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Modeling the spatial distribution of snow water equivalent, taking into account changes in snow-covered area

机译:考虑到冰雪覆盖地区的变化,模拟雪水当量的空间分布

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A good estimate of the spatial probability density function (PDF) of snow water equivalent (SWE) provides the mean of the snow reservoir, but also enables modelling of the changes in snowcovered area (SCA), which is crucial for the runoff dynamics in spring. The spatial PDF of accumulated SWE is here modelled as a sum of correlated gamma-distributed variables, called units. The spatial variance of accumulated SWE is evaluated by the covariance matrix of the units. For accumulation events, there are only positive elements in the covariance matrix, whereas for melting events there are both positive and negative elements. The negative elements dictate that the correlation between melt and SWE is negative. After accumulation and melting events, the changes in the spatial moments are weighted by changes in SCA. Results from the model are in good agreement with observed spatial moments of SWE and SCA and found to provide better estimates of the spatial variability than the current model for snow distribution used in the Norwegian version of the Swedish rainfall–runoff model HBV. The parameters in the distribution model are estimated from observed historical precipitation, so no calibration parameters are introduced.
机译:对雪水当量(SWE)的空间概率密度函数(PDF)进行良好的估算不仅可以提供积雪的平均值,而且还可以对积雪面积(SCA)的变化进行建模,这对于春季的径流动力学至关重要。累积SWE的空间PDF在此建模为相关的伽玛分布变量之和,称为单位。累积SWE的空间方差由单位的协方差矩阵评估。对于累积事件,协方差矩阵中只有正元素,而对于融化事件,既有正元素又有负元素。负元素指示熔体和SWE之间的相关为负。在积累和融化事件之后,空间矩的变化由SCA的变化加权。该模型的结果与观测到的SWE和SCA的空间矩非常吻合,并且比挪威版本的瑞典降雨-径流模型HBV中使用的当前降雪模型提供了更好的空间变异性估计。分布模型中的参数是根据观测到的历史降水估算的,因此没有引入校准参数。

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