|Year : 2015 | Volume
| Issue : 2 | Page : 79-88
Multi hazards risk assessment, a new methodology
Leila Eshrati, Amir Mahmoudzadeh, Masoud Taghvaei
Department of Geography and Regional Research, Research Institute of Shakhespajouh, University of Esfahan, Esfahan, Iran
|Date of Web Publication||12-Feb-2015|
Department of Geography and Regional Research, Research Institute of Shakhespajouh, University of Esfahan, Esfahan
Source of Support: None, Conflict of Interest: None
Background: Multi-hazards pose a serious threat to human life. It can cause considerable damages. The evaluation of the expected losses due to multi-hazards requires a risk assessment. Multi-hazards risk assessment allow the identification of the most endangered areas and suggest where further detailed studies have to be carried out. Aim: This study aims to give a new methodology for Multi-hazard risk assessment that makes easier the comparability analysis of vulnerability for different hazards and accounts for possible triggering (domino) effects. Materials and Methods: Methods used in this paper are based on theoretical approach and documentation. Two types of hazards will be assessed, namely earthquake and fire following earthquake. Statistical Analysis: Semi-quantitative and quantitative approach would assess risk rates at both regional and local levels. Result: In this study, representation of a new methodology for multi-hazards risk assessment includes determination of a model with parameters, consideration of the indicator-based pattern of vulnerability assessment that selected of all the relevant indicators and presented new classification of indicators based on comparison to different hazards and possible triggering (domino) effects. This means a potential multi-hazard indicator could be higher than the simple aggregation of single risk indicators calculation. Conclusion: The focus is on establishing a general overview of the emerging issues, and indicating how hazard relations can be considered in multi-hazard studies. The hazard relation is identified and studied by means of a new method and the overlay of hazard areas to determine overlaps in final multi-hazards map.
Keywords: Domino effects, indicator-based vulnerability, multi-hazard, risk assessment, new methodology
|How to cite this article:|
Eshrati L, Mahmoudzadeh A, Taghvaei M. Multi hazards risk assessment, a new methodology. Int J Health Syst Disaster Manage 2015;3:79-88
|How to cite this URL:|
Eshrati L, Mahmoudzadeh A, Taghvaei M. Multi hazards risk assessment, a new methodology. Int J Health Syst Disaster Manage [serial online] 2015 [cited 2019 Mar 26];3:79-88. Available from: http://www.ijhsdm.org/text.asp?2015/3/2/79/151315
| Introduction|| |
In recent decades, rapid urban growth and economic development in hazardous area have greatly increased the potential of natural and technological hazards to cause direct and indirect damages; although built environment are threatened by a significant number of hazards, in this study, the focus is earthquake and fire. The possible impacts of hazards are large, the evaluation of the expected damages and losses requires a risk assessment at different space and time. Risk assessments are important components of risk management and it can provide the basis for reduction of the overall risk. However, to manage the overall risk, all hazards threatening the area of concern have to be studied. A multi-hazard approach account different probability of occurrence and intensity from hazard to hazard, assessing the hazards, which are frequently damaging and losing in built environment. Such so-called Multi Hazards Risk assessment has different explanation, between compound and multi-hazards.  While compound hazard are characterised as 'several elements acting together above their respective damage threshold', multi-hazards are characterised as 'elements of quite different kinds coinciding accidentally, or more often, following one another with damaging force'. 
The Hyogo framework of action 2005-2015 of the UN-ISDR indicates risk assessment and education for the development of action in the coming years.The Hyogo Framework for activities in accordance with the Johannesburg Plan, the following was adopted: "Adjustment for multiple hazards approach to disaster risk reduction,Direction of policy, planning and programming related to sustainable development, relief, rehabilitation, and recovery activities in post-disaster and post-conflict".
A risk assessment undertaking will quantify and locate the multi-hazards risk in the state and will facilitate an integration of the calculated risk information in the making of hazard risk reduction and development plans of the state. Consequently, the term multi-hazards risk can be interpreted as the consideration of multiple (if possible all relevant) hazards posing risk to a certain area under observation.
Furthermore, a global assessment of the risks associated with potential hazards would benefit from development of international risk assessment methodologies.
In the following, to present a review on how multi-hazards risk are assessed, models are (usually fire follows a significant earthquake) addressed in various studies.
