1. Agenda CALVIN: Optimization of California’s Water Supplies
 29 November 2001
10:00am – 4:00 pm
744 P St., Sacramento, CA; Auditorium
 CALVIN is an optimization model which suggests operations of California’s inter-tied water supply system which would maximize statewide economic benefits to agricultural and urban water users within environmental flow requirements. Morning sessions will focus on technical aspects, with the afternoon sessions on results, policy, and management implications. Project descriptions, details, and results can be found at:
Tentative Workshop Agenda
 10:00 Overview of CALVIN Model (Jay Lund)
10:30 Economic Valuation of Water Uses (Richard Howitt, Mimi Jenkins)
11:00 Managing Data and Model Outputs (Ken Kirby)
Model engineering and economic outputs and how they are used
Data Management and Databases
11:30 Model Calibration (Mimi Jenkins)
12:00 Limited Foresight and Carryover Storage (Andy Draper)
12:30 Lunch
1:30 Limitations of Model and Data (Jay Lund)
1:45 Results and Implications (Various speakers)
Alternatives Examined (Randy Ritzema)
Delivery & Economic Performance with Optimized Operations (Randy Ritzema)
Willingness-to-Pay for Additional Water (Richard Howitt)
Water Transfers and Exchanges (Richard Howitt)
2:30 Break
2:45 Results and Implications (continued)
Economic Values for Facility Expansion (Stacy Tanaka)
Economic Costs of Environmental Flows (Stacy Tanaka)
Conjunctive Use (Mimi Jenkins)
Other operational changes (Mimi Jenkins)
3:30 Implications for State Water Policy and Planning (Jay Lund and Richard Howitt)
3:45 Continuing Work (Jay Lund)
Conclusions
4:00 End
Agenda

2. CALVIN Web site: cee.engr.ucdavis.edu/faculty/lund/CALVIN/
Economic-Engineering Optimization for California’s Water Supplies
Professor Jay R. Lund
Civil & Environmental Engineering, UC Davis
Professor Richard E. Howitt
Agricultural & Resource Economics, UC Davis
Web site:
cee.engr.ucdavis.edu/faculty/lund/CALVIN/

3. Real work done by Dr. Marion W. Jenkins Dr. Andrew J. Draper
Dr. Kenneth W. Kirby Matthew D. Davis
Kristen B. Ward Brad D. Newlin
Brian J. Van Lienden Stacy Tanaka
Randy Ritzema Guilherme Marques
Siwa M. Msangi Pia M. Grimes
Jennifer L. Cordua Mark Leu
Matthew Ellis Dr. Arnaud Reynaud

4. Funded by CALFED Bay Delta Program
State of California Resources Agency
National Science Foundation
US Environmental Protection Agency
California Energy Commission
US Bureau of Reclamation
Lawrence Livermore National Laboratory

5. Overview 1) California Water Problems 2) What is CALVIN?
3) Modeling Approach and Data
4) What is Optimization?
5) Results
6) Innovations and Uses
7) Major Themes

6. California Water Problems
California: an often dry place with a good climate
Wetter winters, very dry summers.
Water in north/mountains,
demands in south, central and coast.
Groundwater is 30-40% of supply.
Competition for water:
Agriculture, urban, environment

7. Motivation for Project
California’s water system is huge and complex.
Water is controversial and economically important.
Major changes are being considered.
Can we make better sense of this system?
Understanding from data and analysis
Insights from results
Reduce reliance on narrow perspectives
How could system management be improved?
What is user willingness to pay for additional water and changes in facilities & policies?
These are not “back of the envelope” calculations.

8. What is CALVIN? Entire inter-tied California water system
Surface and groundwater systems
Economics-driven optimization model
Economic Values for Agricultural and Urban Uses
Flow Constraints for Environmental Uses
Prescribes monthly system operation

9. Approach a) Develop schematic of sources, facilities, & demands.
b) Develop explicit economic values for agricultural & urban water use for 2020 land use and population.
c) Identify minimum environmental flows.
d) Reconcile estimates of unimpaired inflows, & identify problems therein.
e) Develop databases, metadata, and documentation for more transparent and flexible statewide analysis.

10. Approach (continued)
f) Apply economic-engineering optimization to combine this information and suggest:
1) promising capacity expansion & operational solutions,
2) economic value of additional water to users,
3) costs of environmental water use, and
4) economic value of changes in capacities and policies.

11. Model Schematic Over 1,200 spatial elements 51 Surface reservoirs
28 Ground water reservoirs
24 Agricultural regions
19 Urban demand regions
600+ Conveyance Links

12. CALVIN’s Demand Coverage

13. Economic Values for Water
Willingness to pay
Agricultural
Urban
Operating Costs

14. Agricultural Water Use Values
July
70,000
June
August
60,000
50,000
March
Benefits ($ 000)
40,000
May
3,000
30,000
October
April
2,000
February
20,000
January
1,000
10,000
September 5 10 15
October 50
100
150
200
250
300
350
400
Deliveries (taf)

15. Urban Water Use Values Winter Summer Spring Deliveries (taf) 50,000
45,000
40,000
35,000
Spring
Penalty ($000)
30,000
Summer
25,000
20,000
15,000
10,000
5,000 20 25 30 35 40 45 50 55 60
Deliveries (taf)

16. Operating Costs Fixed head pumping Groundwater recharge basins
Energy costs
Maintenance costs
Groundwater recharge basins
Wastewater reuse treatment
Fixed head hydropower
Urban water quality costs

17. Environmental Flow Constraints
Minimum instream flows
Rivers and lakes
Delta outflows
Wildlife refuge deliveries
Sources:
DWRSIM
PROSIM - CVPIA
Various local studies

18. Hydrology Surface & Groundwater
historical period:
Monthly unimpaired inflows
Surface inflows from State & Federal data
Groundwater from Federal & local studies
Need to reconcile conflicting data!

