# Study on the Risk Assessment Method of Rainfall Landslide

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## Abstract

**:**

## 1. Introduction

## 2. Study Area and Data

#### 2.1. Study Area

#### 2.2. Landslide Data

## 3. Regional Security Risk Assessment

#### 3.1. Analysis of Influencing Factors

#### 3.1.1. Topography

#### 3.1.2. Rock–Soil Mass Types

#### 3.1.3. Geological Structure

#### 3.1.4. Rainfall

#### 3.2. Risk Analysis

#### 3.2.1. Determination of Slope Unit

#### 3.2.2. The Method of Hazard Assessment

_{L}= P(N

_{L}) × P(S)

#### 3.2.3. The Method of Vulnerability Assessment

#### 3.2.4. Risk Assessment and Characteristics Analysis

## 4. Individual Landslide Risk Assessment

#### 4.1. Landslide Features

^{4}m

^{2}. The vegetation on the landslide slope is more developed and mainly covered by shrubs and citrus trees. The material composition of the landslide is mainly residual slope sedimentary silty clay, siltstone, and silty mudstone. The slip mass is mainly strongly weathered silty mudstone. The altitude of the rock is 330°∠28°. The joint fissures are extremely developed and open, and the average occurrence is about 162°∠65°. It is speculated that the sliding surface is rock mass level. The seasonal variation of groundwater level and water volume in the landslide area is strong, and the water volume varies greatly with atmospheric precipitation.

#### 4.2. Probability Analysis of Extreme Rainfall

_{0}, α, and β are the location parameter, shape, and scale of Pearson III distribution, respectively, which can be expressed as $\alpha =\frac{4}{{C}_{s}^{2}},\text{}\beta =\frac{2}{E\left(x\right){C}_{V}{C}_{S}}$, ${a}_{0}=E\left(x\right)\left(1-\frac{2{C}_{V}}{{C}_{S}}\right)$; E (x) is the mathematical expectation; C

_{V}and C

_{s}are the off-potential coefficient and skewness coefficient. The density function can be determined after a

_{0}, α, and β are determined.

#### 4.3. Risk Assessment of Landslide

## 5. Conclusions

- (1)
- According to a large amount of statistical data analysis, the main influencing factors of landslide disasters in Mayang County are topography, geological lithology, geological structure, and rainfall. Controlled by formation lithology in space, most of them are developed in the distribution area of red clastic rocks; controlled by rainfall distribution in time, they mainly occur from April to July and have a positive correlation with rainfall.
- (2)
- In this paper, taking slope units as the basic evaluation unit, the risk calculation formula proposed by Varnes was used to evaluate the risk of slopes and the vulnerability of the disaster-bearing bodies. Comprehensively considering the population and economic risks, the geological disaster risk assessment of regions in Mayang County was completed. From the perspective of spatial distribution, there were 45 slope units in high-risk areas, which were scattered throughout the key areas and more distributed in Shiyangshao Township–Yanmen Town–Changtan Village Yanmen Town; there were 195 medium-risk slope units, which were mainly distributed in Shiyangshao Township–Yanmen Town; there were 119 low-risk slope units.
- (3)
- In this paper, taking the Shiyantan Landslide in Hunan Province as an example, the landslide disaster risk assessment was carried out. Landslides are generally stable in natural and half-saturated conditions, but slopes are highly likely to cause damages in case of extreme rainfall (e.g., five consecutive five days of rainfall in 50 years). In this case, the Shiyantan Landslide has low economic risk and high life risk, so it is necessary to formulate relevant measures to alleviate the risk.

## Author Contributions

## Funding

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 7.**The distribution of landslide occurrence and rainfall over the study period 2005 to 2017, (

**a**) for yearly distribution and (

**b**) for monthly distribution.

**Figure 15.**Photos of the Shiyantan landslide ((

**a**) damaged house at the leading edge of the landslide (

**b**) tensile crack).

Degree | Reappearing Period of 10 Years | Reappearing Period of 20 Years | ||
---|---|---|---|---|