Fires following earthquakes (the San Francisco 1906 and Tokyo 1923) caused more damages than the earthquake itself. A mathematical model that predicts the place where fire outbreaks may occur after an earthquake, and simulated dynamic fire spreading by using data from past fires following earthquakes in USA, Japan and China.  A numerical model in which a random event and distribution were used to construct the spatial-temporal probability distribution of fire following an earthquake by a GIS-based schema.  Modelling post earthquake fire ignitions using generalized linear (mixed) models up to the late twentieth century of California.  A finite element model that a framework for studying the effects of post-earthquake fire on wooden structures by using ANSYS3D modelling software (ANSYS). 
Effective multi-hazards assessment models are still in their infancy period. Multi-hazards risks are being addressed by national and international institutions.
Multi hazards risk assessment tools currently have different development. A number of multi hazards risk assessment tools exist (Central America Probabilistic Risk Assessment - CAPRA, Riskscape in New Zealand, HAZUS-MH in the US),  MATRIX programme presented probabilistic multi-risk assessment. 
The tool Hazard United States (HAZUS) developed by the Federal Agency of Management utilizes a quantitative approach and is entirely based on vulnerability curves for earthquakes.  And HAZUS provides an estimate of fire following earthquake with induced damage models. The objective of application HAZUS method is to point out the future needs for multi hazards risk assessment, which can serve as a tool for effective risk assessment and disaster management.
The temporal, spatial or causal relationships frequently occur between hazards. However, these models very rarely account comparison to different hazards and hazard relations. A certain amount of harmonization has been carried out, allowing for some comparability among hazards. From a vulnerability research point of view, vulnerability indicators exist, such as the World Risk Index, which account different types of vulnerability, but they do not take into account relationships occur between hazards.
To meet the objective of this paper, we focus on the three main steps of a multi-hazards risk assessment:
- Present the overall analysis scheme for multi-hazard risk as a new methodology. The parameters of multi-hazards risk analyses model is explored
- The assessment of multi-hazards. In this study, risks are expressed in hazard-independent manner, such as number of fatalities or physical damages that qn be directly compared. Thus, after having presented the multi-hazards risk assessment model, the next step towards a full assessment of multi-hazard risks is the examination of vulnerability for single and multi-hazards. The principal approaches to assess vulnerability, to the multitude of processes involved as the need for comparability of the single-hazard results, an equivalent indicator-based vulnerability assessment towards multi-hazards, multi-hazards classification scheme. Quantitative method is used to calculate the direct physical damage and loss of human life directly
- Finally, presents the final multi-hazards risk analysis output.
| Materials and Methods|| |
This study discussed theoretical approaches of multi-hazards risk assessment at both regional and local levels. The model utilizes a quantitative and semi-quantitative approach. These are discussed below in brief. Semi-quantitative methods: An overall analysis scheme is needed to compare final risk classes. So, all single-hazard classes must be equivalent, then compare with vulnerability classes. This is also applied for an index-based semi-quantitative method.  Risk is not the result of classification step. Combination of hazards and vulnerabilities would be for qualitative analyses, with a computation process. Index-based multi-hazard risk analysis schemes are provided by previous researchers.  Previous computed hazard and vulnerability indexes are equally weighted and summed to integrated risk.
Quantitative methods: Quantitative multi-hazards risk analyses provide information on potential damages/or losses. , In this regards, a large multitude metrics and formula based on differing parameters are used (refer them). Annual risk of life loss as well as economic in buildings and infrastructure calculated.  Quantitative method is used to calculate the direct physical damage and loss of human life directly.
The built environment is a 'bottom-up' approach that relates damages to the performance of specific building types. The earthquake casualty estimation processes in local scale base on damage scenarios method, that is entirely based on vulnerability curves for earthquakes and provides an estimate of fire following earthquake that rely on fire behaviour, potential assessment with simulation model. ,
Studied subjects are described by various authors and institutions. Hazard is defined as the 'probability of occurrence within a specified period of time or a given area of a potentially damaging phenomenon'.  However, risk includes, apart of the hazard aspect, degree of loss due to a particular natural phenomenon, as well as product of vulnerability of hazards.  Risk is defined as 'the expected losses of lives, persons injured, property damaged and economic activity disrupted due to a particular hazard for a given area and reference period'.  Hazard analysis referred to hazard evaluation and assessment.
However, reduction of risk cannot only be based on better knowledge about natural hazards, technical assessment as well as optimization of risks as quantified entities. It has a social and psychological dimensions, that are shaped by values, beliefs, political systems and cultural factors.  Examination and quantification of multiple hazards would be difficult, since they exhibit a wide range of characteristics, which are analyzed by different models. 
