基于物理的滑坡易发性概率建模 QGIS 框架:QGIS-FORM

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Environmental Modelling & Software Pub Date : 2024-10-29 DOI:10.1016/j.envsoft.2024.106258
Jian Ji , Bin Tong , Hong-Zhi Cui , Xin-Tao Tang , Marcel Hürlimann , Shigui Du
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引用次数: 0

摘要

地震引发的区域性山体滑坡经常造成重大经济损失和人员伤亡。进行滑坡易发性评估对于降低这些风险和减少潜在损失至关重要。为了满足各学科专业人员的不同需求,我们为 QGIS 开发了一个开源插件,名为 QGIS-FORM。该插件集成了基于物理的模型(PM)和基于物理的概率模型(PPM)的功能。物理模型采用伪静态无限边坡稳定性模型,而概率模型则利用改进的一阶可靠性方法(FORM)对空间区域进行滑坡概率分析。为验证其有效性,该插件被应用于 2022 年的马康滑坡事件。在 PM 和 PPM 的基础上,使用多个参数(包括坡度、坡向、地层和 PGA)对滑坡易发性进行了评估。此外,还采用了接收者工作特征曲线(ROC)和平衡精度来评估其预测性能。滑坡易发性结果表明,马尔康的滑坡主要集中在 30° 至 50° 的斜坡上,新都桥地层(T3X)的地质条件更容易发生滑坡。与 PM 相比,当参数的不确定性得到适当描述时,PPM 可获得更高的 AUC 值。总体而言,与基于物理的模型相比,PPM 模型具有更高的精度和更强的识别潜在滑坡的能力,从而为滑坡灾害风险的管理和缓解提供了更可靠的方法和/或科学依据。
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A QGIS framework for physically-based probabilistic modelling of landslide susceptibility: QGIS-FORM
Earthquake-induced regional landslides frequently result in substantial economic losses and casualties. Conducting landslide susceptibility assessments is essential for mitigating these risks and minimizing potential damage. To address the diverse needs of professionals in various disciplines, we have developed an open-source plugin for QGIS, named QGIS-FORM. This plugin integrates functions of both physically-based model (PM) and physically-based probabilistic model (PPM). The PM employs pseudo-static infinite slope stability model, while the PPM utilizes an improved first order reliability method (FORM) to perform landslide probability analysis over a spatial region. To verify its effectiveness, the plugin was applied to the Maerkang landslide event in 2022. Based on the PM and the PPM, the landslide susceptibility assessments were evaluated using several parameters including slope, aspect, stratum, and PGA. In addition, the Receiver Operating Characteristic (ROC) curve and Balanced Accuracy were employed to assess their predictive performance. The landslide susceptibility results indicate that landslides in Maerkang are mostly concentrated in slopes between 30° and 50°, and the geological conditions of the Xinduqiao Formation (T3X) are more prone to landslides. Compared to PM, the PPM can achieve higher AUC values when the parameter uncertainties are properly characterized. Overall, the PPM exhibits higher accuracy and is more capable of identifying potential landslides than the physically-based model, thereby providing a more reliable way and/or offering a scientific basis for the management and mitigation of landslide disaster risks.
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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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