The Disruption Index (DI) as a tool to measure disaster mitigation strategies (original) (raw)
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Disruption index, DI: an approach for assessing seismic risk in urban systems (theoretical aspects)
Bulletin of Earthquake Engineering, 2014
Urban systems are characterized by very complex interactions. After an earthquake, a wide variety of services, networks and urban facilities may be unavailable to the public during the system failure and recovery processes, thereby causing disruptions in the basic social needs of the affected area. After a disaster, communities face several challenges. For example, the lack of education may impose population migrations, or malfunctions in the electricity distribution system can produce electrical power outages of varying duration with respect to time and space, which generates consequences in the water distribution system, transportation, communications, etc. A methodology called the Disruption index (DI), based on graph theory, includes these multiple interdependencies. It has been developed to estimate the dysfunction of some fundamental dimensions of urban systems on a broad level, starting with the physical damages directly suffered by the exposed assets, proceeding to the impacts that each node has on the functional performance of the nodes depending on them, until reaching the top node. This paper presents the fundamental theory to support the DI concept. The DI provides the likely impacts and consequences of an earthquake in an urban area to fulfill hazard mitigation and provide civil protection agencies and local and state governments with a new decision-making instrument to reduce or prevent severe and recurrent impacts. The DI concept can also be extended to other natural and man-made disasters and may be used as a tool for optimizing the resources of the system components. Keywords Seismic risk • Interdependencies • Propagation • Disruption • Urban systems 1 Introduction A few short minutes may be all it takes to destroy not only lives but also schools, homes and livelihoods.
Bulletin of Earthquake Engineering, 2011
The earthquake that struck Faial, Pico and São Jorge in 1998 has allowed the collection of an unprecedented quantity of good-quality data on damage to construction, costs of repair and other variables. A general overview of the impact of the earthquake is presented, and its effects on the population, housing, monumental structures and economy 10 years after its occurrence are analysed and briefly reported in this paper. We present the overall results obtained from multiple sources of information, primarily from an integrated database containing all the data gathered. The results that describe the inflicted damage, costs of repair and other variables are presented both statistically and geographically. This information was valuable for the construction of an overall earthquake impact based on the systemic analysis of the urban area through the identification of criteria and definition of descriptors leading to a disruption index. The paper is developed as follows. First, we introduce the descriptions of the earthquake effects on the broader set of existing urban systems. In the second part we present the main methodological aspects leading to the disruption index, as well as analysing and discussing the data to provide a clearer picture of how the analysed systems and their disruption affect an urban area.
In order to analyze and evaluate any post-disaster phases it is necessary to address the pre-existent vulnerability conditions. The methodology consists of four steps: the first step comprises of a review of vulnerability and recovery indicators; the second step is to identify indicators based on spatial variables; the third step is to find the common variables among the subsets of spatial variables from vulnerability and recovery indicators; and the fourth step more pragmatic, is an investigation of the availability of data. The initial results are the set of vulnerability and recovery indicators. Reducing the set of indicators to the indicators represented in a spatial context and the indicators with common features of vulnerability and recovery indices bears the risk to ignore some important single indicators; nevertheless, the added value of the on-going research is to show the advantages of using indicators based on spatial variables.
Disaster Risk Index: A Review of Local Scale Concept and Methodologies
IOP Conference Series: Earth and Environmental Science, 2020
Disaster Risk Index (DRI) is a tool for risk identification, risk management and risk exposure which measured at a different level of scales such as global, regional, trans-boundary or local. This paper reviews DRI and its developments at a local scale of nine countries. There are differences in the risk index components used. Some countries from the previous study such as China, Indonesia, Philippines, USA, and Brazil applied World Risk Index (WRI) concept while others use a combination of other risk components to define risk. The paper also reviews the methodologies used in terms of indicators’ weight and the purpose of DRI development. The vulnerability component, which divided into six dimensions for assessment (social, environmental, economic, institutional, physical and economic) mostly focused on the social and physical dimensions. There is a limitation for the WRI concept at the local level in terms of data availability. The indicator used does not represent the local attrib...
