U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2015–1017

Prepared in cooperation with the California Landscape Conservation Cooperative, California 

Department of Fish and Wildlife, and U.S. Fish and Wildlife Service

A Framework for Modeling Anthropogenic Impacts on 

Waterbird Habitats—Addressing Future Uncertainty in 

Conservation Planning

A Framework for Modeling Anthropogenic Impacts on 

Waterbird Habitats—Addressing Future Uncertainty in 

Conservation Planning

By Elliott L. Matchett, Joseph P. Fleskes, Charles A. Young, and David R. Purkey

Prepared in cooperation with the California Landscape Conservation Cooperative, 

California Department of Fish and Wildlife, and U.S. Fish and Wildlife Service

Open-File Report 2015–1017 

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2015 

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Suggested citation:

Matchett, E.L., Fleskes, J.P., Young, C.A., and Purkey, D.R., 2015, A framework for modeling anthropogenic impacts on 

waterbird habits—Addressing future uncertainty in conservation planning: U.S. Geological Survey Open-File Report 

2015-1017, 40 p., http://dx.doi.org/10.3133/ofr20151017.

ISSN 2331-1258 (online)
Contents

Abstract ...................................................................................................................................................................... 1

Introduction................................................................................................................................................................. 2

Water Evaluation and Planning System (WEAP) Software ..................................................................................... 5

Waterbird Habitats and Water Resources in the Central Valley.............................................................................. 6

Implications of Climate Change for Central Valley Waterbird Habitats................................................................ 6

Water Supply Management for Central Valley Waterbird Habitats ...................................................................... 6

Methods...................................................................................................................................................................... 7

Tool Development................................................................................................................................................... 7

Model Development and Parameterization.......................................................................................................... 7

Basin Drainage and Water Supply Systems ...................................................................................................... 10

Valley Drainage Systems............................................................................................................................... 10

Water Supply and Delivery Constraints ......................................................................................................... 10

Classification and Management of Central Valley Habitats ............................................................................... 11

Wetland Habitats ........................................................................................................................................... 11

Agricultural Habitats....................................................................................................................................... 13

Model Calibration .............................................................................................................................................. 14

Calculating Area of Each Habitat Supported by Available Water Supplies ........................................................... 17

Scenario Development and Evaluation ................................................................................................................. 18

Climate Change Projections.............................................................................................................................. 18

Urban Growth Projections ................................................................................................................................. 19

Water Management: Streamflow Requirements................................................................................................ 19

Water Management: Rice Land Idling ............................................................................................................... 20

Evaluating Scenarios......................................................................................................................................... 20

Results...................................................................................................................................................................... 21

Discussion ................................................................................................................................................................ 24

Challenges to Adapting the WEAP-CV Model for Waterbird Habitats................................................................... 24

Modeling Lessons ................................................................................................................................................. 25

Applications of Modeling Approach....................................................................................................................... 26

Conclusions.............................................................................................................................................................. 27

Acknowledgments .................................................................................................................................................... 28

References Cited...................................................................................................................................................... 29

Appendix A. Description of Water Evaluation and Planning System Model for the Central Valley (WEAP-CV) 

and Adapted for Waterbird Habitats (WEAP-CVwh) Used in Scenario Modeling....................................................... 32

Appendix B. Information Used in Producing Water Evaluation and Planning System Model for the 

Central Valley of California Adapted for Waterbird Habitat (WEAP-CVwh) for the Scenario Modeling Approach ...... 36
iv

Figures 

Figure 1. Modeling approach used to project future available waterbird habitats under various climate, land use, and 

water supply management scenarios ............................................................................................................................ 3

Figure 2. Central Valley Joint Venture (CVJV) hydrologic basins comprising the Central Valley of California.............. 4

Figure 3. As part of Water Evaluation and Planning System model for the Central Valley adapted for waterbird 

habitat (WEAP-CVwh), water supplies, demands, and delivery in part of Butte Basin, California, which the 

WEAP software represents as a system of links and node............................................................................................ 9

Figure 4. Comparison of performance (modeled minus observed values [zero represents no difference]) of 

Water Evaluation and Planning system model for the Central Valley of California (WEAP-CV) with WEAP-CV 

adapted for waterbird habitat (WEAP-CVwh) for (A) Oroville Reservoir storage, (B) Shasta Reservoir storage, 

(C) Feather River streamflow at flow gage near Gridley, California, and (D) Sacramento River streamflow at 

flow gage near Colusa, California................................................................................................................................ 15

Figure 5. Proportion of existing waterbird habitat in Butte Basin, Central Valley of California, projected under 

each modeling scenario evaluating impacts of climate, urbanization, and two changes in water supply 

management (a series of enhanced instream flow requirements [IFRs] on major Sacramento Valley streams 

include a 14 cubic meters per second [m3/s] requirement on Lower Butte Creek during October–June, and an 

additional year-round 142 m3/s requirement on each of the Sacramento and Feather Rivers; and Butte Basin 

rice-idling to meet urban water demands of Planning Areas 606 and 702).................................................................. 22

Figure 6. Areas of Butte Basin, Central Valley of California, habitats used by waterbirds through the wintering 

period that are supported during the most severe drought period under each modeling scenario evaluated .............. 23

Tables

Table 1. Management characteristics of habitats (excluding basin hydrologic unit [HU] geography and irrigation 

schedule) used by wintering waterbirds in the Water Evaluation and Planning system model for the Central Valley 

of California adapted for waterbird habitat (WEAP-CVwh) ............................................................................................ 12

Table 2. Water supply deliveries (in thousands of cubic meters per hectare) required for optimal management of 

winter-flooded rice and wetland habitats in the Butte Basin, California, as modeled in Water Evaluation and 

Planning system model for the Central Valley of California adapted for waterbird habitat (WEAP-CVwh) and 

reported in the literature............................................................................................................................................... 16
v

Conversion Factors

Inch/Pound to International System of Units

Multiply By To obtain

Area

acre 4,047 square meter (m2)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2) 

acre 0.004047 square kilometer (km2)

Volume

cubic foot (ft3) 28.32 cubic decimeter (dm3) 

cubic foot (ft3) 0.02832 cubic meter (m3) 

acre-foot (acre-ft) 1,233 cubic meter (m3)

acre-foot (acre-ft) 0.001233 cubic hectometer (hm3) 

Water application rate per unit area

acre-foot per acre (acre-ft/acre) 3,048 cubic meter per hectare (m3/ha)

International System of Units to Inch/Pound

Multiply By To obtain

Length

meter (m) 3.281 foot (ft) 

meter (m) 1.094 yard (yd) 

kilometer (km) 0.6214 mile (mi)

Area

hectare (ha) 2.471 acre

hectare (ha) 0.003861 square mile (mi2) 

square hectometer (hm2) 2.471 acre

square kilometer (km2) 247.1 acre

square kilometer (km2) 0.3861 square mile (mi2)

Volume

cubic meter (m3) 1.308 cubic yard (yd3) 

cubic meter (m3) 0.0008107 acre-foot (acre-ft) 

Flow rate

cubic meter per second (m3/s) 70.07 acre-foot per day (acre-ft/d) 

cubic meter per second (m3/s) 35.31 cubic foot per second (ft3/s)

Water application rate per unit area

cubic meter per hectare (m3/ha) 0.0003281 acre-foot per acre (acre-ft/acre)
vi

Acronyms and Abbreviations

CNRM-CM3 B1 Centre National de Recherches Météorologiques Coupled global climate Model, version 3, IPCC emissions scenario

based on a global human population peaking mid-century and declining thereafter

CVJV Central Valley Joint Venture

CVPIA Central Valley Project Improvement Act 

DWR California Department of Water Resources

DU Ducks Unlimited, Inc.

EU expansive urbanization

GFDL-CM2.1 A2 Geophysical Fluid Dynamics Laboratory Coupled Model, version 2.1, IPCC emissions scenario based on a continuously

increasing population

GCM global climate model

GIS geographic information system.

HU hydrologic unit

IFR instream flow requirement

IPCC Intergovernmental Panel on Climate Change

NCAR-CCSM3 A2 National Center for Atmospheric Research Community Climate System Model, version 3, IPCC emissions scenario based

on a continuously increasing population

Seas. Wetl. Seasonal Wetland

Semip. Wetl. Semipermanent Wetland

SEI Stockholm Environment Institute

SU strategic urbanization

WEAP software Water Evaluation and Planning system software

WEAP-CV WEAP model for the Central Valley

WEAP-CVwh WEAP-CV model adapted for waterbird habitat

WF Rice Winter-flooded Rice
1

A Framework for Modeling Anthropogenic Impacts on 

Waterbird Habitats—Addressing Future Uncertainty in 

Conservation Planning

By Elliott L. Matchett1, Joseph P. Fleskes1, Charles A. Young2, David R. Purkey2

Abstract

The amount and quality of natural resources available for terrestrial and aquatic wildlife habitats 

are expected to decrease throughout the world in areas that are intensively managed for urban and 

agricultural uses. Changes in climate and management of increasingly limited water supplies may 

further impact water resources essential for sustaining habitats. In this report, we document adapting a 

Water Evaluation and Planning (WEAP) system model for the Central Valley of California. We 

demonstrate using this adapted model (WEAP-CVwh) to evaluate impacts produced from plausible 

future scenarios on agricultural and wetland habitats used by waterbirds and other wildlife. Processed 

output from WEAP-CVwh indicated varying levels of impact caused by projected climate, urbanization, 

and water supply management in scenarios used to exemplify this approach. Among scenarios, the 

NCAR-CCSM3 A2 climate projection had a greater impact than the CNRM-CM3 B1 climate 

projection, whereas expansive urbanization had a greater impact than strategic urbanization, on annual 

availability of waterbird habitat. Scenarios including extensive rice-idling or substantial instream flow 

requirements on important water supply sources produced large impacts on annual availability of 

waterbird habitat. In the year corresponding with the greatest habitat reduction for each scenario, the 

scenario including instream flow requirements resulted in the greatest decrease in habitats throughout all 

months of the wintering period relative to other scenarios. This approach provides a new and useful tool 

for habitat conservation planning in the Central Valley and a model to guide similar research 

investigations aiming to inform conservation, management, and restoration of important wildlife 

habitats.

1

U.S. Geological Survey. 2

Stockholm Environment Institute. 
2

Introduction

In many regions throughout the world, the future sustainability of many terrestrial and wetland 

habitats and the ecology they support is in question (Myers, 1996; Hoekstra and others, 2005; 

Baldassarre and Bolen, 2006). In regions that are intensively managed for urban and agricultural uses, 

the amount and quality of land and water resources currently (2014) available for habitats are expected 

to decrease through time (Tilman and others, 2001; Brinson and Malvárez, 2002; Jetz and others, 2007). 

In addition to pressures from growing human populations and intensive agricultural production, 

changing climate and efforts to manage decreasing water supplies are likely to further impact water 

resources essential for sustaining habitats (Meyer, 1999; Jetz and others, 2007). It is the job of habitat 

conservation planning to provide a framework that can be feasibly implemented, and when 

implemented, ensures meeting habitat sustainability goals through time. 

Projecting into the indefinite future, cumulative impacts of anthropogenic stressors on the 

natural resources, ecosystems, and habitats they support is highly uncertain (Pilkey-Jarvis and Pilkey, 

2008). Unless accounted for, uncertainty in the future trajectory of impacts across regional and local 

scales confounds efforts by natural resource specialists to conserve, manage, and restore ecosystems and 

their habitats (Holling and Meffe, 1996; Peterson and others, 2003). For any given region, uncertain 

future change in climatic, demographic, socioeconomic, and institutional factors confers indefinite 

future conditions influencing habitat sustainability. Thus, given such inherent uncertainty, additional 

habitat management and conservation tools are needed to better understand and address the future 

potential impacts collectively caused by anthropogenic stressors. 

In this report, we document a specific modeling approach useful for understanding impacts of a 

range of potential future climate, landscape management, and water supply management conditions on 

wildlife habitats (fig. 1). The approach first required producing a tool for modeling impacts of multiple 

combinations of factors on water and land resources supporting wildlife habitats. Scenario-based models 

commonly are used by practitioners in environmental and natural resource disciplines for addressing 

uncertainty in future conditions (for example, related to climate change). Using such a scenario 

modeling tool would enable the evaluation of impacts produced across a range of plausible future 

conditions to identify scenarios presenting the greatest threat to wildlife habitats. Thus, for a part of the 

Central Valley of California (an archetype of regional land use, water management, and climate change 

stressors on the local habitats; Fleskes, 2012; fig. 2), we document the development of a scenario 

analysis tool based on the Water Evaluation and Planning software (Yates and others, 2005a, 2005b). 
3

Figure 1. Modeling approach used to project future available waterbird habitats under various climate, land use, 

and water supply management scenarios.
4

Figure 2. Central Valley Joint Venture (CVJV) hydrologic basins comprising the Central Valley of California.
5

This analysis tool was developed for evaluating future sustainability of habitats supporting 

waterbirds (but applying to other wildlife species as well) during the wintering period. (Waterbirds 

include many taxa that forage extensively, although not exclusively, in wetlands and other flooded 

habitats. Wintering period is defined to include months August–March.) To develop the tool, a Water 

Evaluation and Planning system (WEAP) model (hereafter referred to as WEAP model for the Central 

Valley of California or “WEAP-CV”) was adapted to more accurately model habitats for wintering 

waterbirds. The WEAP-CV model had been developed for, and represents, the watershed hydrology and 

water demands of the Central Valley region (Joyce and others, 2011). To adapt a WEAP-CV model for 

waterbirds, we: 

1. Added winter-flooded agricultural habitats that had not been represented, 

2. Updated and corrected the area of wetland habitats,

3. Distinguished certain water supply sources not specifically represented,

4. Combined multiple land cover datasets in a geographic information system (GIS) 

(Environmental Systems Resource Institute, Inc., 2012) to calculate areas of various 

land cover classes, and

5. Made other changes while accommodating a variety of scenarios we wanted to examine.

The resulting CV model adapted for waterbird habitat (that is, WEAP-CVwh) produces accurate 

estimates of projected available water supplies supporting agricultural and wetland habitats important 

for wintering waterbirds and water demands of all uses including for habitats. In modeling, WEAPCVwh achieves this objective while also accounting for projected changes in land resources (for 

example, urbanization of agricultural land) upon which habitats depend. Subsequent to modeling, a 

methodology for calculating availability of each habitat was developed as a function of modeled water 

supplies and demands pertaining to habitats. 