The risk analysis of this scenario cannot be restricted to a single process. This would lead to a misestimating in overall risk and risk patterns. So, all relevant perils must be considered in a multi-hazard approach. 
Thereby, all studies falling through multi-hazards definition that must be involved more than one hazard. Multi-hazards assessment is basically established different types of risks taking into account possible domino effects. Hazard relationships conclude both mutual influence as well as spatial or temporal coincidence. Hazard relationships and hazard interrelations are synonymous. 
| Results|| |
A new method to assessment of risk for multi-hazards
The multi-hazards risk assessment method makes easier comparison of different hazards and triggering effects. Vulnerability assessment is proposed on the basis of indicators. Regional modelling schemes form a top-down multi-hazard risk analysis approach. A regional overview is undertaken an initial step of top-down model, which is designed threatened zones, hazard overlaps and potential risk zones. This comprises hazards analysis that is including examination of possible hazard relationships. Moreover, relationships within hazards effect at hazard level and manifestation is important. This refers to triggering of one hazard by another. Not only vulnerabities are directly derived from secondary hazard damage but also are derived from triggering hazard damage output. Although, 'Event Tree Method' takes into account this overall concept, which is considered and incorporate into an analysis procedure. Indicator-based vulnerability made assessment approach more local scale. In this model, the vulnerability assessment is an event tree model that uses the relationship between the physical damages and the social, economic, environment losses and the indirect losses which is calculated by combining the following relationships.
Finally multi-hazard risk analysis is calculated for vulnerabilities towards a single or multi-hazards risk [Figure 1].
It not only refers into choice of methods that is producing compatible outputs with respect to indicators but also this makes suitable results. Clear visualization of multi-dimensional outputs will present many aspects of interest. The multi-h risk assessment model is defined as the probability of harmful consequences, or expected direct loss (physical, social, economic or environment damaged) or/and indirect loss resulting from interactions between triggering and secondary hazards.
| Discussion|| |
Development of multi-hazard risk analysis model:
The multi-hazard risk analysis model comprises parameters. Model parameters determination will be explored in the following:
The relationships within natural hazards would be an important issue in multi-hazard studies. ,,, Hazards relationship refers to many different types of influence of hazards to each other. Hazards relationships pose a difficult issue in multi-hazard as well as vulnerability analyses. Not only it refers to triggering of one hazard by another/or other types of influences but also the impact of risk elements is simulated. Following phenomena are described in this study:
- Triggering of a hazard by another ,
- Simultaneous impact of several hazards due to same triggering event 
- Disposition alteration of a hazard after another hazard occurrence 
- Multiple effects of a hazard phenomenon, ,,,, such as firing after earthquake. Multiple effects of earthquake could be facility firing, etc., Identification of both different hazards overlapping as well as individual chains of a hazard that is triggering the next one distinguished as main approaches in this regard.  In this study, the focus is on establishing a general overview of the emerging issues, and indicating how hazard relations can be considered in multi-hazard studies. Conceptual model used to characterization of modified hazard manifestations as well as hazard levels.  The triggering model supports both classification and description of hazard relationships that is facilitated their consideration in hazard analysis procedures. 
Hazard relationships alter to actual hazard levels and lead to very particular phenomena as domino effects or exert influence on the vulnerability. Domino effects refer to the triggering of a hazard by another, such as the triggering of fires by earthquake. This is simulate to a failure in a system of interconnected parts, where the services depend on the operation of a preceding part, and the failure of a preceding part can trigger the failure of successive parts.  These failures cause effects that are posed risks. They are not captured by a separated single-hazard analyses. Understanding domino effects was clearly identified as an important issue.
The conceptual approach is elaborated detail domino effects in regional scale. First, hazards and their influencing factors considered for any of hazards. The influencing factors refer to input data used for the modelling such as building type, damage state, collapse, etc.
Possible relationships of hazards as well as influencing factors have to be identified. It is called interaction event tree. The hazards are juxtaposed in opposition in branches and possible effects are entered.  Though they use this method for the determination of triggering effects, this can be applied to detect potential modification as well as determination of triggering effects. This implies for any combination of two hazards such as earthquake and fire. There are two questions. What does domino hazards occur? How fire may alter the earthquake and whether fire can trigger earthquake?
The consideration of triggering effects at a regional level does not go beyond to the identification of potentially prone zones to specific hazard combinations.
