Abstract:
Glaciers and snow are critical components of the hydrological cycle in the Himalayan
region, and they play a vital role in river runoff. Therefore, it is crucial to monitor the glaciers and
snow cover on a spatiotemporal basis to better understand the changes in their dynamics and their
impact on river runoff. A significant amount of data is necessary to comprehend the dynamics
of snow. Yet, the absence of weather stations in inaccessible locations and high elevation present
multiple challenges for researchers through field surveys. However, the advancements made in
remote sensing have become an effective tool for studying snow. In this article, the snow cover
area (SCA) was analysed over the Beas River basin, Western Himalayas for the period 2003 to 2018.
Moreover, its sensitivity towards temperature and precipitation was also analysed. To perform
the analysis, two datasets, i.e., MODIS-based MOYDGL06 products for SCA estimation and the
European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis of the
Global Climate (ERA5) for climate data were utilized. Results showed an average SCA of ~56%
of its total area, with the highest annual SCA recorded in 2014 at ~61.84%. Conversely, the lowest
annual SCA occurred in 2016, reaching ~49.2%. Notably, fluctuations in SCA are highly influenced
by temperature, as evidenced by the strong connection between annual and seasonal SCA and
temperature. The present study findings can have significant applications in fields such as water
resource management, climate studies, and disaster management.
