In the Snowmelt-Runoff Model (SRM), the estimate of discharge volume is based on temperature condition in the form of degree days which are used to melt the snowpack in the area of the basin covered by snow as observed from satellites. Precipitation input is used to add any rainfall runoff to the snowmelt component. When SRM was applied to the large, international Kabul River basin, initial simulations were much above the observed stream flow values. Close inspection revealed several problems in the application of SRM to the Kabul Basin that were easily corrected. Foremost among the corrections were determination of an appropriate lapse rate, substitution of a more representative mean elevation for extrapolation of temperature data, and use of an automatic streamflow updating procedure. These improvements led to a simulation for 1976 that was comparable to other simulations on large, inaccessible basins. As SRM is applied to more basins similar to the Kabul River, the determination of suitable parameters for new basin will be enhanced. Additional improvements in simulations would result from installation of climate stations at the mean elevation of basins and work to assure delivery of timely and reliable satellite snow cover data.
Air temperature and snow cover variability are sensitive indicators of climate change. This study was undertaken to forecast and quantify the potential streamflow response to climate change in the Jhelum River basin. The implications of air temperature trends (+0.11°C/decade) reported for the entire north-west Himalaya for past century and the regional warming (+0.7°C/decade) trends of three observatories analyzed between last two decades were used for future projection of snow cover depletion and stream flow. The streamflow was simulated and validated for the year 2007-2008 using snowmelt runoff model (SRM) based on in-situ temperature and precipitation with remotely sensed snow cover area. The simulation was repeated using higher values of temperature and modified snow cover depletion curves according to the assumed future climate. Early snow cover depletion was observed in the basin in response to warmer climate. The results show that with the increase in air temperature, streamflow pattern of Jhelum will be severely affected. Significant redistribution of streamflow was observed in both the scenarios. Higher discharge was observed during spring-summer months due to early snowmelt contribution with water deficit during monsoon months. Discharge increased by 5%−40% during the months of March to May in 2030 and 2050. The magnitude of impact of air temperature is higher in the scenario-2 based on regional warming. The inferences pertaining to change in future streamflow pattern can facilitate long term decisions and planning concerning hydro-power potential, water resource management and flood hazard mapping in the region.
Log-linear, exponential and fractional relations for estimating seasonal snowmelt from early-spring snow accumulation in the Indus and Kabul river basins in the western Himalayas are developed with a view to improve the prediction given by bivariate linear regression models earlier developed by the senior author in collaboration with others. This study shows that although the transformed data may improve the above prediction, they fail to satisfy the condition of nonlinearity; a property that must be borne in mind before recommending any nonlinear regression model. Any further improvement in the prediction of seasonal flow volume from basin snow cover area, therefore, has to come from within the domain of linear regression models only or from improvements in the original input data.
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