U.S. Department of the Interior January 2020

Central Valley Project

Final Cost Allocation Study

Economic Benefits Analysis 

Appendix
Mission Statements

The mission of the Department of the Interior is to protect and provide access to our 

Nation’s natural and cultural heritage and honor our trust responsibilities to Indian Tribes 

and our commitments to island communities.

The mission of the Bureau of Reclamation is to manage, develop, and protect water and 

related resources in an environmentally and economically sound manner in the interest of 

the American public.
Economic Benefits Analysis Appendix | iii

Table of Contents

Page

Chapter 1. Introduction .................................................................................................................................. 1

Chapter 2. Irrigation Water Supply ............................................................................................................... 5

Chapter 3. Municipal and Industrial Water Supply................................................................................... 29

Chapter 4. Water Quality .............................................................................................................................. 43

Chapter 5. Flood Control ............................................................................................................................. 47

Chapter 6. Hydropower................................................................................................................................ 53

References....................................................................................................................................................... 61

List of Attachments

Attachment 1 – Economic Benefits Analytical Tool Descriptions

Attachment 2 – Forecast of Economic Value of CVP Power 2014-2113
iv | Central Valley Project Final Cost Allocation Study

This page intentionally left blank.
Economic Benefits Analysis Appendix | 1

Chapter 1. Introduction

The economic valuation approach for Federal water resource projects and the Central Valley Project 

(CVP) Final Cost Allocation Study (CAS) is consistent with the Federal Economic and 

Environmental Principles and Guidelines for Water and Related Land Resources Implementation 

Studies (P&G) (Water Resources Council 1983). The P&Gs support the Federal objective of 

contributing to national economic development in water and related land resources project planning 

consistent with protecting the nation’s environment, pursuant to national environmental statutes, 

applicable executive orders, and other Federal planning requirements. CVP CAS economic benefits 

were estimated for the four authorized project purposes that will share in joint costs of the CVP: 

water supply (including irrigation and municipal and industrial (M&I) water supplies), water quality, 

flood control, and hydropower.

This Economic Benefits Analysis Appendix to the CVP Final CAS is organized into the following 

chapters and attachments:

• Chapter 1, Introduction, provides a general background of economic benefits estimated for the 

CAS, including an overview of economic analysis parameters.

• Chapter 2, Irrigation Water Supply, describes the irrigation water supply economic benefit 

estimation methodology and results of the analysis.

• Chapter 3, Municipal and Industrial Water Supply, describes the M&I water supply economic 

benefit estimation methodology and results of the analysis.

• Chapter 4, Water Quality, describes the water quality economic benefit estimation 

methodology and results of the analysis.

• Chapter 5, Flood Control, describes the flood control economic benefit estimation 

methodology and results of the analysis.

• Chapter 6, Hydropower, describes the hydropower economic benefit estimation methodology 

and results of the analysis.

• The References section presents a comprehensive list of references used throughout this 

Appendix.

• The Economic Benefits Analytical Tool Descriptions Attachment, presents descriptions of economic 

analytical tools used to estimate economic benefits.

• The Forecast of Economic Value of CVP Power 2014-2113 Attachment, presents methodology and 

results of analysis to estimate hydropower benefits of the Central Valley Project.
2 | Central Valley Project Final Cost Allocation Study

1.1 Economic Analysis Parameters

The estimation of economic benefits presented in this appendix is based on a prospective analysis of 

the CVP over a 100-year period. The methodology used to estimate economic benefits had the 

following common elements, except where noted:

• Hydrology outputs from the CalSim 2 model presented in the Hydrological Modeling Appendix 

are used as inputs for the economics models, with the exception of flood control that was 

based on damages avoided as estimated by the USACE.

• All benefit values reflect 2013 dollars.

• All benefits are based on future conditions expected over the 100-year period of analysis. 

The economic benefits attributed to each project purpose are assumed to remain constant 

over the entire period of analysis. It is acknowledged that CVP project operations and 

related conditions are dynamic and will change over the 100-year period of analysis. 

However, due to modeling and data limitations, a single year, average condition scenario was 

used to reflect the prospective period of analysis.

• The benefit estimates used for Separable Costs-Remaining Benefits (SCRB) analysis reflect 

the present value of annual benefits over the 100-year period of analysis using a discount rate 

of 3.25 percent.

• Economic benefits are based on a water year type analysis for those purposes dependent on 

hydrology outputs, namely irrigation, M&I, water quality, and hydropower. (The water year 

type analysis does not apply to the flood control benefits because those estimates already 

reflect average annual values across a range of water year types.) Benefits were estimated by 

water year type (based on the 82-year hydrological record in the CalSim 2 model) and the 

results of the various water year scenarios were weighted based on the relative distribution in 

the hydrologic record, which was extended through 2013. Additional information on the 

water year type analysis is presented below.

1.2 Water Year Analysis

In the CVP, project benefits that are dependent on water supply availability include water supply 

(principally irrigation and municipal and industrial uses), water quality, and hydropower. Generally, 

the magnitude of economic benefits attributed to these purposes varies based on the quantity of 

water available in any given year and on the scarcity value of water across its many uses. As a result, 

each respective benefit analysis should account for annual fluctuations in water supply availability. In 

many studies, benefit estimates for water supply-dependent benefits have been calculated using longterm average annual deliveries, which does not account for potential differences in benefits across 

water year types. As a result, over a 100-year period of analysis, use of a single point estimate for 

water deliveries may not accurately predict the cumulative impact associated with the range and 

variability across individual water years. Using an approach which integrates the frequency of water 

year types into a single point estimate based on a series of runs for each water year type may 

generate results which may be more representative of long-term conditions. Accordingly, this 
Economic Benefits Analysis Appendix | 3

approach is able to account for the variability of different water supply conditions by estimating 

benefits separately for each water year type under consideration and appropriately weighting the 

results to derive average annual benefits.

Water year classifications provide a means to aggregate years with similar hydrologic conditions.

Water year classifications have been developed by the State Water Resources Control Board 

(SWRCB) for several hydrologic basins in California, including the Sacramento Valley, which 

represents the most applicable measure of hydrologic conditions affecting the CVP. The Sacramento 

Valley index defines wet, above normal, below normal, dry, and critical water year types.

Conceptually, the weighting of benefits should be consistent with the frequency of the forecasted 

water year types in the period of analysis, in this case, a 100-year prospective analysis. Forecasting 

water supply availability over the next 100 years is based on historic hydrologic conditions, which 

includes the hydrologic record used in the CalSim2 model plus additional water years through the 

base year used in the CAS (2013). The resulting water year distributions used in the economic 

benefit analyses is presented in Table 1-1.

Table 1-1: Water Year Classifications (Sacramento Valley Index)

Water Year Type # Years Percent

Wet 28 30.43%

Above Normal 13 14.13%

Below Normal 17 18.48%

Dry 21 22.83%

Critical 13 14.13%
4 | Central Valley Project Final Cost Allocation Study

This page intentionally left blank.
Economic Benefits Analysis Appendix | 5

Chapter 2. Irrigation Water Supply

2.1 Introduction & Overview

This chapter presents the economic benefits attributed to CVP irrigation water supplies. The 

information includes a detailed overview of the Statewide Agricultural Production (SWAP) model, 

which was used to estimate irrigation benefits, as well as the results of the benefits analysis based on 

a comparison of with-CVP and without-CVP conditions. This chapter is organized into three main

sections:

• Section 2.1: Introduction & Overview. This section describes the contents and structure 

of the appendix. It also presents a general overview of CVP irrigation water supplies, which 

are critical to agricultural production in the Central Valley of California.

• Section 2.2: Methodology – SWAP Model. The CAS uses the SWAP model to quantify 

the economic benefits of CVP irrigation water supplies. This section provides detailed 

information about the development, conceptual and analytical framework, geographic 

coverage, and key sources of input data for SWAP. It also documents the assumptions 

underlying the SWAP model simulations of the with-CVP and without-CVP scenarios.

• Section 2.3: Irrigation Benefits Results. This section presents the results of the SWAP 

model. Detailed information is presented covering acres in agricultural production, water 

use, and production value. It also presents estimates of irrigation benefits that are consistent 

with National Economic Development (NED) guidelines; these benefits are used as inputs 

to the SCRB cost allocation process.

To provide context to the importance of CVP irrigation water supplies, it is insightful to note the 

prominence of California’s agricultural industry. California has the largest agricultural sector in the 

U.S with approximately $47.1 billion in crop sales in 2015 (CDFA 2016). Agricultural production in 

the state is diverse, with over 400 different crops produced. Over a third of the country's vegetables 

and two-thirds of the country's fruits and nuts are grown in California. The magnitude and diversity 

of California agriculture supports a substantial export market. In fact, California exported 

approximately 26 percent of its agricultural production by volume, accounting for $20.69 billion in 

value, in 2015 (CDFA 2016). Although agricultural production extends across California, the Central 

Valley is at the center of the State’s agricultural industry. The top five counties for agricultural sales 

in 2015 were Tulare, Kern, Fresno, Monterey and Stanislaus counties. Many of these counties and 

other important agricultural regions throughout the State are directly served by CVP water supplies.

2.2 Methodology – SWAP Model

The SWAP model is a regional agricultural production and economic optimization model that 

simulates the decisions of farmers across 93 percent of agricultural land in California. It is the most 

current in a series of production models of California agriculture developed by researchers at the 
6 | Central Valley Project Final Cost Allocation Study

Universityof California at Davis under the direction of Professor Richard Howitt in collaboration 

with the California Department of Water Resources (DWR). The SWAP model has been subject to 

peer review and technical details can be found in “Calibrating Disaggregate Economic Models of Irrigated 

Production and Water Management” (Howitt et al. 2012). In addition, SWAP has been used in multiple 

studies undertaken by the Bureau of Reclamation. Additional details on the application of SWAP to 

federal planning projects can be found in “Statewide Agricultural Production (SWAP) Model Update and 

Application to Federal Feasibility Analysis” (Bureau of Reclamation 2012). Additional SWAP model 

documentation can be found in the reference list below. For this analysis, SWAP Model Version 6.1 

was used.

2.2.1 SWAP Model Development History

The SWAP model is an improvement and extension of the Central Valley Production Model 

(CVPM). The CVPM was developed in the early 1990s and was used to assess the impacts of the 

Central Valley Project Improvement Act (Reclamation and USFWS 1999). The SWAP model allows 

for greater flexibility in production technology and input substitution than CVPM does, and has

been extended to allow for a range of analyses, including interregional water transfers and climate 

change effects. Its first application was to estimate the economic scarcity costs of water for 

agriculture in the statewide hydro-economic optimization model for water management in 

California, CALVIN (Draper et al. 2003). More recently, the SWAP model has been used to estimate 

the economic losses caused by salinity in the Central Valley (Howitt et al. 2009a), economic losses to 

agriculture in the Sacramento-San Joaquin Delta (Lund et al. 2007), and economic effects of water 

shortage to Central Valley agriculture (Howitt et al. 2009b). The model was updated and augmented 

for use by Bureau of Reclamation in 2012 for use in several ongoing studies of water projects and

operations.

2.2.2 SWAP Conceptual Framework

SWAP is a representation of a complex water delivery and farm production system. It is 

characterized as a non-linear optimization model that reflects farm-level decision making. The 

theoretical basis of the model is driven primarily by crop demand functions for the primary crops 

grown in the Central Valley, available water supplies (both surface water and groundwater), and farm 

production costs and revenues. As with any model, SWAP requires that assumptions and 

simplifications be made due to the complexities involved in modeling such a large-scale system.

The SWAP model assumes that growers select the crops, water supplies, and other inputs to 

maximize profit subject to resource constraints, technical production relationships, and market 

conditions. Growers face competitive markets, thus no one grower can influence crop prices. The 

competitive market is simulated by maximizing the sum of consumer and producer surplus subject

to the following characteristics of production, market conditions, and available resources:

2.2.2.1Calibration Using Positive MathematicalProgramming (PMP)

The SWAP model self-calibrates using a three-step procedure based on PMP (Howitt 1995a) and the 

assumption that farmers behave as profit-maximizing agents within a competitive market. In a 

traditional optimization model, profit-maximizing farmers would simply allocate all land, up until 

resource constraints become binding, to the most valuable crop(s). In other words, a traditional

model would have a tendency for overspecialization in production activities relative to what is 
Economic Benefits Analysis Appendix | 7

observed empirically. PMP incorporates information on the marginal production conditions that 

farmers face, allowing the model to replicate a base year of observed input use and output. Farmand field-specific conditions that are unobserved in aggregated data may include inter-temporal 

effects of crop rotation, proximity to processing facilities, management skills, farm-level effects such 

as risk and input smoothing, and heterogeneity in soil and otherphysical capital. In the SWAP 

model, PMP is used to translate these unobservable marginal conditions, in addition to observed 

average conditions, into an exponential “PMP” cost function. This cost function allows the model to 

calibrate to a base year of observed input use and output.

The SWAP model assumes additional land brought into production faces an increasing marginal cost 

of production. The most fertile or lowest cost land is cultivated first; additional land brought into 

production is of lower “quality” because of poorer soil quality, drainage or other water quality issues, 

or other factors that cause it to be more costly to farm. This is captured through an exponential land 

cost function (PMP cost function) for each crop and region. The exponential function is 

advantageous because it is always positive and strictly increasing, consistent with the hypothesis of 

increasing land costs. The PMP cost function is both region- and crop-specific, reflecting differences 

in production across crops and heterogeneity across regions. Functions are calibrated using 

information from acreage response elasticities and shadow values of calibration and resource 

constraints. The information is incorporated in such a way that the average cost conditions (the 

observed cost data) are unaffected.

2.2.2.2Constant Elasticity of Substitution Production Function

Crop production in the SWAP model is represented by a constant elasticity of substitution (CES) 

production function for each region and crop with positive acres. In general, a production function 

captures the relationship between inputs and output. For example, land, labor, water, and other 

inputs are combined to produce a crop. CES production functions in the SWAP model are specific 

to each region; thus, regional input use is combined to determine regional production for each crop.

The calibration routine in SWAP guarantees that both input use and output match a base year of 

observed data.

The SWAP model considers four aggregate inputs to produce each crop in each region: land, labor, 

water, and other supplies. All units are converted into monetary terms, e.g., dollars of labor per acre 

instead of worker hours. Land is simply the number of acres of a crop in any region. Land costs 

represent basic land investment, cash overhead, and (when applicable) land rent. Labor costs 

represent both machinery labor and manual labor. “Other supplies” is a broad category that captures 

a range of inputs including fertilizer, pesticides, chemicals, capital recovery, and interest on operating 

capital. Water costs and use per acre vary by crop and region.

The generalized CES production function allows for limited substitution among inputs (Beattie and 

Taylor 1985). This is consistent with observed farmer production practices (farmers are able to 

substitute among inputs in order to achieve the same level of production). For example, farmers may 

substitute labor for chemicals by reducing herbicide application and increasing manual weed control.

Or, farmers can substitute labor for water by managing an existing irrigation system more intensively 

in order to reduce water use. The CES function used in Version 6.1 of the SWAP model is nonnested; thus, the elasticity of substitution is the same between all inputs.
8 | Central Valley Project Final Cost Allocation Study

2.2.2.3Crop Demand Functions

The SWAP model is specified with downward-sloping, California-specific crop demand functions.

The demand curve represents consumers’ willingness-to-pay for a given level of crop production.

With all else constant, as production of a crop increases, the price of that crop is expected to fall.

The extent of the price decrease depends on the elasticity of demand or, equivalently, the price

flexibility, which is the percentage change in crop price due to a percent change in production.

Demand functions are specific to a crop but not to a region.

Therefore, large changes in production in one set of regions can, through the demand-induced price 

changes, lead to changes in production in other regions.

The SWAP model is specified with linear demand functions. The nature of the demand function for 

specific commodities can change over time due to tastes and preferences, population growth, 

changes in income, and other factors. TheSWAP model incorporates linear shifts in the demand 

functions over time due to growth in population and changes in real income per capita. Changes in 

the demand elasticity itself, resulting from changing tastes and preferences, are not considered in the 

model, though they can be evaluated by changing demand function parameters in the model’s input

data.

2.2.2.4Water Supply and Groundwater Pumping

Total available water for agricultural production is specified on a regional basis in the SWAP model.

Each region has six sources of supply, although not all sources are available in every region:

• CVP water service contracts (including Friant-Kern Class 1 water service contracts)

• CVP Sacramento River settlement contracts and San Joaquin River exchange contracts

• Friant Kern Class 2 water service contracts

• SWP entitlement contracts

• Other local surface water

• Groundwater

Data sources and associated calculations are described in Statewide Agricultural Production (SWAP) 

Model Update and Application to Federal Feasibility Analysis (Reclamation 2012). State and Federal project 

deliveries are estimated from delivery records of DWR and Reclamation. Local surface water 

supplies are based on DWR estimates and reports of individual water suppliers, and, where 

necessary, are drawn from earlier studies.

Costs for surface water supplies are compiled from information published by individual water supply 

agencies. There is no central data source for water prices in California. Agencies that prepared CVP 

water conservation plans or agricultural water management plans in most cases included water prices

and related fees charged to growers. Other agencies publish and/or announce rates on an annual 

basis. Water prices used in SWAP are intended to be representative for each region, but vary in their 

level of detail.
Economic Benefits Analysis Appendix | 9

Groundwater availability is specified by region-specific maximum pumping estimates. These are 

determined by consulting the individual districts’ records and information compiled by DWR. DWR 

analysts provided estimates of the actual pumping in the base year and the existing pumping capacity 

by region. The base assumptions in the SWAP model are used for modeling with-CVP conditions; 

additional constraints are applied to without-CVP conditions as described below.

The model determines the optimal level of groundwater pumping for each region, up to the capacity 

limit specified. SWAP or CVPM has also been used interactively with a groundwater model to 

evaluate short-term and long-term effects on aquifer conditions and pumping lifts.

Pumping costs vary by region depending on depth to groundwater and power rates. The SWAP 

model includes a routine to calculate the total costs of groundwater. The total cost of groundwater is 

the sum of fixed, operation and maintenance (O&M), and energy costs.

2.2.2.5 Agricultural Land Use

The SWAP calibrates to observed cropping patterns in the Central Valley. Agricultural land use data 

in SWAP correspond to the year 2010 and were prepared by DWR analysts. DWR is now 

developing more detailed annual time series data on agricultural land use, but the current version of 

the SWAP model calibrates to 2010 as a relatively normal base year.

2.2.2.6Farm Production Costs

The production of crops involves both fixed and variable costs. Fixed costs represent ownership 

costs and land and capital equipment, while variable costs include expenditures on farming inputs 

(e.g., seed, fertilizer, etc.) and labor. Farm production costs data in SWAP are based on crop budgets 

developed by the University of California Cooperative Extension (UCCE).

2.2.2.7Farm-Level Revenues

Agricultural revenues realized by farmers are based on crop yields and prices. Representative prices 

and yields for crops in the SWAP model are based on county agricultural commissioner data.

2.2.2.8Summary of SWAP Model Inputs and Supporting Data

Table 2-1 summarizes input data and sources used in the SWAP model. All prices and costs in 

SWAP are in constant 2010 dollars for consistency with the land use data. Post-processing 

adjustments were made to convert all values to 2013 dollars for use in the CAS.

Table 2-1. SWAP Model Input DataSummary

Input Source Notes

Land Use DWR Base year 2010

Crop Prices

County Agricultural 

Commissioners

By proxy crop using 2010-2012 average prices, 

indexed to 2010 price level
10 | Central Valley Project Final Cost Allocation Study

Input Source Notes

Crop Yields UCCE crop budgets

By proxy crop for various years (most recent 

available)

Interest Rates UCCE crop budgets Crop budget interest costs adjusted to year 2010

Land Costs UCCE crop budgets

By proxy crop for various years (most recent 

available), in 2010 dollars

Other Supply 

Costs UCCE crop budgets

By proxy crop for various years (most recent 

available), in 2010 dollars

Labor Costs UCCE crop budgets

By proxy crop for various years (most recent 

available), in 2010 dollars

Surface Water 

Costs

Reclamation, DWR, individual 

districts By SWAP model region; in 2010 dollars

Groundwater 

Costs PG&E, individual districts

Total cost per acre-foot includes fixed, O&M, and 

energy cost, in 2010 dollars

Irrigation Water DWR

Average crop irrigation water requirements, in 

acre-feet per acre.

Available Water

CVPM, DWR, Reclamation, 

individual districts By SWAP model region and water supply source

Elasticities Russo et al. 2008 California estimates

2.2.2.9 Other SWAP Model Assumptions

The following represent key modeling assumptions integrated into the SWAP model: 

• Groundwater pumping costs are based on a base electricity rate of $0.22/kwh, pumping

efficiency factor of 70 percent, and O&M cost of $0.025/kwh. The base electricity rate was

escalated to 2024 using a scalar of 1.266 (reflecting a 26.6 percent increase real electricity

rates) The 2024 timeframe was selected in order to be consistent with the power benefits

analysis, which is based on forecasted wholesale electricity costs in 2024. Energy costs are

based on a blend of agricultural power rates provided by Pacific Gas and Electric Company

(PG&E) and forecasts by the California Energy Commission (CEC 2014).

• Elasticity of substitution (inputs) is 0.17.

• Elasticity of supply (acreage response elasticity) reflect long run conditions and varies by

crop.
Economic Benefits Analysis Appendix | 11

• Crop prices are endogenous in response to population and real income growth. Population

growth rate is estimated at 2.5 percent annually. Real income growth is estimated at one

percent annually.

• Consumer surplus benefits are excluded from the calculation of benefits. Consumer surplus

benefits accrue to society (consumers of agricultural products), rather than agricultural

producers. Because the objective of cost allocation is to allocate costs across project

purposes, including water supply, which subsequently is passed on to agricultural producers,

it was determined that it would not be appropriate to include consumer surplus benefits.

2.2.3 Geographic Coverage (SWAP Regions)

The SWAP model has 27 base regions in the Central Valley. The model is also able to include 

agricultural areas of the Central Coast, the Colorado River region that includes Coachella, Palo 

Verde and the Imperial Valley, and San Diego, Santa Ana, and Ventura and the South Coast; 

however, those regions were not analyzed for the CAS. Figure 2-1 shows the numbered California 

agricultural areas covered in SWAP. Table 2-2 details the major water users in each of the regions. 

