Quantitative multi-risk analysis for natural hazards: a framework for multi-risk modelling

Schmidt, Jochen; Matcham, Iain; Reese, Stefan; King, Andrew; Bell, R. G.; Henderson, Roddy; Smart, Graeme; Cousins, Jim; Smith, Warwick D.; Heron, David

doi:10.1007/s11069-011-9721-z

Cited by 147 publications

(95 citation statements)

References 8 publications

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“…In the literature, there are several examples of applications that consider the combined effects of different natural (or man-made) hazards on given sets of elements at risk (Van Westen et al 2002;Lacasse et al 2008;Kappes et al 2010;Schmidt et al 2011). Marzocchi et al (2012) proposes the following equation for two interacting hazards with occurrences of E 1 and E 2 (and where H 1 is the probability of occurrence of E 1 ):…”

Section: Landslide Multi-hazard Assessmentmentioning

confidence: 99%

Recommendations for the quantitative analysis of landslide risk

Corominas

Westen

Frattini

et al. 2013

Bull Eng Geol Environ

698

666

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This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.

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Section: Landslide Multi-hazard Assessmentmentioning

confidence: 99%

Recommendations for the quantitative analysis of landslide risk

Corominas

Westen

Frattini

et al. 2013

Bull Eng Geol Environ

698

666

View full text Add to dashboard Cite

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“…The first two points are generally solved in dedicated multi-risk projects at the national (e.g., HAZUS-MH, http://www.fema.gov/hazus), international (e.g., CAPRA, http://www.ecapra.org/) or private sector levels (e.g., Grossi and Kunreuther 2005;Schmidt et al 2011). The third point remains to be solved.…”

mentioning

confidence: 99%

The quantification of low-probability–high-consequences events: part I. A generic multi-risk approach

2014

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Dynamic risk processes, which involve interactions at the hazard and risk levels, have yet to be clearly understood and properly integrated into probabilistic risk assessment. While much attention has been given to this aspect lately, most studies remain limited to a small number of site-specific multi-risk scenarios. We present a generic probabilistic framework based on the sequential Monte Carlo Method to implement coinciding events and triggered chains of events (using a variant of a Markov chain), as well as time-variant vulnerability and exposure. We consider generic perils based on analogies with real ones, natural and man-made. Each simulated time series corresponds to one risk scenario, and the analysis of multiple time series allows for the probabilistic assessment of losses and for the recognition of more or less probable risk paths, including extremes or low-probability-high-consequences chains of events. We find that extreme events can be captured by adding more knowledge on potential interaction processes using in a brick-by-brick approach. We introduce the concept of risk migration matrix to evaluate how multi-risk participates to the emergence of extremes, and we show that risk migration (i.e., clustering of losses) and risk amplification (i.e., loss amplification at higher losses) are the two main causes for their occurrence.

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“…one hazard may occur repeatedly in time; different hazards may occur independently in the same place; different hazards may occur dependently in the same place) (Kappes et al, 2012;Marzocchi et al, 2012). Figure 1 lists a basic framework of MHRA (Bell and Glade, 2004;Di Mauro et al, 2006;Marzocchi et al, 2009;Carpignano et al, 2009;Schmidt et al, 2011). There are five main components: (1) hazard identification: identify which natural hazards influence a given area; (2) hazard interaction analysis: calculate the probability and magnitude of multiple hazards occurring together; (3) exposure analysis: identify the elements exposed to these hazards; (4) vulnerability analysis: calculate the possible loss for the exposure, under con- ditions caused by multiples hazards of varying magnitude; and (5) multi-hazard risk curve/map: draw a curve/map based on the probability of multiple hazards and the corresponding loss.…”

Section: Application In Multi-hazard Risk Assessmentmentioning

confidence: 99%

Hazard interaction analysis for multi-hazard risk assessment: a systematic classification based on hazard-forming environment

Liu

Siu

Mitchell

2016

Nat. Hazards Earth Syst. Sci.

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Abstract. This paper develops a systematic hazard interaction classification based on the geophysical environment that natural hazards arise from -the hazard-forming environment. According to their contribution to natural hazards, geophysical environmental factors in the hazard-forming environment were categorized into two types. The first are relatively stable factors which construct the precondition for the occurrence of natural hazards, whilst the second are trigger factors, which determine the frequency and magnitude of hazards. Different combinations of geophysical environmental factors induce different hazards. Based on these geophysical environmental factors for some major hazards, the stable factors are used to identify which kinds of natural hazards influence a given area, and trigger factors are used to classify the relationships between these hazards into four types: independent, mutex, parallel and series relationships. This classification helps to ensure all possible hazard interactions among different hazards are considered in multi-hazard risk assessment. This can effectively fill the gap in current multihazard risk assessment methods which to date only consider domino effects. In addition, based on this classification, the probability and magnitude of multiple interacting natural hazards occurring together can be calculated. Hence, the developed hazard interaction classification provides a useful tool to facilitate improved multi-hazard risk assessment.

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Quantitative multi-risk analysis for natural hazards: a framework for multi-risk modelling

Cited by 147 publications

References 8 publications

Recommendations for the quantitative analysis of landslide risk

Recommendations for the quantitative analysis of landslide risk

The quantification of low-probability–high-consequences events: part I. A generic multi-risk approach

Hazard interaction analysis for multi-hazard risk assessment: a systematic classification based on hazard-forming environment

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