An Integrated Approach for Sustainable Water Management: Demand Forecasting and Reservoir Optimization for Gangapur Dam

This research investigates the forecasting of future water requirements and reservoir storage capacities for sustainable water management in the Gangapur dam command area, Nashik, India. Due to rapid urbanization, intense agricultural expansion, and climate change have put tremendous pressure on water resources, particularly on multipurpose reservoirs such as Gangapur dam. The study integrates hydrological modeling, climate and rainfall data, and GIS-based analysis to provide an accurate prediction framework for future water demand and supply scenarios in the Gangapur command area. The main objective of this study is to analyze historical storage trends, simulating future storage needs under various scenarios, and recommending strategic interventions for sustainable water resource management. Data sources span hydrological, demographic, and agricultural datasets collected from government agencies, meteorological records, and validated institutional reports. The methodology employs advanced forecasting tools and complemented by QGIS for in depth demand, inflow, and spatial analyses. Results indicate that changing cropping patterns, population growth, reservoir sedimentation, and climate variability are expected to further exacerbate existing water stress in the region. Sector-wise demand projections up to 2050 highlight the growing imbalance between supply and demand across agricultural, domestic, and industrial users. Scenario analyses, including wet, normal, dry, and drought years, offer insights into the resilience and sustainability of storage capacities. The research emphasizes the importance of integrated water management, efficiency improvements, and adaptive reservoir operations to maintain reliable supply while ensuring equity and environmental sustainability. It recommends actionable measures for optimizing water release, enhancing irrigation efficiency, reducing non-revenue losses, and incorporating climate resilience into planning. Outcomes from this study aim to inform policymakers, water managers, and local stakeholders in adopting data-driven, climate-resilient strategies for future water security. The research contributes to the Sustainable Development Goals by supporting clean water access and climate action. Ultimately, this work underscores the urgent need for continuous monitoring, innovative management, and holistic forecasting in the supervision of vital water resources in rapidly developing regions.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-30
DOI
https://doi.org/10.5281/zenodo.23057125
Primary Topic
Water resources management and optimization
Type
article
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article

An Integrated Approach for Sustainable Water Management: Demand Forecasting and Reservoir Optimization for Gangapur Dam

Valmik M. Mahajan, Rahul Ashok Shinde, Tushar Pawar, Rushikesh Vijay Kolhe et al.
Zenodo (CERN European Organization for Nuclear Research)
Water resources management and optimization
article

An Integrated Approach for Sustainable Water Management: Demand Forecasting and Reservoir Optimization for Gangapur Dam

Valmik M. Mahajan, Rahul Ashok Shinde, Tushar Pawar, Rushikesh Vijay Kolhe, Nilesh Anil Shinde, Tejas D. Patel
article en

Abstract

This research investigates the forecasting of future water requirements and reservoir storage capacities for sustainable water management in the Gangapur dam command area, Nashik, India. Due to rapid urbanization, intense agricultural expansion, and climate change have put tremendous pressure on water resources, particularly on multipurpose reservoirs such as Gangapur dam. The study integrates hydrological modeling, climate and rainfall data, and GIS-based analysis to provide an accurate prediction framework for future water demand and supply scenarios in the Gangapur command area. The main objective of this study is to analyze historical storage trends, simulating future storage needs under various scenarios, and recommending strategic interventions for sustainable water resource management. Data sources span hydrological, demographic, and agricultural datasets collected from government agencies, meteorological records, and validated institutional reports. The methodology employs advanced forecasting tools and complemented by QGIS for in depth demand, inflow, and spatial analyses. Results indicate that changing cropping patterns, population growth, reservoir sedimentation, and climate variability are expected to further exacerbate existing water stress in the region. Sector-wise demand projections up to 2050 highlight the growing imbalance between supply and demand across agricultural, domestic, and industrial users. Scenario analyses, including wet, normal, dry, and drought years, offer insights into the resilience and sustainability of storage capacities. The research emphasizes the importance of integrated water management, efficiency improvements, and adaptive reservoir operations to maintain reliable supply while ensuring equity and environmental sustainability. It recommends actionable measures for optimizing water release, enhancing irrigation efficiency, reducing non-revenue losses, and incorporating climate resilience into planning. Outcomes from this study aim to inform policymakers, water managers, and local stakeholders in adopting data-driven, climate-resilient strategies for future water security. The research contributes to the Sustainable Development Goals by supporting clean water access and climate action. Ultimately, this work underscores the urgent need for continuous monitoring, innovative management, and holistic forecasting in the supervision of vital water resources in rapidly developing regions.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 16%
Water resources management and optimization
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