Figure 2-1. SWAP Model Coverage of Agriculture in California
12 | Central Valley Project Final Cost Allocation Study

Table 2-2. SWAP Model Regions and Water Users

Region User

1 CVP Users: Anderson Cottonwood ID, Clear Creek CSD, Bella Vista WD, and misc. 

Sacramento River water users

2 CVP Users: Corning Canal, Kirkwood WD, Tehama, and misc. Sacramento River water users

3a CVP Users: Glenn Colusa ID, Provident ID, Princeton-Codora ID, Maxwell ID, and Colusa 

Basin Drain MWC

3b Tehama Colusa Canal Service Area. CVP Users: Orland-Artois WD, most of Colusa County, 

Davis WD, Dunnigan WD, Glide WD, Kanawha WD, La Grande WD, and Westside WD

4 CVP Users: Princeton-Codora-Glenn ID, Colusa IC, Meridian Farm WC, Pelger Mutual WC, 

RD 1004, RD 108, Roberts Ditch IC, Sartain MWC, Sutter MWC, Swinford Tract IC, Tisdale 

Irrigation and Drainage Co., and misc. Sacramento River water users

5 Most Feather River Region riparian and appropriative users

6 Yolo and Solano Counties. CVP Users: Conaway Ranch and misc. Sacramento River water 

users

7 Sacramento County north of American River. CVP Users: Natomas Central MWC, misc. 

Sacramento River water users, MWC, and Placer County WA

8 Sacramento County south of American River and northern San Joaquin County

9 Direct diverters within the Delta region. CVP Users: Banta Carbona ID, West Side WD, and 

Plainview

10 Delta Mendota service area. CVP Users: Panoche WD, Pacheco WD, Del Puerto WD, Hospital 

WD, Sunflower WD, West Stanislaus WD, Mustang WD, Orestimba WD, Patterson WD, 

Foothill WD, San Luis WD, Broadview, Eagle Field WD, Mercy Springs WD, San Joaquin River 

Exchange Contractors

11 Stanislaus River water rights: Modesto ID, Oakdale ID, and South San Joaquin ID

12 Turlock ID

13 Merced ID CVP Users: Madera ID, Chowchilla WD, and Gravely Ford

14a CVP Users: Westlands WD

14b Southwest corner of Kings County

15a Tulare Lake Bed. CVP Users: Fresno Slough WD, James ID, Tranquillity ID, Traction Ranch, 

Laguna WD, and RD 1606
Economic Benefits Analysis Appendix | 13

Region User

15b Dudley Ridge WD and Devils Den (Castaic Lake)

16 Eastern Fresno County. CVP Users: Friant-Kern Canal, Fresno ID, Garfield WD, and 

International WD

17 CVP Users: Friant-Kern Canal, Hills Valley ID, Tri-Valley WD, and Orange Cove

18 CVP Users: Friant-Kern Canal, County of Fresno, Lower Tule River ID, Pixley ID, portion of 

Rag Gulch WD, Ducor, County of Tulare, most of Delano-Earlimart ID, Exeter ID,

Ivanhoe ID, Lewis Creek WD, Lindmore ID, Lindsay-Strathmore ID, Porterville ID, Sausalito 

ID, Stone Corral ID, Tea Pot Dome WD, Terra Bella ID, and Tulare ID

19a SWP Service Area, including Belridge WSD, Berrenda Mesa WD

19b SWP Service Area, including Semitropic WSD

20 CVP Users: Friant-Kern Canal. Shafter-Wasco, and South San Joaquin ID

21a SWP Users and CVP Users served by Cross Valley Canal and Friant-Kern Canal

21b Arvin Edison WD and portions of Wheeler Ridge–Maricopa WSA

21c SWP service area: Wheeler Ridge–Maricopa WSD

2.2.4 SWAP Crop Groups

The SWAP model covers 20 different crop groups grown in the Central Valley. For each crop 

group, a proxy crop is identified, which is intended to be representative of the group in terms water 

use, costs, and revenues. Crop group definitions and the corresponding proxy crop are shown in 

Table 2-3. 

Table 2-3. SWAP Model Crop Groups

SWAP Definition Proxy Crop Other Crops

Almonds and Pistachios Almonds Pistachios

Alfalfa Alfalfa hay –

Corn Grain corn Corn silage

Cotton Pima cotton Upland cotton

Cucurbits Summer squash Melons, cucumbers, pumpkins
14 | Central Valley Project Final Cost Allocation Study

SWAP Definition Proxy Crop Other Crops

Dry Beans Dry beans Lima beans

Fresh Tomatoes Fresh tomatoes –

Grain Wheat Oats, sorghum, barley

Onions and Garlic Dry onions Fresh onions, garlic

Other Deciduous Walnuts Peaches, plums, apples

Other Field Sudan grass hay Other silage

Other Truck Broccoli Carrots, peppers, lettuce, other vegetables

Pasture Irrigated pasture –

Potatoes White potatoes –

Processing Tomatoes Processing tomatoes –

Rice Rice –

Safflower Safflower –

Sugar Beet Sugar beets –

Subtropical Oranges Lemons, misc. citrus, olives

Vine Wine grapes Table grapes, raisins

2.2.5 NED Post-Processing Adjustments

The benefits analyses used in the CAS are consistent with NED benefits outlined in the Principles & 

Guidelines (P&Gs). Although the optimization of the SWAP model are based on the parameters 

described above, the following NED post-processing adjustments have been applied for the 

purposes of the CAS: 

• The interest rate used in the CAS is 3.25 percent. The short-run variable interest rate and

fixed interest rate were both adjusted to reflect the CAS interest rate.

• Normalized prices were applied to basic crops based on USDA data. Normalized prices were

calculated based on a five-year average between 2009 and 2013. The basic crops in the model

are corn, cotton, dry beans, grain, rice, and sugar beets.

• Five-year average prices were applied to non-basic crops using statewide (California) values

for the period 2009 to 2013. The non-basic crops in the model are alfalfa,

almonds/pistachios, cucurbits, fresh tomatoes, onion/garlic, other deciduous crops, other
Economic Benefits Analysis Appendix | 15

field crops, other truck crops, potatoes, processing tomatoes, safflower, subtropical crops, 

and vines. 

• Estimated irrigation benefits were adjusted to net out the cost of CVP water supplies.

Paragraph 8 of Reclamation Manual D&S PEC 01-02, Project Cost Allocations, states that the

benefits used in the cost allocation should be the same as those used for project justification.

For project justification, project water costs are excluded from benefit estimates because

they are accounted for in the cost of the project. In the context SWAP, because all water

costs are included in the estimate of net revenues for the purposes of optimization, CVP

water costs were added back to the estimate of irrigation water supply benefits.

• Irrigation benefits include avoided land fallowing costs attributed to CVP water supplies.

Fallowing costs are calculated at $40.12 per acre

• All cost and revenues were adjusted to 2013 dollars using the GDP implicit Price Deflator

(IPD)

2.2.6 Model Limitations and Applicability

The SWAP model is an optimization model that makes the best (most profitable) adjustments to 

water supply and other changes to maximize net revenues. Constraints can be imposed to simulate 

restrictions on how much adjustment is possible or how fast the adjustment can realistically occur.

Nevertheless, an optimization model can tend to over-adjust and minimize costs associated with 

detrimental changes or, similarly, maximize benefits associated with positive changes. 

In addition, SWAP does not explicitly account for the dynamic nature of agricultural production; it 

provides a point in time comparison between two conditions. This is consistent with the way most 

economic and environmental impact analysis is conducted, but it can obscure sometimes important 

adjustment costs. SWAP also does not explicitly incorporate risk or risk preferences (e.g., risk 

aversion) into its objective function. Risk and variability are handled in two ways. First, the 

calibration procedure for SWAP is designed to reproduce observed crop mix, so to the extent that 

crop mix incorporates farmers’ risk spreading and risk aversion, the starting, calibrated SWAP base 

condition will also. Second, variability in water delivery, prices, yields, or other parameters can be 

evaluated by running the model over a sequence of conditions or over a set of conditions that 

characterize a distribution, such as a set of water year types.

Ground water is an alternative source to augment local surface, SWP, and CVP water delivery in all 

SWAP regions. The cost and availability of groundwater therefore has an important effect on how 

SWAP responds to changes in delivery. However, SWAP is not a groundwater model and does not 

include any direct way to adjust pumping lifts and unit pumping cost in response to long-run 

changes in pumping quantities; such modifications must come from an accompanying groundwater 

analysis.

2.2.7 Other Methodological Considerations

The methodology described above focuses on the SWAP model; however, there are other important 

methodological considerations in the estimation of CVP water supply benefits, which are described 

below. 
16 | Central Valley Project Final Cost Allocation Study

2.2.7.1 With- and Without-CVP Conditions

The evaluation of CVP benefits is based on the change (or difference) between with-CVP and 

without-CVP conditions. From a hydrologic perspective, available water supplies under with-CVP 

conditions are modeled using CalSim2; for more information on the CalSim2 modeling prepared for 

the CAS, refer to the Hydrological Modeling Appendix. It is not possible to model without-CVP 

conditions using CalSim2. Therefore, for the without-CVP scenario, available CVP water supplies 

were manually adjusted as follows: 

• Set CVP water service contracts (including Friant-Kern Class 1 water service contracts) to

zero;

• Set Friant Kern Class 2 water service contracts to zero;

• Set CVP Section 215 water to zero;

• Set CVP Sacramento River settlement contractor deliveries as follows:

o Wet: 88.78%

o Above Normal: 96.39%

o Below Normal: 87.00%

o Dry: 83.84%

o Critical: 80.14%

• Set San Joaquin River Exchange Contractors deliveries as follows:

o Wet: 94.98%

o Above Normal: 87.50%

o Below Normal: 82.14%

o Dry: 72.01%

o Critical: 61.87%

For both the CVP Sacramento River settlement contractors and San Joaquin River Exchange 

Contractors, it is assumed that they would continue to receive irrigation water pursuant to their 

water rights in the without-CVP scenario. The proportion of water that these groups receive without 

the CVP is based on CalSim2 modeling analysis. All other surface water supplies, namely SWP 

supplies and local supplies, are held constant in the with-CVP and without-CVP scenarios.

Additional considerations related to the without-CVP scenario were required. Specifically, removing 

all CVP water service contract delivery and a portion of settlement and exchange contract delivery 

with no assessment of the consequences to historical land development, groundwater depletion, or 

groundwater cost, results in an analysis that likely understates the benefits of CVP irrigation water.

As a result, additional modifications were made relative to groundwater pumping constraints in the 

without-CVP scenario. It is difficult to estimate available groundwater pumping supplies without the 

CVP, which represents a significant source of groundwater recharge. In addition, it is not plausible 

that groundwater supplies without the CVP would be comparable to with-CVP conditions. In the 
Economic Benefits Analysis Appendix | 17

absence of groundwater modeling, it was necessary to develop groundwater assumptions for the 

without-CVP scenario. For this analysis, groundwater pumping in the without-CVP scenario was 

generally limited to endogenous with-CVP groundwater pumping levels. In other words, 

groundwater pumping without the CVP was not allowed to exceed estimated groundwater pumping 

levels with the CVP in place. It was determined that limiting groundwater pumping in the withoutCVP scenario in this manner provides a more reasonable estimate of CVP irrigation water supply 

benefits. 

2.2.7.2 Prospective Period of Analysis – Assumptions

Irrigation benefits are based future conditions expected over the 100-year period of analysis. For this 

analysis, the prospective period of analysis is based on 2030 conditions unless noted otherwise. This 

is generally consistent with the level of development modeled by CalSim. Future crop demands are 

based on shifts over time due to growth in population and real per-capita income. It is 

acknowledged that agricultural conditions and markets are dynamic and will change over the 100-

year period of analysis; however, due to modeling and data limitations, a single year scenario was 

used to reflect the prospective period of analysis. 

2.3 Irrigation Benefits Results

The SWAP model estimates irrigation benefits based on changes in cropping patterns and farm-level 

production costs and revenues in response to available water supplies under the with-CVP and 

without-CVP scenarios. This section presents forecasted physical changes in the agricultural 

landscape attributed to the CVP, namely cropping patterns (irrigated acres) and agricultural water 

use. Based on these physical changes, irrigation benefits are calculated based on changes in net farm 

income (profit or producer surplus), surface water and groundwater costs, and land fallowing costs. 

All monetary values are reported in 2013 dollars.

2.3.1 Acreage in Agricultural Production

Available water supplies directly affect the extent of irrigated acreage in agricultural production.

Tables 2-3A and 2-3B show irrigated acreage by crop under the with-CVP and without-CVP 

scenarios, respectively. With the CVP, there are approximately 6.9 million acres in irrigated 

agriculture across SWAP regions. Without the CVP, irrigated acreage falls to about 6.3 million acres.

In both scenarios, the leading crop type in terms of acreage is almond/pistachios, with nearly 1.1 

million acres in production with the CVP. 

Table 2-3A. Irrigated Acres, by Crop and Water Year Type, With-CVP Conditions (acres)

Crops Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

Alfalfa 670,967 671,095 670,978 669,550 663,635 669,628

Almond/Pistachio 1,084,988 1,085,071 1,084,956 1,082,687 1,070,906 1,082,479
18 | Central Valley Project Final Cost Allocation Study

Crops Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

Corn 730,027 730,098 730,086 729,161 721,234 728,608

Cotton 284,726 284,734 284,730 284,571 282,673 284,402

Cucurbits 108,925 108,926 108,925 108,921 108,915 108,923

Dry Beans 75,698 75,710 75,709 75,657 75,409 75,652

Fresh Tomato 36,861 36,861 36,861 36,859 36,853 36,860

Grain 368,501 366,437 367,263 365,304 357,809 365,740

Onion, Garlic 64,429 64,431 64,431 64,417 64,383 64,421

Other Deciduous 639,245 639,256 639,251 639,101 638,727 639,142

Other Field 564,952 564,990 564,991 564,772 561,883 564,490

Other Truck 206,380 206,381 206,381 206,357 206,256 206,357

Pasture, Irrigated 267,983 268,188 267,851 266,259 265,179 267,198

Potato 16,872 16,872 16,872 16,872 16,871 16,872

Process Tomato 318,409 318,435 318,437 318,346 317,632 318,294

Rice 567,957 569,430 569,177 563,115 556,753 565,702

Safflower 37,356 37,355 37,364 37,361 37,328 37,355

Sugar Beets 592 592 592 592 591 592

Subtropical 275,750 275,753 275,752 275,708 275,534 275,710

Vineyard 612,462 612,465 612,471 612,425 612,237 612,424

Total 6,933,078 6,933,080 6,933,080 6,918,033 6,870,808 6,920,845

Table 2-3B. Irrigated Acres, by Crop and Water Year Type, Without-CVP Conditions (acres)

Crops Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

Alfalfa 621,155 621,318 621,649 620,572 638,324 623,562
Economic Benefits Analysis Appendix | 19

Crops Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

Almond/Pistachio 953,656 993,812 1,028,560 1,052,042 1,059,753 1,010,625

Corn 555,402 595,329 605,984 638,509 687,447 608,023

Cotton 236,093 236,116 236,535 238,585 279,192 242,837

Cucurbits 106,556 108,030 108,121 108,440 108,891 107,814

Dry Beans 67,418 66,987 65,984 62,512 66,944 65,905

Fresh Tomato 36,682 36,773 36,783 36,807 36,835 36,764

Grain 291,693 292,953 296,244 294,951 360,526 303,182

Onion, Garlic 56,358 60,008 60,174 63,239 64,149 60,251

Other Deciduous 626,180 635,240 635,719 636,913 637,661 633,296

Other Field 517,453 519,372 518,784 512,687 525,686 518,045

Other Truck 203,107 204,900 205,086 205,855 206,354 204,812

Pasture, Irrigated 210,857 208,819 211,678 216,537 231,127 214,882

Potato 15,418 16,172 16,247 16,640 16,881 16,164

Process Tomato 235,279 235,382 283,861 308,243 315,591 272,277

Rice 509,973 493,339 485,432 478,014 456,660 488,258

Safflower 37,009 37,165 37,246 37,150 37,331 37,153

Sugar Beets 588 590 593 596 594 592

Subtropical 264,682 270,207 270,609 273,443 274,757 269,982

Vineyard 575,224 591,523 600,048 608,176 611,150 594,714

Total 6,120,784 6,224,034 6,325,339 6,409,911 6,615,852 6,309,136

Table 2-3C shows the change in irrigated acreage between the with-CVP and without-CVP 

scenarios. On average, approximately 612,000 additional acres are irrigated with the CVP in 

place. In the without-CVP scenario, irrigated agriculture is supported by local and state surface 

water supplies and groundwater in lieu of CVP water. 
20 | Central Valley Project Final Cost Allocation Study

Table 2-3C. Irrigated Acres, by Water Year Type, Summary (acres)

Scenario Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

With-CVP 6,933,078 6,933,080 6,933,080 6,918,033 6,870,808 6,920,845

Without-CVP 6,120,784 6,224,034 6,325,339 6,409,911 6,615,852 6,309,136

Difference 812,295 709,046 607,741 508,122 254,956 611,710

2.3.2 Agricultural Production Value

The gross value of agricultural production is based on the quantity and price of crops produced. 

Tables 2-4A and 2-4B show agricultural production value under the with-CVP and without-CVP 

scenarios, respectively. With the CVP in place, the value of agricultural production across SWAP 

regions is estimated at $25.7 billion, which is greater than without the CVP ($24.3 billion). The 

prominent crops supported by the CVP, as measured by annual production value, are 

almond/pistachio ($5.3 billion), other deciduous crops ($4.5 billion), and vine crops ($4.4 billion). 

Table 2-4A. Agricultural Production Values, by Crop and Water Year Type, With-CVP Conditions 

($)

Crops Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

Alfalfa $1,021,207,573 $1,021,367,591 $1,021,222,405 $1,019,250,151 $1,011,925,345 $1,019,474,466

Almond, 

Pistachio

$5,356,942,801 $5,357,322,198 $5,356,798,926 $5,344,603,228 $5,286,858,808 $5,344,249,829

Corn $891,561,012 $891,646,127 $891,629,733 $890,520,610 $881,205,149 $889,884,931

Cotton $385,220,436 $385,231,198 $385,226,121 $385,011,624 $382,449,765 $384,783,840

Cucurbits $1,132,976,552 $1,132,986,499 $1,132,983,751 $1,132,935,612 $1,132,872,950 $1,132,955,302

Dry Beans $91,337,023 $91,350,598 $91,348,306 $91,287,407 $91,013,194 $91,283,942

Fresh 

Tomato

$427,722,049 $427,723,214 $427,721,278 $427,694,037 $427,633,326 $427,703,139

Grain $295,367,758 $293,981,746 $294,534,368 $292,778,857 $285,396,971 $293,017,986

Onion, 

Garlic

$267,749,135 $267,756,984 $267,756,519 $267,704,072 $267,576,600 $267,716,941

Other 

Deciduous

$4,510,098,350 $4,510,166,881 $4,510,134,637 $4,509,045,015 $4,506,370,450 $4,509,347,511
Economic Benefits Analysis Appendix | 21

Crops Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

Other Field $433,265,925 $433,295,505 $433,296,404 $433,128,696 $430,889,504 $432,908,620

Other 

Truck

$1,041,957,649 $1,041,964,990 $1,041,964,150 $1,041,841,325 $1,041,330,680 $1,041,844,740

Pasture, 

Irrigated

$127,955,605 $128,054,886 $127,893,245 $127,130,429 $126,615,246 $127,580,329

Potato $106,641,603 $106,641,677 $106,641,633 $106,640,545 $106,635,786 $106,640,556

Process 

Tomato

$1,066,582,097 $1,066,664,583 $1,066,671,599 $1,066,372,771 $1,064,088,400 $1,066,210,144

Rice $1,029,261,016 $1,031,922,559 $1,031,468,297 $1,020,572,197 $1,009,104,697 $1,025,213,252

Safflower $23,670,902 $23,670,406 $23,676,161 $23,674,530 $23,653,566 $23,670,183

Sugar

Beets

$1,381,912 $1,381,929 $1,381,904 $1,381,691 $1,381,106 $1,381,749

Subtropical $3,153,651,771 $3,153,693,218 $3,153,683,774 $3,153,172,124 $3,151,167,061 $3,153,202,949

Vineyard $4,373,193,167 $4,373,217,421 $4,373,250,281 $4,372,905,720 $4,371,630,075 $4,372,920,660

Total $25,737,744,338 $25,740,040,208 $25,739,283,492 $25,707,650,641 $25,599,798,679 $25,711,991,067

Table 2-4B. Agricultural Production Values, by Crop and Water Year Type, Without-CVP Conditions 

($)

Crops Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

Alfalfa $944,383,041 $944,800,512 $945,357,236 $943,659,881 $972,361,236 $948,410,282

Almond, 

Pistachio $4,646,717,886 $4,881,208,873 $5,054,514,471 $5,188,423,585 $5,233,011,606 $4,961,726,985

Corn $673,511,361 $723,544,218 $736,841,988 $777,727,609 $839,131,822 $739,479,244

Cotton $319,719,928 $319,748,772 $320,319,056 $323,080,288 $377,747,588 $328,801,201

Cucurbits $1,108,088,973 $1,123,568,586 $1,124,526,981 $1,127,880,091 $1,132,613,150 $1,121,297,565

Dry Beans $80,745,821 $80,210,907 $78,967,307 $74,720,900 $80,484,717 $78,929,185

Fresh 

Tomato $425,055,900 $426,435,761 $426,575,255 $426,952,147 $427,426,885 $426,299,584

Grain $226,906,325 $227,925,870 $230,236,392 $228,991,137 $286,724,261 $236,594,020
22 | Central Valley Project Final Cost Allocation Study

Crops Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

Onion, 

Garlic $234,381,718 $250,422,592 $251,159,656 $262,803,629 $266,604,657 $250,790,680

Other 

Deciduous $4,413,398,164 $4,480,796,859 $4,484,292,756 $4,493,158,836 $4,498,716,637 $4,466,287,782

Other Field $396,958,408 $398,404,105 $397,944,735 $393,283,597 $403,256,783 $397,395,959

Other 

Truck $1,025,721,110 $1,034,613,227 $1,035,541,052 $1,039,391,616 $1,041,832,999 $1,034,189,878

Pasture, 

Irrigated $100,668,340 $99,686,398 $101,053,728 $103,353,914 $110,241,489 $102,566,614

Potato $97,065,040 $102,030,893 $102,523,678 $105,112,800 $106,703,160 $101,974,641

Process 

Tomato $777,269,520 $777,655,400 $945,987,447 $1,031,639,774 $1,057,329,042 $906,148,257

Rice $924,404,718 $894,341,629 $880,059,465 $866,582,412 $827,976,170 $885,135,615

Safflower $23,458,799 $23,554,912 $23,606,083 $23,545,388 $23,659,285 $23,547,695

Sugar

Beets $1,372,598 $1,377,885 $1,383,674 $1,391,748 $1,386,046 $1,381,664

Subtropical $3,027,669,130 $3,090,417,720 $3,095,011,878 $3,127,337,331 $3,142,310,755 $3,087,933,558

Vineyard $4,093,668,975 $4,216,387,610 $4,280,151,413 $4,341,141,953 $4,363,519,825 $4,240,099,079

Total $23,541,165,754 $24,097,132,729 $24,516,054,251 $24,880,178,636 $25,193,038,114 $24,338,989,487

Table 2-4C shows the change in gross agricultural production value between the with-CVP and 

without-CVP scenarios. The CVP supports an additional $1.4 billion in production value 

compared to without-CVP conditions on average. This is driven by additional acreage in 

agricultural production, in conjunction with shifts to higher-value crops.

