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The study investigates the future climate change in the Jammu and Kashmir (J&K) Himalaya, India, by the end of the twenty-first century under 3 emission scenarios and highlights the changes in the distribution of the prevalent climate zones in the region. The multi-model climate high-resolution projections for the baseline period (1961–1990) are validated against the observed climate variables from 8 meteorological stations in the region. The temperature projections from the GFDL CM2.1 model are found in good agreement with the observations; however, no single model investigated in the present study reasonably simulates precipitation and therefore multi-model ensemble is used for precipitation projections. The average annual temperature is projected to increase by 4.5 °C, 3.98 °C, and 6.93 °C by the end of the twenty-first century under A1B, RCP4.5, and RCP8.5 scenarios, respectively. In contrast, an insignificant variation in precipitation projection is observed under all the 3 scenarios. The analysis indicates that, unlike the 13 climate zones under the updated Köppen-Geiger climate classification scheme, the J&K Himalaya broadly falls into 10 main climate zones only namely, “3 subtropical (~ 11%), 4 temperate (~ 19%), and 3 cold desert (~ 70%) zones”. The projected climate change under the 3 emission scenarios indicates significant changes in the distribution of prevalent climate zones. The cold desert climate zone in the Ladakh region would shrink by ~ 22% and correspondingly the subtropical and temperate zones would expand due to the projected climate change. This information is vital for framing robust policies for adaptation and mitigation of the climate change impacts on various socio-economic and ecological sectors in the region.

The local weather and climate of the Himalayas are sensitive and interlinked with global-scale changes in climate, as the hydrology of this region is mainly governed by snow and glaciers. There are clear and strong indicators of climate change reported for the Himalayas, particularly the Jammu and Kashmir region situated in the western Himalayas. In this study, using observational data, detailed characteristics of long- and short-term as well as localized variations in temperature and precipitation are analyzed for these six meteorological stations, namely, Gulmarg, Pahalgam, Kokarnag, Qazigund, Kupwara and Srinagar during 1980–2016. All of these stations are located in Jammu and Kashmir, India. In addition to analysis of stations observations, we also utilized the dynamical downscaled simulations of WRF model and ERA-Interim (ERA-I) data for the study period. The annual and seasonal temperature and precipitation changes were analyzed by carrying out Mann–Kendall, linear regression, cumulative deviation and Student's t statistical tests. The results show an increase of 0.8 ∘C in average annual temperature over 37 years (from 1980 to 2016) with higher increase in maximum temperature (0.97 ∘C) compared to minimum temperature (0.76 ∘C). Analyses of annual mean temperature at all the stations reveal that the high-altitude stations of Pahalgam (1.13 ∘C) and Gulmarg (1.04 ∘C) exhibit a steep increase and statistically significant trends. The overall precipitation and temperature patterns in the valley show significant decreases and increases in the annual rainfall and temperature respectively. Seasonal analyses show significant increasing trends in the winter and spring temperatures at all stations, with prominent decreases in spring precipitation. In the present study, the observed long-term trends in temperature (∘Cyear-1) and precipitation (mm year−1) along with their respective standard errors during 1980–2016 are as follows: (i) 0.05 (0.01) and −16.7 (6.3) for Gulmarg, (ii) 0.04 (0.01) and −6.6 (2.9) for Srinagar, (iii) 0.04 (0.01) and −0.69 (4.79) for Kokarnag, (iv) 0.04 (0.01) and −0.13 (3.95) for Pahalgam, (v) 0.034 (0.01) and −5.5 (3.6) for Kupwara, and (vi) 0.01 (0.01) and −7.96 (4.5) for Qazigund. The present study also reveals that variation in temperature and precipitation during winter (December–March) has a close association with the North Atlantic Oscillation (NAO). Further, the observed temperature data (monthly averaged data for 1980–2016) at all the stations show a good correlation of 0.86 with the results of WRF and therefore the model downscaled simulations are considered a valid scientific tool for the studies of climate change in this region. Though the correlation between WRF model and observed precipitation is significantly strong, the WRF model significantly underestimates the rainfall amount, which necessitates the need for the sensitivity study of the model using the various microphysical parameterization schemes. The potential vorticities in the upper troposphere are obtained from ERA-I over the Jammu and Kashmir region and indicate that the extreme weather event of September 2014 occurred due to breaking of intense atmospheric Rossby wave activity over Kashmir. As the wave could transport a large amount of water vapor from both the Bay of Bengal and Arabian Sea and dump them over the Kashmir region through wave breaking, it probably resulted in the historical devastating flooding of the whole Kashmir valley in the first week of September 2014. This was accompanied by extreme rainfall events measuring more than 620 mm in some parts of the Pir Panjal range in the south Kashmir.