In combination, changing climate, urbanization, and changes in water supply management have 

the potential to greatly impact the amount and distribution of waterbird habitats on the Central Valley 

landscape. We are unaware of any other method that can be used to evaluate the combined and 

potentially synergistic effects of these factors on waterbird habitats in the Central Valley. Using this 

comprehensive accounting approach described herein, projections of climate (recent historical [years 

1971–2000] climate and from global climate model results that were spatially-downscaled), land, and 

water resources management are varied to evaluate multiple scenarios reflecting different futures.

Following a description of its development, we demonstrate the use of WEAP-CVwh for modeling 

habitat landscape conditions based on a range of scenarios. Finally, we describe lessons learned through 

this model-building and scenario-planning process. This report provides a new approach using a 

scenario-based water resources model for habitat conservation planning and protection. This research 

also may be informative in identifying specific software and its application for similar projects, or an 

additional application of the software for other WEAP users. 

Water Evaluation and Planning System (WEAP) Software

Our approach allowed us to model surface water and groundwater supplies and water demands 

completely within a single framework using the commercial WEAP software developed by the 

Stockholm Environment Institute (SEI). A primary asset of the WEAP software is the ability to flexibly 

construct scenarios. Conditions representing any given scenario are projected into the future from a 

“Current Accounts” year representing existing conditions. The WEAP-CV was obtained from the State 

of California and SEI. WEAP-CV has undergone peer review, its use has been published, and it is being 

used by the State of California and others for water supply management and planning in the 
6

Central Valley (for example, Yates and others, 2009; Joyce and others, 2010). In addition to modeling 

watershed hydrology, WEAP-CV contains the major components of water supply management and 

delivery systems, and water demands defined for California Department of Water Resources (DWR) 

“Planning Areas” (Joyce and others, 2010; figs. 2 and 3; appendix A). Thus, we determined that the 

WEAP-CV was a sufficiently representative model that could be adapted to develop a scenario analysis 

tool for evaluating concurrent impacts on water and land resources supporting Central Valley habitats. 

Waterbird Habitats and Water Resources in the Central Valley

The Central Valley of California is one of the most important regions for waterbirds in North 

America (Fleskes, 2012). Waterbird habitats in the Central Valley (table 1; fig. 2) that are critical to 

waterfowl and other wetland birds are dependent on snow pack and other precipitation for water 

supplies. Surface water supplies entering hydrologic basins are either (1) produced at high elevation a 

great distance from valley habitats and generally are stored in reservoirs, or (2) available as rainfall and 

rainfall runoff. The hydrology of most waterbird habitats in the Central Valley, which include wetlands, 

flooded rice fields, and other flooded agricultural lands, has been greatly modified. Natural overflow 

flooding from snowmelt and rain mostly has been replaced by managed flooding with controlled 

diversions and pumped water delivery from ditches, rivers, sloughs, and wells. Thus, the amount of 

water stored in reservoirs is crucial to determining the amount of waterbird habitat in the Central Valley.

During years with average or above-average reservoir levels, water is available to allow summer 

irrigations and normal fall flooding, and winter maintenance of managed habitats; winter rains provide 

additional winter habitat. Dry-to-extreme drought conditions can restrict summer irrigations, reducing 

wetland production of seeds, and reducing or delaying fall and winter flooding of wetlands, harvested

rice fields, and other agricultural lands. Dry winters also produce little or no lowland or bypass 

(constructed floodplain designed for flood-control and contains waterbird habitats) flooding. 

Implications of Climate Change for Central Valley Waterbird Habitats

Global climate models indicate substantial changes in the temperature and timing and amounts 

of precipitation in watersheds of the Central Valley (Cayan and others, 2009, 2012), which would cause 

temporal and spatial variations in many of the driving forces that define the availability and productivity 

of habitats. Changes in timing, amounts, and distribution of precipitation can have major impacts on 

waterbirds and their habitats. For instance, lack of adequate water supplies in the Central Valley could 

reduce productivity of wetland habitats, and the area of wetlands and post-harvest flooded crop fields, 

changing waterbird distribution in the valley (Fleskes and others, 2005; Ackerman and others, 2006). 

Climate-induced changes in water demand and soil moisture that impact vegetation and associated fauna 

and insects surrounding wetlands may reduce the ecosystem diversity and impact wetland habitats.

Thus, climate change could alter when and where critical resources are available and needed for 

migratory birds. 

Water Supply Management for Central Valley Waterbird Habitats

Statewide or regional changes in water supply management also can alter the timing and amount 

of water that is supplied to Central Valley waterbird habitats. In situations where water supplies become 

limited (for example, drought), water management entities prioritize allocation of supplies for various 

competing water uses. Certain water management practices may result in a reduction of water delivered 

to Central Valley habitats, thereby reducing the amount or productivity of habitats. Examples of changes 
7

in water supply management in the Central Valley that may reduce the amount of water delivered to 

habitats include intensified idling of rice land to allow interregional water transfers, increased 

streamflow protection measures for fisheries, and urban expansion requiring water that would otherwise 

support habitats.

Methods

First, we developed a tool for modeling potential effects of climate, urbanization, and water 

supply management scenarios on water and land resources supporting habitats. Second, we developed a 

method to calculate the area of each habitat supported by available water supplies under each scenario 

evaluated. Finally, we developed and evaluated scenarios, which included identifying climate and land 

and water management factors potentially affecting water supply reliability, translating these factors

into meaningful WEAP-CVwh scenarios, and evaluating scenarios using our approach. 

Tool Development

Considerable work was required to adapt WEAP-CV to accurately model habitats for wintering 

waterbirds in the Central Valley, while accommodating a variety of scenarios we intended to evaluate.

Initially, we researched land and water resource information and assessed regional and statewide water 

supply management policies (appendix B). Based on this research, we: 

1. Identified important waterbird habitats and obtained pertinent habitat data, 

2. Identified important supply sources for habitats, 

3. Analyzed timing and amount of habitat water requirements, 

4. Identified valley urban and agricultural drainage areas and managed drainage systems, 

5. Analyzed water supply and delivery constraints pertaining to agriculture and wetlands, 

6. Obtained urbanization projections and calculated projections of corresponding reductions in crop 

areas, 

7. Analyzed current and hypothetical supply prioritization of various wetland and crop types, 

8. Identified proposed streamflow requirements dedicated for fisheries protection, and 

9. Identified possible future rice land idling and water transfer scenarios that may impact habitats.

Model Development and Parameterization

To accurately represent wintering waterbird habitat area and water needs, to facilitate model 

development, and to accommodate scenarios of interest, we used the above research information to 

develop WEAP-CVwh in finer temporal and spatial detail of hydrologic and land management 

characteristics than existed in WEAP-CV. This included adding winter-flooded agricultural habitats not 

represented in WEAP-CV, modifying land cover represented in WEAP-CV to also include wetland 

habitats identified in the Central Valley Joint Venture (CVJV) Plan (Central Valley Joint Venture, 

2006), and distinguishing certain water supply sources not specifically represented in WEAP-CV. For 

each hydrologic unit (HU), drainage systems and water delivery constraints within basins also were 

characterized. 
8

To model land cover and hydrology in finer temporal and spatial detail required for WEAPCVwh, we created fine-scale HUs within CVJV basins and intersecting DWR Planning Areas and 

calculated land-cover areas of HUs (fig. 2). HUs were created using a GIS to intersect multiple datasets 

characterizing waterbird habitat conservation goals, water supplies and demands, and management of 

water supplies and drainage. Polygons produced from the intersections of these data represented basin 

HUs. Tabular data of total areas represented in WEAP-CV for wetlands (adjusted based on Central 

Valley Joint Venture [2006]) and other land cover types were apportioned among HUs in WEAP-CVwh

using a GIS and multiple land cover datasets (appendix B). Using Butte Basin as an example, a GIS was 

used to create the boundaries of each area of intersecting CVJV subbasin (“Upper Butte” and “Butte 

Sink”), DWR Planning Area, Butte Creek Watershed boundary area, Upper watershed of West Branch 

of Feather River, and 500-m elevation contours related to Butte Basin hydrology and water demands.

The resulting GIS layer delineating HUs then was intersected with GIS land cover data for various 

agricultural crops, wetlands, urban areas, and other non-irrigated areas. The final layer combining HU 

and land cover information was used to calculate proportions of each cover class among HUs. 

Corresponding with calculated proportions of crops, total crop areas already present in WEAP-CV were 

divided among HUs. Similarly, using calculated wetland proportions, we divided seasonal, 

semipermanent, and permanent wetland areas summarized in CVJV (2006), and based on additional 

information (Central Valley Joint Venture, 2000; Mark Petrie, Ducks Unlimited, Inc., unpub. data, 

October 2010), we reclassified wetland areas for each HU. Based on HUs delineating the Butte Creek 

watershed in WEAP-CVwh, we distinguished hydrology of Butte Creek from other sources that in the 

WEAP-CV were aggregated with Butte Creek. Natural and irrigation runoff and groundwater 

infiltration also were distinguished and modeled for each HU in Butte Basin. 

In WEAP, basin characteristics are represented as a system of links and nodes (fig. 3). We 

developed and parameterized links and nodes characterizing land cover and hydrology for each HU. 

Using WEAP “catchment” nodes (appendix A) for each HU, we characterized (1) irrigated agriculture

and public and private wetlands; (2) non-irrigated forest, non-forest, and barren land; and (3) urban 

cover types and hydrology. WEAP-CVwh catchment climate variables (appendix A, table A1) generally 

were populated with values used in WEAP-CV catchment nodes characteristic of the DWR Planning 

Area spatial scale. In a few situations requiring finer spatial detail of climate effects, such as 

disaggregating surface water streams across an expansive elevation gradient (represented in WEAP-CV 

as a single combined source), location-specific temperature and precipitation climate data were obtained 

(U.S. Department of the Interior and others, 2013). In WEAP-CVwh, Butte Creek was represented as a 

“river” link (table A1) with tributary inflow into the existing WEAP-CV Sutter Bypass “diversion” link 

(table A1). Catchments representing the upper watershed of Butte Creek were parameterized using an 

existing WEAP model of the Butte Creek system as a template (Thompson and others, 2012). We also 

added a Butte Creek “flow requirement” node (table A1) and minimum flow information reflecting 

historical regulatory constraints in the upper-middle reaches of Butte Creek (appendix B). In addition to 

specifying Butte Creek, we used river links to account for natural, agricultural, and urban-related 

drainage produced and available for use and reuse within and downstream of respective valley HUs. 

Supply prioritization of surface-water reservoirs and competing water uses already present in WEAPCV generally were adopted in WEAP-CVwh (appendix A, table A2).
9

Figure 3. As part of Water Evaluation and Planning System model for the Central Valley adapted for waterbird 

habitat (WEAP-CVwh), water supplies, demands, and delivery in part of Butte Basin, California, which the WEAP 

software represents as a system of links and nodes. Links are defined as follows: water transmission to demand 

sites (green arrows), rivers (blue arrows), diversions (orange arrows). Nodes are defined as follows: surface 

storage reservoirs (green triangles), catchments (green circles), streamflow requirements (purple circles with crosshairs), streamflow gages (blue circles with arrows). For illustrative purposes, runoff and infiltration links and urban 

demand site nodes are not shown.
10

Basin Drainage and Water Supply Systems

Valley Drainage Systems

The spatial relationships between drainage systems on the valley floor and waterbird habitats 

influence availability of drainage water usable by waterbird habitats. The amount of drainage water 

available to habitats depends on the location and size of drainage systems and associated area of local 

urban, agricultural, or other land cover. Habitats within and downstream of drainage systems have 

greater access to water collected within and draining from these systems. Return flows (for example, 

unconsumed irrigation tailwater inputs during the agricultural growing season) and local natural runoff 

are important water sources for many habitats, especially certain wetlands supplied entirely with return 

flows and local natural runoff. Therefore, we conducted additional research to identify the spatial 

extents and points of outflow (into major tributaries specified in the model) of local drainage systems.

