Hydrology

Accordion Container

Overview

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.

Methods

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 1. Hydrologic 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. (2017) 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 using meteorological forcings from MACA (Multivariate Adaptive Constructed Analogs) training data derived from observed weather station data (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. (2017).

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).

Results

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.

More Information

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 Hydrology, 388(3), 186-207.

Jaeger W.K, Amos AL, Bigelow DP, Chang H, Conklin DR, Haggerty R., Langpap C, Moore KM, Mote PW, Nolin AW, Plantinga A.J., Schwartz C, Tullos D, Turner DP (2017). Finding water scarcity amid abundance using human–natural system models. Proceedings of the National Academy of Science. http://dx.doi.org/10.1073/pnas.1706847114

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

Printer-friendly version

About Willamette Envision

Willamette Envision is a whole watershed model, i.e. it attempts to represent all the significant processes related to the supply and fate of water in the entire basin. These processes are both natural (e.g. precip, snow dynamics, infiltration, runoff, evapotranspiration) and human (e.g. reservoir operations, irrigation, municipal water use, crop choice). The model takes exogenous projections of climate, population, and income as its drivers. It operates by simulating the processes across the entire basin for one time step, recording the effects on the landscape, and then advancing to the next timestep. Some processes are modeled at a daily timestep, for example streamflow and evapotranspiration, while others are modeled at an annual timestep, such as population growth and urban expansion. For more information about Willamette Envision, refer to the model introduction page.

Water cycle diagram. Image modified from NASA, https://pmm.nasa.gov/education/water-cycle.

About WW2100 Modeling Scenarios

The Willamette Water 2100 project modeled 22 scenarios, a reference or base case, and a suite of alternative scenarios. The Reference Case scenario represents future conditions in the Willamette River Basin, under expected trends in population and income growth, existing policies and institutions, and a mid-range climate change projection. A suite of 18 alternative scenarios explore the influence of a single model driver or policy setting at a time. They each vary a single element or assumption from the Reference Case. Three alternative scenarios vary multiple scenario elements from the Reference Case and represent plausible thematic narratives such as “Extreme” or “Worst Case.” Refer to the scenarios page for a detailed description of the WW2100 modeling scenarios, their purpose, and their assumptions.

Willamette Water 2100

You are here