Publications

Choubin, B; Alamdarloo, EH; Mosavi, A; Hosseini, FS; Ahmad, S; Goodarzi, M; Shamshirband, S (2019). Spatiotemporal dynamics assessment of snow cover to infer snowline elevation mobility in the mountainous regions. COLD REGIONS SCIENCE AND TECHNOLOGY, 167, UNSP 102870.

Abstract
Due to the complex physics of both snow and snowmelt, particularly in mountainous topographic regions, studying the dynamics and variations of snow cover (SC) has been a very challenging task, and therefore, its relationship with snowline elevation (SLE) mobility has not been well documented. The spatiotemporal dynamics of SC in the Haraz Watershed, where streamflow is snowmelt-dominated, is of great importance, particularly for monitoring ecosystem processes, irrigation practices, and water management in the region. In the current study, due to the lack of a ground-based station, the remotely sensed eight-day Moderate Resolution Imaging Spectroradiometer (MODIS) images were considered in order to assess the dynamics of SC through investigating the monthly-normalized difference snow index (NDSI) during 2001 to 2018. Additionally, the SLE mobility was inferred through representing and assessing three indices related to SC, including variability in the number of snowy pixels and variations of the minimum and mean elevation in snowy pixels over time. According to the results, generally, 99.49% of the study regions showed NDSI declines, and 56.85% of these pixels showed significant trends. Variations of SC frequency showed that 32% of the study area has a moderate to very high snow existence probability. The trend of minimum and average elevation in snowy pixels indicates that January and December had significant increases, meaning that SLE increases during that time and moves towards higher elevations. The rate of changes in the average elevation of snowy pixels indicated an increasing rate of SLE in the months of January, February, March, August, and December, respectively equal to 8.18, 0.69, 2.51, 22.59, and 5.82 m per year. Further, results indicated that the percentage of the significant decrease in SC is highest on the slope aspects of southeast, south, and southwest (respectively equal to 66.81%, 62.35%, and 62.35%), meaning that SLE increases faster on these slope aspects.

DOI:
10.1016/j.coldregions.2019.102870

ISSN:
0165-232X