface irrigated farmlands.

 

Conclusions

Urban water use will increase significantly due to growth in population and rising income per household. Price increases in recent years, and those that are anticipated in the coming decade, will curb urban water demand to a significant degree. However, because a large portion of urban water in the basin comes from outside sources (primarily the Bull Run watershed), and because most water is used indoors and returns to the surface water sources from where it originated, the urban consumptive use of in-basin surface water is a small fraction (only 7%) of total urban water use.

Notes, Related Publications & Links

  • Jaeger W.K, Plantinga A.J., Langpap C., Bigelow DP, Moore KM.  2017.  Water, Economics, and Climate Change in the Willamette Basin, Oregon. OSU Extension Service Publication EM 9157.

  • Note: Our projections for both urban and agricultural water use are based on the set of behavioral economic models described here and elsewhere. These models reflect and are derived from economic theory; they are spatially and temporally explicit, and take into account many factors, including the following: water price, household income, population, population density, water delivery costs, land values and farm profits, land use change, crop choice, planting date, water availability across space and time, shifts in seasonality of crop growth due to climate change, daily determination of crop evapotranspiration, urban displacement of farmlands, and utilization rates for irrigation water rights. The 2015 Statewide Long-Term Water Demand Forecast Report, prepared by the consulting firm MWH for Oregon’s Water Resources Department, also makes estimates of future water demand in Oregon. Their methodologies differs from ours in several ways. In the case of agriculture, the MWH report draws on USGS estimates (which in turn are based on USDA Census of Agriculture data) for irrigated acres by county and by crop. Irrigation water demand is then estimated based on Net Irrigation Water Requirements, which are then adjusted to reflect the effects of climate change. In the case of urban water demand forecasting, MWH relied on existing Water Management and Conservation Plans (WMCP) developed by various city governments, and these were then adjusted in proportion to estimated population growth. Changes in per capita demand were estimated by MWH from 50 of the most recent WMCPs from communities across Oregon.

Contributors to WW2100 Urban Water Use Modeling

  • Christian Langpap, OSU Applied Economics (lead)

  • William Jaeger, OSU Applied Economics

  • David Conklin, Oregon Freshwater Simulations

References

Bell, D. R., & Griffin, R. C. (2011). Urban water demand with periodic error correction. Land Economics, 87(3), 528-544.

Jaeger et. al. (2016). Scarcity amid abundance: Water, climate change, and the policy role of regional system models. Manuscript in preparation.

Mansur, E. T., & Olmstead, S. M. (2012). The value of scarce water: Measuring the inefficiency of municipal regulations. Journal of Urban Economics, 71(3), 332-346.

Olmstead, S. M. (2009). Reduced-form versus structural models of water demand under nonlinear prices. Journal of Business & Economic Statistics, 27(1), 84-94.

Olmstead, S. M. (2010). The economics of managing scarce water resources. Review of Environmental Economics and Policy, 4(2), 179-198.

Olmstead, S. M., Hanemann, W. M., & Stavins, R. N. (2007). Water demand under alternative price structures. Journal of Environmental Economics and Management, 54(2), 181-198.

 

Web page authors: C. Langpap, W. Jaeger
Last updated: September 2016

Agricultural Land & Water Use

The Willamette Valley is home to a large agriculture sector that sustains an important part of the Oregon economy. The water used in producing both irrigated and nonirrigated crops in the valley’s diverse agricultural system depends on several factors, including crop and soil type, precipitation and temperature, water rights, costs, and other factors. To understand and anticipate long-term water-use trends within the region’s agriculture industry, economic models were developed to describe the location, timing, crop choices, and irrigation decisions involved in agriculture in the Willamette River Basin (WRB). These economic models characterize land-use decisions based on economic returns to different land uses, crop choices that reflect economic returns to different crops, irrigation decisions that reflect the economics behind utilizing existing water rights, and the economics behind acquiring additional water rights, based on a range of factors that vary by location and year. These models generate estimates of daily water quantities expected to be used at each location in each subbasin in the WRB in future decades, for both surface water and groundwater. These projections show a small decline of 8% in both farmland acres overall, and also for surface and groundwater irrigated acres (a 5% reduction). These trends are mainly due to the expansion of urban land development that displace agriculture. Climate change and the resulting warmer summer temperatures are not found to have a significant effect on crop water requirements. Indeed, warmer temperatures are found to lead to earlier planting dates, which in turn give rise to earlier start and finish dates for irrigation. This means that a larger proportion of crop water demand takes place earlier in the season, when average temperatures are lower and precipitation is higher.

 

 

Agricultural Land and Water Use Methods in Brief

Agricultural water use depends on a range of factors. These include (1) the land area on which agriculture is practiced, (2) the choice of crops, (3) whether irrigation water rights are held, the availability of water from a given source, and the usage rates of those irrigation water rights. Water is consumed by plants on a daily basis, whether irrigated or not. For rain-fed agriculture crops, water demand will reduce the amount of water in soils, in groundwater reserves, and the amounts seeping to streams; for surface irrigation, the crop water demand will involve diverting water from surface flows when soil moisture is insufficient to meet crop water needs.

Agricultural Modeling

The agricultural water use models consist of several interconnected economic models including the limitations imposed by water rights and dynamic models of agricultural evapotranspiration and evolving soil moisture.  The models operate at the scale of the Willamette Envision’s map polygons, which are called Integrated Decision Units (IDUs). The four economic models determine: (1) which lands are put to agricultural uses, (2) which crops are grown on a given parcel of land, (3) whether the parcel of land has or will have an irrigation water right, and (4) whether the irrigation water right is used in a given year. These four models interact with the agricultural evapotranspiration model (crop water demand) that simulates daily evapotranspiration (ET) as a dynamic function of climate, land cover, soil water, and growth stage of each crop, from planting date, to ‘greening up,’ to harvest and dormancy. Soil water will vary as a function of precipitation, crop cover, irrigation, and seepage. These four models also interact with water rights that may impose limits on the timing and quantities of water available for irrigation. Farmland transitioned in or out of agriculture versus developed or forest land uses is described in the land use change section. This page provides a brief overview of agricultural modeling in Willamette Envision.  For a more complete explanation, refer to refer to Kalinin (2013) and Jaeger et al. (in prep).

In a given year where a particular land parcel is assigned to the agricultural land use, farmer decisions are modeled to simulate crop and irrigation decisions. Irrigation is only possible on IDUs with existing irrigation water rights. These initial decisions are then followed by daily decisions related to planting and harvesting, and (possibly) applying irrigation water. The availability of irrigation water is also subject to regulatory shutoffs in accordance with the prior appropriations seniority system under state law (discussed below).

The combination of decisions, choices, actions, and responses to other factors produces a unique pattern of crop water use, irrigation diversions, soil moisture, and groundwater contributions. It also influences economic returns to farming (annual farmland rent) at the parcel level. To the extent that irrigation water is shut off by regulators, current and expected future annual farmland rent is reduced.

The crop choice model estimates the probability of growing each of seven crop types or groups for the modeled year. The empirical model is estimated at the parcel level based on observed cropping patterns in recent years. The model estimates the crop observed as a function of IDU characteristics including soil quality (land capability class), elevation, and the presence of an irrigation water right, as well as varying attributes, crop prices and expected water availability (for those IDUs with irrigation water rights). Given the estimated probabilities for each IDU, the simulation models determine the crop for each IDU in each year with a random draw reflecting these estimated probabilities. No evidence of crop choices being correlated across years (i.e., a crop rotation schedule) were found in the data or in interviews with farmers or agricultural extension personnel. The resulting modeled values are interpreted as the probabilities for each crop to be grown. For perennial crops (orchards, vineyards, tree crops), a fixed set of IDUs is permanently assigned.

The model of irrigation decisions is based on a detailed farmer survey conducted for WW2100 by the USDA National Agricultural Statistics Service (Kalinin, 2013). Data on a six-year history of irrigation and cropping practices for a sample of fields from 530 randomly selected farmers was collected. From this, an irrigation decision model was estimated to represent the probability of irrigating a specific parcel as a function of parcel attributes (e.g., soil type, elevation), and seasonal factors (e.g., June precipitation).

The economic rent or annual profit from farming a given piece of land can play an important role in farm decisions to plant a crop, irrigate, or transition out of farming. Our estimate of farmland rent takes a “Ricardian” approach that is common in models of the economic returns to agriculture (Mendelsohn et al., 1994). Land value is assumed to equal the net present value of future rents from putting the land to its highest value use; as a result, we expect to see variation in land values and annual rents due to characteristics of the land that would influence agricultural productivity such as soil quality and precipitation or irrigation water rights. Similar to the hedonic model of crop choice, here we decompose the farmland rents associated with factors affecting agricultural productivity (see Kalinin, 2013 for more detail).

Agricultural lands in the WRB that currently do not have irrigation water rights may benefit from opportunities to acquire new water rights under federal contracts for stored water at one of the US Army Corps of Engineers reservoirs. The profitability of a new contract for stored water will depend on a comparison of the irrigation benefits (higher yields and wider range of crop choices) and the additional costs (capital investments in infrastructure, labor, and energy costs). For farmlands with existing irrigation water rights, these costs and benefits are already incorporated into the WW2100 estimates of farmland rent (annual profits) by soil class.

For new contract water rights, we would expect the irrigation premium to be the same as for existing irrigation water rights if the costs of irrigating are similar to the average costs for existing surface and groundwater rights. In the case of new water rights from stored water, we expect the costs to be somewhat higher due to a) the fee paid to the Bureau of Reclamation for the water contract, b) the extra cost for mainline conveyance to bring the water from a below-reservoir tributary to the field, and c) the extra lift required. Whether a new irrigation water right is attractive to a farmer depends on its profitability. Farmlands without irrigation water rights are given the opportunity to acquire new irrigation water rights based on stored water in the “New Irrigation Scenario,” provided that there is an economic justification for doing so.

Water Rights Modeling

Irrigation water demands compete with other water uses, include instream water rights. Because irrigation and instream water rights have the greatest potential to compete directly, we include a description of these water rights and our modeling of them here.

Water is allocated in the WRB according to Oregon water law, which operates according to the “prior appropriations doctrine” used in Oregon and most western states (Getches et al., 2015). The water rights system allocates water according to water right priority date (first date of use historically). Under Oregon law, all water is publicly owned. Water rights certified by the state are defined in terms of the timing of use, the maximum rate of diversion, and the annual volume allowed under the water right. When conflicts arise due to shortage, the more senior water right is given priority, while more junior water rights are required to curtail their water use if it conflicts with the senior water right holder. Water rights may be transferred between points of use under Oregon law when transactions are arranged by parties and approved by the OWRD (Amos, 2008), for example an irrigation right transferred from one farm to another.

Willamette Envision mimics this process: it takes account of the demand or request for water at a given point of diversion (POD) on a given day (from a farm, city, rural residential water user, or instream flow water right), and it evaluates the availability of water from the relevant streams and groundwater source. If there is sufficient water available, it withdraws water to satisfy the demand. If there is insufficient water to meet the needs of an existing water right, the request is denied. At the same time the model determines whether there is a junior water right in the same river reach or any upstream reaches that could be curtailed to make additional water available to satisfy the senior water right. A similar procedure is followed to satisfy instream water rights by protecting flows in streams where such water rights exist. The model includes instream water rights implemented as of 2010. When more than one instream water right applies at the same time to the same reach, the water rights model applies both water requirements. If an instream water right is “senior” to an irrigation water right, the irrigator may be shut off is there is insufficient water to meet both demands. Willamette Envision includes more than 15,000 irrigation water rights, 1,000 municipal water rights, and 90 instream water rights.

Select Findings from Agricultural Analysis

Agricultural Water Use

  • The agricultural land use model estimates that total farmland will decline gradually in coming decades, by about 8% by the year 2100. Irrigated lands are projected to decline by 5% (Fig. 1).

Agricultural lands in the WRB.

Figure 1. Projected agricultural lands in the WRB for the Reference Case scenario.

 

  • Cropping patterns are expected to remain stable in coming decades for the largest crops (by acreage). Given the very large number of crops grown in the WRB, the data suggest that possible increases or decreases in the acres planted for one or several crops is unlikely to have a significant effect on total crop water use (Fig. 2).

Projected cropping patterns in the WRB.

Figure 2. Projected cropping patterns in the WRB for the Reference Case scenario.

  • The acreage irrigated in the WRB in any given year represents about 17% of the total agricultural land area of 1.5 million acres, with about half of this being surface water irrigated. There is significant year-to-year variation in the crops and acreage irrigated (Fig. 3). Diverted Irrigation amounts vary significantly year to year, but are estimated to average 435,000 ac-ft initially while declining by about 15% late in the century in the Reference Case scenario.

Irrigated crops, by acres planted.

Figure 3. Irrigated crops, by acres planted, for the Reference Case scenario.

  • Agricultural land values vary due to differences in soil type, elevation, average temperature, and precipitation, as well as with ownership of an irrigation water right (Fig. 4).  

 

WW2100 agricultural land values.

Figure 4. Agricultural land values.

  • In any given year there are a number of irrigation water rights that are shut off by regulators during the growing season due to a lack of available surface water. Consistent with Oregon water law, relatively junior water right holders may be forced to curtail irrigation to ensure the availability of water for more senior water right holders. These conflicts between water rights can involve instream or other surface irrigation water rights. For the Reference Case scenario, our model results suggest a surprising decline in the number of shutoffs in future decades. This is occurring in the model because climate change gives rise to warmer spring temperatures which begin to encourage earlier planting dates; with earlier planting comes an earlier start (and end) to irrigation. For some crops in future decades, and in particular locations, this will mean that some farmers will have completed their irrigation by the time that they would have (previously) been shut off (Figs. 5 and 6).  The model suggests a reduction of 10-30%.

Seasonal distribution of irrigation requests.

Figure 5. Seasonal distribution of irrgation requests for the Reference Case scenario.

Projected changes in irrigation shutoffs, Reference and HighClim scenarios.

Figure 6. Projected changes in irrigation shutoffs - Reference Case and HighClim scenarios.

  • For a range of alternative scenarios, the impact of varied assumptions about external factors (high population growth, high climate change, low climate change), and changes in assumptions related to sensitivity analysis (high irrigation, low irrigation), and combinations of these modified assumptions (Worst Case and Extreme scenarios), produce changes in the level and trajectory of irrigation shutoffs. The High Climate Change (HighClim) scenario produces a similar reduction in irrigation shutoffs as for the Reference Case (Fig. 6). For the other scenarios, the relative levels of irrigation shutoffs are consistent with what would be expected under these alternative assumptions (e.g., higher levels of shutoffs for “high irrigation” and for “worst case” scenarios).  

  • When non-irrigated farmlands are given the option of acquiring new irrigation water rights tied to federal stored water contracts, some previously non-irrigated parcels acquire new water rights in our model. However, because of (1) the high additional costs of conveyance to move water to a farmer’s field from one of the tributaries below a federal reservoirs, and (2) the relatively modest incremental profits or increased net revenue that would be expected from irrigation, the adoption of new irrigation from stored water rights is found to be profitable for only a small number of acres (less than 8,000). Even when making optimistic assumptions about the low costs of conveyance, less than 30,000 acres of land adopt new irrigation water rights (Fig. 7).

Locations of new irrigation water rights with low conveyance cost assumptions.

Figure 7. Location of new irrigation water rights, with low conveyance cost assumptions.

 

Notes, Related Links & Publications

  • Jaeger W.K, Plantinga A.J., Langpap C., Bigelow DP, Moore KM.  2017.  Water, Economics, and Climate Change in the Willamette Basin, Oregon. OSU Extension Service Publication EM 9157. https://catalog.extension.oregonstate.edu/em9157

  • Jaeger et. al. (2016). Scarcity amid abundance: Water, climate change, and insights from a coupled human-natural systems model. Manuscript in preparation.

  • Kalinin, A. (2013). Right as Rain? The Value of Water in Willamette Valley Agriculture (MS Thesis). Oregon State University, Corvallis, Ore. http://hdl.handle.net/1957/42123

  • Jaeger, W. (2014, October 8). Modeling the Human Side of Water Scarcity in the Willamette Basin. WW2100 Recorded Webinar. https://media.oregonstate.edu/media/t/0_d5bbiufd  

  • Note: Our projections for both urban and agricultural water use are based on the set of behavioral economic models described here and elsewhere. These models reflect and are derived from economic theory; they are spatially and temporally explicit, and take into account many factors, including the following: water price, household income, population, population density, water delivery costs, land values and farm profits, land use change, crop choice, planting date, water availability across space and time, shifts in seasonality of crop growth due to climate change, daily determination of crop evapotranspiration, urban displacement of farmlands, and utilization rates for irrigation water rights. The 2015 Statewide Long-Term Water Demand Forecast Report, prepared by the consulting firm MWH for Oregon’s Water Resources Department, also makes estimates of future water demand in Oregon. Their methodologies differs from ours in several ways. In the case of agriculture, the MWH report draws on USGS estimates (which in turn are based on USDA Census of Agriculture data) for irrigated acres by county and by crop. Irrigation water demand is then estimated based on Net Irrigation Water Requirements, which are then adjusted to reflect the effects of climate change. In the case of urban water demand forecasting, MWH relied on existing Water Management and Conservation Plans (WMCP) developed by various city governments, and these were then adjusted in proportion to estimated population growth. Changes in per capita demand were estimated by MWH from 50 of the most recent WMCPs from communities across Oregon.

Contributors to WW2100 Agricultural Land and Water Use Modeling

  • William Jaeger, OSU Applied Economics (lead)
  • Alexey Kalinin, OSU Applied Economics (completed MS 2013, now a PhD student at the University of Wisconsin)
  • Dan Bigelow, OSU Applied Economics (completed PhD 2015)
  • Kathleen Moore, OSU Geography (completed PhD 2015; now a post-doctoral researcher, OSU Applied Economics)
  • Cynthia Schwartz, OSU Biological and Ecological Engineering
  • David Conklin, Oregon Freshwater Simulations

References

Amos, A. (2008). Freshwater Conservation in the Context of Energy and Climate Policy: Assessing Progress and Identifying Challenges in Oregon and the Western United States. University of Denver Water Law Review 12(1).

