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Estimating the snow water equivalent from snow depth measurements in the Italian Alps

机译:通过意大利阿尔卑斯山的积雪深度估算来估算积雪水量

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摘要

The Snow Water Equivalent (SWE), combining the information of snow depth (Hs) and snow bulk density (rho b) is a necessary variable for snow-hydrological studies and applications, as well as, for ecological function or avalanche forecasting. The SWE direct measurement is challenging, and estimating the SWE from the single Hs measurements presents many advantages compared to the direct SWE measurement or the implementation of complex model needing to be fed by local meteorological data. In this study we propose a spatial and temporal variability description of the SWE, Hs and rho b and compare existing approaches over the Italian Alps. Finally, we propose a simple parametrization, introducing non-linearly in the snow bulk density variability. The resulting overall uncertainty on SWE is 15.6%. The proposed model has the potential to be a valuable tool to estimate the SWE from the only HS measurement in the Italian Alps, presenting even better performances during the late season (13.9%, 12.9% and 14.3% in March, April and May, respectively) that makes it particularly suitable for snow-hydrology studies.
机译:雪水当量(SWE),结合雪深(Hs)和雪堆积密度(rho b)的信息,对于雪水文学研究和应用以及生态功能或雪崩预报来说是一个必要变量。 SWE直接测量具有挑战性,并且与直接SWE测量或需要由本地气象数据提供的复杂模型的实现相比,从单个Hs测量估计SWE具有许多优势。在这项研究中,我们提出了SWE,Hs和rhob的时空变化描述,并比较了意大利阿尔卑斯山上的现有方法。最后,我们提出了一个简单的参数化方法,将雪堆密度的可变性非线性地引入。由此得出的SWE总体不确定性为15.6%。拟议的模型有可能成为有价值的工具,可以根据意大利阿尔卑斯山唯一的HS测量来估算SWE,在后期季节表现得更好(3月,4月和5月分别为13.9%,12.9%和14.3%) ),因此特别适合雪水文学研究。

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