Mass balance is a good indicator of glacier health and sensitivity to climate change. The debris-covered Hoksar Glacier (HG) in the Upper Indus Basin (UIB) was studied using direct and geodetic mass balances. During the 5-year period from 2013 to 2018, the glacier’s mean in situ mass balance (MB) was − 0.95 ± 0.39 m w.e. a −1 . Similarly, the glacier’s mean geodetic MB from 2000 to 2012 was − 1.20 ± 0.35 m w.e. a −1 . The continuously negative MB observations indicated that the HG is losing mass at a higher rate than several other Himalayan glaciers. The glacier showed increased mass loss with increasing altitude, in contrast to the typical decreasing MB with increasing elevation, due to the existence of thick debris cover in the ablation zone, which thins out regularly towards the accumulation zone. Rising temperatures, depleting snowfall and increasing black carbon concentration in the region, indicators of climatic change, have all contributed to the increased mass loss of the HG. During the lean period, when glacier melt contributes significantly to streamflow, the mass loss of glaciers has had a considerable impact on streamflow. Water availability for food, energy, and other essential economic sectors would be adversely affected, if, glaciers in the region continued to lose mass due to climatic change. However, long-term MB and hydro-meteorological observations are required to gain a better understanding of glacier recession in the region as climate changes in the UIB.

This study employs a knowledge-based geospatial modelling technique to conduct a comprehensive flood vulnerability assessment of the Upper Jhelum Basin (UJB), in the Kashmir Himalaya, India. This study evaluates the interplay of watershed characteristics on runoff potential at a watershed scale and integrates a number of physical and socio-economic factors including geomorphology, land use, land cover, topography, soil, census, and field observations from the 2014 floods, to ascertain the overall flood vulnerability of the basin. The Lidder watershed, emerges as the primary source of excess runoff, while the Bringi, Sandran, and Vishav watersheds, contribute to a lesser extent, and the Kuthar watershed produces very minimal excess runoff at the outlet near Sangam. This study combines social vulnerability with the watersheds' excess-runoff potential to assess flood risk in the five watersheds of UJB. The Vishav watershed emerges as highly vulnerable, supported by floodwater inundation data from 2014, showcasing the effectiveness of the novel approach used. Approximately, 5% of the UJB, affecting ∼300,000 inhabitants, is covered by floodplains. The insights generated from this study are poised to guide policymaking for improved flood control and risk reduction strategies in the UJB, particularly in the face of climate change and socio-economic transformations.

Complex mountainous environments such as Himalayas are highly susceptibility to natural hazards particular those that are triggered by the action of water such as floods, soil erosion, mass movements and siltation of the hydro-electric power dams. Among all the natural hazards, soil erosion is the most implicit and the devastating hazard affecting the life and property of the millions of people living in these regions. Hence to review and devise strategies to reduce the adverse impacts of soil erosion is of utmost importance to the planners of watershed management programs in these regions. This paper demonstrates the use of satellite based remote sensing data coupled with the observational field data in a multi-criteria analytical (MCA) framework to estimate the soil erosion susceptibility of the sub-watersheds of the Rembiara basin falling in the western Himalaya, using geographical information system (GIS). In this paper, watershed morphometry and land cover are used as an inputs to the MCA framework to prioritize the sub-watersheds of this basin on the basis of their different susceptibilities to soil erosion. Methodology included the derivation of a set of drainage and land cover parameters that act as the indicators of erosion susceptibility. Further the output from the MCA resulted in the categorization of the sub-watersheds into low, medium, high and very high erosion susceptibility classes. A detailed prioritization map for the susceptible sub-watersheds based on the combined role of land cover and morphometry is finally presented. Besides, maps identifying the susceptible sub-watersheds based on morphometry and land cover only are also presented. The results of this study are part of the watershed management program in the study area and are directed to instigate appropriate measures to alleviate the soil erosion in the study area.

Abstract The study investigates the impact of changes in the form of precipitation and the consequent changes in the snowmelt contribution under changing climate on the streamflow in the Lidder, the most glaciated watershed in the Jhelum basin situated in the Upper Indus Basin (UIB). The Tracer Aided Catchment-Distributed (TACd) model is used to assess the present and future status of snowfall, snowmelt contribution and streamflow changes using the observed and projected climate data from an ensemble of 8 global climate models under various Representation Concentration Pathways (RCPs), viz. RCP2.6, RCP4.5, RCP6.0 and RCP8.5. Snow precipitation presently comprises 52% of the total annual precipitation and contributes ~ 55% to the annual streamflow with the peak observed in May in the Lidder River. However, projections to the end of twenty-first century under various RCPs indicate that there shall be considerable decrease in both the snow precipitation and snowmelt contribution to the streamflow. Moreover, early snowmelt is predicted during spring by the end of the twenty-first century under climate change, which leads to the shifting of streamflow peak from the late spring to early spring in the upstream and from summer to spring in the downstream areas of the basin. The observed streamflow shows a noticeable shift in the streamflow peak after 1990s and is more prominent in the downstream areas of the basin. The projected future climate change, snowfall depletion and streamflow changes are expected to significantly impact the timely availability of waters for various uses, flood vulnerability and sharing of the Indus waters.

