EGU23-252, updated on 22 Feb 2023
https://doi.org/10.5194/egusphere-egu23-252
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Linking Changes in Gangotri Glacier Features Derived at a Large-Scale with Climate Variability

Kavita Vaijanath Mitkari1, Sanjeev Sofat1, Manoj K Arora2, and Reet Kamal Tiwari3
Kavita Vaijanath Mitkari et al.
  • 1Punjab Engineering College (Deemed To Be University), Chandigarh, India (kavitavaijnathmitkari.phdcse16@pec.edu.in; sanjeevsofat@pec.edu.in)
  • 2SRM University AP, Mangalagiri, Andhra Pradesh, India (vc@srmap.edu.in)
  • 3Indian Institute of Technology Ropar, Rupnagar, Punjab, India (reetkamal@iitrpr.ac.in)

Changes in glacier area, snow, ice, debris cover, and other geomorphological features such as debris cones have a significant impact on the glacial dynamics, are a direct measure of glacier advance and retreat, form a critical input for measuring glacier mass balance, help identify the location of equilibrium line altitude, contribute to the global sea-level rise, and are a good index for understanding local climatic changes. Formation of glacial lakes enhance the rate of glacial melting and catastrophic events arising out of the outburst of glacial lakes can have serious impacts on the human life and economy. So, monitoring the spatial and temporal changes of glacier surface as well as non-surface features is imperative for assessing the health of glaciers and their behavior toward the climate change. The availability of high spatial resolution remote sensing images, has made precise mapping and monitoring of the changes in the glacier surface features and geomorphological features viable at a local level using object-based change detection (OBCD) rather than traditional pixel-based change detection (PBCD). OBCD has been used in numerous applications however, it has received little attention within the glaciological community. Advantage of using OBCD over PBCD is that the object-based paradigm enables the characterization of different land cover classes within the same image, using different object sizes. Further, in OBCD, each image object is considered as a single entity and hence, the small spurious changes and misregistration errors that occur due to high spectral variability are reduced because segmentation generates image objects which are less sensitive to the small spurious changes and misregistration respectively. Furthermore, a comprehensive literature survey on the Gangotri Glacier, Indian Himalayas uncovered that so far, no work has been done linking the variation of glacier surface and non-surface features with the important climate variables that is, temperature and precipitation. Therefore, this study has evaluated the changes in the Gangotri Glacier features at a large scale using class OBCD approach from high spatial resolution WorldView-2 and LISS-4 images for a three-year period from 2011-2014. The meteorological data of Gangotri Glacier was obtained from Climate Research Unit Time Series v.4.06 dataset. A surge in the annual mean temperature and decline in the annual precipitation caused snow/ice area reduction by ~52%. This is accompanied by an increase in the ice-mixed debris (IMD) area by ~11%. The increase in IMD may lead to enhanced ice melting as it could reflect less incoming solar radiations. This further should have revealed expansion in supraglacial debris (SGD) area, however, it has minimized by ~0.4% which is justified with a rise in the periglacial debris (PGD) and debris cones by ~21% and ~9% respectively. Ascend in the annual mean temperature has also shown an increase of ~70% in the area of supraglacial lakes (SGLs), though the number of SGLs decreased; decrease in the number of SGLs suggests widening of SGLs in area. Thus, the dynamics of the glacier features is greatly affected by the yearly temperature and precipitation alterations in the area.

How to cite: Mitkari, K. V., Sofat, S., Arora, M. K., and Tiwari, R. K.: Linking Changes in Gangotri Glacier Features Derived at a Large-Scale with Climate Variability, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-252, https://doi.org/10.5194/egusphere-egu23-252, 2023.