Modeling the Spatial Distribution of Snow Cover in the Dudhkoshi Region of the Nepal Himalayas

被引:49
作者
Shrestha, Maheswor [1 ]
Wang, Lei [1 ]
Koike, Toshio [1 ]
Xue, Yongkang [2 ]
Hirabayashi, Yukiko [3 ]
机构
[1] Univ Tokyo, Dept Civil Engn, Tokyo 1138656, Japan
[2] Univ Calif Los Angeles, Dept Geog, Los Angeles, CA 90024 USA
[3] Univ Tokyo, Inst Engn Innovat, Tokyo 1138656, Japan
基金
美国国家科学基金会;
关键词
LAND-SURFACE TEMPERATURE; BIOSPHERE HYDROLOGICAL MODEL; REMOTE-SENSING DATA; UPPER TONE RIVER; RUNOFF MODEL; BASIN; ENERGY; MODIS; STREAMFLOW; AREA;
D O I
10.1175/JHM-D-10-05027.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
In this study, a distributed biosphere hydrological model with three-layer energy-balance snow physics [an improved version of the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM-S)] is applied to the Dudhkoshi region of the eastern Nepal Himalayas to estimate the spatial distribution of snow cover. Simulations are performed at hourly time steps and 1-km spatial resolution for the 2002/03 snow season during the Coordinated Enhanced Observing Period (CEOP) third Enhanced Observing Period (EOP-3). Point evaluations (snow depth and upward short- and longwave radiation) at Pyramid (a station of the CEOP Himalayan reference site) confirm the vertical-process representations of WEB-DHM-S in this region. The simulated spatial distribution of snow cover is evaluated with the Moderate Resolution Imaging Spectroradiometer (MOD IS) 8-day maximum snow-cover extent (MOD 10A2), demonstrating the model's capability to accurately capture the spatiotemporal variations in snow cover across the study area. The qualitative pixel-to-pixel comparisons for the snow-free and snow-covered grids reveal that the simulations agree well with the. MODIS data to an accuracy of 90%. Simulated nighttime land surface temperatures (LST) are comparable to the MOD IS LST (MOD11A2) with mean absolute error of 2.42 degrees C and mean relative error of 0.77 degrees C during the study period. The effects of uncertainty in air temperature lapse rate, initial snow depth, and snow albedo on the snow-cover area (SCA) and LST simulations are determined through sensitivity runs. In addition, it is found that ignoring the spatial variability of remotely sensed cloud coverage greatly increases bias in the LST and SCA simulations. To the authors' knowledge. this work is the first to adopt a distributed hydrological model with a physically based multilayer snow module to estimate the spatial distribution of snow cover in the Himalayan region.
引用
收藏
页码:204 / 222
页数:19
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