Fine‐resolution soil moisture maps (10–30 m grid cells) are useful for many applications, including agricultural production and off‐road vehicle mobility. Fine‐resolution maps of soil moisture can be produced by downscaling coarse‐resolution soil moisture data from remote sensing. Soil moisture downscaling has been conducted by modeling key hydrologic processes in the soil, but current downscaling methods neglect two key aspects of soil hydrology: surface runoff and residual water content. The objective of this study is to understand how these hydrologic considerations affect spatial patterns of soil moisture and whether their inclusion improves downscaling performance. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) downscaling model is used to address these questions. Surface runoff is introduced to the model by implementing an infiltration capacity based on the saturated hydraulic conductivity. Residual water content is included by assuming that all hydrologic processes cease when soil moisture is at or below the residual water content. The pre‐existing EMT+VS model is compared with the new models using data from northeastern Colorado. The results show that both model additions introduce more complex dependence on the spatial variability of soil texture, which is difficult to estimate accurately. Including surface runoff provides only a small improvement in model performance, and residual water content shows almost no effect on the performance in this case. Thus, the simplifying assumptions of the pre‐existing model provide an appropriate level of complexity, given the uncertainties of the spatial input data.

中文翻译：

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如果不改善土壤特征，增强的水文模拟可能无法改善土壤尺度缩小的土壤水分模式

高分辨率的土壤湿度图（10–30 m网格）可用于许多应用，包括农业生产和越野车辆的机动性。可以通过缩小遥感的粗分辨率土壤水分数据的比例来生成精细分辨率的土壤水分图。通过模拟土壤中的关键水文过程来进行土壤水分降尺度，但是当前的降尺度方法忽略了土壤水文学的两个关键方面：地表径流和残留水分。这项研究的目的是了解这些水文因素如何影响土壤水分的空间格局以及它们的加入是否能改善降尺度性能。地形，植被和土壤的平衡水分（EMT + VS）降尺度模型用于解决这些问题。通过基于饱和水力传导率实现渗透能力，将表面径流引入模型。假定土壤湿度等于或低于残留水含量时，所有水文过程都将终止，则包括了残留水含量。使用科罗拉多州东北部的数据，将现有的EMT + VS模型与新模型进行了比较。结果表明，两种模型的加入都对土壤质地的空间变异性提出了更复杂的依赖性，这很难准确估计。在这种情况下，包括地表径流只会对模型性能产生很小的改善，而残留水分几乎对性能没有影响。因此，考虑到空间输入数据的不确定性，现有模型的简化假设提供了适当的复杂度。