Snow density variations: consequences for ground‐penetrating radar

Snow density variations: consequences for ground‐penetrating radar
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雪密度:探地雷达的变化后果

DOI:
10.1002/hyp.5944
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发表时间:
2006
影响因子:
3.2
通讯作者:
C. Andersson
C. Andersson
中科院分区:
地球科学3区
文献类型:
--
作者:
A. Lundberg;C. Richardson;C. Andersson

文献摘要

被引文献

相似文献

对许多地区来说,可靠的融雪径流水文预报是非常重要的。利用探地雷达(GPR)测量来评估瑞典北部规划水电生产所需的积雪水当量。利用研究流域的恒定积雪平均密度,记录雷达脉冲穿过积雪的旅行时间,并将其转换为雪水当量(SWE)。在本文中,我们通过引入与深度相关的积雪密度来改进估计SWE的方法。我们在瑞典山区的11个地点使用了6年的峰值雪深和积雪平均密度测量。原始方法系统地高估了浅层深度的SWE (0.5 m +25%),低估了大深度的SWE (2.0 m−35%)。通过引入基于几年平均条件的深度-密度关系,得到了很大的改进,而通过使用单个年份的单独关系来改进,得到的改进较小。对于厚积雪,SWE估计得到了显著改善,在1.2 - 2·0 m深度范围内,平均误差从162±23 mm降低到53±10 mm。因此,引入与深度相关的雪密度可以大大提高从GPR数据计算的SWE值的精度。版权所有©2005 John Wiley & Sons, Ltd
Reliable hydrological forecasts of snowmelt runoff are of major importance for many areas. Ground‐penetrating radar (GPR) measurements are used to assess snowpack water equivalent for planning of hydropower production in northern Sweden. The travel time of the radar pulse through the snow cover is recorded and converted to snow water equivalent (SWE) using a constant snowpack mean density from the drainage basin studied. In this paper we improve the method to estimate SWE by introducing a depth‐dependent snowpack density. We used 6 years measurements of peak snow depth and snowpack mean density at 11 locations in the Swedish mountains. The original method systematically overestimates the SWE at shallow depths (+25% for 0·5 m) and underestimates the SWE at large depths (−35% for 2·0 m). A large improvement was obtained by introducing a depth–density relation based on average conditions for several years, whereas refining this by using separate relations for individual years yielded a smaller improvement. The SWE estimates were substantially improved for thick snow covers, reducing the average error from 162 ± 23 mm to 53 ± 10 mm for depth range 1·2–2·0 m. Consequently, the introduction of a depth‐dependent snow density yields substantial improvements of the accuracy in SWE values calculated from GPR data. Copyright © 2005 John Wiley & Sons, Ltd.