Central Himalaya, the third-largest ice mass globally, is the source of major rivers like the Ganges, upon which almost 655 million people from India, Nepal, and Bangladesh rely for livelihood. However, climate change is appearing as the largest threat for its snow cover. Therefore, this study examines spatio-temporal variations in snow cover area, volume, and areal fragmentation over thirty years utilizing remotely sensed data. Different landscape metrics (class area, number of patches, patch density, largest patch index, mean patch size, edge density, and perimeter area ratio) is used and a novel index is developed to study fragmentation. NDSI is used to map the snow cover and area volume scaling based on empirical observations to estimate the volume. Despite fluctuations, a trend of decline emerges in thick and thin snow cover (from 10,768 to 3258.6 km2 in thick snow, and from 3798 to 6863.56 km2 in thin snow during maxima, whereas, from 1678.44 to 539.66 km2 in thick snow and from 2414.12 to 1300.56 km2 in thin snow during minima). Thick snow cover fluctuated with a period of decline up to 2006, followed by a slight recovery and subsequent reduction in 2021. Conversely, thin snow cover shows a gradual increase up to 2006, followed by a rapid decline in 2021, highlighting the region’s high susceptibility to warming. Furthermore, it was found that B4, C2, C3, and C4 were the grids with very high fragmentation of thick snow. However, C1, D2, and E4 were marked as highly fragmented for thin snow cover. The research underscores the urgent need for adaptive and mitigation measures to impact climate change in the fragile cryosphere of the Central Himalaya.
Spatio-Temporal Assessment of Areal Fragmentation and Volume of Snow Cover in the Central Himalaya
Sudip ChakrabortySupervision
2024-01-01
Abstract
Central Himalaya, the third-largest ice mass globally, is the source of major rivers like the Ganges, upon which almost 655 million people from India, Nepal, and Bangladesh rely for livelihood. However, climate change is appearing as the largest threat for its snow cover. Therefore, this study examines spatio-temporal variations in snow cover area, volume, and areal fragmentation over thirty years utilizing remotely sensed data. Different landscape metrics (class area, number of patches, patch density, largest patch index, mean patch size, edge density, and perimeter area ratio) is used and a novel index is developed to study fragmentation. NDSI is used to map the snow cover and area volume scaling based on empirical observations to estimate the volume. Despite fluctuations, a trend of decline emerges in thick and thin snow cover (from 10,768 to 3258.6 km2 in thick snow, and from 3798 to 6863.56 km2 in thin snow during maxima, whereas, from 1678.44 to 539.66 km2 in thick snow and from 2414.12 to 1300.56 km2 in thin snow during minima). Thick snow cover fluctuated with a period of decline up to 2006, followed by a slight recovery and subsequent reduction in 2021. Conversely, thin snow cover shows a gradual increase up to 2006, followed by a rapid decline in 2021, highlighting the region’s high susceptibility to warming. Furthermore, it was found that B4, C2, C3, and C4 were the grids with very high fragmentation of thick snow. However, C1, D2, and E4 were marked as highly fragmented for thin snow cover. The research underscores the urgent need for adaptive and mitigation measures to impact climate change in the fragile cryosphere of the Central Himalaya.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
