Development and application of a spatially distributed snowmelt runoff model for limited data condition

被引:0
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作者
S. Rajkumari
N. Chiphang
Liza G. Kiba
A. Bandyopadhyay
A. Bhadra
机构
[1] National Institute of Hydrology,Department of Agricultural Engineering
[2] North Eastern Regional Institute of Science and Technology,undefined
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关键词
Distributed snowmelt runoff model; Modified temperature index approach; Snow cover; Snow albedo; Modified Clark routing; Limited data condition;
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摘要
Two main approaches are used to calculate snowmelt, namely, energy balance (physically based) and temperature index (conceptual). Energy balance requires comprehensive data to solve physical equations. In this study, a distributed conceptual model, “spatially distributed snowmelt runoff model”, based on modified temperature index approach was developed to estimate snow-related parameters like snow density and degree day factor in a distributed manner over space and time to meet the hydrological demands of data-scarce snow-dominated mountainous catchment. The model needs only daily temperature, precipitation, snow cover, and albedo as basic inputs. It gives pixel-wise output of snow density, snow depth, snow water equivalent, degree day, net radiation, snowmelt depth, rain-induced runoff, snowmelt runoff, actual evaporation, and infiltration, while routing the flow up to the catchment outlet to estimate discharge as time series along with contribution breakup between snowmelt and rain-induced runoff. The developed model was tested for a small-sized watershed Nuranang (58 km2) as well as for a medium-sized watershed Mago basin (844 km2) both located in the Tawang district of Arunachal Pradesh, India, and was successfully calibrated for 2004–2005 and validated for 2008–2009 for Nuranang watershed. In the case of Mago basin, a single year (2007) was used for calibration and validation was also performed for a single year (2009) as well due to the unavailability of data. Performance of the model was found satisfactory for both the basins with modelling efficiency (ME) greater than 0.6 and coefficient of residual mass (CRM) in between − 0.2 and 0.2 for both calibration and validation years in these data-scarce eastern Himalayan watersheds. Considering the satisfactory performance of the model in both the small- and medium-sized watersheds, the model can be very useful for any un-instrumented mountainous basins for pixel-wise snowmelt runoff computation and gridded output generation using degree day approach, where observed snow density data is not available.
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