Climate dynamics and the effect of topography on snow cover variation in the Indus-Ganges-Brahmaputra river basins

Abstract

The river basins of the Indus-Ganges-Brahmaputra (IGB) are characterized by rapid population growth, increased water demand, and rapid snow/ice melting, all of which combine to make these catchments especially vulnerable to climate change. Here, we present a comprehensive dataset (2003−2020) for precipitation, temperature and snow cover area (SCA) to investigate the spatio-temporal variability of important climate factors in relation to elevation and across three major sub-basins of the IGB. Improved MODIS (Moderate Resolution Imaging Spectro-radiometer) Terra and Aqua snow cover data are used to estimate regional snow cover, while Climate Hazards Group InfraRed Precipitation with Station Data version 2.0 (CHIRPS-V2.0) is deployed for precipitation, and MODIS Land Surface Temperature (LST) data are used to estimate temperature. The analysis reveals significant changes in precipitation, LST and snow cover throughout the IGB region together with a strong degree of spatial coherence between SCA and regional surface topography (R2 = 0.82).Maximum changes were observed in the Brahmaputra basin at mean annual precipitation (13.9 mm/year) and reduced SCA (155.4 km2/year) over the period studied. Similar trends are also evident, albeit with relatively lower absolute values in the other two basins, whereby the Indus basin evidences a significant reduction in annual SCA, averaging 82.2 km2/year with increased precipitation (3.12 mm/year) and LST. This investigation further highlights the relative influence of climate change factors and regional human activities in determining high-elevation changes in SCA. Most of the middle elevation regions of the Ganges experienced a significant reduction in SCA, with human impact contributing 82% of the observed variation, while climate factors are more prominent in the Indus and Brahmaputra basins. Understanding the dynamics of snow cover and its regional influencing factors is crucial to the more accurate evaluation of water resources and to defining appropriate mitigation and adaptation strategies for the coming decades.