Departmental Seminar on 03.06.2026

Efficient and adaptive water allocation is a critical challenge for sustainable watershed management under climate variability, drought risk, urban and industrial growth, agricultural pressure, and ecosystem protection needs. This study proposes an AI-assisted, scenario-based decision support framework for integrated water management within the Water–Energy–Food–Ecosystem (WEFE) Nexus. The framework focuses on the Porsuk Sub-basin, where population growth, Organized Industrial Zones, agricultural activities, wastewater infrastructure, and ecosystem flow requirements create complex trade-offs among competing water uses. The main contribution of this study is its integration of AI-assisted future scenario generation, fuzzy logic-supported WEFE priority configuration, and multi-objective optimization into a basin-specific framework for adaptive water allocation. Unlike conventional nexus assessments that mainly evaluate existing interactions, the proposed framework enables future development alternatives to be tested before implementation and translates basin-specific priorities into practical water allocation plans. The framework integrates basin-scale data on surface water and groundwater availability, sectoral demands, wastewater treatment and reuse capacities, land use, population and industrial development trends, climate projections, and ecosystem requirements. Future scenarios are constructed by combining climate pathways, possible development alternatives such as new or expanded Organized Industrial Zones, population and land-use changes, water source changes, and water management strategies derived from previous Circular Water Economy assessments. Reduce and recycle strategies, particularly industrial wastewater recycle in Organized Industrial Zones, are considered adaptive options due to their potential to improve ecosystem flow conditions and WEFE performance. Scenario-specific indicators representing water, energy, food, ecosystem, social, and economic dimensions are evaluated through fuzzy logic-supported priority configuration. These priorities guide optimization under water balance, demand, groundwater, environmental flow, infrastructure, and land-use constraints. The expected outcome is a decision support framework for comparing scenarios, identifying water-scarce areas and sectoral trade-offs, and generating priority-based water allocation plans under future uncertainty.