Table 2-4C. Agricultural Production Values, by Water Year Type, Summary ($) 

Scenario Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

With-CVP $25,737,744,338 $25,740,040,208 $25,739,283,492 $25,707,650,641 $25,599,798,679 $25,711,991,067

Without-CVP $23,541,165,754 $24,097,132,729 $24,516,054,251 $24,880,178,636 $25,193,038,114 $24,338,989,487

Difference1 $2,196,578,584 $1,642,907,479 $1,223,229,241 $827,472,005 $406,760,564 $1,373,001,580

1. Difference reflects difference between with-CVP and without-CVP conditions
Economic Benefits Analysis Appendix | 23

2.3.3 Agricultural Net Revenues

From a NED perspective, net agricultural revenues (or profits) associated with agricultural 

production are reflective of economic benefits. In this context, net revenues are calculated as gross 

revenues less fixed and variable production costs (other than water costs). Table 2-5 show net 

revenues in the with-CVP and without-CVP scenarios. On average, net agricultural revenues across 

SWAP regions is estimated at approximately $6.8 billion annually with the CVP and $6.3 billion 

without the CVP. With the CVP, farmers are expected to realize about $496.6 million in additional 

profits compared to without-CVP conditions. 

Table 2-5. Agricultural Net Revenues, by Water Year Type, Summary ($)

Scenario Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

With-CVP $6,804,051,297 $6,804,578,903 $6,804,032,747 $6,790,796,345 $6,755,523,737 $6,794,239,370

WithoutCVP

$5,986,641,460 $6,217,583,639 $6,369,793,159 $6,514,279,497 $6,602,832,917 $6,297,607,641

Difference 

1

$817,409,837 $586,995,264 $434,239,589 $276,516,848 $152,690,820 $496,631,729

1. Difference reflects difference between with-CVP and without-CVP conditions

2.3.4 Agricultural Water Use

Changes in agricultural water use (and related costs) also represent a major factor in the estimation 

of irrigation benefits. Tables 2-6A and 2-6B show agricultural water use (both surface water and 

groundwater) under the with-CVP and without-CVP scenarios, respectively. With the CVP, 

agricultural water use totals about 21.4 million AF per year, comprised mainly by surface water (13.7 

million AF), supplemented by about 7.7 million AF of groundwater, on average. Without the CVP, 

there is a decline in agricultural water use to 19.2 million AF, primarily due to land fallowing and 

limits on groundwater availability.

Table 2-6A. Agricultural Water Use, by Source and Water Year Type, With-CVP Conditions (AF)

Water Type Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

Surface Water 14,629,640 14,102,599 13,754,862 13,163,357 11,999,000 13,687,048

Groundwater 6,816,781 7,351,101 7,691,034 8,205,010 9,223,235 7,710,807

Total 21,446,421 21,453,700 21,445,896 21,368,367 21,222,235 21,397,855
24 | Central Valley Project Final Cost Allocation Study

Table 2-6B. Agricultural Water Use, by Source and Water Year Type, Without-CVP Conditions 

(AF)

Water Type Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

Surface Water 11,827,810 11,575,908 11,468,196 11,186,185 10,711,728 11,421,574

Groundwater 6,878,441 7,424,578 7,771,164 8,278,480 9,246,889 7,774,876

Total 18,706,251 19,000,486 19,239,360 19,464,665 19,958,618 19,196,450

Table 2-6C shows the difference in agricultural water use between the with-CVP and withoutCVP scenarios. With the CVP, surface water use increases by about 2.3 million AF and 

groundwater use decreases slightly by about 64,000 AF compared to without-CVP conditions. 

As expected, the reliance of groundwater in both scenarios becomes more prominent as 

hydrological conditions become drier, which reduces the quantity of surface water available. 

Table 2-6C. Agricultural Water Use, by Source and Water Year Type, Summary (AF)

Scenario Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

Surface Water

With-CVP 14,629,640 14,102,599 13,754,862 13,163,357 11,999,000 13,687,048

Without-CVP 11,827,810 11,575,908 11,468,196 11,186,185 10,711,728 11,421,574

Difference 1 2,801,830 2,526,691 2,286,666 1,977,171 1,287,272 2,265,474

Groundwater

With-CVP 6,816,781 7,351,101 7,691,034 8,205,010 9,223,235 7,710,807

Without-CVP 6,878,441 7,424,578 7,771,164 8,278,480 9,246,889 7,774,876

Difference 1 -61,660 -73,478 -80,130 -73,470 -23,654 -64,069

1. Difference reflects difference between with-CVP and without-CVP conditions

2.3.5 Surface Water Costs

Changes in the quantity and type of agricultural water use directly affect water costs incurred by 

farmers. Table 2-7 shows the difference in surface water costs between the with-CVP and withoutCVP scenarios excluding the cost of CVP water supplies, which are not considered for the purposes 

of estimating project benefits. As explained above, surface water use increases with the CVP; 

accordingly, surface water costs also increase. However, when excluding CVP water supplies, other 
Economic Benefits Analysis Appendix | 25

surface water costs decrease with the CVP compared to without the CVP. On average, other surface 

water supplies cost farmers approximately $267.6 million annually with the CVP, compared to 

$286.8 million without the CVP. This reduction in costs, -$19.2 million, represents a benefit to 

growers served by CVP water supplies.

Table 2-7. Surface Water Cost, by Water Year Type, Summary ($) 1

Scenario Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

With-CVP $283,512,325 $272,063,753 $268,324,043 $259,578,649 $240,916,208 $267,604,958

Without-CVP $305,954,440 $293,523,457 $289,740,987 $275,175,462 $253,574,585 $286,773,582

Difference 2 -$22,442,114 -$21,459,704 -$21,416,944 -$15,596,813 -$12,658,377 -$19,168,624

1. Excludes CVP water costs

2. Difference reflects difference between with-CVP and without-CVP conditions

2.3.6 Groundwater Pumping Costs

Groundwater represents an alternative water source available to growers in lieu of surface water 

supplies. Groundwater use declines with the CVP as more surface water becomes available; 

however, due to constraints on groundwater pumping in the without-CVP scenario, the difference 

in groundwater pumping costs between the two scenarios is minor. Table 2-8 shows the difference 

in groundwater costs between the with-CVP and without-CVP scenarios. With the CVP, 

groundwater pumping costs are estimated to be about $796.6 million annually, while without the 

CVP, groundwater costs are $801 million annually. This represents a savings in groundwater 

pumping costs of $4.4 million annually with the CVP. 

Table 2-8. Groundwater Pumping Cost, by Water Year Type, Summary ($)

Scenario Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

With-CVP $660,429,298 $746,117,644 $801,110,890 $874,070,734 $1,009,171,119 $796,586,579

Without-CVP $665,161,403 $751,501,969 $806,769,265 $878,214,085 $1,010,444,126 $800,958,834

Difference 1 -$4,732,105 -$5,384,325 -$5,658,375 -$4,143,351 -$1,273,007 -$4,372,255

1. Difference reflects difference between with-CVP and without-CVP conditions

2.3.7 Land Fallowing Costs

There are also costs associated with fallowing land. These costs are typically attributed to 

maintenance activities, such as weed control. With the CVP, additional acreage is put into 

agricultural production, resulting in fewer acres being fallowed compared to without-CVP 

conditions. Table 2-9 shows the cost savings (avoided land fallowing costs) under the with-CVP 

scenario. On average, land fallowing costs decline by about $24.5 million annually with the CVP.
26 | Central Valley Project Final Cost Allocation Study

Table 2-9. Land Fallowing Costs, by Water Year Type, Summary ($)

Scenario Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

With-CVP -$32,591,473 -$28,448,873 -$24,384,224 -$20,387,239 -$10,229,515 -$24,543,453

Without-CVP -- -- -- -- -- --

Difference 1 -$32,591,473 -$28,448,873 -$24,384,224 -$20,387,239 -$10,229,515 -$24,543,453

1. Difference reflects difference between with-CVP and without-CVP conditions

2.3.8 Summary of Irrigation Water Supply Benefits

The economic benefits associated with CVP irrigation water supplies reflect the additional profit 

(producer surplus) realized by farmers across SWAP regions. This benefit is comprised of four 

components: net income, surface water costs, groundwater pumping costs, and land fallowing costs. 

Specifically, the calculation of the irrigation benefits in SWAP is calculated using the following 

formula (where the change reflects the difference between with-CVP and without-CVP conditions): 

Change in net income 

less change in surface water costs

less change in groundwater costs 

less change in land fallowing costs 

= CVP Irrigation Benefits

Table 2-10 displays estimated irrigation benefits attributed to the CVP. Average irrigation benefits 

are estimated to be $544.7 million annually. The greatest benefits occur in wet years ($877.2 million 

annually) based on the relatively high quantity of CVP surface water that is delivered. Conversely, 

the lowest benefits occur in dry years ($176.9 million annually).
Economic Benefits Analysis Appendix | 27

Table 2-10. Economic Benefits of CVP Irrigation Water Supplies, by Water Year Type ($) 1

Category Wet

Above 

Normal

Below 

Normal Dry Critical

Average 

(Wgt)

Net Income $817,409,837 $586,995,264 $434,239,589 $276,516,848 $152,690,820 $496,631,729

SW Costs 2 -$22,442,114 -$21,459,704 -$21,416,944 -$15,596,813 -$12,658,377 -$19,168,624

GW Costs -$4,732,105 -$5,384,325 -$5,658,375 -$4,143,351 -$1,273,007 -$4,372,255

Fallowing Costs -$32,591,473 -$28,448,873 -$24,384,224 -$20,387,239 -$10,229,515 -$24,543,453

Total $877,175,528 $642,288,166 $485,699,131 $316,644,252 $176,851,718 $544,716,061

1. Benefits reflects difference between with-CVP and without-CVP conditions

2. Excludes CVP water costs

For the CAS, annual irrigation benefits are capitalized over the 100-year period of analysis using a 

3.25 percent interest rate. The present value of CVP irrigation benefits is $16,076,140,223. 
28 | Central Valley Project Final Cost Allocation Study

This page intentionally left blank. 
Economic Benefits Analysis Appendix | 29

Chapter 3. Municipal and Industrial Water 

Supply

3.1 Introduction

This appendix describes the analytical methods the Central Valley Project Cost Allocation Study 

(CAS) team used to estimate Municipal and Industrial (M&I) water supply benefits of the Central 

Valley Project (CVP) and presents the results. The CAS used two models to estimate (M&I) 

benefits: 1) the Least Cost Planning Simulation Model (LCPSIM) and 2) the Other Municipal Water 

Economics Model (OMWEM). LCPSIM was used to estimate CVP M&I water supply benefits in 

the San Francisco Bay Area and OMWEM estimated CVP M&I benefits for the Central Valley.

3.2 Methodology

This section provides information on the methodology and analytical framework of LCPSIM and 

OMWEM, including information on assumptions, input data, and results within the context of the 

CVP-CAS.

3.2.1 LCPSIM in the Central Valley Project Cost Allocation Study

The LCPSIM was developed by the State of California’s Department of Water Resources (DWR) to 

estimate the benefits of improving M&I water service reliability for California’s South Coast and 

South San Francisco Bay Regions. For the CAS, LCPSIM only considers the South Bay Region as 

there are no M&I CVP contractors in the South Coast Region. 

LCPSIM is an annual time-step urban water service system simulation/optimization model. Its 

objective is to find the least-cost water management strategy for a region/district, given the demand 

and available supplies. It uses shortage management measures, including the use of regional 

carryover storage, water market transfers, contingency conservation, and shortage allocation rules to 

reduce costs and losses associated with shortage events. It also considers the adoption of long-term 

demand reduction and supply augmentation measures that reduce the frequency, magnitude, and 

duration of shortage events. 

A shortage event is the most direct consequence of water service system unreliability. A shortage 

event may occur when residential users or businesses have an established lifestyle or level of 

economic production based on expected availability of water that is not met in a particular year or 

sequence of years. For the CAS, the costs of these shortage events are calculated in LCPSIM and 

OMWEM by estimating the area under the demand curve that is lost by water users consuming less 

water than expected; it is assumed that demand is best represented by a constant price elasticity 

specification with a price elasticity coefficient equal to -0.2.
30 | Central Valley Project Final Cost Allocation Study

Assuming that long-term demand reduction and supply augmentation measures are adopted in order 

of cost, with lowest cost measures adopted first, the models solve for the water management 

strategy that minimizes the sum of the total annual cost of the adopted long-term reliability 

enhancement measures and the annual shortage costs and losses remaining after their adoption 

(Figure 1). Beyond the least-cost point shown, the cost of additional reliability enhancement exceeds 

the avoided costs and losses resulting from foregone use. At any lower level of reliability 

enhancement, the expected costs and losses from foregone use exceed the costs to enhance 

reliability. The value of the availability of supply provided by the CVP can be determined from the 

change it produces (relative to a without-CVP scenario) in this least-cost mix of demand and supply 

measures and shortages.

Figure 3-1. Least Cost Point – Optimizing Shortage Costs/Losses and Reliability Augmentation (DWR 

2010).

3.2.1.1 LCPSIM Coverage for CVP-CAS

The CVP M&I water service contractors modeled in the LCPSIM include: Contra Costa Water 

District (CCWD), East Bay Municipal Utility District (EMMUD), Santa Clara Valley Water District 

(SCVWD), and the San Benito County Water District (SBCWD). For the CAS, the majority of State 

Water Project (SWP) M&I water contractors and deliveries were not modeled in LCPSIM. The 

exception is the SCVWD as they receive CVP and SWP water. Removing SWP M&I water deliveries 

ensures that the LCPSIM optimization process will not consider SWP supplies allowing the costs 

associated with the without-CVP scenario to be assigned to only to CVP contractors. 
Economic Benefits Analysis Appendix | 31

3.2.1.2 Water Supply Modeling Assumptions (LCPSIM and OMWEM)

Both LCPSIM and OMWEM use output from the CALSIM II operations model to estimate 

deliveries in both project scenarios (with- and without-CVP). Water delivery data from the CALSIM 

II modeling is the only difference between each scenario and is the basis for the changes in 

economic costs. 2030 CVP M&I contractor water supply portfolios assumed in the CAS were 

developed from Urban Water Management Plans and CALSIM II modeled water rights and CVP 

project water. In both the with-CVP scenario and without-CVP scenario, each CVP M&I 

contractor's local water supplies and CALSIM II modeled water rights are included in the analysis.

Only in the with-CVP alternative are the CALSIM II modeled project water deliveries included.

3.2.1.3 LCPSIM Contractor Demand

Table 3-1 below displays the year 2030 CVP M&I contract quantities and demands for each 

contractor modeled in LCPSIM for the CVP-CAS. There are a few important points to consider in 

regard to the assumed 2030 demand levels used for this study:

• 2030 demands sourced from CVP M&I contractor’s 2010 Urban Water Management Plan

(UWMP), if available

• 2030 demands sourced from the Bureau of Reclamation’s Central Valley Project M&I Water

Shortage Policy Draft Environmental Impact Statement (2014), if UWMP is not available

• The 2030 demands published in the UWMPs are assumed to be compliant with the “20% by

2020” legislation, which refers to conservation criteria

• When an UWMP accounts for additional conservation as part of 2030 supply, this is

reflected in OMWEM as a demand reduction instead of as new supply

Table 3-1. LCPSIM Modeled Demands in 2030

CVP M&I Contractor

2030 CVP Contract 

Quantities (AF)

2030 Demands from 

UWMP (AF)

Contra Costa Water District 195,000 215,471

East Bay Municipal Utilities 

District 133,000 304,000

Santa Clara Valley Water District 219,400 409,370

San Benito County Water 

District 8,250 11,583
32 | Central Valley Project Final Cost Allocation Study

3.2.1.4 LCPSIM Contractor Supply

Table 3-2 below displays the CVP M&I contractor non-CVP supplies for a below normal or better 

water year and a dry or critical water year modeled in LCPSIM. There are some important points to 

consider in regard to the assumed non-project supplies used for this study: 

• Local supplies expected to be available in the year 2030 are based on information from the

UWMPs

• LCPSIM uses the 2030 “normal” year supplies reported in the UWMPs to represent the

2030 supplies in wet, above normal, and below normal water year types

• LCPSIM uses the “multiple-year drought” supplies reported in the UWMPs to represent the

2030 supplies in dry and critical water year types

Table 3-2. LCPSIM Assumed 2030 Non-CVP Supplies

CVP M&I Contractor

Non-CVP 2030 Supplies in 

Below Normal or Better 

Water Year Type (AF)

Non-CVP 2030 Supplies 

in Dry or Critical Water 

Year Type (AF)

Contra Costa Water District 44,800 32,400

East Bay Municipal Utilities 

District 19,000 19,000

Santa Clara Valley Water District 246,830 179,980

San Benito County Water 

District 1,170 1,170

3.2.1.5Water Transfers

For the CAS study it is assumed water transfers will not occur without the CVP in place. There are 

two primary reasons for this: 1) without the CVP in place, transfers would most likely come from 

agricultural contractors, but since the study is not accounting for these potential/hypothetical 

transfers on the agricultural side, it was assumed that the they also would not occur on the M&I side 

and 2) even if water was available to transfer, there would significant infrastructure constraints that 

would hinder deliveries. The removal of water transfers forces LCPSIM to employ other demand 

reduction/supply augmentation options in order to balance demand and supply or to incur more 

shortage costs.

3.2.1.6 LCPSIM limitations

The results presented below are best estimates based on various assumptions and best available data. 

It is believed that the estimate of benefits derived using the LCPSIM is reasonable and useful for the 

purposes of measuring avoided costs of having the CVP in place. Potential limitations of LCPSIM 

include: 
Economic Benefits Analysis Appendix | 33

• LCPSIM is not appropriate for individual water agency management decisions because of

the simplifying assumptions it makes about regional system operations.

• Because LCPSIM is used to optimize regional economic efficiency from a statewide

perspective, LCPSIM results may not reflect decisions made by local water agencies that are

based on their cost perspective. Also, local planning decisions are likely to be influenced by

local cost effectiveness and political concerns as well as additional factors of importance to

regional water agency managers and water users that are not necessarily aligned with the

LCPSIM objective.

• LCPSIM uses regional operations studies for local imported supplies to obtain annual

delivery information. Regional water supply sources that are not modeled on a year-to-year

basis are assumed to be available at their average year values.

• LCPSIM determines its reliability benefits estimates on the basis of a risk-neutral view of risk

management. Risk-averse management (risk minimization) by regional agencies–which has

been the predominant mode–might result in the justification of more costly water

management measures than under the risk neutral assumption.

• LCPSIM is operated on an annual basis. Therefore, it does not simulate seasonal water

decisions.

• Base urban use amounts are not reduced in LCPSIM in response to the higher urban user

water prices that can be anticipated as regions use water pricing to offset water reliability cost

increases.

3.2.2 OMWEM in the Central Valley Project Cost Allocation Study

OMWEM simulates individual water contractor’s decision making based on 2030 development 

conditions using publicly available information. The majority of the water demand and supply data 

were taken from contractors’ Urban Water Management Plans. OMWEM analyzes the economic 

benefits of the M&I water supply for contractors by minimizing total costs of meeting annual M&I 

water demands, per contractor, and subject to constraints. These costs include conveyance and 

operations costs, existing supply and new permanent supply costs, transfer or other option costs, 

local surface and groundwater operations costs, end-user shortage costs, and lost water sales 

revenues. OMWEM was revised for the CAS study to include only CVP M&I water contractors in 

the Sacramento and San Joaquin Valleys of California.

Operating on an annual time step over the 1922 to 2003 hydrologic period, the model uses 1) 

contract delivery data (which is modeled in CALSIM II), 2) local water supply information, and 3) 

imported water information (if applicable) to simulate the decision making of each individual 

contractor as it attempts to meet its 2030 water demand levels at the lowest economic cost. When 

demand exceeds supply, the model will compute the economic cost of each water contractor as it 

attempts to either use local stored supplies, purchase or transfer water on the market, or short its 

customers. If these shortages happen frequently over the hydrologic period, an individual contractor 

may choose to invest in additional fixed-yield supply. This is represented in OMWEM as a trade-off 

between incurring shortage costs and investing in additional fixed-yield supply. As in LCPSIM, 

shortage costs are calculated in OMWEM using a -0.2 constant elasticity of demand function. The 
34 | Central Valley Project Final Cost Allocation Study

retail water price and the 2030 demand level of a contractor define one point on its demand 

function, wherein the slope is defined by the price elasticity.

Within the OMWEM model, individual CVP M&I contractors were grouped into two main regions, 

the Sacramento Valley and San Joaquin Valley. The with-CVP and without-CVP scenarios for both 

regions were estimated using one model run. Table 3-3 lists the CVP M&I contractors included in 

each region.
Economic Benefits Analysis Appendix | 35

Table 3-3. CVP Water Contractors included in OMWEM by Region

Sacramento Valley San Joaquin Valley

El Dorado Irrigation District All other Friant-Kern M&I contractors (ArvinEdison Water Storage District, Delano-Earlimart 

Irrigation District, Lindsay-Strathmore Irrigation 

District)

City of Folsom City of Avenal

Placer County Water Agency City of Coalinga

City of Redding City of Fresno

City of Roseville City of Huron

Sacramento County Water Agency City of Lindsay

San Juan Water District City of Orange Cove

City of Shasta Lake, Shasta County Water Agency, 

Centerville CSD (CSD), Mountain Gate CSD, and 

Shasta CSD

Stockton-East Water District

City of West Sacramento City of Tracy

As noted above, the San Francisco Bay Area CVP contractors, EBMUD, CCWD, SCVWD, and 

SBCWD, are not included in the CAS OMWEM model as they are modeled in the LCPSIM. 