Getches, David, Sandi Zellmer, and Adell Amos. (2015). Water Law in a Nutshell, 5th. Minneapolis, Minn: West Academic.

Jaeger et. al. (2016). Scarcity amid abundance: Water, climate change, and the policy role of regional system models. Manuscript in preparation.

Kalinin, A. (2013). Right as Rain? The Value of Water in Willamette Valley Agriculture (MS thesis). Oregon State University, Corvallis, Ore. http://hdl.handle.net/1957/42123

Mendelsohn, R., Nordhaus, W. D., & Shaw, D. (1994). The impact of global warming on agriculture: a Ricardian analysis. The American Economic Review, 753-771.

 

Web page author: W. Jaeger
Last updated: September 2016

Hydrology

The goal of the WW2100 hydrologic modeling team was to develop a hydrologic model that could capture potential effects of long term changes in climate, land cover, and water use on the hydrology of the Willamette River Basin (WRB). To do this, we developed a modeling component for Willamette Envision called the Willamette Hydrology Model (WHM). WHM translates daily values of meteorological input (including precipitation, air temperature, wind speed, and radiation) into estimates of soil moisture and snowpack across the landscape, and daily average streamflow at locations throughout the Willamette Envision stream network. Importantly, WHM integrates with human systems by simulating operations of the 13 federal reservoirs that are a key feature of the Willamette system, and by simulating water diversions, including constraints imposed by Oregon water law.

We used results from the hydrologic model to develop a water budget of the annual water cycle in the WRB and explore how the water budget might respond to climate and demographic changes over the 21st century. The water budget illustrates several key features of the Willamette hydrologic system, including:

  • The highly seasonal nature of precipitation - more than 75% of annual precipitation falls between November and May.

  • The importance of natural and built reservoirs in sustaining summer flows.

  • The small size of human, out of stream water use, relative to the total amount of water moving through system annually.

  • The relatively small role that snowpack plays in the basinwide water budget; the Willamette is a rain-dominated hydrologic system.

  • The important role of upland forests as water users. Forests cover over 70% of the basin, extensive changes in forest land cover affect the overall water budget by changing evapotranspiration.

  • The proximity of river flows in late summer to minimum environmental flow requirements.

Hydrology Modeling in Brief

Within Willamette Envision, we model the storage and flux of water from rain or snow, into soils, groundwater, and streams using a sub-model developed for the project called the Willamette Hydrology Model (WHM). WHM is, in part, based on the widely-used rainfall-runoff model called HBV (Bergström and Singh 1995; Bergstrom et al., 2001; Seibert, 1997). For a more detailed explanation of the hydrologic modeling framework concept, refer to Vache et al. (in review).

WHM translates daily values of meteorological input (including precipitation, air temperature, wind speed, and radiation) into a spatially distributed estimate of water storage and release. It is run on a daily timestep over the full 90-year WW2100 modeling timeframe, and results in a dynamic estimate of the response of the hydrology to the evolving landscape. The hydrologic model is comprised of four overall elements describing key features of the system.

  • The mountain snowpack - Each winter, snow accumulates in the higher elevations of the Willamette River Basin (WRB). This natural reservoir serves to store a proportion of the winter precipitation, releasing into streams (and reservoirs) during the spring. We simulate the seasonal evolution of the mountain snowpack with a hybrid approach that includes the influence of both air temperature and radiation. The temperature- and radiation-driven melt depends directly on vegetation, so that the snowpack changes as forest disturbance and growth occurs over the scenario timeframe.

  • Watershed runoff - Incoming precipitation and snowmelt are stored within a set of conceptual reservoirs representing soil and groundwater (Fig. 1). WHM defines the spatial distribution of those reservoirs based primarily on a set of approximately 9000 sub-watersheds, defined by the National Hydrography Dataset (NHD). Water is released from the reservoirs based on algorithms developed as part of the HBV model (Bergström and Singh 1995; Bergstrom et al., 2001; Seibert, 1997). Biophysical processes such as evapotranspiration respond to changes in land cover simulated by the forest and human systems models.

  • Instream routing and reservoir storage - WHM uses a kinematic wave approach to simulate the flow of water within the stream network. The spatial pattern of the network was taken from NHD, and allows the model to estimate stream discharge throughout the watershed. Manmade reservoirs are a key feature of the Willamette river system, and WHM simulates operation of the 13 largest reservoirs – those that are managed by the U.S. Army Corp of Engineers (USACE) as the Willamette Project. Refer to the reservoir operations page for more details about reservoir modeling.

  • Water Allocation and water use - The use of water by human society is the fourth key feature of the hydrology of the Willamette. WHM models the movement of water through the stream network, while also allowing water to be added or removed at specific points in accordance with Oregon water law. Human water demand is estimated in the WW2100 economic models as the outcome of household and farm demand relationships. Refer to the agricultural land and water use and urban water use pages for more information about these models.

Diagram of conceptual reservoirs and fluxes modeled with the Willamette Hydrology Model.

Figure 1Hydrologic modeling within Willamette Envision involves movement of water through a set of conceptual reservoirs simulating soil and groundwater (diagram by K. Vache).

Evapotranspiration

Willamette Envision models both biophysical and human aspects of water use. The primary biophysical use modeled is evapotranspiration (ET) — water movement from soil and plants into the atmosphere. ET is calculated on a daily basis for all modeling polygons and responds to changes in landcover modeled by the forest and human systems modeling components. ET is modeled as follows:

  • Forest (~70% of the basin land area in 2010 starting conditions) - For forested lands, WHM models ET using a Penman-Monteith expression that includes both transpiration from vegetation and soil evaporation. The Penman-Monteith expression includes vegetation canopy, represented by leaf area index (LAI), as an independent variable. Thus, forest areas respond to changes in canopy cover simulated by the forest dynamics models. For example, as the forest in a modeling polygon matures, leaf area index (LAI) rises, which leads to a higher ET. When a fire occurs, the LAI decreases to almost zero. Refer to Turner et al. (2016) for more details about modeled vegetation shifts and modeling ET in the Willamette upland forests. Some forest IDUs (about 2% of basin area) were left out of the state-and-transition model due to gaps in the initial condition data. Those forest IDUs are modeled for ET using Penman-Monteith, an LAI of 1, and a canopy height of 10 meters.
  • Agricultural lands (~22% of the basin land area in 2010) - On agricultural lands, modeling of ET takes into account crop type and growth stage, and augmentation of soil moisture due to irrigation. The sequence for a modeling polygon is as follows. First, the human systems modeling components set the crop type and determine whether the land will be irrigated that year. Next, at a daily timestep, WHM determines crop growth stage and water requirements. The model then estimates actual crop water use (ET) by taking into account the amount of water available in the soil. Soil water can come from natural sources (e.g., precipitation) or it can be supplemented by irrigation if water is available (as determined by the water rights model). Modeling of crop water demand and ET is based on the crop cover approach as described in the Food and Agriculture Organization (FAO) Irrigation and Drainage Paper 56 (Allen, Pereira, Raes, & Smith, 1998) and further developed by Allen and Robison (2007). Refer to Jaeger et al. (in prep) for more details. 
  • Urban and other non-forested, non-agricultural lands (~8% of the basin land area in 2010) - Elsewhere, WHM approximates ET using a Penman-Monteith expression using a LAI of 1.0, and a canopy height of 10 meters, that does not change. In urban areas (~5% of the basin land area in 2010) modeling of ET also takes into account outdoor water use for lawns and gardens. Municipal water use is modeled by the human systems models as a unit for each urban growth area. A fraction of the water diverted for municipal use is added to ET. This fraction varies seasonally so that it is very small in winter and higher in summer when outdoor water use peaks. 

Model Calibration

The rainfall-runoff model within WHM has nine calibration parameters related to snowfall, runoff, and percolation. Calibration of these parameters affects the flux between the conceptual reservoirs shown in Figure 1. We used the Parameter Estimation program, PEST, to identify sets of the 9 parameter values which produce good correlations between modeled and measured datasets. The calibration period was 1980-1994 and we used the following measured data sets in the calibration process: USGS stream gage records, NRNI synthetic flow data, Oregon SNOTEL snow survey records, and measured inflow data for federal reservoirs. We ran the model for the calibration period using meteorological forcings representing simulated historical climate conditions from the MIROC5 global climate model (MACAv1-METDATA).

We divided the WRB into a number of sub-basins for calibration purposes, ultimately using 14 different sets of parameter values in different parts of the WRB. Thirteen of the parameter sets were produced by Oregon Freshwater Simulations in 2016; one parameter set was taken from prior calibration work by Eric Watson and Heejun Chang at Portland State University in 2015. Our use of PEST was an adaptation and refinement of the methods used by Watson and Chang (PSU) in 2015.

The main analysis steps within PEST are as follows: (1) PEST selects a set of parameter values, (2) it runs the WHM model, and (3) it calculates a value representing the divergence of the simulation results from the historical stream gage records. This process is repeated with different sets of parameter values in a systematic exploration of the parameter space. The process terminates when successive adjustments to the parameter values fail to reduce the divergence by a specified amount. The model may exhibit equifinality: different sets of parameter values may produce equally good simulation results.

Accurate simulation of the inflows to the WRB reservoirs is important to the success of the WW2100 model as a whole, so we identified nine reservoir drainages to be individually calibrated using PEST as the first step in our process. Parameter values for the remaining parts of the WRB were selected using a variety of methods in subsequent steps. For a more detailed description of model calibration, refer to Jaeger et al (in prep).

Because our focus in WW2100 was on water scarcity, calibration focused on low flows and reservoir inflows. The model was less able to accurately predict high flows, and users should use caution when making interpretations about flood events and winter peak flows.

Model Limitations

As of summer 2016, Willamette Envision does not include a detailed groundwater model and instead relies on the simpler approach of a conceptual groundwater reservoir that is part of HBV, and includes a calibration parameter, which represents groundwater recharge. Because of the simplified groundwater model, we do not model water scarcity for groundwater withdrawals. We simulate water withdrawals from groundwater, but the model does not impose a specific limit on them.

In addition, we do not model potential future changes in groundwater supplied by mountain springs in the High Cascades. Instead, we simulate springflow by adding constant discharge to High Cascades catchments that reflect measured spring flows (Jefferson et al., 2007; Grant & Lewis, 2016). The addition of High Cascades groundwater is held constant throughout the simulations. This assumption is based on measured flows in spring-fed mountain sub-basins.

As of summer 2016, Willamette Envision does not model water quality or water temperature. We are developing an energy balance stream temperature model and hope to incorporate it into future versions of Willamette Envision. WW2100 did include some offline field measurements and modeling of the potential effects of increased water temperature on mainstem fish population. Read about that analysis on the fish and stream temperature section of this website.

Water Budget Calculations

One of our goals for the hydrologic analysis was to determine how the flow of water into and out of the WRB might change in response to changing climate and water demands. WHM allowed us to calculate a water budget for the WRB and estimate how the inputs and outputs to that budget might change over the 21st century. Here we describe the calculations we made to determine the water budget using output from Willamette Envision.

All calculations were performed using daily values that were then averaged over each month of the year. All values were calculated and reported as fluxes (cm3/y per cm2 of the WRB, so cm/y). Most of us are familiar with precipitation as cm/y, but all other inputs, stores, and outputs of water can be reported in the same way. This allowed us to easily compare basinwide precipitation, storage, human diversions of water, and so forth. Monthly, seasonal, and annual fluxes are all reported in the same units of cm/y. Therefore, the annual precipitation can be calculated simply as the sum of the monthly precipitation.

Precipitation is the sum of all rain and snow in the basin divided by the basin area. Evapotranspiration (ET) is all ET in the WRB. The ET related to human uses (municipal and agriculture) is included in the basinwide number and indicates the fraction of total ET based on human uses. Environmental flows are those in the Biological Opinion [U.S. Fish and Wildlife Service, 2008, Appendix B, p. 12, Table 9.2-1] for the Willamette River at Salem. These are the flow objectives for "adequate" and "abundant" water years. We did not include upstream environmental flows because these would be duplicates for the purpose of the water budget. Reservoir storage was calculated as the difference between inflow and outflow each month. Snow was calculated as the difference between snow water equivalent (SWE) on the first of each month and the first of the previous month. Municipal water use was calculated endogenously within Willamette Envision. The ET for municipal uses was calculated as the total water use each month minus the municipal indoor water use, which we estimated each year from Jan. 3 to Feb. 3. Agriculture ET was calculated within Willamette Envision. Storage of water in soil moisture and groundwater was calculated to balance the monthly water budget of the basin. The model does not include evaporation from open water such as reservoirs and lakes.

The seasons “Summer” and “Winter” were chosen to be of the same length of time, six months. No single six-month period uniquely qualifies as “Winter” or “Summer”, but we chose Winter to be defined in the water budget as November 1 through April 30. This aligns approximately with the historical snow storage season. We defined “Summer” as the other six months of the year. This seasonal definition is equivalent to “dry” and “wet” season in the WRB (Chang and Jung, 2010).

Selected Findings

Water Budget

The simulated historical water budget for the WRB is shown in Figure 2 and Table 1 and 2. An interactive version of the figure, called a Sankey diagram, is available online. This interactive version of the Sankey diagram allows users to examine the water budget for every month and season for several different scenarios.

  • Precipitation is 162 cm/y (37.9 million ac-ft) of water averaged over the WRB. This is in agreement with the best available data set, PRISM (NWACSE, 2015) because modeled precipitation was trained using the PRISM precipitation data over the historical period.
  • Snow water equivalent (SWE) accounts for 3.7 cm/y (~875,000 ac-ft, or 2.3% of total annual precipitation) in the simulated historical scenario (also called HistoricRef). Snowfall mainly occurs from November through March. This is certainly an underestimate of total snowfall in the basin, resulting from the method of accounting, which is the sum of monthly values, which are the difference between values on the first day of successive months averaged over the simulated historical period (1950-2010). In reality, each winter month (plus October and April) have significantly more snowfall than the model numbers indicate. However, the “within-month” snow does not include snowfall that subsequently melted within that month. Such within-month snow melt is not considered to contribute to winter season storage and instead it functions like rainfall runoff. Some readers may find that an estimate of 2.3% stored snow for the WRB is small. It may be. We worked to estimate the upper bound on the amount of stored snow. Nearly all precipitation that falls below 1200 m in the basin melts within a few days during winter. Therefore, 1200 m may be considered as an approximate lower limit of the snow storage ‘zone’. Furthermore, snow that falls before November 1 or after April 1 is not usually stored except at the very highest locations of the basin. The WRB receives only 10.6% of its precipitation between Nov. 1 and Apr. 1 above 1200 m. Therefore, 10.6% could be considered an absolute upper maximum on stored snow. However, many years are warmer than average, and so the stored snow line is higher. Furthermore, most years have warm periods in which much snow above 1200 m melts. Consequently, the amount of snow stored in an average winter in the WRB is probably well under 10.6% of annual precipitation.
  • The reservoirs in the simulated historical scenario have net positive storage of water from February through May. During that period, they store an average of 5.1 cm/y of water, which is approximately 1.2 million ac-ft of water. We know that the reservoirs in the Willamette Valley Project have an active storage of 1.6 million ac-ft. However, the reservoirs do not fill every year. Therefore, our simulation agrees reasonably well with the observed storage.

Annual water budget for the simulated historical scenario.

Figure 2. Average yearly WRB water budget for simulated historical scenario (1950-2009). The amount of precipitation in the basin is shown on the left, and outflow of the Willamette River is shown on the right. Water use for irrigation and municipal is an estimate of water use from in-basin sources. The blue line from soil moisture and groundwater includes an estimate of contributions from springs sourcing from the High Cascades aquifer. An interactive version of this diagram is available online where you can view the water budget month by month, and for different modeling scenarios.

  • The biggest storage of water in the model, and certainly in reality as well, is soil moisture and groundwater. Soil moisture and groundwater show net positive storage of water from September through January, totaling 36 cm/y (8.6 million ac-ft). In addition, springs sourcing from the High Cascades aquifer contribute significant discharge to the headwaters of some sub-basins such as the McKenzie. The model simulates this contribution based on measured spring flows (Jefferson et al., 2007; Grant & Lewis, 2016). In model simulations, total discharge from springs sourcing from the High Cascades aquifer is 8.1 cm/y (1.9 million ac-ft).

  • Agriculture extracts 1.2 cm/y (~280,000 ac-ft) of water in the simulated historical scenario. Agriculture receives significantly more water as precipitation, but the amount reported here is for irrigation only. Total municipal uses within the basin use a similar amount of water, 0.91 cm/y (~210,000 ac-ft). However, a significant fraction of municipal water, particularly in the Portland Metro area, is supplied from outside of the Willamette Basin (primarily Bull Run). Municipal use of water from within the WRB is only about 0.52 cm/y (~130,000 ac-ft). Of the water that agriculture and municipal together extract from in-basin sources, approximately 1.0 cm/y (~235,000 ac-ft) evapotranspire. This latter quantity can be considered the amount of water that the agricultural and municipal sectors extract without returning (consume).

  • Environmental flows at Salem require 14.8 cm/y (3.5 million ac-ft) of water in the simulated historical scenario. Environmental flows are the flow objectives for "adequate" and "abundant" water years prescribed by the Biological Opinion [U.S. Fish and Wildlife Service, 2008, Appendix B, p. 12, Table 9.2-1] for the Willamette River at Salem.