Identification of potentially prone zones could be identified previous domino hazards that are the principal task of regional analyses.  Overlay of potential interacting hazards prone to these effects. The principal task of regional analyses is identified by potential locations that taken place this phenomenon. ,,,,,,,, Overlapping of the modelling results can be distinguished potential sequential occurrence of events, in detail with their respect to probabilities by the event trees. ,,,
Elaboration of event trees is proposed to integrate triggering effects to a model possible series of events have to be examined to analysis the potential consequences of a triggering event effects in more detail. For this, target event trees is a useful method, although their elaboration is extremely demanding.  For the modelling multi-hazards, first, a triggering event is defined. Then, possible subsequent incidences are identified and arranged in a tree-structure. Finally, probabilities are assigned to the single branches. It is mostly based on serious assumptions and subjective appraisals. This is a very challenging step. However, this method is, due to the immense multitude possibilities and the lack of information lead to assess their probabilities. It is not applicable to examine all potential situations and incidences. Potential occurrence of combination events used to examination of specific scenarios at a local scale.
Multi-hazard relationships indicate a strong dependence on the regional scale as well as specific set of hazards. Moreover, the consideration of hazard relationships is an important issue for multi-hazards analyses. The neglect of this aspect may otherwise lead to occurrence of unexpected and completely unforeseen effects due to a misjudgment of the actual hazard situation. 
In this study, risks are expressed in hazard-independent manner, such as number of fatalities, persons affected or physical damages and can therefore be directly compared. Thus, after having presented the multi-hazards casualty model, the next step towards a full analysis of multi-hazard risks is the examination of vulnerability.
Multi-hazards vulnerability assessment
Vulnerability is a multi-dimensional term that means different definitions in social and natural sciences.  In this study, physical vulnerability defines as the potential for physical impact on the physical or built environment and population. Physical vulnerability is analyzed per group of constructions (i.e., structural types) having similar damage performance; social vulnerability as experienced by casualty.
The casualty estimination is originated after some other models such as Coburn and Spence, Murkami and Shiono model et al.  However, it is not as same as 'event tree format'. The Murkami model is an event tree model that includes only fatalities caused by collapsed buildings and does not account for lesser injuries. Shiono's model is similar to the Murkami model and only estimated fatalities. Stojanovski and Dong have proposed a methodology that takes into account a wider range of causal relationships in the casualty modelling.  Following section is discussed general procedure for multi-hazards vulnerability assessment. Creation a set of scenarios to correlate triggering event is one of peculiar aspects of this procedure. Triggering event would be correlated in a parallel sequence series of happenings through an event tree that is caused risk scenarios. Each branch of the event tree will be quantified by both events probabilistic analysis as well as vulnerability values of the specified target.
The events tree is a useful tool that could be used in this step in order to mimic possible chain of events. It allows a straightforward evaluation of the probability of a given chain of events, hence being the premise of a quantitative evaluation of risk [Figure 2]. The logic of its construction is forward (inductive). There is a question at each node of the tree (node branching) such as: What happens if the preceding event leading to the node occurs? The answers of this question are represented by the branches of the tree. The number of branches of any node is as same as number of answers defined for node branching question. Each branch of the tree is assigned as a probability of occurrence.
The events are shown by rectangular diagrams; a short event description given in each diagram. The symbol '<' means that branching out of nodes is identified to other nodes branching.
Not only domino-overlapping of hazards would not influence threat of natural hazards pose but also would have an important impact on vulnerability of them.
Domino effects of multiple hazards would have cumulative impacts, which called hazard sequence.  Shortly after an event (for example an earthquake), the second one (a triggered fire) would be occur. A human condition or process results from physical, social, economic and environmental factors, which determine the likelihood and scale of damage from the impact of multi-hazards. Vulnerability changes continuously over time. Vulnerability map showing the relationship of the hazards. Consideration of the consequences overlapping hazards on multi-hazard vulnerabilities sets in early stage of development. The studies would cover consequences of sequential impacts.
The indicator-based pattern of vulnerability assessment
Vulnerability indicators are checked on the base of multi-hazards risk assessment method. Vulnerability functions should be estimated for both single and domino effects of triggering events. For example, in the seismic case, they should be computed for a single event. However, they should consider the effects of ground acceleration of structures under an ignite condition for combined seismic and fire hazards.
Principal approaches would be to assess vulnerability in multitude processes, to comparing with single-hazard.
A complete vulnerability analysis must be starting a careful identification of elements at risk. These generally include man-made structures, infrastructures, buildings and human. In this paper, the vulnerability is investigated without taking into consideration the social, legal or cultural setting and in directed damages. The focus is on the physical damages and casualty, particularly, on the impact of multi-hazards on the built environment.
