| 基于修正Green-Ampt模型的降雨诱发区域浅层斜坡失稳灾害分析 |
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| 引用本文： | 阳帅,谭泽颖,陈宏信,张洁.基于修正Green-Ampt模型的降雨诱发区域浅层斜坡失稳灾害分析[J].地质科技通报,2022,41(2):219-227. |
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| 作者姓名： | 阳帅 谭泽颖 陈宏信 张洁 |
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| 基金项目： | 国家重点研发计划项目2021YFB260050国家自然科学基金项目42072302上海市教育发展基金会和上海市教育委员会曙光计划19SG19中央高校基本科研业务费专项资金 |
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| 摘 要： | 由于具有类似的工程地质和水文地质条件, 在高度相关的降雨作用下, 同一个区域中的降雨诱发浅层斜坡失稳灾害常成群出现。在区域尺度预测浅层斜坡失稳灾害对滑坡灾害的防灾减灾工作具有重要的意义。为此, 提出了一种基于力学原理的降雨诱发浅层斜坡失稳灾害预测新模型RARIL。该模型采用修正Green-Ampt模型进行降雨入渗分析, 采用无限体边坡模型进行安全系数计算, 利用可靠度原理考虑区域斜坡稳定性分析中的参数不确定性。该模型具有可考虑降雨诱发浅层斜坡的失稳力学机理、可考虑区域内斜坡土体参数不确定性, 以及计算效率高、易于在GIS平台上实现等优点。案例分析表明, RARIL模型较为准确地预测了2010年8月12日11∶00至2010年8月14日9∶00期间强降雨在四川省汶川县映秀镇附近的303省道K0-K20段沿线区域引发的滑坡灾害, 研究结果证明RARIL模型在预测降雨诱发区域斜坡失稳灾害方面有很好的应用前景。
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| 关 键 词： | Green-Ampt模型 蒙特卡罗法 区域滑坡 非稳态降雨 可靠度 浅层斜坡 |
| 收稿时间： | 2021-07-30 |
Analysis of instability disaster of rainfall induced shallow landslides at the regional scale based on the modified Green Ampt model |
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| Abstract: | Due to similar engineering and hydrogeological conditions, landslides in the same area often occur in groups under highly correlated rainfall. As a result, predicting shallow landslide instability disasters at the regional scale is of great significance to disaster prevention and mitigation work. This paper suggests a new prediction model, the regional assessment of rainfall induced landslides (RARIL), in which the modified Green-Ampt model is used to analyse rainfall infiltration, the infinite-slope model is used to calculate the safety factor, and the reliability principle is used to consider the parameter uncertainty in regional landslide stability analysis. The model has the advantages of considering the instability mechanism of rainfall-induced shallow landslides, the uncertainty of the slope soil parameters in the area, and high computational efficiency and can be easily implemented in GIS. The case study shows that the RARIL model can accurately predict the landslide disaster caused by heavy rainfall in the region along the 303 provincial Highway K0-K20 section from 11∶00 on August 12, 2010, to 9∶00 on August 14, 2010. Therefore, it has good application prospects in predicting regional landslide instability disasters induced by rainfall. |
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