Snow cover variability and trend over the Hindu Kush Himalayan region using MODIS and SRTM data

Abstract

Abstract. Snow cover changes have a direct bearing on the regional and global energy and water cycles and the change in the Earth's climate conditions. We studied the relatively long-term (2000–2017) altitudinal spatiotemporal changes in the coverage of snow and glaciers in one of the world's largest mountainous regions, the Hindu Kush Himalayan (HKH) region, including Tibet, using remote sensing data (5 km grid resolution) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra satellite. This dataset provided a unique opportunity to study zonal and hypsographic changes in the intra-annual (accumulating season and melting season) and interannual variations in snow and glacial cover over the HKH region. The zonal and altitudinal (hypsographic) analyses were carried out for the melting season and accumulating season. The altitude-wise linear trend analysis (Pearson's) of snow cover, shown as a hypsographic curve, clearly indicates a major decline in snow cover (average of 5 % or more at 100 m interval aggregates) between 4000–4500 and 5500–6000 m altitudes, which is consistent with the median trend (Theil–Sen – TS) and the monotonic trend (Mann–Kendall – MK; statistics) analysis. This analysis also revealed the regions and altitudes where major and statistically significant increases (10 % to 30 %) or decreases (−10 % to −30 %) in snow cover are identified. The extrapolation of the altitude-wise linear trend shows that it may take between ∼ 74 and 7900 years, for 3001–6000 and 6000–7000 m altitude zones respectively, for mean snow cover to decline approximately 25 % in the HKH. More detailed analysis based on longer observational records and model simulations is warranted to better understand the underlying factors, processes, and feedbacks that affect the dynamic of snow cover in HKH. These preliminary results suggest a need for continued monitoring of this highly sensitive region to climate variability and change that depends on snow as a major source of freshwater for all human activities.

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

“…In this regard, seasonal trends of SCA were analyzed between December 2002 and November 2020 at grid scale, which remained understudied so far. Recent studies generally focused on annual trends and study periods until 2017 (Ackroyd et al, 2021;Desinayak et al, 2022) and 2018 (Notarnicola, 2020). In detail, the results of this study pointed towards partially significant decreasing and increasing trends at seasonal scale (Figure 5c), whereas trends at basin scale were mostly insignificant indicating that SCA remained stable (Table 2).…”

Challenges in Understanding the Variability of the Cryosphere in the Himalaya and Its Impact on Regional Water Resources

“…The present synthesis shows that procuring a trend in snow cover changes is challenging for the Himalayan region due to the limited number of observations, substantial annual and inter-annual variability, and scarce in-situ snow depth area data (Kulkarni et al, 2021). However, overall, it is widely reported that depleting snow cover and its spatiotemporal changes are associated with changes in climatic variables over the Himalaya (Sood et al, 2020;Desinayak et al, 2022). Understanding variability of snow cover with respect to altitude and air temperature is vital for assessing availability of regional water resources and the impact of climate change in the Himalaya (Immerzeel et al, 2010;Shrestha et al, 2015).…”

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

“…Accurately identifying alterations in snow coverage remains a challenging task due to multiple factors. For example, the rough geography of mountainous regions, the influence of shadow effects, and the ever-changing climatic conditions [35,36]. Change detection plays a crucial role in analysing temporal variations and visually representing diverse changes on a unified map [37].…”