Future projection of  extreme climate events using various general circulation model scenarios over the Mahi River Basin, India

The authors have analyzed twentieth-century precipitation extreme events from the climatic models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) generated by NASA (NEX-GDDP). This study is focused on the long west flowing perennial Mahi River Basin (MRB) has great ecologically and economically significance basin of India. A precipitation extreme is quantified using the Expert Team on Climate Change Detection and Indices (ETCCDI) index. The most suitable Global Climate Models (GCMs), INMCM-4, MRI-CGCM3 and ensemble mean (Root Mean Square-0.075 mm/day, Correlation Coefficient-0.9, Standard Deviations-0.75mm/day) were applied for base period (1981-2010) and near future projection (2011-2040). The precipitation extreme events in term of Consecutive Dry Days (CDD), Annual maximum 1-day precipitation amount in day (RX1) and Annual maximum 5-day precipitation amount in days (RX5), Simple Daily Intensity Index (SDII) as well as maximum annual number of Consecutive Wet Days (CWD) are overestimated whereas, 10 Rainy days with heavy precipitation in days (R10) and 20 Rainy days with very heavy precipitation in days (R20) are overestimated in future (2011-2040) with respect to (1981-2010). The spatial extent of precipitation extreme indicated that, CDD values are increases in N-W region of Rajasthan and Gujarat while CWD, increases in Madhya-Pradesh. Consequently, SDII decreases in all region. Further, the RX1, RX5 along with R10 and R20 day precipitation decreases all region of MRB. Thus, overall finding indicated the CDD decrease with increases CWD may be good for agriculture and local society also. In addition, SDII decreases same manner in all the region indicated precipitation intensity decreases, which affect the hydrological cycle. Similarly, RX1 and RX5 represented that low precipitation, indicates that the sufficient amount of water is needed to manage the irrigation scheduling for increment of crop productivity. The changes in R10 and R20 day precipitation have affect the geographic condition. Thus, the scope of developing the extreme climate indices would be beneficial for farmers who are the main stakeholders in agriculture as well as it will help in water resource developer and disaster preparedness.