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

    • 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 -

  • 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 ( 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