  • Outflow of the Willamette River to the Columbia is 100 cm/y (23.5 million ac-ft) of water in the simulated historical scenario. The average discharge of the basin, based on the period of record at Portland, is 102 cm/y (23.9 million ac-ft). Of that, 75% discharges from Nov. 1 to Apr. 30. To put that in perspective, urban water users in the WRB use approximately 100 gal/day/person. If only 20% of the winter discharge of the Willamette River were used for urban supply, it would be enough to supply approximately 32 million people water for one year.

Table 1. Summary of WRB water budget for the simulated historical scenario (1950-2009; also called HistoricRef). All units are cm/y averaged over the basin. Annual totals are shown in the top of each section, and monthly values are shown below that.

Time Precip Δ Snow Δ Reservoirs HighC GW Δ Soil & GW ET Ag Muni Ag+Muni ET Env Flow Outflow
Ann 161.53 0.00 -0.05 8.16 0.00 71.74 1.21 0.52 0.97 14.77 99.82
Oct 12.50 0.00 -1.74 0.68 7.93 3.82 0.01 0.04 0.01 1.73 3.32
Nov 25.27 0.08 -1.28 0.68 16.96 3.75 0.00 0.04 0.00 0.00 6.59
Dec 26.81 1.53 -0.20 0.68 8.84 3.77 0.00 0.04 0.00 0.00 13.70
Jan 22.15 1.40 -0.14 0.68 1.27 3.92 0.00 0.04 0.00 0.00 16.53
Feb 18.41 0.72 1.56 0.68 -1.03 4.34 0.00 0.03 0.00 0.00 13.64
Mar 17.18 -0.52 1.68 0.68 -3.14 6.53 0.01 0.04 0.01 0.00 13.46
Apr 13.09 -0.82 1.23 0.68 -6.16 8.45 0.06 0.04 0.05 3.41 11.22
May 10.52 -1.44 0.68 0.68 -6.88 10.78 0.17 0.04 0.14 2.96 8.21
Jun 6.39 -0.75 -0.02 0.68 -8.63 10.90 0.33 0.05 0.26 2.02 5.72
Jul 1.92 -0.19 -0.28 0.68 -8.02 8.04 0.37 0.06 0.30 1.48 3.21
Aug 2.10 -0.01 -0.47 0.68 -2.71 4.08 0.21 0.06 0.18 1.49 2.05
Sep 5.21 0.00 -1.05 0.68 1.57 3.34 0.04 0.05 0.04 1.67 2.18

 

Table 2. Summary of WRB water budget as simulated for the late 21st century Reference Case scenario (2070-2099). All units are cm/y averaged over the basin. Annual totals are shown in the top of each section, and monthly values are shown below that.

Time Precip Δ Snow Δ Reservoirs HighC GW Δ Soil & GW ET Ag Muni Ag+Muni ET Env Flow Outflow
Ann 171.89 0.00 0.00 8.16 0.00 66.71 1.34 1.12 1.16 14.77 115.97
Winter 137.63 0.29 3.14 4.08 20.52 27.31 0.08 0.47 0.06 3.41 91.76
Summer 34.26 -0.29 -3.14 4.08 -20.52 39.39 1.26 0.66 1.09 11.35 24.22
Oct 9.98 0.00 -1.69 0.68 5.63 3.50 0.01 0.09 0.02 1.73 3.43
Nov 27.64 0.00 -1.04 0.68 19.55 2.93 0.00 0.08 0.00 0.00 7.09
Dec 34.82 0.25 0.32 0.68 12.46 3.10 0.00 0.08 0.00 0.00 19.58
Jan 23.69 0.19 -0.36 0.68 -1.00 3.43 0.00 0.08 0.00 0.00 22.32
Feb 15.85 0.18 1.05 0.68 -3.56 3.92 0.00 0.07 0.00 0.00 15.15
Mar 22.00 0.00 1.95 0.68 0.46 6.01 0.02 0.08 0.01 0.00 14.48
Apr 13.63 -0.33 1.22 0.68 -7.40 7.92 0.07 0.08 0.05 3.41 13.12
May 8.44 -0.23 0.50 0.68 -9.64 10.50 0.28 0.09 0.22 2.96 8.22
Jun 5.42 -0.06 -0.14 0.68 -8.48 9.86 0.42 0.11 0.34 2.02 5.14
Jul 2.22 0.00 -0.32 0.68 -7.01 7.56 0.40 0.13 0.34 1.48 2.90
Aug 2.68 0.00 -0.48 0.68 -2.46 4.33 0.11 0.13 0.13 1.49 2.19
Sep 5.52 0.00 -1.01 0.68 1.44 3.64 0.04 0.10 0.05 1.67 2.34

 

Estimated water budget for August, for the simulated historical scenario.

Estimated water budget for August, for the Reference Case scenario.

Figure 3. August WRB water budget for simulated historical period (top) and 2070 - 2100 in Reference Case scenario (bottom). An interactive version of this is available online. Municipal extraction of water was increases and water use for irrigation declines in the 2070 – 2100 future scenarios. Snowmelt declines as a source of stored water in the 2070 – 2100 futures scenarios.

 

Plots of discharge at Portland for various WW2100 scenarios

Figure 4. Willamette River at Portland. Reference Case scenario. In bottom and right figures, shading is as follows. Light blue = climate effects (Range of HighClim, LowClim, StationaryClim; this is blue-green where overlapping with green; see also shading legend at bottom of page). Red = all scenarios with modeled changes in human systems (population, land use, etc.) Green = all possible scenarios (excludes counterfactual scenarios). The overall behavior of discharge in the Willamette River is similar in the future to what it has been in the past. In the Reference Case scenario, as in all scenarios, discharges are highest in December and January, on average. Flows begin to decline in late winter, and get particularly low in August and September. Average total annual flows in the Willamette are similar over the century to what they are today. Similar graphs of discharge at other locations in the basin are available online. (Plots by R. Haggerty)

Appendix: Shading Notes for Cascade Plots

Explanation of shading in monthly plots in Figure 5.

Legend for shading in cascade plots.

Related Links & Publications

  • Videos from a 2013 OSU graduate course on hydrologic modeling with a focus on Willamette Envision.

  • Vache, K. Bolte, J, Schwartz, C., Sulzman, J. (2016). A flexible framework to support socio-hydrological scenario analysis. Manuscript submitted for publication.

Contributors to Hydrologic Analysis

  • Roy Haggerty, OSU College of Earth, Ocean and Atmospheric Sciences (lead)
  • Kellie Vaché, OSU Biological & Ecological Engineering
  • Heejun Chang, PSU Department of Geography
  • Anne Nolin, OSU College of Earth, Ocean and Atmospheric Science
  • David Conklin, Oregon Freshwater Simulations
  • Maria Wright, OSU Institute for Water and Watersheds

References

Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome, 300(9), D05109.

Allen RG, Walter IA, Elliot RL, J Howell TA, Itenfisu D, Jensen ME, Snyder R. 2005. The ASCE standardized reference evapotranspiration equation. Report No. ASCE and American Society of Civil Engineers.

Bergström, S., Carlsson, B., Gardelin, M., Lindström, G., Pettersson, A., & Rummukainen, M. (2001). Climate change impacts on runoff in Sweden assessments by global climate models, dynamical downscaling and hydrological modelling. Climate research, 16(2), 101-112.

Bergström, S. and V. P. Singh. 1995. The HBV model. In V.P. Singh (Ed.) Computer Models of Watershed Hydrology (pp.443–76). Water Resources Publications.

Chang, H., & Jung, I. W. (2010). Spatial and temporal changes in runoff caused by climate change in a complex large river basin in Oregon. Journal of Hydrology388(3), 186-207.

Klipsche, J. D., & Hurst, M. B. (2007). HEC-ResSim: Reservoir system simulation user’s manual, v. 3.0, CPD 82. Davis: US Army Corps of Engineers Hydrologic Engineering Center, available at http://www. hec. usace. army. mil/software/hec-ressim.

Northwest Alliance for Computational Science and Engineering (NWACSE). (2015), PRISM Climate Data. http://prism.oregonstate.edu

Seibert, J. (1997). Estimation of parameter uncertainty in the HBV model.Hydrology Research, 28(4-5), 247-262.

Turner, D. P., Conklin, D. R., Vache, K. B., Schwartz, C., Nolin, A. W., Chang, H., ... & Bolte, J. P. (2016). Assessing Mechanisms of Climate Change Impact on the Upland Forest Water Balance of the Willamette River Basin, Oregon. Ecohydrology.

US. Fish and Wildlife Service, Oregon Fish and Wildlife Office (2008), Biological Opinion On the Continued Operation and Maintenance of the Willamette River Basin Project and Effects to Oregon Chub, Bull Trout, and Bull Trout Critical Habitat Designated Under the Endangered Species Act, File Number: 8330, F0224(07), Tails Number: 13420-2007-F-0024.

Web page authors: R. Haggerty, M. Wright, K. Vache, D. Conklin, H. Chang, A. Nolin
Last updated: December 2016

Reservoir Operational Performance

Streamflow in the Willamette River Basin (WRB) is regulated by 13 federally owned reservoirs. Together they operate as a system to provide flood regulation, power production, recreation, fish and wildlife conservation, irrigation, and water quality regulation. The reservoirs were constructed primarily to regulate flood flows, an objective that remains the highest priority for determining reservoir releases. The priority of other operating objectives varies by reservoir and circumstance.

The WW2100 reservoir team investigated whether reservoirs will continue to meet operational objectives, given expected hydrologic responses to climate change, population growth, and economic growth over the next century. We modeled operation of federal reservoirs by incorporating code from the US Army Corp of Engineers model called ResSim into Willamette Envision. ResSim determines water release quantities from reservoirs following a system of time and place specific operating rules.

In this analysis, we evaluated (1) the reliability of hydrologic modeling within Willamette Envision by comparing modeled reservoir inflows to observed historical data, and (2) the potential effects of climate warming on reservoir operational performance, by comparing outcomes for different WW2100 futures scenarios. Our analysis indicates that basinwide, Willamette Envision tends to underestimate inflows during the winter months but reliably produces inflows during the July to November time period. Our comparison of WW2100 futures scenarios suggests that climate warming will have a limited effect on the ability of the system to meet spring and summer flow targets. 

 

Reservoir Modeling in Brief

Reservoir modeling within Willamette Envision duplicates the rules of the US Army Corps of Engineers’ 2012 ResSim model for the Willamette River Basin (WRB). Each reservoir has operational zones, which are based on pool elevation on a particular date (Fig. 1) and rules sets associated with each zone. These rule sets are prioritized within each zone and across reservoirs, such that the model calculates release quantities and locations (e.g., Powerhouse, Regulating Outlet, Spillway) at each time step to meet the highest priority rule. Example rules are those that establish minimum or maximum flows or water elevations, such as the minimum flow targets established by the 2009 Biological Opinion (NMFS, 2008) for April to October, which vary based on the type of water year. These rules are often evaluated at important downstream locations, called control points, which are used to establish releases at reservoirs upstream. Many reservoirs can be influenced by a single control point (e.g., Salem), and many control points can be influenced by a single reservoir. For more information about reservoir modeling in Willamette Envision, refer to the supplemental materials from Jaeger et al. (2016).

Diagram of reservoir operation zones.

Figure 1. Reservoir operating zones (Lookout Point). The conservation curve (green) is the primary rule curve. The zone above the rule curve is the Flood Control Zone, while below the curve is the Conservation Zone. If the pool elevation is above the elevation demarcating the primary flood control zone (horizontal dark blue line), the zone is labeled Top of Dam Zone. If the pool elevation falls below the red line, the zone is labeled the Buffer Zone. An alternative flood control zone exists in this case, when the pool elevation is above the rule curve but below the secondary flood control line (in light blue).

Evaluation of Predicted Reservoir Inflows

We compared simulated reservoir inflows to those observed historically to evaluate the reliability of the hydrologic model in replicating the key hydrologic processes of the catchment. The three measures and their interpretation are summarized below.

  • Root mean square error (RMSE) is an absolute measure of model fit, meaning that the units are directly interpretable, such that higher values represent higher errors. RMSE is calculated as the square root of the variance of the residual. There is no absolute value for a reliable RMSE, as it must be interpreted with respect to the range of predicted values and practical application.
  • Normalized RMSE (NRMSE) is a nondimensional form of the RMSE, normalized to the mean of the observed data, which is useful for comparing between basins and across seasons with different ranges of flows. Expressed as a percentage, the NRMSE is interpreted as the error relative to the mean.
  • Nash Sutcliff Efficiency (NSE) measures the signal-to-noise ratio of hydrologic models by comparing the magnitude of model residuals to the variance in the observed data. A value of 1 represents perfect fit between observed and simulated inflows, a value of 0 represents a model that is equally well represented by the mean, and a value less than 0 indicates a model of questionable value. The reliability of NSE is compromised when extreme values are present in the dataset.

Analysis of Reservoir Operational Performance

The 13 federal reservoirs in the WRB are operated with a primary objective of flood regulation, while power production, recreation, fish and wildlife conservation, irrigation, and water quality regulation provide ancillary benefits. In this analysis, we focused on the potential effect of climate change on two high priority operational objectives: flood regulation and fish and wildlife conservation (low flow targets). We evaluated the ability of reservoirs to meet these operating objectives based on the concept of operational reliability, where reliability is defined (e.g., Hashimoto, 1982; Ray et al., 2010) as the likelihood of achieving a flow target or level of flood protection.

Selected Findings from Reservoir Performance Analysis

Observed vs. Simulated Reservoir Inflows

  • The simulated historical hydrograph of all reservoir inflows combined (Fig. 2) illustrates that the model tends to underestimate inflows during the winter months but reliably produces basinwide inflows during the July to November time period.
  • The relative model fit across reservoirs varies with the metric used to evaluate fit.

    • Based on root mean square error (RMSE; Table 1), model fit is lowest at Green Peter and Detroit reservoirs, which are among the largest reservoirs in the system.

    • Based on normalized root mean square error (NRMSE; Table 2), model fit is lowest at Blue River, Fall Creek, and Fern Ridge, likely as a result of lower flows into those reservoirs.

    • Based on Nash Sutcliff efficiency (NSE; Table 3), model fit is lowest at Blue River reservoir.

  • Model fit is generally higher for the dry summer months than for the wet winter months.

    • Based on RMSE (Table 1), model error is lower in dry summer months than wet winter months.

    • Based on NRMSE (Table 2), model fit is generally higher in dry summer months than wet winter months. Note that because this metric is normalized by mean flows, it will inherently be higher for summer months than winter months, since mean flows are higher in winter than summer.

    • Based on NSE (Table 3), model fit is generally higher for summer than winter months, with the exceptions of Cottage Grove and Fern Ridge.

  • There is no strong evidence of any trend in model fit across the tributaries with the expected degree of groundwater contributions.
  • Note that Foster and Lookout Point reservoirs were omitted from this analysis because they are located downstream of and are under the influence of reservoir operations at Green Peter and Hills Creek, respectively, complicating comparisons of historical and simulated inflows.

Total daily-averaged reservoir Inflow - observed vs. simulated 1980-2009

Figure 2. Total daily averaged reservoir inflow - observed vs. simulated for the period 1980-2009. Results were generated by taking a geometric average of daily streamflows to account for a log-normal streamflow distribution. The simulated data is from the simulated historical climate scenario (called HistoricRef), a WW2100 scenario that modeled the historical period using simulated historical weather data.

 

Table 1. Root mean square error (cms) of observed reservoir inflows vs. modeled reservoir inflows for the HistoricRef scenario, 1980-2009.

  Annual Nov-May Jun-Oct
Blue River 3.74 4.8 1.21
Cottage Grove 1.2 1.49 0.59
Cougar 4.21 5.1 2.5
Detroit 8.41 10.22 4.89
Dorena 3.82 4.9 1.2
Fall Creek 3.85 4.91 1.4
Fern Ridge 2.97 3.79 1.08
Green Peter 8.27 10.57 2.87
Hills Creek 4.06 5.11 1.76

 

Table 2. Normalized root mean square error of observed reservoir inflows vs. modeled reservoir inflows for the HistoricRef scenario, 1980-2009.

  Annual Nov-May Jun-Oct
Blue River 41% 33% 65%
Cottage Grove 24% 19% 63%
Cougar 22% 19% 27%
Detroit 16% 15% 19%
Dorena 27% 22% 44%
Fall Creek 34% 28% 52%
Fern Ridge 31% 24% 122%
Green Peter 24% 20% 34%
Hills Creek 15% 14% 13%

 

Table 3. Nash Sutcliffe efficiency of observed reservoir inflows vs. modeled reservoir inflows, for the HistoricRef scenario, 1980-2009.

  Annual Nov-May Jun-Oct
Blue River 0.71 -0.48 0.55
Cottage Grove 0.91 0.7 0.43
Cougar 0.83 0.04 0.71
Detroit 0.88 0.12 0.81
Dorena 0.88 0.46 0.8
Fall Creek 0.8 0.08 0.61
Fern Ridge 0.91 0.81 -3.26
Green Peter 0.88 0.29 0.81
Hills Creek 0.9 0.43 0.92

 

Simulated vs. Future Reservoir Inflows

  • We compared total systemwide reservoir inflows between the simulated historical scenario (HistoricRef) and two futures scenarios with different intensities of climate warming. These two scenarios were the Reference Case, which included moderate climate warming (4° C or 7.5° F) warming over the 21st century, and the High Climate Change scenario (with 6° C or 10.5° F) of warming over the 21st century. Refer to the climate page for more information about these scenarios. The analysis suggests that relative to the past, future reservoir inflows to the system will be the same or higher except for the early summer months (May-July) and late fall, primarily for late century.

Total reservoir inflow – Reference scenario

Figure 3. Total daily averaged reservoir inflows for early, middle, and late century periods of the Reference scenario. For comparison, values from the simulated historical scenario, 1980-2009, are also shown.

Total reservoir inflow – HighClim scenario

Figure 4. Total daily averaged reservoir inflows for early, middle, and late century periods of the HighClim scenario. For comparison, values from the simulated historical scenario, 1980-2009, are also shown.