19. Policy Constraints All Cases Environmental flows Flood control storage
Current Policy Base Case
DWRSIM surface operations
CVGSM pumping and deliveries
Unconstrained economic case
Only environment & flood control

20. Model Inputs Schematic and facility capacities
Agricultural water values
Environmental Flow Constraints
Urban water values
Operating costs
Hydrology: Surface & ground water
Policy Constraints

21. Data Flow for the CALVIN Model

22. Database and Interface
Tsunami of data for a controversial system
Political need for transparent analysis
Practical need for efficient data management
Databases central for modeling & management
Metadata and documentation
Database & study management software
Planning & modeling implications

23. What is Optimization? Finding the “best” decisions within constraints.
“Best” implies performance objective(s).
Constraints limit the range and flexibility of decisions.
Some constraints are physical.
Other constraints are policy.
Optimization can identify promising solutions.

24. Network Optimization – In Words
Decisions: Water operations and allocations
Best performance:
(1) Minimize sum of all costs over all times
Subject to some constraints:
(2) Conservation of mass
(3) Maximum flow limits
(4) Minimum flow limits

25. Network Flow with Gains - Math
Minimize:
(1) Z =  cij Xij, Xij is flow from node i to node j
Subject to:
(2)  Xji =  aij Xij + bj for all nodes j
(3) Xij  uij for all arcs
(4) Xij  lij for all arcs
cij = economic costs (ag. or urban)
bj = external inflows to node j
aij = gains/losses on flows in arc
uij = upper bound on arc
lij = lower bound on arc

26. Some Results Delivery, Scarcity, and Cost Performance
Willingness to pay
Water transfers and exchanges
Economic Value of Facility Changes
Costs of Environmental Flows
Conjunctive Use and other Operations

27. CALVIN’s Innovations 1) Statewide model
2) Groundwater and Surface Water
3) Supply and Demand integration
4) Optimization model
5) Economic perspective and values
6) Data - model management
7) Supply & demand data checking
8) New management options

28. Themes
Economic “scarcity” should be a major indicator for California’s water performance.
Water resources, facilities, and demands can be more effective if managed together, especially at regional scales.
The range of hydrologic events is important, not just “average” and “drought” years.
Newer software, data, and methods allow more transparent and efficient management.

29. cee.engr.ucdavis.edu/faculty/lund/CALVIN/
More Information ...
Web site:
cee.engr.ucdavis.edu/faculty/lund/CALVIN/

31. Water Demand Functions
Urban demands are generally demands for direct consumption.
Agricultural demands are derived demands that depend on the cost of other inputs and the value of the output.
Environmental demands are represented by constraints.
The elasticity of demand measures the responsiveness of the quantity demanded to changes in the price ( cost ) of water.
An elastic demand has an elasticity greater than one, and is relatively responsive to price changes.
Direct statistical estimation of demands is prevented by the absence of price variation in Californian agricultural or urban water

32. Calvin’s Economic Requirements
Calvin needs a stepped “Penalty function” for each delivery node on the schematic.
The penalty is the cost of not having a quantity of water and is the inverse of the demand function that measures the value of having water.
The continuous economic demand functions are divided into discrete steps for linear solution.
The agricultural and urban demand functions must be calibrated so that the marginal value of the observed deliveries is equal to the observed water price.

33. Data Base for the SWAP Model
The Statewide Agricultural Production Model ( SWAP ) models the regional adjustment of profit maximizing farmers allocating water over the range of crops currently grown in the region.
The base year for calibrating SWAP is 1992
Base costs, prices, yields and input quantities are largely based on CVPM data.
SWAP crop acreages were extrapolated to 2020 levels using forecasts from DWR Bulletin

35. SWAP Model Regions

37. Agricultural Crop Descriptions

38. Agricultural Response to Changes in the Price and Quantity of Water
Changes at the Extensive Margin
Changes in the total Area of Irrigated crops
Adjustments in the regional cropping mix.
Changes at the Intensive Margin
A change in crop input use per acre
Changes in Water application efficiency due to technology and management.

40. Efficiency-Cost Trade-offs. Orchards Sacramento Valley

41. Calibrating Regional Crop Production Functions
Regional data available- acres, average yields, input quantities, crop price, input cash cost, resource constraints
Optimize a constrained problem to obtain shadow values on binding constraints.
Define the form of the production function- in this case, a quadratic function of three inputs.
Use maximum entropy methods, marginal and average product conditions to estimate the production function coefficient values.
Use the ME coefficient values to define a production model that calibrates to the base year, but is only constrained by the resource constraints.

43. Linking Annual Cropping Decisions to Monthly Water Use
Assume that crops require water in a predetermined monthly pattern based on ET requirements.
Farmers can make small water reallocations between months.
Any changes in the total applied water due to technology or stress irrigation are allocated are allocated proportionally across months

45. SWAP-Derived Agricultural Water demands
1000
800
600
Willingness to Pay in $/AF
July Demand
400
April Demand
200 20 40 60
Water Availability in KAF

46. Agricultural Water Use Values
July
70,000
June
August
60,000
50,000
March
Benefits ($ 000)
40,000
May
3,000
30,000
October
April
2,000
February
20,000
January
1,000
10,000
September 5 10 15
October 50
100
150
200
250
300
350
400
Deliveries (taf)

47. Tomato production-Yolo county
Water
Land

48. Calibrated Production Surface for Grapes, Fresno

49. Urban Demands
Residential demands are based on comprehensive survey of estimated price elasticities. The demand function is fitted through the observed 1995 price and quantity demanded with the function slope determined by the elasticity.
The 2020 demand are obtained by scaling the 1995 quantities by population growth.
Commercial is assumed proportional to the population and is added to the residential demand.
Industrial are based on a 1991 survey of shortage induced production losses in 12 counties, and scaled to 2020.

