A statistical approach to landslide risk modelling at basin scale: from landslide susceptibility to quantitative risk assessment

Landslides ◽  
2005 ◽  
Vol 2 (4) ◽  
pp. 321-328 ◽  
Author(s):  
J. Remondo ◽  
J. Bonachea ◽  
A. Cendrero
Keyword(s):  
Risk Assessment ◽  
Landslide Susceptibility ◽  
Statistical Approach ◽  
Quantitative Risk Assessment ◽  
Landslide Risk ◽  
Risk Modelling ◽  
Basin Scale

scholarly journals Parameters Derived from and/or Used with Digital Elevation Models (DEMs) for Landslide Susceptibility Mapping and Landslide Risk Assessment: A Review

2019 ◽  
Vol 8 (12) ◽  
pp. 545 ◽  
Author(s):  
Nayyer Saleem ◽  
Md. Enamul Huq ◽  
Nana Yaw Danquah Twumasi ◽  
Akib Javed ◽  
Asif Sajjad
Keyword(s):  
Risk Assessment ◽  
Landslide Susceptibility ◽  
3D Visualization ◽  
Digital Elevation Models ◽  
Susceptibility Mapping ◽  
Landslide Susceptibility Mapping ◽  
Landslide Risk ◽  
Conditioning Factors ◽  
Digital Elevation ◽  
The Impact

Digital elevation models (DEMs) are considered an imperative tool for many 3D visualization applications; however, for applications related to topography, they are exploited mostly as a basic source of information. In the study of landslide susceptibility mapping, parameters or landslide conditioning factors are deduced from the information related to DEMs, especially elevation. In this paper conditioning factors related with topography are analyzed and the impact of resolution and accuracy of DEMs on these factors is discussed. Previously conducted research on landslide susceptibility mapping using these factors or parameters through exploiting different methods or models in the last two decades is reviewed, and modern trends in this field are presented in a tabulated form. Two factors or parameters are proposed for inclusion in landslide inventory list as a conditioning factor and a risk assessment parameter for future studies.

scholarly journals Quantitative Risk Assessment and Application of Landslide Disaster in Chongqing

2021 ◽  
Author(s):  
Ke Li ◽  
Dongsheng Liu ◽  
Yanlei Wang ◽  
Na She
Keyword(s):  
Risk Assessment ◽  
Assessment Method ◽  
Assessment Methods ◽  
Quantitative Risk Assessment ◽  
Landslide Risk ◽  
Practical Applications ◽  
Geological Disasters ◽  
Mathematical Probability ◽  
Risk Assessment Method ◽  
Discrimination Factors

Chongqing is located in southwestern China, and geological disasters occur frequently. The amount of potential landslide disasters is far greater than the number of landslides that can be managed by government funds, so the risk assessment for potential landslide disasters is critical. In practical applications, risk assessment methods based on landslide stability and loss are restricted by various factors. These methods can be simplified to semi-empirical assessment methods, which are influenced by the discrimination factors near the limit values of the determined conditions, possibly leading to sudden changes in the evaluation results and distort the conclusions. To solve this problem, we propose a full quantitative risk assessment method according to the probability of landslide damage. The mathematical probability model is used to quantitatively describe the risk assessment impacting factors, weaken the boundary influence, and improve the accuracy of landslide risk assessment. Correspondingly, the software is developed to conduct quantitative risk assessment on six landslides in Feng jie County, Chongqing, which verifies the accuracy and reliability of the full quantitative risk assessment method, and provides an important reference for judging urban landslide geological disasters.

scholarly journals Quantitative Risk Assessment of Vehicles Hit by Landslides: A Case Study

2020 ◽  
Author(s):  
Meng Lu ◽  
Jie Zhang ◽  
Lulu Zhang ◽  
Limin Zhang
Keyword(s):  
Risk Assessment ◽  
Hong Kong ◽  
Failure Probability ◽  
Impact Analysis ◽  
Suggested Method ◽  
Quantitative Risk Assessment ◽  
Landslide Risk ◽  
The Road ◽  
On The Road

Abstract. Landslides threaten the safety of vehicles on highways. Nevertheless, a rigorous quantitative highway landslide risk assessment seems difficult. Using a case study in Hong Kong, this paper presents a method for quantitative risk assessment for highway landslides. The suggested method consists of three parts, i.e., analysis of annual failure probability of the slope, the spatial impact analysis and the consequence analysis. In the case study, the annual failure probability of the slope is analyzed based on historical failure data in Hong Kong. The spatial impact of the landslides is estimated based on empirical correlations with the geometry of the slope. The consequence is assessed based on probabilistic modeling of the traffic on the highway. Based on the suggested method, the annual failure probability of the slope, the distance from the slope and the road and the density of vehicles on the road can significantly affect the landslide risk and the suggested method can be used to quantify the effects of these factors. The suggested method can be also potentially used to analyze the highway landslide risk in other regions.

scholarly journals GIS-Based Landslide Susceptibility Mapping for Land Use Planning and Risk Assessment

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 162
Author(s):  
Anna Roccati ◽  
Guido Paliaga ◽  
Fabio Luino ◽  
Francesco Faccini ◽  
Laura Turconi
Keyword(s):  
Risk Assessment ◽  
Land Use ◽  
Land Use Planning ◽  
Landslide Susceptibility ◽  
Risk Mitigation ◽  
Current Model ◽  
Susceptibility Mapping ◽  
Mitigation Strategies ◽  
Landslide Susceptibility Mapping ◽  
Landslide Risk

