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Modelling the spatial variability of snow water equivalent at the catchment scale

机译:在流域尺度上模拟雪水当量的空间变异性

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The spatial distribution of snow water equivalent (SWE) is modelled as a two parameter gamma distribution. The parameters of the distribution are dynamical in that they are functions of the number of accumulation and melting events and the temporal correlation of accumulation and melting events. The estimated spatial variability is compared to snow course observations from the alpine catchments Norefjell and Aursunden in Southern Norway. A fixed snow course at Norefjell was measured 26 times during the snow season and showed that the spatial coefficient of variation change during the snow season with a decreasing trend from the start of the accumulation period and a sharp increase in the melting period. The gamma distribution with dynamical parameters reproduced the observed spatial statistical features of SWE well both at Norefjell and Aursunden. Also the shape of simulated spatial distribution of SWE agreed well with the observed at Norefjell. The temporal correlation tends to be positive for both accumulation and melting events. However, at the start of melting, a better fit between modelled and observed spatial standard deviation of SWE is obtained by using negative correlation between SWE and melt.
机译:雪水当量(SWE)的空间分布被建模为两个参数的伽马分布。分布的参数是动态的,因为它们是累积和融化事件的数量以及累积和融化事件的时间相关性的函数。将估计的空间变异性与挪威南部高山流域Norefjell和Aursunden的雪道观测结果进行比较。在雪季期间,对Norefjell的固定雪道进行了26次测量,结果表明,在雪季期间,空间变异系数发生了变化,从蓄积期开始便呈下降趋势,而融化期则急剧上升。具有动力学参数的伽马分布在Norefjell和Aursunden都很好地再现了SWE的空间统计特征。 SWE的模拟空间分布形状也与Norefjell观测到的相吻合。累积和融化事件的时间相关性往往呈正相关。但是,在熔化开始时,通过使用SWE和熔体之间的负相关性,可以在SWE的建模和观察到的空间标准偏差之间获得更好的拟合。

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