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Covering sixty years (1955–2016), this paper analyzed the spatio-temporal trends of daily annual and seasonal means of precipitation, temperature, and extreme climate indices. The long-term decadal change analysis was carried out in two timeframes for consecutive analysis periods of 1955–1985 and 1986–2016 to capture the relative regional variations. The trends were evaluated using the modified Mann-Kendall (MMK) and Sen's slope (SS) statistical tests. The pattern visualized on maps was assessed for regions and districts located in the four states of the Indian Himalayan Region. The results revealed significant increases in the annual mean precipitation (1.61 mm/year) and temperature (0.07°/year) in Uttarakhand, followed by Himachal Pradesh from 1986 to 2016. The seasonal monsoonal precipitation showed a significantly increasing trend in parts of Himachal Pradesh, followed by Uttarakhand. The maximum and minimum temperature values increased in all the states, increasing temperature extremes. Significant trends in climate indices were observed in the second period of analysis. A rise of 0.02 °C/year in temperature extremes was observed in Uttarakhand. There is a progressive rise in precipitation indices, specifically in Uttarakhand (0.49 mm/year), and a drop in cold extremes with an increase of hot events in most states. The spatio-temporal variations were driven by multiple dominant mechanisms like orography, anthropogenic activities, land-use changes, teleconnections, and the emission of greenhouse gases. This study highlights the influence of climate change in different divisions of the Himalayas.

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<p>Groundwater is a major source of water supply over most regions, accounting for nearly one-third of all water abstraction globally. However, due to overreliance on this resource, many aquifers around the United States have experienced rapid depletion, while some aquifers have seen increasing water levels due to extensive recharge efforts. It is essential to have a comprehensive understanding of the rate at which groundwater storages are changing to assess the potential availability of groundwater in the future. In this work, we estimate groundwater storage changes across more than 1000 watersheds over the US from a proposed algorithm for baseflow extracted using streamflow and precipitation observations. We also study the spatial and temporal variations in the characteristic of baseflow recession. We compare the storage change estimated from baseflows with those obtained from the estimates from the Gravity Recovery and Climate Experiment (GRACE) and observations from monitoring wells. The results help in validating the application of the proposed baseflow-based storage estimates in different aquifers and climatic regions. The proposed approach is simple and computationally efficient for estimating baseflows and groundwater storage changes in poorly-gauged watersheds.</p>

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