The Number of Units | Percentage | The Number of Units | Percentage | |

High-risk region | 46 | 12.8% | 74 | 20.6% |

Medium-risk region | 146 | 40.7% | 198 | 55.2% |

Low-risk region | 167 | 46.5% | 87 | 24.2% |

Vs | Affected Area | Slip Body |
---|---|---|

Soil-wood | 0.9 | 1.0 |

Brick-wood | 0.7 | 1.0 |

Brick-concrete | 0.5 | 1.0 |

Railway | 0.7 | 1.0 |

Motorway | 0.6 | 1.0 |

Highway | 0.3 | 1.0 |

Transmission line | 0.7 | 1.0 |

Village road | 0.3 | 1.0 |

Farmland | 0.3 | 1.0 |

Orchard | 0.3 | 1.0 |

Wasteland | 0.7 | 1.0 |

Minerals | 0.6 | 1.0 |

Vulnerability | Soil-Wood | Brick-Wood | Brick-Concrete |
---|---|---|---|

0.1 | 0.00 | 0.00 | 0.00 |

0.3 | 0.01 | 0.01 | 0.01 |

0.5 | 0.02 | 0.02 | 0.02 |

0.8 | 0.08 | 0.13 | 0.13 |

1 | 0.24 | 0.45 | 0.45 |

Different Rainfall Durations/d | E(x)/mm | C_{v} | C_{s} |
---|---|---|---|

1 | 99.069 | 0.28622 | 1.15347 |

3 | 133.115 | 0.31363 | 1.35802 |

5 | 146.385 | 0.25625 | 0.63550 |

7 | 169.762 | 0.23527 | 1.32693 |

Return Periods | IDe (1 Day) | IDe (3 Days) | IDe (5 Days) | IDe (7 Days) |
---|---|---|---|---|

10 | 3.34 | 4.61 | 4.79 | 5.45 |

50 | 4.22 | 5.99 | 5.74 | 6.76 |

100 | 4.58 | 6.55 | 6.11 | 7.29 |

Conditions | Stability Coefficient | Failure Probability (%) |
---|---|---|

1 | 1.293 | 7.06% |

2 | 1.048 | 35.42% |

3 | 0.883 | 59.18% |

Structural Typology | S_{str} | S_{mai} | S_{ser} | S_{dir} | I_{f-dep} | I_{fai-s} | V |
---|---|---|---|---|---|---|---|

Brick-concrete | 0.5 | 0.2 | 0.1 | 0.7 | 1.0 | 1.0 | 0.89 |

Half-timbered | 0.7 | 0.35 | 0.7 | 0.7 | 1.0 | 1.0 | 0.98 |

Type | Number | Unit Price (yuan) | Price (10^{4} yuan) | Total (10^{4} yuan) |
---|---|---|---|---|

Farmland | 6000 m^{2} | 30 | 18 | 667.42 |

Half-timbered building | 672 m^{2} | 600 | 40.32 | |

Brick-concrete structural building | 2995 m^{2} | 1800 | 539.1 | |

Village road | 300 m | 1000 | 30 | |

Citrus orchard | 8000 m^{2} | 50 | 40 |

Most Dangerous Condition | Deadweight + Complete Saturation (50 Years) |
---|---|

Annual instability probability (%) | 1.183 |

Total economic value (10^{4} yuan) | 667.42 |

Number of people | 103 |

Societal economic risk(10^{4} yuan) | 4.69 |

Individual economic risk(10^{4} yuan) | 4.55 × 10^{−2} |

Total life risk | 0.13 |

Individual life risk | 1.19 × 10^{−3} |

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**MDPI and ACS Style**

Sui, H.; Su, T.; Hu, R.; Wang, D.; Zheng, Z.
Study on the Risk Assessment Method of Rainfall Landslide. *Water* **2022**, *14*, 3678.
https://doi.org/10.3390/w14223678

**AMA Style**

Sui H, Su T, Hu R, Wang D, Zheng Z.
Study on the Risk Assessment Method of Rainfall Landslide. *Water*. 2022; 14(22):3678.
https://doi.org/10.3390/w14223678

**Chicago/Turabian Style**

Sui, Haoyue, Tianming Su, Ruilin Hu, Dong Wang, and Zhengwei Zheng.
2022. "Study on the Risk Assessment Method of Rainfall Landslide" *Water* 14, no. 22: 3678.
https://doi.org/10.3390/w14223678