The melt of seasonal snowpack in mountain regions provides downstream river basins with a critical supply of freshwater. Snowdrift-permitting models have been proposed as a way to accurately simulate snowpack heterogeneity that stems from differences in energy inputs, over winter redistribution, sublimation, melt, and variations in precipitation. However, these spatial scales can be computationally intractable for large extents. In this work, the multiscale Canadian Hydrological Model (CHM) was applied to simulate snowpacks at snowdrift-permitting scales (≈50 m) across the Canadian Cordillera and adjacent regions (1.37 million km²) forced by downscaled atmospheric data. The use of a multiscale land surface representation resulted in a reduction of computational elements of 98% while preserving land-surface heterogeneity. CHM includes complex terrain windflow and radiative transfer calculations, lapses temperature, humidity, and precipitation with elevation, redistributes snow by avalanching, wind transport and forest canopy interception and calculates the energetics of canopy and surface snowpacks. Model outputs were compared to a set of multiscale observations including snow-covered area (SCA) from Sentinel and Landsat imagery, snow depth from uncrewed aerial system lidar, and point surface observations of depth and density. Including snow redistribution and sublimation processes improved the summer SCA r² from 0.7 to 0.9. At larger scales, inclusion of snow redistribution processes delayed full snowpack ablation by an average of 33 days, demonstrating process emergence with scale. These simulations show how multiscale modeling can improve snowpack predictions to support prediction of water supply, droughts, and floods.

中文翻译：

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大范围山区季节性积雪过程的允许雪堆模拟


山区季节性积雪的融化为下游流域提供了重要的淡水供应。允许雪堆模型被提出作为一种准确模拟积雪异质性的方法，这种异质性源于能量输入的差异、冬季的重新分配、升华、融化和降水的变化。然而，这些空间尺度在很大程度上在计算上是难以处理的。在这项工作中，采用多尺度加拿大水文模型 (CHM) 来模拟受降尺度大气数据影响的加拿大科迪勒拉山脉和邻近地区 (137 万 km ² ) 允许雪堆尺度 (约 50 m) 的积雪。使用多尺度陆地表面表示可以减少 98% 的计算元素，同时保留陆地表面的异质性。 CHM 包括复杂地形风流和辐射传输计算、随海拔变化的温度、湿度和降水量，通过雪崩重新分布雪、风传输和森林冠层拦截，并计算冠层和表面积雪的能量。将模型输出与一组多尺度观测进行比较，包括来自 Sentinel 和 Landsat 图像的积雪覆盖区域 (SCA)、来自无人驾驶航空系统激光雷达的积雪深度以及深度和密度的点表面观测。包括雪的重新分布和升华过程将夏季 SCA r ²从 0.7 提高到 0.9。在更大的尺度上，包含雪的重新分布过程使积雪完全消融平均延迟了 33 天，这表明该过程随尺度的出现而出现。这些模拟展示了多尺度建模如何改进积雪预测，以支持供水、干旱和洪水的预测。