3.2.2.1 OMWEM Contractor Demand 

Table 3-4 below displays the year 2030 CVP M&I contract quantities and demands for each 

contractor modeled in OMWEM for the CAS. As noted about with LCPSIM, there are a few 

important points to consider in regard to the assumed 2030 demand levels used for this study:

• 2030 demands sourced from CVP M&I contractor’s 2010 Urban Water Management Plan

(UWMP), if available

• 2030 demands sourced from the Bureau of Reclamation’s Central Valley Project M&I Water

Shortage Policy Draft Environmental Impact Statement (2014), if UWMP is not available

• The 2030 demands published in the UWMPs are assumed to be compliant with the “20% by

2020” legislation, which refers to conservation criteria

• When an UWMP accounts for additional conservation as part of 2030 supply, this is

reflected in OMWEM as a demand reduction instead of as new supply
36 | Central Valley Project Final Cost Allocation Study

Table 3-4. OMWEM Modeled Demands in 2030

CVP M&I Contractor

2030 CVP 

Contract 

Quantities (AF)

2030 Demands 

from UWMP (AF)

All other Friant-Kern M&I contractors (Arvin-Edison 

Water Storage District, Delano-Earlimart Irrigation 

District, Lindsay-Strathmore Irrigation District)

2,926 6,000

City of Avenal 3,500 3,500

City of Coalinga 10,000 10,000

El Dorado Irrigation District 7,550 57,039

City of Folsom 34,000 36,259

City of Fresno 60,000 201,100

City of Huron 3,000 3,000

City of Lindsay 2,500 2,689

City of Orange Cove 1,400 2,790

Placer County Water Agency 100,000 156,333

City of Redding 27,140 27,852

City of Roseville 62,000 49,334

Sacramento County Water Agency 81,438 77,535

San Juan Water District 82,200 57,265

City of Shasta Lake, Shasta County Water Agency, 

Centerville CSD, Mountain Gate CSD, Shasta CSD

10,672 10,942

Stockton-East Water District 75,000 64,960

City of Tracy 20,000 31,000

City of West Sacramento 23,600 19,273
Economic Benefits Analysis Appendix | 37

3.2.2.2 OMWEM Contractor Supply

Table 3-5 below displays the CVP M&I contractor non-CVP supplies for a below normal or better 

water year and a dry or critical water year. There are some important points to consider in regard to 

the assumed non-project supplies used for this study: 

• Local supplies expected to be available in the year 2030 are based on information from the

UWPMs

• OMWEM uses the 2030 “normal” year supplies reported in the UWMPs to represent the

2030 supplies in wet, above normal, and below normal water year types

• OMWEM uses the “multiple-year drought” supplies reported in the UWMPs to represent

the 2030 supplies in dry and critical water year types

Table 3-5. OMWEM Assumed 2030 Non-CVP Supplies

CVP M&I Contractor

Non-CVP 2030 Supplies in 

Below Normal or Better 

Water Year Type (AF)

Non-CVP 2030 Supplies 

in Dry or Critical Water 

Year Type (AF)

All other Friant-Kern M&I 

contractors (Arvin-Edison Water 

Storage District, Delano-Earlimart 

Irrigation District, LindsayStrathmore Irrigation District)

3,000 0 

City of Avenal 0 0

City of Coalinga 0 0

El Dorado Irrigation District 54,789 54,789

City of Folsom 3,250 11,250

City of Fresno 228,800 232,400

City of Huron 0 0

City of Lindsay 1,210 1,210

City of Orange Cove 0 0

Placer County Water Agency 68,119 103,119

City of Redding 13,424 13,424

City of Roseville 3,397 3,397
38 | Central Valley Project Final Cost Allocation Study

CVP M&I Contractor

Non-CVP 2030 Supplies in 

Below Normal or Better 

Water Year Type (AF)

Non-CVP 2030 Supplies 

in Dry or Critical Water 

Year Type (AF)

Sacramento County Water Agency 74,898 74,898

San Juan Water District 0 0

City of Shasta Lake, Shasta County 

Water Agency, Centerville CSD, 

Mountain Gate CSD, Shasta CSD

1,064 1,064

Stockton-East Water District 28,000 50,000

City of Tracy 15,250 16,050

City of West Sacramento 5,000 5,000

3.2.2.3 Summary of OMWEM Logic

The model selects a level of supply that minimizes total cost over the 82-year hydrologic period. For 

each year and agency, the OMWEM considers demand requirements and CVP supply quantities and 

attempts to bring about a water balance under average water supply conditions. If new water 

supplies are necessary, then the model will calculate the amount and costs of additional supplies that 

would generate the least overall costs by optimizing the mix of shortage and new supply costs, while 

at the same time accounting for all other costs and savings. This is an iterative process until the total 

annual cost of water demand and supply management is minimized. 

It is important to point out that the OMWEM and LCPSIM are inherently inexact because complex 

human and organizational decisions surrounding the use of limited resources must be simulated 

using mathematical descriptions. So although it may not be possible for the economic costs and 

tradeoffs faced by each CVP M&I contractor to be calculated precisely, the model can provide 

realistic and representative estimates of economic costs associated with each scenario (with-CVP and 

without-CVP) and by extension, a representative estimate of the difference in economic costs 

between the two scenarios. This difference in economic costs represents the benefits (i.e., avoided 

additional costs of not having the CVP) of the CVP and is the benefit estimate used for the M&I 

water supply purpose in the SCRB analysis. 

Not all CVP M&I water contractors were modeled in OMWEM. If the necessary modeling 

information required for OMWEM was unavailable or deficient for a particular contractor, then 

these contractors were not explicitly modeled in OMWEM. To capture the total benefits of the CVP 

for all non-modeled contractors, average benefits per acre foot were obtained from OMWEM 

output for the Sacramento and San Joaquin Valleys then multiplied by each contractor’s long term 

historical deliveries. The historical long term average deliveries and benefits by region are shown in 

Table 7 (in the Results section). The following is a list CVP M&I contractors and conveyance 

source, if applicable, that are not explicitly modeled in OMWEM:
Economic Benefits Analysis Appendix | 39

Sacramento Valley

• Colusa County Water District – Black Butte

• Elk Creek Community Services District

• US Forest Service –Black Butte

• Whitney

• Clear Creek Community Services District

• Bella Vista Water District

• Lake CA Property Owners Association

• Riverview Golf & Country Club

• Colusa County Water District –Tehama Colusa Canal

• Kanawha Water District

• US Forest Service Toyon Pipeline–

• SMUD –Folsom South Canal

San Joaquin Valley 

• Fresno County

• Tulare County

• Byron Bethany Irrigation District

• Del Puerto Water District

• Department of Veterans Affairs

• Panoche Water District– Delta Mendota Canal

• San Luis Water District – Delta Mendota Canal

• Madera County Water District

• Fresno County Waterworks #18

• State of California – San Luis Canal

• Westlands Water District – San Luis Canal

• Pacheco Water District – San Luis Canal

• Panoche Water District – San Luis Canal

• San Luis Water District – San Luis Canal
40 | Central Valley Project Final Cost Allocation Study

3.3 Results

3.3.1 Non-Modeled Results

Table 3-7 shows the deliveries and benefits for all CVP M&I contractors by region that are not 

modeled in OWMEM. 

Table 3-6. Expected Deliveries and Benefits of CVP M&I Contractors NOT Included in 

OMWEM (2013 prices) 

Category

Sacramento 

Valley

San Joaquin 

Valley Total

Long Term Average CVP M&I Deliveries 

(TAF)

25 6 31

Average Annual Benefits ($1,000) $9,046 $3,360 $12,406

3.3.2 LCPSIM and OMWEM Results, Annual Benefits and Present Value of Annual 

Benefits

Table 3-8 shows the change in CVP M&I deliveries and total expected costs by water year type 

assumed in each model. The values for change in expected costs are calculated as the total costs of 

water supply reliability with-CVP in place minus total costs without-CVP in place. As mentioned 

above, in both the with-CVP and without-CVP scenarios, each CVP M&I contractor's local water 

supplies and CALSIM II modeled water rights are included in the analysis. Only in the with-CVP 

scenario are the CALSIM II modeled project water deliveries included. The total expected costs 

entries in Table 8 represent: 1) all costs to water purveyors as they attempt to meet 2030 water 

demands and 2) shortage costs faced by water users when actual delivered water does not meet their 

demands. 

Both LCPSIM and OMWEM calculate benefits as the reduction of overall costs by having the CVP 

in place. To be consistent with other CAS related economics benefit estimates, only the benefit for 

the water year type “weighted average” is calculated and carry forward for the SCRB analysis. For 

M&I water supply, it is estimated to be approximately $220 million and is shown in the rightmost 

column of Table 8; this value is calculated as LCPSIM and OMWEM total water year type weighted 

average expected costs with-CVP minus weighted average expected costs without-CVP ($207.6 

million) plus the total benefits of the CVP contractors not included in OMWEM ($12.4 million 

from Table 3-7).
Economic Benefits Analysis Appendix | 41

Table 3-7: Without-CVP versus With-CVP Expected M&I Water Deliveries and Economic Costs 

by Water Year Type and Benefits (2013 prices)

Water Year Type LCPSIM OMWEM

Total LCPSIM and 

OMWEM Benefits1

Weighted Average

CVP M&I Deliveries (TAF) 195 282 477

Total Expected Costs 

includes water provision and 

shortage costs ($1,000) $82,269 $125,455 $207,587 $219,994

Wet

CVP M&I Deliveries (TAF) 196 333 529

Total Expected Costs 

includes water provision and 

shortage costs ($1,000) $88,351 $124,872 $213,223

Above Normal

CVP M&I Deliveries (TAF) 188 301 489

Total Expected Costs 

includes water provision and 

shortage costs ($1,000) $85,581 $115,613 $201,194

Below Normal

CVP M&I Deliveries (TAF) 184 288 472

Total Expected Costs 

includes water provision and 

shortage costs ($1,000) $79,800 $110,801 $190,601

Dry

CVP M&I Deliveries (TAF) 197 253 450

Total Expected Costs 

includes water provision and 

shortage costs ($1,000) $77,603 $145,535 $223,138

Critical

CVP M&I Deliveries (TAF) 208 190 398
42 | Central Valley Project Final Cost Allocation Study

Water Year Type LCPSIM OMWEM

Total LCPSIM and 

OMWEM Benefits1

Total Expected Costs 

includes water provision and 

shortage costs ($1,000) $75,660 $123,277 $198,937

1. Includes total benefits from LCPSIM, OMWEM and non-modeled OMWEM contractors

The overall water year type weighted average value of $220 million is used to calculate the present 

value of future CVP M&I benefits. The present value formula is: 

PV = present value 

Benefits = annual benefits (constant over the project life) 

i = discount rate 

n = number of years (project life) 

For CAS, it is assumed the project life is 100 years and the discount rate is 3.25 percent. Table 3-9 

shows the present value of CVP M&I benefits to be approximately $6.5 billion in 2013 prices. 

Table 3-8. Total Present Value of CVP M&I Benefits (100 Year Project Life, 3.25% interest rate,

2013 prices)

Total Annual CVP M&I Benefits $219,994,319

Present Value of CVP M&I Benefits $6,492,666,135

3.4 Summary of M&I Water Supply Benefits

The present value of CVP M&I benefits estimated for the San Francisco Bay Area (from LCPSIM) 

and the Central Valley (from OMWEM) are approximately $6.5 billion. This value will be added to 

the CVP irrigation water supply benefits to calculate the total benefits for all CVP related water 

supply purposes. The total value of all CVP water supply related benefits will be compared to the 

single-purpose alternative (SPA) cost estimate for water supply, the lower of the two estimates 

(benefits or SPA costs) will be the justifiable expenditure for water supply in the SCRB analysis.
Economic Benefits Analysis Appendix | 43

Chapter 4. Water Quality

4.1 Introduction & Overview

Water quality is an authorized purpose of the Central Valley Project (CVP). The CVP maintains 

increased flows in the Trinity, American, and Stanislaus rivers to improve the fisheries habitat and 

water quality conditions in the San Francisco Bay/Sacramento-San Joaquin Delta and Estuary 

(Delta). The California State Water Resources Control Board (SWRCB) is responsible for setting 

water quality standards in the Delta, which govern the operations of both the CVP and the State 

Water Project (SWP). Specifically, the CVP is responsible for meeting its share of the salinity 

outflow standards set by the SWRCB, including Water Rights Decision 1485 (D-1485) and Decision 

1641 (D-1641). Compliance with D-1485 water quality standards is considered mitigation and not a 

water quality benefit of the CVP; the cost of complying with D-1485 will be reimbursed in 

accordance with existing Reclamation law and policy. Conversely, compliance with D-1641 (above 

D-1485 requirements) is considered a water quality benefit of the CVP and the associated costs are

non-reimbursable.

4.2 Methodology

The economic benefits attributed to water quality can be estimated by various methods. For the 

CAS, water quality benefits are based on the foregone value of the next best use of the water used to 

meet water quality standards (i.e., irrigation). In other words, CVP water quality benefits are based 

on the irrigation value of water, which is estimated using the SWAP model. Refer to Chapter 2 

(Irrigation Benefits) for more information on the SWAP model and underlying methodology used to 

estimate the value of irrigation water supplies.

4.2.1 Hydrology Inputs

As noted above, the water quality benefits of the CVP are based on the incremental flow 

requirements required to meet D-1641 water quality standards (above D-1485); these incremental 

flows have been measured using CalSim hydrology modeling. CVP water supplies that are used to 

support water quality benefits are derived from two sources – foregone water deliveries and Delta 

outflows. Foregone water deliveries consist of irrigation, M&I, and refuge deliveries, and Delta 

outflows represent water that is retained in stream and ultimately flow out of the system. Foregone 

irrigation water deliveries are estimated to be approximately 107 TAF annually on average (i.e., 

across all water year types), while foregone M&I and refuge deliveries are estimated to total about 5 

TAF annually. For Delta outflows, approximately 156 TAF of water is required from the combined 

CVP/SWP system on average; however, only the CVP contribution to Delta outflow requirements 

is accounted for in the CAS, which is estimated to be about 60 TAF based on COA operating rules. 

Table 4-1 presents a summary of water requirements to meet incremental D-1641 water quality 

standards by source and water year type.
44 | Central Valley Project Final Cost Allocation Study

Table 4-1. D-1641 Water Requirements, by Source and Water Year Type (TAF)

Water Year 

Type

Foregone Irrigation 

Water

Foregone M&I & 

Refuge Water

Delta 

Outflows 1,2 Total

Wet 34.1 1.9 0.0 36.0

Above Normal 114.1 5.0 0.0 119.1

Below Normal 166.9 6.6 206.0 379.5

Dry 117.5 4.2 338.3 460.0

Critical 171.1 9.7 449.0 629.8

Average 106.8 4.8 60.4 171.9

1. Represents CVP portion of Delta outflow requirement

2. CalSim modeling show that (D1641 – D1485) changes to estimated Delta outflow requirements in wet

and above normal years are negative; these values have been adjusted to zero.

There are adjustments to the Delta outflow data by water year type that must be accounted for in the 

modeling of water quality benefits. Delta outflow requirements for the CVP in wet and above 

normal years are lower under D-1641 relative to D-1485 based on CalSim modeling, suggesting 

there are no water quality benefits attributed to Delta outflows in those water year types. Therefore, 

it is not appropriate to include (model) Delta outflows in wet and above-normal water years in 

SWAP. i.e., Delta outflows were set to zero in wet and above normal water years. Delta outflows 

were only considered in below normal, dry, and critical water years. 

The fundamental premise of the water quality benefit analysis is that all CVP water that is required 

meet incremental D-1641 requirements must be valued, including foregone irrigation and 

M&I/refuge deliveries and Delta outflows. As shown in Table 1, this quantity ranges from a low of 

36 TAF in wet years to nearly 630 TAF in critical years, averaging 172 TAF across all water years. 

4.2.2 Application of SWAP Model

Water quality benefits are quantified based on the value of the water in its next most likely 

alternative use; in this case, agricultural production using the SWAP model. The steps used in the 

application of the SWAP model to estimate water quality benefits is presented below: 

1. Quantify all CVP water requirements that support water quality benefits (see Table 1).

2. Run the SWAP model simulating the change between the D-1641 and D-1485 hydrology 

scenarios from CalSim.

3. Distribute the estimated water supplies that support water quality benefits (Step 1) across 

SWAP regions based on the distribution of changes in irrigation supplies across SWAP 

regions in the model run in Step 2.
Economic Benefits Analysis Appendix | 45

4. Add the calculated CVP water quality requirements (AF) by SWAP region to the existing 

base-case SWAP model run depicting current conditions (note that this is the SWAP model 

depicting the with-CVP scenario in the irrigation benefits analysis).

5. Run the SWAP model evaluating the change between the base-case (with-CVP) hydrology 

and the water quality-adjusted hydrology.

6. Estimate the water quality benefits as the difference in irrigation benefits in the two 

modeling scenarios in Step 5.

4.2.3 Other Methodological Considerations

The methodology outlined above focuses on the hydrology associated with water quality and the 

SWAP model; however, there are other important methodological considerations in the estimation 

of CVP water quality benefits, which are described below.

4.2.3.1 Prospective Period of Analysis – Assumptions 

Water quality benefits are based future conditions expected over the 100-year period of analysis. For 

this study, estimated water quality benefits (reported as an annual value) are assumed to remain 

constant over the entire period of analysis. The 100-year stream of benefits is discounted over the 

100-year period of analysis using a 3.25 percent interest rate for use in the SCRB cost allocation

process. It is acknowledged that water quality conditions are dynamic and will change over the 100-

year period of analysis; however, due to modeling and data limitations, a single year scenario was

used to reflect the prospective period of analysis.

4.3 Water Quality Benefits Results

This section presents estimated water quality benefits provided the CVP. As explained in the 

methodology section, the water quality benefits are based SWAP modeling, which provides a proxy 

value for water quality benefits using agricultural values. The benefits reported by SWAP are 

calculated based on changes in net farm income (profit or producer surplus), surface water and 

groundwater costs, and land fallowing costs. All monetary values are reported in 2013 dollars.

4.3.1 Summary of Water Quality Benefits

Table 4-2 displays estimated water quality benefits attributed to the CVP. Water quality benefits are 

estimated to be $49.4 million annually, on average. The greatest benefits occur in critical years 

($103.3 million annually) based on the relatively large quantity of CVP water that is needed to meet 

incremental D-1641 water quality standards. Conversely, the lowest benefits occur in wet years ($7.0 

million annually).
46 | Central Valley Project Final Cost Allocation Study

Table 4-2. NED Economic Benefits of CVP Water Quality, by Water Year Type ($)

Benefit Wet

Above 

Normal

Below 

Normal Dry Critical

Weighted 

Average 

Water Quality $7,043,111 $21,357,148 $60,744,532 $80,594,730 $103,332,263 $49,387,199

For the CAS, annual water quality benefits are discounted over the 100-year period of analysis 

using a 3.25 percent interest rate. The present value of CVP water quality benefits is 

$1,457,558,518. 
Economic Benefits Analysis Appendix | 47

Chapter 5. Flood Control

5.1 Introduction

The Central Valley Project (CVP) is composed of several dams/reservoirs that were authorized and 

constructed to meet multiple purposes, one being flood control. The CVP dams/reservoirs that 

provide flood control benefits include: 

• Shasta Dam & Reservoir (Shasta County)

• Folsom Dam & Reservoir (Sacramento County)

• New Melones Dam & Reservoir (Calaveras County)

• Friant Dam & Reservoir (Fresno County)

There are several other CVP facilities that provide flood control benefits, which have not been 

quantified for the CAS. These facilities include Trinity Dam & Reservoir, Los Banos Creek 

Detention Dam, and Whiskeytown Dam & Reservoir. Although these facilities provide flood 

control benefits, they have not been quantified due to lack of available data. As such, the benefits 

provided in this paper represent a lower bound of flood control benefits provided by the CVP. 

Further, the omission of flood control benefits at these facilities does not affect the cost allocation 

because the flood control SPA (and not benefits) represents the justifiable expenditure for flood 

control in the SCRB calculations. 

The following sections summarize the methodology, data, assumptions, and analysis used to 

estimate the flood control benefits provided by the dams/reservoirs. Benefit estimates for use in the 

SCRB analysis for the CVP Cost Allocation Study (CAS) are summarized in Table 3 of this report. 

5.2 Methodology

Damages Prevented. Flood control benefit estimates were made for each of the first four 

dams/reservoirs using historical annual damages prevented information provided by the U.S. Army 

Corps of Engineers (USACE), Sacramento District. The damages prevented reports represent 

preliminary estimates, by dam/reservoir, using data available at the end of each fiscal year. Because 

the Corps is responsible for all federal flood control storage, the report includes damages prevented 

by Corps-operated projects as well as non-Corps projects that have federal flood control storage. 

The USACE (Sacramento District) calculates annual damages prevented by comparing downstream 

river stages at selected sites under regulated flow conditions and unregulated flow conditions. The 

river stages under each condition are then compared to a stage-damage curve, which describes the 

amount of damages that could be expected based on a range of river stages representing high 

exceedance probability to low exceedance probability flow events. The lower amount of damages 

under the with-project condition as compared to the without project condition reflect the positive 
48 | Central Valley Project Final Cost Allocation Study

effects of reservoir operations on downstream flows and are considered to be the damages 

prevented (benefits). This computational exercise is performed annually for each dam/reservoir 

facility having a flood damage reduction purpose. 

The USACE damages prevented information was used to estimate benefits for the Shasta Dam & 

Reservoir, the Folsom Dam & Reservoir, the New Melones Dam & Reservoir, and the Friant Dam 

& Reservoir. The damages prevented information was updated to October 2013 price levels, and 

total benefits were computed over a 100-year period of analysis using a discount rate of 3.25%. The 

damages prevented information for each dam/reservoir is presented in Table 1 below. 

5.3 Data

Damages Prevented. The USACE provided damages prevented data up to the year 2010. Table 5-

1 below displays the information by dam/reservoir. Adjustment factors for each year of record were 

calculated using 2013 as the base year and the Gross Domestic Product (GDP) Implicit Price 

Deflator. These factors, which are displayed in the table, were applied to the historical nominal 

values to convert annual damages prevented to 2013 prices.

The information from the Corps of Engineers indicate that over the historical period of record, 

Shasta Dam & Reservoir, Folsom Dam & Reservoir, New Melones Dam & Reservoir, and Friant 

Dam & Reservoir have prevented approximately $29 billion, $33 billion, $525 million, and $525 

million in damages, respectively. A total of approximately $63 billion in damages have been 

prevented by these dams/reservoirs combined. 

