Abstract
Large area of Himalayas covered with seasonal snow during winter are rapidly changing during summer, significantly affects the stream flow of many rivers originating from Himalayas. This necessitates the efficient time series monitoring of seasonal snow cover in the rugged mountainous region throughout the winter and summer periods for weekly/monthly as well as seasonal forecast of stream run-off for water management and other developmental activities.
In the present paper, the stream flow simulation model is implemented for a quantitative estimation of snowmelt run-off in winter and summer seasons for Beas and Parbati catchments of Beas river in Himachal Pradesh. The main input parameters used in the model were seasonal snow cover extent, permanent snow/glacier extent, seasonal snow line, different elevation zones, catchments areas, and basin area generated using remote sensing and GIS techniques and field data such as degree day temperature index, snowfall and rainfall. Multitemporal Advance Wide Field Sensor (AWiFS) of IRS-P6 has been used for the period between October–June for the years 2004–05, 2005–06 and 2006–07. Normalized Difference Snow Index (NDSI) technique which is based on reflectance in visible (VIS) and short-wave infrared (SWIR) bands has been used for mapping of snow covered area. The terrain characteristics have been extracted from Digital Elevation Model (DEM) of Beas basin generated using 1:50,000 scale SoI maps at 40m contour interval.
The study reveals that the month-wise discharge pattern varies from year to year; however, the stream flow rhythm for both catchments follow the same pattern. It shows that climatic parameters such as degree day temperature index, snowfall and rainfall have direct impact on daily, weekly and monthly snow melt run-off. Hence precise estimation for snow melt runoff in real time is helpful in the planning and execution of mini and micro hydel schemes.
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Singh, M., Mishra, V.D., Thakur, N.K. et al. Impact of climatic parameters on statistical stream flow sensitivity analysis for hydro power. J Indian Soc Remote Sens 37, 601–614 (2009). https://doi.org/10.1007/s12524-009-0053-3
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DOI: https://doi.org/10.1007/s12524-009-0053-3