5. Example - Use of a simulation- optimization approach to assess potential strategies for ground- water management in the Albuquerque area, New Mexico Laura Bexfield, Wesley Danskin, and Doug McAda In cooperation with the City of Albuquerque

6. Background on Management Issues City of Albuquerque has historically relied on ground water only City of Albuquerque has historically relied on ground water only Up to ¾ of known basin-wide pumping is by COA Up to ¾ of known basin-wide pumping is by COA Water-level declines have become large and extensive Water-level declines have become large and extensive COA concerned about subsidence, increasing pumping costs, declining water quality COA concerned about subsidence, increasing pumping costs, declining water quality Water-level declines (ft), 1960 to 2002

7. Study Objectives Quantify likely effects of overall change in COA water-management strategy on the regional river-aquifer system Quantify likely effects of overall change in COA water-management strategy on the regional river-aquifer system Determine optimal pumping strategies to achieve specified management objectives for the regional system Determine optimal pumping strategies to achieve specified management objectives for the regional system

8. Available Tools— Flow Model (McAda & Barroll) MODFLOW 2000 MODFLOW 2000 156 rows x 80 columns 156 rows x 80 columns 1 km uniform horizontal spacing 1 km uniform horizontal spacing Steady-state and transient Steady-state and transient Simulates 1900 - 2000 Simulates 1900 - 2000 Summer and winter seasons, 1990 - 2000 Summer and winter seasons, 1990 - 2000 Specified-flow and head- dependent flow boundaries Specified-flow and head- dependent flow boundaries

9. Objective—Determine optimal pumping strategies to achieve regional management objectives

10. Management Objectives 1. Minimize net depletion of aquifer storage 2. Minimize net infiltration from the Rio Grande 3. Minimize net depletion of aquifer storage, with water- level constraints 4. Minimize net depletion of aquifer storage, with constraints on water levels and arsenic concentrations 5. Minimize net depletion of aquifer storage after eliminating river “debt”

11. Approach to Optimization Optimize pumping for 2006-2040 Optimize pumping for 2006-2040 Use projections of demand and surface-water availability provided by COA Use projections of demand and surface-water availability provided by COA Use currently available wells Use currently available wells Optimize pumping on an annual basis by well field Optimize pumping on an annual basis by well field

12. Key Equations for Optimization Composed of decision variables whose values define the solution to the problem Objective function Restricts values decision variables can take Constraint

13. Optimization Model Design Minimize objective function representing combined change in aquifer storage (for assigned annual pumping in 25 well fields) Minimize objective function representing combined change in aquifer storage (for assigned annual pumping in 25 well fields) Observe constraints on: Observe constraints on: -Total annual GW demand -Maximum annual capacity in each well field -Minimum withdrawal from each well field -Water-level decline (no more than 2.5 ft/yr) Assume system response a linear function of rate of withdrawal Assume system response a linear function of rate of withdrawal

14. Optimization Model Results

15. Optimization Model Results (cont.) Recovery of water in storage increased by 242,000 acre-ft (more than 2 years of supply) Recovery of water in storage increased by 242,000 acre-ft (more than 2 years of supply) Increased storage recovery derived from increased river/drain leakage Increased storage recovery derived from increased river/drain leakage Results for 2006-2040