Although agricultural intensification has generally increased crop yields, it also resulted in a range of environmental issues. These include increased erosion rates and declined soil organic carbon (SOC) stocks. In order to improve our understanding on how erosion impacts the overall SOC storage capacity of croplands, this study analyses the 3D distribution of SOC as a function of water and tillage erosion in a conventionally ploughed field in the Belgian silt loam region. We present a novel methodological framework to integrate the output of an advanced erosion model as a co-variate within a Digital Soil Mapping (DSM) approach with the objective to create detailed SOC maps. More precisely, we combined (i) the Water and Tillage Erosion Model and Sediment Delivery Model (WaTEM/SEDEM), simulating spatial patterns of soil erosion and sediment deposition due to water and tillage erosions, with (ii) a SOC sampling campaign, resulting in a SOC spatial distribution model that considers both types of erosion. The results show that, as compared to plateaus, SOC stocks are nearly half as large along eroding slopes (i.e. convex slope positions affected by tillage erosion and steep slopes affected by water erosion). Yet, they are up to twice as large in areas characterized by sediment deposition (i.e. concave positions due to tillage erosion and foot slope positions due to water erosion). Our results further show that tillage erosion has a significant influence on the SOC stocks in the top 0.7 m and in particular on the top 0.4 m. The influence of water erosion is less strong but mostly significant along the entire depth profile. Overall, this work demonstrates the relevance of considering different erosion processes when aiming to predict spatial patterns of SOC. Considering the top 1 m and a WaTEM/SEDEM application at a resolution of 10 m our 3D SOC modelling approach obtained a coefficient of determination (R) of 0.62, a relative root mean square error (RRMSE) of 30.5 % and a relative mean absolute error (RMAE) of 26.0 %. While future work may likely lead to further improvements e.g. a more detailed SOC sampling network along the foot slopes and thalwegs in order to obtain a more spatially detailed prediction of the area characterized by depositions due to water erosion, we demonstrate the great potential of existing erosion and deposition models in doing so.

中文翻译：

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通过将水和耕作侵蚀的预测整合到数字土壤制图方法中来评估土壤有机碳的 3D 分布：粉质壤土农田的案例研究（比利时）


尽管农业集约化普遍提高了农作物产量，但也导致了一系列环境问题。其中包括侵蚀率增加和土壤有机碳（SOC）储量下降。为了加深我们对侵蚀如何影响农田整体 SOC 存储能力的理解，本研究分析了比利时淤泥质壤土地区传统犁耕田地中 SOC 的 3D 分布，作为水和耕作侵蚀的函数。我们提出了一种新颖的方法框架，将先进侵蚀模型的输出集成为数字土壤测绘 (DSM) 方法中的协变量，目的是创建详细的 SOC 地图。更准确地说，我们将 (i) 水耕侵蚀模型和沉积物输送模型 (WaTEM/SEDEM) 与 (ii) SOC 采样活动相结合，模拟水土流失和耕作侵蚀引起的土壤侵蚀和沉积物沉积的空间模式，从而得出在考虑两种类型侵蚀的 SOC 空间分布模型中。结果表明，与高原相比，侵蚀斜坡（即受耕作侵蚀影响的凸坡位置和受水力侵蚀影响的陡坡位置）的 SOC 储量几乎是高原的一半。然而，在具有沉积物沉积特征的区域（即由于耕作侵蚀而形成的凹处和由于水力侵蚀而形成的坡脚位置），它们的面积高达两倍。我们的结果进一步表明，耕作侵蚀对顶部 0.7 m，特别是顶部 0.4 m 的 SOC 储量有显着影响。水蚀的影响较弱，但沿整个深度剖面最为显着。总体而言，这项工作证明了在预测 SOC 空间模式时考虑不同侵蚀过程的相关性。 考虑到顶部 1 m 和分辨率为 10 m 的 WaTEM/SEDEM 应用，我们的 3D SOC 建模方法获得了 0.62 的决定系数 (R)、30.5% 的相对均方根误差 (RRMSE) 和相对平均绝对值误差 (RMAE) 为 26.0%。虽然未来的工作可能会带来进一步的改进，例如为了对因水蚀而沉积的区域进行更详细的空间预测，我们沿着脚坡和海堤建立了更详细的 SOC 采样网络，证明了现有侵蚀和沉积模型在这方面的巨大潜力。