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Climate change and human activities have massively impacted the hydrological cycle. Thus, it is of the greatest concern to examine the effect of climate change on water management, especially at the regional level, to understand possible future shifts in water supply and water-related crises and support regional water management. Fortunately, there is a high degree of ambiguity in determining the effect of climate change on water requirements. In this paper, the Statistical DownScaling (SDSM) model is applied to simulate the potential impact of climate on crop water requirements (CWR) by downscaling ET 0 in the region of Western Maharashtra, India, for the future periods, viz., the 2030s, 2050s, and 2080s, across three meteorological stations (Pune, Rahuri, and Solapur). Four crops, i.e., cotton, soybean, onion, and sugarcane, were selected during the analysis.The Penman-Monteith equation calculates reference crop evapotranspiration (ET 0 ). Further, in conjunction with the crop coe cient (Kc) equation, it calculates crop evapotranspiration (ETc)/CWR. The predictor variables were extracted from the NCEP reanalysis dataset for 1961-2000 and the HadCM3 for 1961-2099 under the H3A2 and H3B2 scenarios. The results indicated by SDSM profound good applicability in downscaling due to satisfactory performance during calibration and validation for all three stations. The projected ET 0 indicated an increase in mean annual ET 0 compared to the present condition during the 2030s, 2050s, and 2080s. The ET 0 would increase for all months (in summer, winter, and pre-monsoon seasons) and decrease from June to September (monsoon season). The estimated future CWR shows variation in the range for cotton (-0.97 to 2.48%), soybean (-2.09 to 1.63%), onion (0.49 to 4.62%), and sugarcane (0.05 to 2.86%).

The hydrological cycle has been massively impacted by climate change and human activities. Thus it is of the highest concern to examine the effect of climate change on water management, especially at the regional level, to understand possible future shifts in water supply and water-related crises, and to provide support for regional water management. Fortunately, there arises a high degree of ambiguity in determining the effect of climate change on water requirements. In this paper, the Statistical DownScaling (SDSM) model is applied to simulate the potential impact of climate on crop water requirement (CWR) by downscaling ET0 in the region of Western Maharashtra, India for the future periods viz., 2030s, 2050s, and 2080s across three meteorological stations (Pune, Rahuri, and Solapur). Four crops i.e. cotton, soybean, onion, and sugarcane are selected during the analysis. The Penman-Monteith equation is used to calculate reference crop evapotranspiration (ET0), which further in conjunction with the crop coefficient (Kc) equation is used to calculate crop evapotranspiration (ETc) / CWR. The predictor variables are extracted from the NCEP reanalysis dataset for the period 1961-2000 and the HadCM3 under H3A2 and H3B2 scenarios for the period of 1961 – 2099. The results indicated by SDSM profound good applicability in downscaling due to satisfactory performance during calibration and validation for all three stations. The projected ET0 indicated an increase in mean annual ET0 as compared to the present condition during the 2030s, 2050s, and 2080s. The ET0 would increase for all months (in summer, winter, and pre-monsoon seasons) and decrease from June to September (monsoon season). The estimated future CWR show variation in the range for cotton (-0.97 to 2.48%), soybean (-2.09 to 1.63 %), onion (0.49 to 4.62 %), and sugarcane (0.05 to 2.86 %).