Table 5-9. Annual Flood Damages Prevented by Dam/Reservoir ($1,000s) – Nominal and 2013 

Price Level

Year

Shasta

(Nominal)

Folsom

(Nominal)

New 

Melones

(Nominal)

Friant

(Nominal)

Value Index 

Adjustment

Shasta

(2013 

Price 

Level)

Folsom

(2013 

Price 

Level)

New 

Melones

(2013 

Price 

Level)

Friant

(2013 

Price 

Level)

1952 0 -- -- -- 7.122 0 -- -- --

1953 0 -- -- -- 7.035 0 -- -- --

1954 0 -- -- -- 6.970 0 -- -- --

1955 105,000 -- -- -- 6.853 719,614 -- -- --

1956 0 -- -- -- 6.627 0 -- -- --

1957 1,000 -- -- -- 6.414 6,414 -- -- --

1958 100,000 -- -- -- 6.272 627,246 -- -- --

1959 100,000 -- -- -- 6.186 618,602 -- -- --
Economic Benefits Analysis Appendix | 49

Year

Shasta

(Nominal)

Folsom

(Nominal)

New 

Melones

(Nominal)

Friant

(Nominal)

Value Index 

Adjustment

Shasta

(2013 

Price 

Level)

Folsom

(2013 

Price 

Level)

New 

Melones

(2013 

Price 

Level)

Friant

(2013 

Price 

Level)

1960 0 -- -- -- 6.101 0 -- -- --

1961 194,000 -- -- -- 6.035 1,170,823 -- -- --

1962 0 -- -- -- 5.962 0 -- -- --

1963 200,000 -- -- -- 5.895 1,179,049 -- -- --

1964 0 -- -- -- 5.806 0 -- -- --

1965 150,000 -- -- -- 5.702 855,303 -- -- --

1966 0 -- -- -- 5.546 0 -- -- --

1967 10,000 -- -- -- 5.390 53,895 -- -- --

1968 0 110 -- -- 5.170 0 569 -- --

1969 12,000 0 -- -- 4.927 59,123 0 -- --

1970 100,000 6 -- -- 4.680 468,007 28 -- --

1971 0 0 -- -- 4.454 0 0 -- --

1972 0 0 -- -- 4.269 0 0 -- --

1973 0 0 -- -- 4.048 0 0 -- --

1974 80,000 0 -- -- 3.714 297,104 0 -- --

1975 0 0 -- -- 3.400 0 0 -- --

1976 0 0 -- -- 3.223 0 0 -- --

1977 0 0 -- -- 3.035 0 0 -- --

1978 55,000 0 2 -- 2.837 156,012 0 6 --

1979 0 0 0 -- 2.619 0 0 0 --

1980 120,000 5 298 -- 2.402 288,286 12 716 --

1981 0 0 0 -- 2.197 0 0 0 --

1982 130,000 7 13,000 -- 2.069 268,966 14 26,897 --

1983 2,801,000 900 12,700 23,690 1.991 5,576,216 1,792 25,283 47,162

1984 40,000 0 0 0 1.922 76,896 0 0 0
50 | Central Valley Project Final Cost Allocation Study

Year

Shasta

(Nominal)

Folsom

(Nominal)

New 

Melones

(Nominal)

Friant

(Nominal)

Value Index 

Adjustment

Shasta

(2013 

Price 

Level)

Folsom

(2013 

Price 

Level)

New 

Melones

(2013 

Price 

Level)

Friant

(2013 

Price 

Level)

1985 0 0 0 0 1.863 0 0 0 0

1986 3,116,000 6,488,100 102,500 33,190 1.826 5,689,243 11,846,078 187,146 60,599

1987 0 0 0 0 1.781 0 0 0 0

1988 0 0 0 0 1.720 0 0 0 0

1989 0 0 0 0 1.656 0 0 0 0

1990 0 0 0 0 1.597 0 0 0 0

1991 0 0 0 0 1.545 0 0 0 0

1992 0 0 0 0 1.511 0 0 0 0

1993 0 0 0 0 1.476 0 0 0 0

1994 0 0 0 0 1.445 0 0 0 0

1995 3,499,000 5,700 2,100 54,310 1.415 4,952,651 8,068 2,972 76,873

1996 0 0 2,400 0 1.390 0 0 3,336 0

1997 4,267,000 15,194,472 175,770 3,320 1.367 5,831,689 20,766,215 240,224 4,537

1998 12,229 900 8,030 28,630 1.352 16,534 1,217 10,857 38,709

1999 0 3,190 2,670 15,390 1.333 0 4,252 3,559 20,515

2000 8,350 0 470 36,200 1.303 10,883 0 613 47,182

2001 0 0 0 11,750 1.274 0 0 0 14,971

2002 6,690 0 0 4,420 1.255 8,395 0 0 5,546

2003 13,140 0 0 21,270 1.230 16,167 0 0 26,170

2004 28,610 0 0 4,470 1.198 34,261 0 0 5,353

2005 0 0 1,750 64,440 1.160 0 0 2,031 74,769

2006 11,550 90,910 18,740 72,530 1.126 13,001 102,332 21,095 81,643

2007 0 0 0 0 1.097 0 0 0 0

2008 0 0 0 0 1.075 0 0 0 0

2009 1,818 0 370 9,678 1.067 1,940 0 395 10,329
Economic Benefits Analysis Appendix | 51

Year

Shasta

(Nominal)

Folsom

(Nominal)

New 

Melones

(Nominal)

Friant

(Nominal)

Value Index 

Adjustment

Shasta

(2013 

Price 

Level)

Folsom

(2013 

Price 

Level)

New 

Melones

(2013 

Price 

Level)

Friant

(2013 

Price 

Level)

2010 0 0 0 10,284 1.055 0 0 0 10,845

Total 15,162,387 21,784,300 340,800 393,572 -- 28,996,323 32,730,577 525,129 525,203

5.4 Summary of Flood Control Benefits

Damages Prevented. The damages prevented totals from Table 5-1 were divided by the number of 

years of record, per dam/reservoir, to derive an average annual damages prevented value. For 

example, the total damages prevented for Shasta Dam & Reservoir over the entire period of record 

for that reservoir (1952 to 2010) is approximately $29.0 billion (2013 dollars). This value was then 

divided by 59 (the number of years in the period of record for Shasta Dam) to derive an average 

annual flood damages prevented value of approximately $491.5 million; note that the period of 

record for each dam/reservoir varies. Table 5-2 displays the average annual damages prevented 

values for each dam/reservoir.

Table 5-10. Average Annual Damages Prevented by Dam/Reservoir (2013 dollars)

Shasta Dam & 

Reservoir

Folsom Dam & 

Reservoir

New Melones Dam 

& Reservoir

Friant Dam & 

Reservoir

$491,463,000 $761,176,000 $15,913,000 $18,757,000

Average annual damages prevented for each dam/reservoir were then used to calculate the 

present value of future benefits over the 100-year period of analysis using a discount rate of 

3.25%. The present value formula is: 

PV = present value 

PMT = payment (benefits) per period 

i = discount rate 

n = number of payment periods 

The present value of a future stream of payments (benefits) for each dam/reservoir was calculated

using the average annual damages prevented values displayed in Table 5-2. Table 5-3 shows the total 

benefits for each dam/reservoir. Using the USACE damages prevented information, total flood 
52 | Central Valley Project Final Cost Allocation Study

control benefits over the 100-year period of analysis for all facilities are estimated to be 

approximately $38.0 billion.

Table 5-11. Total Benefits1 over 100-Year Period of Analysis (2013 dollars)

Shasta Dam & 

Reservoir

Folsom Dam & 

Reservoir

New Melones 

Dam & 

Reservoir

Friant Dam & 

Reservoir Total

$14,504,492,000 $22,464,503,000 $469,638,000 $553,581,000 $37,992,214,000

1. 100-Year Period of Analysis, using 3.25% Discount Rate
Economic Benefits Analysis Appendix | 53

Chapter 6. Hydropower 

This chapter describes the methodology used to estimate economic benefits attributed to CVP 

hydropower generation and results of the analysis. The estimation of hydropower benefits was 

coordinated with the Western Area Power Administration (WAPA) and CVP energy generation was 

estimated using output from CalSim 2 and LTGEN models (see Hydrological Modeling Appendix for 

more details). Attachment 1 (Economic Benefits Analytical Tool Descriptions) and Attachment 2 (Forecast of 

Economic Value of CVP Power 2014-2113) to this Economic Benefits Analysis Appendix describe the 

PLEXOS model and application of the model to estimate CVP hydropower benefits, respectively. 

Background, methodology, and results are described below. 

6.1 Background

CVP hydropower benefits were estimated for energy, ancillary services, and planning 

capacity/resource adequacy components, generally described below: 

6.1.1 Energy

The California Energy Commission (CEC) defines energy as “the capacity for doing work.” Forms 

of energy include thermal, mechanical, electrical, and chemical. For hydropower, energy is in the 

form of electrical generation that is produced when water runs through the hydro-electric turbines. 

Traditionally, hydropower plant operators have strived to maximize on-peak generation, (i.e., 

generation provided during the peak load hours as defined by the North American Energy Standards 

Board (NAESB)). In the case of CVP, since hydropower is generated only when reservoir releases 

are made to meet higher priority purposes as flood control, water supply, and environmental 

regulatory needs, hydropower is not optimized for its maximal value of electricity generation, but 

only suboptimal for electricity generation within the context of the daily water release schedule. This 

study, therefore, estimated the value of CVP hydropower generation subject to given constraints due 

to hydrology, project consumption, and regulatory operations or COA requirements which may 

change the timing, value, and quantity of CVP hydropower available for sale. The results of the 

study are estimates because the constraints used by the model are a simplified representation of the 

complex reality of operational and regulatory requirements. 

The study is based on the contemporary fact that the value of CVP generation is realized through 

the local organized electricity market operated by the CAISO. The value of the CVP generation to a 

wholesale CVP customer is assessed and realized by the CAISO wholesale electricity market price. 

The CAISO market prices are determined by locational marginal prices. A locational marginal price 

is usually the highest bid price accepted by the market at a given location. A wholesale electricity 

consumer can simply go to the CAISO wholesale electricity market to purchase the electricity if the 

CVP generation is priced higher than the CAISO locational marginal prices. Therefore, the study 

evaluates CVP generation values using the locational marginal prices simulated by the PLEXOS 

model. In calculating the locational marginal prices, it was determined that since the CVP 

hydropower generation represented a very small amount of the total generation output available to 

the California market, it was decided that a with-and without-CVP analysis was not necessary. As a 
54 | Central Valley Project Final Cost Allocation Study

result, the value of CVP hydropower was estimated using the simulated CAISO’s hourly day-ahead 

price (i.e., market prices) as a proxy to represent the marginal value of the hydropower generation. 

This is the streamlined approach referenced later in Section 6.2 of this appendix.

The calculated locational marginal prices are based on assumptions of certain resource mixes that 

represent a snapshot in time, for example the 33 percent renewable portfolio standard (RPS). In 

recent years as the amount of renewable generation from wind and solar resources have increased

from the imposition of the mandatory RPS, it has resulted in the creation of surplus capacity and 

generation during certain hours of the day, and consequently resulted in the displacement of 

generation from traditional sources such as natural gas, nuclear, and hydropower. Simultaneously, 

energy demands have leveled and increased at lower rates as a result of increased energy use 

efficiencies, distributed generation resources and lower than expected population growth rates. 

As the renewable generation from wind and solar resources has increased, there may be more value 

in the future energy and ancillary markets if CVP generation can be dispatched to fully utilize the 

fast-ramping capability of a hydro generator. The value of such benefits, however, are not 

sufficiently realized now and may be constrained by water operations, environmental regulations, 

contractual constraints/limitations, and the governing Power Marketing Plan.

6.1.2 Ancillary Services

The CEC defines ancillary services as “services other than scheduled energy that are required to 

maintain system reliability and meet Western Electricity Coordinating Council/North American 

Electric Reliability Corporation operating criteria. Such services include spinning, non-spinning, and 

replacement reserves, voltage control, and black start capability.” Hydropower can be particularly 

valuable at providing regulation-up and regulation-down ancillary services because hydro generation 

can be ramped up (regulation-up) or down (regulation-down) quickly to allow the grid operator to 

precisely match generation to load, especially when wind and solar generation fluctuates 

unexpectedly. When ancillary services are bid into the market, it is common that they are not called 

upon. A generating entity is paid for providing ancillary service capacity into the market and then 

paid for the energy, if generation is actually called upon in connection with the bid. 

6.1.3 Planning Capacity/Resource Adequacy

The CEC defines capacity as “the amount of electric power for which a generating unit, generating 

station, or other electrical apparatus is rated either by the user or manufacturer.” Capacity is valuable 

because of the need for sufficient machine capability to meet the peak electrical load hour during the 

hottest summer day. Flexible capacity is becoming more valuable as California continues to increase 

the proportion of renewable energy (other than large hydro) required to meet total energy 

demanded. Because renewables have resulted in creating a significant amount of excess capacity in 

California, estimating a value for capacity, especially where the CAISO does not run a capacity 

market can be problematic. Resource Adequacy (RA) is a mandatory planning and procurement 

process to ensure resources are secured by Load Serving Entities to meet CAISO’s forecast system, 

local, and flexible capacity needs.
Economic Benefits Analysis Appendix | 55

6.2 Methodology

The power benefit analysis for the CAS is based on a streamlined approach to estimate benefits of 

CVP hydropower based on simulated market prices. A proof-of-concept test was implemented to 

validate a streamlined approach, which confirmed the hypothesis that electricity market prices withand without-CVP conditions are not significantly different, thus allowing a market-price approach. 

The annual value of energy, ancillary services, and planning capacity/resource adequacy hydropower 

benefits evaluated for the CAS was composed of as follows: 

• Energy – Forecasted California Independent System Operator (CAISO) hourly day-ahead

market prices for energy from PLEXOS model (see Attachment 1 - Economic Benefits

Analytical Tool Descriptions, for description of PLEXOS model),

• Ancillary Services – Forecasted CAISO hourly day-ahead market prices for ancillary

services from PLEXOS model, and

• Planning Capacity/Resource Adequacy – Claimed RA by CVP Preference Power

Customers to meet demand/load growth considerations by applying CAISO market prices.

The PLEXOS Integrated Energy Model (PLEXOS) is a power market simulation model used to 

evaluate CVP power accomplishments and benefits. The PLEXOS Model (described in Attachment 

1 – Economic Benefits Analytical Tool Descriptions) was used to estimate energy and ancillary service 

benefits (see Attachment 2 – Forecast of Economic Value of CVP Power 2014-2113), while planning 

capacity/resource adequacy was estimated as the avoided cost of RA that is currently claimed by 

some CVP preference power customers. 

The PLEXOS model was selected for use in the CVP CAS based on a variety of factors including 

(but not limited to) its relative ability to accurately simulate different future scenarios given specific 

constraints, as well as its widespread usage in the power industry. PLEXOS simulates power markets 

by optimizing energy, ancillary services, generation, and transmission utilization subject to physical 

and operational constraints. Two simulations were run to determine CVP power benefits. The first 

covered the entire Western Electricity Coordinating Council’s (WECC) system to generate projected 

pricing and ancillary services data, including CVP facilities. A subsequent simulation optimized the 

dispatch of the CVP facilities using the projected pricing and ancillary services data generated in the 

first simulation. The simulated generation data is a 2024 baseline year used to calculate annual 

benefits across the period of analysis used in the study. See Attachment 2 – Forecast of Economic Value 

of CVP Power 2014-2113 for more detailed documentation of the analysis used to estimate energy 

and ancillary services. 

The energy component of CVP hydropower benefits was adjusted in relation to two factors 

discussed below: 1) estimated generator flood bypass, and 2) San Luis Unit pump-generating unit. In 

addition, valuation of planning capacity/resource adequacy is described below. 
56 | Central Valley Project Final Cost Allocation Study

6.2.1 Energy Benefit Adjustment for Estimated Generator Flood Bypass

The LTGEN model estimates monthly generation at a given hydropower facility based on 

generation capacity, monthly storage, and total monthly release1. Output from LTGEN (i.e., total 

monthly generation) and facility data (i.e., minimum and maximum generation) were inputted to 

PLEXOS to develop constraints during the second PLEXOS simulation to estimate power benefits 

given the estimated locational market prices in the first simulation. After the PLEXOS CVP benefit 

simulation was completed, it was determined that the version of the LTGEN model used to develop 

inputs to the PLEXOS model overestimated generation when compared to the historical generation 

levels due to underestimation of generator flood bypasses. This overestimation was identified based 

on a separate analysis where the LTGEN modeled generation developed with historical water record 

inputs exceeded the actual historical generation due to missed (underestimated) flood bypass. 

Because monthly generator constraints were estimated using the version of LTGEN subject to 

underestimation of generator flood bypass and input into PLEXOS, the simulated 2024 baseline 

year utilizes overestimated generation leading to inflated power benefits.

A post-production methodology was developed to isolate the missed flood bypass from LTGEN to 

adjust the power benefits estimated by PLEXOS. This post-process adjustment of LTGEN and 

PLEXOS results was performed for the energy component of the power benefits in the CAS. The 

methodology consisted of isolating flood bypass using hourly data (acquired from Reclamation’s 

Central Valley Operations Office) of operations at Trinity, Folsom, Shasta, Keswick, and Nimbus 

reservoirs2. These are the main CVP facilities which experience flood bypass operations and thus 

contributed to the over-calculation in LTGEN. A comparison was made between the total bypass 

and the amount of remaining available capacity at each facility on an hourly timestep to generate an 

hourly time-series of flood bypass. This newly generated time-series data was aggregated to a 

monthly time-step for compatibility with the LTGEN model. This data was then subtracted from 

the LTGEN predicted spill and multiplied by the monthly efficiency factor to produce a prediction 

of overestimated generation due to missed flood bypass. 

Logarithmic regression analyses were then developed to map the historical data to the respective 

CalSim 2 data. Estimated generation from LTGEN was regressed on the Sacramento Valley 

Hydrological Classification Index3

 for the adjusted and unadjusted numbers. The difference in the 

regression lines was summarized by water year type to estimate the average percentage CVP 

generation overestimated due to missed flood bypass by water year type. The result of this analysis 

provides the adjustment factor applied to estimated generation by water year type, which is reported 

in Table 6-1. 

1 See the Hydropower Purpose section of the Hydrological Modeling Appendix for more information about the LTGEN 

model. 

2 In coordination with the Central Valley Operations Office, historical data from 2009 – 2017 water years were chosen 

due to consistency with historical and simulated operations, constraints on the availability of hourly data, and variability 

in water year types over the time period. 3 The Sacramento Valley Hydrological Classification Index (Sac Index) is computed annually by the California 

Department of Water Resources to determine the water year type. The regression used the computed index value for 

each water year incorporated into the analysis. Sac index values are publicly available on DWR’s website. 
Economic Benefits Analysis Appendix | 57

Table 6-1. Percent Reduction of Energy Component of Power Benefit Energy Results by Water 

Year Type

Wet

Above 

Normal

Below 

Normal Dry Critical

Percent Reduction for 

Energy Generation 

Benefits

3.74% 3.27% 2.71% 2.37% 0.74%

Table 2 of Attachment 2 displays the 2024 simulated energy sales and associated energy revenue by 

water year type as estimated by the PLEXOS model. By dividing the total energy revenue by energy 

sales, average unit prices by water year type were estimated. These unit prices range from $39/MWh 

in wet years to $43/MWh in critical years. The quantity of energy generation by water year type was 

then reduced by the respective percentage reported in Table 6-1. This reduction in generation was 

subsequently multiplied by the respective unit price. The resulting reduction in energy value 

(revenue) by water year type was weighted by the water year distribution to calculate an annual 

average reduction in energy value accounting for missed flood bypass. Table 6-2 reports the power 

benefits after implementation of the adjustment4.

6.2.2 Energy Benefit Adjustment for the San Luis Unit Pump-Generating Unit 

The San Luis Unit is part of both the Federal CVP and the California SWP. Authorized by the San 

Luis Act in June 1960 (Public Law 86-488), it is jointly operated by Reclamation and the DWR 

primarily for the purpose of water supply. Two features of the San Luis Unit are pump-generating 

(“pump-gen”) plants – the O’Neill Pump-Generating Plant and the William R. Gianelli PumpGenerating Plant. These two facilities pump water into the O’Neill Forebay and San Luis Reservoir 

respectively, for off-stream storage. During water operations, water is either released for delivery 

from O’Neill Forebay into the Delta Mendota Canal or from San Luis Reservoir back through the 

pump-turbines of both facilities to generate reclaimed energy. The reclaimed energy helps offset 

part, but not all of the cost of pumping water into San Luis Reservoir. Because the energy required 

to pump water into the reservoir is greater than the energy generated when the water is released for 

delivery, all of the energy generated by these pump-gen plants is considered to be an offset to the 

cost of pumping. 

Accordingly, the total cost of both pump-gen plants, as well as the value of the energy generated by 

them, was assigned to the water supply purpose. As a result, it was necessary to adjust (reduce) the 

energy power benefits modeled in PLEXOS by the value of generation produced by the pump-gen 

plants and add that value to the water supply benefits. The relative proportion of generation at the 

San Luis Unit was calculated by dividing the annual energy generated by the San Luis Unit minus 

transmission losses by the total annual CVP energy generated minus transmission losses. 

Specifically, the adjustment factor used to adjust hydropower benefits is calculated by the following 

equation: 

4 See Table 2 of Attachment 2 (Forecast of Economic Value of CVP Power 2014-2113) for the results of the power benefits 

analysis prior to the application of the adjustment to account for underestimated generator flood bypass.
58 | Central Valley Project Final Cost Allocation Study

AAAAAAAAAAAAAAAAAAAA FFFFFF FFFF (%) = 11 − AAAAAAAA AA SS LL LL UU GG −SS LL LL UU TT LL

TT AAAAAAAA AA CCCCCC GG −TT TT LL

The adjustment factor (0.975) was multiplied by the estimated annual energy generation benefits

prior to calculating the discounted net present value over the planning horizon. The adjustment 

factor did not affect the benefits attributed to ancillary services or RA. 

6.2.3 Planning Capacity/Resource Adequacy

Planning capacity/resource adequacy was estimated as the avoided cost of RA that is currently 

claimed by some CVP preference customers. This is different from the planning capacity benefits 

described in Attachment 2 (Forecast of Economic Value of CVP Power 2014-2113).

Although WAPA only markets two non-firm variable products, energy and ancillary services, some 

of WAPA’s customers claim their CVP allocation for capacity purposes, thus avoiding certain 

CAISO costs related to short-term operational requirements to ensure grid reliability. These grid 

reliability requirements are referred to as RA. Using the CAISO market value for RA is considered 

to be representative of the actual value that WAPA preference power customers are realizing when 

claiming CVP capacity benefits. A CAISO market-based price for RA was used as a proxy for that 

value now and for the foreseeable future, since its value is calibrated to the amount of capacity 

present in the existing and predicted future system. 

As referenced in Table 3 of Attachment 2 (Forecast of Economic Value of CVP Power 2014-2113), CVP 

Preference Customers claim 635 MW of capacity to meet their RA commitment. The 635 MW is 

dispersed among the Sacramento Municipal Utility District (308 MW), Northern California Power 

Agency (229 MW), and City of Redding (98 MW). The capacity amounts are directly stated in 2014 

California Energy Commission (CEC) filings titled “Electric Resource Planning Form S-1” for each 

utility, which are publicly available on the CEC website. The values reported for each utility are the 

peak month capacity claimed in 2014.

The economic value of RA is based on the peak month capacity to account for avoided cost and 

willingness to pay similar to single purpose alternative facility sizing. For example, if a single purpose 

power plant to provide RA were built, it would be sized to handle the peak month value so the 

facility could provide the claimed capacity when needed. For the purposes of this CVP CAS, this 

capacity is being considered as an avoided cost to be claimed as additional benefits. The value of RA 

varies due to heterogeneous seasonal demand throughout the year. To model RA, an average price 

of $2.21/kw-month was determined using WAPA’s RA purchases during 2009-2013. The total value 

for RA is then: 

(635,000 kw) x (12 months) x ($2.21/kw-month) = $16.8 million/year
Economic Benefits Analysis Appendix | 59

6.3 Results

The estimated energy and ancillary service CVP power benefits are shown in Table 6-2, and 

estimated total hydropower benefits are shown in Table 6-3. As discussed above, the benefit values 

used in the CAS for the power purpose are the values of CVP energy generated without the San Luis 

Unit. The value of energy generated by the O’Neill and Gianelli pump-generating plants was 

subtracted from the estimated hydropower benefit and added to the estimated water supply benefit. 

In addition (shown in Table 6-3), the estimated capacity/resource adequacy value ($16.8 million) was 

added and total hydropower benefits (without San Luis Unit) and benefits are estimated to be nearly 

$193.9 million annually, on average.

