Abstract Snowpack melting in the High Atlas constitutes the major source of freshwater for the semi-arid agricultural plains of central Morocco. Snow runoff fills dams during spring and recharges groundwater, thus providing the necessary water for irrigation and hydropower production. Despite its critical importance for the region, basic questions about the High Atlas snowpack remain largely unanswered. In particular, the spatial and temporal distribution of snow water equivalent, as well as sublimation losses, potentially significant in this region, have yet to be thoroughly investigated. The scarcity of ground data has been a major obstacle to investigating snow processes in the High Atlas. Here, we demonstrate the potential of remotely-sensed meteorological variables and downscaled climate reanalysis data to gain important insights into snow water balance in a semi-arid region. We apply a distributed energy balance snow model based on SNOW17, constrained by topographic data, meteorological data from satellites and high-resolution dynamically-downscaled ERA-Interim data, to simulate snowpack dynamics within the Oum-Er-Rbia watershed, at the heart of Morocco’s High Atlas. The simulations are compared to MODIS snow cover maps and observed snow depth at one field station. Results show that the spatial extent and temporal dynamics of snow cover at various elevation ranges are accurately captured. The snowpack is essentially concentrated above 2500 m, extends over 500–6000 km2 and holds 0.05–0.4 km3 at its peak in early February. Additionally, we find that losses by sublimation range from 0.06 to 0.14 km3 for an average of 0.09 km3 a year, about 10% of all snowfall. Above 3000 m elevation, sublimation removes on average 20% of the snowpack. Finally, we discuss the sensitivity of our results to uncertainties in the forcing meteorological data. This study reveals the essential components of the snow water balance in the High Atlas and paves the way for better understanding of its sensitivity to climate change.

中文翻译：

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高阿特拉斯的季节性积雪动态

摘要 High Atlas 中的积雪融化是摩洛哥中部半干旱农业平原的主要淡水来源。春季积雪径流填满水坝并补充地下水，从而为灌溉和水电生产提供必要的水。尽管它对该地区至关重要，但关于高阿特拉斯积雪的基本问题在很大程度上仍未得到解答。特别是，雪水当量的空间和时间分布以及在该地区可能显着的升华损失尚未得到彻底调查。地面数据的稀缺一直是调查高阿特拉斯雪过程的主要障碍。这里，我们展示了遥感气象变量和缩小规模的气候再分析数据的潜力，以获得对半干旱地区雪水平衡的重要见解。我们应用基于 SNOW17 的分布式能量平衡雪模型，受地形数据、卫星气象数据和高分辨率动态缩小的 ERA-Interim 数据的约束，以模拟 Oum-Er-Rbia 流域内的积雪动力学。摩洛哥的高阿特拉斯。将模拟与 MODIS 积雪图和在一个现场站观测到的积雪深度进行比较。结果表明，可以准确捕获不同海拔范围内积雪的空间范围和时间动态。积雪基本上集中在 2500 m 以上，延伸超过 500-6000 平方公里，并在 2 月初的高峰期保持 0.05-0.4 平方公里。此外，我们发现升华造成的损失范围为 0.06 到 0.14 平方公里，平均每年 0.09 平方公里，约占所有降雪量的 10%。在海拔 3000 m 以上，升华平均会去除 20% 的积雪。最后，我们讨论了我们的结果对强迫气象数据中的不确定性的敏感性。这项研究揭示了高阿特拉斯雪水平衡的基本组成部分，并为更好地了解其对气候变化的敏感性铺平了道路。