Prediction of shallow landslide occurrence: Validation of a physically-based approach through a real case study.
Prediction of shallow landslide occurrence: Validation of a physically-based approach through a real case study.
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DOI：
10.1016/j.scitotenv.2016.06.124
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发表时间：
2016-11
期刊：
影响因子：
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通讯作者：
L. Schilirò;L. Montrasio;G. Scarascia Mugnozza
中科院分区：
文献类型：
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作者：
L. Schilirò;L. Montrasio;G. Scarascia Mugnozza
近年来，基于物理的数值模型经常被用于致力于滑坡灾害监测和减灾的预警系统的框架。出于这个原因，在这项工作中，我们描述了潜在的SLIP（浅层滑坡不稳定性预测），一个简化的基于物理的模型，用于分析浅层滑坡的发生。为了检验该模型的可靠性，对2009年10月1日发生在研究区（位于意大利西西里东北部墨西拿西南部）的滑坡事件进行了反分析。模拟结果已与那些获得了相同的事件，使用TRIGRS，另一个行之有效的模型浅层滑坡预测。之后，在同一地区进行了为期两年的模拟，目的是评估SLIP作为预警工具的性能。结果证实了良好的预测能力的模型，无论是在空间和时间预测的不稳定现象。出于这个原因，我们建议的操作程序，在流域尺度，这是基于使用SLIP校准通过一个特定的多方法的方法的实时定义浅层滑坡触发的情况。
In recent years, physically-based numerical models have frequently been used in the framework of early-warning systems devoted to rainfall-induced landslide hazard monitoring and mitigation. For this reason, in this work we describe the potential of SLIP (Shallow Landslides Instability Prediction), a simplified physically-based model for the analysis of shallow landslide occurrence. In order to test the reliability of this model, a back analysis of recent landslide events occurred in the study area (located SW of Messina, northeastern Sicily, Italy) on October 1st, 2009 was performed. The simulation results have been compared with those obtained for the same event by using TRIGRS, another well-established model for shallow landslide prediction. Afterwards, a simulation over a 2-year span period has been performed for the same area, with the aim of evaluating the performance of SLIP as early warning tool. The results confirm the good predictive capability of the model, both in terms of spatial and temporal prediction of the instability phenomena. For this reason, we recommend an operating procedure for the real-time definition of shallow landslide triggering scenarios at the catchment scale, which is based on the use of SLIP calibrated through a specific multi-methodological approach.