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首页> 外文期刊>Hydrology and Earth System Sciences >The role of liquid water percolation representation in estimating snow water equivalent in a Mediterranean mountain region (Mount Lebanon)
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The role of liquid water percolation representation in estimating snow water equivalent in a Mediterranean mountain region (Mount Lebanon)

机译:液体水渗透表示在地中海山区估算雪水中的作用(黎巴嫩山)

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In many Mediterranean mountain regions, the seasonal snowpack is an essential yet poorly known water resource. Here, we examine, for the first time, the spatial distribution and evolution of the snow water equivalent (SWE) during three snow seasons (2013–2016) in the coastal mountains of Lebanon. We run SnowModel (Liston and Elder, 2006a), a spatially distributed, process-based snow model, at 100 m resolution forced by new automatic weather station (AWS) data in three snow-dominated basins of Mount Lebanon. We evaluate a recent upgrade of the liquid water percolation scheme in SnowModel, which was introduced to improve the simulation of the SWE and runoff in warm maritime regions. The model is evaluated against continuous snow depth and snow albedo observations at the AWS, manual SWE measurements, and MODIS snow cover area between 1200 and 3000 m a.s.l. The results show that the new percolation scheme yields better performance, especially in terms of SWE but also in snow depth and snow cover area. Over the simulation period between 2013 and 2016, the maximum snow mass was reached between December and March. Peak mean SWE (above 1200 m a.s.l.) changed significantly from year to year in the three study catchments, with values ranging between 73 and 286 mm w.e. (RMSE between 160 and 260 mm w.e.). We suggest that the major sources of uncertainty in simulating the SWE, in this warm Mediterranean climate, can be attributed to forcing error but also to our limited understanding of the separation between rain and snow at lower-elevations, the transient snowmelt events during the accumulation season, and the high variability of snow depth patterns at the subpixel scale due to the wind-driven blown-snow redistribution into karstic features and sinkholes. Yet, the use of a process-based snow model with minimal requirements for parameter estimation provides a basis to simulate snow mass SWE in nonmonitored catchments and characterize the contribution of snowmelt to the karstic groundwater recharge in Lebanon. While this research focused on three basins in the Mount Lebanon, it serves as a case study to highlight the importance of wet snow processes to estimate SWE in Mediterranean mountain regions.
机译:在许多地中海山区,季节性雪崩是一个必不可少的知名水资源。在这里,我们首次检查雪季三雪季节(2013-2016)的雪水等同(SWE)的空间分布和演变。我们在黎巴嫩三个雪撬盆地中迫使新的自动气象站(AWS)数据,以100米的分辨率运行SnowModel(Liston和Gender,2006A),以100米的分辨率,在黎巴嫩三个雪撬盆地中被迫被新的自动气象站(AWS)数据。我们评估了最近升级SnowModel中的液态水渗透方案,这是在温暖的海上地区改善SWE和径流的模拟。该模型在AWS,手动SWE测量和Modis雪覆盖面积的连续雪深度和雪剂观测中进行评估,以及1200到3000米A.L.结果表明,新的渗透方案产生了更好的性能,特别是在SWE方面,也是在雪藏和雪覆盖区域方面。在2013年至2016年间的仿真期间,12月至3月之间达到了最大的雪群。峰值平均SWE(超过1200米A.L.)从三个研究流域的一年中显着变化,值在73到286毫米之间。 (RMSE在160到260 mm w之间。我们建议在这种温暖的地中海气候中模拟SWE的主要不确定性来源可以归因于迫使错误,但也迫使我们对雨水和较高海滩之间分离的了解,瞬态融雪事件在积累期间季节,以及子像素尺度下雪深度模式的高变异性,由于风力驱动的吹雪再分配到岩溶特征和下沉雪地。然而,利用基于过程的雪模型对参数估计的最小要求提供了基础,为在非监控集水区中模拟雪大质量SWE,并表征了雪花对黎巴嫩喀斯特地下水充电的贡献。虽然这项研究专注于黎巴嫩山的三个盆地,其作为一个案例研究,以突出湿雪流程的重要性来估算地中海山区的SWE。

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