Topographical impact on snow cover distribution in the Trans-Himalayan region of Ladakh, India

• Verfasst von: Passang, Stanzin [VerfasserIn]
• Verfasst von: Schmidt, Susanne [VerfasserIn]
• Verfasst von: Nüsser, Marcus [VerfasserIn]
• Titel: Topographical impact on snow cover distribution in the Trans-Himalayan region of Ladakh, India
• Verf.angabe: Stanzin Passang, Susanne Schmidt, Marcus Nüsser
• Jahr: 2022
• Umfang: 22 S.
• Fussnoten: Published: 20 August 2022 ; Gesehen am 24.07.25
• Titel Quelle: Enthalten in: Geosciences
• Ort Quelle: Basel : MDPI, 2011
• Jahr Quelle: 2022
• Band/Heft Quelle: 12(2022), 8, Seite 311
• ISSN Quelle: 2076-3263
• DOI: doi:10.3390/geosciences12080311
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: India
• Sach-SW: Ladakh
• Sach-SW: MODIS
• Sach-SW: snow cover
• Sach-SW: snow cover trends
• Sach-SW: terrestrial photography
• Sach-SW: Trans-Himalaya
• K10plus-PPN: 1931726612

Abstract

This article presents the distribution of seasonal snow cover in the Trans-Himalayan region of Ladakh over the observation period of 2000-2019. Seasonal snow cover area and duration have been monitored and mapped based on the MODIS Normalised Difference Snow Index (NDSI). Using different MODIS cloud removal algorithms, monthly mean cloud-covered areas have been reduced to 3%. Pixel-wise approaches using Mann-Kendall (MK) and Sen’s slope trend tests allow to assess seasonal and annual trends of snow cover days (SCD) and snow cover area (SCA) across seven delineated subregions of Ladakh. Analyses include the impact of topographical parameters (elevation, slope, aspect). Overall, the mean annual SCA amounts to 42%, varying from 15% in August to 71% in February. However, large differences of SCA have been detected between and within subregions. The trend analysis of SCA shows a non-significant, slight increase for summer as well as for the entire year and a decrease for spring and winter seasons. The SCD trend analysis indicates more pixels with a significant increase than a decrease. In total, 12% of all pixels show an increasing trend in summer, 6% over the entire year, 3% in autumn, and 2% in spring and winter, whereas less than 2% of all pixels show a decreasing trend in all seasons. The results are important for regional irrigated agricultural production and freshwater supply in the context of climate change.