Storage, Markets, and the Inter- temporal Allocation of Water in Colorado Andre Dozier Alex Maas Dale Manning CSU Water Center Faculty Fellow Funding

Storage, Markets, and the Inter- temporal Allocation of Colorado- Big Thompson Water CSU Water Center Faculty Fellow Funding Andre Dozier Alex Maas Dale Manning

Storage, Markets, and the Inter- temporal Allocation of Horsetooth Water CSU Water Center Faculty Fellow Funding Andre Dozier Alex Maas Dale Manning

Water Allocation in the Western United States Increasing urban population  E.g., 45% increase in Colorado by 2040 (Colorado.gov) Economists have demonstrated gain to water trades (E.g., Young, Colby, Howe) We consider within- and across-year water allocation Storage increases the effectiveness of markets  Balances marginal benefit and cost across time  Water consumption smoothed over time

Research Questions Does inter-annual storage increase the value of water over time (and by how much)? How do water allocation institutions affect optimal storage and water value? Are some institutions better suited to respond to a changing climate?

Colorado-Big Thompson Project (Horsetooth Reservoir for now) C-BT determines annual quota of water Horsetooth gets ~38%  Average inflow of ~87,188 acre-ft per year  Average storage ~90,000 acre-ft

Model Setup 2 water users with parameterized benefit functions (quadratic)  Agriculture  Municipal and Industrial Central reservoir manager  1 release decision per year Water Allocation (with and without storage)  Free market  Restricted trade given 1957 rights (or high transaction costs that prevent trades)  50 time periods

Institutions Restricted Trade:  Ownership is fixed and no lease market  Each user type owns and uses a fixed proportion of total water  With storage, reservoir manager makes storage decision to equate marginal benefit over time Perfect market  Users trade water to equate the marginal benefit across uses  With storage, reservoir manager makes storage decision to equate marginal benefit over time

Water availability Stochastic inflows of water, based on historic inflows With storage:  Optimal release schedule  Solved using stochastic dynamic programming No storage:  Water use equals inflows in a given year  Marginal benefit not equal across time

Results: Release Decision Same rule for both institutions (for this case)

Results: Total Value of Water *Value of within year storage not accounted for **Only Horsetooth water considered Present Value of Water** (millions) No StorageStorage 10% Increase in Storage Trade $212.4*$214.30$ No Trade $154.90$157.60

Results: Total Value of Water Present Value of Water (millions), Decreased Mean Inflow by 10% No StorageStorage 10% Increase in Storage Trade $208.30$210.30$ No Trade $147.60$151.00

Discussion Trade and storage increase value of water Gains from trade across users large compared to inter-annual storage Water trading with 10% less water produces 40% more value than no-trade and current water supply

Ongoing work Theoretical model of optimal water storage Expand model to C-BT (west slope) storage  Account for infrastructural constraints, hydrology/externalities  Incorporate annual carryover program (ex post individual banking)  Incorporate more detailed climate projections Time-varying benefits of C-BT water Distributional impacts

Other water research (since seed grant) General equilibrium impacts on rural-urban water transfers in the west (Manning, Goemans and UN-Reno team) Economic impact of groundwater pumping policies (Manning, Goemans, and Suter)  Agricultural output  Other sectors Multi-state management of the Ogallala High Plains Aquifer (Kelly, Waskom, Manning, Goemans, Suter, teams from UNL,OSU,USGS, and USDA)

Thanks…

C-BT Water Use

Water consumption over time with and without storage

C-BT Water Use Agriculture still receives more water despite change in ownership

Quota (Storage) Decision Percent of 310,000 acre-ft of water to release November and April Considers:  Water in C-BT reservoirs  Water in non-C-BT reservoirs  Snowpack, projected run-off, soil moisture  Input from water users Average Quota: 75% Quota graph

C-BT Timeline Year 0 Year1 N D J F M Leftover water eligible for ACP O A M JJ A S O N Year 2 Quota Decision 1 (%) Quota Decision 2 (%) Deadline to declare ACP Lose remaining ACP

Horsetooth Reservoir

Back

Storage and Inter-temporal Efficiency Storage allows for optimal water use across multiple years Increases the effectiveness of markets  Balances marginal benefit and cost across time  Water consumption smoothed over time “Storage or Markets” (Goodman 2000) We investigate their interaction