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India experienced more flood situations due to the increasing extreme rainfall events over the different Indian River Basins (IRBs) during the last few decades. An Extreme Value Theory (EVT) is used to examine trends of rainfall extremes over the IRBs using long-term observed high-resolution grid-based rainfall (1901-2019) of the India Meteorological Department. The analysis depicts that when generalized extreme value theory (GEV) is applied to annual maximum rainfall over IRBs, statistically significant uniform trends were not seen. The spatial variations in the annual maximum rainfall for the 10-, 30- and 100-year return levels show statistically significant increasing trends over the IRBs. The shifting trend of rainfall extremes from northeast towards the western river basins of IRBs in the last two decades and resulted in damage to life and property on the west coast. The decadal changes in average intensity of dry and wet condition at 12- months running time window reveals that the shifting and increasing pattern of the rainfall extremes events during the last decades of the 20th century (1981-2000) and current decades of the 21st century (2001-2019) over the western ghats and west-flowing river basin leads to several floods situations. This research highlights the significant increasing trend in extreme rainfall events over the IRBs, which may pose a grave risk to agriculture, human life, and predominantly on the vulnerable sections of the society.

The present study aims to analyse future changes in mean maximum and extreme temperature over India using 17 regional climate simulations from CORDEX-SA experiment RCM ensembles at a spatial resolution of 0.5° x 0.5° for mid-term (2041-2060) and long-term (2081-2099) future under RCP 4.5 and RCP 8.5 scenarios. The regional climate simulations of the three RCM ensembles namely IITM-RegCM4, SMHI-RCA4 and MPI-CSC-REMO2009 were first evaluated against observed seasonal maximum temperature (Mar-Jun) during historical period (1971-2005). The datasets were obtained from CCCR-IITM ESGF data node for the study period. The model performance was assessed using standard performance measure statistics such as mean absolute error, root mean square error, mean bias, percentage bias. The RCMs show warm and cold bias in simulating the climatological mean maximum temperature with mean bias ranging from to 8.43°C(warmest) to -37.29°C (coldest) by CNRM-CM5 RCM of IITM-RegCM4 ensemble and by CSIRO-Mk3.6 RCM of SMHI-RCA4 ensemble respectively over the country. Variance scaling bias correction method was applied to correct the bias associated with the RCMs which significantly reduced the RMSE of RCMs from 11.03 (SMHI-RCA4) and 9.17 (IITM-RegCM4) to around zero after bias correction. Future changes assessed in mean maximum temperature show an increase in the range of 0.5°C to 4.5°C during mid-term (2041-2060) and 0.6°C to 5.84°C long-term (2081-2099) future period while under RCP 8.5 the increase ranges from 0.88° C to 5.40° C for mid-term (2041-2060) and 1.31° C to 12.87° C for long-term (2081-2099) period. The most pronounced increase is observed in the northern, eastern and north-eastern region of the country in which highest rise was simulated by IPSL-CM5A-MR(SMHI-RCA4) in northern region of the country for both the scenarios. The study also analyses changes in different ET-SCI indices as a measure of extreme temperature which have increased multi-fold in the future over the country. The study identifies the regions and magnitude of significant climate change signal expected in the mean maximum and extreme temperature in the future. It enhances the understanding and quantification of inter-model uncertainties within CORDEX-SA experiment RCM simulations. The outcomes of the study have both scientific and societal values in building resilience and informed efforts to avert the severe implications posed by increasing extreme temperature and heat events over India. Keywords: Future Climate Change, CORDEX-SA, Regional Climate Model, Bias Correction, Extreme weather events

Enhancing the productivity of rainfed crops, especially rice, while coping with climate adversities and saving critical natural resources is essential for ensuring the food and nutrition security of a growing population. With this context, the present study was undertaken to validate promising farm innovation and adaptation practices used by small-medium landholding farmers for rice cultivation in eastern Uttar Pradesh (UP), north India, as well as to examine the sustainability of innovative practices for large-scale adoption. For this, a 3-year study comprising extensive field surveys and experiments was undertaken to compare single transplantation (ST) and double transplantation (DT) in rice along with organic addition (farm-yard manure, FYM) on crop growth, yield, climate resilience, soil quality, and overall sustainability i.e., social (women involvements and labour productivity), environmental (water productivity and nutrient use efficiency), and economic (benefit:cost ratio) dimensions of sustainability. Field experiments were conducted in triplicate using two local rice varieties (MotiNP-360 and Sampurna Kaveri) in two agroclimatic zones, namely the middle Gangetic plains and the Vindhyan zone, in the Mirzapur district of eastern Uttar Pradesh. The DT practices of rice with and without farm yard manure (FYM) (replacing at a dose of 25% NPK) were evaluated over conventional methods of rice cultivation (i.e., ST, as control) and analysis was done periodically. The DT practice improved growth (p 0.05), percent fertile tiller and grain (p 0.05), and rice yield (15-20% higher than ST), while also improving soil quality, yield indices, water and labour productivity, and the benefit-cost ratio. The DT practice also resulted in early maturity (10-15 days earlier than ST), created more labour days for women, decreased lodging and pest/disease incidence, as well as a subsequent reduction in the use of synthetic chemical pesticides and associated environmental costs. Importantly, the residual effects of FYM application significantly improved (p 0.05) the grain yield in subsequent years of cropping. Optimizing DT cultivation practices, preferably with FYM input for various agro-climatic regions, is essential for large-scale sustainable rice production under changing climatic conditions.