ISSN 1000-3665 CN 11-2202/P
    刘凡,邓亚虹,慕焕东,等. 基于最大熵-无限边坡模型的降雨诱发浅层黄土滑坡稳定性评价方法研究[J]. 水文地质工程地质,2023,50(5): 146-158. DOI: 10.16030/j.cnki.issn.1000-3665.202207050
    引用本文: 刘凡,邓亚虹,慕焕东,等. 基于最大熵-无限边坡模型的降雨诱发浅层黄土滑坡稳定性评价方法研究[J]. 水文地质工程地质,2023,50(5): 146-158. DOI: 10.16030/j.cnki.issn.1000-3665.202207050
    LIU Fan, DENG Yahong, MU Huandong, et al. A study of the stability evaluation method of rainfall-induced shallow loess landslides based on the Maxent-Sinmap slope model[J]. Hydrogeology & Engineering Geology, 2023, 50(5): 146-158. DOI: 10.16030/j.cnki.issn.1000-3665.202207050
    Citation: LIU Fan, DENG Yahong, MU Huandong, et al. A study of the stability evaluation method of rainfall-induced shallow loess landslides based on the Maxent-Sinmap slope model[J]. Hydrogeology & Engineering Geology, 2023, 50(5): 146-158. DOI: 10.16030/j.cnki.issn.1000-3665.202207050

    基于最大熵-无限边坡模型的降雨诱发浅层黄土滑坡稳定性评价方法研究

    A study of the stability evaluation method of rainfall-induced shallow loess landslides based on the Maxent-Sinmap slope model

    • 摘要: 无限边坡(Sinmap)模型在评价降雨作用下浅层黄土滑坡稳定性时精度较低。针对这一问题,基于最大熵(Maxent)模型对Sinmap模型评价进行改进,构建了最大熵-无限边坡(Maxent-Sinmap)模型,评价降雨作用下区域性浅层降雨型黄土滑坡稳定性。以黄土滑坡高发区的陕西省志丹县为例,利用野外及室内相关工作获取地形、岩土体力学参数及地质灾害等相关数据,通过Maxent模型获取主要环境变量,再根据主要环境变量进行分区,通过Sinmap模型对降雨作用下不同分区的浅层黄土滑坡稳定性进行评价。研究结果表明:基于Maxent模型得到志丹县内滑坡主要受坡度、降雨量、地貌、道路缓冲区及归一化植被覆盖指数等5个指标影响,对历史灾点的贡献率分别为27.1%、20.3%、18.8%、18.7%、6.2%。相较于传统Sinmap模型,该模型不稳定区域灾点密度在小雨、中雨、大雨、暴雨和大暴雨情况下分别提高了17.26%、16.54%、17.39%、14.20%、12.96%。Maxent-Sinmap模型计算结果相较于Sinmap模型计算结果具有更大的稳定区域,且稳定区的扩大区无历史灾点分布。表明该模型具有更高精度及更可靠的结果,可以更好的为区域性浅层降雨型滑坡评价提供科学依据。

       

      Abstract: To address the problem of low evaluation accuracy of the Sinmap model in evaluating the stability of shallow loess landslides under the action of rainfall, a method based on the Maxent-Sinmap model is constructed to evaluate the stability of regional shallow rainfall loess landslides under the action of rainfall by improving the evaluation of the Sinmap model based on the maximum entropy model.Taking Zhidan County, Shaanxi Province, a high-incidence area of loess landslides, as an example, the relevant data of topography, geotechnical parameters and geological disasters were obtained by field and indoor work. The main environmental variables were obtained by Maxent model, and then the main environmental variables were partitioned. The Sinmap model was used to evaluate the stability of shallow loess landslides in different partitions under rainfall. The results show that based on the Maxent model, the landslide in Zhidan County is mainly affected by five indicators, such as slope, rainfall, landform, road buffer zone and normalized vegetation coverage index. The contribution rates to historical disaster points are 27.1 %, 20.3 %, 18.8 %, 18.7 % and 6.2 %, respectively. Compared with the traditional Sinmap model, the density of disaster points in the unstable area of the model increased by 17.26 %, 16.54 %, 17.39 %, 14.20 % and 12.96 % respectively under the conditions of light rainfall, moderate rainfall, heavy rainfall, rainstorm and downpour. The results of the Maxent-Sinmap model have a larger stable area than those of the Sinmap model, and there is no historical disaster distribution in the expanded area of the stable area. The model has higher accuracy and more reliable results, which can provide a better scientific basis for the evaluation of regional shallow rainfall landslides.

       

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