50. Residential Price Elasticities

51. Estimating Residential Demands
Residential price elasticities
1995 retail water prices
1995 population x pcu
= Demand Curve
1995 demand curve scaled by 2020 population
4 = Demand Curve

52. Calibrating Residential Demands to the 2020 Population
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
6,000
6,500 10 15 20 25 30 35 40 45 50 55 60
Monthly Quantity (taf)
Price ($/af)
Jan
Jan
Apr
Apr
Jul
Jul
1995 Price

53. Converting Residential demands to Urban Loss Functions
Integrate the 2020 residential demand function
Add a constant level of 2020 commercial use
Find the quantity that drives the demand price ( or loss of not having water) to zero
Plot the loss function against monthly delivery.

54. Residential Loss Functions for 2020

55. Industrial Values
1991 production losses due to water shortages – 12 counties
1995 industrial use scaled by population to 2020
1+2 = Industrial Loss Function

56. 1995 Urban Residential Water Prices in California

57. Conclusions
Water demand functions must reflect rational adjustments to changing scarcity by users
Demand functions need to be specified by use, region and month
Urban demands can be estimated on a regional basis using published elasticities and base year data
Agricultural demand functions can be estimated using regional production data and ET requirements.

58. Managing Data in CALVIN
Model, Database, Documentation, and Post-processing SOFTWARE

59. CALVIN Physical Outputs
Flow
Flows across all links
EOM Storage Levels at all storage nodes
Evaporation at all storage nodes
Deliveries to all demand nodes
TIME SERIES of MONTHLY:
Storage

60. CALVIN Economic Outputs
Scarcities
Cost of scarcities
Marginal WTP for more water
Shadow values on constraints (Lagrange Multiplier)
Marginal value of water at each node
Post-processed by intersecting deliveries with economic water loss functions for Ag & Urban
Produced directly by HEC-PRM Optimization

61. SWAP Post-Processed Outputs
Ag annual deliveries by water source from CALVIN
SWAP Model
Irrigation efficiencies
Crop acreages
Crop yields
Gross revenue
Net revenue

62. Data Management Design Principles
HEC-PRM Requirements
Transparent model assumptions
Easily modified model inputs
Object oriented data management
Documentation of input values = metadata
Metadata attached to each piece of data
RELATIONAL DATABASE
Time series stored in DSS
Paired data stored in DSS
Model definition file in ASCII
Output in DSS

63. CALVIN Data Storage & Software

64. Region 3 Schematic

65. Network Component Listing

66. Node Properties

67. Metadata

68. Summary Metadata is essential
Relational databases and software allow modeling of complex systems in more detail than otherwise possible
Data management eliminates majority of input file errors (especially related to syntax)
More work to be done

69. Hydrologic and Agricultural Demand Calibration
Integrate DWRSIM’s surface hydrology with CVGSM’s groundwater hydrology
Reconcile DWR agricultural water demand assumptions with deliveries in the CVPIA PEIS
Produce a model consistent with established representations of California’s hydrology and demands
Identify data problems and regions than cannot be fully reconciled
Objectives of the CALIBRATION
General purpose was to reconcile data from disparate sources
More specifically are the points listed in slide.
Point 3 is: essentially makes CALVIN match groundwater in CVGSM NAA and surface water in DWRSIM Run 514 at the same time

70. Calibration Procedures
Impose “Base Case” diversions, deliveries, and operations on CALVIN
Adjust agricultural demands to match BC deliveries
Adjust agricultural return flows and reuse rates to calibrate groundwater to CVGSM NAA
Run CALVIN Base Case and adjust streamflows to match DWRSIM 514a at 15 matching control points
Verify scarcity results with similar estimates
NOTE: BASE CASE refers to a combination of CVPIA PEIS run NAA, and DWRSIM Run 514

71. Configuration of Physical and Calibration Links
Isolate calibration parameters from more physically based parameters in the CALVIN model

72. GW Calibration Results
Sacramento Valley GW
GW Calibration Results
Agricultural demands increased by about 10% (1.9 MAF)
Reuse rates reduced in a few regions
SW return flows eliminated in much of Tulare Basin
GW calibration successful in Sac Valley (top chart)
Problems with GW calibration in Tulare Basin, esp. CVPM region 14, 18, 19, and 21
SJ Valley & Tulare Basin GW
Difference between CVGSM for Region 4 (Tulare Basin, CVPM 14-21) and CALVIN calibrated is about 450 taf/yr more long-term depletion of GW.
- CVGSM NAA indicates 143 taf/yr avg. long-term recovery
- our best calibrated results are 300 taf/yr avg. long-term depletion
Data problems in Region 4 (Tulare Basin) reduce confidence in CVGSM results and make this area particularly difficult to calibrate.

