Multi-objective conflict resolution optimization model for reservoir's selective depth water withdrawal considering...

Area of Science:

• Environmental Engineering
• Water Resource Management
• Operations Research

Background:

• Water resource management faces complex conflicts between diverse user demands.
• Reservoir operations significantly impact downstream water quality and thermal stratification.
• Optimizing water allocation requires balancing user needs with environmental quality objectives.

Purpose of the Study:

• To develop a multi-objective simulation-optimization model for conflict resolution among water users.
• To optimize river water quality through selective depth water withdrawal from reservoirs.
• To integrate game theory and decision-making methods for effective water resource management.

Main Methods:

• A leader-follower game model incorporating Nash-Harsanyi bargaining theory for user competition.
• Simulation of water quality and temperature using the calibrated CE-QUAL-W2 model.
• Development and validation of Artificial Neural Network (ANN) surrogate models coupled with NSGA-II optimization.
• Application of AHP, PROMETHEE, and TOPSIS for selecting the optimal compromise solution.

Main Results:

• Selective withdrawal from multiple reservoir outlets effectively optimizes water allocation among agricultural, domestic, and industrial users.
• The model successfully balances competing stakeholder interests with water quality preservation.
• ANN surrogate models accurately predicted water quality variables based on CE-QUAL-W2 simulations.
• The top reservoir outlet (181 m) demonstrated desirable water quality characteristics.

Conclusions:

• Multi-objective optimization using selective depth withdrawal is a viable strategy for resolving water user conflicts.
• Integrating simulation, optimization, and decision-making tools enhances reservoir management.
• Strategic water withdrawal from different depths can mitigate thermal stratification and improve overall water quality.