Contrasting patterns of change in snowline altitude across five Himalayan catchments

Seasonal snowmelt in High Mountain Asia is an important source of river discharge. Therefore, observation of the spatiotemporal variations in snow cover at catchment scales using high-resolution satellites is essential for understanding changes in water supply from headwater catchments. In this study, we adapt an algorithm to automatically detect the snowline altitude (SLA) using the Google Earth Engine platform with available high-resolution multispectral satellite archives that can be readily applied for areas of interest. Here, we applied and evaluated the tool to five glacierized watersheds across the Himalayas to quantify the changes in seasonal and annual snow cover over the past 21 years and analyze climate reanalysis data to assess the meteorological factors influencing the SLA. Our findings revealed substantial variations in the SLA among sites in terms of seasonal patterns, decadal trends, and meteorological controls. We identify positive trends in SLA in Hidden Valley (+11.9 m yr−1), Langtang (+14.4 m yr−1), and Rolwaling (+8.2 m yr−1) in the Nepalese Himalayas but a negative trend in Satopanth (−15.6 m yr−1) in the western Indian Himalayas and no significant trend in Parlung in southeastern Tibet. We suggest that the increase in SLA in Nepal was caused by warmer temperatures during the monsoon season, whereas the decrease in SLA in India was driven by increased winter snowfall and reduced monsoon snowmelt. By integrating the outcomes of these analyses, we found that long-term changes in SLA are primarily driven by shifts in the local climate, whereas seasonal variability may be influenced by geographic features in conjunction with climate.