Engineering Geology for Society and Territory - Volume 5, 2014
The Disruption Index is used here for the assessment of urban disruption in the Mt. Etna area after a natural disaster. The first element of the procedure is the definition of the seismic input, which is based on information about the historical seismicity and seismogenic faults. The second element is the computation of the seismic impact on the building stock and infrastructure in the region considered. Information on urban-scale vulnerability was collected and a geographic information system was used to organize the data relating to buildings and network systems (e. g., typologies, schools, strategic structures, lifelines). The central idea underlying the definition of the Disruption Index is the identification and evaluation of the impacts on a target community, considering the physical elements that contribute most to the severe disruption. The results of this study are therefore very useful for earthquake preparedness planning and for the development of strategies to minimize the risks from earthquakes. This study is a product of the European "Urban Disaster Prevention Strategies using Macroseismic Fields and Fault Sources" project (UPStrat-MAFA European project 2013).
Dimensions of Earthquake Disaster in Urban Areas
In disaster management, earthquakes are one of the leading causes of death. The aftermath of such phenomena can be abated if proper actions take place before the onset of the earthquake. Various sectors in a country are responsible for managing earthquakes but lack of knowledge about the positive effects of their actions makes them reluctant to do so. Stabilizing houses and structures, positioning humanitarian goods, retrofitting transportation links, and devising a disaster response plan can help save more lives. Of course, these actions are separate projects with defined budgets which are assigned to different sectors, but coordination of them is necessary. To highlight the effects of pre-disaster actions on recovery costs, Recovery Indexes are introduced which show the state of the city after the earthquake. Also a model is proposed to calculate the recovery costs of an earthquake when different actions have taken place. The results show how significant any pre-disaster action can be on the recovery cost and the essentiality of taking actions before it is too late.
Alternative Analytical tools to Evaluate Natural Disasters Impact and Risk Reduction
The first chapter shows the introduction of this monograph. This monograph is divided into twelve chapters to facilitate to our reader’s different topics about natural disasters final impact and the risk reduction respectively. The second chapter attempts to compare the magnitudes of destruction between natural disasters and socio-economic-political disasters anywhere and anytime. In the methodological part, this research suggests to mixing of quantitative and qualitative methods simultaneously to evaluate the different type of disasters as a whole. Subsequently, the same paper proposes a new analytical tool is entitled “The General Disasters Final Impact Simulator (GDFI-Simulator).” The third chapter in order to grasp the ordinary people's risk perception of liquefaction at their dwelling areas and understand its distinguishing features, we conducted a web based questionnaire survey on citizens in four high liquefaction risk areas in Japan. Based on the obtained data, we compared people's risk perception of liquefaction with those of other ten kinds of hazards. We found out some quantitative results as follows; although they lived in high liquefaction risk area, the respondents who anticipated liquefaction damage would occur in their municipalities were only approx. 33%. This percentage was much lower than the cases of earthquake, flood and rainfall inundation. As priority to take countermeasures against the hazards, their valuations focus on earthquake, whereas the priority of liquefaction rating was relatively low, or nearly half level of earthquake. The fourth chapter explains how natural hazards have a potentially large impact on economic growth but measuring their economic impact is subject to a great deal of uncertainty. The central objective of our paper is to set forth a model – the natural disasters vulnerability evaluation (NDVE) model – to evaluate the impact of natural hazards on GNP growth. In addition, we apply the NDVE Model to the Northeast Japan earthquake and tsunami of March 2011 to evaluate its impact on the Japanese economy. The fifth chapter shows how a lot of liquefaction and damage occurred in various parts of East Japan by the 2011 off the Pacific coast of Tohoku Earthquake on March 11, 2011. Although liquefaction rarely causes human loss immediately, it creates some incidents such as inclination of housing lot, obstacles of infrastructures and air environment deterioration by sand boil might bring serious and harmful influences to inhabitants' living in the disaster-stricken area in the long term. Therefore, this kind of disaster involves difficult problems on the reconstruction of the area aiming sustainability. Hinode district, Itako city, Ibaraki prefecture was one of the places where the most tremendous liquefactions and damage occurred by the earthquake. The district is a relatively new housing area which was developed in 1970's. And the population of the district accounted for approx. 