Table 6-2. Estimated Annual CVP Hydropower Energy and Ancillary Benefits, by Water 

Year Type ($millions)

Power 

Component Wet

Above 

Normal

Below 

Normal Dry Critical

Weighted 

Average

Energy $228.1 $201.5 $170.6 $155.1 $115.4 $181.1

Ancillary Services $0.7 $0.5 $0.4 $0.4 $0.5 $0.5

Total $228.7 $202.1 $171.0 $155.5 $116.0 $181.6

Table 6-3. Estimated Annual Total CVP Hydropower Benefits ($millions)

Benefit Amount

CVP Hydropower Energy and Ancillary Service Benefit (with San Luis Unit) $181.6

Less: San Luis Unit Energy Benefit (Water Supply Cost Saving Benefit) $4.5

CVP Hydropower Energy and Ancillary Service Benefit $177.1

Plus: CVP Capacity (Resource Adequacy) Benefit $16.8 

Total Estimated Annual CVP Hydropower Benefit $193.9
60 | Central Valley Project Final Cost Allocation Study

This page intentionally left blank. 
Economic Benefits Analysis Appendix | 61

References

Beattie, B. R., and C. R. Taylor. 1985. The Economics of Production. New York: Wiley and Sons. 

California Energy Commission (CEC). 2014. California Energy Demand 2014–2024 Final Forecast 

Volume 1: Statewide Electricity Demand, End‐User Natural Gas, Demand, and Energy 

Efficiency. Staff report. CEC‐200‐2013‐004‐V1‐CMF. January. Available at: 

http://www.energy.ca.gov/2013publications/CEC-200-2013-004/CEC-200-2013-004-V1-

CMF.pdf 

California Department of Food & Agriculture (CDFA). 2016. California Agricultural Statistics 

Review, 2015-2016.

Draper, A. J., M. W. Jenkins, K. W. Kirby, J. R. Lund, and R. E. Howitt. 2003. EconomicEngineering Optimization for California Water Management. Journal of Water Resources Planning 

and Management 129: 3.

Howitt, R. E. 1995a. Positive Mathematical Programming. American Journal of Agricultural Economics 

77(2): 329-342.

Howitt, R. E., D. MacEwan, and J. Medellín-Azuara. 2009a. Economic Impacts of Reduction in 

Delta Exports on Central Valley Agriculture. Agricultural and Resource Economics Update. Pp. 1-4. 

Giannini Foundation of Agricultural Economics.

Howitt, R. E., J. Medellín-Azuara, and D. MacEwan. 2009b.Estimating Economic Impacts of Agricultural 

Yield Related Changes. Prepared for California Energy Commission, Public Interest Energy 

Research (PIER).

Howitt, R. E, J. Medellín-Azuara, D. MacEwan, and J. R. Lund. 2012. Calibrating Disaggregate 

Economic Models of Agricultural Production and Water Management. Environmental Modeling and 

Software 38: 244-258.

Lund, J., E. Hanak, W. Fleenor, R. Howitt, J. Mount, and P. Moyle. 2007. Envisioning Futures for the 

Sacramento-San Joaquin Delta. Public Policy Institute of California. 

Reclamation (Bureau of Reclamation). 2012. Statewide Agricultural Production (SWAP) Model 

Update and Application to Federal Feasibility Analysis.

Reclamation and USFWS (Bureau of Reclamation and U.S. Fish and Wildlife Service). 1999. Central 

Valley Project Improvement Act Programmatic Environmental Impact Statement. 

Raftelis Financial Consultants, Inc. and California-Nevada Section of the American Water Works 

Association. 2015. 2013 Water Rate Survey. Accessed 20 March 2017 from http://ca-nvawwa.org/canv/downloads/2015/CANVRateSurvey2013.pdf 
62 | Central Valley Project Final Cost Allocation Study

State of California, Department of Water Resources (CA DWR). September 2010. Least Cost 

Planning Simulation Model. Sacramento, CA. 

http://www.water.ca.gov/economics/downloads/Models/LCPSIM_Model_Ray.pdf

U.S. Bureau of Reclamation (Reclamation). 2013. Central Valley Project Schedule of M&I Contract 

and Cost of Service Water Rates Per Acre-foot by Contractor, 2013 M&I Water Rates. Accessed 

20 March 2017 from 

https://www.usbr.gov/mp/cvpwaterrates/ratebooks/mi/2013/2013_mi_sch_a-1.pdf

U.S. Bureau of Reclamation (Reclamation). 2015. Draft Coordinated Long Term Operation of the 

CVP and SWP Environmental Impact Statement (LTO EIS) Environmental Consequence 

Analysis, Appendix 19A – California Water Economics Spreadsheet Tool (CWEST) 

Documentation. Sacramento, CA.
RECLAMATION 

Managing Water in the West 

•

•

•

•

•

•

•

Attachment 1 - Economic Benefits Analytical Tool Descriptions 

CVP Cost Allocation Study 

November 19, 2013 

Description of Analytical Tools 

Name 

Statewide Agricultural Production Model (SWAP) 

Availability of Technical Support 

A summary of SWAP documentation is available on SWAP web site: 

http://swap.ucdavis.edu/ 

Categories

Optimization of crop acreage 

Main Features and Capabilities 

Yearly time step 

Spatial scale (27 regions comprising the Central Valley of California 

based on local hydrology and DWR's Detailed Analysis Units (DAU) 

SWAP considers 20 crops 

SWAP projects future cropping patterns, land use, and water use by 

considering land and water availability and their costs, market conditions, 

and production costs. 

The model selects those crops, acreage and water supplies that maximize 

profit subject to certain constraints. 

Constraints include availability of land, labor, water and supplies. 

SWAP uses Positive Mathematical Programming (PMP) technique to 

incorporate both marginal and average economic conditions when 

maximizing profit. 

Applications

SWAP is an extended and improved version of Central Valley Production Model 

(CVPM). The older CVPM has already been applied in the past Water Plan 

Updates to forecast future crop acreage for the of the Central Valley regions. 

Though the current SWAP has not yet been used to forecast future crop acreage, 

but it has been tested with past historical data for the purpose of calibration and 

verification. 

Calibration/Validation/Sensitivity Analysis 

Calibration refers to the calculation of some model parameters in such a way that 

the model will predict a given set of target data. The SWAP is calibrated against 

irrigated acreage by crop and by region. 

U.S. Department of the Interior 

Bureau of Reclamation 
Attachment 1 - Economic Benefits Analytical Tool Descriptions 

An innovation in the SWAP model over the CVPM model and related PMP 

models is the use of exponential cost functions. The exponential form of the cost 

function has several advantages over the more frequently specified quadratic cost 

function. The most important practical advantage is that the exponential cost 

function is better able to fit a desired elasticity of supply without forcing the 

marginal cost of production of the initial unit to assume unrealistic values. 

Peer Review 

Although PMP technique has been published in refereed journals, no official 

Review of SWAP has been conducted. 

Anatomy of SWAP 

Conceptual Basis 

Conceptually, SWAP is an agricultural crop acreage model that simulates the 

decisions of agricultural producers (farmers) on a regional level based on 

principles of economic optimization. The model assumes that farmers maximize 

profit subject to resource, technical, and market constraints. Farmers sell and buy 

in technical and institutional constraints. 

Theoretical Basis 

Traditional optimization models such as linear programming rely on data based 

on observed average conditions (e.g., average production costs, yields, and 

prices), which are expressed as fixed coefficients. As a result, these models tend 

to select crops with highest average returns until resources (land, water, and 

capital) are exhausted. The predicted crop mix is therefore less diverse than 

observed in reality. The most widespread reason for diversity of crop mix is the 

underlying diversity in growing conditions and market conditions. Simply put, 

any crop-producing region includes a broad range of production conditions. All 

farms and plots of land do not produce under the same, average set of conditions. 

Therefore, the marginal cost and revenue curves do not coincide with average cost 

and revenue curves. To account for crop diversity, SWAP has been formulated on 

the basis of marginal (incremental) conditions. 

Numerical Basis 

Numerical basis of SWAP is a technique called Positive Mathematical 

Programming (PMP) which incorporates both marginal and average conditions. In 

the conventional case of diminishing economic returns, productivity declines as 

output increases. Therefore, the marginal cost of producing another unit of crop 

increases as production increases and the marginal cost exceeds the average cost. 

The PMP technique uses this idea to reproduce the variety of crops observed in 

the data. Several possible or combined reasons for crop diversity are: diverse 

growing conditions that cause variation in production costs or yield; crop 

diversity to manage and reduce risk; and constraints in marketing or processing 

capacity. SWAP assumes that the diversity of crop mix is caused by factors that 

can be represented as increasing marginal production cost for each crop at a 

regional level. For example, SWAP costs per acre increase for cotton farmers as 
Attachment 1 - Economic Benefits Analytical Tool Descriptions 

they expand production onto more acreage. The PMP approach used in SWAP 

uses empirical information on acreage responses and shadow prices—implicit 

prices of resources—based on standard linear programming techniques and a 

calibration period data set. The acreage response coefficients and shadow prices 

are used to calculate parameters of a quadratic cost function that is consistent with 

economic theory. The calibrated model will then predict exactly the original 

calibration data set, and can be used to predict impacts of specified policy changes 

such as changes in water supplies. 

Input and Output 

Main categories of inputs and outputs in SWAP are as follows. Inputs: (Water 

supply by source, Crop unit water use (ETAW), Ag water use efficiency, Crop 

production function, Crop yield, Crop demand information, Crop price, Cost of 

water, Cost of groundwater pumping (energy cost), groundwater pumping depths 

and lifts, Farm policy) Outputs: (Crop acreage by region, Ag water use by region, 

Crop revenues, Producers profit, Consumers surplus) 

Data Management 

All input and output data are stored locally. Some of SWAP input data are based 

on field and market information (e.g. crop yield, Ag water use efficiency, crop 

prices, and cost of water). Other inputs come from the result of other models like 

CALSIM to provide information on amount water supply available for Ag from 

SWP and CVP projects. 

Software 

SWAP operates using the General Algebraic Modeling System (GAMS) software. 

GAMS software is available from GAMS Development Corp., 1217 Potomac 

Street, N.W., Washington, and D.C 20007, U.S.A. This software is available for 

Window based personal computers and a variety of workstations or larger 

computers. The SWAP code is public domain and portable across all of these 

platforms. 
•

•

•

•

•

•

•

•

•

•

Attachment 1 - Economic Benefits Analytical Tool Descriptions 

Figure 1. SWAP Coverage of Agriculture in California 

20 Proxy Crops used in SWAP Model 

Almonds 

Alfalfa Hay 

Corn 

Cotton, Upland and/or Pima 

Summer Squash/Squash 

Dry Beans 

Fresh Tomatoes 

Wheat 

Onions 

Walnuts 
•

•

•

•

•

•

•

•

•

Attachment 1 - Economic Benefits Analytical Tool Descriptions 

Sudan Grass, Hay 

Broccoli 

Pasture 

Potato 

Processing Tomatoes 

Rice 

Safflower 

Sugar Beets 

Oranges, Navel and/or Valencia 

Vineyards, Grapes Wine, Table Grapes, Raisin Grapes 
 

RECLAMATION 

Managing Water in the West 

Attachment 1 - Economic Benefits Analytical Tool Descriptions 

CVP Cost Allocation Study 

November 19, 2013 

Description of Analytical Tools 

Name 

Least-Cost Planning SIMulation model (LCPSIM) 

Author 

California Department of Water Resources (Ray Hoagland, Division of Planning 

and Local Assistance) 

Categories

Economic optimization, urban water system simulation 

Main Features and Capabilities 

• Spatial scale at hydrologic region/planning area. 

• Simulation runs through a hydrologic sequence of supplies and rainfallcorrelated demands at a specified level of future demand (e.g., 2020) on a 

yearly time step. 

• Reliability enhancement options are adopted based cost minimization ($ 

per thousand acre-feet) and include long-run demand reduction and supply 

augmentation measures, such as toilet retrofit and wastewater recycling, to 

reduce frequency, magnitude, and duration of shortage events. 

• Cost of reliability enhancement (thousands of $) expressed as a function 

of the level of adoption of reliability enhancement options (thousands of 

acre-feet). 

• Shortage contingency measures such as water transfers (based on 

minimizing cost among transfer options) and shortage allocation by water 

use category in the region/planning area (residential, commercial, 

industrial, and large landscaping); are used for shortage management. 

• Expected economic losses (thousands of $) are produced by an economic 

loss function which uses the percentage size of shortage (foregone use) 

events generated by the simulation as well as the percentage size of each 

water use category. 

• Demand hardening is computed as a function of the level of use of 

demand reduction measures and used to adjust expected economic losses. 

• Cost of unreliability (thousands of $) is expressed as a function of the

level of adoption of reliability enhancement options (thousands of acrefeet) and includes expected economic losses as well as the expected costs 

of shortage contingency measures. 

U.S. Department of the Interior 

Bureau of Reclamation 
Attachment 1 - Economic Benefits Analytical Tool Descriptions 

• Reliability management cost (thousands of $) includes the cost of 

reliability enhancement, the cost of unreliability, and the cost of carryover 

storage operations, conveyance, treatment, and distribution. 

• The least-cost reliability management plan is identified by minimizing 

reliability management cost expressed as a function of reliability 

enhancement. 

• Operations of carryover storage facilities available to the region/planning 

area (including ground water banking) are used for reliability management 

in LCPSIM. 

• Priority-based objective, mass balance-constrained linear programming is 

used to operate carryover storage facilities and balance (to the extent 

possible) available supplies with demands on a yearly basis. 

• The State Water Project is treated as the residual source of supply: SWP 

supply quantities available for delivery to the region/planning area which 

are unusable and unstorable in any year of the simulation are identified. 

Applications

The model has been applied to the San Francisco Bay and South Coast hydrologic 

regions at the 2020 level of demand to determine the regional economic benefit 

value of additional State Water Project deliveries. 

Calibration/Validation/Sensitivity Analysis 

Validation of LCPSIM has not been performed due to lack of comparable 

historical data available for a region to check against model results and the fact 

that LCPSIM was designed as a normative rather that a positive (predictive) 

model. Verification is being performed in a peer review process (see below). 

Sensitivity analysis, which does not require actual historical data, can be 

performed independently of calibration/validation to test the sensitivity of model 

results against key input parameters. Limited sensitivity analyses have been part 

of the peer review process. 

Peer Review 

Members of the Bay-Delta Authority Common Assumptions Economics 

Workgroup has been involved in reviewing and suggesting modifications to 

LCPSIM since mid-July of 2004. This work was completed in 2005. 

Anatomy of LCPSIM 

Conceptual Basis 

Conceptually, the primary objective of LCPSIM is to develop an economically 

efficient regional water management plan based on the principle of least-cost 

planning. At the least complex level, LCPSIM evaluates the effect of the 

availability of additional imported water supplies on the net value of adopting 

regional long-run water management options such as recycling or toilet retrofit 

programs and on costs and losses associated with shortage events. At a more 

complex level, LCPSIM evaluates the availability and use of contingency 
Attachment 1 - Economic Benefits Analytical Tool Descriptions 

strategies to mitigate the economic impacts of shortage events, such as short-term 

water market transfers, use of supplies from carryover storage (conjunctive use), 

and water allocation programs. These strategies can affect the economically 

efficient level of adoption of the long-term water management measures. 

Conversely, the level of adoption of long-term measures can influence the 

effectiveness of the contingency management strategies and, therefore, their use. 

Annual Regional

Water Balance

(Foregone Use 

Amount,

Frequency, and 

Duration)

Regional 

Contingency

Management

Capabilities & 

Strategies

Adopted LongTerm Regional

Water 

Management

Options

Annual Regional 

Water Balance 

(Foregone Use 

Amount, 

Frequency, and 

Duration) 

Regional 

Contingency 

Management 

Capabilities & 

Strategies 

Adopted LongTerm Regional 

Water 

Management 

Options 

Figure above depicts the primary planning interrelationships important for 

evaluating, from a least-cost perspective, the cost of alternative plans to increase 

the reliability of a hypothetical water service system. The link between the 

investment in long-term water management options and the size and frequency of 

shortages is shown, as is the link between shortage contingency management 

strategies and the costs and losses associated with foregone use: a greater 

investment in the ability to manage shortages will lessen the economic costs and 

losses due to foregone use when they occur. 

Theoretical Basis 

The theoretical basis of LSPSIM is to minimize the total cost of reliability 

management, the sum of two costs: cost of unreliability and the cost of reliability 

enhancement, recognizing that the former is inversely related to the latter. 

The cost of unreliability is most directly measured by forgone use. Foregone use 

occurs when residential users or businesses, for example, have established a 

lifestyle or a level of economic production based on an expected level of water 
~ G) 

> w 

G) 

Cl 

~ 0 

.r. 

"' E 

,g 

1/1 

G) 

1/1 

1/1 

0 

-I 

,, 

C 

cu 

1/1 

-1/1 

0 

0 

s 

• 0 

0 

C 

:::, 

a: 

• Cl 

C 

.3 

Reliability Enhancement 

Reliability Enhancement 

Attachment 1 - Economic Benefits Analytical Tool Descriptions 

supply available for use and that expectation is not realized (i.e., a “shortage 

event”) in a particular year or sequence of years. 

Figure below illustrates the expected decrease in the costs and losses associated 

with foregone use as water management options are adopted to enhance 

reliability. This enhancement may be obtained from either supply augmentation 

or demand reduction options. 

The next figure shows incremental effect of enhancing reliability on long-run 

water management costs. The assumption is made that options will be adopted in 

an order inversely related to their unit cost, including any associated treatment 

and distribution costs: the least expensive options are expected to be adopted 

first. 
Attachment 1 - Economic Benefits Analytical Tool Descriptions 

When the information from the two Figures above is combined, it results in a total 

cost tied to the level of reliability enhancement as shown in the following figure: 

Reliability Enhancement 

Total Costs 

Costs and Losses from Shortage Events 

Reliability Enhancement Costs 

Least-Cost Point 

The least-cost point represents the economically efficient plan, that is, it is the 

level of reliability enhancement beyond which it is economically less costly, 

compared to the cost of additional reliability enhancement, to accept the expected 

costs and losses from foregone use. Conversely, at any level of enhancement less 

than this, compared to the expected costs and losses from foregone use, it is less 

costly to enhance reliability. This solution is the least-cost reliability management 

plan. 

Numerical Basis 

In LCPSIM, a priority-based objective, mass balance-constrained linear 

programming solution is used to simulate regional water management operations 

on a yearly time-step, including the operation of surface and groundwater 

carryover storage capacity assumed to be available to the region/planning area. 

The system operations context allows the evaluation of the reliability contribution 

of additional regional long-term reliability enhancement options, including 

increased carryover storage capacity, to account for any synergistic interactions 

between options. The cost of adding those measures is determined using a 

quadratic-programming algorithm which minimizes the cost of each incremental 

addition. The sum of the cost of unreliability (which decreases) and the cost of 

the adoption of the reliability enhancement options (which increases) is mapped 

against the increasing level of use of those reliability enhancement options and a 

polynomial smoothing function is fitted. The polynomial function is then solved 

for the least-cost reliability management plan. 
I r:::::::::::::::::::::::::::::::::::::::::::::::::J r::::::::::::::::::::::::::::::::::::::::::::::::J I 

I 11~- L+ ~-n-d] 

Attachment 1 - Economic Benefits Analytical Tool Descriptions 

Input and Output 

Figure below shows the general types of both the Input data required by LCPSIM 

and the resulting Output information generated by the model. 

Annual

Regional

Base Use

Base Regional G round

and Surface

Carryover Storage

Regional Reliability

Management Options

Shortage

Management

Market

Transfer

Options

Annual

Regional

Base Supplies

LCPSIM

Foregone Use-Related

Costs & L osses

Total Regional Costs and Losses

Regional Long-Term

Reliability

Augmentation Cost

Market Transfer

Costs

Water Balance 

Logic

Foregone Use 

Cost Logic

Annual 

Regional 

Base Use 

Base Regional Ground 

and Surface 

Carryover Storage 

Regional Reliability 

Management Options 

Shortage 

Management 

Market 

Transfer 

Options 

Annual 

Regional 

Base Supplies 

LCPSIM 

Foregone Use-Related 

Costs & Losses 

Total Regional Costs and Losses 

Regional Long-Term 

Reliability 

Augmentation Cost 

Market Transfer 

Costs 

Water Balance 

Logic 

Foregone Use 

Cost Logic 

Data Management 

LCPSIM was developed to use CALSIM II output as its primary data source. 

Excel© VBA macros are used to extract time series delivery data from CALSIM 

II DSS files and store them as the ASCII files used by LCPSIM. Data on other 

regional deliveries available as time-series data are also stored as ASCII files. All 

system operations and regional options parameters used by the model are stored 

as ASCII files. Results from the model are exported in Excel® file format. 

Excel® VBA macros are available for interfacing LCPSIM results with CALAG 

shadow values to calculate the net value of “excess” urban supplies made 

available for agricultural use in wet and above normal years and transfers from 

agricultural use to urban use in dry and critical years. All input and output data 

are stored locally. 

Software 

LCPSIM software runs on Windows 95® and above and is designed to be datadriven in order to represent different water service systems without changing the 

model code. The semi-self-documenting source code is written in the Delphi® 

language (formerly, Borland Object Pascal) with an emphasis on modularity to 

facilitate extending the model, if needed. Compiling the source code requires 

Version 6 (or greater) of the Borland Delphi® Integrated Development 

Environment. A Windows® help file is callable from the program (a users’ 
Attachment 1 - Economic Benefits Analytical Tool Descriptions 

manual is not yet available). To run, LCPSIM requires either a proprietary 

quadratic programming solver DLL from Frontier Systems (very fast) or a free 

quadratic programming solver DLL developed by Csaba Mészáros at the MTA 

SZTAKI, Computer and Automation Research Institute, Hungarian Academy of 

Sciences, Budapest, Hungary (much slower). Licensed Delphi® IDE users can 

also freely distribute the Visual Components Formula One® ActiveX component 

required by LCPSIM. 
Attachment 1 - Economic Benefits Analytical Tool Descriptions 

CVP Cost Allocation Study 

Description of Analytical Tools 

Name 

Other Municipal Water Economics Model (OMWEM) 

Author 

California Department of Water Resources and U.S. Bureau of Reclamation 

Categories 

Statistical demand function 

Main Features and Capabilities 

• The model includes CVP M&I supplies north of Delta, SWP and CVP 

supplies to the Central Valley and the Central Coast, and SWP supplies or 

supply exchanges to the desert regions east of LCPSIM’s South Coast 

region. 

• The model estimates the economic value of M&I supply changes in these 

areas as the change in cost of shortages and alternative supplies (such as 

groundwater pumping or transfers). 

• Data from the available 2005 Urban Water Management Plans were used 

to estimate 2025 water demand and supplies for an average condition and 

a dry condition, and to identify additional water supply options and their 

costs. 

• For a water supply scenario, OMWEM uses water deliveries, defined as 

the percent of SWP Table A or percent of CVP municipal contract by 

year. 

• SWP and CVP water deliveries are provided by CALSIM II. 

• If supply is insufficient to meet demand in years categorized as having 

below normal, above normal or wet water supply, the model calculates the 

cost of additional water supplies. 

• If the water supply year is categorized as dry or critical, the model allows 

for shortfalls to be managed with dry/critical supply sources and with end-
Attachment 1 - Economic Benefits Analytical Tool Descriptions 

user shortage. The shortage costs are estimated using a constant of 

elasticity demand function. 