The vulnerability indicators, defining the physical, economic, social and environmental vulnerability can be aggregated and combined into an overall vulnerability value. The parameters of HAZUS methodology are such as type of construction, age, size, height and type of residence for physical vulnerability. In this study, by analyzing the vulnerability, we identify the consideration of important vulnerability indicators and the selection of all the relevant indicators. Subsequently, overall scheme for thresholds specification and classification indicators is based on different origins and characteristic of hazard and hazards relation. The indicator-based pattern of vulnerability assessment on basis of indicator weights for earthquake (single hazard), fire following earthquake (multi hazards) is presented [Figure 3].
|Figure 3: Structural model of relative vulnerability index calculation on basis of indicator weights and scores for earthquake|
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On the base of the methodology, these indicators include those characteristics that are primarily influencing vulnerability of a structure/population and induced physical damage/casualty in respect to single and multi-hazards. Physical damage are depending on different indicators such as model building type that based on building land use (residential, commercial, industrial, communication), building condition(ruin,bad,medium and good), archaism(pre code.low code,moderate code and high code), height of the buildings(the number of floor: 8+, 4-7 ,1-3) and separation building(short distance, moderate distance and long distance) that is integrated distance between buildings [Figure 3].
Many indicators affect the severity of the fires following an earthquake, including: Number ignition per million square feet, wind character, physical character, direct physical damage[Figure 4]. Evaluation of population vulnerability requires knowledge of indicators such as the population density per square kilometre, scenario time for three times of day, night time, day time and commute time scenario [Figure 5].
|Figure 4: Structural model of relative vulnerability index calculation on basis of indicator weights and scores for fire following earthquake|
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|Figure 5: Structural model of relative vulnerability index calculation on basis of indicator weights and scores for socal losse/casualty|
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Not only these descriptions indicate variation of potential indicators but also could be distinguished weight indicators of each single hazard. Different properties contribute specific hazard vulnerabilities. The quantifying of indicators differs for hazards and risk level.
The scores of each indicator have to be defined that indicate degree of a certain characteristic. Relative Vulnerability Index (RVI) is calculated vulnerability of a structure, on the base of score and weight.
Calculation hazard intensity would be the most fundamental and important step of identification of prior indicators. The scores are assigned on the basis of hazard type, while the weights depend on user and hazard characteristics. The RVI is calculated by following formula: 
Scores and weights is basis of relative vulnerability index calculation of that is assigned on the basis of expert appraisal.
Additional parameters are presented below, due to determination in spatial scale of development stage during a multi-hazard risk analysis scheme.
Determination of spatial scale would be a fundamental step in development of a multi-hazard risk analysis scheme. The scale primarily depends on type of study as well as used data. Different scales within hazards and hazard models would be subject of a analysis scale and output.
The top-down approach  refers to a multi-step method that is starting with rough and large scale analyses on the basis of interest zones. Detailed and sophisticated investigations are performed for these local zones. A top-down approach was adopted for current study. At the beginning, this shall refer to regional (1:10,000 and 1:50,000) and local (>1:10,000) scales. The regional scale would be used for faults, soil and geological information. However, the local scale would be exploited for physical and population information in urban areas.  Regional analysis would be designed potential risk zones and possible domino hazard to enable detailed local studies. Elaboration of multi-scale multi-hazard analysis scheme is initiated in of regional as well as local scales development.
Regional analysis identifies hotspots nor the full-hazard and risk modelling. However, vulnerability analyses shall be carry out the latest.  So, low data is accompanied high quality application in multi-hazard assessment.
Spatial scale refers to size of study area. Temporal resolution of planning and performance of emergency activities ranges several days, weeks, years, decades or even centuries for land use planning. 
Risk indicator corresponds to type of it that could be examined by physical, economic, social and environmental factors as well as direct or indirect ones. Qualitative metrics as well as qualitative and semi-quantitative approaches are also in use. ,,
Curves/functions, matrices/coefficients and index/indicator-based methods are the principal approaches to assess vulnerability.  Although all three approaches are already used in multi-hazard vulnerability analyses, they are not equally applied for whole hazards. Vulnerability curves referred to damage and risk, whereby fragility curve is based a large amount of data at damaged buildings that is collected after hazard events. The event intensity is depending on causing damages at a certain type of building. The curves are adjusted to observed intensity as well as damage combinations. This is a common approach for extensive hazards such as storms, floods and earthquakes. For very local hazards such as fire, this method would not be a sufficient method.  HAZUS software offers analysis of hurricane, earthquake and flood based on vulnerability curves. 