Because topography on the valley floor has been greatly altered for agricultural and urban development, 

it varies little and cannot be used reliably to identify valley drainage areas. Therefore, we reviewed the 

literature and compared literature references of drainage systems with spatially explicit GIS data 

(appendix B) to identify drainage areas and points of outflow. In a GIS, we combined existing GIS 

datasets and maps we digitized of drainage areas and points of outflow to produce a dataset delineating 

drainage areas. The drainage area dataset was intersected with other layers related to groundwater, 

DWR Planning Areas, and CVJV basin boundaries. The resulting layer characterized HUs based on 

variation in drainage areas, water supply sources, water and land management, and waterbird 

conservation goals for each basin. Thus, natural, agricultural, and urban-related drainage available for 

use and reuse within and downstream of each basin HU can be accounted for in WEAP-CVwh.

Water Supply and Delivery Constraints 

Maximum limits on the amount of water delivered from individual water sources to meet water 

demands in WEAP-CV reflect physical limits of supply and delivery systems at the spatial scale of 

DWR Planning Areas. However, spatial detail of HUs is much higher than DWR Planning Areas, and 

water sources and the extent that each source is used varies substantially among basin HUs. Therefore, 

based on available information, we assessed water sources used for meeting basin water demands. In the 

assessment, we identified sources of information (appendix B) that delineated agencies, companies, and 

individuals that managed Central Valley water supplies for agricultural and managed wetland habitats 

within each HU. Based on this information, we conducted research on each water supplier to determine 

the surface streams, groundwater, or return flows that are diverted from or pumped as supply sources. 

Using multiple GIS datasets delineating land cover, water agency boundaries, water supply sources, and 

HUs (appendix B), we quantified the area of each land cover (classified as agriculture, private wetland, 

public wetland, or urban) in each HU by water source used. For each HU, the quantified area of a cover 

class receiving water from a given supply source was assumed to be proportional to the water demand 

of the respective cover class supported by that source. The fraction of a cover class’s water demand 

supported by each source was estimated as the cover class’s area receiving each source divided by the 

total area of the cover class. In a few specific situations, water source fractions were adjusted based on 

information that we believed to be more accurate than calculations. Calculated water source fractions 

were included in the model as constraints on the maximum amount of water supplied by each available 

source. Additionally, if research indicated limits in physical or operational capacity of major water 

delivery infrastructure, this information was included as additional constraints in WEAP-CVwh. 
11

Classification and Management of Central Valley Habitats

Central Valley habitats important for waterbirds during the wintering period include wetlands 

and certain harvested crop fields (Central Valley Joint Venture 2006). In Colusa, Butte, Sutter, Yolo, 

American, and Delta Basins, rice and corn fields and wetlands are the predominant foraging habitats. In 

Suisun and San Joaquin Basins, wetlands are the predominant foraging habitats, and in Tulare Basin, 

wetlands and a variety of fields flooded after harvest or before planting provide waterbird habitat 

(Fleskes and others, 2012). Seasonal wetlands are the primary wetland type that provides food for 

wintering waterbirds, whereas semipermanent and permanent wetlands are important mainly as roosting 

habitat (Central Valley Joint Venture, 2006). 

Wetland Habitats

Within a given basin, managed wetlands were classified in as many groups as current 

information would allow, which should better aid future refinement and accuracy of WEAP-CVwh as 

new information becomes available. Central Valley Joint Venture (2000) provided detailed information 

about privately owned wetlands by basin. Based on this and other information (appendix B), we were 

able to distinguish several wetland habitat types providing food for waterbirds (table 1). Wetland 

classifications were based on ownership, water supply source, water supply reliability, hydroperiod, and 

supply priority (table 1). We also accounted for the flooding schedule of managed wetlands in the 

Central Valley, where all such wetlands are not initially flooded at the same time and an increasing 

amount becomes inundated throughout much of the wintering period. Wetland flooding schedules 

(Central Valley Joint Venture, 2006; Mark Petrie, Ducks Unlimited, Inc., written commun., March 15, 

2012) indicating the relative fractions of seasonal wetland areas that are flooded on biweekly intervals 

were used to interpolate inundated wetland areas from the middle of each month during the flooding 

period through the remaining season. Resulting seasonal wetlands included as land cover classes within 

catchments were divided into wetlands flooded initially by middle of August, September, October, and 

November (a small proportion of wetlands flooded initially in December were included in November). 

In our modeling, we assumed that hydroperiods of the few permanent wetlands in the Central Valley 

(Mark Petrie, Ducks Unlimited, Inc., written commun., October 7, 2010) were the same as 

semipermanent wetlands (i.e., flooded all months except August and September; Central Valley Joint 

Venture, 2000; Fleskes, 2012). We represented wetlands (table 1) within each HU using three 

catchments identifying publicly owned wetlands, privately owned wetlands with highly reliable 

supplies, and privately owned wetlands with less reliable supplies that rely on local natural and 

agricultural drainage water.
12

Table 1. Management characteristics of habitats (excluding basin hydrologic unit [HU] geography and irrigation 

schedule) used by wintering waterbirds in the Water Evaluation and Planning system model for the Central Valley 

of California adapted for waterbird habitat (WEAP-CVwh). 

[Water supply reliability: Adapted from Central Valley Joint Venture (2000). Reported “High” and “Moderate” reliability were classified 

herein as “High-reliability.” (We also classified as “High-reliability” certain atypical wetlands reported as “Low-reliability” using supplies 

in addition to return flows.) Supply priority: 1, highest; 3, equivalent to agriculture; RF, basically relies on agricultural return flows and 

generally consistent with “Low-reliability” water supply classification. Public wetlands with Central Valley Project Improvement Act 

(CVPIA) contracts have water supplies that are more secure than other public wetlands; thus, the difference in supply priority] 

Habitat Ownership Water supply reliability Hydroperiod Supply 

priority

 Wetland Public (CVPIA) High-reliability Seasonal 1

 Wetland Public (CVPIA) High-reliability Semipermanent 1

 Wetland Public High-reliability Seasonal 3

 Wetland Public High-reliability Semipermanent 3

 Wetland Private High-reliability Seasonal 3

 Wetland Private High-reliability Semipermanent 3

 Wetland Private Low-reliability Seasonal RF

 Wetland Private Low-reliability Semipermanent RF

 Winter-flooded rice Private 3

 Unplowed winter-dry rice Private 3

 Winter-flooded corn Private 3

 Unplowed winter-dry corn Private 3

In addition to classifying and calculating areas for managed wetlands (see section, “Model 

Development and Parameterization,” for details), we specified model catchment parameter values for 

wetlands in WEAP-CVwh. Catchment soil and land-use variables (appendix A, table A1) initially were 

populated with values characteristic of managed wetland nodes already implemented in WEAP-CV; 

some parameter values were further adjusted during model calibration (see section, “Model 

Calibration,” for details). Catchment irrigation and pond-depth variables (appendix A, table A1) were 

parameterized and calibrated based on wetland management information (Central Valley Joint Venture, 

2000, 2006). We considered our information on continuous flow through wetlands and winter-flooded 

rice fields for maintaining water quality and reducing disease risk in them to be inadequate to model this 

management practice; consequently, the ponding release requirement parameter was not used in WEAP.

The supply prioritization of wetlands (table 1) was based on wetland water supply and delivery 

operations (appendix B). 
13

Agricultural Habitats

Agricultural foraging habitats for wintering waterbirds in Sacramento Valley basins were 

classified as winter-flooded rice, unplowed winter-dry rice, and unplowed winter-dry corn based on 

habitats identified in Central Valley Joint Venture (2006) (table 1). Other agricultural waterbird habitats 

exist elsewhere in the Central Valley (for example, flooded corn and wheat in the Delta Basin). The 

estimated fraction of post-harvested rice that is flooded in fall/winter varies among CVJV basins 

(Fleskes and others, 2005; estimates provided by Kevin Petrik, formerly of Ducks Unlimited, Inc., 

written commun., June 13, 2012). We calculated the total area of winter-flooded rice within each HU as 

the product of basin-specific fractions of flooded rice and the total rice area within each HU previously

calculated using a GIS (see section, “Model Development and Parameterization,” for details). As with

seasonal wetlands, the total area of winter-flooded rice was divided into mid-monthly amounts for 

October–March, equating to four land cover classes, according to timing of initial flooding (Central 

Valley Joint Venture, 2006). Winter-flooded rice land cover classes were added to HU catchments 

containing the suite of crop classes calculated in the GIS by dividing “rice” into winter-flooded and 

winter-dry classes. (Note: Some winter-dry rice is deep-plowed and, thus, is not waterbird habitat; this 

rice was excluded as habitat in later processing steps [see section, “Calculating Area of Each Habitat 

Supported by Available Water Supplies,” for details].) We also produced additional habitat catchments 

representing winter-flooded rice, dry rice, corn, pasture, and alfalfa. Depending on the scenario, these 

additional catchments allow flexibility in allocating a certain fraction of respective agricultural habitats 

to a separate supply priority from the rest of agriculture. 

We specified WEAP-CVwh catchment parameter values for agricultural habitats similarly as for 

wetlands. To model winter flooding of rice in WEAP-CVwh, a capability not in WEAP-CV, we adopted 

catchment parameter values from rice in WEAP-CV to parameterize crop coefficient, soil water 

capacity, root zone conductivity, and preferred flow direction variables. Similarly, we adopted from 

fallow land in WEAP-CV values for the runoff resistance factor variable (appendix A, table A1).

Irrigation and pond-depth variables could not be populated with WEAP-CV parameter values.

Therefore, these variables were parameterized from information on post-harvest management of rice ( 

California Department of Water Resources, 2003; Central Valley Joint Venture, 2006). Irrigation and 

pond-depth parameters were further adjusted during model calibration (see section, “Model 

Calibration,” for details). 
14

Model Calibration

After WEAP-CV was revised to include additional habitats, water supplies, and water delivery 

constraints, WEAP-CVwh was calibrated by evaluating model performance and adjusting model 

parameters where necessary to improve accuracy. Model performance was evaluated by comparing 

modeled water supplies and habitat demands with observed water supplies and habitat demands under 

recent historical (years 1971-2000) climate and water demands. We compared differences in model 

output and stream gage and reservoir storage measurements between the WEAP-CV and WEAP-CVwh

to assess their relative performance. 

WEAP-CVwh generally performed slightly better in tracking patterns and magnitudes of 

observed streamflow and reservoir storage of major water bodies than WEAP-CV (fig. 4). Model 

parameters that determined operations of the Round Valley and Philbrook Reservoirs were obtained 

from an earlier WEAP study of the Butte Creek system (Thompson and others, 2012). In calibrating 

wetland soil, irrigation, and pond-depth parameters, modeled monthly and annual water deliveries (in 

thousands of cubic meters per hectare) were compared to wetlands with water application rates reported 

for optimal management of wetlands (Central Valley Joint Venture, 2000). In calibrating irrigation and 

pond-depth parameters for winter-flooded rice, we compared modeled water deliveries (in thousands of 

cubic meters per hectare) during October–February to reported deliveries over the same months 

(California Department of Water Resources, 2003). Modeled delivery amounts used in this comparison 

are based on a model simulation producing full supply allocation to wetlands and rice (that is, modeled

optimal supply delivery). During calibration, irrigation and pond-depth parameters were adjusted within 

a range of values characteristic of water management for wetlands and winter-flooded rice (Central 

Valley Joint Venture, 2000; California Department of Water Resources, 2003). One additional wetland 

catchment soil and land-use parameter (root zone hydraulic conductivity) was adjusted during 

calibration to improve modeling performance of seasonal and semipermanent wetland water demands.

Calibration of habitat parameters generally resulted in close agreement between modeled and reported 

deliveries (table 2).
15

Figure 4. Comparison of performance (modeled minus observed values [zero represents no difference]) of Water 

Evaluation and Planning system model for the Central Valley of California (WEAP-CV) with WEAP-CV adapted for 

waterbird habitat (WEAP-CVwh) for (A) Oroville Reservoir storage, (B) Shasta Reservoir storage, (C) Feather River 

streamflow at flow gage near Gridley, California, and (D) Sacramento River streamflow at flow gage near Colusa, 

California. 
16

Table 2. Water supply deliveries (in thousands of cubic meters per hectare) required for optimal management of 

winter-flooded rice and wetland habitats in the Butte Basin, California, as modeled in Water Evaluation and 

Planning system model for the Central Valley of California adapted for waterbird habitat (WEAP-CVwh) and reported 

in the literature.

[Habitat: WF Rice, Winter-flooded rice; Seas. Wetl., Seasonal Wetland; Semip. Wetl., Semipermanent Wetland. Year: Reported values 

for winter flooding of rice occurring during October–February are based on California Department of Water Resources (2003); annual, but 

not monthly (blank cells), reported values were available in the literature. Reported values for wetlands were based on Central Valley Joint 

Venture (2006). "Wet", "Normal”, and "Dry" water-year classifications are based on the Sacramento Valley Hydrologic Index. Percent 

difference (Perc. diff.): Defined as (Modeled Annual Total - Reported Annual Total)/Reported Annual Total × 100. Reported Annual 

Total used in this calculation for Winter-flooded rice is the median (5.5)] 

Habitat Year Oct Nov Dec Jan Feb Mar Apr May June July Aug Sept

Annual 

total

Perc.

diff.

