Optimized water allocation in persistent severe climatic conditions: A novel metaheuristic approach

Area of Science:

• Environmental Science
• Water Resource Management
• Climate Change Adaptation

Background:

• Increasing global water tensions necessitate robust management frameworks for persistent harsh conditions.
• Existing studies often lack adaptability for long-lasting severe climatic events and detailed sector-specific strategies.
• A comprehensive approach is vital to balance diverse water resources and demands across agriculture, industry, and the environment.

Purpose of the Study:

• To design a novel, multi-objective, evolutionary-based framework for optimal water management during continuous extreme climate events.
• To provide detailed cultivation patterns and reservoir management strategies for sustainable water allocation.
• To establish sustainability, economic welfare, and equitability as core allocation principles.

Main Methods:

• Utilizing complex, metaheuristic algorithms to manage big data and optimize intricate water systems.
• Adopting a comprehensive, detailed, and evolutionary approach for multi-objective water management.
• Applying the framework to the Karkheh basin case study for validation.

Main Results:

• Full recovery of the Hoor al-Azim wetland requires drastic reductions in agricultural water demand within the Karkheh basin.
• A 10% increase in agricultural net benefit correlates with a 40% rise in the Gini coefficient, indicating significant equity concerns.
• The framework demonstrates the trade-offs between economic gains in agriculture and ecological/equitable water allocation.

Conclusions:

• The developed framework offers a precise and adaptable solution for water management under prolonged extreme climate conditions.
• Balancing agricultural water demand with ecological needs (wetland recovery) and social equity is a critical challenge.
• Policy interventions must address the inverse relationship between agricultural economic benefits and equitable water distribution.