Flood Regulation

  • Model results indicate that regulation of floods at Salem is very high, represented by zero days above flood stage for the simulated historical scenario. Flood regulation at Salem remains high in nearly all years for the Reference and HighClim future scenarios (Fig. 5).
  • The No Reservoirs scenario illustrates the degree of flood regulation provided by the reservoirs, the benefits of which are particularly evident in the mid- and late-century time periods when flood stage is regularly exceeded.
  • Model calibration emphasized summer flows since the project focused on water scarcity. As a result, model fit for reservoir inflows was lower in winter than in summer, introducing some uncertainty in the results regarding impacts of climate change on flooding.

Time reliability of flood regulation on the Willamette River at Salem

Figure 5. Time reliability of flood regulation on the Willamette River at Salem, Ore., for three WW2100 scenarios. The Reference scenario includes a moderate degree of climate warming (weather inputs were derived from the MIROC global climate model). The No Reservoirs scenario includes these same weather inputs, but models behavior of the river system as though no federal reservoirs were present. The High Climate Change scenario models the system with reservoirs, as in the Reference scenario, but includes more intense climate warming (weather inputs derived from the HadGEM global climate model). For more information about WW2100 modeling scenarios, refer to the scenarios page.

Spring and Summer Flow Targets

  • Model results indicate that, with a warmer climate, the number of days when summer targets are met increases in the future relative to the simulated historical scenario. This counterintuitive effect is greater for the Reference scenario than for the HighClim scenario. This reflects the increase in runoff projected for the April-May time period (Figs. 3, 4). However, future reservoir inflows are lower than the simulated historical during the July-August months when the reservoirs appear to provide higher reliability in summer targets.
  • Results for the No Reservoirs scenario also illustrate the role of reservoirs in augmenting flows from July to October. In this scenario (Fig. 6), the number of days when late summer flow targets are met is nearly zero.
  • The No Reservoirs scenario also demonstrates the limited effect of the reservoirs on providing flows for the spring and early summer months. Even without reservoirs, the scenario shows a high reliability of meeting flow targets from April to June.

Time reliability of spring and summer flow targets on the Willamette River at Salem

Figure 6. Time reliability of spring and summer flow targets on the Willamette River at Salem for the Reference, HighClim, and No Reservoirs scenarios. Results are plotted as the ratio of days above the flow target relative to the number of days in a given month.

Conclusions

  • Model fit: basinwide the model tends to underestimate inflows during the winter months but reliably produces inflows during the July to November time period.

  • Flood regulation: climate change appears to have limited to no effect on flood regulation. However, the model underpredicts the historical winter inflows to reservoirs, indicating that this finding has some associated uncertainty.

  • Spring flow targets: climate change appears to have limited to no effect on the ability of the system to meet spring flow targets.

  • Summer flow targets: climate change appears to have a positive effect on the ability of the system to meet summer flow targets in the late century, perhaps because of projected increases in spring runoff.

Related Links & Publications

Contributors to WW2100 Reservoir Modeling

  • Desiree Tullos, OSU Biological & Ecological Engineering (lead)

  • Cara Walter, OSU Biological & Ecological Engineering

  • Kathleen Moore, PhD Student, OSU Geography (Graduated: 2015; now a post-doctoral researcher, OSU Applied Economics)

  • Matt Cox, OSU Biological & Ecological Engineering (now at Interfluve, Hood River, Oregon)

References

Jaeger et. al. (2016). Scarcity amid abundance: Water, climate change, and the policy role of regional system models. Manuscript in preparation.

National Marine Fisheries Service. (2008). Continued Operation of 13 Dams & Maintenance of 43 Miles of Revetments in the Willamette Basin, OR. (PCTS Tracking No. NWR 2000-2117). Portland, OR.

Hashimoto, T., Stedinger, J. R., & Loucks, D. P. (1982). Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation. Water Resources Research, 18(1), 14-20. http://dx.doi.org/10.1029/WR018i001p00014

Ray, P. A., Vogel, R. M., & Watkins, D. W. (2010). Robust optimization using a variety of performance indices. In Proceedings of the World Environmental and Water Resources Congress, ASCE, Reston, VA.

 

Web page authors: D. Tullos, C. Walter, K. Moore
Last updated: August 2016

Reservoir Economics

Together the 13 federal reservoirs in the Willamette River Basin help to mitigate water scarcity. Although the reservoirs were primarily built for flood control, they also provide a large capacity – a combined 1.6 million acre-feet – to store water from abundant winter and spring streamflows for possible use during the summer when natural flows are low. While flood risk reduction remains the priority use of these reservoirs, stored water uses – including reservoir recreation and increasing downstream flows for endangered species, irrigated agriculture, and municipal uses – have become increasingly important. Because reservoir capacity cannot be used for flood control and water storage at the same time, these uses must be traded off during the transition from the wet to dry season.
Our modelling results indicate increasing shortfalls from full storage at the beginning of summer over the next century, particularly under warmer climate scenarios. Greater summer drawdowns are also more likely, as obligations to release water for downstream conservation flows or contracted stored water increasingly exceed natural inflow. Based on empirical evidence that fewer people visit these reservoirs for recreation when water levels are reduced, losses in annual recreational benefits are expected to increase from an average of $5 million over the first half of this century to more than $12 million toward the end of the century. These estimated losses represent approximately 5% of total estimated reservoir recreational benefits each summer. Recreational losses should, however, be considered relative to the estimated value of flood risk reduction. We estimate current flood control benefits at more than a billion dollars annually and expect these benefits to triple by 2100 with economic growth and urban expansion.

Reservoir Economics Methods in Brief

We estimated the value of stored water for recreation at the Willamette Basin federal reservoirs using monthly visitor count data obtained from the US Army Corp of Engineers (USACE) for the years 2001-2011 (period available at time of analysis), and an expected average willingness-to-pay per visitor day (Loomis, 2005). Lowered water levels can impact recreational use in various ways, including loss of boat ramp access and compromised aesthetics such as ‘bathtub rings.' Estimated losses in recreational benefits were based on WW2100 projected shortfalls in summer storage, and empirical evidence that fewer people visit the reservoirs when water levels are reduced (Moore, 2015).

We then estimated the value of reservoir capacity for flood risk reduction based on WW2100 projected land use within the Willamette River floodplain, the probability of flood events, and expected flood inundation. The extent of the floodplain was delineated according to the SLICES data layer developed by the Pacific Northwest Ecosystem Research Consortium (Hulse et al., 2002). We used a ‘bathtub’ model along with high-resolution topographic information (LiDAR) to estimate inundation associated with flood stage. Flood frequency and timing was assessed using the stream gauge record at Salem. Expected flood damages and the related value of reservoir capacity for flood risk reduction were estimated by integrating the spatially explicit estimates of structural value in the Willamette River floodplain, the modeled flood inundation, and assessed flood frequency distributions (Moore, 2015).

Select Findings from Reservoir Economics Analysis

The federal reservoirs in the Willamette River Basin serve multiple purposes, including flood risk reduction, reservoir recreation, and downstream flow augmentation. At certain times of the year, however, these uses compete with one another, and the value that society places on these competing uses should be considered in management decisions for water allocation. This section describes the expected changes in value for reservoir recreation and flood risk reduction over the next century.

Reservoir Recreation Benefits

  • Our modeling results indicate increasing shortfalls from full storage at the beginning of summer over time, particularly under warmer climate scenarios, as well as greater summer drawdowns as obligations to release water downstream for conservation flows or contracted stored water are increasingly unmet by natural inflow (Fig. 1).

  • Lost recreational benefits resulting from lowered summer (June-August) water levels are estimated to increase from an average of $5 million per year over most of this century to more than $12 million toward the end of the century under the Reference Case scenario (Fig. 2). Under the warmest climate scenario, average annual losses increase to almost $13.5 million during the last two decades of the century (Fig. 2).

Average shortfall from full summer storage by decade for the high climate scenario.

Figure 1. Average shortfall from full summer storage by decade for the High Change Climate scenario.

 

Reduction in recreational benefits due to reservoir drawdown.

Figure 2. Reduction in recreational benefits due to reservoir drawdown.

Flood Risk Reduction Benefits

  • Current benefits from flood risk reduction are estimated at more than a billion dollars annually (Fig. 3).
  • These benefits are expected to triple by 2100 under the Reference Case scenario, while under the High Population scenario, the projected benefits increase more than five times (Fig. 3).

Estimated flood risk reduction benefits from January through May under the reference and high population scenarios.

Figure 3. Estimated flood risk reduction benefits from January through May under the Reference Case and High Population scenarios.

Conclusions

Losses in recreational benefits, associated with lowered summer reservoir water levels, are expected to increase from an average of $5 million per year over the first half of this century to more than $12 million by the end of the century. However, since the reservoirs are managed for both flood control and stored water uses, these projected recreational losses should be tempered against the estimated value of flood risk reduction. We estimate current flood control benefits at more than a billion dollars annually and expect these benefits to triple by 2100 with economic growth and urban expansion. Thus, there is a strong economic rationale to keep reservoir fill low as long as flood risk is high at the beginning of each calendar year, before beginning to fill for storage.

Related Links & Publications

  • Moore, K.M. (2015, May 5). Optimizing reservoir operations to adapt to climate and social change in the Willamette River Basin, Oregon, Recorded WW2100 Webinar. https://media.oregonstate.edu/media/t/0_qrvmvk9h

  • Moore, K.M. (2015). Optimizing reservoir operations to adapt to 21st century expectations of climate and social change in the Willamette River Basin, Oregon (Doctoral dissertation). Oregon State University, Corvallis, Ore. http://hdl.handle.net/1957/56208

Contributors to WW2100 Reservoir Economics Analysis

  • Kathleen Moore, OSU Geography (completed PhD 2015; now a post-doctoral researcher, OSU Applied Economics)
  • William Jaeger, OSU Applied Economics

References

Hulse, D., S. Gregory, and J. P. Baker (2002). Willamette River Basin Planning Atlas: Trajectories of Environmental and Ecological Change. Oregon State University Press.

Loomis, J. B. (2005). Updated outdoor recreation use values on national forests and other public lands. US Department of Agriculture, Forest Service, Pacific Northwest Research Station.

Moore, K.M. (2015). Optimizing reservoir operations to adapt to 21st century expectations of climate and social change in the Willamette River Basin, Oregon (Doctoral dissertation). Oregon State University, Corvallis, Ore. http://hdl.handle.net/1957/56208

Web page authors: K. Moore, W. Jaeger
Last updated: September 2016

Fish & Stream Temperature

One of the major impacts of future climate change in the Pacific Northwest is the alteration of native fish communities, which include a substantial number of cold water species (Williams et al., 2014). Projected warming trends in the Pacific Northwest create direct physiological challenges for cold water species and indirect challenges through competition with species that are tolerant of warmer water, especially those species that are not native to the region. Currently, in the entire Willamette River Basin there are 69 species of fish—36 native species and 33 non-natives. 

The objectives of the WW2100 fisheries team were to:

  1. Determine the composition and distribution of native and non-native fish communities along the mainstem Willamette River.
  2. Determine the likelihood of occurrence for representative fish species based on the temperatures at which those species occurred in the Willamette River.

During our field sampling in summers of 2011-2013, we captured more than 36,000 fish including 22 native and 19 non-native species. Most fish captured (more than 90%) were native species. Species richness and abundance exhibited strong longitudinal patterns; higher numbers of fish were collected in the upper river, and a higher proportion of the fish captured were native species. We do not have modeled estimates of water temperature for 2100, but we projected the consequence of a potential temperature change on the likelihood of capturing representative fish species in our standard sampling protocol. Our results suggest that the likelihood of occurrence of native cold-water species, such as juvenile Chinook salmon, would decrease substantially if future river temperature increases by 2° C (3.6° F) or more. 

 

Fisheries Methods in Brief

Field Sampling Methods

We divided the mainstem Willamette River into three sections from its mouth, upstream 301 km to the confluence of the Coast and Middle Fork Willamette, based on analysis of river geomorphology. The SLICES framework served as the geomorphic basis of randomized site selection for fish community assessment. Each 1-km slice of the mainstem river or floodplain slough within a river slice represented a single sampling location. In each 1-km slice in 2011-2013, we captured fish with standardized boat and backpack electrofishing.  Sampling locations included 96 mainstem reaches and 71 sloughs. We measured environmental and habitat characteristics at each site.

We developed a Willamette River Fish Database (http://gis.nacse.org/wrfish/) to make spatially explicit data on fish communities in the mainstem Willamette River publicly available. Watershed councils, land trusts, NGOs, and state and federal agencies have full access to the data for designing projects to conserve or restore the aquatic ecosystems and floodplains of the Willamette River. The information also contributes to the collective development of a guiding vision of a future Willamette River and its floodplain for all partners.

Modeling Approach

We related possible temperature increases in the mainstem river to the likelihood of capturing various fish species in a standard sampling effort (e.g., spring Chinook salmon, coastal cutthroat trout, common carp). Specifically, we describe the consequence of a hypothetical increase (2° C or 3.6° F) in stream temperature on the likelihood of capturing representative fish species in our standard sampling protocol, based on the temperatures at which we observed them in 2011-2013. Such an increase in stream temperature is highly likely in the future during normal flow years.

The fisheries analysis is limited to the mainstem Willamette River, downstream of the major reservoirs, and was not coupled to Willamette Envision, the project's integrative water system model.

Select Findings from Fisheries Analysis

Fish Distribution

During our field sampling in summers of 2011-2013, we collected 41 fish species – 22 native and 19 non-native. Of the total of 36,586 individual fish collected, 93% were native species and 7% non-native (Williams, 2014). In mainstem habitat, 97% of the individual fish captured were native and 3% were non-native. A greater proportion of catch in slough habitats was non-native (13%), but native species comprised the majority (87%) of fish captured in the sloughs as well.

Species richness and relative abundance of fish exhibited significant longitudinal patterns (Fig. 1). Higher numbers of fish were collected in the upper river, and higher proportions of those fish were native species. In contrast, non-native species exhibited the opposite pattern, increasing in relative abundance and total number of taxa from the upper river to lower river. The 1-km standard sample reaches in the upper river contained 16-19 native fish species, but similar samples from the lower river contained only 3-10 native fish species.

Number of native fish species captured in BOAT electrofishing samples for the mainstem Willamette River for 2011 - 2013.

Figure 1. Number of native fish species captured in BOAT electrofishing samples for the mainstem Willamette River for 2011-2013.

Temperature Sensitivity

During our three-year monitoring study, we sampled both fish communities, habitat, and water quality throughout the Willamette River mainstem (Fig. 2). The green and red lines and markers in Fig. 2 represent the maximum daily temperature observed at each station in 2012 and 2013, respectively. We do not have modeled estimates of water temperature for 2100, but we projected the consequence of a potential temperature change on the likelihood of capturing representative fish species in our standard sampling protocol. If water temperatures in the Willamette River increase by 2° C (3.6° F, less than the projected air temperature), the longitudinal profile (blue line and markers) would increase to more than 26° C (78.8° F) in the lower river. Such an increase is highly likely in the future during normal flow years. As a frame of reference, the USGS gaging station in Portland recorded temperatures of 26.8° C (80.2° F) in early July 2015, a year that was extremely warm and when flows in the river were much lower than average (Fig. 3).

Longitudinal pattern of river temperature in observed in 2012 and 2013 (green and red, respectively) and longitudinal pattern of river temperature in 2100 if river temperatures increase by 2°C.

Figure 2. Longitudinal pattern of river temperature observed in 2012 and 2013 (green and red, respectively) and longitudinal pattern of river temperature in 2100 assuming an increase in river temperatures of 2° C (3.6° F).

Temperature at the USGS gaging station in Portland in summer 2015.

Figure 3.  Temperature at the USGS gaging station in Portland in summer 2015.

We estimated the likelihood of occurrence of juvenile Chinook salmon in our standard sampling protocol based on the temperatures at which we observed this species in 2011-2013. Projections for the likelihood of occurrence currently decreases from approximately 50% in the upper river to less than 30% in the lower river (Fig. 4). The projected temperature increase by 2100 would lower that likelihood to less than 40% in the upper river and roughly 15% in the lower river. Coastal cutthroat trout are a cold-water salmonid that resides in the Willamette River throughout the year. Cutthroat trout exhibited even greater sensitivity to temperature (based on the locations they were captured). The likelihood of occurrence of cutthroat trout in the lower river would be extremely low under potential future temperatures (Fig. 5). In contrast, the likelihood of occurrence of common carp, a warm-water non-native species, increase longitudinally and would increase to more than 90% in the lower river by 2100 (Fig. 6).

These projections of the likelihood of cold-water fish species occurrence at higher temperatures are likely to be overestimates because the National Marine Fisheries Service (NMFS) does not allow us to sample at temperatures higher than 18° C (64.4° F). We are extrapolating beyond observed temperatures and occurrences.  Based on the incipient lethal levels of these species, it is highly unlikely to observe Chinook salmon, cutthroat trout, or other salmonids in water warmer than 26° C (78.8° F).

Longitudinal pattern of the likelihood of capturing juvenile spring Chinook salmon in our standard sampling protocol based on the river temperatures in observed in 2012 and 2013..

Figure 4.  Longitudinal pattern of the likelihood of capturing juvenile spring Chinook salmon in our standard sampling protocol based on the river temperatures observed in 2012 and 2013 (green and red, respectively) and longitudinal pattern of river temperature in 2100 if river temperatures increase by 2° C (3.6° F).

Longitudinal pattern of the likelihood of capturing resident coastal cutthroat trout in our standard sampling protocol based on the river temperatures.

Figure 5.  Longitudinal pattern of the likelihood of capturing resident coastal cutthroat trout in our standard sampling protocol based on the river temperatures observed in 2012 and 2013 (green and red, respectively) and longitudinal pattern of river temperature in 2100 if river temperatures increase by 2°C (3.6°F).

