Contrasting patterns of change in snowline altitude across five Himalayan catchments

Abstract. Seasonal snowmelt in the high mountains of 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 propose 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 globally. Here, we applied and evaluated the tool to five glacierised watersheds across the Himalayas to quantify the changes in seasonal and annual snow cover over the past 21 years and to analyse 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. SLA has been increasing in the Hidden Valley (+11.9 m yr^-1), Langtang Valley (+14.4 m yr^-1), and Rolwaling Valley (+8.2 m yr^-1) in the Nepalese Himalaya, but decreasing in the Satopanth (−15.6 m yr^-1) in the western Indian Himalaya, while we found no significant trend in Parlung Valley in southeast Tibet. We suggest that the increase in SLA was caused by warmer temperatures during the monsoon season in Nepal, whereas the decrease in SLA were driven by increased winter snowfall and reduced monsoon snowmelt in India. 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.