Understanding and characterizing the spatial distribution of snow are critical to represent the energy balance and runoff production in mountain environments. In this study, we investigate the interannual and seasonal variability in snow depth scaling behavior at the Izas experimental catchment of the Spanish Pyrenees (2,000 to 2,300 m above sea level). We conduct variogram analyses of 24 snow depth maps derived from terrestrial light detection and ranging scans, acquired during six consecutive snow seasons (2011–2017) that span a range of hydroclimatic conditions. We complement our analyses with bare ground topography data and wind speed and direction measurements. Our results show temporal consistency in the spatial variability of snow depth, with short‐range fractal behavior and scale break lengths that are similar to the optimal search distance (25 m) previously reported for the topographic position index, a terrain‐based predictor of snow depth. Beyond the 25‐m scale break, there is little to no fractal structure. We report a long‐range scale break of the order of 185–300 m for most dates—aligned with the dominant wind direction—and patterns between anisotropies in scale break lengths of shallow snow cover and directional terrain scaling behavior. The temporal consistency of snow depth scaling patterns suggests that, in addition to guiding the spatial configuration of physically based models, fractal analysis could be used to inform the design of independent variables for statistical models used to predict snow depth and its variability.

中文翻译：

---

亚高山流域积雪深度变化行为的年际和季节变化

了解和表征雪的空间分布对于代表山区环境中的能量平衡和径流产生至关重要。在这项研究中，我们调查了西班牙比利牛斯山脉伊萨斯实验流域（海拔2,000至2,300 m）雪深尺度行为的年际和季节变化。我们对24个雪深图进行了变异函数分析，这些雪深图是从陆地光检测和测距扫描获得的，这些雪深图是在六个连续的雪季（2011-2017年）中跨越一系列水文气候条件采集的。我们用裸露的地面地形数据以及风速和风向测量来补充我们的分析。我们的结果表明，雪深的空间变化具有时间一致性，其短程分形行为和阻垢长度与先前针对地形位置指数（基于地形的雪深预测指标）报告的最佳搜索距离（25 m）相似。除了25 m的刻度断裂，几乎没有分形结构。我们报告了大多数日期的185-300 m量级的远距离尺度断裂（与主要风向一致），以及浅雪覆盖层尺度断裂长度的各向异性与定向地形尺度变化行为之间的关系。积雪深度缩放模式的时间一致性表明，除了指导基于物理的模型的空间配置外，分形分析还可以用于告知独立变量的设计，以供用于预测积雪深度及其可变性的统计模型使用。