73. SW Calibration Results
Sac R.
Colusa BD
Net addition of 38 taf/year calibration flows
Biggest monthly imbalances on Sac R. (below Colusa BD) & Feather R. (incl. Yuba+Bear), > +/- 1 MAF
Largest annual imbalances on Sac R taf/yr, Lower SJR -434 taf/yr, and in-Delta CU (- 380 taf/yr)
Largest net additions of SW in CALVIN Region 1 and 4; net removals in CALVIN Region 2 and 3
Sac R.
Hood
In-Delta CU

74. What we learned Calibration is necessary and long
Hydrologic data needs improvement:
more explicit and separate GW & SW hydrologic data
better estimates (methods) for local accretions/depletions
Agricultural water use uncertainty is significant
Very weak data for modeling Tulare Basin:
conjunctive use operations
groundwater-surface water interactions
Large discrepancy in in-Delta CU estimates
the calibration exercise has identified fundamental and potentially significant inconsistencies and uncertainties in the available and commonly used hydrologic and water demand data. Such inconsistencies are not surprising given that most of these data were not developed to be consistent with active and integrated surface, groundwater, and water demand management. Additional hydrologic and modeling data development clearly is needed, as
BIG Uncertainty in modeling CU and GW in Tulare Basin – discrepancy of over 500 taf/yr in estimates of long-term change in GW storage in the region.
identifying important data gaps and inconsistencies

75. A Limited Foresight Model and the Value of Carryover Storage

76. Perfect Foresight or the Model that Knew too Much
Multi-year optimization – too omniscient
Over valuation of existing facilities
Under valuation of new facilities
Excessive carryover storage prior to droughts
Single-year optimization – too short sighted
How to construct model with limited foresight to:
Reflect imperfect knowledge of probability distribution of inflows
Balance present and future water needs

77. Sequential Annual Runs
Use one year time period (Oct – Sep)
72 consecutive model runs for period-of-analysis
Model runs linked by ending/carryover storage
Carryover storage value functions limit drawdown
System performance sum of 72 year costs excluding carryover storage penalties

78. Iterative Solution START
Define initial carryover storage penalty function
Iteration n=1
Iteration n= n + 1
Set yr=1, read initial conditions
Run HEC-PRM for one year No
yr=72?
yr = yr +1
BOP Oct = EOP Sep
Yes
Calculate total penalties
Yes
Iteration n=1?
Significant
improvement
Yes
Revise carryover storage penalty function No
STOP

79. Model Run Times
Run times remain an obstacle for analyzing complex systems
Solver times proportional to cube of number of constraints
Solver times proportional to number of variables
Run time as a function of years of analysis found to be approx. quadratic
Limited foresight model exploits rapid increase in run times

80. Case Studies Three case studies used as proof of concept
Single reservoir operation
Integrated two reservoir operation
Single reservoir operated conjunctively with groundwater
Reservoirs operated for water conservation and flood control
Objective function to minimize economic cost of shortage associated with d/s agricultural deliveries
Network flow solver (HEC-PRM)

81. Case (a): Application to a Single Reservoir
Four separate models developed:
New Don Pedro Reservoir, Tuolumne River
Lake McClure, Merced River
Pine Flat Reservoir, Kings River
Lake Berryesssa, Putah Creek
Case studies to provide a framework for the presentation of ideas rather than a realistic operation of each stream-reservoir system.
Value functions developed for agricultural deliveries

82. Valuing Carryover Storage
Assume quadratic penalty
P = a + bS + cS2
P|S=K = 0
dP/dS is -ve, d2P/dS2 is +ve
dP/dS between reasonable limits

83. Grid Search Simple to implement Ensures global optimum
Response surface mapped-out
Computationally inefficient
Accuracy limited by grid spacing
Coarse grid search starting point for more efficient methods

84. Nelder-Mead Simplex Method
1: initial simplex
2: simplex expansion
3: simplex reflection
4: simplex reflection (reflection adjusted to stay within feasible region)
5: simplex reflection (reflection adjusted to stay within feasible region)
6: simplex reflection
7: simplex contraction
8: simplex contraction
9: simplex contraction, solution tolerance satisfied
optimal penalties Pmin = -9 $/af , Pmax = -148 $/af 1 5 4 3 2 6 7 8 9
Unconstrained minimization of several variables
Zero-order search method
Global optimum not guaranteed

85. New Don Pedro Reservoir Average Annual Shortage Cost as a Function of Pmin and Pmax

86. Lake McClure Average Annual Shortage Cost as a Function of Pmin and Pmax

87. Pine Flat Reservoir Average Annual Shortage Cost as a Function of Pmin and Pmax

88. Lake Berryessa Average Annual Shortage Cost as a Function of Pmin and Pmax

89. New Don Pedro Reservoir Operation under Perfect Foresight

90. New Don Pedro Reservoir Operation under Limited Foresight

91. New Don Pedro Reservoir Carryover Storage for Different Levels of Information

92. Reservoir Operating Rules

93. Case (b): Integrated Two-Reservoir System

94. Flood Control & Carryover Storage
Flood Control Diagram
100
200
300
400
500
600
Aug
Sep
Oct
Nov
Dec
Jan
Feb
Mar
Apr
May
Jun
Jul
Storage (taf)
Conditional
Space
Rainflood
Conservation
Min Operating Lvl K

95. Balancing Storage Between Reservoirs in Parallel4 5 3 2 1
Objectives:
Equalize refill potential
Minimize EV(spills)
Avoid inefficient conditions

96. Carryover Storage Penalty Functions

97. Carryover Storage: New Don Pedro and New Exchequer Reservoirs

98. Case (c): Conjunctive Use

99. Groundwater Mining
For perfect foresight model groundwater mining prevented by applying constraint to ending groundwater storage
For limited foresight model linear penalty attached to end-of-year storage
Initial value of penalty set equal to shadow value on groundwater mining constraint from perfect foresight run
Penalty iteratively raised until no groundwater mining occurs

100. Comparison of Groundwater Storage under Perfect and Limited Foresight Models

101. Conclusions: Perfect Foresight
Perfect foresight may significantly distort reservoir operation where reservoirs are used for over-year storage, and where multi-year droughts occur.
The impacts of perfect foresight revealed by
lack of hedging under average hydrologic conditions
aggressive hedging during the initial years of an extended drought.
The perfect foresight models can substantially under estimate shortages and shortage costs
As system storage increases the effects of perfect foresight are diminished.