Applications 

The model has undergone several recent updates. OMWEM now includes 2009 

and 2025 development conditions. This work, reflected in the discussion above, 

improves the demand/supply input. The model does not include the full level of 

detail that may exist in local water providers’ plans. Results are useful for 

comparing alternatives and to provide an approximate estimate of avoided cost. 

They should not be viewed as precise representations of individual water 

providers’ costs or options. 

Calibration/Validation/Sensitivity Analysis 

The model has been updated to include the effect of real energy cost increases on 

water prices. The rate of increase in real water costs is assumed to be the same as 

the rate of increase in electricity prices. The annual rate of increase is 

approximately 1.3 percent. Generally, OMWEM has the same limitations as 

LCPSIM. In addition, decision rules about water supply costs and shortage are 

relatively simplistic. The areas included in OMWEM could be modeled in a 

LCPSIM framework. A variety of updates are being considered, primarily 

involving demands and water supply costs under recent conditions. A number of 

relatively small M&I water providers receive SWP or CVP water but are not 

covered by LCPSIM. 

Software 

The Other Municipal Water Economics model (OMWEM) is a set of compiled 

(individual) Excel-based spreadsheet application. 
RECLAMATION 

Managing Water in the West 

•

•

•

•

•

•

Attachment 1 - Economic Benefits Analytical Tool Descriptions 

CVP Cost Allocation Study 

November 19, 2013 

Description of Analytical Tools 

Name 

PLEXOS® Integrated Energy Model 

Author/Developer

Glenn Drayton, Ph.D./Energy Exemplar LLC 

Category 

Power market simulation model used to evaluate CVP power accomplishments 

and benefits 

Main Features and Capabilities 

• Weekly, hourly or sub-hourly time steps 

• Spatial scale – California’s power grid, but with the capability of 

simulating the power dispatch in the entire Western Interconnection 

• Using the monthly water operations and constraints simulated in the

CalSim2 model as input parameters to PLEXOS, simulates hourly 

dispatch of CVP power features to meet load and reserve requirements 

while respecting electrical transmission and generation constraints in order 

to depict on-peak and off-peak generation and the provision of ancillary 

services in such a way as to accurately reflect the current and future 

operations of the CVP power features 

• Values CVP generation attributes by modeling the power markets 

operated by the California Independent System Operator (CAISO) under 

current and year 2020 conditions when California’s mandate requiring 

33% of electricity used to serve load be produced from renewable 

resources will be fully implemented 

Applications

PLEXOS is widely used for the following purposes: 

Price Forecasting 

Power Market Simulation and Analysis 

Detailed Operational Planning and Optimization of Power Plants and Grid 

Trading and Strategic Decision Support 

Generation and Transmission Capacity Expansion Planning (Investment 

Analysis) 

Renewable Integration Analysis 

U.S. Department of the Interior 

Bureau of Reclamation 
•

•

•

•

Attachment 1 - Economic Benefits Analytical Tool Descriptions 

Co-optimization of Ancillary Services and Energy Dispatch 

Transmission Analysis and Congestion Management 

Portfolio Optimization and Valuation 

Risk Management and Stochastic Optimization 

PLEXOS’ unique capability to model hydro generation in a dynamic manner 

considering the numerous regulatory and institutional constraints imposed on the 

hydro system makes it the ideal transmission-constrained power production model 

to evaluate hydropower operations and benefits. In addition to the work on the 

CVP Cost Allocation Study, Reclamation has contracted with Energy Exemplar to 

use the PLEXOS model to evaluate net power benefits of enlarging Shasta Dam, 

constructing Sites Off-stream Storage Reservoir with a daily pump-back operation 

and constructing Temperance Flat Reservoir upstream of Millerton Lake 

considering the impact to the Kerckhoff Power Project. 

Calibration/Validation/Sensitivity Analysis 

PLEXOS results have been validated in a number of settings including the 2012 

Long-Term Procurement Plan (LTPP) process, which is under the purview of the 

California Public Utility Commission (CPUC). Every two years, the CPUC holds 

an LTPP proceeding to review and adopt ten-year procurement plans for 

California’s Investor-Owned Utilities (IOUs). The LTPP evaluates the utilities’ 

need for new resources and establishes rules for rate recovery of procurement 

transactions1

. For the 2012 LTPP, the CPUC requested that the California ISO 

conduct a system operational flexibility modeling study. The PLEXOS model 

was used to perform this study for the California ISO to study the status of 

CAISO’s power system in the year 20222. The results of the 2012 LTPP study 

have been used to inform PLEXOS modeling for Reclamation’s storage studies 

and will be used in the CVP Cost Allocation Study’s power benefits evaluation. 

PLEXOS is a very flexible modeling tool, which is ideally suited to perform such 

sensitivity analyses such as looking at impacts on power benefits resulting from 

various forecasts of natural gas prices, different hydro conditions, variations in 

electric load forecasts, evolving cap and trade market assumptions, etc. 

Peer Review 

The 2012 LTPP study reflects the inputs from multiple resources and has been 

reviewed by multiple stakeholders in the California power sector, as shown in 

Figure 1. WECC’s Transmission Expansion Planning Policy Committee (TEPPC) 

oversees and maintains a public database for production cost and related analysis3

. 

In the 2012 LTPP study, the latest TEPPC 2022 base case, along with the 2012 

WECC Loads and Resources Subcommittee (LRS)’s report, were used for the 

1 See http://www.cpuc.ca.gov/PUC/energy/Procurement/LTPP/index_2012.htm 2 See

http://www.caiso.com/informed/Pages/StakeholderProcesses/RenewableIntegrationMarketPro

ductReviewPhase2.aspx

3 See https://www.wecc.biz/committees/BOD/TEPPC/Pages/TEPPC_Home.aspx
2010 LTPP 

Study Group 5 

Assumptions 

- ----~ 

TEPPC 2022 PC1 

Case& WECC 

2012 LRS Report 

ISO Operation 

Data 

- -

CPUC RPS 

Calculator 

2012 Llif?~ 

~--· mg)(_Q$-.~ -~ 

Model 

~ 

Additional CPUC 

and CEC Inputs 

CPUC Scenario 

Toolv5 

CEC 2012 IEPR & 

2013 IEPR 

Preliminary 

ISO Master 

Generating 

Capability List 

Attachment 1 - Economic Benefits Analytical Tool Descriptions 

majority of the assumptions. The assumptions within California were further 

updated with CPUC’s inputs from 2010 LTPP assumptions, Renewable Portfolio 

Standards (RPS), and scenario selection tool; with California Energy Commission 

(CEC)’s inputs on load forecast from Integrated Energy Policy Report (IEPR) and 

natural gas price forecast; with California ISO’s inputs on generator data and 

operation data, etc. 

Description of PLEXOS Software 

The energy and ancillary service co-optimization is the basis of the PLEXOS 

algorithm. The PLEXOS Mixed Integer Programming Algorithm (MIP) in 

SCUC/ED (Security Constrained Unit Commitment/Economic Dispatch) 

produces the optimal decision on the generation and reserve provisions from each 

generator to meet the system energy demand and reserve requirements. 

Figure 1. Source of LTPP Assumptions from Multiple Resources 

Source: R.12-03-014: LTPP Track II Workshop – Operating Flexibility Modeling 

Results 
 

 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

Forecast of Economic Value of CVP Power 2014-2113 

Consultants’ Report – Energy Exemplar LLC and Pinnacle Consulting LLC 

March 2, 2017 

Methodology Overview 

The Central Valley Project (CVP) power benefits for this analysis are based on the principles 

and methodology specified by the Bureau of Reclamation (Reclamation) over the course of the 

study and documented in Appendix A. 

The three power components to be evaluated include: (a) energy; (b) ancillary services (AS); 

and, (c) planning capacity. The economic analysis is performed from a “national perspective 

rather than from the effects to a particular locality or regional standpoint.” Therefore, the 

analysis does not represent a utility or Northern California perspective, but a societal 

perspective. The market price is based on marginal production costs rather than average costs. 

and the economic analysis is based on a period of 100 years. The 100-year period for this 

study is 2014 through 2113 as the Cost Allocation Study (CAS) base year is 2013. 

2 3 

1 

This is the same methodology used by Reclamation in the Shasta Lake Water Resources 

Investigation and the North-of-Delta Offstream Storage Investigation. The specific 

methodology, tools, assumptions, results, and conclusions are described in the following 

sections. 

1 Ibid. 

2 Ibid. 

3 Ibid., p. 5. 

1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

Energy and Ancillary Services Derivation 

The energy and ancillary services valuation is based on a forecast of the marginal cost of 

production (i.e. incremental costs) in the future. A sophisticated production-costing software 

tool, PLEXOS, is used for this analysis because it has the unique capability of simultaneously 

optimizing energy, ancillary services, generation, and transmission utilization.4 

The energy and ancillary-services price forecast is then utilized to forecast the value of CVP 

power in the future. The steps involved in developing this forecast can be summarized as 

follows: 

1. Develop WECC production-costing database

2. Forecast WECC hourly energy and ancillary-service prices

3. Extract hourly Northern California prices

4. Develop CVP representation in PLEXOS

5. Forecast CVP energy and ancillary-service revenue

Each of these tasks will be summarized below: 

Develop WECC production-costing database – This is a very time-consuming activity that 

incorporates the input of all major Western Electric Coordinating Council (WECC) utilities, as 

well as regional, federal, and state planning and regulatory agencies. Due to complexity and 

cost to develop, the WECC-wide production costing database is produced only for a single year 

(10 years in the future) and is produced every other year. WECC coordinates this effort under 

the direction of its Transmission Expansion Planning Policy Committee (TEPPC).5 

This WECC (i.e. TEPPC) database contains the most comprehensive and well-vetted set of 

assumptions available for WECC. The TEPPC database is converted into production-costing 

input data for various models including PLEXOS and is used for WECC-wide transmission and 

other regional studies. At the time this study was initiated, the 2014 TEPPC database 

represented the latest set of assumptions available from WECC and projects values for the year 

2024.. 

6 

As in any database, there are many key assumptions that drive the results of the study. A 

summary of a few key assumptions from the 2014 TEPPC database is contained in Appendices 

A and B. 

Forecast WECC hourly energy and ancillary-service prices – Once the WECC database has 

been developed, energy and AS prices can be derived on an hourly basis for various regional 

locations. These prices represent the incremental cost to provide an additional MWh of energy 

or MW-hour of ancillary services in that location. These prices reflect the generation mix in the 

region as well as the cost of imports and transmission and other major operational constraints. 

Due to modeling complexity and time constraints, only a limited number of ancillary-service 

prices are forecast. These included regulation, spin, and non-spin. 

4 

For more information regarding the model PLEXOS, please refer to www.energyexemplar.com. 

5 See https://www.wecc.biz/TEPPC/Pages/Default.aspx. 

6 The PLEXOS dataset used to determine regional energy and AS prices is from the 2014 LTPP study 

without any modification. For additional information see CPUC May 14, 2014 Assigned Commissioner’s

Ruling, 13-12-2010). This dataset rep resents the “Trajectory Scenario” which is 33 percent renewable

and little change in existing policies. 

2 
 

 

 

 

 

 

 

 

 

 

Table 1 

CVP Modeled Hydropower Stations 

Plant Name Capacity (MW) 

Trinity 139.4 

Carr 154 

Spring Creek 189.1 

Shasta 715 

Keswick 105 

Folsom 207.7 

Nimbus 16 

New Melones 380 

Gianelli 191.3 

O’Neill 8.6 

Total 2,103.1 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

Extract hourly Northern California prices – The WECC modeling described in the previous task 

provides energy and ancillary-service prices for 20 to 30 different regions in WECC, including 

Northern California. The Northern California hourly energy, regulation, spin, and non-spin 

prices are extracted from the 2024 WECC database and used in the CVP evaluation analysis. 

Develop CVP representation in PLEXOS – Once the hourly prices are available and input into 

PLEXOS, the next step is to develop a representation of the CVP in PLEXOS. PLEXOS has a 

wide spectrum of options for modeling the CVP, ranging from a single unit with constraints, to 

modeling it as multiple units with extensive detailed constraints including water-flow limitations 

and time-associated requirements (i.e. “cascading waterway and storage”).

For the purposes of this study, CVP is modeled with the power stations summarized in Table 1. 

The Gianelli and O’Neill plants are modeled as pumping-generating stations, which are 

optimized with a 58.82% efficiency. 

The hydropower plants (or stations) summarized in Table 1 are modeled as distinct and 

separate resources with the following characteristics, many of which vary monthly: 

 Minimum generation

 Maximum generation

 Total energy7 

 Must-run energy

 Dispatchable energy

 Ramp-up rate8 

7 The total monthly energy equals the sum of the must-run and dispatchable energy. Must-run energy is 

often used to meet minimum water outflow requirements. 8 The ability of a plant to go from minimum to maximum generation in terms of MW/hour. Although 

PLEXOS has the capability to include multiple ramp rates for a given plant, in this study only a single 

ramp rate was used. The plants were generally assumed to be able to go from minimum to maximum 

3 
 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

 Ramp-down rate 

 Maximum hourly regulation-up and regulation-down sales 

The minimum, maximum, and total monthly energy amounts by plant were developed outside of 

PLEXOS and were input as constraints. These monthly values were developed by Reclamation 

and the California Department of Water Resources (CDWR) professionals using the CalSim

and LTGEN models. 10

9 

Two zones were then modeled in PLEXOS. The first zone represented the Northern California 

market. The second zone represented CVP and its resource capability. Exports from the CVP 

zone to the “market” zone incurred a $14/MWh wheeling rate to reflect the current cost of 

wheeling from CVP to the California Independent System Operator (CAISO) market. 12 

11 

Forecast CVP energy and ancillary service revenue -- In this application, the objective function 

of the PLEXOS model is to maximize the CVP net revenue from energy and ancillary services, 

subject to constraints. If the model did not have any CVP constraints, the model would move 

unlimited energy and ancillary services into the super-peak period where it has the most value. 

However, due to the constraints, the energy and ancillary services are spread out over the day 

and month, and therefore, more limited in terms of revenue potential. 

The PLEXOS 2024 energy and ancillary-service results are summarized in Table 2 for various 

hydrological conditions.13 

generation in about ten minutes (same from ramp-down). Thus, ramp rates were not a constraint in this 

particular study. 

9 For a description of the CalSim model, see 

http://baydeltaoffice.water.ca.gov/modeling/hydrology/CalSim/Documentation/CalsimManual.pdf. 

For a description of the LTGen model, see Section 2, “Overview of Analytical Approach”, 

https://www.usbr.gov/mp/SSJBasinStudy/documents/02_sec1-4.pdf.. 11 2013 dollars. 

12 The wheeling rate to CVP members is $0/MWh. Since all exports are modeled to incur the $14/MWh 

rate, the CVP energy value is understated with respect to its value to CVP customers in this analysis. 

This wheeling assumption was made in order to reduce the complexity of the study.

13 The analysis was originally done using 2014 dollars. These values have been deflated to 2013 dollars 

using the GDP implicit price deflator. 

4 

10 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

Table 2 

2024 CVP Energy and Ancillary-Service Sales and Revenue14 

(2013 $) 

Parameter Wet Above 

Average 

Average Dry Critical Weighted 

Average 

Energy Sales 

(GWh/year) 

6,048 5,180 4,216 3,806 2,728 4,606 

AS Sales (GW-hour) 1,044 1,047 1,049 1,049 1,048 1,047 

Energy Rev. (mil. $) 237 208 175 159 116 187 

AS Rev. (mil. $) 0.7 0.5 0.4 0.4 0.5 0.5 

Total Rev. (mil. $) 238 209 176 159 117 187 

The information below summarizes the various Northern California hydrological conditions for 

the water-years 1921-2003 that were used for estimating both water deliveries and power 

production and are categorized as follows:15 

 Wet – 28 years 

 Above normal – 13 years 

 Below normal – 17 years 

 Dry – 21 years 

 Critical – 13 years 

 Total – 92 years 

The annual energy sales are a function of the monthly energy amounts derived outside of 

PLEXOS and input into the model. Except during relatively rare “dump” conditions, all CVP 

energy would be sold into the market at the prevailing price.16 

In 2024, CVP ancillary-service sales are not forecast in PLEXOS to be particularly significant. 

This is a consequence of limitations placed on CVP in terms of ancillary-service capability and 

sales and the relatively low price compared to energy sales. The ancillary-service sales that are 

made are solely regulation. 

The third row contains the forecast annual energy revenue for the various hydrological 

conditions. These amounts vary from $116 to $236 million depending on the amount of 

14 All ancillary sales modeled in this analysis are regulation, since the regulation price is higher and CVP 

is assumed to have limited AS production capability.

15 Email dated Oct. 28, 2016 from N. Parker (USBR) to S. McBride and E. Toolson 16 “Dump” conditions occur when the total minimum generation of the online resources exceeds the 

system load for a specific location and additional exports are not feasible. In PLEXOS, the market price 

of power during these dump conditions is input as a negative $100/MWh. Therefore, CVP would only 

generate during dump conditions due to “must-run” constraints, such as minimum instream water flows. 

In 2024, these dump conditions were calculated from the WECC runs to occur only about 100 hours per 

year. 

5 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

hydropower available. The average annual energy sales price also varies from 40 to 43 $/MWh 

depending on hydrological conditions.17 

The ancillary-service revenue is not significant in these cases. The average annual ancillaryservice price for all five of the hydrological cases summarized in Table 2 is less than $1. That 

figure is consistent with the recent CAISO market where the average annual ancillary-service 

price for the period 2011-2015 is considerably less than $1/MW-hour.18 In fact, for the last three 

years, the average annual AS cost for all services is less than $0.30/MW-hr. Since the AS 

revenue is relatively insignificant, the total revenue for each water-year type is very similar to the 

total energy revenue. CVP energy production and sales are clearly the driver of hydropower 

benefits in these results. 

A critical assumption in the derivation of the CVP energy revenue is the 2024 Northern 

California natural gas price. The gas price has a direct bearing on California market in over half 

of all hours. As summarized in Appendix A, the Northern California (i.e. PG&E burner-tip) gas 

price assumed in the development of the WECC LTPP cases is $4.30/MMBtu. 

Some of the participants in the study have questioned whether this is an appropriate 

assumption for 2024 or if the forecast gas price should be closer to $2.50/MMBtu (the 

approximate price earlier in the summer of 2016). This issue is discussed in Appendix C, 

Natural Gas Price Assumption.19 

The recommended annual energy revenue forecast for the 100-year period is contained in the 

Conclusion to this report. 

17 This average annual energy price in 2024 (in 2014$) of $40-$43/MWh compares favorably with the 

price of WAPA power sold in 2014 which averaged $48/MWh, presentation made by Dr. Tong Wu, WAPA 

entitled “Western Experience of Marketing CVP Generation”, slide 9 entitled “Summary: CVP Power 

Products and 2014 Market Value”.

CAISO “market report”, Figure E.5 “Ancillary service cost as a percentage of wholesale energy cost”, 

http://www.caiso.com/Documents/2015AnnualReportonMarketIssuesandPerformance.pdf. 

19 Several study participants have requested information regarding the impact of lower gas prices. If the 

2024 gas price was assumed to be $2.50/MMBtu instead of the $4.30/MMBTU utilized in the study, the 

energy revenue in Table 8 could decrease about 20 percent. This figure is an approximation. No WECC 

simulations were performed with the lower gas price since this assumption was not assumed to be valid 

for the 100-year forecast period. 

6 

18 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

Capacity Derivation20 

Capacity is only used once in the generation of energy and is used to provide either energy or 

ancillary services. However, capacity that is available for only the next day (short term) has a 

much different value than capacity that is available for the next 100 years (long term). It is the 

long-term value of this planning capacity that needs to be estimated for the purpose of this 

analysis. 

A simple example might better explain this concept. Assume that a person can go to the gas 

station today and fill the car with gas at approximately $2.50 a gallon. But it is unlikely that the 

same person will be able to find a gas station owner who would be willing to sign a contract that 

would allow the car to be filled at $2.50 a gallon for the next 100 years. The gasoline is only 

used in “real-time” in either case. But the long-term price guarantee is a valuable contract that 

is priced at a significant premium over the current-day price. 

This example illustrates the significant difference between a short-term (one-day) and a longterm (100-year) contract. In the end, both products deliver power in real-time, but the guarantee 

of freezing the long-term price at today’s values, carries a significant monetary premium. The 

same is true in any commodity market with a sustainable demand, including power. 

CVP member utilities are able to rely on this power, subject to contractual and physical 

restrictions, over the long-term. As a result of these long-term contractual guarantees, the 

capacity qualifies as “planning capacity” that can meet a utility’s future load and reserve 

obligations. 

The North American Electric Reliability Corporation (NERC) recommends a 15 percent 

“planning reserve margin” for predominately thermal systems and a 10 percent reserve margin 

for predominately hydro systems.21 Most utilities in the United States, except for a few hydrobased systems in the Northwest, plan for a 15 percent reserve margin. This NERC provision 

has been interpreted by the utilities in California to mean 15 percent planning reserve 

requirement as evidenced by their filings to the California Energy Commission (CEC), where the 

utilities demonstrate their ability to meet a 15 percent reserve margin.22 23 

The value of the long-term capacity available from CVP is the product of the amount available 

and the estimated market price of that capacity. These two subjects are addressed separately 

in the following two subsections. 

CVP Planning Capacity Amount -- In the most recent CEC filings (Capacity Resource 

Accounting Tables), CVP member utilities list the amount of CVP planning capacity they rely on 

20 Planning Reserve Margin – Defined by NERC as the “amount of generation capacity available to meet 

expected demand in planning horizon” North American Electric Reliability Council. 21 North American Electric Reliability Council (NERC), 

http://www.nerc.com/pa/RAPA/ri/Pages/PlanningReserveMargin.aspx. 22 SMUD and NCPA “Public S-1 supply forms 04-23-15”, table “Capacity Resource Accounting Table 

(CRAT). 

23 The California Public Utility Commission adopted a Resource Adequacy framework in 2004 to ensure 

the reliability of electric service in California.23 The concept of resource adequacy is much broader than 

the single index of planning reserve margin and includes policies, programs, and reliability assessments 

to accomplish its overall purpose. 

7 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

to meet their 15 percent planning reserve requirement. In Table 3, the available CVP planning 

capacity information for the largest six utility recipients is summarized. The capacity amount is 

derived from the public sources as footnoted below and the allocation was provided by Western 

Area Power Administration (WAPA).24 The capacity that the utility claims is available to meet 

their planning reserve margins is publically available for the SMUD, NCPA, and Redding, but 

not readily available for SVP, PWRPA, or Roseville (their hydro data are aggregated and not 

listed as separate resources).25 

From these data, it is straight-forward to extrapolate the total CVP planning capacity amount by 

dividing each utility’s CVP allocation by their relative percentages. This calculation is contained 

in the last column of Table 3. For SMUD and NCPA, the total CVP planning capacity is 

calculated to be about 1210 MW. For the City of Redding, the total amount is 1089 MW. The 

weighted amount for the three utilities for which data are available is 1190 MW. 

