Comparison of passive microwave and modeled estimates of total watershed SWE in the continental United States
Comparison of passive microwave and modeled estimates of total watershed SWE in the continental United States
复制标题
美国大陆总流域 SWE 的被动微波与模型估计的比较
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
S. Daly
中科院分区：
文献类型：
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作者：
C. Vuyovich;J. Jacobs;S. Daly
在美国，一个专门的积雪测量系统和积雪模型产品可用于估计整个冬季的雪水当量（SWE）。在世界上其他依赖融雪获取水资源的地区，积雪数据可能很少，而且这些地区容易受到干旱或洪水的影响。即使在美国，水资源管理也受到某些地区有限的积雪数据的阻碍，2011年密苏里盆地的洪水就是明证，这在很大程度上是由于平原积雪造成的。卫星数据可能在采样不足的地区提供重要信息。本研究将9个冬季的每日AMSR - E和SSM/I SWE产品与美国连续2100个流域的空间分布的模拟输出SNODAS进行了比较。结果表明，在大片地区，被动微波反演数据与SNODAS数据高度相关，特别是在大平原北部和落基山脉南部地区。然而，被动微波SWE在森林茂密地区和典型的深积雪地区明显低于SNODAS。相关性最好的是年最大SWE小于200 mm、森林分数小于20%的流域。即使在被动微波数据与SNODAS最大年SWE值相关性较差的许多流域，累积和消融的总体模式也显示出良好的一致性，因此可能提供有关融化时间和季节长度的有用水文信息。
In the U.S., a dedicated system of snow measurement stations and snowpack modeling products is available to estimate the snow water equivalent (SWE) throughout the winter season. In other regions of the world that depend on snowmelt for water resources, snow data can be scarce, and these regions are vulnerable to drought or flood conditions. Even in the U.S., water resource management is hampered by limited snow data in certain regions, as evident by the 2011 Missouri Basin flooding due in large part to the significant Plains snowpack. Satellite data could potentially provide important information in under‐sampled areas. This study compared the daily AMSR‐E and SSM/I SWE products over nine winter seasons to spatially distributed, modeled output SNODAS summed over 2100 watersheds in the conterminous U.S. Results show large areas where the passive microwave retrievals are highly correlated to the SNODAS data, particularly in the northern Great Plains and southern Rocky Mountain regions. However, the passive microwave SWE is significantly lower than SNODAS in heavily forested areas, and regions that typically receive a deep snowpack. The best correlations are associated with basins in which maximum annual SWE is less than 200 mm, and forest fraction is less than 20%. Even in many watersheds with poor correlations between the passive microwave data and SNODAS maximum annual SWE values, the overall pattern of accumulation and ablation did show good agreement and therefore may provide useful hydrologic information on melt timing and season length.