102. Conclusions: Limited Foresight
The limited foresight model
Results in an economically derived value of carryover storage.
Prescribes more realistic reservoir operations.
More likely to be acceptable to stakeholders
Facilitates the deduction of operating rules
Can quantify the over-achievement of perfect foresight models.
There exists a wide range of near-optimal carryover storage policies.
Differences between the limited and perfect foresight model are minor except prior and during drought conditions.

103. Conclusions: Conjunctive Use
Conjunctive use can substantially improve overall system reliability and reduce total costs
Considerable benefits may accrue by explicitly adjusting surface reservoir operations to account for contingent groundwater supplies.
The value of surface carryover storage rapidly diminishes with increasing groundwater supplies.
Carryover storage rules determined without explicitly accounting for the presence of groundwater storage become economically very inefficient as groundwater supplies increase.
Integrated conjunctive use greatly reduces the impact of perfect foresight.

104. Limitations Major sources of CALVIN’s limitations:
Weak or unavailable input data from other sources.
Limitations of HEC-PRM network solver.
Lack of hydropower, flood control, and recreation benefits.

105. Major Limitations Surface Hydrology Groundwater Hydrology
Valley floor inflows
Delta local supplies
Southern California
Groundwater Hydrology
Weak Tulare Basin data
Simplified stream-aquifer interaction
groundwater extensions
CVGSM data
Pumping capacities, costs, and use

106. Major Limitations (continued)
Water Demands and Deliveries
Year-type variation
Limited water quality
Limited understanding of agricultural flows
Base case delivery data from CVGSM
Representation of local systems
Environmental Regulations
Delta representation
Other “pre-operated” flow constraints
Water quality limitations

107. Major Limitations (continued)
Perfect Foresight
Less important with lots of groundwater storage
Probably causes 5-10% of S. California benefits
Need to be careful
Limited foresight methods under development
Value of simulation modeling;
Excluded Operating Benefits
Hydropower
Flood Control
Recreation

108. Limitations Implications
Data problems apply to ANY regional and statewide analysis.
Use simulation models to refine and test optimization-based solutions.
“All models are wrong, but some are useful.” G.E.P. Box (Like budget estimates?)

109. CALVIN Modeling Alternatives
Randall Ritzema

110. How is water allocated now?
Water rights and contracts
+ Operating agreements
+ Environmental regulations
+ Water markets (sometimes)
= Complex institutional framework
Typically analyzed using simulation

111. Objective, in words:
To quantify overall economic performance under flexible operations and allocations, within environmental requirements.
Performed by comparing current operations (Base Case) to flexible operations (Unconstrained Case).

112. Example Network OptimizationSW GW
AGRICULTURAL
URBAN
Inflow
Link, no economic value
Link, w/ economic value
ENVIRONMENTAL

113. Base Case SW GW AGRICULTURAL URBAN ENVIRONMENTAL Constrained flow
Unconstrained flow

114. BC Delivery ConstraintsSW GW
AGRICULTURAL
URBAN
DWRSIM Run 514, CVGSM NAA 1997
DWRSIM Run 514, CVGSM NAA 1997
ENVIRONMENTAL
Constrained flow
Unconstrained flow

115. BC Operations ConstraintsSW GW
DWRSIM Run 514
CVGSM NAA 1997
AGRICULTURAL
URBAN
ENVIRONMENTAL
Constrained flow
Unconstrained flow

116. Environmental ConstraintsSW GW
AGRICULTURAL
URBAN
Refuges (Level 2)
Minimum Instream Flows
(PROSIM NAA 1997)
ENVIRONMENTAL
Constrained flow
Unconstrained flow

117. Unconstrained Case Constraints: Environmental flowsSW GW
AGRICULTURAL
URBAN
Constraints:
Environmental flows
Physical capacities
Reservoir flood control storage
ENVIRONMENTAL

118. Model Alternatives Base Case Basis for Comparison
Goal: mimic simulation planning models
Current water allocations
Current water operations
Current environmental flows

119. Model Alternatives Base Case Regional Unconstrained
Statewide model is divided into 5 regions
Supplies re-operated and re-allocated within regions.
Base Case inter-regional boundary flows

120. CALVIN Regions

121. Model Alternatives Base Case Regional Unconstrained
Statewide Unconstrained
Inter-regional boundary constraints removed

122. Delivery and Economic Performance
Comparison of Base Case, Regional Unconstrained, and Statewide Unconstrained Alternatives
Randall Ritzema

123. Urban and Agricultural Deliveries (annual average, in taf)

124. Delivery Changes to Ag Sector (annual average, in taf)

125. Delivery Changes to Urban Sector (annual average, in taf)

126. Agricultural Scarcity Costs (annual average, in $ millions)

127. Urban Scarcity Costs (annual average, in $ millions)

128. Total Costs (annual average, in $ billions)
4.18
2.85
2.78

129. Total Cost by Region (annual average, in $ millions)

130. The importance of marginal values and spatial equilibrium
Marginal changes in water allocation and management must be evaluated using marginal measures of value.
Models of spatial equilibrium have conditions which balance the marginal profitability conditions of water between regions and uses
In CALVIN, the marginal values are measured in terms of the productive uses of water at each of the demand nodes.
Underlying marginal values are production decisions which balance the marginal value productivity of water across crops and months.
Optimal CALVIN runs are in spatial equilibrium since water cannot be reallocated without violating a constraint or reducing the overall economic value of California’s water.

131. The Spatial information in CALVIN
CALVIN explicitly defines the constraints and conveyance costs that constrain the movements of water across space.
The shadow values measure the marginal cost of constraints.
Calvin has the willingness-to-pay explicitly represented for each node.
The gainers and losers from trades are clearly identified by location and sector

134. Practical Impediments to Water Trades
Third party economic impacts in the exporting regions
Defining the tradeable quantities of water by the consumptive use of applied water
Avoiding negative environmental impacts from wheeling traded water or changing the type and location of use.

