Mass Balance Reconstruction Since 1963 and Mass Balance Model for East Rathong Glacier,Eastern Himalaya,Using Remote Sensing Methods

In this study mass balance, accumulation, ablation, runoff and temperature lapse rate for the East Rathong glacier are estimated for the time period 1963–2011 using remote sensing methods and climate data. A mass balance model is proposed for the glacier that computes mass balance as difference of volumes of consecutive years. Volume estimates of glacier are based on application of volume–area scaling law to glacier area computed from satellite images. It is observed that the glacier is summer‐accumulation type. Time series analysis is applied to the annual mass balance series. The annual mass balance of the glacier is showing a statistically significant negative trend. It is also showing a statistically significant shift in the year 1985. Change in the mean of mass balance before and after the shift year is 0.19 m w.e. Cumulative mass balance suggests that the glacier has lost ～11 m w.e. or 0.047 km³ during the last 48 years.     

Predictions of future hydrological conditions and contribution of snow and ice melt in total discharge of Shigar River Basin in Central Karakoram, Pakistan

The high mountains of Hindu-Kush Karakoram and Himalaya(HKKH) contain a large volume of snow and ice, which are the primary sources of water for the entire mountainous population of HKKH. Thus, knowledge of these available resources is very important in relation to their sustainable use. A Modified Positive Degree Day Model was used to simulate daily discharge with the contribution of snow and ice melt from the Shigar River Basin, Central Karakoram, Pakistan. The basin covers an area of 6,921 km2 with an elevation range of 2,204 to 8,611 m a.s.l.. Forty percent of the total area is glaciated among which 20% is covered by debris and remaining 80% by clean ice and permanent snow. To simulate daily discharge, the entire basin was divided into 26 altitude belts. Remotely sensed land cover types are derived by classifying Landsat images of 2009. Daily temperature and precipitation from Skardu meteorological station is used to calibrate the glacio-hydrological model as an input variable after correlating data with the Shigar station data(r=0.88). Local temperature lapse rate of 0.0075 °C/m is used. 2 °C critical temperature is used to separate rain and snow from precipitation. The model is calibrated for 1988~1991 and validated for 1992~1997. The model shows a good Nash-Sutcliffe efficiency and volume difference in calibration(0.86% and 0.90%) and validation(0.78% and 6.85%). Contribution of snow and ice melt in discharge is 32.37% in calibration period and 33.01% is validation period. The model is also used to predict future hydrological regime up to 2099 by using CORDEX South Asia RCM considering RCP4.5 and RCP8.5 climate scenarios.Predicted future snow and ice melt contributions in both RCP4.5 and RCP8.5 are 36% and 37%, respectively. Temperature seems to be more sensitive as compared to other input variables, which is why the contribution of snow and ice in discharge varies significantly throughout the whole century.