Large-scale monitoring of snow cover and runoff simulation in Himalayan river basins using remote sensing

被引:517
作者
Immerzeel, W. W. [1 ,2 ]
Droogers, P. [1 ]
de Jong, S. M. [2 ]
Bierkens, M. F. P. [2 ]
机构
[1] FutureWater, NL-6702 AA Wageningen, Netherlands
[2] Univ Utrecht, Dept Phys Geog, Utrecht, Netherlands
关键词
MODIS; TRMM; Snow cover; Runoff; Climate Change; Indus; Himalaya; INDIAN-SUMMER MONSOON; TIBETAN PLATEAU; CLIMATIC-CHANGE; DEPTH; VARIABILITY; RAINFALL; ENSO;
D O I
10.1016/j.rse.2008.08.010
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Various remote sensing products are used to identify spatial-temporal trends in snow cover in river basins originating in the Himalayas and adjacent Tibetan-Qinghai plateau. It is shown that remote sensing allows detection of spatial-temporal patterns of snow cover across large areas in inaccessible terrain, providing useful information on a critical component of the hydrological cycle. Results show large variation in snow cover between years while an increasing trend from west to east is observed. Of all river basins the Indus basin is, for its water resources, most dependent on snow and ice melt and large parts are snow covered for prolonged periods of the year. A significant negative winter snow cover trend was identified for the upper Indus basin. For this basin a hydrological model is used and forced with remotely sensed derived precipitation and snow cover. The model is calibrated using daily discharges from 2000 to 2005 and stream flow in the upper Indus basin can be predicted with a high degree of accuracy. From the analysis it is concluded that there are indications that regional warming is affecting the hydrology of the upper Indus basin due to accelerated glacial melting during the simulation period. This warming may be associated with global changes in air temperature resulting from anthropogenic forcings. This conclusion is primarily based on the observation that the average annual precipitation over a five year period is less than the observed stream flow and supported by positive temperature trends in all seasons. (C) 2008 Elsevier Inc. All rights reserved.
引用
收藏
页码:40 / 49
页数:10
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