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

Authors

  • S. A. Choudhari JSPM Rajarshi Shahu College of Engineering
  • R. U. Kamodkar Govertment Polytechnic Nashik, MSBTE, Maharashtra State, India.
  • J. B. GURAV Amrutvahini College of Engineering, Sangamner, SPPU Pune, Maharashtra State, India
  • D. G. Regulwar MIT, Chhatrapati Sambhajinagar(Aurangabad) 431005, Maharashtra State, India
  • P. Anand Raj National Institute of Technology, Warangal, 506004, India

DOI:

https://doi.org/10.26437/ckwryc65

Keywords:

Environment. fuzzy. hydropower. optimisation. reservoir

Abstract

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.

Author Biographies

  • S. A. Choudhari, JSPM Rajarshi Shahu College of Engineering

    Prof. Sumant Choudhari is an Associate Professor with  JSPM Rajarshi Shahu College of Engineering, Tathawade, SPPU Pune, Maharashtra State, India.

  • R. U. Kamodkar, Govertment Polytechnic Nashik, MSBTE, Maharashtra State, India.

    R. U. Kamodkar is a Senior  Lecturer with the Government  Polytechnic Nashik, MSBTE, Maharashtra State, India.

  • J. B. GURAV, Amrutvahini College of Engineering, Sangamner, SPPU Pune, Maharashtra State, India

    Prof. J.B. Gurav is a Professor at  Amrutvahini College of Engineering, Sangamner, SPPU Pune, Maharashtra State, India

  • D. G. Regulwar, MIT, Chhatrapati Sambhajinagar(Aurangabad) 431005, Maharashtra State, India

    Prof. D. G. Regulwar is the Dean  incharge of Research & Development and Innovation, MIT, Chhatrapati Sambhajinagar(Aurangabad) 431005, Maharashtra State, India.

  • P. Anand Raj, National Institute of Technology, Warangal, 506004, India

    Prof.  P. Anand Raj is a  former Professor at the  Water and Environment Division, Department of Civil Engineering, National Institute of Technology, Warangal, India

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Published

06-11-2025

How to Cite

Performance of the Reservoir System in River Sub-Basin for Uncertain Parameters within a Partially Fuzzy Environment. (2025). AFRICAN JOURNAL OF APPLIED RESEARCH, 11(5), 511-529. https://doi.org/10.26437/ckwryc65

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