Implication of climate change on crop water requirement in the semi-arid region of Western Maharashtra, India.

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 the 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 ET₀ 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 (ET₀). Furthermore, in conjunction with the crop coefficient (K_c) equation, it calculates crop evapotranspiration (ET_c)/CWR. The predictor variables were extracted from the National Centre for Environmental Prediction (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 ET₀ indicated an increase in mean annual ET₀ 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 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 significance of this research lies in its contribution to understanding the potential impacts of climate change at a regional level. This study provides valuable insights into the expected changes in water demand for key crops. The research also manifests implementing an identical methodology for downscaling other environmental parameters using a similar approach. [ABSTRACT FROM AUTHOR]