Indicator approaches fill this gap, since they consider a range of properties and combine them to describe or quantify the vulnerability.
However, they are mostly used in a rather qualitative than quantitative way, in contrast to curves and matrices.
Comparability analysis of vulnerability for multi hazards. One approach has to be chosen for all processes that compares vulnerability analysis of multi-hazards. Moreover, equivalent criteria have to be used, which indicator approaches applied to ensure the comparability within vulnerabilities of multi-hazards. So, a coherent vulnerability analysis scheme requires assuring comparability of the final single-risks. Developed approach is based on indicators of vulnerability, as a step towards local-scale analysis where vulnerability assessments and analysis of exposure risk in region is not necessary. 
An indicator-based method is introduced, according to limited curves and matrices. Contrasting hazard characteristics refer to time of onset, duration, extent, intensity, return period and influence parameters on environment and humans. These are reflected in modelling approaches. Furthermore, separate analyses such as disparate procedures and time-space resolutions will most probably apply. Comparing risk with different origins is difficult. Emphasis on constant improvement of single hazard approaches is primarily. However, multi-hazard approaches must consider outlined above challenges. Comparison of hazards is one of the major objectives of multi-hazard analysis that is difficult to achieve since hazards differ widely by their nature, intensity, return periods and the effects.  Indicators are not directly comparable. An additional step to accomplish comparability is necessary. Single hazards can be classified into hazard categories, by intensity and frequency thresholds. ,,,,,,,,,,,,,,,,,,,,, A common approach is important to assure the comparability of the single risks, in a multi-hazard context with generating comparable single-hazard assessments.  Equivalent thresholds can be established for multi-hazards assessment. Without an overall scheme for thresholds specification and hazards classification are most probably equivalent and therefore comparable.
Indicator is a semi-quantitative approach  that produces cardinal results. Not only cardinal result could not be rank hazard levels but also they quantify difference within them and carry out simple mathematical operations. Indicator computation as well as classification approaches are classified single-hazard magnitudes, frequencies and proportion of the potentially affected area by a hazard event. Indicator methodology offer comparison within single-hazards and their combination to overall hazard. Usual options for classification approaches are adoption the highest class of all overlapping hazards/or an intermediate rating within coinciding hazards.  In the case of indices, single and multi-hazards values can be summed according to importance of each hazard.
Comparing indicators impact of different hazard characteristics would be entail development of specific indicators in analysis methods for each hazard. Technologies used to assess the risks of different origin disasters of multiple technological and natural hazards.
- Techniques for assessment of earthquake hazard: Earthquake occurrence and ground motion models 
- Techniques for assessment of fire hazard: Extent of past fire, occurrence models by operational and statistical methods.
No common terminology has been applied for description of the methods. The differences seem particularly pronounced. An overview of hazard methodologies based on a synthetic analysis of current approaches that is indicating the differences within analysis approaches as well [Table 1].  Type of hazard models depends on specific hazard as well as scale.
|Table 1: The applied methods for analyzing different hazards in various scales|
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Hazards are analyzed by either rather similar or rather distinct method, respective to scale. 
A closer examination reveals the differences of analysis methods. Consequently, different approaches have to be used to consider respective characteristics. Overcoming the problem of single-hazard comparability has been a multi-hazard indicator-based vulnerability, due to differing influence parameters and indicator. Identification of vulnerability indicators would be the first step of hazard-specific vulnerability assessment.
The final multi-hazards risk analysis output
Multiple types of map or visualization concept has been described by a clear exploration of the analysis results. They depend on precise and aspect of case study and who they do it.
The final step relates to magnitude of outcome information. ,
Simultaneous visualization or several types of map allows to identifying relationships within different parameters. However, it is important to avoid an overload maps by too much information, as too much information lead to confuse and reduce readability. It is not possible to transmit all information in one single map. Thus, several maps are necessary to depict information of multi-hazard risk analysis. Susceptibilities, full hazards, vulnerabilities and exposures of risks are presented in single hazard maps. However, distribution of spatial probabilities, hazard intensities, risk quantities are investigated by multi-hazard maps. These maps are identified areas of hazard overlaps. The most critical areas are actual overlap areas. Merging single-hazard components could be lead to overall susceptibility to full hazard or risk results.
| Conclusion|| |
In this study, a multi-hazard risk analysis model on the basis of a top-down approach has been presented. This model includes two levels, (a) a regional analysis to identifying prone zones of multiple hazards and potential risk areas that is followed by (b) a local detail investigation. The elaboration of an indicator-based pattern of vulnerability assessment has been presented, as step towards a more local analysis level. The main idea was to create an indicator-based pattern for physical vulnerability and casualties assessment following a new model that also enables assessing risk for multi-hazards. Methodology for domino probabilistic risk assessment could consider final risk as second hazards triggered that amplified by first hazards.
