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首页> 外文期刊>Earth Surface Processes and Landforms: The journal of the British Geomorphological Research Group >Assessment of calanchi and rill-interrill erosion susceptibilities using terrain analysis and geostochastics: A case study in the Oltrepo Pavese, Northern Apennines, Italy
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Assessment of calanchi and rill-interrill erosion susceptibilities using terrain analysis and geostochastics: A case study in the Oltrepo Pavese, Northern Apennines, Italy

机译：利用地形分析和地产科技评估Calanchi和RILL-Interiorion侵蚀敏感性：奥尔特雷普帕夫，意大利北部亚平诺的案例研究

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摘要

Soil erosion is one of the most important environmental problems distributed worldwide. In the last decades, numerous studies have been published on the assessment of soil erosion and the related processes and forms using empirical, conceptual and physically based models. For the prediction of the spatial distribution, more and more sophisticated stochastic modelling approaches have been proposed - especially on smaller spatial scales such as river basins. In this work, we apply a maximum entropy model (MaxEnt) to evaluate badlands (calanchi) and rill-interrill (sheet erosion) areas in the Oltrepo Pavese (Northern Apennines, Italy). The aim of the work is to assess the important environmental predictors that influence calanchi and rill-interrill erosion at the regional scale. We used 13 topographic parameters derived from a 12 m digital elevation model (TanDEM-X) and data on the lithology and land use. Additional information about the vegetation is introduced through the normalized difference vegetation index based on remotely sensed data (ASTER images). The results are presented in the form of susceptibility maps showing the spatial distribution of the occurrence probability for calanchi and rill-interrill erosion. For the validation of the MaxEnt model results, a support vector machine approach was applied. The models show reliable results and highlight several locations of the study area that are potentially prone to future soil erosion. Thus, coping and mitigation strategies may be developed to prevent or fight the soil erosion phenomenon under consideration. (c) 2020 John Wiley & Sons, Ltd.
机译：土壤侵蚀是全球分布的最重要的环境问题之一。在过去的几十年中，已经发表了许多研究，以评估土壤侵蚀和相关流程以及使用经验，概念和物理基础的模型形式。为了预测空间分布，已经提出了越来越复杂的随机建模方法 - 尤其是在诸如河流盆地等较小的空间尺度上。在这项工作中，我们应用了最大熵模型（MaxEnt），以评估Oltrepo Pavene（意大利北亚平宁山脉）的荒地（Calanchi）和罗格里歇（薄板侵蚀）区域。这项工作的目的是评估影响Calanchi和Rill-Insteripl侵蚀在区域规模的重要环保预测因子。我们使用了从12米数字高度模型（TANDEM-X）和岩性和土地使用的数据衍生的13个地形参数。有关植被的其他信息是通过基于远程感测数据（ASTER图像）的归一化差异植被指数引入的。结果以易感图的形式提出，显示了Calanchi和瑞尔内侵蚀侵蚀的发生概率的空间分布。为了验证最大模型结果，应用了支持向量机方法。该模型显示了可靠的结果，并突出了几个可能易于未来土壤侵蚀的研究区域的位置。因此，可以制定应对和缓解策略以防止或打击正在考虑的土壤侵蚀现象。 （c）2020 John Wiley＆Sons，Ltd。

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