Performance of the Reservoir System in River Sub-Basin for Uncertain Parameters within a Partially Fuzzy Environment

Purpose: To develop a fuzzy multi-objective optimisation framework for improving the operational efficiency of interconnected multi-reservoir systems, with a focus on balancing irrigation and hydropower demands under uncertainty. Design/Methodology/Approach: The study applies fuzzy linear programming within a multi-objective optimisation model (MOFUOPT), built using LINGO software. The framework addresses uncertainties in system parameters, such as resource availability and demand coefficients. The model is applied to a real-world case—the Godavari sub-basin in Maharashtra, India—featuring four interconnected reservoirs in a series-parallel configuration. The objectives include maximising irrigation releases and hydropower generation; both treated as fuzzy goals. Performance is evaluated using statistical indicators and reliability, resilience, and vulnerability (RRV) metrics. Findings: The fuzzy multi-objective optimisation model effectively handles uncertainties and provides optimal reservoir operation strategies that balance irrigation and hydropower requirements. The results demonstrate improved system performance under variable water and power demands, highlighting the value of fuzzy modelling in complex water resource systems. Research Limitation: The model is limited to monthly time-step simulations and focuses only on two objectives. The broader integration of ecological or flood control objectives and real-time data could enhance the model's applicability. Practical Implication: The proposed MOFUOPT model provides water resource managers with a decision-support tool to optimise reservoir operations under uncertainty, contributing to better planning in water-scarce and energy-dependent regions. Social Implication: Efficient reservoir operation strategies help ensure equitable water distribution for agriculture and a reliable hydropower supply, benefiting rural communities and supporting regional development goals. Originality/Value: This study introduces a novel integration of fuzzy logic and multi-objective linear programming for reservoir system optimisation, offering a robust and adaptable framework for sustainable water resource management under uncertainty.