The final multi-hazards risk analysis output has been described by a clear exploration of the analysis results. Developed analytical approaches would be useful to understanding critical points of risks. Domino effects would emphasis critical points to identifying and developed priorities to better modelling of risk assessment. Although this analysis leads to an estimation of the endangered areas and the number of exposed elements, it offers the determination of comparison different hazards, and areas of hazard overlaps as critical points at risk. Reducing the risks at these critical points would result in a substantial reduction in overall risk at regional and local scales.
Presented method supports identification of those situations, while further analyses and measures have to be based on engineering experience and technical knowledge.
| Acknowledgments|| |
The authors are grateful to the Research Institute of Shakhes Pajouh that supported this study as well. Many thanks also to Cees van Westen, Stefan Greiving and Melanie Simone Kappes for very helpful discussions and valuable advices.
1 New Multi-Hazard and Multi-Risk Assessment Methods for Europe.
2 UNU-EHS, 2011.
| References|| |
Hewitt K, Burton I. Hazardousness of a place: A regional ecology of damaging events. Toronto: Toronto Press; 1971. Access 1973 Jan 12.
Rin A, Xie X. The simulation of post-earthquake fire prone area based on GIS. J Fire Sci 2004;22:421-39.
Zhao S, Xiong L, Ren A. A spatial-temporal stochastic simulation of fire outbreaks following earthquake based on GIS. J Fire Sci 2006;24:313-39.
Davidson RA. Modeling post earthquake fire ignitions using generalized linear (mixed) models. J Infrastruct Syst 2009;15:351-60.
Yue Li M, ASCE Aakash Ahuja, Jamie E, Padgett M. ASCE3, 2012 American Society of Civil Engineers. J Performance Constructed Facilities © Asce/January/February; 2012.
FEMA (2007). Multi-hazard Loss Estimation Methodology: Earthquake, Hurricane and Flood Model. HAZUS-MH MR3. Technical Manual, Department of Homeland Security, Federal Emergency Management Agency. Access 09 January; 2009.
BBK (2010). Method Fur Die Risk Analyse in Bevolkerungsschutz. Tech. rep., Bundesamt fur Bevolkerungsschutz und Katastrophenhilfe. Available from: URLhttp:// target="_blank" href="www">www
.bbk.bund.de/cln_027/nn_402322/SharedDocs/Publikationen/Broschueren__Flyer/MethodeRisikoa7alyse- BS, templateId = raw, property = publicationFile.pdf/Methode_Risikoanalyse-BS.pdf [Last accessed 2011 June 25].
Greiving S. Integrated risk assessment of multi-hazards: A new methodology. In: Schmidt-Thome P, editor. Natural and Technological Hazards and Risks Affecting the Spatial Development of European Regions. Vol. 42. Geological Survey of Finland; 2006. p. 75-81.
Schmidt J, Matcham I, Reese S, King A, Bell R, Smart G, et al
. Quantitative multi-risk analysis for natural hazards: A framework for multi-risk modeling. Natural Hazards Online First; 2011.
vanWesten C, Montoya A, Boerboom L, Badilla Coto E. Multi hazards risk assessment using GIS in urban areas: A case study for the city of Turrialba, Costa Rica. In: Proceedings of the Regional Workshop on Best Practices in Disaster Mitigation: Lessons Learned from the Asian Urban Disaster Mitigation program and other; 2002.
Grunthal G, Thieken A, Schwarz J, Radtke K, Smolka A, Merz B. Comparative risk assessment for the city of cologne-storms, floods, earthquakes. Natural Hazards 2006;38:21-44.
Delmonaco G, Margottini C, Spizzichino D. ARMONIA Methodology for multi-risk assessment and the harmonisation of different natural risk maps. Deliverable 3.1.1, ARMONIA; 2006.
Huttenlau M, Stotter J. The structural vulnerability in the framework of natural hazard risk analysis and the exemplary application for storm loss modeling in Tyrol (Austria). Natural Hazards 2011;58:705-29.
