Discharge sensitivity to snowmelt parameterization: a case study for Upper Beas basin in Himachal Pradesh, India

被引:22
作者
Hegdahl, Trine J. [1 ,2 ]
Tallaksen, Lena M. [1 ]
Engeland, Kolbjorn [1 ,2 ]
Burkhart, John F. [1 ,3 ]
Xu, Chong-Yu [1 ]
机构
[1] Univ Oslo, Dept Geosci, POB 1047, N-0316 Oslo, Norway
[2] Norwegian Water Resources & Energy Directorate, POB 5091 Majorstua, N-0301 Oslo, Norway
[3] Statkraft AS, Oslo, Norway
来源
HYDROLOGY RESEARCH | 2016年 / 47卷 / 04期
关键词
discharge/runoff; glacier; Himalaya; hydrological modelling; snowmelt parameterization; HYDROLOGICAL MODEL; WESTERN HIMALAYA; GLACIER; CALIBRATION; CHALLENGES; BALANCE; RETREAT;
D O I
10.2166/nh.2016.047
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Snow- and glacier melt are important contributors to river discharge in high-elevated areas of the Himalayan region. Thus, it is important that the key processes controlling snow and glacier accumulation and melting, are well represented in hydrological models. In this study, the sensitivity of modelled discharge to different snowmelt parameterizations was evaluated. A distributed hydrological model that operated on a 1 x 1 km(2) grid at a daily time resolution was applied to a high elevated mountainous basin, the Upper Beas basin in Indian Himalaya, including several sub-basins with a varying degree of glacier covered areas. The snowmelt was calculated using (i) a temperature index method, (ii) an enhanced temperature-index method including a shortwave radiation term, and (iii) an energy balance method. All model configurations showed similar performance at daily, seasonal, and annual timescales and a lower performance for the validation period than for the calibration period; a main reason being the failure to capture the observed negative trend in annual discharge in the validation period. The results suggest that model performance is more sensitive to the precipitation input, i.e. interpolation method than to the choice of snowmelt routine. The paper highlights the challenges related to the lack of high quality data sets in mountainous regions, which are those areas globally with most water resources.
引用
收藏
页码:683 / 700
页数:18
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