135. Using CALVIN to Measure Third party Economic Impacts
CALVIN is optimized for a base condition, and an optimal trade condition.
Urban benefits from trades are immediately shown by comparing the net benefits at urban nodes.
Agricultural effects are measured by “Post-optimality” analysis using SWAP.
CALVIN traded water allocations are fed back into SWAP which then estimates the change in regional crop production caused by the trade.
Regional income and employment multipliers are used to measure the community effects of the change in production.

136. Defining Tradeable Water Quantities
CALVIN tries to explicitly measure consumptive use and return flows.
The net change in consumptive use by region and water use is calculated.
CALVIN only proposes trades in which the change in return flows do not violate environmental constraints.

137. CHANGES IN SCARCITY COSTS ($ M/yr)
-35
-15 -4
-18 39
-1,255 34
-1,323 -1
-1,400
-1,200
-1,000
-800
-600
-400
-200
200
Upp Sac V. Ag
Upp Sac V. Urb
L.Sac.V.& BD Ag
L.Sac.V.& BD Urb
SJV.& SBay Ag
SJV.& SBsy Urb
Tulare B. Ag
Tulare B. Urb
SoCal Ag
SoCal Urb
TOTAL AG
TOTAL URB
CHANGES IN SCARCITY COSTS ($ M/yr)

139. Measuring Wheeling Costs and Constraints
In calculating the value of water trades, CALVIN accounts for wheeling costs and constraints
Constraints on wheeling water often limit trades, CALVIN shows the marginal shadow values of such constraints.
In proposing trades, CALVIN not only identifies the buyer and seller, but shows how the water can optimally be wheeled between the buyer and seller in a particular month and for a water year type.

140. Conclusions on Marginal Value and Trade
Water allocations and adjustments occur “on the margin” accordingly, marginal values- not average values- must be used to calculate efficient allocations.
CALVIN optimal results suggest potentially valuable water trades that take into account all the costs and constraints on the system.
By “post optimality” analysis CALVIN can measure and adjust for the main third party effects of water trades.

141. Conjunctive Use and Operational Changes
Presented by Mimi Jenkins

142. Overview Role of GW in California
Conjunctive Use Operations & Changes in CALVIN
Operational Changes
Sacramento Valley Conjunctive Use
Potential Impacts
Some Limitations
Implications
IN MY PRESENTATION TODAY, I’D LIKE TO…
START w/ some background on the role of GW and aquifers in California,
AND REVIEW how GW and CU are represented in CALVIN
2) THEN take a look at RESULTS – FIRST AT the changes in CU that occur under the ECONOMICALLY-DRIVEN Unconstrained CALVIN RUNS, at both regional and statewide scales.
3) WE WILL then REVIEW some of the more promising operational changes that occur in CALVIN across the state
4) For the second half of the presentation, I WILL FOCUS ON the Sacramento Valley, and THE INTERESTING OPERATIONAL CHANGES that occur with increased conjunctive use management in this area
5) WE WILL ALSO EXAMINE some POTENTIAL impacts of this increased CU, PARTICULARLY for environmental demands on the American and SAC RIVERS, and in the Delta
6) THERE ARE SOME limitations PARTICULAR TO these results THAT I WILL POINT OUT
7) FINALLY, WILL CONCLUDE with some implications

143. GW in California 30-40% of California’s supplies in average years
More groundwater use in dry years
Total storage capacity = 850 MAF
Largely unmanaged

144. GW in CALVIN GW Resources: Economic Drivers: Operating Constraints:
28 GW basins
Fixed inflows
Economic Drivers:
Economic values for water use
Operating costs of using water sources
Operating Constraints:
Ending storage set to Base Case (no additional mining)
Pumping capacities
Other capacities
SO how does CALVIN manage CONJUNCTIVE USE and OPERATED GW???
CALVIN jointly OPERATES GW RESOURCES OVER THE HISTORIC PERIOD, TO OPTIMIZE PUMPINC AND RECHARGE DECISIONS IN CONJUNCTION WITH ALL OTHER WATER ALLOCATION AND STORAGE DECISIONS IN THE NETWORK.
GW OPERATIONS ARE DRIVEN BY ECONOMIC VALUES, considering the OPERATING COSTS and AVAILABILLTY of other resources IN THE MODEL.
THESES DECISIONS are ALSO SUBJECT TO CAPACITY CONSTRAINTS and NO ADDITIONAL MINING BEYOND the BASE CASE.
GW Resources:
FIXED INFLOWS consist of interbasin flows, various recharge sources, & stream-aquifer gains
As explained this morning, GW resources are calibrated to CVGSM in Central Valley
Economic Drivers are the values for ag and urban water use
Operating costs for different water sources include pumping, treatment, local distribution, water quality,conveyance and other such costs of using different water sources
Other storage and conveyance capacities

145. Statewide Reliance on GW and CU
Figure shows the frequency (ACROSS THE BOTTOM OF THE CHART) of different levels of groundwater use statewide (SHOWN IN % along the VERTICAL AXIS), comparing Base Case with the Regional and Statewide Unconstrained Alternatives.
Statewide, the median groundwater use is about 33% of total water deliveries for all THREE ALTERNATIVES.
In wet years, this can drop to as low as about 16-22%, and in dry years it can increase to as high as about 56%.
In GENERAL THE CHART SHOWS that economically-based operations tend to use GW far more conjunctively
than in the Base Case, with greater variation in groundwater use between years.
WE can see that under water markets groundwater is used, in conjunction with surface water, for over-year storage to a greater extent than the Base Case.
THE DIFFERNCE is most pronounced between the BC and Regional WM case.
With a statewide water market, conjunctive use appears to increase only somewhat more.