WF Rice 1998 (Wet) 4.9 0.3 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 5.5 0

2000 (Normal) 4.9 0.9 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 6.4 22

2001 (Dry) 4.3 1.2 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 6.1 15

Reported 3.0–7.6

Seas. Wetl. 1998 (Wet) 1.5 0.0 0.6 0.0 0.0 0.6 0.0 2.1 0.0 0.0 3.0 7.3 14.9 -12

2000 (Normal) 1.5 0.6 0.9 0.0 0.0 0.9 0.0 3.0 0.0 0.0 3.4 7.3 17.7 4

2001 (Dry) 0.9 0.9 0.9 0.0 0.3 1.2 0.0 3.4 0.0 0.0 3.4 7.3 18.3 7

Reported 1.5 1.2 0.6 0.6 0.6 0.6 0.0 3.0 0.0 0.0 2.7 6.1 17.1

Semip. Wetl. 1998 (Wet) 9.8 0.0 0.6 0.0 0.0 0.6 1.2 0.6 2.4 3.0 0.0 0.0 18.6 -18

2000 (Normal) 10.1 0.6 0.9 0.0 0.0 0.9 1.2 1.8 2.7 3.0 0.0 0.0 21.9 -3

2001 (Dry) 9.4 0.9 0.9 0.0 0.3 1.2 1.2 2.4 2.7 3.0 0.0 0.0 22.6 0

Reported 9.1 1.2 0.6 0.6 0.6 1.2 1.5 1.5 3.0 3.0 0.0 0.0 22.6
17

Calculating Area of Each Habitat Supported by Available Water Supplies

This scenario modeling approach required translating land and water resources output produced 

from the scenario modeling tool (WEAP-CVwh) into habitat areas supported by projected water supplies. 

To achieve this objective, WEAP-CVwh output was post-processed in spreadsheets to translate amount 

and timing of water available compared to water needed to support optimal management of habitats. 

Modeling scenarios of interest provided output on water availability for each scenario. However, two 

additional steps were needed to calculate the water requirement for optimal habitat management to 

compare with water available based on scenarios. First, we made changes to the model to ensure that 

habitats received full supply in every month. Second, we modeled the delivery of the full water 

requirement to habitats under each climate projection and historical climate because water demand 

varies with climate. Calculations initially were performed for each habitat type that combined land 

cover, hydroperiod, irrigation schedule (for example, October–March), ownership (for example,, 

private), water reliability (for example, low reliability), supply priority (for example, 1), and geography 

(generally reflected in HUs). WEAP-CVwh output on monthly amount of water supply delivered (in 

thousands of cubic meters) and total area of each habitat (in hectares) was used to calculate monthly 

volume per area rates of water delivery (in thousands of cubic meters per hectare). Calculating volume 

per area rates allowed us to broadly compare water availability in each scenario with water required in 

situations for which projected habitat areas change (for example, scenarios having different rates of 

urbanization). Because water supplied to users generally is based on annual (not monthly) water 

allocations that depend on environmental conditions (for example, dryness of year), we further 

calculated annual unit area rates of water deliveries. For each habitat, the ratio of available water to 

required amount of water (both in thousands of cubic meters per hectare) represents the fraction of total 

annually available area of habitat. 

Subsequent to water supply modeling, the availability of each habitat under each scenario was 

calculated as a function of modeled water supplies and demands pertaining to habitats. Because the 

wintering period includes two water years, two sets of annual (water-year) fractions of habitat areas 

were used to multiply with the annual areas of respective years to calculate habitat areas for both years 

within a season. To calculate monthly available habitat areas, we adjusted the calculated annual habitat 

areas to reflect temporal variation in harvest of rice (U.S. Department of Agriculture, 2011) and corn 

(U.S. Department of Agriculture, 2010), and timing of normal flooding of wetlands and harvested fields 

(Central Valley Joint Venture, 2006) through the wintering period. In years for which water required for 

the winter flooding of rice (October–February) is insufficient for optimal flooding, we generalized 

allocation of available water for winter flooding in later months. For example, the rice area estimated to 

be normally available as winter-flooded rice habitat in October, under supply limitation, is alternatively 

calculated as winter-dry rice habitat until flooding is possible in November or later, depending on 

severity of water limitation. We assumed based on observations that when water supplies are limited, 

many managers delay winter flooding until the start of waterfowl hunting season in late October, after 

which runoff from precipitation generally is available to help maintain habitats until the end of hunting 

season in late January. Ultimately, we produced projections of the amount of habitat available during 

each month of the wintering period from August through March under each scenario. 
18

Scenario Development and Evaluation

We reviewed literature and contacted researchers and managers to identify climate and land and 

water management potentially affecting water supply reliability (appendix B). We then modified 

structural elements (links and nodes) and specified related parameters in WEAP-CVwh to translate these 

factors into meaningful WEAP-CVwh scenarios and to develop the model structure needed for efficient 

and flexible evaluation of scenarios. Minor differences in model design can effectively result in 

different scenarios being evaluated, or result in more or less flexibility to evaluate similar scenarios. We 

define elements of model specification in more detail below for selected scenarios we are using to 

demonstrate our scenario modeling approach. 

Climate Change Projections

Recent historical (years 1971–2000) climate and a range of downscaled climate change 

projections, including projections of key interest, already are represented in WEAP-CV. As climate 

change models improve, updated projections may be included in future scenarios. The three climate 

change projections that we evaluated (Salas-Mélia and others, 2005; Collins and others, 2006; Delworth 

and others, 2006; Stouffer and others, 2006; Cayan and others, 2009) were:

1. CNRM-CM3 B1 (Centre National de Recherches Météorologiques Coupled global climate 

Model, version 3, Intergovernmental Panel on Climate Change [IPCC] emissions scenario 

based on a global human population peaking mid-century and declining thereafter), 

2. NCAR-CCSM3 A2 (National Center for Atmospheric Research Community Climate 

System Model, version 3, IPCC emissions scenario based on a continuously increasing 

population), and 

3. GFDL-CM2.1 A2 (Geophysical Fluid Dynamics Laboratory Coupled Model, version 2.1, 

IPCC emissions scenario based on a continuously increasing population).

These climate projections were selected because they are a subset of projections previously 

selected to investigate climate change impacts on California and they represent a broad range of 

potential future climate conditions (Cayan and others, 2009). Temperature and precipitation data for 12 

climate change projections (Nakicenovic and others, 2000; Cayan and others, 2009) through year 2099, 

including these 3 projections, can be identified by geographic location, downloaded, and stored in 

comma-seperated values format (U.S. Department of the Interior and others, 2013) that can be read in 

WEAP. These climate projections have been bias-corrected and further scaled down to 0.125 degree (12 

× 12 km2

) resolution from the 2.5-degree (275 × 275 km2) resolution of antecedent global climate 

models (GCMs).
19

Urban Growth Projections

California has one of the most rapidly increasing human populations (in total residents) in the 

United States (American Farmland Trust, 1995; U.S. Census Bureau, 2014), and resulting urbanization 

impacts waterbirds by replacing their agriculture and wetland habitats with urban areas and by reducing 

water available for habitat management (Hathaway and Welch, 2002; Fleskes, 2012). We evaluated 

“strategic” and “expansive” urban growth scenarios developed for the California Water Plan Update 

2013 (California Department of Water Resources, 2013) that differed substantially in terms of projected 

growth. Depending on region (that is, DWR Planning Area) within the Central Valley and SacramentoSan Joaquin Delta, total irrigated crop area was projected to decrease by 0–29 percent under strategic 

growth rates and 18–86 percent under expansive growth rates by year 2100. Crop projections that we 

calculated through year 2099 produce uniform decreases in areas of all crop types by the proportion of 

projected total crop area decreases in respective DWR Planning Areas. We produced corresponding 

projections of increases in urban outdoor areas specific to each DWR Planning Area to represent crop 

land conversion into urban area. We produced projections of urban indoor demands for each growth 

scenario by scaling urban indoor household (single- and multi-family), industrial, and commercial 

demand units to appropriately correspond with urban outdoor demand projections.

Water Management: Streamflow Requirements

Streamflow requirements can impact waterbirds by restricting the timing and amount of water 

that can be diverted for waterbird habitat management. Numerous environmental flow requirements 

exist in WEAP-CV, and other flow requirements have been proposed for streams throughout the Central 

Valley (for example, reduced diversions to augment flows in Butte Creek for spring-run Chinook 

salmon and steelhead trout migration and rearing [California Department of Fish and Game, 2005]). For 

demonstration purposes, we modeled a hypothetical scenario reflecting greater fisheries protection by 

requiring that minimum instream flow requirements (IFRs) during October–June be increased by 142 

m3

/s year-round in the Sacramento and Feather Rivers and by 14 m3/s during October–June in Butte 

Creek and the Sutter Bypass. Modeling Butte Creek and Sutter Bypass flow requirements in WEAPCVwh involved adding flow requirement nodes on Butte Creek upstream of the Butte Slough-Sutter 

Bypass confluence and on the Sutter Bypass downstream of Sacramento Slough. 

The streamflow requirements modeled for Sacramento and Feather Rivers, respectively, 

represent mean annual increases of 118 and 465 percent in minimum flow compared to flow 

requirements already existing in the model. The flow requirements modeled for Butte Creek and Sutter 

Bypass represent a mean annual increase of 1,022 percent in minimum flow compared to an existing 

flow requirement on Butte Creek that is upstream of the modeled flow requirements. Modeled flow 

requirements were for demonstration; scenario flow requirements were not intended to model (and

would likely exceed) proposed or future flow requirements for these tributaries. 
20

Water Management: Rice Land Idling

Rice fields provide a large proportion of the food habitat for many waterfowl and other 

waterbird species (Elphick and Oring, 1998). To demonstrate how water supply management potentially 

could impact the amount of rice habitat, we modeled scenarios for which unmet urban water demands 

(indoor and outdoor) in and west of the San Joaquin and Tulare Basins (that is, WEAP-CVwh Planning 

Areas 606 and 702) were fulfilled by allowing through-Delta transfer of water supplies made available 

by increased fallowing of rice land in Butte Basin (fig. 2). For scenarios combining rice land idling with 

projected urbanization, urban water demand was projected through year 2065 based on projected urban 

growth throughout the Central Valley. Thus, unmet urban demand for water in Planning Areas 606 and 

702 also changed through time with projected urbanization.

This scenario allowed for unlimited fallowing of rice land in Butte Basin necessary to meet any 

unmet water needs in Planning Areas 606 and 702, assuming that the use of water transferred from the 

Sacramento River system would be preferable to other available water supplies (that is., groundwater 

and San Joaquin River water), and that development of any required new local water distribution 

facilities would be cost-effective. In this scenario, all water was transferred solely during July–

September (when allowed by current transfer policy) directly to WEAP-CVwh Planning Areas 606 and 

702 for urban demands, and no additional water was transferred to storage in the San Luis Reservoir 

throughout the year. Specific changes were made to the model structural components and model 

constraints to appropriately model the amount of supply that could be transferred based on scenario 

assumptions (appendix A, table A3). 

Evaluating Scenarios

For demonstration purposes, we present modeling results of four of the scenarios that we 

developed, representing a range of conditions, and combine the three climate change projections (and 

recent historical [years 1971–2000] climate for comparison), two urban growth projections, and two 

water supply management scenarios. Modeling results indicated impacts of monthly historical (1971–

2000) and projected (2006–2065) changes in climate and urbanization and changes in water 

management on waterbird habitats within basins. For evaluating climate change impacts, modeling 

results were further divided for each scenario into “projection” periods 2006–2035 (30 years) and 2036–

2065 (30 years). To demonstrate using our modeling approach, results were provided for the following 

scenarios 1-4, representing a range of land and water resource conditions in Butte Basin through year 

2065: 

• Scenario 1. CNRM-CM3, B1 projected climate + Strategic urban growth projection; 

• Scenario 2. NCAR-CCSM3, A2 projected climate + Expansive urban growth projection;

• Scenario 3. Historical climate + Strategic urban growth projection + Sacramento River, Feather 

River, and Butte Creek IFRs; and

• Scenario 4. GFDL-CM2.1, A2 projected climate + Expansive urban growth projection + 

Unlimited Butte Basin rice-idling to meet urban water demands of Planning Areas 606 and 702. 
21

Results

Results of the four climate-urbanization-water management scenarios through year 2065 

demonstrate potential marked decreases in availability of Central Valley waterbird habitats. The climate 

impacts on waterbird habitats of scenario 2 (including the NCAR-CCSM3 A2 climate projection) were 

more frequent and generally more severe than the impacts of scenario 1 with the CNRM-CM3 B1 

climate projection (fig. 5). Relative to NCAR-CCSM3 A2 and CNRM-CM3 projections and to each 

other, projected impacts of historical and GFDL-CM2.1 A2 climates could not be easily interpreted 

because of interactions with water management also included in these scenarios. Among scenarios 1 and 

2 that did not include water management, projected impacts of urbanization on habitat were cumulative 

and greater for expansive urbanization than for strategic urbanization (fig. 5). Water management 

change scenarios 3 and 4 produced substantial decreases in waterbird habitats (fig. 5). In scenario 3, 

which included the IFRs, the greater fraction of the water required to remain in streams for fisheries 

greatly decreased diversions in historically dry years and, thus, waterbird habitat availability (fig. 5).