20% of the city before the earthquake. Then, by May two months after the earthquake, 287 persons (113 households) that were 4.5% of previous population had already moved out from the district. In order to clarify factors of inhabitants' moving out from liquefaction disaster area and continuous habitation there, we conducted questionnaire survey on all householders who had lived in the district just before the earthquake, in cooperation with Itako city authorities. We sent questionnaire to 2,562 householders by postal mail on Nov. 10 2011, and received 939 answers from them by postal mail by Dec. 12. Based on the collected data, at first we grasped their housing conditions, residential environment in the district before the earthquake, damage of their houses by the disaster, the present habitations and so on. Then, by using cross-tabulations and multivariate analyses, we analyzed correlations between some factors and implementations of moving out from the district after the earthquake / intentions of continuous habitation there in the future. The results suggest some important points on recovery and reconstruction of Hinode district. For the short term, immediate restorations of infrastructures must be necessary. Then, community development to encourage inhabitants' sense of belonging to the community and some measures to promote settlement there for younger generation are required for the long term. For the reconstruction of the disaster-stricken district aiming sustainability, both improvements of structures and social measures (especially for young generation) are required. The sixth chapter is following the Minimum Food Security Quota (MFS-Quota) proposed by Ruiz Estrada (2010) to evaluate and determine the food sustainability of any given country in the event of any natural disaster, this paper sets out to apply the MFS-Quota to test Malaysia’s food storage and supply readiness for any potential disaster that may critically affect the socio-economic and political wellbeing of the country. The primary objective of the MFS-Quota is to calculate the approximate amount of annual food storage that any country needs in order to subsist through any potential natural disaster or socio-economic and political instability. Moreover, any country is able to build its own MFS-Quota according to their agriculture production system(s) and national food policy focus. The seventh chapter shows in order to grasp the ordinary people's intentions to take prior countermeasure against liquefaction and understand its distinguishing features, we conducted a web-based questionnaire survey on citizens in four high liquefaction risk areas in Japan. Based on the obtained data, we estimated people's degree of priority of taking countermeasures against liquefaction by comparing with other ten kinds of hazards, and we analyzed correlations of some factors with the priority to take liquefaction countermeasures by using a multivariate analysis method. We found out some quantitative results as follows; as priority to take measures against the hazards, their valuations focused on earthquake, whereas the priority of liquefaction rating was relatively low, or nearly half level of earthquake. The main factors which influenced the intentions to take the measures were subjective possibility of a liquefaction occurring in their own zones, expectation of housing damage in that place by the hazard and anxiety over it. The eighth chapter set forth the macroeconomics evaluation of floods (MEF) model, a new model to assess and evaluate the impact of floods on GNP growth. This model points to a new, more concrete way to measure the economic impact of floods, which until now has been subject to a great deal of uncertainty. To illuminate and demonstrate its promise, we employ the model to evaluate and analyze the impact of People’s Republic of China risk floods on the country’s economy. Finally, the MEF-Model can generate different simulations for future potential floods in People’s Republic of China under different floods magnitudes by region(s) respectively. The ninth chapter intends to establish conceptual foundations on the identification of standards and metrics for assessing the impact of hydrological hazards. The economic evaluation of flood damage cost model (EFDC-Model) attempts to estimate the impact of water occurrence, movement, and distribution on GNP growth. The model investigates the recent floods in the Malaysian states of Kelantan and Terengganu for the period 2014-2015. The tenth chapter contemplates the spatial impact of the recent seismic activity in Kathmandu, Nepal through an economic prism. Study methodology involves the application of the Earthquake Vulnerability Evaluation model (EVE-Model). The spatial modelling approach attempts to estimate the economic aftermath of the seismic hazard in the Nepalese economy, including long term macroeconomic implications. The eleventh chapter evaluates the crucial role of unmanned aerial vehicles –UAV’s- (or Drones) in the case of natural disasters response and humanitarian relief aid. The twelfth chapter is analyzing how a sustainable social protection platform can mitigate the final damage of any natural disaster anywhere and anytime. We propose the joint use of quantitative and qualitative methods to evaluate recovery from disaster damage. In this context, we propose a new analytical tool to evaluate disaster damage, “The Natural Disaster Damage Recovery Index Model (ξ-Model)”. The natural disasters damage recovery index (ξ-Model) is based on a number of elements, and it is applied to study the relationship between social protection and natural disasters recovery. Finally, the ξ-Index was applied on a few European countries such as France, Germany, Italy, Netherlands, and Spain from 1998 to 2018.
Disaster Preparedness Indicators
Cidades, Comunidades e Território, 2021
Cidades. Comunidades e Territórios is licensed under a Creative Commons Atribuição-Uso Não-Comercial-Proibição de realização de Obras Derivadas 4.0 International.