146. Average Monthly % GW Supply
On a monthly or seasonal basis (Figure), the regional water market decreases average groundwater pumping during the wet months of January and February and increases average pumping during the drier months (July and August).
This seasonal trend is somewhat greater with a statewide water market.

147. Statewide Groundwater Storage
changes in surface and groundwater use improved supply reliability to users and/or decreased operating costs (related to delivery and urban water quality). There are examples of improved conjunctive use operations that involve urban and agricultural transfers as well as agricultural to agricultural transfers.

148. Operational Changes in CALVIN
Quality exchanges in Sac Valley, & between SJ River & Bay Area
Sac Valley CU Operations
Regional operation of Bay Area resources
Reduced Delta exports with South-of-Delta re-operations (Region 3, 4 and 5)
Increased Ag-Ag & Ag-Urban transfers in Tulare Basin to increase CU and eliminate scarcities
Mojave River Basin GW banking operations
Southern California Ag-Urban & Urban-Urban transfers, increased CU operations
Here is a list of some of the more promising operational changes that come out of CALVIN.
Many more. THESE are some of the more interesting and significant operational changes that occur in the economically driven unconstrained CALVIN runs.
Under the statewide unconstrained alternative, the area of the state south of the Delta experiences significant changes in conveyance and reservoir operations. These changes are driven by both agricultural-to-urban transfers and through re-operation of the SWP and CVP facilities, which export water from the Delta to the Bay Area, agricultural users in the San Joaquin and Tulare Basin portion of the Central Valley, and urban areas of Southern California.
In concert with the changes in California Aqueduct operations, deliveries through the Mendota Pool and the Friant Kern Canal play a greater role in meeting Tulare Basin demands. Friant Kern Canal diversions from Millerton Lake increase by almost 350 taf/yr and Tulare Basin agricultural supplies from the Mendota Pool increase by 81 taf/yr. Since these increased flows reduce water to the San Joaquin River system, the Delta Mendota Canal increases supplies to San Joaquin River users through the Mendota Pool. Ultimately, about 440 taf/yr of California Aqueduct diversions to the Tulare Basin Region are replaced with water from the San Joaquin system.
THE * refers to the focus on the rest of this presentation, where I will present in more detail the interesting changes that occur with CU management in the Sac Valley.

149. Sacramento Valley Conjunctive Use
Unconstrained
Base Case
Non-drought Year
Drought Year
Sacramento R.
American R.
Groundwater
TOTAL PIE is about 5,300-5,400 taf/year
GW especially in GW-7 and GW-8
Reducing ag and urban water supply operating costs for the Basin by $10-15 Million/yr
NON-DROUGHT YEAR includes normal or wet years
DROUGHT = 14 dry years spanning the 3 major droughts in CALIFORNIA
In wetter years, more surface water is used than for the Base Case, and in dry years more groundwater is used.
Exchanges of water sources to support the greater conjunctive use suggested by CALVIN are somewhat more extensive in some regions. Some of these exchanges also support urban water quality benefits for the Solano-Napa, Sacramento, Tulare, and Bay areas, as elaborated further in Chapter 4 and the appendices.
Greater conjunctive operation of local, regional, and statewide water resources decreases competition with environmental uses for limited streamflows. This is especially true under critical dry conditions when agricultural and urban reliance on surface flows is significantly reduced from Base Case levels. Under the statewide water market, total diversions from the Sacramento River are reduced on average by 429 taf during drought years with supplies made up by greater use of groundwater. Similarly, American River diversions during droughts are reduced by 228 taf/yr.
The Sacramento and American Rivers not only have large minimum instream flow requirements, but also are major water sources shared by many local water users. Figure 4-17 illustrates increased conjunctive operation of Sacramento basin surface and groundwater resources under the statewide water market. The figure also compares Base Case and statewide water market use of the three sources in drought and non-drought years. In both the Base Case and statewide water market during non-drought years (normal and wet), the largest supply source is the Sacramento River, with groundwater pumping a close second and the American River a distant third. However, under optimized statewide operations, Sacramento River in-basin use in non-drought years is higher than in the Base Case, contributing over half of the supply (Table 4-8). Non-drought year diversions from the American River and groundwater pumping are lower than for Base Case operations.
During drought years (14 out of the 72-year hydrologic period) the situation is markedly different. While the Base Case obtained a little more than half (53%) of its supply from groundwater during drought years (Figure 4-17), the statewide water market used significantly more groundwater, providing 64% of drought year supply. Simultaneously, withdrawals from the Sacramento and American Rivers drop respectively 430 taf and 228 taf, in the statewide water market compared to Base Case drought year operations (Table 4-8).
An important limitation is that minimum groundwater pumping requirements are not imposed in CALVIN. In practice not all agricultural water users in a CVPM region have access to surface water, and some must pump groundwater. Every CVPM region has some minimum amount of groundwater pumping which may not be respected in the CALVIN results.
Overall under the statewide water market, diversions are reduced during drought periods by 1206 taf/yr from non-drought year averages, compared to only 330 taf/yr reduction in Base Case diversions from non-

150. Sacramento Valley Re-operations
Principal Demands:
Upper Sacramento Valley Ag (CVPM 1-4)
Lower Sacramento Valley Ag (CVPM 6-8)
Lower Sacramento Valley Urban (Greater Sac Area)

151. Sacramento River Diversions
Changes in diversions from the Sacramento and American Rivers under the statewide water market re-operations can have significant consequences for the environmental concerns in the region. In the Base Case, diversions from both the Sacramento and American Rivers are fairly consistent across all years, even during critically dry periods (Figures 4-18 and 4-20). In contrast, under the greater basin-wide conjunctive operations of the statewide water market, diversions are much more variable, depending on hydrologic conditions. They frequently drop much lower than in the Base Case, especially during critically dry periods (Figures 4-19 and 4-21) and rise to higher levels during wet years.
In the statewide water market, the Lower Sacramento urban area (Greater Sacramento) completely eliminated diversions from the Sacramento River.
In non-drought years, statewide water market allocations from the Sacramento River increase by 326 taf/yr, on average, over the Base Case while allocations from the American River and groundwater pumping decrease.

