Research on delayed effect of landslides caused by air pressure under heavy rainfall

HAN Tong-chun; MA Shi-guo; XU Ri-qing

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Research on delayed effect of landslides caused by air pressure under heavy rainfall

更新时间：2026-06-25

- Research on delayed effect of landslides caused by air pressure under heavy rainfall
- Vol. 34, Issue 5, (2013)
- 作者机构：
  
  1. 浙江大学滨海和城市岩土工程研究中心,杭州,310058
  2. 浙江大学软弱土与环境土工教育部重点实验室,杭州,310058
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU441
- Online First：14 May 2013，
  
  Published：2013
- 稿件说明：
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HAN Tong-chun, MA Shi-guo, XU Ri-qing. Research on delayed effect of landslides caused by air pressure under heavy rainfall[J]. 2013, 34(5).
DOI：

HAN Tong-chun, MA Shi-guo, XU Ri-qing. Research on delayed effect of landslides caused by air pressure under heavy rainfall[J]. 2013, 34(5). DOI：

摘要

在强降雨入渗条件下，浅层边坡土体中的气体可能被封闭，孔隙气压力在封闭条件下随着雨水的入渗不断增加。结合湿润峰面受力分析对封闭气体压力的物理意义进行了说明，通过考虑简化的气阻入渗模型，对比经典的Green-Ampt入渗模型，研究了气压对入渗率和下移的湿润峰的影响。应用该入渗模型，对下部为基岩的大面积浅层边坡雨水入渗过程以及边坡稳定性进行分析。研究表明，封闭气压显著降低了边坡体内雨水的入渗率，对安全系数的降低具有明显的延时性，这进一步揭示了部分地区雨后滑坡频繁发生的重要原因。因此，考虑封闭气压对大面积边坡降雨安全预报具有重要意义

Abstract

Under the intense rainfall infiltration

the air in the shallow slope is likely to be confined

and the pore air pressure in air-confining condition increases constantly as the infiltration of rainfall. The physical meaning of the air-closing pressure is illustrated through the force analysis of the wetting front. Compared with the classical Green-Ampt infiltration model

the simplified infiltration model considering the air pressure is used to study the effects of air pressure on the infiltration rate and the moving wetting front. Then the infiltration process and stability analysis of a large area of shallow slope with bedrock beneath is studied through the simplified infiltration model. The results show that the air pressure in the air-confining condition reduces the infiltration rate and the safety factor remarkably

which could also reveal the reason that why some areas had frequent landslides after the rainfall. So considering air pressure for landslide forecasting is greatly significant.

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