Longitudinal pattern of the likelihood of capturing common carp, a warm-water non-native fish species, in our standard sampling protocol based on the river temperatures observed in 2012 and 2013.

Figure 6. Longitudinal pattern of the likelihood of capturing common carp, a warm-water non-native fish species, in our standard sampling protocol based on the river temperatures observed in 2012 and 2013 (green and red, respectively) and longitudinal pattern of river temperature in 2100 if river temperatures increase by 2° C (3.6° F).

Conclusions

The Willamette River has recovered greatly from past water pollution and river channel modifications, but it faces many threats in the future. Population in the region is expected to continue growing rapidly. Land development continues to see increasing demands for urban and residential lands while agricultural and forest industries are fighting to protect their land base. Much of the new development pressures are in the valley along the mainstem Willamette River and its floodplain. Streams and river temperatures already approach the lethal limits of native cold-water fish species, especially in the lower river near the major urban centers. Many miles of streams in the basin are listed by environmental agencies as water quality impaired because of water temperature. The climate in the basin is projected to warm by 1.0 to 3.4° C (2 to 6° F) by the middle of the century. Our results suggest that the likelihood of occurrence of native cold-water species, such as juvenile Chinook salmon, would decrease substantially if future river temperature increases by 2° C (3.6° F) or more.

One of the greatest challenges is to create a scientifically sound vision of the new river, a river that is changing because of its altered flow regimes and sediment supply, a river that is changing because of social changes in the towns and communities along its banks (Wallick et al., 2013). Water management authorities are facing increasing demands to store water in reservoirs and withdraw more water during low flow seasons when the needs of the aquatic ecosystem also are most acute. Flood control reservoirs already have reduced sediment transport to the mainstem by 60%, and peak flows in the river are reduced roughly 30 to 70%. The momentum of current trends and uncertainty of future changes make it critical for our region to anticipate the future Willamette River.

Related Links & Publications

Contributors to WW2100 Fisheries Research

  • Stan Gregory, OSU Fisheries and Wildlife (lead)
  • Josh Williams, MS Student, OSU Fisheries and Wildlife (Graduated: 2014) 

References

Wallick, J. R., Jones, K. L., O’Connor, J. E., Keith, M. K., Hulse, D., & Gregory, S. V. (2013). Geomorphic and Vegetation Processes of the Willamette River Floodplain, Oregon—Current Understanding and Unanswered Questions. US Geological Survey Open File Report, 1246. http://pubs.usgs.gov/of/2013/1246/pdf/ofr2013-1246.pdf

Williams, J. E., Giannico, G. R., & Withrow-Robinson, B. (2014). Field guide to common fish of the Willamette Valley floodplain. Corvallis, Or.: Extension Service, Oregon State University. http://ir.library.oregonstate.edu/xmlui/handle/1957/50100

 

Web page author: S. Gregory
Last updated: October 2015

Water Users Survey

The objective of the landowner survey component of the WW2100 project was to evaluate Willamette Valley landowner attitudes toward and perceptions of water availability, water scarcity, present and future water management policy, and present and future land use and management goals. Additional survey questions focused on perceptions of risks to quality of life in the Willamette Valley, environmental values and value orientations, sources of information used to learn about water, desirable community characteristics, household activities, participation in organizations related to natural resources, and socioeconomics. A summary of general results for the most salient items is presented here.  In survey responses, most landowners believe that the Willamette Valley has enough water currently. Of 1,402 respondents, approximately 54% strongly agreed that the Willamette Valley currently has enough water to meet the needs of people, plants, and animals, however respondents indicated greater uncertainty as time increased into the future. When asked about activities perceived to be high or moderate risk to water availability in the Willamette Valley, at least 70% of respondents indicated agriculture, drought conditions, and population growth.

 

Survey Methods in Brief

We used property tax records to create a sample of landowners for the survey. We used a geographic information system to stratify the sample in three ways:

  • Location in the Willamette Valley,

  • Residential versus agricultural property, and

  • Inside versus outside of the Urban Growth Boundaries (UGBs).

In winter and spring 2013, we sent questionnaires to 1,600 landowners in each of Lane, Marion, and Washington-Yamhill Counties. From this effort, 1,402 surveys were completed and returned. There were 430 surveys returned as undeliverable and 56 refusals. Therefore, the overall response rate was approximately 32%.

 

Table 1. Survey respondents by stratum (n=1,402).

  Lane Marion Washington-Yamhill Total

By property type and county

Residential

Agricultural

 

239

198

 

131

360

 

149

325

 

519

883

By location relative to Urban Growth Boundary and county

Inside UGB

Outside UGB

 

183

254

 

200

291

 

149

325

 

532

870

Total by county 437 491 474 1402

 

A follow-up questionnaire was sent to all landowners from the sample who did not answer the original survey. Approximately 400 questionnaires were completed. The most commonly reported reasons for not completing the survey were lack of interest in completing surveys, perceived lack of knowledge about water management, the survey was too long or complicated, and personal reasons.

Select Findings from Water Users Survey

This summary is divided into the basic sections of the survey. All results are considered preliminary until peer-review of data is completed. Because of the sampling strategy used, results are not generalizable to the entire Willamette Valley.

Sample demographics

  • Survey respondents averaged 64 years of age.

  • More than half (60%) of survey respondents were male.

  • Nearly all (99%) of survey respondents own their home.

  • Average length of residence at the current address was 23 years.

 

Perceptions of Water Availability

Most respondents reported that they think about the role of water in their life in terms of their lifetime (25%) or for future generations (57%). When asked the degree to which they believe that the Willamette Valley has enough water to meet the needs of people, plants, and animals in several time periods, respondents indicated greater uncertainty as time increased into the future (Fig. 1). No statistical difference existed between residential versus agricultural landowners.

The degree to which respondents believe that the Willamette Valley has enough water to meet the needs of people, plants, and animals for different future time periods.

Figure 1. The degree to which respondents believe that the Willamette Valley has enough water to meet the needs of people, plants, and animals for different future time periods.

Risk to Water Availability

When asked about their perceived risk of activities to availability of water in the Willamette Valley, more than 40% of respondents indicated:

  • Drought conditions and population growth to be high risk.

  • Agriculture, forest management, and industry to be moderate risk.

  • Water storage (e.g., hydro-electric dams), private wells, and historical appropriation (e.g., water rights) to be low risk.

Activities perceived to be high or moderate risk to availability of water in the Willamette Valley by at least 70% of respondents include: agriculture (74%), drought conditions (73%), and population growth (85%).

  • Marion County respondents were less likely to perceive high or moderate risk of agriculture and drought conditions than the other two locations.

  • Residential landowners were less likely to perceive high or moderate risk of agriculture than agricultural landowners.

 

Definition of Water Scarcity

A group of WW2100 stakeholders developed a definition of water scarcity:

“Water scarcity occurs when there is not an affordable, attainable, and reliable source of clean water when and where it is wanted or needed by humans and animals and plants currently and into the future.”

Landowners were asked to indicate the extent to which they perceived each underlined term to be associated with their own perception of water scarcity.

  • The greatest number of respondents indicated their perceptions to be strongly associated with “clean” and “humans.”

  • “Affordable” and “currently” were terms identified as weakly associated by the greatest number of landowners.

  • Two terms varied statistically for residential versus agricultural landowners. More residential (37%) than agricultural (26%) landowners indicated “affordable” (37% versus 26%) and “clean” (67% versus 57%) as strongly associated with their perception of scarcity.

  • Perceived association of several terms varied by location (county): attainable, reliable, clean, needed, humans, and animals and plants. Exploration of patterns in these differences is ongoing.

Landowners were asked to indicate the extent to which they perceived each underlined phrase in the water scarcity definition to be associated with their own perceptions of water scarcity.

Figure 2. Landowners were asked to indicate the extent to which they perceived each underlined phrase in the water scarcity definition to be associated with their own perceptions of water scarcity. This chart shows responses by phrase.

 

Water Regulation

Water law in Oregon currently is a “first in line, first in right” (i.e., those with the most recently acquired water rights lose them first). Most landowners (79%) believe that at least some regulation should exist related to water use and management, regardless of whether residential (81%) or agricultural (77%). Agreement with this statement was greatest in Washington-Yamhill Counties (83%), followed by Lane (80%) and Marion (74%) Counties.

Landowners were asked to indicate, in their opinion, the acceptability of different ways of distributing water among competing uses at times of limited water availability (Fig. 3). These included:

  • Current Oregon water law (see above)
  • The method that makes the most economic sense, regardless of priority
  • Users must share any excess water beyond what they need
  • Users can sell any excess water beyond what they need
  • All potential users have equal access to water that is available
  • Those who use more water pay more for its use
  • Users farther from the water source pay more for its use
  • Store enough water in reservoirs to account for all potential users
  • Give water not used by agriculture to municipal use
  • Give water not used by agriculture to biological use (e.g., more water in streams to maintain appropriate water temperature for fish)
  • Give water not used by agriculture to recreational use
  • Build more facilities for water storage and replenishment
  • Allow the state to decide allocation methods for water

Among the most acceptable distribution methods were those where excess is shared among users, those who use more water pay for its use, and water storage. Exploration of differences between residential and agricultural landowners and among counties are ongoing.

Responses from agricultural landowners about why they currently participate (or not) in selected land conservation practices.

Figure 3. Landowners were asked to indicate, in their opinion, the acceptability of different ways of distributing water among competing uses at times of limited water availability. This chart shows responses for the the options provided in the survey. Note: options are shown in the graph in the same order as the list provided above.

 

Future Use of Agricultural Land (Agricultural Landowners Only)

Agricultural landowners were asked several additional questions about water management on their land, and current and future use of their land. Eighty-seven percent (87%) reported that they currently live on their property. A majority of those who do not live on their property do live in Oregon. Ninety-three percent (93%) reported that they or an immediate member of their household manages decisions about water use on their property. Landowners were asked why they currently participate (or not) in selected land conservation practices (Fig. 4) and their interest in future participation in selected land conservation practices (Fig. 5).

Landowners were asked to indicate, in their opinion, the acceptability of different ways of distributing water among competing uses at times of limited water availability.

Figure 4. Responses from agricultural landowners about why they currently participate (or not) in selected land conservation practices.

 

Responses from agricultural landowners about their interest in participating in land conservation practices in the future.

Figure 5. Responses from agricultural landowners about their interest in participating in land conservation practices in the future.

Sixty-six percent (66%) of respondents indicated that they now have a formal, defined plan for future ownership of their land. There was no statistical difference between counties or location relative to UGB. Of those with a plan:

  • Forty-eight percent (48%) reported that the land will remain in its current use.
  • Twenty-five percent (25%) reported that a beneficiary will make any land use decisions.
  • Two percent (2%) reported either land will be divided into residential parcels or be part of a conservation easement.
  • Twenty-three percent (23%) reported “other.” Further evaluation of specific items provided by respondents is ongoing.

Landowners were asked to indicate which of the following will most likely to influence their decision in developing a plan for future ownership of their land, or potentially change an existing plan. Although there was no difference among counties, variation existed based on location relative to the UGB (Fig. 6).

 Influences on future ownership plans reported by agricultural landowners, grouped by property location relative to the Urban Growth Boundary.

Figure 6. Influences on future ownership plans reported by agricultural landowners, grouped by property location relative to the Urban Growth Boundary.

Landowners were also asked to report on factors that influence their decisions about changing the land use on their property (Fig. 7). Preliminary results suggest that differences among counties exist for demand for particular products and possession of a current water right for the property, and differences in relation to UGB exist for regulations on land management practices, and regulations on water use.

The extent to which selected factors are likley to influence agricultural landowners decisions about future land use.

Figure 7. The extent to which selected factors are likley to influence agricultural landowners decisions about future land use.

Related Links & Publications

Contributors to WW2100 Water Users Survey

  • Anita Morzillo, OSU Forest Ecosystems & Society, now at Department of Natural Resources and the Environment, University of Connecticut
  • Meagan Atkinson, MS Student, OSU Environmental Science (Graduated: 2014)

  • Stephanie Graham, MS Student, Professional Science Masters (Graduated: 2012)

 

Web page author: A. Morzillo
Last updated: October 2015

Education & Engagement

The Willamette Water 2100 project included education and outreach components for K-12 students and educators, undergraduate and graduate students, and community and professional audiences. Over its six years, the project trained eight MS and five PhD students and conducted graduate courses on (1) the use of focus groups in stakeholder engagement and (2) multi-scale hydrologic modeling. The project also supported a multi-day watershed education workshop for K-12 teachers, research experiences for K-12 teachers and high school students, and developed a place-based children’s book on water. Through its Learning and Action Network, the project team hosted many events for regional water stakeholders and managers, and gave more than 100 professional and outreach presentations to regional and professional audiences including 10 workshops, 3 field trips and 13 webinars.

Photos from WW2100 broader impacts activities.

Graduate Education

Graduate students in a variety of fields received mentoring and carried out research as part of the WW2100 project team. Their studies resulted in eight MS and five PhD theses (Table 1). In addition, we conducted two graduate-level courses, one on the use of focus groups in stakeholder engagement (WRP 599) and a second on multi-scale hydrologic modeling (WRS 599). We also delivered two special seminar courses (WRS 507) focused on water sustainability, and climate projects and issues, one in spring term 2011, the other in spring term 2015. An average of 25 students enrolled, and the seminars were also open to and attended by the public. Further description of these courses is provided below.

WRP 599 course enrolled ten students, WRS 599 enrolled 12 students at OSU and was cross-listed at Portland State University where an additional 12 students were enrolled.

WRP 599 Practicum in Conducting Focus Group Interviews - Spring 2012

Course Description from Syllabus: This graduate-level practicum course is centered around an NSF funded water experts stakeholders engagement workshop, applies the theory and practice of focused group interviews to elicit expert information and capture expert knowledge through the use of concept maps of water management in a major river basin. The course begins with a set of targeted readings and an introductory lecture to provide an overview of (1) the theory and practice of focus group process, including elements of IRB (Institutional Review Board) approval (2) the specific goals of the focused interviews in the context of the NSF funded Willamette Water 2100 research project. In the second and third week students will participate in interactive discussions to help refine interview questions and follow-up questions. In weeks four and five, students will assist in facilitation of a practice focus group followed by a written critique of the process. In Week 6 students will use the techniques learned to facilitate and record up to 6 different focus group interviews at the Willamette Water 2100 May 9 symposium. Following the symposium Week 6, students will critique and report on interactions in their own focus group. In weeks 7-10, Denise Lach will present a guest lecture on inter-investigator consistency in coding interview responses, students will code and summarize the data collected from their focus group notes and flip charts. The course final will be a report from the focus group you facilitated, and class discussion and synthesis of the major findings.

WRS 599 Multi-scale Hydrologic Modeling - Spring 2013

Course Description from Syllabus: This graduate-level course addresses issues related to water resource scarcity under changing landscape conditions. To accomplish this, the course focuses upon the theory and practice of hydrologic modeling at various spatial scales from small catchments to a major river basin such as the Willamette River Basin, and compares different modeling approaches used to evaluate potential future impacts of global change.The models discussed and presented represent different elements of a complex water resource system, and are linked by their use in a common project, the Willamette Water 2100 project.The course begins with a set of readings and an introductory lecture to provide an overview of (1) the specific goals of modeling approaches used in the context of the Willamette Water 2100 research project and (2) the theory and practice of hydrologic modeling. In weeks 2-9, collaborators on the WW 2100 project will each give two lectures discussing their modeling approach in the specific context of the Willamette Water 2100 project. Each lecturer will address the same set of key topics and themes in their lectures, using their modeling approach to illustrate the advantages and constraints imposed by that approach, how the model “plugs in” to Envision or if the model is not coupled as a plug-in, the way that this model helps to inform the larger project and other modeling efforts. Each lecturer will provide a homework assignment. In the laboratory sessions students will learn to use Envision and the associated HBV-FLOW model. For the group projects, groups of 3-4 students will select and focus on an interdisciplinary research question that can be addressed by the Envision model and use Envision to explore the potential outcomes associated with this research question. Students will prepare a group technical summary and give a 30 minute presentation on the results of their project. In week 10, the course wrap-up, students will examine and critique reference runs of the Envision model and prepare in class a joint assessment of the application of this model in the WRB and recommendations for its improvement. On the final day of class, we will discuss technology transfer and application of Envision and other models in other regions.

WRS 507 Seminar - Spring 2011 and WRS 507 Seminar- Spring 2015

Course Description from Syllabus:The seminar is a chance for students to learn from and interact with water resources professionals with many different experiences and perspectives. Speakers were chosen both to cover specific topics and to represent different disciplines and career tracks. Students are expected to be engaged listeners and to ask questions about the presentation. Learning Objectives include:

  1. To become familiar with current research in the area of Water Resource Science, specifically with respect to interdisciplinary water resources research on Water Sustainability and Climate

  2. To observe various ways of presenting research results

  3. To practice critiquing presentations and developing questions to ask of presenters

  4. To provide students with opportunities to meet scholars and practitioners in the field

Table 1. Graduate student theses supported by the Willamette Water 2100 project.

