Climate change profoundly affects water resource allocation by disrupting the availability, distribution, and quality of water across various regions. Optimal allocation of water resources represents a comprehensive strategy for water resource management by addressing the intricate connections between water allocation systems and their repercussions on the environment, society, and economy. In this study, an Optimal Water Resources Management (OWRM) framework was developed, focusing on the optimal allocation of water resources and crop planting structures across various sectors. The Munneru river basin, located in the lower Krishna River region of India, was selected as the study area to validate the proposed framework. Five distinct water-demanding sectors-irrigation, domestic, livestock, industrial, and irrigation water requirements for major agricultural seasons-were identified in the study area, and their sectoral water demands were calculated at the basin level. The crop water and irrigation water requirements for various crops were estimated using the CROPWAT tool, while the framework also optimized crop planting structures to maximize returns and resource efficiency. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was applied, with two objectives focused on equity and economic value. Superior solutions were then identified using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The OWRM framework was applied after identifying critical cases of water availability in future periods under climate change scenarios. Through this integrated approach, an average annual increase of 52.6% in agricultural sector returns was achieved for the simulation period (2016-17 to 2022-23). For a condition of providing at least 90% water supply to each sector, the optimal crop patterns led to revenue increases of 136.4%, 59.2%, and 74.7% compared to actual revenues for the water years 2020-21, 2021-22 and 2022-23 respectively. The developed OWRM methodology can be applied to other basins across the world that are impacted by climate change.
Keywords: CROPWAT tool; Climate change; Multi-objective optimization; NSGA-II; OWRM; Sectoral water demands; TOPSIS.
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