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Optimal Management of Groundwater-Surface Water Resources: A Brief Overview. James R. Craig Assistant Professor Dept. of Civil & Environmental Engineering. Outline. Brief overview of groundwater and surface water interactions Optimization problem Common constraints /objectives Discussion

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optimal management of groundwater surface water resources a brief overview

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

James R. Craig

Assistant Professor

Dept. of Civil & Environmental Engineering

outline
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
premise
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
water management
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
conceptual models
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

stream depletion
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

typical gw sw optimization problem
“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
quantity constraints
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
quality constraints
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

current state of practice
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
important issues
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?