Primary Subject Area

Project Advisor

Thesis Citation

human dimensions

Sam Chan

Ferguson, L. 2015. Characterizing and Assessing the Researcher-Stakeholder Engagement Process for Water Sustainability: The Willamette Water 2100 Project, Master of Science (MS) in Marine Resources Management. Oregon State University, Corvallis, OR.

snow hydrology

Anne Nolin

Gleason, KE. 2015. Forest Fire Effects on Radiative and Turbulent Fluxes over Snow: Implications for Snow Hydrology. Doctor of Philosophy (PhD) in Geography: 202. Oregon State University, Corvallis, OR.

applied economics

Andrew Plantinga

Bigelow, DP. 2015. How Do Population Growth, Land-use Regulations, and Precipitation Patterns Affect Water Use? A Fine-scale Empirical Analysis of Landscape Change. Doctor of Philosophy (PhD) in Applied Economics: 199. Oregon State University, Corvallis, OR.

geography and applied economics

Julia Jones and William Jaeger

Moore, KM. 2015. Optimizing Reservoir Operations to Adapt to 21st Century Expectations of Climate and Social Change in the Willamette River Basin, Oregon. Doctor of Philosophy (PhD) in Geography: 183. Oregon State University, Corvallis, OR.

hydrology

Naomi (Christina) Tague

Garcia, ES. 2014. Ecohydrologic Modeling in Three Western U.S. Mountain Watersheds: Implications of Climate, Soil, and Carbon Cycling Interactions for Streamflow. Doctor of Philosophy (PhD) in Geography: 142. UC-Santa Barbara, Santa Barbara, CA.

human dimensions

Anita Morzillo

Atkinson, M. 2014. Attitudes toward Water Allocation Policy in the Willamette Valley, Oregon. Masters of Science (MS) in Natural Resources: 91. Oregon State University, Corvallis, OR.

fisheries

Stan Gregory

Williams, J. 2014. Habitat Relationships of Native and Non-native Fishes of the Willamette River, Oregon. Fisheries and Wildlife. Master of Science (MS) in Fisheries Science: 123. Oregon State University, Corvallis, OR.

water resources policy

Mary Santelmann

Hunter, ML. 2013. Water, Energy, and Ecosystem Services: A Study of Businesses in Oregon's Willamette Valley. Master of Science (MS) in Water Resources Policy & Management: 80. Oregon State University, Corvallis, OR.

applied economics

William Jaeger

Kalinin, A. 2013. Right as Rain? The Value of Water in Willamette Valley Agriculture Department of Applied Economics. Master of Science (MS) in Applied Economics: 48. Oregon State University, Corvallis, OR.

groundwater hydrology

Roy Haggerty

Neumann, PE. 2012. Shallow Aquifer Storage and Recovery (SASR): Regional Management of Underground Water Storage in Hydraulically Connected Aquifer-stream Systems. Master of Science (MS) in Water Resources Science: 37. Oregon State University, Corvallis, OR.

applied economics

JunJie Wu

Olen, B. 2012. Irrigation Choices for Major West Coast Crops: Water Scarcity and Climatic Determinants. Agricultural and Resource Economics. Master of Science (MS) in Applied Economics: 96. Oregon State University, Corvallis, OR.

snow hydrology

Anne Nolin

Sproles EA. 2012. Climate Change Impacts on Mountain Snowpack Presented in a Knowledge to Action Framework. College of Earth, Ocean, and Atmospheric Sciences. Doctor of Philosophy (PhD) in Water Resources Science: 192. Oregon State University, Corvallis, OR.

K-12 and Public Outreach

Understanding the importance of engaging and informing broader audiences about regional water issues, we also conducted activities and generated products relevant to both public education and K-12 education in water. Dr. Mary Santelmann and her graduate student, Maria Lewis Hunter, wrote a children’s book about water with illustrations both by a professional artist and art drawn by K-12 students. The student artwork was prepared under the direction of the artist through artist-in-residence sessions. The book, entitled Water was published as an eBook by the College of Earth, Ocean and Atmospheric Sciences (CEOAS), and includes a Spanish language version, Agua.

K-12 WW2100 WISE Teacher Professional Development: Addressing Emerging Issues on Water and Climate Change through STEM and Service Stewardship

We also collaborated with an Oregon Sea Grant teacher’s professional development program called WISE (Watershed and Invasive Species Education) that is co-funded by NOAA. In FY 2013-2014, we used the WW2100 project as a framework to design WISE teacher professional development. We adapted WISE teachers workshops and included new elements on framing, understanding, and using a model to ask what-if questions about water and the influences of people. Segments included:

  1. Causes of water availability through climate change, population growth, snow, and land use. Taught by Dr. Sam Chan, OSU Sea Grant

  2. Implications of the drivers of water scarcity in our watersheds: science system learning, social perspectives. Taught by Dr. Sam Chan, OSU Sea Grant

  3. Don’t be afraid of the mechanics of models and modeling (Learn how we can use models to predict future water scarcity and quality). Taught by Dr. Scott Wells, PSU Civil Engineering

  4. Let’s model! Curious about the patterns of flow, water quality and the role of humans on the Willamette River? Taught by Dr. Scott Wells, PSU Civil Engineering

  5. Modeling through a jar of jellybeans. The science of making predictions about water sustainability and climate change. Taught by Laura Ferguson, graduate research assistant, OSU CEOAS

A total of 12 teachers participated (about our capacity) over three full days of WISE workshops, including a two-day workshop (October 11-12, 2013 in Beaverton, OR) at the beginning of the school year, and a one-day workshop (May 28, Tualatin, OR) at the end of the school year to share learning activities developed by the teachers. Several of the WW2100 WISE teachers also participated in the project as teacher-researchers, attending project field trips and workshops and in some cases working with Dr. Anne Nolin’s snow monitoring research group on winter snow surveys in the Cascade mountains.

Related Publications and Links

Broader Impacts Team

  • Samuel Chan, Oregon Sea Grant
  • David Hulse, University of Oregon (UO) Landscape Architecture
  • Linda Modrell, Former Benton County Commissioner
  • Anita Morzillo, OSU Forest Ecosystems & Society
  • Mary Santelmann, OSU Water Resources Graduate Program
  • Laura Ferguson, MS Student, OSU Marine Resource Management (Graduated: 2015)
  • Maria Lewis Hunter, MS Student, OSU Water Resources Policy and Management (Graduated: 2013)
  • Adam Stebbins, Benton County
  • Maria Wright, OSU Institute for Water and Watersheds

Stakeholder Engagement

Stakeholder engagement from project inception to completion distinguished WW2100 from many other large scale biophysical and socioeconomic research projects. By engaging stakeholders in the research project, we sought to:

  • enhance advancement in science by placing a deliberate emphasis on societal relevance and adaptation,

  • provide a mechanism for regional and “boots-on-the-ground” project review, and

  • support learning and information exchange among water users, managers, scientists, and educators

To achieve these goals, we employed three strategies to reach various audiences in the Willamette River Basin throughout the project. Table 1 outlines these strategies and this web page highlights two key project components, our “Learning and Action Network” (LAN) and “Technical Advisory Group” (TAG).

Table 1. WW2100's three-level stakeholder involvement strategy.

Strategy Group Outreach and Feedback Strategy
1 Learning Action Network (LAN) - ~215 self-identified listserv participants; 120 people attended at least one WW2100 event Field trips, workshops and webinars designed to foster interaction and shared learning between researchers and stakeholders, and provide regional feedback on model and scenario design (project years 1-5; 2011-2015)).
2 Technical Advisory Group (TAG) - group of ~25 professionals chosen by Research Team based on their expertise, constituency affiliation, and representation; charged with defining assumptions of two stakeholder scenarios. Six half-day meetings in project year 5 (2014-2015), as well as phone calls, and emails on specific questions; provided specific quantities for scenario assumptions, and judgments on future land and water use policies and practices.
3 Regional Outreach – regional audiences of water managers, policy makers and the public 35 invited presentations on the Willamette water system and the WW2100 project; many invitations stemmed from connections made through the LAN and TAG.

About the Learning and Action Network

The Learning and Action Network (LAN) was our primary mechanism to encourage collaboration between scientists and stakeholders.LAN events consisted of fieldtrips, workshops, and webinars, where we encouraged dialogue about water issues in the basin, and introduced and received feedback on WW2100 modeling approaches and analysis. We invited participation in the LAN through professional contacts, and by engaging a representative working in local government (Adam Stebbins) to serve as a stakeholder liaison in the early years of the project. The LAN grew to include county commissioners, managers and scientists from state and federal natural resource agencies, farmers, K-12 educators, and representatives from water utilities, conservation organizations and industry. Over 120 people participated in at least one LAN event, which included:

  • Fieldtrips: Three daylong LAN fieldtrips in project year 1 (April, August, and September 2011) toured the upper, middle and lower Willamette River Basin (WRB). Water managers and scientists gave short presentations at field trip stops which encouraged networking and gave participants an on-the-ground view of geologic controls on hydrology, reservoir operations, fisheries concerns, restoration and water quality mitigation, and water storage and delivery for power supply, agriculture and urban uses. Over 70 people attended the three field trips.

  • Water Scarcity Discussion: A workgroup of the LAN convened in project year 1 (June 2011) to develop a stakeholder driven definition of water scarcity. The session paralleled an effort among the research team to develop a formal academic definition of the concept (Jaeger, et al., 2013). The LAN group’s goal was to develop a plain language definition that reflected regional concerns about biophysical and human constraints on water availability. They reached consensus on the following definition, “Water scarcity occurs when there is not an affordable, attainable and reliable source of clean water when and where it is wanted or needed by humans, animals and plants, currently and into the future.”

  • Focus Group Discussions: We convened six focus groups in project year 2 (May 2012) to establish a baseline of knowledge, needs, networks, and expectations around water sustainability and scarcity in the WRB. The focus groups clustered participants by geography and perspective as managers or research scientists. Seventy-one people participated.

  • Workshops: In years 2-6 we held annual LAN forums where we invited the LAN to review and provide feedback on the model design, data sources, and draft scenario assumptions of the WW2100 modeling effort. Attendance at each forum ranged from 36-74 people. Pre and post surveys on expectations, information needs and knowledge gain were conducted at each of the annual forums.

  • Webinars: In years 3-5 we held 12 webinars focused on different project components, from regional climate projections to modeling land use change. These webinars provided background information on particular components of water supply and demand, and featured related research that influenced development of WW2100 modeling components. The webinars were each attended by an average of 50 people made up of both the research and LAN communities.

  • Electronic Mailing List: Our LAN email distribution list grew to 215 self-subscribed participants. Notices to the listserv included invitations to LAN events, summary newsletters of workshop activities and outcomes, and topical research and news stories.

  • Dialogue: Members of the LAN were encouraged to and felt comfortable calling the BIT to provide input on data, share concerns and suggestions. This provided an additional trusted avenue of informal and formal dialogue between the LAN and the research team.

About the Technical Advisory Group (TAG)

Beginning in project year 5 (Fall 2014) we invited a core group of 25 citizen stakeholders to participate in a series of half-day meetings to define the assumptions for two stakeholder scenarios. Called the Technical Advisory Group (TAG), members were affiliated with municipal, county, state and federal agencies, tribes, agricultural and forestry interests, industry, public utilities, irrigation districts, and farmers. These individuals were approached by the research team and asked if they would volunteer to serve on the TAG. We recruited TAG participants based on the depth and breadth of their knowledge of water issues in the WRB, and for their capacity to represent the broad range of sectoral and geographic water use and management interests and past participation. Many of these eventual TAG members had participated in LAN events in project years 1-3.

Within the larger WW2100 effort, the group’s charge was to define the driving assumptions of two future scenarios. The TAG chose to create scenarios in which multiple scenario characteristics varied at the same time. Early TAG discussions centered on the unifying theme or scenario name that would distinguish one TAG scenario from the other. The TAG ultimately chose the names Extreme and Managed Case for their two scenarios.

Scenario assumptions were defined by specifying the particularities for each of the nine key scenario elements the TAG believed best represented an Extreme versus a Managed Case water availability future (shown in Figure 3c-1). These TAG scenario definition decisions were made by consensus, with each meeting facilitated by a Research Team member. Meetings frequently included presentations by research team members to explain the technical background of the WW2100 Envision model and to present in-process results of research team scenarios, as they became available.

Reflections on the WW2100 Stakeholder Engagement Process

Here we reflect on the successes and challenges of our effort to involve regional stakeholders in an academic research project. This reflection is partially informed by results from a formal assessment of the WW2100 stakeholder engagement process that wass the subject of an OSU master’s thesis (Ferguson, 2015). Ms. Ferguson conducted semi-structured interviews and a detailed online survey to characterize and assess expectations and outcomes from researchers and stakeholders who participated in the LAN and TAG.

We present this reflection in the context of three goals developed by the broader impacts team, the group of researchers that led stakeholder engagement activities. By involving regional water managers and users in the project, we sought to:

  • enhance advancement in science by placing a deliberate emphasis on societal relevance and adaptation,

  • provide a mechanism for regional and “boots-on-the-ground” project review,

  • support learning and information exchange among water users, managers, scientists, and educators in the Willamette River Basin (WRB).

 

Goal 1: enhance advancement in science by placing a deliberate emphasis on societal relevance and adaptation

LAN and TAG meetings did lead to meaningful discussions about regional water policy that influenced the scope and direction of the project. For example, a LAN meeting in May 2012 generated a list of specific water management policies that attendees felt were regionally relevant, and that they wanted to see incorporated into WW2100 modeling and scenarios. The research team then considered each suggestion and where possible adapted model design to accommodate the suggestions. The TAG process – where a group of representative stakeholders designed the constraints for two multivariable scenarios – is another example of how stakeholder knowledge informed the research process. The TAG designed the thematic direction and assumptions for the Extreme and Managed scenarios, and in the process also influenced the direction of many of the single variable human dimensions scenarios.

However, there was also tension among participants about the role that stakeholders should play in the research process. Some researchers came from traditions and disciplines that placed a strong emphasis on the value of local knowledge. Others raised concerns about the institutional bias that stakeholders might bring, or had little experience working on teams with non-academic partners. In interviews with researchers and stakeholders, Ferguson (2015) found that the most prevalent challenge mentioned during interviews was diversity of visions for the project. This manifested both within the research team and in the stakeholder engagement aspect of the project, as participants pursued different research or stakeholder engagement goals. Other project challenges mentioned by interviewees included: the logistical difficulties of coordinating so many people, the complexity of the modeling endeavor in and of itself, interpersonal differences among participants, and the challenge of merging research styles from different disciplines.

The technical challenge of modeling such a complex system led to frustration for some LAN and TAG participants. Development of the model took longer than expected, and this reduced the time and project emphasis placed on the evaluation of policy alternatives and adaptation strategies to mitigate future water scarcity. For example, stream water temperature played an important role in early LAN discussions, because it affects regulatory requirements to protect endangered fish. Yet by project year 5, the research team had not been able to incorporate stream temperature into the integrated model in the way they had hoped.

Analysis scale was another source of tension between researcher and stakeholder goals. The complexity of the model meant that much of the analysis and interpretation focused at the scale of the entire Willamette watershed, while stakeholder questions and interest often focused on the more localized scale where their management decisions played out. In TAG meetings, participants suggested that analyses at a sub-basin scale could be one direction for future research.

Despite these challenges, Ferguson’s interviews showed that LAN and TAG participants felt that they had contributed to building the model and that the completion of an integrated water model for the basin was a great success for the project. Her survey also showed that participation was positively correlated with participants’ perceptions of feeling heard (rs = .36, p < .001) and valuing the stakeholder engagement process (rs = .39, p < .001).

 

Goal 2: provide a mechanism for regional and “boots-on-the-ground” project review

We found that LAN workshops created useful checkpoints where researchers could present progress and receive feedback. This feedback sometimes led to explicit model adjustments, for example, changes in assumptions about farmer planting dates, and careful consideration about how to incorporate Bull Run, the large water source outside the WRB for the city of Portland (Ferguson et. al., 2014). But LAN engagement also sometimes led to frustration, when researchers could not or would not adjust assumptions or model components to match stakeholder experience. This frustration sometimes stemmed from the different perspective of researchers and stakeholders. For example, a sub-group of project researchers developed a model for urban water demand that was guided by the academic literature in economics and, based on this literature, identified water price and household income as the greatest determinants of future residential water demand. But some representatives from urban water providers felt that this model did not adequately represent the influence of water conservation education and technology, or the declines in per capita water demand they had observed in recent decades.

The complexity of Envision and its modeling components also hindered the regional review process. Pre- and post-event surveys showed that participants came away from LAN meetings with a much greater understanding of modeling components (IWW, 2012; Ferguson, 2015). But some participants felt that it was unrealistic for them to provide meaningful feedback within the one-day, large group format of the annual LAN meetings. Researchers responded to these concerns with follow-up correspondence and meetings, by developing workshop summaries, and by creating an online FAQ document (IWW, 2012; IWW, 2014; Ferguson et. al., 2014).

The format of the TAG process also helped address these concerns. By involving fewer participants (25) and more frequent (six roughly monthly) half-day meetings, it provided more opportunities for participants to ask questions and share their diverse perspectives. Questions about the limits of the WW2100 model, understanding of the larger Willamette water system, and what constituted Extreme versus Managed futures, prompted further inquiries and conversations between TAG meetings and related model refinements. These questions also led to what several TAG members described as, for them, among the most educational parts of the TAG process.

One of the benefits of the stakeholder engagement process is that it created awareness about the project among regional water managers. Ferguson’s survey showed that active participants in the WW2100 stakeholder engagement process understood the Willamette Envision model better and found the model to be more useful. In the survey, participation was positively correlated with survey respondents’ perception of the Willamette Envision model’s utility (rs = .32, p = .002) and understanding of the Willamette Envision model (rs = .42, p < .001). Interviewed stakeholders also expressed that through the process they gained an understanding of the model and other water users. They also found the Willamette Envision model more credible than they may have otherwise and implied that they could serve as project ambassadors, sharing the information with their colleagues.

 

Goal 3: Support learning and information exchange among water users, managers, scientists, and educators in the WRB.

In Ferguson’s analysis, the most frequently mentioned outcome of the stakeholder engagement was that participants were learning and had an overall positive experience. Interviewed stakeholders valued the process for the opportunity to build relationships with diverse water users, regulators, and researchers and to begin a constructive dialogue about planning now for possible water availability constraints in the future. Some example interview comments included, “I would say that the discussions and the relationship-building have been more beneficial to me than the actual nitty-gritty numbers that it produces,” and “I think just even having that dialogue amongst the users was probably one of the most successful parts of the project.”

