Optimal Management of Groundwater-Surface Water Resources: A Brief Overview

1. Optimal Management of Groundwater-Surface Water Resources:A Brief Overview James R. Craig Assistant Professor Dept. of Civil & Environmental Engineering

2. Outline • Brief overview of groundwater and surface water interactions • Optimization problem • Common constraints /objectives • Discussion • Current practice • Important considerations • A global search algorithm, DDS, presented by Prof. Tolson

3. Premise • Groundwater and surface water resources are intimately connected • Management of either resource requires knowledge of the impact of management decisions on both • Due to the complexity of these systems, predictive models should be used to facilitate decision making • Management problem posed as a “simulation-optimization” exercise

4. Water Management • Water managers are tasked with determining how best to obtain and allocate our water resources – who gets water, how much they get, and where they can get it from. • In the case of groundwater allocation, the selection of well locations and pumping schedules can • impact the quantity and distribution of water present in streams, wetlands, or aquifers and • determine the quality of both the pumped water and affected areas

5. Conceptual Models Gaining Stream Groundwater and surface water exchanges occur in both directions-Behavior is generally transient and can rarely be predicted in a purely deterministic manner Losing Streams

6. Stream Depletion Recharge/Infiltration Stream Depletion: Lowers water levels, reduces base flow, effects wetland ecosystems “Safe Yield”: Pumping balanced by recharge Drying out of well- Water rights infringement Typical systems dominated by 10-100s of wells, extensive stream networks and complicated exchange patterns influenced (in part) by transient precipitation, treated either deterministically or stochastically

7. “Typical” GW-SW optimization problem • Maximize groundwater withdrawal with minimal impact to surface water resources • By changing: • Pumping rates, schedules, & locations • Surface irrigation and storage measures • Subject to multiple constraints: • Groundwater quantity & quality • Surface water quantity & quality • Cost

8. Quantity Constraints • Groundwater quantity / distribution • Sustainable pumping rates (or close enough) • No water rights infringements (penalty function) • Surface water quantity / distribution • Water levels must typically be maintained high enough to sustain fish and bird habitats, recreation • Flow rates have to be within desirable limits for • Hydropower • Dilution of agricultural & industrial waste • Sediment transport • All impacts propagate downstream – watershed-scale management is common

9. Quality Constraints • May wish to minimize or disallow amount of surface water allowed to reach pumping wells • Reduces/removes presence of surface water contaminants • Seawater intrusion From www.lenntech.com

10. Current State-of-Practice • “Manual optimization” still quite common • Black-box management tools (rather than physics-based models) used to test “what-if” scenarios • State-of-the science • **Oversimplified Systems** • The standard heuristic toolbox • GA, PSO, SA, Integer programming, etc., etc. • Limited by the ability to solve real-world problems in a reasonable time frame

11. Important Issues • The subsurface is unknown! • How can the optimization process explicitly address the presence of uncertainty? • The systems are often large (watershed scale) and poorly characterized • Computationally expensive – How to develop surrogate models? • “Perfect” Global optimum is not the real goal • How to replace the chase for perfection with the chase for “good enough”? • Appropriate formulation of the objective function is an issue • Philosophical question: How to quantify ecological damage? • What are the impacts of changing the objective function? • Long-term research objective: • How to develop multi-objective tradeoff curves (e.g., cost vs. extraction vs. environmental quality) under the presence of fundamental uncertainty at watershed scales?