Table 3 

CVP 2024 Planning Capacity Amount 

Utility26 CVP Capacity (MW) CVP Percentage (%) Total CVP Capacity 

(MW) 

SMUD 308 25.454995 27 1210 MW 

NCPA 229 18.879611 28 1213 MW 

SVP n/a29 9.603401 

Redding 98 9.000850 30 1089 MW 

PWRPA n/a 7.279168 

Roseville n/a 4.853328 

Total 635 53.335456 31 1190 MW 

For purposes of this study, 1190 MW will be considered the total CVP planning capacity 

available for the years 2014 through 2113. 

CVP Planning Capacity Value -- The “CVP Power Benefits Methodology” approach states that

the forecast market prices be based on the “marginal production costs rather than average 

costs”.32 In other words, what does it cost for the next increment of demand to be produced and 

when is it needed. 

24 Email from R. Rieger of WAPA to S. McHale of USBR dated January 31, 2017. 

25 NCPA has expressed reservations regarding the capacity value recorded in their 2014 CEC submittal. 

However, no additional information has been received since the concern was expressed in a January 30, 

2017 meeting at USBR.

26 Utility abbreviations include Sacramento Municipal Utility District (SMUD), Northern California Power 

Agency (NCPA), Silicon Valley Power (SVP), Power and Water Resources Pooling Authority (PWRPA), 

27 SMUD 2014 CEC filing, Capacity Resource Accounting Table, Electric Resource Planning Form S-1, 

line 19-3. 

28 NCPA 2014 CEC filing, Capacity Resource Accounting Table, Electric Resource Planning Form S-1, 

line 19d. 

29 Data not available. SVP hydro is aggregated in 2014 CEC supply forms. 30 City of Redding 2014 CEC filing, Capacity Resource Accounting Table, Electric Resource Planning 

Form S-1, line 19d.

31 This is the total percentage of those utilities that have a corresponding CVP Capacity in Table 3. 32 See Section 1 of this paper. 

8 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

This is a difficult question since the California market currently has a substantial surplus of 

planning capacity. Additional difficult questions include: What type of capacity will be added to 

the system? Will the new capacity include traditional thermal resources (such as a combustion 

turbine or combined cycle)? Or will all of the new resources be renewables, storage, or other 

newer and more advanced technologies? And will these new renewable and storage resources 

earn sufficient revenue in markets other than long-term capacity (i.e. renewable and energy 

services) to effectively mitigate the need for a significant long-term capacity payment? 

At the time of this study, planning reserve margins throughout California were relatively high 

with little load growth projected for the foreseeable future. For example, the CAISO projected 

planning reserve margins in excess of 34% for the summer of 2014 – more than twice the 

required 15% amount.33 

By 2014, the type of new generating resources had changed from significantly from gas-fired to 

renewable. In 2013, the California Energy Commission records that 3,900 MW of new capacity 

become operational and 12% of that was considered renewable. By 2014, only 375 MW of new 

generating capacity was added and 100% was renewable. And for the year 2014, no new 

generating capacity was added in California.34 

Given this high level of uncertainty regarding the timing and type of future planning capacity, the 

following sensitivity analysis was developed and summarized in this report: 

Table 4 

Description of Capacity-Value Sensitivity Cases 

Case Description Planning Capacity Deficit 

Year 

Resource to Meet Capacity 

Deficiency 

CC in 2030 2030 Combined cycle 

CC in 2040 2040 Combined cycle 

CC in 2050 2050 Combined cycle 

No CC needed Never None 

The same methodology is applied to each of these four cases. The capacity value in the initial 

year of the study is the historical value recorded in the marketplace. Based on previous 

information received from SMUD short-term traders, this value is assumed to be $29/kw--yr in 

2013$.35 This value is considered to be constant in real terms from 2014 through 2020. 

The value in the year that the planning-capacity is projected to occur (2030, 2040, 2050, or 

never) is the fixed cost to build and operate the least-cost source of new capacity, minus the net 

33 California Independent System Operator (CAISO), 2014 Summer Loads and Resources Assessment, 

“Summer 2014 Supply and Demand Outlook (Planning Reserve Margins), Table 1, p. 6. 34 California Energy Commission, Energy Facility Status, 

http://www.energy.ca.gov/sitingcases/all_projects.html. 35 Based on conversations between E. Toolson and SMUD short-term traders over the last couple of 

years. This value is subject to updating, if more recent or documentable information becomes available. 

9 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

revenues expected from the marketplace.36 This value is assumed to be the same annually (in 

real dollars) throughout the remaining 100-year CVP economic analysis.37 

For the case in which new planning-reserve capacity is assumed to not be needed throughout 

the term of the study, the forward-looking fixed costs (net market revenues) of the most-recently 

built combined cycle units must still be recovered in the market or the units will be retired. 

The annual value of planning capacity in the interim years between current conditions and the 

first year of deficiency is subject to much speculation. For purposes of this study, it has been 

assumed that the current real market value will remain constant through 2020, when the value 

will escalate at a constant real rate until the assumed capacity deficiency year. 

The value of planning capacity for the deficit period is based on the least-cost resource able to 

provide this type of reserve. Generally, this resource has been assumed to be a combustion 

turbine (CT) or a combined cycle (CC) generating unit. The annual net costs for these two 

types of units in are summarized in Table 5. 

Table 5 

Net Costs for Combustion Turbine and Combined Cycle Units38 

(2013 $)39 

Parameter Units Combined Cycle Combustion 

Turbine 

Capacity MW 500 100 

Heat Rate40 Btu/KWh 7,100 9,300 

Financing Costs $/kw-yr 87.5 104.0 

Insurance $/kw-yr 6.6 7.9 

Ad Valorem41 $/kw-yr 8.7 10.4 

Fixed O&M $/kw-yr 43.0 34.1 

Taxes $/kw-yr 16.8 16.8 

Total Fixed Costs $/kw-yr 162.4 173.3 

Net Revenue $/kw-yr 38.9 35.2 

Net Fixed Costs $/kw-yr 123.5 138.1 

36 Net revenues are defined as the gross energy and ancillary-service revenue earned from the 

marketplace, minus the net costs of providing those services (i.e. variable fuel and O&M).

37 The assumption means no real escalation of capital and fixed operating costs and no real escalation or 

change to net revenue.

38 California Independent System Operator (CAISO), “2015 Annual Report On Market Issues and 

Performance”, http://www.caiso.com/Documents/2015AnnualReportonMarketIssuesandPerformance.pdf, 

p. 53-56.

39 These figures are originally in 2015 dollars and have been deflated to 2013 dollars using a multiplier of 

0.983. 

40 At maximum generating capacity. 41 An Ad Valorem is determined based on the value of the facility. 

10 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I I I I I I 

I I I I I I 

I I 

I I 

I I 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

Based on the information shown in Table 5, the net annual costs for a new combined cycle are 

about 10 percent lower than the comparable costs for a combustion turbine. Therefore, for 

purposes of this study, the net cost of a combined cycle will be used as the least-cost source of 

planning reserves once (or if) a planning capacity deficiency occurs. These costs will be valued 

at $124/kw-year in 2013 dollars.42 

On the other hand, if a planning-capacity surplus situation exists throughout the 100-year 

planning horizon, then recently-built combined cycle units need only meet their forward-looking 

operating costs. In this case, the net forward-looking fixed operating costs are $36/kw-year.43 

The specific market value assumptions for the four cases outlined in Table 4 are summarized in 

Table 6 below. As explained in the preceding paragraphs, the market value in 2014 is assumed 

to be $29/kw-yr (2013 $). This value remains constant in real dollars through 2020. Starting in 

2021, the capacity value is escalated at a constant real rate until new planning capacity is 

needed. 

Table 6 

Projected Annual Planning Capacity Costs for Alternative Cases 

(2013 $/kw-yr) 

Year CC in 2030 CC in 2040 CC in 2050 No CC 

2016 $29 $29 $29 $29 

2020 $29 $29 $29 $29 

2025 $60 $42 $37 $36 

2030 $124 $60 $47 $36 

2040 $124 $124 $77 $36 

2050 $124 $124 $124 436 

2100 $124 $124 $124 $36 

2113 $124 $124 $124 $36 

Levelized $91 $80 $71 $34 

The key values which are input into the table and drive the rest of the analysis are highlighted in 

turquoise. For example, in the first case, assuming that a new combined cycle is required in 

2030, the key input values are $29/kw-yr for 2016 and 2020, and the total forward-looking 

combined cycle costs of $124 in 2030. The other cases are similarly constructed. The 

remaining values in the table are derived from these key input values. 

The 100-year levelized value for the four cases are $91, $80, $71, and $34/kw-year 

respectively. The capacity value in the last case is much lower than the other three since it is 

based on two critical assumptions: (1) no future planning capacity is needed; and, (2) the net 

42 Rounded to the nearest $1/kw-yr. 43 The net forward-looking costs for a CC are $124/kw-yr as summarized in Table 5. If the unit is recently 

constructed, the financing costs can be avoided, and the cost is $124-$88 or $36/kw-yr in 2016 dollars. 

11 
 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

forward-looking costs of a CC are only $36/kw-yr.44 Appendix C contains the 100-year detailed 

calculations. 

The recommended capacity planning value is the “No CC” scenario and is contained in the 

Conclusion to this report. 

44 The $36/kw-year is equal to the total levelized CC cost of $124/kw-yr minus the financing cost of 

$88/kw-yr (see Table 5). 

12 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

Summary and Conclusion 

This analysis projects the value of the power produced by the Central Valley Project (CVP) over 

the 100-year period from 2014 through 2113. This study is based on two salient assumptions: 

 There is an efficient, transparent, and functioning energy, ancillary-services, and 

planning-capacity marketplace for that period. 

 The majority of new generation will need to recover all of its costs from the marketplace. 

For an existing unit, total cost is equal to fixed and variable operating costs. For a new unit, the 

total cost is equal to all construction costs plus fixed and variable operating costs. 

It is likely that many new generating units will be built in the next 100 years. Most will bring 

specific attributes in the generation mix including energy efficiency, renewable, storage, and 

very flexible power. It is uncertain, however, whether any new conventional thermal generation 

will be needed during this time period. That uncertainty makes this analysis more difficult. 

Projecting into the future, there are multiple current and potential energy products that may be 

bought and sold in the market, as utilities and system operators strive to meet their load 

requirements economically and reliably. Some of these market products are listed in Table 7. 

Table 7 

Current and Potential Products in the Electric Power Marketplace 

Product Included in Analysis Notes 

Planning capacity Yes Modeled outside of PLEXOS 

Energy Yes CVP has significant energyproduction flexibility 

constraints 

Regulation Yes CVP regulation-up and down 

limited to 60 MW in all hours 

Renewable credit No Not applicable for most of 

CVP 

Flexible capacity45 No CVP flexibility significantly 

limited 

Congestion revenue rights No Assumed not applicable to 

CVP 

The following assumptions and observations are critical in developing a recommended planning 

capacity value: 

1. New and existing resources will need to cover their existing and future costs with 

revenue from the marketplace as discussed previously in this paper. 

May not be a future market product, but a procurement requirement. Source: CAISO “Market and

Infrastructure Policy, Draft Final Proposal, July 26, 2012, 

https://www.caiso.com/Documents/DraftFinalProposal-FlexibleCapacityProcurement.pdf. 

13 

45 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

2. There will be new and significant future markets that are either not in existence 

today or are just developing. Government mandates create new markets. For 

example, California is considering a 50 percent renewable mandate by the year 2030.46 

This is a significant increase over the current Renewable Portfolio Standard (RPS) of 20 

percent by 2020. This potential mandate causes an increase in demand for renewable 

resources (thus causing the market price to increase). Even the existing value of 

renewable can be considerable. As an example, according to the Department of Energy 

(DOE), in those markets where a minimum level of renewable energy is required, 

Renewable Energy Credits (RECs) are currently as high as $60/MWh.47 

Another California mandate that will create demand and an associated market is energy 

storage. In October 2013, the California Public Utilities Commission (CPUC) approved a 

proposed mandate for 1,300 MW of energy storage to the California system by 2020.48 

With the increased variability and uncertainty of additional renewable resources, 

increased system flexibility will also be required.49 This variability has caused some 

system operators to define and establish a new market for “flexible capacity”.50 

The above paragraphs illustrate that new markets are being created for new system 

requirements. It is anticipated that if these markets provide significant revenue, newlybuilt resources will earn much of their future revenue from these new markets, thus 

requiring less revenue from a traditional planning reserve market. 

3. These new markets will reduce the capacity planning payment. The supply of 

existing and future resources that can provide renewable, storage, or very flexible 

capacity is quite limited. The demand for new resources that can provide one or more of 

these attributes is greater than the existing supply. This situation causes a twofold 

expectation: (1) the majority of new resources will provide one or more of these 

attributes; and, (2) the market prices paid for these attributes will be substantia due to 

the limited supply. Given this future market expectation, new resources can be expected 

to pay for their forward-looking fixed costs from these new markets, instead of relying 

primarily on a traditional planning capacity payment. This phenomenon is already 

observable in the California marketplace as massive cancellations of conventional 

46 Energy and Environmental Economics (E3) report entitled “Investigating a Higher Renewables Portfolio 

Standard in California, January 2014, p. 3.

47 US Department of Energy (DOE), “Energy Efficiency and Renewable Energy”, Compliance Markets for 

RECS, http://apps3.eere.energy.gov/greenpower/markets/certificates.shtml?page=5. 48 “California Passes Huge Grid Energy Storage Mandate”, Green Tech Media, Jeff st. John, October 17, 

2013. https://www.greentechmedia.com/articles/read/california-passes-huge-grid-energy-storagemandate, 49 “Evolution of Wholesale Electricity Market Design with Increasing Levels of Renewable Generation”, 

National Renewable Energy Laboratory, September 2014, p. 14/139.

50 Flexible capacity generally means energy resources which can ramp-up and ramp-down as quickly as 

needed, potentially starting up and shutting down multiple time a day. http://sustainableferc.org/caisosflexible-capacity-proposal-approved-by-ferc/. 

14 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

thermal projects in California have occurred and little or no new thermal plants being 

proposed.51 

4. The Central Valley Project will earn minimal revenue from these new markets. The 

value of CVP power in each of the markets is very limited. Large hydro projects are not 

considered to be renewable in California. Therefore, no renewable credit is available. 

Second, the CVP has very minimal storage capabilities. And third, the CVP is assumed 

to have very limited flexibility due to other competing project purposes such as water 

deliveries, fisheries, recreation, and others. 

Given that the CVP project has significant physical and contractual constraints and is limited in 

its ability to participate in these markets, we do not expect that the CVP revenues will be 

equivalent to those required to build a new generating unit. Therefore, we recommend the 

following forecast be used to value the CVP project over the period of 2014 through 2113. 

Table 8 

Recommended CVP Power Values for the Period of 2014 through 2113 

(2013 $) 52 

Product Levelized Present Value 

(mil. $) (mil. $) 

Planning capacity 41 1,202 

Energy 187 5,508 

Ancillary services 1 15 

Total 229 6,725 

The total levelized value of CVP power through the 100-year period is forecast to be 

approximately $230 million per year. The present-value of power over the same 100-year 

period is about $6.7 billion. Based on this analysis, energy production accounts for about 82 

percent of the total value. 

52 Values are rounded to two significant digits. 

15 

51 
 

 

 

 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

Appendix A 

Key Assumptions – 2014 TEPPC WECC Database 

(2014 $) 

 Model year – 2024 (in 2014 dollars) 

 WECC planning reserve margin – 22 percent 

 CA 2015-24-year energy load growth – 0.33 percent 

 CA 2014-24 resource additions – 7,500 MW (nameplate, mostly renewable) 

 PG&E burner-tip gas cost -- $4.30/MMBtu 

 CVP export wheeling rate -- $14/MWh 

 CA CO2 emission cost -- $23.27 per ton 

 CO2 wheeling adder 

o BPA to CA -- $2/MWh 

o Other NW or SW to CA -- $10/MWh 

 Nuclear resources – Diablo Canyon at 2240 MW 

16 
 

 

 

 

 

 

 

 

 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

Appendix B 

CVP-Specific Assumptions 

Summary of CVP Monthy Assumptions 

Must-Run Dispatchable 

Maximum Minimum Energy Energy Total Energy 

Month Capacity (MW) Capacity (MW) (GWh/mo) (GWh/mo) (GWh/mo) 

Jan 1551.7 46.5 239.2 26.6 265.7 

Feb 1620.9 49.5 228.4 25.4 253.8 

Mar 1685.5 44.7 239.2 26.6 265.8 

Apr 1729.3 45.0 275.5 30.6 306.1 

May 1733.1 52.0 381.4 42.4 423.8 

Jun 1710.8 69.7 413.1 45.9 459.0 

Jul 1655.8 84.9 498.6 55.4 554.0 

Aug 1564.2 63.9 398.3 44.3 442.6 

Sep 1498.2 48.6 284.2 31.6 315.8 

Oct 1462.7 40.1 207.3 23.0 230.3 

Nov 1461.6 45.2 191.0 21.2 212.2 

Dec 1490.4 41.8 192.8 21.4 214.2 

Average 

Total 

1597.0 

n/a 

52.7 

n/a 

295.8 

3549.1 

32.9 

394.3 

328.6 

3943.4 

 CVP ramp rates 

o Energy and ancillary-service ramp rates considered as non-binding constraints 

o CVP energy and ancillary-service production can ramp up minimum to maximum 

capacity within an hour 

o CVP energy and ancillary-service production can ramp down from maximum to 

minimum capacity with an hour 

 CVP regulation production 

o Same amount of regulation-up and regulation-down sold every hour 

o Limited each hour to 60 MW on a CVP wide basis 

17 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

NG Electricity Price 

14 ~------------------------------~ 

2% 

$6 

$4 

$2.75 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

Appendix C 

Natural Gas Cost Assumption 

As mentioned in the Energy Section of this report, this study assumed that the PG&E burner-tip 

natural gas price is $4.30/MMBtu in 2024 (in 2014 $). Some of the participants in this study 

believed that a 2016 current market price would be more appropriate and suggested using a 

price closer to $2.50/MMBtu. This appendix discusses the reasons for using the original 

$4.30/MMBtu assumption. 

1. Since the energy and AS revenue for 2024 are used to represent the entire 100-year 

period from 2014 through 2113, it is unlikely that there would be no real escalation in 

natural gas prices for this period. It is much more defendable to assume a long-term 

real escalation rate, even if it is very conservative. 

2. The $4.30/MMBtu natural gas price was derived through an extensive WECC regionwide process and reflects the best thinking of natural gas experts at that time. We are 

reluctant to start changing the 2014 WECC and LTPP assumptions individually without 

reviewing updates to the entire dataset. 

3. EIA pricing data on Natural Gas from 2002-2016 shows pricing was above $4.00 for 

80% of the time, indicating that $4.30 is a more appropriate assumption39. 

18 
Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

 

Appendix D 

Calculation of 100-Year Capacity Value 

Assumptions Value Units 

- first year 2014 year 

- real discount rate 3.25% percent 

- 2016 nominal value $29 $/kw-yr 2013$ 

- total CC cost $124 $/kw-yr 2013 $ 

- CC operating cost $36 37$/kw-yr 2013 $ 

- CVP Planning Capacity 1190 MW see Table 3 

esc. period 2020-2030 2020-2040 2020-2050 2020-2025 

esc. rate 15.54% 7.49% 4.98% 4.50% 

CC in 2030 

Year ($/kw-year) CC in 2040 CC in 2050 No CC 

1 2014 29 29 29 29 

2 2015 29 29 29 29 

3 2016 29 29 29 29 

4 2017 29 29 29 29 

5 2018 29 29 29 29 

6 2019 29 29 29 29 

7 2020 29 29 29 29 

8 2021 34 31 31 30 

9 2022 39 34 32 32 

10 2023 45 36 34 33 

11 2024 52 39 35 35 

12 2025 60 42 37 36 

13 2026 69 45 39 36 

14 2027 80 48 41 36 

15 2028 93 52 43 36 

16 2029 107 56 45 36 

17 2030 124 60 47 36 

18 2031 124 64 50 36 

19 2032 124 69 52 36 

20 2033 124 75 55 36 

21 2034 124 80 58 36 

22 2035 124 86 60 36 

23 2036 124 93 63 36 

24 2037 124 99 67 36 

25 2038 124 107 70 36 

26 2039 124 115 73 36 

19 
Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

27 2040 124 124 77 36 

28 2041 124 124 81 36 

29 2042 124 124 85 36 

30 2043 124 124 89 36 

31 2044 124 124 94 36 

32 2045 124 124 98 36 

33 2046 124 124 103 36 

34 2047 124 124 108 36 

35 2048 124 124 114 36 

36 2049 124 124 119 36 

37 2050 124 124 124 36 

38 2051 124 124 124 36 

39 2052 124 124 124 36 

40 2053 124 124 124 36 

41 2054 124 124 124 36 

42 2055 124 124 124 36 

43 2056 124 124 124 36 

44 2057 124 124 124 36 

45 2058 124 124 124 36 

46 2059 124 124 124 36 

47 2060 124 124 124 36 

48 2061 124 124 124 36 

49 2062 124 124 124 36 

50 2063 124 124 124 36 

51 2064 124 124 124 36 

52 2065 124 124 124 36 

53 2066 124 124 124 36 

54 2067 124 124 124 36 

55 2068 124 124 124 36 

56 2069 124 124 124 36 

57 2070 124 124 124 36 

58 2071 124 124 124 36 

59 2072 124 124 124 36 

60 2073 124 124 124 36 

61 2074 124 124 124 36 

62 2075 124 124 124 36 

63 2076 124 124 124 36 

64 2077 124 124 124 36 

65 2078 124 124 124 36 

66 2079 124 124 124 36 

67 2080 124 124 124 36 

68 2081 124 124 124 36 

69 2082 124 124 124 36 

20 
 

 

Attachment 2 - Forecast of Economic Value of CVP Hydropower 2014-2113

70 2083 124 124 124 36 

71 2084 124 124 124 36 

72 2085 124 124 124 36 

73 2086 124 124 124 36 

74 2087 124 124 124 36 

75 2088 124 124 124 36 

76 2089 124 124 124 36 

77 2090 124 124 124 36 

78 2091 124 124 124 36 

79 2092 124 124 124 36 

80 2093 124 124 124 36 

81 2094 124 124 124 36 

82 2095 124 124 124 36 

83 2096 124 124 124 36 

84 2097 124 124 124 36 

85 2098 124 124 124 36 

86 2099 124 124 124 36 

87 2100 124 124 124 36 

88 2101 124 124 124 36 

89 2102 124 124 124 36 

90 2103 124 124 124 36 

91 2104 124 124 124 36 

92 2105 124 124 124 36 

93 2106 124 124 124 36 

94 2107 124 124 124 36 

95 2108 124 124 124 36 

96 2109 124 124 124 36 

97 2110 124 124 124 36 

98 2111 124 124 124 36 

99 2112 124 124 124 36 

100 124 124 124 36 

c present value ($/kw-yr) 2686 2357 2101 1010 

a levelized ($/kw-yr) 91 80 71 34 

d present value (mil. $) 3196 2805 2500 1202 

b levelized (mil. $) 108 95 85 41 

2113 

21