We believe that two key factors enabled these learning successes. First, the goal to develop an integrated model of the Willamette water system created a forum for sharing different regional and sector perspectives. The topic of anticipating water scarcity drew the interest of individuals in many different water-related sectors, and provided an opportunity for different types of water users to learn about and consider how the water system is interconnected. The project’s broad geographic scale and long modeling horizon also freed participants to think about big picture connections. Second, because this was a research project, led by university partners, it created a neutral forum not tied to specific agency perspectives or a short-term management objective. Many stakeholders commented that they had enhanced their whole basin perspective by engaging in WW2100, and that they had few other professional opportunities to build that perspective.

Epilogue

As educators, we count the learning fostered by the stakeholder engagement process as among the greatest successes of the project, and we hope that it will enhance stewardship of water resources in the basin over the long term. WW2100 was an ambitious biophysical and socioeconomic modeling project that emphasized stakeholder participation as a central way of working. Stakeholder engagement in science is not a new concept. The engagement of researchers and stakeholders in discussions and decision making from project initiation to completion sets WW2100 apart in that the process is itself an experiment. Many examples can be cited on how stakeholder input was incorporated into the model. Examples can also be cited on how stakeholders’ thinking was enhanced by working with the researchers and engaging people from different sectors around a common theme.

The project revealed that there are needs and questions around water scarcity, climate change, people, policies, and land uses beyond the scope of the project. With many of the results and their interpretation coming only in the latter half of the fifth and final year of the project, we simply ran out of resources (time and funding) to address the many uses that researchers and stakeholders see as valuable from the project. A final stakeholders’ workshop served as a forum for elucidating, prioritizing, and discussing a future action plan. At this meeting, stakeholders identified such unfulfilled research needs such as integrating fish life history with a temperature model, new ways to explore and predict urban water demand that might include conservation and different infrastructure pricing, anticipating additional drivers to farming and irrigation practices, more in-depth analysis on the impacts of water policies, and perhaps even the role of changing water storage capacity in the basin.

Our project is among the first to describe and analyze the engagement process from project inception to completion. We were not perfect. However, our research of the process has revealed that engagement in science from inception to completion provides a societally relevant peer-review process, one that stimulates critical thinking on the applications and needs for water science.

Related Publications & Links

  • Ferguson L, Chan S, Santelmann M, Tilt B.  2016.  Exploring participant motivations and expectations in a researcher-stakeholder engagement process: Willamette Water 2100Landscape and Urban Planning. 157:447–456.

  • Ferguson LB.  (2016).  Collaborative science-stakeholder engagement: An annotated reference guide for scientific engagement with natural-resources practicioners (ORESU-H16-001). Corvallis, Oregon: Oregon Sea Grant.

  • Ferguson LB.  (2015).  Characterizing and Assessing the Researcher-Stakeholder Engagement Process for Water Sustainability: The Willamette Water 2100 Project. Oregon State University, Corvallis, Oregon.

     

  • Summary materials from LAN events:

    • LAN Workshop - December 4, 2015 - Salem, Oregon - Workshop Summary (PDF iconmeetingsummary_12_4_15.pdf) - This workshop shared key stories that have emerged over the project's five years, and sought feedback from stakeholders on applying and communicating project findings.

    • LAN Workshop - March 18, 2014 - Salem, Oregon - Workshop Summary (PDF iconmarch2014_summary_7_15_14s.pdf) - This workshop described the WW2100 modeling framework, and introduced early findings from the Reference scenario, a model of future water availability under expected trends in population and income growth, existing policies and institutions, and a mid‐range climate change scenario.  See also the online FAQ document researchers created following the workshop (PDF iconww2100_faq_march2014.pdf).

    • Small-group LAN Workshop - February 22, 2013, Salem, Oregon - This workshop brought together 25 stakeholders to provide feedback on elements and assumptions of the Reference Case scenario (the initial modeling scenario) and to provide feedback on metrics designed to evaluate and compare modeling scenarios.

    • LAN Workshop - May 9, 2012, Salem, Oregon - Workshop Summary (PDF iconmay2012summary_7_28_12.pdf) - The workshop was an opportunity to learn about and to provide feedback on the project’s effort to model the Willamette water system and to help the project research team understand the current and future water issues facing basin stakeholders and public agencies.

    • Lower Willamette LAN Field Trip - September 23-24, 2011 - Fieldtrip Materials (PDF iconseptember23-24_2011_lowerwillametteguide.pdf) - This trip focused on water supply for municipal, industrial and power generation in the Portland Metropolitan area. Participants visited the Tualatin River Basin on the first day with stops at Hagg Lake, the major reservoir on the Tualatin system, the Joint Water Commission water treatment plant in Forest Grove, and riparian and wetland restoration projects near Forest Grove. Participants also attended a lecture by Dr. Heejun Chang on his hydrologic modeling work for the Tualatin River Basin. On the second day, participants joined the annual Clackamas River Watershed Tour hosted by the Clackamas River Water Providers. This tour focused on forest management, hydropower generation and waste water treatment in the Clackamas River Basin.

    • Small group LAN Workshop - Albany, Oregon (PDF iconww2100_lanwaterscarcity_definition_june2011.pdf)- The goal of this workshop was to develop a plain language definition of water scarcity that resonated with workshop participants.

    • Middle Willamette LAN Field Trip - August 4, 2011 - Fieldtrip Materials (PDF iconaugust4_2011_fieldtrip_guide.pdf) - This trip focused on issues related to temperature TMDLs, operation of water control districts, and groundwater supply and use. Stops included the Talking Water Gardens in Albany, sites in the Santiam Water Control District near Salem, and presentations by OWRD groundwater geologists.

    • Upper Willamette LAN Field Trip - April 21, 2011 - Fieldtrip Materials (PDF iconapril21_2011_fieldtrip_guide.pdf) - This trip highlighted issues related to floodplain restoration, reservoir storage, and dam operations with stops at Green Island, Leaberg Dam, Lookout Point Reservoir and Fern Ridge Reservoir.

Broader Impacts Team (alphabetical)

  • Samuel Chan, Oregon Sea Grant

  • David Hulse, University of Oregon (UO) Landscape Architecture

  • Laura Ferguson, MS Student, OSU Marine Resource Management (Graduated: 2015)

  • Maria Lewis Hunter, MS Student, OSU Water Resources Policy and Management (Graduated: 2013)

  • Linda Modrell, Former Benton County Commissioner

  • Anita Morzillo, OSU Forest Ecosystems & Society

  • Mary Santelmann, OSU Water Resources Graduate Program

  • Adam Stebbins, Benton County

  • Maria Wright, OSU Institute for Water and Watersheds

References

Ferguson LB.  (2016). Collaborative science-stakeholder engagement: An annotated reference guide for scientific engagement with natural-resources practicioners (ORESU-H16-001). Corvallis, Oregon: Oregon Sea Grant.

Jaeger, W. K., Plantinga, A. J., Chang, H., Dello, K., Grant, G., Hulse, D., ... & Mote, P. (2013). Toward a formal definition of water scarcity in natural‐human systems. Water Resources Research, 49(7), 4506-4517.

IWW. (2014). Workshop Summary. WW2100 Learning and Action Network Workshop, March 18, 2014, Salem, Oregon.

IWW. (2012). Workshop Summary. WW2100 Learning and Action Network Workshop, May 9, 2012, Salem, Oregon.

page authors: Wright, Ferguson, Hulse, Chan
last updated: January 2016

Hydrologic Modeling Course

During Spring 2013, faculty working on the Willamette Water 2100 offered a graduate level course on hydrologic modeling.  The course provided an introduction to many of the different types of hydrologic models used in the project, and provided hands-on experience working with the project's modeling framework, Envision.  The course was led by Dr. Mary Santelmann and Dr. Kellie Vache at OSU, and facilitated by Dr. Scott Wells as PSU.  Lectures and labs were taught via video-conferencing with students and lecturers on both campuses.  The course lectures were video recorded.  Below are descriptions and links to these videos -- they provide a great introduction to Envision and some of the component models utilized in the project.

modeling-image

Week 1:

  • April 2, 2013 - Dr. Mary Santelmann, OSU Water Resources Graduate Program  - Course Overview - Introduction to WRE599/CE410/510 and background on the Willamette Water 2100 project and Envision.
  • April 4, 2013 - Dr. John Bolte, OSU Biological and Ecological Engineering - Introduction to Alternative Futures Analysis and Envision.

Week 2:

  • April 9, 2013 - Dr. Kellie Vache, OSU Biological and Ecological Engineering - 1) More on Envision with an example from Puget Sound; 2) an introduction to Willamette Water 2100 and its plug-in models in Envision; 3) introduction to some Envision definitions - IDU, reach, etc.
  • April 11, 2013 - Dr. John Bolte, OSU Biological and Ecological Engineering - More about Envision, include an explanation of "policies" in Envision and an example of how they are set up and run. The example focuses on population growth and allocation using the plug-in "Target".

Week 3:

  • April 16, 2013 - Dr. Kellie Vache - 1) brief introduction to the climate data used in WW2100; 2) Introduction to hydrologic modeling concepts with a focus on HBV, the hydrologic model used in FLOW, the hydrologic modeling framework in Envision.
  • April 18, 2013 - Dr. Mary Santelmann - Discussion of scenario narratives and the class assignment given to students to write a scenario narrative for a sub-basin in the Willamette.
  • April 19, 2013 - Dr. Kellie Vache - Introduction to FLOW, the hydrologic modeling framework developed for Willamette Water 2100. 1) Background on why it was developed, 2) Key elements and spatial configuration, 3) Intro to XML input files 4) Explanation of hydrologic response units, 5) FLOW plug-ins with an emphasis on HBV, and 6) example videos of FLOW output.

Week 4:

  • April 23, 2013 - Dr. Heejun Chang, PSU Geography  - 1) Overview of PRMS 2) A case study of his work with PRMS in the Willamette Basin to anticipate the affect of climate change in the Willamette Basin.

Week 5:

  • April 30, 2013 - Dr. Anne Nolin, OSU Earth, Ocean & Atmospheric Sciences - Introduction to snow accumulation and melt, the significance of snow in hydrology, and an introduction to snow modeling.
  • May 2, 2013 - Dr. Anne Nolin - 1) Snow modeling in HBV and potential shortcomings; 2) snow monitoring in Willamette Water 2100 and related projects and 3) the use of SnowModel in the project and related projects.

Week 6:

  • May 7, 2013 - Dr. Roy Haggerty, OSU Earth, Ocean & Atmospheric Sciences - Introduction to groundwater modeling, finite differences, introduction to a class exercise to demonstrate finite difference modeling using Google Docs.
  • May 9, 2013 - Dr. Roy Haggerty - Continuation of class exercise to demonstrate finite difference modeling using Google Docs. Introduction to MODFLOW.

Week 7:

  • May 14, 2013 - Dr. Desiree Tullos, OSU Biological and Ecological Engineering - Overview and background on the USACE Willamette Project dams. 2) Introduction to reservoir operation terminology and operating procedures.
  • May 16, 2013 - Dr. Desiree Tullos - 1) Continued overview of USACE Willamette Project including, irrigation, recreational benefits, environmental flows. 2) Introduction to the 2008 Biological Opinion affecting Willamette River operations 3) Introduction to ResSIM and 4) Modeling reservoir operations in Willamette Water 2100 using ResSIM "Lite".

Week 8:

  • May 21, 2013 - Dr. Scott Wells, PSU Civil & Environmental Engineering - Introduction to surface water quality and hydrodynamic modeling. 1) what is a model and why use one 2) example uses of models 3) about hydrodynamics 4) water quality models.
  • May 23, 2013 - Dr. Scott Wells - Introduction to CE-QUAL-W2 - the model developed by the USACE for hydrodynamic and water quality monitoring. Topics include: computing requirements, data preparation, boundary conditions, model components, model verification and an example from Detroit Reservoir in the Willamette Basin system.

Weeks 9-10:

  • May 28, 2013 - Review and critique of the WW2100 project by WRE 599 students. This review was carried out in the style of a NSF review panel. Students answered evaluative questions and provided feedback that reflected what they had learned about the project and Envision over the 10 week course. Students worked in small groups, and this video includes presentations by each small group at OSU and PSU.
  • Group Project Presentations - WRE 599 group project presentations. Students worked in small groups to develop and run futures scenarios for sub-basins in the Willamette Basin using a preliminary version of Envision with the hydrologic modeling framework FLOW. Students presented outcomes from their group work in these videos. 
    • May 30, 2013 - Presentations by students who worked in the Blue River Watershed and on the McKenzie Watershed.
    • June 4, 2013 - Presentations by students working in the  Santiam Watershed and on the Johnson Creek Watershed.
    • June 6, 2013 - Student presentation on the Yamhill Watershed and a course wrap up presented by Mary Santelmann highlighting some of the accomplishments and lessons learned during the course.

    Children's Water Book

    Download English version in PDF format | Download Spanish version in PDF format

    About the Book

    Members of the Willamette Water 2100 team developed a children's book about water and water resources. It addresses issues such as where water comes from, what we use water for, water scarcity, and climate change. The book also contains artwork and poems created by students who live in the Willamette River Basin, as well as suggestions for water-related classroom science activities. The text is available in both English and Spanish.  We compiled book content from publicly available information from the USGS on water and climate. A curriculum specialist, Angela Ruzicka, and three K-12 teachers provided feedback on the relevance and appropriateness of the text for middle and high school students.

    Acknowledgements

    Text by Maria Lewis Hunter, Sam Chan and Mary Santelmann

    Illustrations and poems by students from South Eugene High School, Eugene, Ore.; Kennedy Alternative School, Cottage Grove, Ore.; Garfield Elementary School, Corvallis, Ore.; Oregon State University, Corvallis, Ore.; and professional artist Jennifer Mercedes

    Translation for Spanish language version by Paula Jiménez-Arango and Ricardo González-Pinzon

    Design and Layout by Crystal Barnes, College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, Ore.

    We thank Julia Harvey, Vickie Costello, and Valerie Boggs, the teachers of the K-12 classes that allowed us to work with their students to produce much of the art in this book. We thank our colleagues Thea Hayes and Angela Ruzicka for reviewing and commenting on the text and for their suggestions and edits to the book.

    Seminars and Webinars

    WW2100 hosted a series of webinars about project related topics and components.  Follow the links below to access recordings of these events.

    Recorded Webinars

     

    More Details About Previous Webinars and Recorded Seminars

    September 28, 2015

    Characterizing and Assessing the Researcher-Stakeholder Engagement Process for Broader Impacts: The Willamette Water 2100 Project

    Presenter: Laura Ferguson, M.S. Candidate in Marine Resource Management

    Advisor: Dr. Sam Chan (Oregon Sea Grant, Fisheries and Wildlife)
    Committee: Dr. Mary Santelmann (Water Resources, CEOAS) and Dr. Bryan Tilt (Anthropology)

    View recording on OSU Media Space

    Abstract: Natural resource management and policy is ideally informed by the best available science. Natural resource researchers ideally participate in broader impacts activities to extend the reach of their best available research. Researcher-stakeholder engagement is one proposed solution to overcome barriers to integrating science and management and to achieve both broader impact and science-based policy goals. Literature has documented many researcher-stakeholder engagement process case studies where researchers offer lessons learned and speculate on their impacts, but few offer data on the engagement process structure, the stakeholder perspective of the engagement process, or the impacts of collaboration between academic research teams and scientific stakeholders. This work addresses these gaps by taking a closer look at how one team of researchers engaged with its stakeholders and voicing the perceptions of stakeholders in addition to researchers. Twenty-six semi-structured interviews and an online survey (n=137) were conducted for an in-depth case study of participant motivations to, expectations for, participation in, and outcomes of Willamette Water 2100. Researchers and stakeholders were motivated to participate for social, knowledge, and utility reasons and held different expectations for the roles they would play, the researcher-stakeholder engagement process itself, and the resulting research results. Four types of challenges were identified: lack of a shared vision, differing professional languages, research complexities, and project management. Participants identified successful outcomes including: overcoming challenges, facilitating learning, greater understanding, conversation among diverse perspectives, and improving and extending research results. Researcher-stakeholder engagement in natural resource research can create more relevant science and achieve scientific broader impact goals. This research offers novel evidence of researcher-stakeholder engagement impacts and proposes more specific criteria for broader impact activity evaluation. This research was part of the Willamette Water 2100 project.

    --

    May 5, 2015

    Optimizing reservoir operations to adapt to climate and social change in the Willamette River Basin, Oregon

    Presenter: Ms. Kathleen Moore, Ph.D. Candidate in Geography
    Doctoral Advisors Dr. Julia Jones (Geography, CEOAS) and Dr. William Jaeger (Applied Economics)

    View recording on OSU Media Space

    Abstract: Reservoir systems in the western US are managed to serve two main competing purposes: to reduce flooding during the winter and spring, and to provide water supply for multiple uses during the summer. Because the storage capacity of a reservoir cannot be used for both flood damage reduction and water storage at the same time, these two uses are traded off as the reservoir fills during the transition from the wet to the dry season. Climate change, population growth, and development may exacerbate dry season water scarcity and increase winter flood risk, implying a need to critically evaluate reservoir operations. Focusing on the Willamette River Basin, Oregon, we used a dynamic programming approach to social welfare maximization, and derived the optimal reservoir fill path for both historical conditions and future scenarios of climate and social change. Anticipated future increases in winter flood risk and reductions in spring streamflow led to an optimal fill path in which reservoir fill began earlier and proceeded more slowly, compared to the optimal fill path derived under historical conditions. The analysis finds that increased value of stored water associated with increased demand for reservoir recreation or irrigation water for agriculture will shift the initiation of optimal reservoir fill to an earlier date and increase the likelihood of achieving full pool by the end of May. Conversely, an increase in the costs of flooding driven by land use change and development in the floodplain associated with increasing population led to an optimal fill path in which reservoir fill began later and the final optimal reservoir fill level was decreased, compared to the optimal fill path under historical conditions. These findings may contribute to policies for adapting reservoir management to future changes in water supply and demand.

