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Parameterization of soil properties for a model of topographic controls on shallow landsliding: application to Rio de Janeiro

机译:浅层滑坡地形控制模型的土壤特性参数化:在里约热内卢的应用

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摘要

A key problem in the use of physically based models of landslide hazards is how to parameterize the representation of soil properties. We applied a physically based model for the topographic control on shallow landsliding (SHALSTAB) to two catchments in Rio de Janeiro to investigate the accuracy of model results in relation to parameterization of soil properties. In so doing, we address the relevance of values derived from laboratory tests to the field problem, as well as the trade-offs inherent in model parameterization. We ran the model for all combinations of reasonable cohesion, bulk density, and friction angle values and compared model predictions to mapped landslides scars. We rank sorted model performance through the proportion of the total area of landslide scars correctly predicted as potentially unstable. Application of the model to an area where soil properties are not well known can be based on either a standard parameterization that emphasizes topographic controls, or on local calibration of soil parameters against a map of known landslide locations. Our analysis suggests that, in general, acquisition of high-quality digital elevation models (DEMs) is more important than generation of spatially detailed soil property values for reconnaissance level assessment of shallow landslide hazards.
机译:使用基于物理的滑坡灾害模型的关键问题是如何参数化土壤性质的表示。我们在里约热内卢的两个流域应用了基于物理的浅层滑坡地形控制模型(SHALSTAB),以研究与土壤特性参数化相关的模型结果的准确性。通过这样做,我们解决了从实验室测试得出的值与现场问题的相关性,以及模型参数化中固有的权衡问题。我们针对合理的内聚力,堆积密度和摩擦角值的所有组合运行了模型,并将模型预测与映射的滑坡疤痕进行了比较。我们通过正确预测为潜在不稳定的滑坡疤痕占总面积的比例对分类的模型性能进行排序。可以基于强调地形控制的标准参数化,也可以基于已知滑坡位置的地图对土壤参数进行局部校准,从而将模型应用到土壤特性不为人所知的地区。我们的分析表明,总体而言,对于浅层滑坡灾害的勘察水平评估,获取高质量的数字高程模型(DEM)比生成空间详细的土壤属性值更为重要。

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