The pristine waters of Kashmir Himalaya are showing signs of deterioration due to multiple reasons. This study researches the causes of deteriorating water quality in the Lidder River, one of the main tributaries of Jhelum River in Kashmir Himalaya. The land use and land cover of the Lidder catchment were generated using multi-spectral, bi-seasonal IRS LISS III (October 2005 and May 2006) satellite data to identify the extent of agriculture and horticulture lands that are the main non-point sources of pollution at the catchment scale. A total of 12 water quality parameters were analyzed over a period of 1 year. Water sampling was done at eight different sampling sites, each with a varied topography and distinct land use/land cover, along the length of Lidder River. It was observed that water quality deteriorated during the months of June–August that coincides with the peak tourist flow and maximal agricultural/horticultural activity. Total phosphorus, orthophosphate phosphorus, nitrate nitrogen, and ammoniacal nitrogen showed higher concentration in the months of July and August, while the concentration of dissolved oxygen decreased in the same period, resulting in deterioration in water quality. Moreover, tourism influx in the Lidder Valley shows a drastic increase through the years, and particularly, the number of tourists visiting the valley has increased in the summer months from June to September, which is also responsible for deteriorating the water quality of Lidder River. In addition to this, the extensive use of fertilizers and pesticides in the agriculture and horticulture lands during the growing season (June–August) is also responsible for the deteriorating water quality of Lidder River.

In this study, Land Surface Temperature (LST) and its lapse rate over the mountainous Kashmir Himalaya was estimated using MODIS data and correlated with the observed in-situ air temperature ( T air ) data. Comparison between the MODIS LST and T air showed a close agreement with the maximum error of the estimate ±1°C and the correlation coefficient >0.90. Analysis of the LST data from 2002-2012 showed an increasing trend at all the selected locations except at a site located in the southeastern part of Kashmir valley. Using the GTOPO30 DEM, MODIS LST data was used to estimate the actual temperature lapse rate (ATLR) along various transects across Kashmir Himalaya, which showed significant variations in space and time ranging from 0.3°C to 1.2°C per 100 m altitude change. This observation is at variance with the standard temperature lapse rate (STLR) of 0.65°C used universally in most of the hydrological and other land surface models. Snowmelt Runoff Model (SRM) was used to determine the efficacy of using the ATLR for simulating the stream flows in one of the glaciated and snow-covered watersheds in Kashmir. The use of ATLR in the SRM model improved the R2 between the observed and predicted streamflows from 0.92 to 0.97. It is hoped that the operational use of satellite-derived LST and ATLR shall improve the understanding and quantification of various processes related to climate, hydrology and ecosystem in the mountainous and data-scarce Himalaya where the use of temperature and ATLR are critical parameters for understanding various land surface and climate processes.

Rock glaciers are crucial freshwater resources, yet detailed knowledge about their distribution, characteristics, and dynamics in the Himalayan region is scarce. This study presents a comprehensive rock glacier inventory of the Jhelum basin, Kashmir Himalaya, India, using high-resolution Google Earth data. We identified 240 rock glaciers covering an area of 41.24 ± 2.2 km2, with ~76% classified as active, ~20% inactive, and 3.7% relict. The average areas and lengths of these rock glacier types were 0.19 km2, 0.06 km2, and 0.29 km2, and 699 m, 426 m, and 952 m, respectively. Most rock glaciers (~90%) were oriented northwards (N, NE, NW), while only 5% faced southwards (S, SE, SW). The lower limit of permafrost in the Jhelum basin is about 3316 m asl. Furthermore, we estimated the ice storage of rock glaciers in the Jhelum basin at 0.80 ± 0.13 km3, equivalent to 0.72 ± 0.12 km3 of water volume. This study enhances our understanding of permafrost distribution and the characteristics and dynamics in the basin. Given their greater resilience to climate change compared to clean glaciers, the hydrological significance of rock glaciers is expected to increase under projected climate change scenarios. This study highlights their importance as a vital water resource amidst the accelerated recession of clean glaciers.