Scenario 4, which included rice-idling, resulted in the greatest cumulative decrease in habitat, showing 

impacts of the increasing demand for transferred water as the populations in Planning Areas 606 and 

702 grow (fig. 5). Impacts varied among types of waterbird habitats and months. In periods of severe 

drought, winter-dry rice was projected to be most impacted (fig. 6). Among the four example future 

scenarios modeled, scenario 3 including the IFRs caused the greatest decrease in habitats throughout all 

months of the wintering period, and no rice was winter-flooded in October because limited water 

supplies were allocated for rice in later months (fig. 6). However, scenario 4, including water transferrice idling, also produced similarly substantial reductions in winter-flooded rice habitat during 

November–March (fig. 6).
22

Figure 5. Proportion of existing waterbird habitat in Butte Basin, Central Valley of California, projected under each 

modeling scenario evaluating impacts of climate, urbanization, and two changes in water supply management (a 

series of enhanced instream flow requirements [IFRs] on major Sacramento Valley streams include a 14 cubic 

meters per second [m3/s] requirement on Lower Butte Creek during October–June, and an additional year-round 

142 m3/s requirement on each of the Sacramento and Feather Rivers; and Butte Basin rice-idling to meet urban 

water demands of Planning Areas 606 and 702).
23

Figure 6. Areas of Butte Basin, Central Valley of California, habitats used by waterbirds through the wintering 

period that are supported during the most severe drought period under each modeling scenario evaluated.

Scenarios evaluate impacts of climate, urbanization (strategic [SU], expansive [EU]), and two changes in water 

supply management (enhanced instream flow requirements [IFRs] on major Sacramento Valley streams, and 

regional water transfer from increased rice-idling).
24

Discussion

Although we focused our efforts on providing a tool for guiding habitat conservation for 

waterbirds, a similar scenario modeling tool and process could be used to address future uncertainty in 

habitat sustainability for other species as well. Our results were provided as instructive examples of the 

general types of scenarios that are of interest for resource management in the Central Valley and 

perhaps similar regions. Results demonstrate large annual variation and patterns in habitat response 

among different climate, and land and water management scenarios, illustrating the complexity and 

uncertainty in projected future habitat conditions. Monthly variation in the response of individual 

habitats also was relatively substantial among scenarios, similarly indicating the complexity and 

uncertainty in future conditions. Collectively, these findings support the value of using an approach 

similar to this one to evaluate uncertain future impacts. Additional subsequent “informed” steps in 

conservation planning to address such uncertainty then could be implemented. In the process of 

developing a tool for our use, several challenges were encountered, as discussed in section “Challenges 

to Adapting the WEAP-CV Model for Waterbird Habitats.” We also elucidate “lessons learned” through 

this model- and scenario-building process that are especially applicable to other investigations of 

impacts on habitats in regions where land and water resources are intensively managed. Finally, we 

describe specific applications of linking modeling output from this approach to the ecology and 

conservation of wildlife. 

Challenges to Adapting the WEAP-CV Model for Waterbird Habitats

Numerous challenges were encountered in the process of adapting WEAP-CV for waterbird 

habitats and identifying and evaluating an appropriate array of scenarios. Representing diversity in 

habitats and water supplies and possible future scenarios impacting certain important water supplies and 

habitats required substantial effort in adapting WEAP-CV. Examples of water supplies and habitats 

subject to substantial potential risk included Butte Creek runoff and agricultural return flows in the 

Sacramento Valley and low-priority agriculture and wetlands. Challenges included:

1. Researching available GIS data for characterizing habitats and HUs.

2. Extensive pre-processing to disaggregate and import land cover data into WEAP-CVwh. 

3. Model development and calibration of Butte Creek streamflow.

4. Researching model parameterization and calibration of habitat water demands and supplies, 

including instream flow requirements on Butte Creek. 

5. Researching and model parameterization of water drainage, supply distribution systems, and 

delivery constraints. 

6. Researching operational and regulatory restrictions applying to through-delta water transfers and 

developing link-node complex for modeling rice land idling scenario. 

7. Parameterizing projections for conversion of crop areas to urban landscape through year 2065. 

8. Parameterizing projections of urban indoor water use consistent with increases in urban 

landscape through year 2065. 
25

Modeling Lessons

Although evaluating future impacts on habitats within a highly managed ecosystem such as the 

California Central Valley would seem to be more tractable than in less controlled environments, the 

scope and complexity of even heavily managed systems can pose numerous challenges. This is 

especially true for geographically large areas containing numerous heterogeneous interacting land and 

water resources, management entities, water supply operational rules, and regulations. Researching 

available options and identifying an impact-analysis tool that requires the least amount of effort to 

implement necessary changes is essential for success. Optimally, a tool (for example, a water resources 

model) representing the study system already would be available. However, even when an evaluation 

tool is available (that is, WEAP-CV for this Central Valley evaluation), much effort and staff time may 

be required to adapt and implement the tool to address the target conservation issues. In this study, the 

WEAP-CV framework was available as a template for our own model, but considerable effort was 

needed to overcome differences in spatial and temporal detail already in WEAP-CV and that which was 

required for our water resources model. Prior to disaggregating the less detailed model, it was important 

to fully understand the spatial scale of influence for all water supply management options. Research was 

required to represent water supply and delivery constraints at a high level of spatial and temporal detail.

Substantial variation in supply sourcing and drainage network also needed to be represented in the more 

detailed model. 

Through literature research and extensive GIS resources, the necessary information was obtained 

to develop a sufficient understanding of the habitat landscape and optimal water management practices 

for habitats. However, we discovered the difficulty of obtaining detailed information on and developing 

a robust understanding of “on-farm” water management for habitats when environmental and regulatory 

conditions precluded optimal water management for habitats. For example, what are the water 

conservation or best-management practices and resulting changes in timing and amounts of water 

applied under extreme drought and water allocation curtailment? The better the understanding of current 

decision making under a range of historical adverse conditions prohibiting optimal on-farm management 

of water supplies, the better we will be able to realistically account for water management decisions in 

scenarios of future conditions. One way to address this uncertainty in water management is to include 

plausible management practices in scenario modeling. One disadvantage of producing new scenarios 

based on water management is a corresponding increase in the modeling effort. Further improvement of 

understanding of water management decisions may prevent unnecessarily modeling some scenarios and 

may help reduce the number of future candidate scenarios. 
26

Applications of Modeling Approach

This general modeling approach would be useful for conservation planning of wetlands and 

other habitats both inside and outside of the Central Valley. This approach will become increasingly 

appropriate as information about responses of environmental and ecological conditions to anthropogenic 

factors is enhanced through time. As more and better data on ecological-anthropogenic relationships 

become available with time, these data can be used to inform new modeling scenarios. For example, 

impacts of exotic species on native habitats continue to be one of the most critical wildlife conservation 

concerns and are a source of great uncertainty in future sustainability of habitats in many regions, 

including the Central Valley (Fleskes, 2012), suggesting a great need and opportunity for scenario 

analysis. While relationships between anthropogenic factors (for example, between water supply 

management restrictions and climate change) and their resulting cumulative impacts may vary 

considerably, so may relationships between exotic species invasion and expansion and anthropogenic 

factors. Corresponding with progressive anthropogenic changes in natural resources, adaptive 

advantages of native species relative to exotic species generally may decrease through time (Byers, 

2002). Therefore, varying levels and types of anthropogenic changes to environmental conditions may 

cause differing rates of impact by exotic species on habitats through time. In modeling scenarios, 

researchers could vary projections of exotic species invasion and expansion with levels of other factors 

to reflect studied relationships between them. For example, issues of climate change exacerbating exotic 

species invasions have received increasing attention by researchers and conservationists alike (for 

example, Bellard and others, 2013; Vicente and others, 2013). 

A key component of wildlife conservation is understanding how various factors can impact the 

ability to sustain wildlife species at goal population levels. Some conservation efforts (for example, 

CVJV) have focused on a bioenergetics modeling approach of comparing food energy supplies with 

bioenergetic demands of organisms to assess food deficits under varying habitat conditions (Central 

Valley Joint Venture, 2006). To evaluate whether a set of environmental or habitat conditions supports 

goal wildlife populations, information on the projected amount of habitat is needed as an input variable 

for the bioenergetics model. We are using our habitat scenario modeling approach to effectively provide 

such habitat information to inform bioenergetics models, including an agent-based avian foraging model 

(Miller and others, 2013), for waterbirds in the Central Valley. Integrating these models, the 

sustainability of goal wintering waterbird populations can be evaluated based on available waterbird 

food supplies supported under each scenario combining projected anthropogenic impacts. Similarly, 

scenario impacts on goal breeding productivity can be evaluated by relating projected habitat conditions 

to waterbird reproduction and recruitment using different biological models. Combined analyses for 

wintering and breeding periods would provide critical information about the timing and extent of 

potential habitat limitations for each CVJV basin across a range of projected futures. With this 

information, habitat conservation and management goals can be adjusted and strategies robust to 

scenario impacts ultimately produced. 
27

A further advancement in integrating habitat scenario and bioenergetics models would involve a 

modeling effort linking them with other resource, demand, and socioeconomics models. The result 

would be a cross-disciplinary analytical platform assisting policy makers in determining strategies that 

are most supportive of the common good and robust to future uncertainty. We are pursuing 

collaborations to develop such a water resources decision support tool that can be used to balance the 

needs of competing California water users while also reducing conflict among them. In this proposed 

work, we would link our waterbird scenario and bioenergetics models with agricultural, 

socioeconomics, fisheries, urban, and energy models. The goal is to simultaneously compare 

socioeconomic and ecological costs and benefits among each water demand sector in response to 

potential policy-based strategies. Stakeholder engagement and a deliberative “robust decision making” 

process (Lempert and others, 2003) will guide strategies to be modeled for addressing uncertainty in 

climate change, water management, and other factors. 

Because of distinct regional differences in biotic and abiotic characteristics among study systems 

and often limited time and financial resources, researchers adopting this approach should prioritize 

scenario factors based on greatest potential impact or likelihood of impact. Researchers also should 

carefully consider the level of spatial and temporal detail required by the tool to correspond with the 

biology of target species. For example, animal migration or bioenergetic cost related to migration may 

be affected by the spatial distribution and contiguity of habitats, implying need for relatively greater 

spatial disaggregation. 

Conclusions

The goal of this report is to present a new scenario modeling approach to wildlife research and 

conservation fields for evaluating future potential impacts of various factors on wildlife habitats. We 

successfully implemented the use of this approach and integrated output from the approach with 

biological models. Using this type of integrated modeling, wildlife researchers and conservationists can 

ultimately translate scenario impacts on water and land resources into impacts on the ecology of wildlife 

species to assess future sustainability of goal populations. A key feature of this approach is the ability to 

project and account for interactions and the collective impacts of multiple anthropogenic stressors on 

habitats. For the last 3 decades, a growing focus of conservation planning studies has been climate 

change impacts on habitats and biodiversity. However, increasingly more landscapes are intensively 

managed by humans, and research that projects the effects of groups of multiple anthropogenic stressors 

(in conjunction with climate change) would provide useful information for habitat conservation and 

management. In places such as the Central Valley, where water supplies supporting most habitats are 

intensively managed, adaptation or development of a water supply and allocation model with scenarioprojection capabilities may be an essential part of the process. Regardless of the initial framework for 

tool development, results from this study suggest that an approach accommodating uncertainty would 

benefit future natural resource management and policy.
28

We are hopeful that research based on our approach will help bridge the gap between science 

and policy. Because this approach provides a framework for concurrently evaluating impacts and 

mitigating strategies resulting from future policy decisions, we believe that it succeeds as a guidance 

tool for decision makers. However, the value of information provided through this approach, like other 

modeling approaches, will be limited by the availability and quality of input data. The development of 

this model and these scenarios relied on multiple disparate data sources of mixed or unknown quality, so 

understanding effects of data quality on results would be difficult. 

Despite the facilitation that this general modeling approach can provide for future conservation, 

management, and policy of wildlife habitats, specific capabilities could further enhance its usefulness 

for decision making. Through our current efforts with collaborators, we are working to expand 

capability in modeling habitat restoration and management actions to evaluate the robustness of 

proposed strategies to future uncertainty. One additional enhancement, not discussed earlier in this 

report, would include estimating uncertainty in future habitat areas that are projected based on a given 

scenario (for example, through year 2099). Using our approach, this would involve propagating 

uncertainty across all factor projections, in turn, requiring data on uncertainty for each projection in a 

given scenario. Results from this study indicate that development of this functionality would be 

worthwhile for informing future land and resource management processes, and that substantial 

additional resources would be needed to support such an effort. 

Acknowledgments

We thank the numerous individuals and organizations that helped make this study possible. 

