Snow Cover Response to Climatological Factors at the Beas River Basin of W. Himalayas from MODIS and ERA5 Datasets

Sunita; Pardeep Kumar Gupta; George P Petropoulos; Hemendra Singh Gusain; Vishakha Sood; Dileep Kumar Gupta; Sartajvir Singh; Abhay Kumar Singh

doi:10.3390/s23208387

Snow Cover Response to Climatological Factors at the Beas River Basin of W. Himalayas from MODIS and ERA5 Datasets

Sensors (Basel). 2023 Oct 11;23(20):8387. doi: 10.3390/s23208387.

Authors

Sunita^{1

2}, Pardeep Kumar Gupta¹, George P Petropoulos³, Hemendra Singh Gusain⁴, Vishakha Sood⁵, Dileep Kumar Gupta⁶, Sartajvir Singh⁷, Abhay Kumar Singh⁶

Affiliations

¹ Department of Civil Engineering, Punjab Engineering College (Deemed to be University), Chandigarh 160012, India.
² Department of Civil Engineering, Punjabi University, Patiala 147002, India.
³ Department of Geography, Harokopio University of Athens, El. Venizelou St., 70, Kallithea, 17671 Athens, Greece.
⁴ Institute of Technology Management (DRDO), Mussoorie 248179, India.
⁵ Department of Civil Engineering, Indian Institute of Technology, Ropar 140001, India.
⁶ Department of Physics, Banaras Hindu University, Varanasi 221005, India.
⁷ University Institute of Engineering, Chandigarh University, Mohali 140413, India.

Abstract

Glaciers and snow are critical components of the hydrological cycle in the Himalayan region, and they play a vital role in river runoff. Therefore, it is crucial to monitor the glaciers and snow cover on a spatiotemporal basis to better understand the changes in their dynamics and their impact on river runoff. A significant amount of data is necessary to comprehend the dynamics of snow. Yet, the absence of weather stations in inaccessible locations and high elevation present multiple challenges for researchers through field surveys. However, the advancements made in remote sensing have become an effective tool for studying snow. In this article, the snow cover area (SCA) was analysed over the Beas River basin, Western Himalayas for the period 2003 to 2018. Moreover, its sensitivity towards temperature and precipitation was also analysed. To perform the analysis, two datasets, i.e., MODIS-based MOYDGL06 products for SCA estimation and the European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis of the Global Climate (ERA5) for climate data were utilized. Results showed an average SCA of ~56% of its total area, with the highest annual SCA recorded in 2014 at ~61.84%. Conversely, the lowest annual SCA occurred in 2016, reaching ~49.2%. Notably, fluctuations in SCA are highly influenced by temperature, as evidenced by the strong connection between annual and seasonal SCA and temperature. The present study findings can have significant applications in fields such as water resource management, climate studies, and disaster management.

Keywords: European Centre for Medium-Range Weather Forecasts (ECMWF); Himalayas; climatological factors; permafrost; snow cover area (SCA).

Grants and funding

This research work is financially supported by the Women Scientist Scheme-A (WOS-A) Project (Grant No. SR/WOS-A/ET-55/2019) by the Department of Science and Technology (DST), Govt. of India (vishakha.sood@ieee.org). GPP’s participation in the research study was financially supported by the project “EO-PERSIST” European Union’s Horizon Europe Research and Innovation program HORIZON-MSCA-2021-SE-01-01 under grant agreement No. 101086386.