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Singh, Vishal; Kumar Goyal, Manish; Surampalli, Rao Y.; Munoz-Arriola, Francisco (2017)
Languages: English
Types: Article
The present work proposes to improve estimates of how much streamflow is generated by snow in the watersheds of the steep Himalayas. Half of the earth’s glacial catchments in nonpolar areas are in the Himalayas, and they generate almost a third of the streamflows in India. In River catchments with glacier presence in the region, temporal variability in streamflow generation and the associated distribution of accumulated snow illustrate how changes in snowmelt and precipitation can affect water supplies to a growing population of 1.3 billion people. Estimations of snowpack and snowmelt in watersheds are critical for understanding streamflow generation and sources of catchments. However, estimating precipitation and snow accumulation is constrained by the difficulties complex terrain poses to data collection. The primary objective of this study is to assess the role of elevations in the computation of snowfall (snowpack) and snowmelt in sub-catchments. The study area is the Satluj River Catchment (up to Kasol gauge) with moderate (e.g., 526 m) to very high elevations (e.g., 7429 m) dominated by snow covers and glaciers. The Satluj River Catchment was divided into 14 sub-catchments. Snowpack and snowmelt variations in the sub-catchments in both historical and projected near-term (2011–2130) periods were analyzed using observed and Global Circulation Model (GCM) data sets. Both hydrological scenarios used elevation bands and parameter-sensitivity analyses built in the Soil Water Assessment Tool (SWAT) model. For model calibration/validation and parameter sensitivity analysis, an advanced optimization method — namely, Sequential Uncertainty Fitting (SUFI2) approach was used with multiple hydrological parameters. Among all parameters, the curve number (CN2) was found significantly sensitive for computations. The snowmelt hydrological parameters such as snowmelt factor maximum (SMFMX) and snow coverage (SNO50COV) significantly affected objective functions such as R2 and NSE during the model optimization process. The computed snowpack and snowmelt were found highly variable over the Himalayan sub-catchments as also reported by previous researchers in other regions. The magnitude of snowpack change consistently decreases across all the sub-catchments of the Satluj River Catchment (varying between 4 % and 42 %). The highest percentage of changes in snowpack was observed over high-elevation subcatchments.
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