Operational funding was provided by the California Landscape Conservation Cooperative, California 

Department of Fish and Wildlife, Delta Waterfowl Foundation, U.S. Fish and Wildlife Service, and 

Central Valley Joint Venture (CVJV), with in-kind salaries and computing equipment and logistical 

support provided by all project partners including U.S. Geological Survey-Western Ecological Research 

Center (USGS-WERC), Ducks Unlimited, Inc. (DU), Stockholm, Environmental Institute (SEI), Point 

Blue Conservation Science, and University of California-Davis. Ben Gustafson and Bill Perry (both of 

USGS-WERC) provided geographic information system (GIS) support. Mark Petrie (DU) provided 

substantial background information helping to inform WEAP-CVwh model development and data postprocessing. We thank Kevin Petrik (formerly of DU) for providing GIS datasets for land cover and 

management of wetlands, and CVJV basin boundaries, and for information on water management on 

harvested rice fields. Jack Sieber (SEI) provided WEAP technical support. We thank the California 

Department of Water Resources and affiliate contractors for providing the WEAP-CV model and 

supporting documentation. We also acknowledge the modeling groups, the Program for Climate Model 

Diagnosis and Intercomparison (PCMDI) and the World Climate Research Programme (WCRP) 

Working Group on Coupled Modelling (WGCM) for their roles in making available the WCRP CMIP3 

multi-model dataset. Support of this dataset is provided by the Office of Science, U.S. Department of 

Energy. 
29

References Cited

Ackerman, J., Takekawa, J.Y., Orthmeyer, D.L., Fleskes, J.P., Yee, J.L., and Kruse, K.L., 2006, Spatial use 

by wintering greater white-fronted geese relative to a decade of habitat change in California’s Central 

Valley: Journal of Wildlife Management, v. 70, no. 4, p. 965–976. 

American Farmland Trust, 1995, Alternatives for future urban growth in California’s Central Valley—The 

bottom line for agriculture and taxpayers: Washington, D.C., and Davis, Calif., American Farmland Trust, 

129 p. 

Baldassarre, G.A., and Bolen, E.G., 2006, Waterfowl ecology and management (2d ed.): Malabar, Fla.,

Krieger Publishing Company, 567 p. 

Bellard, C., Thuiller, W., Leroy, B., Genovesi, P., Bakkenes, M., and Courchamp, F., 2013, Will climate 

change promote future invasions?: Global Change Biology, v. 19, no. 12, p. 3,740–3,748. 

Brinson, M.M., and Malvárez, A.I., 2002, Temperate freshwater wetlands: types, status, and threats: 

Environmental Conservation, v. 29, no. 2, p. 115–133. 

Byers, J. E., 2002, Impact of non‐indigenous species on natives enhanced by anthropogenic alteration of 

selection regimes: Oikos, v. 97, no. 3, p. 449–458. 

Cayan, D., Tyree, M., Pierce, D., and Das, T., 2012, Climate change and sea level rise scenarios for 

California vulnerability and adaptation assessment: California Climate Change Center, no. CEC‐500‐

2012‐008, 28 p. 

Cayan, D.R., Tyree, M., Dettinger, M.D., Hidalgo, H., Das, T., Maurer, E.P., Bromirski, P., Graham, N., and 

Flick, R., 2009, Climate change scenarios and sea level rise estimates for the California 2009 climate 

change scenarios assessment: California Climate Change Center, no. CEC-500-2009-014-F, 50 p. 

Central Valley Joint Venture, 2006, Central Valley Joint Venture implementation plan—Conserving bird 

habitat: Sacramento, Calif., U.S. Fish and Wildlife Service, 261 p. 

Central Valley Joint Venture, 2000, Central Valley wetlands water supply investigations—CVPIA 3406 

(d)(6)(A,B) —A report to Congress: U.S. Fish and Wildlife Service and Bureau of Reclamation, 296 p. 

Collins, W.D., and others, 2006, The community climate system model version 3 (CCSM3): Journal of 

Climate, v. 19, no. 11, p. 2,122–2,143. 

Dawson, T.P., Jackson, S.T., House, J.I., Prentice, I.C., and Mace, G.M., 2011, Beyond predictions—

Biodiversity conservation in a changing climate: Science, v. 332, p. 53–58. 

California Department of Fish and Game, 2005, Butte Creek, California Department of Fish and Game 

Anadromous Fish Restoration and Calfed Progams: California Department of Fish and Game, accessed 

June 17, 2013, at http://www.buttecreek.org/documents/ButteCreekAnadromousFishRestoration.pdf. 

California Department of Water Resources, 2003, Rice straw decomposition and water use: California 

Department of Water Resources draft memorandum, 7 p. 

California Department of Water Resources, 2013, State Water Analysis Network Workshop, Statewide 

WEAP Demand Model CWP 2013 Preliminary Results, February 2013: California Department of Water 

Resources, accessed January 5, 2015, at 

http://www.waterplan.water.ca.gov/docs/meeting_materials/swan/2013.02.13/6-

WEAP_Statewide_9scenarios_2013_copy.pdf. 

California Department of Water Resources, 2013, California Water Plan Update 2013: California 

Department of Water Resources, accessed May 15, 2013, at 

http://www.waterplan.water.ca.gov/cwpu2013/index.cfm. 

Delworth, T., and others, 2006, GFDL’s CM2 global coupled climate models—Part 1—Formulation and 

simulation characteristics: Journal of Climate, v. 19, no. 5, p. 643–674. 

Elphick, C.S., and Oring, L.W., 1998, Winter management of California rice fields for waterbirds: Journal of 

Applied Ecology, v. 35, no. 1, p. 95–108. 
30

Environmental Systems Resource Institute, Inc., 2012, ArcMapTM 10.1: Redlands, Calif., Environmental 

Systems Resource Institute, Inc. 

Fleskes, J.P., 2012, Wetlands of the Central Valley of California and Klamath Basin, in Batzer, D. and 

Baldwin, A., eds., Wetland habitats of North America: ecology and conservation concerns: Berkeley, 

Calif., University of California Press, p. 357–370. 

Fleskes, J.P., Perry, W.M., Petrik, K.L., Spell, R., and Reid, F., 2005, Change in area of winter-flooded and 

dry rice in the northern Central Valley of California determined by satellite imagery: California Fish and 

Game, v. 91, no. 3, p. 207–215. 

Fleskes, J.P., Skalos, D.S., and Farinha, M.A., 2012, Bird use of fields treated postharvest with two types of 

flooding in Tulare Basin, California: Journal of Fish and Wildlife Management, v. 3, no. 1, p. 164–174. 

Hathaway, R., and Welch, T., 2002, Background, in Braunworth, W.S., Jr., Hathaway, R., and Carlson, H., 

eds., Water allocation in the Klamath Reclamation Project, 2001—An assessment of natural resource, 

economic, social, and institutional issues with a focus on Upper Klamath Basin: Corvallis, Oregon, 

Oregon State University Extension Service, p. 31–43. 

Heller, N.E., and Zavaleta, E.S., 2009, Biodiversity management in the face of climate change—A review of 

22 years of recommendations: Biological Conservation, v. 142, no. 1, p. 14–32.

Hoekstra, J.M., Boucher, T.M., Ricketts, T.H., and Roberts, C., 2005, Confronting a biome crisis—Global 

disparities of habitat loss and protection: Ecology Letters, v. 8, no. 1, p. 23–29. 

Holling, C.S., and Meffe, G.K., 1996, Command and control and the pathology of natural resource 

management: Conservation Biology, v.10, no. 2, p. 328–337. 

Jetz, W., Wilcove, D.S., and Dobson, A.P., 2007, Projected impacts of climate and land-use change on the 

global diversity of birds: PLoS Biology, v. 5, no. 6, p. 1,211–1,219. 

Joyce, B., Purkey, D., Yates, D., Groves, D., and Draper, A., 2010, Integrated scenario analysis for the 2009 

California Water Plan update: California Department of Water Resources technical memorandum, 97 p. 

Joyce, B.A., Mehta, V., Purkey, D., Dale, L., and Hannemann, M., 2011, Modifying agricultural water 

management to adapt to climate change in California's Central Valley: Climatic Change, v. 109, no. 1, p. 

299–316. 

Lempert, R.J., Popper, S.W., and Bankes, S.C., 2003, Shaping the next one hundred years—New methods 

for quantitative, long-term policy analysis: Santa Monica, Calif., RAND Corporation, accessed July 17, 

2013, at http://www.rand.org/pubs/monograph_reports/MR1626. 

Meyer, J.L., Sale, M.J., Mulholland, P.J., and Poff, N.L., 1999, Impacts of climate change on aquatic 

ecosystem functioning and health: Journal of the American Water Resources Association, v. 35, no. 6, p. 

1,373–1,386. 

Miller, M.L., Ringelman, K.M., Schank, J.C., and Eadie, J.M., 2013, SWAMP—An agent-based model for 

wetland and waterfowl conservation management: Simulation, v. 90, no. 1, p. 52–68. 

Myers, N., 1996, The rich diversity of biodiversity issues, in Reaka-Kudla, M.L., Wilson, D.E., Wilson, 

E.O., and Keener, C.S., eds., Biodiversity II—Understanding and protecting our biological resources: 

Washington, D.C., Joseph Henry Press, p. 125–138. 

Nakicenovic, N., and others, 2000, Special report on emissions scenarios—A special report of Working 

Group III of the Intergovernmental Panel on Climate Change: Cambridge, United Kingdom, Cambridge 

University Press, 599 p. 

Peterson, G.D., Cumming, G.S., and Carpenter, S.R., 2003, Scenario planning—A tool for conservation in 

an uncertain world: Conservation Biology, v. 17, no. 2, p. 358–366. 

Pilkey‐Jarvis, L., and Pilkey, O.H., 2008, Useless arithmetic—Ten points to ponder when using 

mathematical models in environmental decision making: Public Administration Review, v. 68, no. 3, p. 

470–479. 
31

Salas-Mélia, D., Chauvin, F., Déqué, M., Douville, H., Gueremy, J.F., Marquet, P., Planton, S., Royer, J.F., 

and Tyteca, S., 2005, Description and validation of the CNRM-CM3 global coupled model: Manuscript 

draft submitted to Climate Dynamics (in 2005), accessed May 15, 2013, at 

http://www.cnrm.meteo.fr/scenario2004/paper_cm3.pdf. 

Stockholm Environment Institute, 2011, The WEAP User Guide, May 2011: Stockholm Environment 

Institute, accessed December 5, 2013, at http://www.weap21.org/downloads/WEAP_User_Guide.pdf. 

Stouffer, R.J., and others, 2006, GFDL’s CM2 global coupled climate models—Part 4—Idealized climate 

response: Journal of Climate, v. 19, no. 5, p. 723–740. 

Thompson, L.C., Escobar, M.I., Mosser, C.M., Purkey, D.R., Yates, D., and Moyle, P.B., 2012, Water 

management adaptations to prevent loss of spring-run Chinook salmon in California under climate change: 

Journal of Water Resources Planning and Management, v.138, no. 5, p. 465–478. 

Tilman, D., Fargoine, J., Wolff, B., D’Antonio, C., Dobson, A., Howarth, R., Schindler, D., Schlesinger, 

W.H., Simberloff, D., and Swackhamer, D., 2001, Forecasting agriculturally driven global environmental 

change: Science, v. 292, p. 281–284. 

U.S. Census Bureau, 2014, Cumulative Estimates of the Resident Population Change for the United States, 

Regions, States, and Puerto Rico: April 1, 2010 to July 1, 2014 (NST-EST2014-02): U.S. Census Bureau, 

accessed December 30, 2014, at http://www.census.gov/popest/data/state/totals/2014/index.html. 

U.S. Department of Agriculture, 2010, Field crops usual planting and harvesting dates: U.S. Department of 

Agriculture, National Agricultural Statistics Service, accessed May 10, 2013, at 

http://usda01.library.cornell.edu/usda/current/planting/planting-10-29-2010.pdf. 

U.S. Department of Agriculture, 2011, Quick stats: U.S. Department of Agriculture, National Agricultural 

Statistics Service database, accessed August 2, 2012, at http://quickstats.nass.usda.gov/. 

U.S. Department of the Interior and others, 2013, Downscaled CMIP3 and CMIP5 Climate and Hydrology 

Projections, accessed May 15, 2013, at http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/. 

Vicente, J.R., Fernandes, R.F., Randin, C.F., Broennimann, O., Gonçalves, J., Marcos, B., Pôças, I., Alves, 

P., Guisan, A., and Honrado, J.P., 2013, Will climate change drive alien invasive plants into areas of high 

protection value?—An improved model-based regional assessment to prioritise the management of 

invasions: Journal of Environmental Management, v. 131, p. 185–195. 

Stockholm Environment Institute, Water Evaluation and Planning (WEAP) system model: Stockholm 

Environment Institute Web site, accessed November 6, 2013, at http://www.weap21.org/. 

Yates, D., Purkey, D., Sieber, J., Huber-Lee, A., Galbraith, H., West, J., Herrod-Julius, S., Young, C., Joyce, 

B., and Raye, M., 2009, Climate driven water resources model of Sacramento Basin, California: Journal of 

Water Resources Planning and Management, v. 135, no. 5, p. 303–313. 

