PhD Project Snow Cover Distribution in the Trans-Himalayan Region of Ladakh, India

Snow cover dynamics play an important role in the sustenance of glacier repositories in the Trans-Himalayan region of Ladakh, India. Understanding the changing nature of snow distribution helps to assess the possible impact of climate change, avalanches, forecasting, and various other applications. Ladakh is a high mountain region that to a large extent relies on irrigated agriculture for its food security. Due to the semi-arid climate conditions, the cryosphere of Ladakh serves as storage for water used for irrigation. Besides glaciers and permafrost, snow cover is one of the vital sources that ensure the availability of freshwater from seasonal snowmelt. This study investigated the distribution of the seasonal snow cover in the region of Ladakh, in the observation period from 2000 until 2019. The snow cover extent and duration were examined and mapped using Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products. The appropriate Normalised Difference Snow Index (NDSI) value representing snow in the region was established at 0.40, validated using Landsat 8 Operational Land Imager (LC8 OLI) cloud-free snow cover maps as a relative ground truth method. Several algorithms were developed to be used in sequence, that reduced the clouds from the MODIS satellite imagery to 3%, which helped to bridge the discontinuity in spatial and temporal scale for the daily long-term snow cover monitoring. The monthly, seasonal, and annual MODIS snow cover area (SCA) and snow cover days (SCD) were examined up to a regional and subregional pixel-wise level, using different statistical approaches like linear regression, Mann-Kendall (MK) with a two-variance correction, Sen’s slope trend and Pearson’s r and Spearman’s ρ correlation coefficient tests. The regional snow line elevation (RSLE) on a regional level, and the topographical impact (the elevation, slope, and aspect) on the snow cover distribution on a subregional level, were analyzed in more detail as well. A fitting forecast model for the prediction of snowfall in the region was also developed. At a local scale, two custom-made weather stations and a snowboard were installed, and in situ snow surveys measuring snow depth and SWE were conducted, to generate outdoor reference data. Included as a separate case study, the installation of four terrestrial cameras in the Leh Valley, featuring different elevations, slopes, and aspects, facilitated a high-resolution quantification and validation of the MODIS and Landsat 8 OLI snow cover distribution patterns and snow lines with the camera oblique photographs, orthorectified using the WSL Monoplotting Tool of the Swiss Federal Institute for Forest, Snow and Landscape Research. Repeat photography is relatively low-cost and without the need for direct field access a useful ground truthing method. Overall, the SCA in Ladakh shows an annual mean of about 42%, ranging from about 15% in August to 71% in February, and displays a high variety between and within the subregions. Trends of the SCA display a non-significant minor increase in the summer as well as annually, but a non-significant decrease for spring and the winter. The month of July manifests a significant positive trend of the SCA of 0.3% year⁻¹. The regional snow line elevation (RSLE) shows a significant downward shift in June (–5.20 m year⁻¹) and July (–5.56 m year⁻¹), with non-significant positive trends only in the winter. The average SCD of the entire study area is 151 days. The analysis of the SCD trend shows more pixels with a significant increase than a decrease. Annually and in summer 6% and 12%, respectively, of all pixels indicate a significant positive trend, and 2% a significant negative trend both annually and in winter. In the subregions, Suru and Zangskar 36% and 18%, respectively, of all pixels have an increasing trend during the summer. The comparison amongst the coarse resolution MODIS, high Landsat, and very high-resolution orthorectified photographs of the terrestrial camera stations shows a good agreement of the snow cover extent and snow lines. The results of the dissertation are important for any hydrological and development studies against the backdrop of global warming and climate change.

PhD Candidate: Stanzin Passang
Duration: 2015-2023