Varnes DJ. Landslide hazard zonation: A review of principles and practice. United Nations Educational, Scientific and Cultural Organisation, Paris, France; 1984
WMO (1999). Comprehensive risk assessment for natural hazards. Technical document 955, World Meteorological Organisation. URL. Available from: http:// target="_blank" href="www">www
.planat.ch/ressources/planat_product_en_198.pdf [Last accessed 2010 May 05].
Assmuth T, Hilden M, Benighaus C. Integrated risk assessment and risk governance as socio-political phenomena: A synthetic view of the challenges. Sci Total Environ 2010;408:3943-53.
Kappes M, Malet JP, Rematre A, Horton P, Jaboyedoff M, Bell R. Assessment of debris follow susceptibility at medium-scale in the Barcelonnette; 2011.
Kappes M, Keiler M, Glade T. From single- to multi-hazard risk analyses: A concept addressing emerging challenges. In: Malet JP, Glade T; 2010.
Kappes M, Keiler KM, von Elverfeldt GT. Challenges of dealing with multi-hazard risk: A review. Natural Hazards; 2012.
Marzocchi W, Mastellone M, Di Ruocco A. (2009). Principles of multi-risk assessment: Interactionsamongst natural and man-induced risks. Tech. rep, European Commission. Available from: http:// target="_blank" href="www">www
.scribd.com/doc/16902233/Principles-of-Multi Risk-Assessment. [Last accessed 2009 July 19].
Carrasco R, Pedraza J, Martin-Duque J, Mattera M, Sanz M. Bodoque J. Hazard zoning for landslides connected to torrential floods in the Jerte Valley (Spain) by using GIS techniques. Natural Hazards 2003;30:361-81.
Luino F. Sequence of instability processes triggered by heavy rainfall in the northern Italy. Geomorphology 2005;66:13-39.
Cannon S, de Graff J. The increasing wildfire and post-fire debris-follow threat in Western USA, and implications for consequences of climate change. In: Sassa K, Canuti P, editors. Landslides-Disaster Risk Reduction. Germany: Springer Verlag; 2009. p. 177-90.
Zuccaro G, Cacace F, Spence R, Baxter P. Impact of explosive eruption scenarios at Vesuvius. J Volcanol Geothermal Res 2008;178:416-53.
Delmonaco G, Margottini C, Spizzichino D. Report on new methodology for multi-risk assessment and the harmonisation of different natural risk maps. Deliverable 3.1, ARMONIA; 2006.
Fuchs S, Dorner W, Sprachinger K, Rochman J, Serrhini K. Flood risk map perceptionthrough graphical semiology. In: Samuels P, Huntington S, Allsop W, Harrop J, editors. Flood Risk Management. Research and Practice. London: Taylor and Francis; 2009. p. 705-14.
Kunz M, Hurni L. How to enhance cartographic visualisations of natural hazards assessment Mortality Prediction in Building Collapse," Proceedings of the 10 WCEE Coburn AW, Spence RJ, 1992, "Factors Determining Human Casualty Levels in Earthquakes: Madrid, Spain: 5989-5994. results. Cartographic J 2011:48:60-71.
Stojanovski P, Dong W. Simulation Model for Earthquake Casualty Estimation," Proc. Fifth US. National Conference on Earthquake Engineering, Paper No. 00592, Chicago, Illinois; 1994. p. 10-4.
Castellanos Abella EA. Multi-scale landslide risk assessment in Cuba. Ph.D. thesis, International Institute for Geo-information Science and Earth Observation, Enschede, Netherlands; 2008.
Foerster E, Krien Y, Dandoulaki M, Priest S, Tapsell S, Delmonaco G, et al
. Methodologies to assess vulnerability of structural systems. Del. 1.1.1., ENSURE; 2009.
Borter P, Bart R. Risk analysis for gravitational natural hazards case studies and data. Environment Materials 107 / II, four Federal Office Environment, Forests and Landscape (BUWAL), Bern, Switzerland; 1999.
Papathoma-Kohle M, Kappes M, Keiler M, Glade T. Physical vulnerability assessment for Alpine hazards-state of the art and future needs. Natural Hazards 2011;58:645-80.
Chiesa C, Laben C, Cicone R. An Asia Pacific natural hazards and vulnerabilities atlas. In 30 th
International Symposium on Remote Sensing of Environment; 2003.
Bartel P, Muller J. Horn of Africa natural hazard probability and risk analysis. Tech. rep., USAID; 2007.
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