Yates, D., Sieber, J., Purkey, D., and Huber-Lee, A., 2005a, WEAP21—A demand, priority, and preference 

driven water planning model—Part 1—Model characteristics: Journal of Water International, v. 30, no. 4, 

p. 487–500. 

Yates, D., Sieber, J., Purkey, D., and Huber-Lee, A., 2005b, WEAP21—A demand, priority, and preference 

driven water planning model—Part 2—Aiding freshwater ecosystem service evaluation: Journal of Water 

International, v. 30, no. 4, p. 501–512. 
32

Appendix A. Description of Water Evaluation and Planning System Model for the 

Central Valley (WEAP-CV) and Adapted for Waterbird Habitats (WEAP-CVwh) 

Used in Scenario Modeling

Watershed characteristics represented in WEAP-CV are State, Federal, and private water supply 

and delivery projects, groundwater, major surface streams, and estimated demands for water by 

agricultural and urban users. WEAP-CV additionally includes physical (for example, reservoir 

capacity), operational (for example, reservoir storage rules), and regulatory constraints (for example, 

various streamflow requirements and priority of water use among users) on water use. Water delivery 

system constraints are reflected in model variables including supply priority, water supply preferences, 

and maximum flow limits. Supply priority (referred to as “Demand priority” in WEAP software) 

represents the priority of water allocation among all types of competing water demands (table A2).

Water supply preference represents the relative preferences of potential supplies used by a particular 

demand site (for example, greater preference for water from Feather River than Sacramento River or 

groundwater). Maximum flow rate of a potential supply is represented as the maximum amount 

(percentage) of demand site water demand that can be supported by a particular water supply, or as 

maximum flow rate (for example, cubic meters per second). The model evaluates three population 

growth scenarios—“Current Trends”, “Strategic Growth”, and “Expansive Growth”—representing 

various population growth and urban land-use projections (Joyce and others, 2010), although more 

recently six more demographic projections have been added (California Department of Water 

Resources, 2013). In 2011, WEAP-CV developers also included in the model 12 climate change 

scenarios projecting to year 2099. (Stockholm Environment Institute, 2011, provides greater technical 

detail about WEAP software used to develop WEAP models for the Central Valley.)
33

Table A1. Key model components in WEAP-CVwh used to represent watershed characteristics.

1. Catchment nodes (referred to as “catchments”): Using catchments in WEAP-CVwh was consistent with the existing structure of 

WEAP-CV, reducing required structural changes. Although multiple land cover types can be included in a single catchment, each 

catchment can be assigned solely one set of water supply sources and supply preferences, and one supply priority. Therefore, 

within a catchment, land covers cannot differ in water supplies, supply preferences, or priorities. This is a factor influencing the 

number of habitat catchments defined for each hydrologic unit represented in WEAP-CVwh. Using catchments in WEAP in 

contrast with “demand sites” is a more efficient and flexible way to model both hydrology and water demand for a region. Directly 

modeling hydrology using catchments, and not manually specifying surface runoff and infiltration to groundwater, generally allows 

more efficient and accurate modeling of temporally and spatially varying available water supplies. Water demands modeled using 

catchments will automatically respond to projected changes in climate, and no additional manual adjustment for climatic effects on 

demands are required. 

2. Catchment climate variables: Precipitation1 (monthly total), air temperature1 (weighted mean of monthly high and low 

temperature), wind (average monthly wind speed), humidity (average monthly relative humidity), cloudiness fraction (fraction of 

daytime hours with no clouds), initial snow (value for snow accumulation at beginning of simulation), melting point (liquid water 

threshold for snow melt), freezing point (solid water threshold for snow accumulation), latitude (latitude in degrees), albedo 

(fraction of solar radiation reflected by a land class), snow accumulation gage (historical snow accumulation data used in 

calibration).

3. Catchment soil and land-use variables: Area (land area, by land cover class), Kc (crop coefficient, by land class), root zone water 

capacity (effective water-holding capacity of top soil layer, by land class), runoff resistance factor (controls surface runoff 

response, by land class), root zone conductivity2 (root zone water conductivity rate [length/time] at full saturation, by land class), 

preferred flow direction (partitions flow of water in root zone between horizontal and vertical directions, by land class), initial z1

(percentage of total root zone water capacity at beginning of simulation, by land class).

4. Catchment irrigation variables: Irrigated area2 (percentage of area irrigated, by land class), lower threshold2 (soil moisture 

percentage less than this level initiates irrigation, by land class), upper threshold2 (soil moisture percentage at this level ceases 

irrigation, by land class).

5. Catchment pond-depth variables: Target depth2 (target water elevation in wetland pond or rice field), minimum depth (minimum 

water elevation in wetland pond or rice field), maximum depth (maximum water elevation in wetland pond or rice field 

corresponding with the depth of the wetland or field basins), release requirement (amount of water released and replaced with new 

supply in a timestep).

6. Runoff and infiltration links: Represents natural runoff and irrigation return flow from catchments to surface water and 

groundwater, respectively.

7. Demand site nodes: Are in contrast with catchments and do not model water demand as a function of climate, but, rather, require 

demand as an input.

8. Return flow links: Represents return flows from demand sites and wastewater treatment plants to rivers and diversions. In WEAPCV and WEAP-CVwh, they generally represent return flows from urban demand site nodes (in contrast with catchment nodes).

9. River links: Represents aggregate watershed runoff and baseflow that can be stored in reservoirs, diverted by users, or remain 

instream for fisheries or other non-consumptive uses.

10. Diversion links: Represents large water delivery canals with maximum monthly diversion limits.

11. Transmission links: Represents water delivery to catchments and demand sites and related physical or other constraints in 

delivering water from a source.

12. Flow requirement node: Defines the minimum instream flow required at a point on a river or diversion link to serve fisheries or 

other modeled requirements.

13. Reservoir nodes: Represents reservoir sites on rivers and are conditioned on operating rules and demand priorities to release water 

for use downstream and for hydropower generation.

14. Groundwater nodes: Represents aquifers that receive and store infiltration from catchments and other sources, and provide 

groundwater supply for overlying demands.

1

Climate projection data were used as input for the variable.

2

Variables used to calibrate water demands of wetlands and winter-flooded rice.
34

Table A2. Water supply demand priorities in WEAP-CV and WEAP-CVwh Models.

Demand sector WEAP-CV priority WEAP-CVwh priority

Urban indoor 1 (highest priority) 1

Public wetland (CVPIA) 11 1

Public wetland (other) NR1 3

Private wetland (High-reliability) NR1 3

Private wetland (Low-reliability) NR1 3

Instream flow 2 2

Agriculture 3 3

Urban outdoor 3 3

Hydropower 4 4

Reservoirs 14–20 14–20

Flood control outside of bypasses 98 98

Sutter and Yolo flood bypass systems 99 99

1

WEAP-CV Model only defines managed public wetlands receiving water through Central Valley Project Improvement Act (CVPIA) 

contracts; other wetlands were not represented (NR) in the model. 
35

Table A3. Documentation of additional processing steps for developing WEAP-CVwh and modeling-specific 

scenarios.

1. Classification of agricultural crops:

Some California Department of Water Resources (DWR) Planning Areas in WEAP-CV intersecting Central Valley Joint 

Venture (CVJV) basin boundaries lacked detail in crop classifications required for WEAP-CVwh. Where Planning Areas and 

basins intersected, we used DWR geographic information system crop land cover data to calculate crop areas and to classify 

crops in greater detail. In WEAP-CVwh, we added the more detailed crop information where it was lacking. 

2. Classification of wetlands: 

Areas of wetlands estimated in Central Valley Joint Venture (2000) were less than more recent estimates (i.e., years 2003–

04) of seasonal and semipermanent wetlands on private land provided in Central Valley Joint Venture (2006).

Consequently, we applied proportions of private wetland area distinguished by water supply reliability in Central Valley 

Joint Venture (2000) to updated wetland areas based on Central Valley Joint Venture (2006) to classify private wetland 

areas used in WEAP-CVwh. 

3. Model adjustments required for water management-rice land idling scenario: 

State Water Project and the Federal Central Valley Project diversions were disconnected from the Sacramento-San Joaquin 

Delta. We replaced delta-diversion connections with two demand site nodes and related return flow links. The indicated 

links and nodes were used to represent the total flow into project diversions under selected climate-urbanization conditions.

We added a complex of transmission links and nodes, demand site node, return flow links and nodes, and diversion link to 

represent additional water transferred from the Sacramento River system to Planning Areas 606 and 702 indoor and outdoor 

urban demands. Before modeling a south-of-delta transfer, initial model output from a selected combination of climate and 

urbanization projections was exported to data files that then were used in adding new constraints to the model in subsequent 

simulation. Output from the climate-urbanization scenario simulation (in the absence of additional transfer of rice irrigation 

water modeled in the subsequent simulation) was (1) projected amounts of water conveyed through State and Federal 

project facilities to south-of-delta users, (2) water delivered to Planning Areas 606 and 702 urban from the Delta compared 

to all other sources, and (3) the relative fraction of water from each surface water source (Sacramento River, Butte CreekSutter Bypass, and Feather River) delivered to irrigate rice land in Butte Basin. The scenario was further evaluated in a 

separate subsequent model simulation. In this simulation, we constrained water transfer amounts: (1) conveyed through the 

State and Federal project pumping facilities in the delta to the remaining operational capacity of the projects, (2) to Planning 

Areas 606 and 702 urban demands based on their remaining water requirement not supported through any projected 

contracted delta deliveries each month, and (3) transferred from each of the three Sacramento River system sources to 

reflect the proportion of water from each source typically allocated to rice in Butte Basin. Additionally, we limited the 

transfer of water to an annual maximum limit of 623,188.3 thousand cubic meters) based on 61,957 rice hectares in Butte 

Basin at 3.3 acre-foot credit per acre (or about 10 thousand cubic meter credit per hectare) rice fallowed under current DWR 

transfer policy. We accounted for assessed 20 percent carriage water loss of water transferred through the delta (Nancy 

Quan, oral commun., May 9, 2012) by adjusting model return flow link routing accordingly. Although the modeled

transfers were limited solely to July–September, water deliveries to rice catchment nodes from the three Sacramento River 

system sources were deactivated in the model and rice could solely receive water from groundwater and some local natural 

runoff and return flows throughout the time series. In this scenario, we assume no substitution of groundwater for the 

surface water that was transferred through rice land idling, as might occur under strict local groundwater ordinances.

However, farmers are allowed to substitute groundwater for transferred surface water under current law. To calculate the 

rice area supported under a similar scenario that includes groundwater substitution, we could reduce the amount of 

calculated rice area fallowed proportionally with the fraction of the water demand for growing rice maximally supported 

through groundwater pumping. This groundwater fraction may be based on the literature or the maximum flow (percent of 

demand) catchment data used in WEAP-CVwh (see section, “Water Supply and Delivery Constraints,” for details) weighted 

by respective catchment areas and averaged.
36

Appendix B. Information Used in Producing Water Evaluation and Planning 

System Model for the Central Valley of California Adapted for Waterbird Habitat

(WEAP-CVwh) for the Scenario Modeling Approach

Table B1. Information used in producing WEAP-CVwh for the scenario modeling approach to evaluate projected 

climate, land management, and water supply management impacts on managed wetland habitats in Butte 

hydrologic basin of the Central Valley of California. 

[Information source: See table B3 for complete references and acronym definitions. Information periodically is updated to reflect 

development of the approach for additional Central Valley Joint Venture (CVJV) basins and other enhancements at 

http://www.werc.usgs.gov/climatewaterbirds] 

Modeling component Basin Information sources (years) Use of information

Habitat areas All basins DU (1993, 1999, 2011); Mark 

Petrie (DU, written commun., 

2010, 2012)

Calculating wetland distributions used for 

area disaggregation by hydrologic unit 

(HU)

1

Habitat areas All basins CVJV (2006) Areas to be disaggregated1,2

Habitat areas All basins CVJV (2000) Calculating wetland areas of varying water 

supply reliability1

Water supplies and 

management

All basins CVJV (2000); DU (2009); 

USFWS-WMPs (various dates); 

USFWS-CCP (2008, 2009); 

CVRWQCB (2006); Drexler 

and others (2008); Smith and 

others (1994)

Wetland water sources, supplies, 

requirements1; hydrologic basin and 

subbasin maps for HU delineation1

; 

wetland ET rates1; wetland management1

Water supplies and 

management

Butte Basin DFW (2009); CDM (2001) Wetland water sources and supplies1

Water supplies and 

management

All basins Reclamation and DWR (2004, 

2010); DWR (1993, 2010);

BCWC (1998); WDCWA 

(2012)

Include DWR Planning Areas in HU 

delineation1; Include groundwater basins 

in HU delineation1

Water supply and 

delivery constraints

All basins Reclamation and DWR (2003–04, 

2009); DWR (1995–2004)

Calculating maximum fractions of wetland 

water demands supplied by each water 

source1

Water supply and 

delivery constraints

Butte Basin DFW (2009); Butte County 

(2012); CDM (2001); SRSC 

(2006, 2011); DWR (2002)

Calculating maximum fractions of wetland 

water demands supplied by each water 

source1

, maximum groundwater 

pumping rates1

Water supply and 

delivery constraints

Butte Basin DWR-WS (2010) Calculating historical instream flow 

requirement for fish in Butte Creek1

Valley drainage areas 

and systems

All basins CV-SALTS (1992) Include drainages in HU delineation1

Valley drainage areas 

and systems

Butte, Colusa, 

Sutter, 

American, 

San Joaquin

USGS-NHD; Reclamation and 

DWR (2003–04); Reclamation 

and DWR (2006); DWR (1993); 

BCWC (1998); CDM (2008); 

LAFCO (2007); SRSC (2011)

Include drainages in HU delineation1

Climate projections All basins Reclamation and others (2013) Precipitation and temperature projections1,3

1

Used in producing WEAP-CVwh. 

