Assessment of Water Supply and Demand in a Watershed with Climate Change Impacts on Potential Adaptation Strategies
摘要
The paper highlights the need to implement water management techniques in the Nuh watershed, covering an area of Mewat and Gurgaon in northwest India. The primary goal is to optimize the utilization of available water resources to sustain agriculture in the study area facing chronic water scarcity, ensuring long-term environmental viability. “Water Evaluation and Planning (WEAP) model was employed to comprehensively analysis of water supply, demand and total water availability for simulating crop water requirements. The WEAP model was customized and set as base year 2010. The model was calibrated and executed using the PEST tool, in-built into WEAP. This calibrated model was used for estimating future water demands and unmet by integrating climate projections from 2011 to 2050, based on the IPCC scenario RCP 4.5 from the GFDL-ESM2M model, it predicts substantial variations in rainfall in the forthcoming years, directly influencing water availability for agriculture and subsequent crop yields “it predicts substantial variations in rainfall in the forthcoming years, which directly influencing water availability for agriculture and subsequent crop yields” .Statistical analysis was carried out to evaluate the performance of the developed WEAP models for flow simulation NSE, RMSE and R2 values for the model are 0.99, 0.3, and 0.81, respectively. The agricultural sector faces significant unmet demand as water supply prioritizes livestock, intensifying pressure on water resources and leading to excessive groundwater extraction. To address these challenges, water management strategies are proposed, emphasizing water-efficient crops, improved farming practices, and optimal suggestions for the number and locations of water bodies based available water resource, especially considering the semi-arid regions. Additionally, WEAP models suggested to explore various stress/deficit irrigation scenarios to enhance overall crop yields.