Spatiotemporal change analysis of snow cover in response to climate (in-situ temperature) over the Upper Indus Basin, Pakistan.

The hydrologiest are debating on the rise in global glacier melting. However, the situation in Karakoram glaciers seems not the same. Therefore, it is essential to measure the status of snow in the Karakoram region of (GB; Gilgit-Baltistan) Pakistan. To this end, the current study examines the dynamics of snow cover using Moderate Resolution Imaging Spectroradiometer (MODIS) 8-days sow-cover in response to in-situ meteorological indicators from four high altitude automatic weather stations in Upper Indus Basin (UIB). The results conclude that the 8-days snow cover images not only show the qualities of MODIS (high resolution) images it's also characterized the high accuracies for snow-cover classification (~85 to 95 %). We analysed the snow-cover dynamics in the UIB and computed the maximum quantity of snow cover days (SCD) in a year that shadowed an increasing trend from 2000-2014, with an increase in snow-covered area (SCA) of 45.04% to 59.26% of the total land area of GB. Besides, there is a slightly decreasing trend observed in the SCA of Hindukush, and Himalayan mountains region in the last 15 years, due to increases in temperature and precipitation. Spearman's correlation analysis is also obtained between monthly and annually snow-cover changes (snow accumulation /depletion over six elevation zones above 2000 m elevation) and temperature. The month of January shows decreasing trends for five elevation zones out of six zones below 6000 m elevation. In spring, particularly in March shows a decreasing trend for two zones above 5000m elevations, while shows increasing trend in autumn for three zones above 4000 m elevation. A negative trend observed between monthly SCA and Khunjerab area (mean temperature and precipitation), and similar results are also noted for the remaining three regions such as Deosai, Naltar and Shandoor of UIB. The study suggests that, in the UIB region, climate change also employ a significant influence on regional SCA and days, as well as the distribution of snow-cover. These findings help for the forecasting of seasonal flow in the area and signifying snow-cover as a possible predictor of climate change. [ABSTRACT FROM AUTHOR]