152. American River Diversions

153. Groundwater Pumping

154. Sac Valley CU Impacts & Outcomes
Surplus Delta outflow up in drought years, slightly down in non-drought years, seasonal shift uncertain
Drought year diversions down taf on Sac R., 228 taf on Amer. R.
More flexibility to manage instream flows on Sac and American R. and in Delta
Reduced opportunity costs of environmental flows
$10 M/yr reduced operating costs (CVPM 7, 8 and Greater Sac Urban)
$42 M/yr reduced scarcity costs
. These changes in the inter-annual patterns of Sacramento and American River diversions may have other impacts for instream flow conditions (see “Other Potential Benefits” below).
. Surplus Delta outflow decreases by approximately 52 taf/yr in non-drought years and increase by 214 taf/yr in drought years (Table 4-12). On average surplus Delta outflows decrease by only 1 taf/yr in the statewide water market, . The same seasonal trend appears during drought years, except there is little to no surplus Delta outflow in summer and significantly higher outflow in winter. Thus the increased surplus Delta outflow presented in Table 4-12 in both non-drought and drought years is due to higher winter flows (Nov. to Mar.), rather than increased flow in all months (Figures 4-27 and 4-28).
reduces total exports from the Delta by an average of 360 taf/yr.
Changes in diversions from the Sacramento and American Rivers under the statewide water market re-operations can have significant consequences for the environmental concerns in the region. In the Base Case, diversions from both the Sacramento and American Rivers are fairly consistent across all years, even during critically dry periods (Figures 4-18 and 4-20). In contrast, under the greater basin-wide conjunctive operations of the statewide water market, diversions are much more variable, depending on hydrologic conditions. They frequently drop much lower than in the Base Case, especially during critically dry periods (Figures 4-19 and 4-21) and rise to higher levels during wet years.

155. Some Limitations of Results
Minimum GW pumping for Ag demands
Capacity for Folsom S. Canal supply to CVPM 8
Dynamic stream-aquifer interactions
Variable head pumping costs
Year-type variation in Ag & Urban demands
These CALVIN model results are idealized in the sense of perfect foresight and do not reflect all considerations, such as hydropower, water temperature, and real time flood control operations. These results are interesting and useful, but not necessarily conclusive from the broader operating context.

156. Implications GW can serve both seasonal & drought demands
“Optimized” GW doesn’t necessarily drain basins
Economics & markets can help us better employ GW
Optimization models can suggest promising conjunctive use solutions
Conjunctive use can substantially reduce need dry year diversions from streams
Conjunctive use can ease conflicts with environmental requirements and operations
Aquifer suited for drought storage
Groundwater mining has some economic value
Groundwater coordinated with other supplies and demands

157. Conclusions and Implications

158. Conclusions from Results
Some qualitative policy conclusions:
a) Regional or statewide markets have great potential to reduce water scarcity costs.
b) Economically efficient local and regional management reduces demands for imports.
c) Environmental flows have economic costs for agricultural, urban, & other activities.
d) Economic values exist for expanded facilities.

159. e) Some scarcity is optimal.
f) Economically optimal water reallocations are very limited, but reduce scarcity and scarcity costs considerably.
g) Integrated local, regional, and statewide operation of water decreases competition with environmental uses.

160. Policy and Planning Implications
Optimization works and shows promise.
Significant new capabilities:
Statewide and regional analysis
Economic and engineering analysis
Explicitly integrated operations
Transparent operations
Suggests new management options
Take the good, but remember the limitations.

161. Implications (continued)
Any regional & statewide analysis needs to:
Improve current data
Central Valley hydrology and demands
Agricultural and urban water use
Tulare Basin
Modernize data management (software and institutions)
Coordinate & extend data

162. Implications (continued)
CALVIN must graduate from the University.
Most uses and data are outside the University
We’re happy to help others use this capability
Models shouldn’t get tenure.
CALVIN is just a tool to help:
Make better sense of a complex system
Develop ideas for water management
Why do modeling? Need analytical ability to provide convincing ideas.

163. Uses for CALVIN?
Integrated statewide supply and demand accounting & data framework
Preliminary economic evaluation
Long-term statewide water planning
Planning & operations studies:
Facility expansion, Joint operations, Conjunctive use, & Water transfers
5) Suggest new management options
6) No panacea, but a step along the way.

164. Continuing Work: Current
Climate Change Study
Economic costs and benefits of different Delta Export levels
Add hydropower and flood control benefits
Faster, more flexible solver
Reasonable foresight
Fixing little things

165. Continuing Work: Envisioned
Improvements in economic water demands
Improvements in environmental demands
Policy studies (catastrophe response, water transfers, new facilities, conjunctive use, environmental flows, etc. ...)
More detailed regional studies (Bay Area)

166. Themes
Economic “scarcity” should be a major indicator for California’s water performance.
Water resources, facilities, and demands can be more effective if managed together, especially at regional scales.
The range of hydrologic events is important, not just “average” and “drought” years.
Newer methods, data, and software, including optimization, support more transparent and efficient management.

167. More Information ... Web site:
cee.engr.ucdavis.edu/faculty/lund/CALVIN/