The Himalayan region is one of the most crucial mountain systems across the globe, which has significant importance in terms of the largest depository of snow and glaciers for fresh water supply, river runoff, hydropower, rich biodiversity, climate, and many more socioeconomic developments. This region directly or indirectly affects millions of lives and their livelihoods but has been considered one of the most climatically sensitive parts of the world. This study investigates the spatiotemporal variation in maximum extent of snow cover area (SCA) and its response to temperature, precipitation, and elevation over the northwest Himalaya (NWH) during 2000–2019. The analysis uses Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra 8-day composite snow Cover product (MOD10A2), MODIS/Terra/V6 daily land surface temperature product (MOD11A1), Climate Hazards Infrared Precipitation with Station data (CHIRPS) precipitation product, and Shuttle Radar Topography Mission (SRTM) DEM product for the investigation. Modified Mann-Kendall (mMK) test and Spearman’s correlation methods were employed to examine the trends and the interrelationships between SCA and climatic parameters. Results indicate a significant increasing trend in annual mean SCA (663.88 km2/year) between 2000 and 2019. The seasonal and monthly analyses were also carried out for the study region. The Zone-wise analysis showed that the lower Himalaya (184.5 km2/year) and the middle Himalaya (232.1 km2/year) revealed significant increasing mean annual SCA trends. In contrast, the upper Himalaya showed no trend during the study period over the NWH region. Statistically significant negative correlation (−0.81) was observed between annual SCA and temperature, whereas a nonsignificant positive correlation (0.47) existed between annual SCA and precipitation in the past 20 years. It was also noticed that the SCA variability over the past 20 years has mainly been driven by temperature, whereas the influence of precipitation has been limited. A decline in average annual temperature (−0.039 °C/year) and a rise in precipitation (24.56 mm/year) was detected over the region. The results indicate that climate plays a vital role in controlling the SCA over the NWH region. The maximum and minimum snow cover frequency (SCF) was observed during the winter (74.42%) and monsoon (46.01%) season, respectively, while the average SCF was recorded to be 59.11% during the study period. Of the SCA, 54.81% had a SCF above 60% and could be considered as the perennial snow. The elevation-based analysis showed that 84% of the upper Himalaya (UH) experienced perennial snow, while the seasonal snow mostly dominated over the lower Himalaya (LH) and the middle Himalaya (MH).
Abstract. The sustainable usage and accurate assessment of water resources in North West Himalaya (NWH) is very important for respective policy makers. NWH receives precipitation from both southwest and northeast monsoon system. The detailed assessment of current and future water resources and hydrological cycle component for NWH river basins using earth observation (EO) satellites and hydrological models is very critical for attaining United Nations sustainable development goals (SDGs) namely, climate action, affordable and clean energy, clean water and sanitation and building resilient infrastructure. Present work highlights the role of various EO sensors and hydrological models and ground based instruments for improved assessment of water resources of NWH river basins. The complete inventory of NWH surface water (including glacier lakes of UK, HP), snow cover, delta SWE and glaciers database was accomplished with Remote Sensing (RS) datasets. Similarly, glacier velocity was estimated for all major glaciers of NWH using feature tracking and differential interferometry (DInSAR) methods. Fully distributed grid based hydrological model was setup for entire NWH and model calibration/validation was done for Beas, Satluj, Upper Ganga and Jhelum river basins. Quantification of relative contribution of snowmelt, glacier melt and rainfall-runoff was estimated for Bhagirathi basin upto Uttarkashi. An extensive network of automatic weather stations (AWS), 27 nos, 10 snow depth sensors, 04 digital water level recorders, two snow pack analysers and 06 long wave solar radiation sensors were installed in various sites of HP and UK for hydro-meteorological data collection, model simulation and validation. A future climate change simulations were done for Beas and Jhelum basins using CORDEX 4.5 and 8.5 scenarios from 2006–2100. Number of flood peaks were found to be increasing in number as well as decrease in total snow fall.
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