    --

    Wednesday, November 5, 2014, 1-2 pm -  

    Climate Change And Upland Forest Dynamics In The Willamette River Basin, Dr. David Turner, Department of Forest Ecosystems & Society, Oregon State University. 

    View recording on OSU Media Space

    As the potential magnitude of anthropogenically-driven climate change becomes clearer, it is increasingly desirable to anticipate impacts of projected climate change on forest ecosystems and forest landscapes. Notable impacts of climate change on forests will include alteration of the disturbance regime, changes in tree species composition, and shifts in the geographic distribution of vegetation types. These potential impacts have been studied using climate change scenarios and a variety of empirical or process-based modeling approaches, but projections of climate change impacts have generally not included the role of land use. For the Willamette Water 2100 Project, we have applied an agent-based landscape simulation model (Envision) to assess potential climate change impacts in the Willamette River Basin (WRB). Envision accounts for harvesting, fire, and land use change. To incorporate climate change impacts, we have integrated it with results from a dynamic global vegetation model (MC2), driven by climate scenarios developed for the 5th IPCC report. Our goal is to evaluate the sensitivity of forest area, biogeography, rates of fire, rates of harvest, and forest age class distribution to three climate change scenarios. The related influences on basin-wide evapotranspiration are also being simulated and are of interest in evaluating the future WRB water budget.

    --

    October 8, 2014

    Modeling the Human Side of Water Scarcity in the Willamette Basin, Dr. William Jaeger, Professor, Department of Applied Economics, Oregon State University.

    View recording on OSU Media Space

    To predict the when, where, and how of future water scarcity in the Willamette Basin we have developed a model that integrates natural system components of water supply with the human system components of water demand. Constructing an economic model for the human side of this system presents a number of challenges. Some of these are different from and others are similar to the challenges faced by those modeling the biophysical system components.

    This seminar will describe some of those challenges, and explain how we have tried to address them. We’ll describe the models we have constructed for agricultural water use and urban water use. These two models have empirical and theoretical underpinnings, and they have strong similarities as well as important differences. In both cases, the models represent powerful tools for addressing questions about future water scarcity: first, they provide a basis for predicting how the demand for water will grow in the future as human and natural systems change; second, these same models represent a way to quantifying the impact of water availability on social values in terms of the costs or benefits of changing water scarcity, as well as the costs and benefits of policy actions aimed at mitigating water scarcity.

    --

    Thursday, May 22, 2014, 2-3 pm -  

    Third time's the charm: the 2014 U.S. National Climate Assessment Report, Dr. Philip Mote, Director, Oregon Climate Change Research Institute. 

    In 1990, Congress passed the U.S. Global Change Research Act which among other things calls for an assessment report every four years. On May 6, the President’s Administration released the third National Climate Assessment. This report is by far the most comprehensive, with 30 chapters covering climate change impacts on various regions and sectors, as well as adaptation and mitigation.  The report emphasizes that climate change is already noticeable and affecting Americans in a variety of ways, and presents fascinating depth and breadth of evidence.  Dr. Mote co-authored the report’s Northwest chapter and served on the report's advisory committee.  In this seminar, he gave an overview of the assessment and its findings.

    The webinar was co-sponsored by the Geography program in the College of Earth, Ocean, and Atmospheric Sciences, the Oregon Climate Change Research Institute, and the Willamette Water 2100 Project.

    The video of Dr. Mote can also be viewed on OSU Media Space.

    Wednesday, December 18, 2013, 10-11 am -  

    Potential Responses of Native and Non-native Fish Communities to Thermal Changes in the Willamette River, Dr. Stan Gregory, Oregon State University.

    The video of Dr. Gregory can also be viewed on OSU Media Space.

    Friday, May 17, 2013 12-1 pm -  

    Willamette River Basin Hydrodynamic and Temperature ModelingScott Wells, Civil and Environmental Engineering, Portland State University.

    View PDF of presentation.

     

    Friday, April 26, 2013 12-1 pm -   

    Modeling ecohydrologic processes in mountain watersheds—implications for the Willamette Watershed, Naomi (Christina) Tague and Elizabeth Garcia, University of Santa Barbara, Bren School of Environmental Science and Management.

     

     

    Thursday, March 21, 2013 1-2 pm - Will We Have to Change the Rules? The Implications of Climate Change for Reservoir Operations at Oregon's Cougar Dam, Thesis Defense by Allison Danner, MS Candidate in Water Resources Engineering.  Thesis advisor: Gordon Grant, US Forest Service and Courtesy Professor, Departments of Geosciences, Forest Engineering, Resources & Management, and Forest Ecosystems & Society.

     

    Friday, March 1, 2013 12-1 pm - Flood Frequency and Water Scarcity in the Santiam Basin in a Changing Climate, Desiree Tullos, Associate Professor, Biological and Ecological Engineering, Oregon State University.  View recording on OSU Media Space.

     

    Friday, February 8, 2013 12-1 pm, OSU Campus - Land-use Models for Willamette Water 2100, Andrew Plantinga, Professor of Environmental Economics, Bren School of Environmental Science and Management and Courtesy Faculty, Department of Agricultural and Resource Economics, Oregon State University.  View recording on OSU Media Space.  View recording on OSU Media Space.

     

    Friday, January 25, 2013 12-12:50 pm, OSU Campus - Development of Regional Climate Scenarios and Their Application to Willamette Water 2100, Phil Mote, Director, Oregon Climate Change Research Institute.  View recording on OSU Media Space.

     

    Friday, January 11, 2013 12-1 pm, OSU Campus - Mountain Snowpack and Vegetation: Implications of Disturbance, Anne Nolin, Professor, College of Earth, Ocean and Atmospheric Sciences.  View recording on OSU Media Space.

    Slide Set for Students

    The WW2100 broader impacts team developed a slide set for students about the water cycle in the Willamette Basin. The slide set helps students think about where the water we use comes from, and the factors that affect its availability and quality. The slide set is designed for students grade eight and above and includes:

    • Specific examples of ways natural and human processes affect water supply and demand in the Willamette Basin.
    • A list of the specific Next Generation Science Standards addressed.
    • Suggestions for pre- and post-quiz questions to determine the content's effect on student understanding and opinions related to water.

    Downloads

    Related Resources

    Data & Simulations

    Downloads

    Empirical Data

    The following observational data sets were collected as part of the WW2100 project. Some of these data sets were used in development of plug-in models for Willamette Envision, others informed detailed, topic specific studies. Click on data set titles to access data and metadata, including links to related publications.

    • Snow and forest canopy - Transect and site based snow, forest canopy, and meteorological data collected during the winters of 2011-2012 through 2015-2016 within the McKenzie and Middle Fork River Basins of the Oregon Cascades. Data were collected at open and forested sites in the low-, mid- and high seasonal snow zones.
    • Snow following forest fire - Snow water equivalent, snowpack surface debris concentrations, and micrometeorological conditions over snow in burned and unburned forest sites for three years following fire.  Data collected in the McKenzie River Basin for the years 2012-2014.
    • Land values - Parcel-level land use and land value data collected for randomly drawn samples of developed, agricultural, and forest land parcels in Benton, Lane, Marion, and Washington Counties for the years 1973, 1980, 1986, 1992, and 2000.  Data were used in development of the land-use transitions modeling component of WW2100.  
    • Irrigation survey - Data about irrigation decisions and crop choice collected through a survey of 530 Willamette valley farmers.  The survey was implemented in 2012 by the USDA National Agricultural Statistics Service.  Survey data informed development of the irrigation and crop choice modeling components of WW2100.
    • Willamette river fish - Fish sampling data collected at 167 Willamette River sites (96 mainstem and 71 sloughs) between 2011-2013.  The data were archived as part of the Willamette Fish Database, a comprehensive database of fish collected by Oregon State University and the Oregon Department of Fish and Wildlife in the Willamette River.
    • Water users survey - Mail survey of 1402 land owners in portions of Washington, Yamhill, Marion and Lane Counties. The survey gathered information about perceptions and priorities for water use and management, sociodemographics, and environmental world view. Contact Anita Morzillo for more information about this dataset.

     

    Willamette Envision Code and Model Inputs

    Willamette Envision code and data inputs to run Willamette Envision can be downloaded here. The version of the code archived here is version 331 from the ww2100svn subversion repository.  This version generated model outputs called WW2100 3.0.  

    Modeling Inputs Description Downloads Related Documentation
    Stream Network Attributed line network used in hydrologic modeling. The line network is based on the National Hydrography Dataset version 2 (NHD+V2). Streams.zip (3.5 MB) Streams_description.zip
    Integrated Decision Units (IDUs) Attributed map polygons that characterize the landscape and store data used by Willamette Envision.   IDU.zip (113.7 MB) IDU_description.zip
    Climate Forcings Climate forcings for WW2100 scenarios were from the University of Idaho MACAv1-METDATA. For more details about the process used to select and downscale climate projections used in Willamette Water 2100, refer to the section of this website on climate modeling. http://maca.northwestknowledge.net  
    Willamette Envision Code and Related Input Files Model code and data inputs needed to run Willamette Envision.  The version of the code archived here is version 331 from the ww2100svn subversion repository. This version of the code generated model outputs called WW2100 3.0.  The model output and analysis on this website is derived from this version of the model code.  WW2100_3.0.zip
    (42.3 GB; note large file size!)
    WillametteEnvision_description.zip

     

    Willamette Envision Model Outputs

    Model outputs for WW2100 3.0 can be downloaded here, grouped by scenario.  WW2100 3.0 output was generated during summer and fall 2016 by Willamette Envision code version 330 and 331. Refer to the description files (linked from the table below) for details about each data set.  Four types of data can be downloaded:

    • Tabular output - 142 comma delimited files containing annual and daily values of model output such as basin-wide land use land cover trends by year, and daily values for stream discharge at specific locations. Output spans the range of sectors modeled with Willamette Envision. 
    • Decadal shapefiles - Attributed shapefiles of IDU map polygons, the spatial modeling unit used by Willamette Envision.  Many of the attributes are calculated as the model runs.  The shapefile for each decade includes attribute values for the last day of each decade of the simulation (e.g. December 31, 2019; December 31, 2029 etc.).
    • Binary outputs - The binary data includes values for each IDU map polygon and stream reaches for each day of the simulations (e.g. January 1, 2010-December 31, 2099). Types of output includes land cover, SWE, ET, precipitation, and stream discharge.  Binary data is available for eight WW2100 scenarios.
    • Cascade plots - Graphical summaries of model outputs for selected scenarios.  These plots were generated by Dr. Roy Haggerty using python scripts and tabular (csv) output from Willamette Envision 3.0 model runs.

     

    Modeling Scenario
    (Refer to the scenarios web page for a description of WW2100 modeling scenarios.)

    CSV Files
    (data file size: ~40 MB)

    Decadal Shapefiles
    (data file size: ~960 MB)

    Binary Data
    (data file size: ~200 MB)

    Cascade and Maplots

    Related Documentation CSV_description.zip decadal_description.zip binary_description.zip cascade_description.zip
    All Scenarios All.zip (837 MB) All_maps.zip (20 GB) All_binaryData.zip (1.6 GB)

    CascadePlots.zip (74 MB)

    SubbasinPlots.zip (11 MB)

    Reference Case (Ref) Ref.zip  Ref_maps.zip Ref_binaryData.zip  
    High Change Climate (HighClim) HighClim.zip HighClim_maps.zip HighClim_binaryData.zip  
    Low Change Climate (LowClim) LowClim.zip LowClim_maps.zip LowClim_binaryData.zip  
    High Population Growth (HighPop) HighPop.zip HighPop_maps.zip    
    Upland Wildfire Suppression (FireSuppress) FireSuppress.zip FireSuppress_maps.zip FireSuppress_binaryData.zip  
    Relaxed Urban Expansion (UrbExpand) UrbExpand.zip UrbExpand_maps.zip UrbExpand_binaryData.zip  
    Late Reservoir Refill (LateRefill) LateRefill.zip LateRefill_maps.zip    
    Limited Irrigation Rates & Duties (LowIrrig) LowIrrig.zip LowIrrig_maps.zip    
    Higher Irrigation Usage (HighIrrig) HighIrrig.zip HighIrrig_maps.zip    
    New Irrigation Rights (NewIrrig) NewIrrig.zip NewIrrig_maps.zip    
    New Instream Flow Rights (NewInstream) NewInstream.zip NewInstream_maps.zip    
    Worst Case Scenario (EconExtreme) EconExtreme.zip EconExtreme_maps.zip EconExtreme_binaryData.zip  
    Extreme (Extreme) Extreme.zip Extreme_maps.zip Extreme_binaryData.zip  
    Managed (Managed) Managed.zip Managed_maps.zip Managed_binaryData.zip  
    Stationary Climate (StationaryClim) StationaryClim.zip StationaryClim_maps.zip    
    Zero Population and Income Growth (NoGrow) NoGrow.zip NoGrow_maps.zip    
    Zero Population Growth (NoPopGrowth) NoPopGrowth.zip NoPopGrowth_maps.zip    
    Zero Income Growth (NoIncGrowth) NoIncGrowth.zip NoIncGrowth_maps.zip    
    Run of the River (NoReservoirs) NoReservoirs.zip NoReservoirs_maps.zip    
    All Fallow (AllFallow) AllFallow.zip AllFallow_maps.zip    
    Historic Mid-Range Climate (HistoricRef) HistoricRef.zip HistoricRef_maps.zip    
    Historic High Climate (HistoricHadGEM) HistoricHadGEM.zip HistoricHadGEM_maps.zip    

    For questions about downloading and using data from the Willamette Water 2100 project, please contact Anne Nolin, or Maria Wright.

    Interactive Map

    You can view spatial output from Willamette Envision simulations via an interactive map developed by OSU graduate student Dan Stephens. The map displays output from different model simulations.The simulations project how the landscape might change in response to changes in climate conditions, population growth, and land and water management policies. Please use Google Chrome or Firefox web browsers to view the map.

    Link to interactive map of WW2100 modeling output.

    The map displays four types of output from modeling simulations -

    • land cover - including simulated changes in developed land area in the Willamette valley and changes in forest types in the Coast Range and Cascade mountains
    • snow water equivalent - a measure of simulated snowpack, averaged by decade
    • land values - simulated for developed and agricultural lands in the Willamette valley
    • evapotranspiration - the amount of water vapor released from soils and plants into the atmosphere, averaged by decade for different simulations

    The map displays a subset of WW2100 scenarios. The table below highlights key differences between the scenarios featured on the map. For more details about modeling scenarios and their assumptions, refer to the scenarios web page.

    Scenario Climate Change Population Growth Selected Management Assumptions
    Reference Case middle range climate change; ~4°C (~7.5°F) increase in Willamette River Basin (WRB) annual mean temperatures over century pop. in 2010 = 2.41M; 2100 = 5.37M

    - forest wildfire suppression at historical rates; forest area burned increases from 0.2%/yr in 2010 to 0.6%/yr in 2100
    - urban growth boundaries expand when 80% developed; PDX development confined to urban reserves through 2060
    - crop mixes similar to today, crop and energy prices do not rise in real terms

    LowClim (Low Climate Change) ~1°C (2°F) increase in WRB annual mean temps. over century same as Reference Case same as Reference Case
    HighClim (High Climate Change) 6°C (~10.5°F) increase in WRB annual mean temps. over century same as Reference Case same as Reference Case
    High Population same as Reference Case pop. growth rates within UGBs doubled relative to Ref; pop. in
    2100 = 8.25M
    same as Reference Case
    Urban Expansion same as Reference Case same as Reference Case

    - urban growth boundaries expand when 70% developed; no urban reserves
    - other assumptions same as Reference Case

    Fire Suppression same as Reference Case same as Reference Case

    - wildfire suppression efforts increase to hold area burned per year to historical rates
    - other assumptions same as Reference Case

    Managed same as Reference Case  

    - differential increase in wildfire suppression on private and public lands; resulting increase in forest area burned on private lands from 0.2%/yr in 2010 to 0.3%/yr in 2100 and on public lands from 0.2%/yr in 2010 to 0.8%/yr in 2100
    - other assumptions same as Reference Case

    Worst Case same as Reference Case same as High Population

    - wildfire suppression same as Fire Suppression scenario
    - greater utilization of irrigation and instream water rights
    - other assumptions same as Reference Case

     

    Interactive Water Budget

    One of the ways we compared output for different modeling simulations was by developing a water budget from model results. A water budget is an accounting of inputs, outputs and changes in the amount of water that flows through a project area.  We used modeling output from Willamette Envision to estimate a water budget for the Willamette River Basin (WRB) and how that budget might change over the 21st century in response to climate change and population growth.

    The interactive water budget displays inputs and outputs to the water budget in terms of water depth over the whole basin. For example, we estimate that if you summed all the water that falls over the entire basin in a year, and spread it out in an even layer over the whole basin, the water would be 162 cm deep, or just over five feet deep.  We use these depth measurements as a way to compare the relative size of different parts of the water budget in the basin. The thickness of the blue lines in the interactive water budget correspond to the quantity of water that flows through the Willamette Basin, from left to right. The units shown are in of cm3/cm2/year (abbreviated as cm; 1 cm = 235,000 acre-feet).

    Users can use a drop down box to view the water balance for different modeling simulations, and the slider to look at how fluxes change during different times of the year. The scenarios on the drop down menu allow users to switch between depictions of the water budget for the past (1950-2010) and for different future scenarios (2070-2100).

    Read more about the methods and interpretation of the water budget on the hydrology web page.

    Link to the interactive water budget.

    Annual water budget for the simulated historical scenario.

    The interactive water budget was developed by Roy Haggerty, Charles Preppernau, and Maria Wright.

     

    Publications