2

Used in post-processing WEAP-CVwh model output to calculate habitat areas.

3

Already included in WEAP-CV, but may be updated in WEAP-CVwh based on available information.
37

Table B2. Information used in producing WEAP-CVwh for the scenario modeling approach to evaluate projected 

climate, land management, and water supply management impacts on agricultural habitats in Butte hydrologic 

basin of the Central Valley of California. 

[Information source: See table B3 for complete references and acronym definitions. Information is periodically updated to reflect 

development of the approach for additional CVJV basins and other enhancements at http://www.werc.usgs.gov/climatewaterbirds] 

Modeling component Basin Information sources Use of information

Habitat areas All basins DWR (1995–2004); DWR land survey 

staff (oral and written commun., 2011)

Calculating crop distributions used 

for area disaggregation1

Habitat areas All basins Kevin Petrik (formerly of Ducks 

Unlimited, Inc.) (written commun., 

2012)

Disaggregating areas of winterflooded rice for each basin1

Habitat areas Butte, Colusa DWR (1995–2004); Parts of areas to be disaggregated 

for which WEAP-CV could not 

be used1,2

Water supplies and 

management

All basins Brandon and others (1995); DWR (1998) Parameterization of water 

management for rice straw 

decomposition and habitat1

Water supplies and 

management

All basins Reclamation and DWR (2004, 2010); 

DWR (1993, 2010); BCWC (1998); 

WDCWA (2012)

Include DWR Planning Areas in 

hydrologic unit (HU) 

delineation1

; Include groundwater 

basins in HU delineation1

Water supply and 

delivery constraints

All basins Reclamation and DWR (2003–04, 2009); 

DWR (1995–2004)

Calculating maximum fractions of 

agricultural water demands 

supplied by each water source1

Water supply and 

delivery constraints

Butte Basin DFW (2009); Butte County (2012); CDM 

(2001); SRSC (2006); DWR (2002)

Calculating maximum fractions of 

agricultural water demands 

supplied by each water source1

, 

maximum groundwater pumping 

rates1

Water supply and 

delivery constraints

Butte Basin DWR-WS (2010) Calculating historical instream flow 

requirement for fish in Butte 

Creek1

Valley drainage areas 

and systems

All basins CV-SALTS (1992); Reclamation and 

DWR (2004)

Include drainages in HU 

delineation1

Valley drainage areas 

and systems

Butte, Colusa, 

Sutter, 

American, 

San Joaquin

USGS-NHD; Reclamation and DWR 

(2003–04, 2006); DWR (1993); BCWC 

(1998); CDM (2008); LAFCO (2007, 

2010); SRSC (2011

Include drainages in HU 

delineation1

Climate projections All basins Reclamation and others (2013) Precipitation and temperature 

projections1,3

Urbanization 

projections

All basins California Water Plan Update data from 

WEAP-CV developers

Urbanization rates of total 

agricultural land1

1

Used in producing WEAP-CVwh.

2

Used in post-processing WEAP-CVwh model output to calculate habitat areas.

3

Already included in WEAP-CV, but may be updated in WEAP-CVwh based on available information.
38

Table B3. References for information sources in appendix B, tables B1 and B2.

[Information is periodically updated to reflect development of the approach for additional Central Valley Joint Venture (CVJV) basins and 

other enhancements at http://www.werc.usgs.gov/climatewaterbirds] 

Information source Reference

BCWC Butte Creek Watershed Conservancy, 1998, Butte Creek Watershed Project, Existing 

conditions report: Butte Creek Watershed Conservancy, accessed January 6, 2015, at 

http://buttecreekwatershed.org/Watershed/ECR.htm.

Brandon and others Brandon, D.M., Brouder, S., Chaney, D., Hill, J.E., Payne, J.M., Scardaci, S.C., Williams, 

J.F., Wrysinski, J.E., 1995, Rice straw management today and tomorrow: Davis, University 

of California Cooperative Extension Publication.

Butte County Butte County, 2012, Butte Basin management objectives: Butte County Department of Water 

and Resource Conservation, accessed January 6, 2015, at 

http://www.buttecounty.net/waterresourceconservation/BasinManagementObjectives.aspx.

CDM Camp Dresser and McKee, Inc., 2008, Butte Basin Integrated Water Flow Model (IWFM), 

IWFM User’s Group, Presentation : Camp Dresser and McKee, Inc., accessed January 6, 

2015, at http://www.cwemf.org/workshops/GWWorkshop/2008/

Heywood_Butte_County_IWFM.pdf.

CDM Camp Dresser and McKee, Inc., 2001, Butte County water inventory and analysis report; 

Camp Dresser and McKee, Inc., accessed January 6, 2015, at 

http://www.buttecounty.net/Portals/26/Reports/2001/WaterInvetoryAnalysis2001Complete

ReportOptimized.pdf. 

CVJV Central Valley Joint Venture, 2006, Central Valley Joint Venture implementation plan—

Conserving bird habitat: Sacramento, Calif., U.S. Fish and Wildlife Service, 261 p.

CVJV Central Valley Joint Venture, 2000, Central Valley wetlands water supply investigations—

CVPIA 3406 (d)(6)(A,B) —A report to Congress: U.S. Fish and Wildlife Service and 

Bureau of Reclamation, 296 p.

CVRWQCB Central Valley Regional Water Quality Control Board, 2006, Irrigated lands management 

practices, chap. 5 of Irrigated Lands Discharge Program—Draft existing conditions report: 

Central Valley Regional Water Quality Control Board, accessed January 7, 2015, at 

http://www.waterboards.ca.gov/centralvalley/water_issues/irrigated_lands/new_waste_dis

charge_requirements/exist_cond_rpt/draft_existing_conditions_rpt/ch05.pdf.

CV-SALTS Central Valley Salinity Alternatives for Long-term Sustainability, 1992, California inland 

surface water plan documents: Central Valley Salinity Alternatives for Long-term 

Sustainability, accessed January 7, 2015, at 

http://www.cvsalinity.org/index.php/docs/documents-and-presentations/iswp-docs.html.

DFW California Department of Fish and Wildlife, 2009, Property description and management 

setting, chap. 2 of Upper Butte Basin Wildlife Area draft land management plan: California 

Department of Fish and Wildife.

Drexler and others Drexler, J.Z., Anderson, F.E., and Snyder, R.L., 2008, Evapotranspiration rates and crop 

coefficients for a restored marsh in the Sacramento–San Joaquin Delta, California, USA: 

Hydrological Processes, v. 22, no. 6, p. 725–735.

DU Ducks Unlimited, Inc., 2011, CVJV protected areas–Publicly and privately-owned upland and 

wetland habitat units, Vector polygon (geographic information system [GIS] dataset): 

Sacramento, Calif., U.S. Fish and Wildlife Service.

DU Ducks Unlimited, Inc. (DU), 2009, CVJV hydrologic basins, Vector polygon (GIS dataset): 

Sacramento, Calif., U.S. Fish and Wildlife Service.

DU Ducks Unlimited, Inc. (DU), 1999, Sacramento Valley, Seasonal and permanent palustrine 

wetlands in the Sacramento Valley, Raster (GIS dataset): Sacramento, Calif., U.S. Fish and 

Wildlife Service.

DU Ducks Unlimited, Inc. (DU), and California Department of Fish and Game, 1993. Wetland 

and riparian—Seasonal and permanent palustrine wetlands in the Sacramento Valley, 

Raster (GIS dataset): Sacramento, Calif., U.S. Fish and Wildlife Service.

DWR California Department of Water Resources, 2010, 

B118_v3_BasinBoundaries_NAD83_unprojected—California groundwater basins, Vector 

polygon (GIS dataset): California Department of Water Resources.

DWR California Department of Water Resources, 2002, Project 12B Sutter Extension Water District 

Sutter-Butte Main Canal Lining Project: California Department of Water Resources. 

DWR California Department of Water Resources, 1998, Rice straw decomposition and water use—

Draft report: California Department of Water Resources.
39

Information source Reference

DWR California Department of Water Resources, 1995–2004 (depending on county), Land cover 

surveys, Vector polygon (GIS dataset): California Department of Water Resources.

DWR California Department of Water Resources (DWR), 1993, Memorandum—Subject, Butte and 

Sutter Basins (summarizes water inflows, outflows, distributions within Butte and Sutter 

Basins): California Department of Water Resources.

DWR-WS California Department of Water Resources, 2010, Butte Creek Watermaster service schedule 

(WS): California Department of Water Resources.

LAFCO Butte Local Agency Formation Commission, 2007, 2010, Final municipal service review of 

irrigation, drainage, and reclamation service providers, and 2010 update for Butte Water 

District: Butte Local Agency Formation Commission.

Smith and others Smith, D.W., Rollins, G.L., Shinn, R., 1994, A guide to wetland habitat management in the 

Central Valley: California Department of Fish and Wildlife and California Waterfowl 

Association, 37 p.

SRSC Sacramento River Settlement Contractors and others, 2011, 2010/2011 Sacramento Valley 

Regional Water Management Plan—Annual update: Sacramento River Settlement 

Contractors and others, 247 p. 

SRSC Sacramento River Settlement Contractors and others, 2006, Final Sacramento Valley 

Regional Water Management Plan (SVRWMP): Sacramento River Settlement Contractors 

and others, 1,660 p.

Reclamation and others Bureau of Reclamation and others, 2013, Downscaled CMIP3 and CMIP5 Climate and 

Hydrology Projections, accessed May 15, 2013, at http://gdodcp.ucllnl.org/downscaled_cmip3_projections/.

Reclamation and DWR Bureau of Reclamation and California Department of Water Resources, 2010, Dwrdauv20—

DWR Planning Areas used in Water Evaluation and Planning system model for the Central 

Valley (WEAP-CV), Vector polygon (GIS dataset): Bureau of Reclamation and California 

Department of Water Resources.

Reclamation and DWR Bureau of Reclamation and California Department of Water Resources, 2009, Federal water 

districts, Vector polygon (GIS dataset): Bureau of Reclamation and California Department 

of Water Resources.

Reclamation and DWR Bureau of Reclamation and California Department of Water Resources, 2006, Reclamation 

districts, Vector polygon data (GIS): Bureau of Reclamation and California Department of 

Water Resources.

Reclamation and DWR Bureau of Reclamation and California Department of Water Resources, 2003–04. Wdpr24 -

Private Water Districts for California 1:24,000-scale; wdst24 - State Water Districts for 

California 1:24,000-scale, Vector polygon (GIS dataset): Bureau of Reclamation and 

California Department of Water Resources. 

Reclamation and DWR Bureau of Reclamation and California Department of Water Resources, 2004, CALSIM III 

draft proposed work plan for Sacramento Basin hydrology: Bureau of Reclamation and 

California Department of Water Resources.

Reclamation and others Bureau of Reclamation and others, 2013, Downscaled CMIP3 and CMIP5 Climate and 

Hydrology Projections, accessed May 15, 2013, at http://gdodcp.ucllnl.org/downscaled_cmip3_projections/.

USFWS-WMPs U.S. Fish and Wildlife Service [various dates], Refuge Water Management Plans: U.S. Fish 

and Wildlife Service, accessed November 12, 2013, at 

http://www.usbr.gov/mp/watershare/wcplans/.

USFWS-CCP U.S. Fish and Wildlife Service, 2008, 2009, Sacramento, Delevan, Colusa, and Sutter 

National Wildlife Refuges—Draft Comprehensive Conservation Plan: U.S. Fish and 

Wildlife Service.

USGS-NHD U.S. Geological Survey, National Hydrography Dataset (NHD): U.S. Geological Survey 

dataset, accessed May 13, 2013, at http://nhd.usgs.gov/.

WDCWA Woodland-Davis Clean Water Agency, 2012, Water supply for California Sacramento Valley 

Communities—Water source trend comparison: Woodland-Davis Clean Water Agency, 

accessed January 7, 2015, at 

http://www.wdcwa.com/images/uploadsdoc/Sac_Valley_Water_Source_Future_Compariso

n102512.pdf. 
40

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http://werc.usgs.gov/
Matchett and others—Framework for Modeling Impacts on Waterbird Habitats—Addressing Future Uncertainy in Conservation Planning Open-File Report 2015-1017 —

ISSN 2331-1258 (online)

http://dx.doi.org/10.3133/ofr20151017