Projected climate extremes over agro-climatic zones of Ganga River Basin under 1.5, 2, and 3° global warming levels.

Recurring floods, droughts, heatwaves, and other hydro-meteorological extreme events are likely to be increased under the climate change scenarios. The increased risk of these extreme events might have more exposure to the population; thus, it is important to discuss such extreme events and their projected behavior under a changing climate scenario. In the present study, we have computed the extreme precipitation and temperature indices over the 10 agro-climatic zones falling under the Ganga River Basin (GRB)utilizing a high-resolution daily gridded temperature and precipitation multi-model ensembled CMIP6 dataset (0.25° × 0.25°) under global warming levels of 1.5 °C, 2 °C, and 3 °C. We found that the annual daily minimum temperature (TNN) showed a higher rise of about 67% than the maximum temperature (TXX) of 48% in GRB. The basin also experiences a greater increase in the frequency of warm nights (TN90P) of about 67.71% compared to warm days (TX90P) of 29.1% for the 3 °C global warming level. Along with extreme indices, the population exposed due to the impact of the extreme maximum temperature has also been analyzed for progressive warming levels. Population exposure to extreme temperature event (TXX) has been analyzed with 20-year return period using GEV distribution method. The study concludes that the exposed population to extreme temperature event experienced an increase from 46.99 to 52.16% for the whole Ganga Basin. Consecutive dry days (CDD) and consecutive wet days (CWD) both show a significant increasing trend, but CWD has a significant increase in the majority of the zones, while CDD shows a significant decreasing trend for some of the zones for three warming levels periods. Extreme climate indices help to understand the frequency and intensity of extreme weather events such as heavy rainfall, droughts, and heatwaves to develop early warning systems and adaptation strategies to mitigate such events.

Future prediction of water balance using the SWAT and CA-Markov model using INMCM5 climate projections: a case study of the Silwani watershed (Jharkhand), India.

The aim of this research was to simulate the future water balance of the Silwani watershed, Jharkhand, India, under the combined effect of land use and climate change based on the Soil and Water Assessment Tool (SWAT) and Cellular Automata (CA)-Markov Chain model. The future climate prediction was done based on daily bias-corrected datasets of the INMCM5 climate model with Shared Socioeconomic Pathway 585 (SSP585), which represent the fossil fuel development of the world. After a successful model run, water balance components like surface runoff, groundwater contribution to stream flow, and ET were simulated. The anticipated change in land use/land cover (LULC) between 2020 and 2030 reflects a slight increase (3.9 mm) in groundwater contribution to stream flow while slight decrease in surface runoff (4.8 mm). The result of this research work helps the planners to plan any similar watershed for future conservation.