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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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Multi-Constrained Catchment Scale Optimization of Groundwater Abstraction Using Linear Programming.
Mehrdis Danapour1,2, Michael N Fienen3, Anker Lajer Højberg1
1Department of Hydrology, Geological Survey of Denmark and Greenland, Copenhagen, Denmark.
Ground Water
|February 3, 2021
Summary
This study developed a groundwater abstraction optimization framework to balance irrigation needs with environmental flow requirements. It ensures sustainable water use by minimizing streamflow reduction, protecting aquatic ecosystems.
Area of Science:
- Hydrology
- Environmental Science
- Water Resource Management
Background:
- Global water demand pressures freshwater ecosystems.
- Groundwater abstraction is vital for irrigation but can deplete resources and harm aquatic life.
- Maintaining environmental flow is crucial for groundwater-dependent ecosystems.
Purpose of the Study:
- To develop a holistic, catchment-scale framework for optimizing groundwater abstraction.
- To integrate economic benefits with environmental flow constraints.
- To provide an objective tool for water resource management.
Main Methods:
- A spatially distributed, coupled groundwater-surface water model was employed.
- A constrained optimization algorithm, including linear programming, was utilized.
- Balanced K-Means clustering and Bayesian linear theory were implemented for efficiency and risk assessment.
Main Results:
- The framework enables spatially explicit groundwater abstraction optimization.
- It successfully incorporates streamflow reduction criteria (Q95, Q50) for numerous stream locations.
- Optimized abstraction plans were generated considering environmental flow needs.
Conclusions:
- Integrated modeling and optimization offer valuable guidance for water practitioners.
- The developed framework supports effective groundwater management plans.
- Balancing abstraction with environmental flow is key to maintaining ecosystem health.
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