Landslide susceptibility mapping is essential for a suitable land use managing and risk assessment. In this work a GIS-based approach has been proposed to map landslide susceptibility in the Portofino promontory, a Mediterranean area that is periodically hit by intense rain events that induce often shallow landslides. Based on over 110 years landslides inventory and experts’ judgements, a semi-quantitative analytical hierarchy process (AHP) method has been applied to assess the role of nine landslide conditioning factors, which include both natural and anthropogenic elements. A separated subset of landslide data has been used to validate the map. Our findings reveal that areas where possible future landslides may occur are larger than those identified in the actual official map adopted in land use and risk management. The way the new map has been compiled seems more oriented towards the possible future landslide scenario, rather than weighting with higher importance the existing landslides as in the current model. The paper provides a useful decision support tool to implement risk mitigation strategies and to better apply land use planning. Allowing to modify factors in order to local features, the proposed methodology may be adopted in different conditions or geographical context featured by rainfall induced landslide risk.

scholarly journals Assessment of the physical vulnerability of buildings affected by slow-moving landslides

2020 ◽  
Vol 20 (9) ◽  
pp. 2547-2565
Author(s):  
Qin Chen ◽  
Lixia Chen ◽  
Lei Gui ◽  
Kunlong Yin ◽  
Dhruba Pikha Shrestha ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Beam Theory ◽  
Quantitative Risk Assessment ◽  
Landslide Risk ◽  
Physical Vulnerability ◽  
Vulnerability Curve ◽  
Length Width ◽  
Slow Moving ◽  
Physical Responses

Abstract. Physical vulnerability is a challenging and fundamental issue in landslide risk assessment. Previous studies mostly focus on generalized vulnerability assessment from landslides or other types of slope failures, such as debris flow and rockfall, while the long-term damage induced by slow-moving landslides is usually ignored. In this study, a method was proposed to construct physical vulnerability curves for masonry buildings by taking the Manjiapo landslide as an example. The landslide's force acting on the buildings' foundation is calculated by applying the landslide residual-thrust calculation method. Considering four rainfall scenarios, the buildings' physical responses to the thrust are simulated in terms of potential inclination by using Timoshenko's deep-beam theory. By assuming the landslide safety factor to be landslide intensity and inclination ratio to be vulnerability, a physical vulnerability curve is fitted and the relative function is constructed by applying a Weibull distribution function. To investigate the effects of buildings' parameters that influence vulnerabilities, the length, width, height, and foundation depth and Young's modulus of the foundation are analysed. The validation results on the case building show that the physical vulnerability function can give a good result in accordance with the investigation in the field. The results demonstrate that the building length, width, and foundation depth are the three most critical factors that affect the physical vulnerability value. Also, the result shows that the higher the ratio of length to width of the building, the more serious the damage to the building. Similarly, the shallower the foundation depth is, the more serious the damage will be. We hope that the established physical vulnerability curves can serve as tools for the quantitative risk assessment of slow-moving landslides.

A semi-quantitative risk assessment model for the outbreak of grass carp hemorrhage

2013 ◽  
Vol 19 (3) ◽  
pp. 521-527 ◽  
Author(s):  
Song YANG ◽  
Shuqin WU ◽  
Ningqiu LI ◽  
Cunbin SHI ◽  
Guocheng DENG ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Grass Carp ◽  
Assessment Model ◽  
Quantitative Risk Assessment ◽  
Risk Assessment Model

Risk assessment of Campylobacter species in shellfish: identifying the unknown

1997 ◽  
Vol 35 (11-12) ◽  
pp. 29-34 ◽  
Author(s):  
P. Teunis ◽  
A. Havelaar ◽  
J. Vliegenthart ◽  
G. Roessink
Keyword(s):  
Risk Assessment ◽  
Quantitative Risk Assessment ◽  
Contamination Level ◽  
Risk Of Infection ◽  
Worst Case ◽  
Considerable Uncertainty ◽  
Risk Estimates ◽  
Consumption Data ◽  
Campylobacter Infection ◽  
Campylobacter Spp

Shellfish are frequently contaminated by Campylobacter spp, presumably originating from faeces from gulls feeding in the growing or relaying waters. The possible health effects of eating contaminated shellfish were estimated by quantitative risk assessment. A paucity of data was encountered necessitating many assumptions to complete the risk estimate. The level of Campylobacter spp in shellfish meat was calculated on the basis of a five-tube, single dilution MPN and was strongly season-dependent. The contamination level of mussels (<1/g) appeared to be higher than in oysters. The usual steaming process of mussels was found to completely inactivate Campylobacter spp so that risks are restricted to raw/undercooked shellfish. Consumption data were estimated on the basis of the usual size of a portion of raw shellfish and the weight of meat/individual animal. Using these data, season-dependent dose-distributions could be estimated. The dominant species in Dutch shellfish is C. lari but little is known on its infectivity for man. As a worst case assumption, it was assumed that the infectivity was similar to C. jejuni. A published dose-response model for Campylobacter-infection of volunteers is available but with considerable uncertainty in the low dose region. Using Monte Carlo simulation, risk estimates were constructed. The consumption of a single portion of raw shellfish resulted in a risk of infection of 5–20% for mussels (depending on season; 95% CI 0.01–60%). Repeated (e.g. monthly) exposures throughout a year resulted in an infection risk of 60% (95% CI 7–99%). Risks for oysters were slightly lower than for mussels. It can be concluded that, under the assumptions made, the risk of infection with Campylobacter spp by eating of raw shellfish is substantial. Quantitative risk estimates are highly demanding for the availability and quality of experimental data, and many research needs were identified.

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