Estimation of Snowmelt Contribution for Kalam Catchment
Abstract
Snowmelt flows are key source for river discharges that is used for agriculture, hydropower generation and domestic use in snow-fed regions. Nature has sanctified Pakistan with the frozen peaks of the Hindu Kush Himalayan (HKH) in the northern part of the country. Mountain ranges receive heavy snowfall in winter playing a dynamic role in water supply estimation and management. Flows in Kalam catchment are mainly generated due to snowmelt. Since foreseeing and understanding the time-space variation of snow magnitude plays an important role in watershed hydrology, it is necessary to simulate snow accretion and melt precisely. Due to the availability of Moderate Resolution Imaging Spectroradiometer (MODIS) data for snowcover area and Rainfall Estimates (RFE) for precipitation records, it is now possible to identify the portion of the snowmelt that may contribute to the flood hydroghraph. The investigation of MODIS snow product (MOD10A1) for the past 14 years (2000-2013) record shows an average snow cover variation in Kalam Catchment ranges from 5% to 99% in September & March, respectively. A correlation is developed between RFE and Kalam rainfall station by extracting the pixel information of RFE coming over the Kalam station showing a monthly and yearly (2000-2012) correlation coefficient of 0.70 & 0.77, respectively. The research employs, water balance approach and SRM for estimating snow melt contribution (Snowmelt Runoff Model). Results from water balance approach gives an overall snowmelt contribution of 65% with an average groundwater and average rainfall runoff contribution as 19% and 16% respectively. The SRM is well calibrated and validated using regular stream flow 2000 to 2012 (average correlation coefficient for Calibration ~0.95 & for validation ~0.89, annual volume bias<6.5%). Snowmelt from SRM is estimated by separating rainfall days on basis of critical temperature. Results of the study reveals that average snowmelt contribution in the Kalam is about 72%, whereas, average contribution from rainfall is 17%. Results from conventional method is compared with SRM to inspect and assess the performance of a model in the Kalam catchment.References
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