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Small scale spatial variability of snow density and depth over complex alpine terrain: Implications for estimating snow water equivalent

机译:复杂高山地形上雪密度和深度的小范围空间变异性:估算雪水当量的意义

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摘要

This study analyzes spatial variability of snow depth and density from measurements made in February and April of 2010 and 2011 in three 1–2 km2 areas within a valley of the central Spanish Pyrenees. Snow density was correlated with snow depth and different terrain characteristics. Regression models were used to predict the spatial variability of snow density, and to assess how the error in computed densities might influence estimates of snow water equivalent (SWE). The variability in snow depth was much greater than that of snow density. The average snow density was much greater in April than in February. The correlations between snow depth and density were generally statistically significant but typically not very high, and their magnitudes and signs were highly variable among sites and surveys. The correlation with other topographic variables showed the same variability in magnitude and sign, and consequently the resulting regression models were very inconsistent, and in general explained little of the variance. Antecedent climatic and snow conditions prior to each survey help highlight the main causes of the contrasting relation shown between snow depth, density and terrain. As a consequence of the moderate spatial variability of snow density relative to snow depth, the absolute error in the SWE estimated from computed densities using the regression models was generally less than 15%. The error was similar to that obtained by relating snow density measurements directly to adjacent snow depths.
机译:这项研究从2010年2月,2010年4月和2011年在西班牙比利牛斯山脉中部山谷的三个1-2 km2地区进行的测量分析了雪深和密度的空间变异性。雪密度与雪深和不同的地形特征相关。回归模型用于预测积雪密度的空间变异性,并评估计算密度的误差如何影响积雪水当量(SWE)的估算。雪深的变化远大于雪密度的变化。四月的平均雪密度比二月大得多。积雪深度和密度之间的相关性通常具有统计学意义,但通常不是很高,并且它们的大小和迹象在站点和调查之间变化很大。与其他地形变量的相关性在大小和符号上显示出相同的变异性,因此,所得的回归模型非常不一致,并且总体上解释的差异很小。每次调查之前的气候和降雪条件有助于突出显示造成雪深,密度和地形之间形成对比关系的主要原因。由于积雪密度相对于积雪深度的适度空间变异性,使用回归模型根据计算密度估算出的SWE的绝对误差通常小于15%。该误差类似于通过将积雪密度测量值直接与相邻积雪深度相关而获得的误差。

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