Abstract In theoretical pedology, the advantage of factor-process-properties models over factor-properties models has been confirmed for the understanding of soil genesis and its changes over time. Currently, the most frequently used model in digital soil mapping (DSM) is the SCORPAN model, which is based on the Dokuchaev-Jenny formula: soil properties are the result of the interactions among soil-forming factors over time. This work aims to incorporate processed-based modeling into DSM and investigate the use of a hydrological model to predict the soil spatial heterogeneity and simulate its spatiotemporal evolution over time in the Central Chernozem Reserve (East European Plain). Our approach, called the Nested Landscape Soil Triad: Factor-Process-Properties, is based on the subordination of soil processes to landscape processes and the nesting of the soil system into the landscape. Landscape processes result in specific landscape properties, which control the direction and intensity of soil-forming processes, and thus control soil properties. We hypothesize that, in the virgin steppe, the result of moisture redistribution via runoff along topography (landscape process) can be expressed quantitatively in the redistributed runoff value (landscape property) that controls the movement of salts within the soil profile (soil-forming processes) and soil taxa (soil properties). We directly linked a result of the landscape process and soil properties due to difficulties in soil-forming processes modeling. We conducted a prediction across the 35 ha study area using a 2.5 m digital elevation model (DEM) and 157 soil profile descriptions as input. The moisture redistribution process was simulated using SIMulated Water Erosion (SIMWE), implemented in open-access software (GRASS GIS). To define the optimal parameter combination for the SIMWE model, we performed multiparameter sensitivity test and optimization. We used Latin Hypercube sampling to generate the 3000 × 6 (the size of sample per number of parameters) parameter set for Monte Carlo ensemble runs within SIMWE. The maximum correspondence between the soil cover pattern and simulated flow depth was achieved with infiltration values of 0–10 mm h−1, Manning’s n of −0.3 to 1.0, water diffusion constant of −0.3 to 0.5, threshold water depth of −0.1 to 0.15 m, diffusion increase constant of −3 to 6, and precipitation excess rate of 60 mm h−1. The runoff redistribution values alone determine the carbonate depth in the soils (64% accuracy) and soil taxa (76% accuracy). Overall, the Nested Landscape Soil Triad: Factor-Process-Properties can explore how soil properties have changed and will change through time and identify areas with risks of soil taxa changes. The contradiction between the selected optimal precipitation excess and current climate prove the polygenetic formation of forest-steppe soils. This approach can be used to inform policymakers and large-scale management to ensure soil security.

中文翻译：

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将基于过程的建模纳入数字土壤制图：俄罗斯中部高地原始草原的案例研究

摘要 在理论土壤学中，因子-过程-特性模型相对于因子-特性模型的优势在理解土壤成因及其随时间的变化方面已得到证实。目前，数字土壤制图 (DSM) 中最常用的模型是 SCORPAN 模型，该模型基于 Dokuchaev-Jenny 公式：土壤特性是土壤形成因素随时间相互作用的结果。这项工作旨在将基于处理的建模纳入 DSM，并研究使用水文模型来预测土壤空间异质性并模拟其在中央黑钙土保护区（东欧平原）随时间的时空演变。我们的方法，称为嵌套景观土壤三元组：因子-过程-属性，是基于土壤过程从属于景观过程以及土壤系统嵌套在景观中。景观过程导致特定的景观特性，它控制着土壤形成过程的方向和强度，从而控制土壤特性。我们假设，在原始草原中，通过沿地形径流（景观过程）的水分再分配的结果可以定量地表达为控制土壤剖面内盐分运动的再分配径流值（景观特性）（土壤形成过程） ）和土壤分类群（土壤特性）。由于土壤形成过程建模的困难，我们直接将景观过程和土壤特性的结果联系起来。我们使用 2 对 35 公顷研究区域进行了预测。5 m 数字高程模型 (DEM) 和 157 个土壤剖面描述作为输入。水分再分布过程是使用模拟水侵蚀 (SIMWE) 模拟的，在开放访问软件 (GRASS GIS) 中实现。为了定义 SIMWE 模型的最佳参数组合，我们进行了多参数灵敏度测试和优化。我们使用拉丁超立方体采样为 SIMWE 内的 Monte Carlo 集成运行生成 3000 × 6（每个参数数量的样本大小）参数集。土壤覆盖模式与模拟水流深度之间的最大对应是通过下渗值为 0-10 mm h-1，曼宁 n 为 -0.3 至 1.0，水扩散常数为 -0.3 至 0.5，阈值水深为 -0.1 至0.15 m，扩散增加常数为−3 到 6，降水过量率为 60 mm h−1。径流再分布值单独决定了土壤中的碳酸盐深度（准确度为 64%）和土壤分类群（准确度为 76%）。总体而言，嵌套景观土壤三元组：因子-过程-属性可以探索土壤属性如何随时间变化以及将如何变化，并确定具有土壤分类群变化风险的区域。选择的最优降水过剩与当前气候之间的矛盾证明了森林草原土壤的多基因形成。这种方法可用于通知决策者和大规模管理人员，以确保土壤安全。Factor-Process-Properties 可以探索土壤特性如何随时间变化以及将如何变化，并确定具有土壤分类群变化风险的区域。选择的最优降水过剩与当前气候之间的矛盾证明了森林草原土壤的多基因形成。这种方法可用于通知决策者和大规模管理人员，以确保土壤安全。Factor-Process-Properties 可以探索土壤特性如何随时间变化以及将如何变化，并确定具有土壤分类群变化风险的区域。选择的最优降水过剩与当前气候之间的矛盾证明了森林草原土壤的多基因形成。这种方法可用于通知决策者和大规模管理人员，以确保土壤安全。