Water is one of the most important ecosystem services because it is essential for food and energy production. The Tungabhadra basin, located in peninsular India, has a variety of challenges, including inter-basin water-sharing issues, low agricultural productivity and value, and rising need for renewable energy production. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) water yield model is used to analyze the consequences of climate change on water related services such as water yield and hydropower generation in the densely populated Tungabhadra basin. The impact of climate change on water supply services is studied for the period 1971-2000 as well as the future period 2021-2040. The model is calibrated using streamflow data collected at the Bawapuram gauge station in Telangana and there is a strong correlation between observed and simulated flow. The water yield for the entire basin declined by 33 and 50% under the Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios, respectively. The RCP 4.5 scenario reduces hydropower production and its Net Present Value (NPV) by 41 to 59%, whereas the RCP 8.5 scenario reduces production and NPV by 56 to 67%. The assessment of ecosystem services at the catchment scale revealed that the basin could be vulnerable to climate change due to a dramatic drop in ecosystem services. The methodology developed in this study can be applied to other river basins where quantifying ecosystem services is critical.

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<p>The biogeochemical source and sink dynamics of terrestrial ecosystems play an important role in balance of carbon in the atmosphere. These biogeochemical processes such as carbon, water and energy cycles were affected by climate change and hydroclimatic disturbances. Hence, it is essential to understand the spatiotemporal variations and drivers of different ecohydrological indicators (EHIs) which links the carbon, water and energy cycles. This study assesses the three EHIs, namely water use efficiency (WUE<sub>e</sub>), rain use efficiency (RUE<sub>e</sub>), and light use efficiency (LUE<sub>e</sub>), as well as their drives based on Net Primary Productivity (NPP) in India from 2002 to 2017 at river basin, climatic zone, and land cover scales. All the three EHIs were found to be higher in forest ecosystems which are high productive regions. The mean annual WUE<sub>e</sub> and RUE<sub>e</sub> showed a slightly decreasing trend, and the mean annual LUE<sub>e</sub> experienced a slightly increasing trend. The ecosystem-based study shown that WUE<sub>e</sub> and LUE<sub>e</sub> in semi-arid zones and shrubland ecosystems experienced a positive trend. A similar trend was observed in RUE<sub>e</sub> for arid and shrubland ecosystems. The drivers investigated includes 11variables, CO<sub>2</sub> concentrations, evapotranspiration (ET), humidity, leaf area index (LAI), normalized difference vegetation index (NDVI), precipitation (PRECIP), soil moisture (SM), solar radiation (SR), temperature (TEMP), vapor pressure deficit (VPD), and wind speed (WS). TEMP and SR were found to be more sensitive drivers of EHIs. Other drivers such as VOD, SM and humidity also played a significant role in local scales. This study will enhance our understanding of variations in EHIs and their mechanisms which can be a reference in predicting the ecosystem responses and resilience to changing climate and climate extremes.</p>

<p>Extreme events are becoming more frequent, intense, and prolonged, with significant impacts on human lives, the environment, and regional development. Rising temperature due to global warming is one the crucial factors causing the rise in the frequency and severity of extreme events. The worst extreme events are caused by a combination of more than one factor/variable, which makes it essential to study the co-occurrences of extremes, also known as compound extremes. In the present study, four compound extremes are assessed over India for the time period of 1971-2020 using two different statistical approaches, empirical approach, and multivariate distribution analysis. The variables used are temperature and precipitation, having a resolution of 0.25° × 0.25°. Firstly, the empirical analysis of four compound extremes, Hot-Dry, Hold-Wet, Cold-Dry, and Cold-Wet, is done by providing threshold percentiles (25<sup>th</sup> and 75<sup>th</sup>) to count the exceedance, and Mann Kendall's trend, p-value, and Sen's slope are calculated to assess the changes and significance of the extremes. Next, multivariate distribution analysis using Copula is conducted to study the dependency between temperature and precipitation. The results indicate a significant increase in compound Hot-Dry and Hot-Wet extremes across the country, with a decrease in Cold-Dry and Cold-Wet conditions. The changes in extremes are more pronounced in the later period (1996-2020) than in the earlier period (1971-1995). This study provides insight into the evaluation of compound extremes in India over the past 50 years, which can help us understand the changes and frequency of their occurrence.</p>

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