Combining Ground‐Penetrating Radar With Terrestrial LiDAR Scanning to Estimate the Spatial Distribution of Liquid Water Content in Seasonal Snowpacks

Combining Ground‐Penetrating Radar With Terrestrial LiDAR Scanning to Estimate the Spatial Distribution of Liquid Water Content in Seasonal Snowpacks
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结合地面穿透雷达与地面激光雷达扫描来估计季节性积雪中液态水含量的空间分布

DOI:
10.1029/2018wr022680
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发表时间:
2018
影响因子:
5.4
通讯作者:
Molotch, N. P.
Molotch, N. P.
中科院分区:
地球科学1区
文献类型:
--
作者:
Webb, R. W.;Jennings, K. S.;Fend, M.;Molotch, N. P.

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世界各地的许多社区和生态系统都依赖于山区积雪来提供宝贵的水资源。水资源规划的一个重要考虑因素是径流时间,这可能会受到季节性积雪中水储存和释放的物理过程的强烈影响。本研究的目的是提出一种新的方法,将光探测和测距与探地雷达相结合,以非破坏性地估计春季融雪期间季节性积雪中散装液态水含量的空间分布。我们开发这些方法的方式是适用于在一个很短的时间窗口内,使之有可能在空间上观察快速变化,发生在subdaily的时间尺度上的这个属性。我们在科罗拉多的两个实验区应用这些方法,显示了雪中液态水含量的高变异性。体积液态水含量范围从接近零到19%vol米的规模内。我们还显示了在近日时间尺度上发生的高达5%vol的散装液态水含量的快速变化。所提出的方法具有1.5%vol的平均不确定性,使其适用于未来的研究,以估计雪中液态水的复杂时空动态。
Many communities and ecosystems around the world rely on mountain snowpacks to provide valuable water resources. An important consideration for water resources planning is runoff timing, which can be strongly influenced by the physical process of water storage within and release from seasonal snowpacks. The aim of this study is to present a novel method that combines light detection and ranging with ground‐penetrating radar to nondestructively estimate the spatial distribution of bulk liquid water content in a seasonal snowpack during spring snowmelt. We develop these methods in a manner to be applicable within a short time window, making it possible to spatially observe rapid changes that occur to this property at subdaily timescales. We applied these methods at two experimental plots in Colorado, showing the high variability of liquid water content in snow. Volumetric liquid water contents ranged from near zero to 19%vol within the scale of meters. We also show rapid changes in bulk liquid water content of up to 5%vol that occur over subdaily timescales. The presented methods have an average uncertainty in bulk liquid water content of 1.5%vol, making them applicable for future studies to estimate the complex spatio‐temporal dynamics of liquid water in snow.
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