Risk Models

Understanding disaster risk modelling

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Computational risk modelling allows us to couple exposure data with vulnerability and hazard models to generate deterministic and probabilistic risk estimates. The modelling of synthetic events is a way of compensating for the limited available historical information, particularly in the case of extreme events related to intensive risk (UNISDR, 2015a).

Models differ in their resolution, computational power and number of variables, are highly technical but only as good as the data used.

Since we do not fully understand nor can we fully replicate reality, a model is a representation of reality and is therefore defined by a series of assumptions. These assumptions are informed by an imperfect historical record of past events, our incomplete knowledge of natural processes and vulnerability, as well as uncertainties in exposure data. Consequently, each of the components within the risk model has its own set of associated uncertainties. As these uncertainties build, the model output may move further away from accuracy. For instance, although a risk model might appear to produce a precise output, e.g. ‘1 in 100 year flood will affect 388,123 people’, in reality the accuracy of the model and input data may provide only an order of magnitude estimate (GFDRR, 2014a). Being aware of the uncertainty and assumptions behind models is therefore critical when applying a model output, however these are not always apparent to the users of model outputs.

Deterministic approaches model a single or small number of scenarios without considering the likelihood of occurrence, whereas probabilistic approaches consider the full range of possible events as well as quantifying the likelihood of occurrence.

The following list of models is not exhaustive, but indicates the range of open (public) and closed (private) models, which are local, national, regional and or global in scope. Global refers to those models that consider several, but not necessarily all countries.

Risk modelling involves combining hazard models with exposure data and vulnerability models (or ‘functions’). The output of the risk model depends on its purpose, but they often estimate potential economic losses, for instance the average annual loss (estimated loss averaged by year considering the full range of loss scenarios relating to different return periods). However, economic losses are not of concern to many DRR decision-makers, who instead want to know for instance how many homes might be damaged in a community given different hazard severities.

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CAPRA (comprehensive Approach to probabilistic Risk assessment)

Provided by: CEPREDENAC, IDB, UNISDR and World Bank

The Comprehensive Approach to Probabilistic Risk Assessment (CAPRA) provides a Geographic Information System (GIS)-based platform of information on natural hazard risk, for disaster risk analysis and communication. CAPRA was developed in partnership with Central American governments with the support of the Central American Coordination Centre for Disaster Prevention (CEPREDENAC), the Inter-American Development Bank (IDB) and the UNISDR and the World Bank. The CAPRA Program is a risk modelling tool and uses a modular, free platform for probabilistic risk assessment of natural hazards. This platform is a Geographic Information System oriented to risk calculations based on hazard, exposure and physical vulnerability data. The CAPRA methodology determines risk in a probabilistic manner, i.e. the intensity and frequency of occurrence of hazards over a period of time is taken into account. Through hazard mapping, risk assessment and cost-benefit analysis tools, the platform tool allows the user to determine conjoint or cascading risk on an inter-related multi-hazard basis (distinguishing the platform from previous single hazard analyses). With the information CAPRA provides, decisions can be made a priori about prevention, mitigation and response to natural hazards. CAPRA-GIS platform was used to calculate risk for the Global Assessment Reports (UNISDR, 2013 and 2015).

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scope Regional, national and local

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CLASIC/2, CATRADER and Touchstone

Provided by: Air worldwide

AIR catastrophe models quantify the risk from natural hazards— earthquakes, tropical cyclones, winter storms, severe thunderstorms, floods, and wildfires—in more than 90 countries across the globe. AIR scientists and engineers combine simulations of the natural occurrence patterns and characteristics of hazards, with information on property values, construction types, and occupancy classes. Model output provides information concerning the potential for large losses before they occur so companies can prepare for their financial impact.

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scope Global

ACCESS Closed

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Earthquake Risk Model (EQRM)

Provided by: Geoscience Australia

The Geoscience Australia has developed the Earthquake Risk Model (EQRM) which can simulate the estimated ground-shaking from earthquakes of a given magnitude and location (seismic hazard), and subsequently calculate the impact to a portfolio of buildings (seismic risk). Losses to the built environment incurred from earthquakes are dependent on the vulnerability of a structure to strong ground-shaking. The EQRM application can be used to estimate the ground motion and its likelihood of occurrence and the direct financial loss and its likelihood of occurrence.

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scope National

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ELEMENTS

Provided by: Impact Forecasting, Aon Benfield

Aon Benfield’s catastrophe management team assesses client catastrophe exposure, models loss estimates and, alongside their actuaries and brokers, designs reinsurance programs to efficiently manage net risks for over 120 countries. Impact Forecasting focus on the development of models for specific hazards and territories where the commercial modelling companies have not yet ventured or existing models are not fully meeting their clients’ requirements.

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scope Global

ACCESS Closed

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Florida Public Hurricane Model (extends to damage and loss)

Provided by: Florida International University

The Florida Public Hurricane Model assesses hurricane risk, and predicted annual expected insured residential losses in Florida for an insurance company, zip code, county, or for the entire state. Separate loss estimates are produced for structure, content, additional structure, and additional living expenses. These losses can be reported for portfolios classified by construction type (e.g. masonry, frame, manufactured homes), by county or zip code, by policy form, by rating territory, and combinations thereof. Furthermore, the model can generate for a given portfolio of policies, the return time, the probability of exceedance, and the probable maximum loss. It can also immediately predict losses from a given event. The model also has some limited capability to estimate the benefit (loss reduction) from certain mitigation efforts.

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Global earthquake model

Provided by: GEM foundation

GEM calculates probabilities of earthquake occurrence and the direct losses resulting from earthquakes. The overall risk is calculated by combining the probability of damage and loss to people and structures due to earthquake shaking, and the vulnerability of society and the economy (taking into account their capacity to cope with earthquake events). This model measures and analyses earthquakes on a global scale by combining information from past earthquakes as well as present information on the way the earth is currently moving. This combination of historical and instrumental catalogues of events, databases of active faults, and models of geodetic strain forms the basis of the model. The global exposure database (GED4GEM) was developed for GEM risk platform OpenQuake and is optimized for earthquake risk assessment. However it can be used for many different types of hazards, natural and man-made. In order to obtain a reliable amount of data for seismic hazard assessment, the data and models are being developed together with local experts.

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scope Global

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Global Risk Assessment model

Provided by: UNISDR-led multi-agency collaboration

The Global Risk Model featured in the Global Assessment Report 2015 is based on a joint effort by leading scientific institutions, governments, UN agencies and development banks, the private sector and non-governmental organisation to share spatial data on global risk from natural hazards. Data on past hazardous events, population, capital stock, economic indicators distribution and risk from natural hazards can be visualized and downloaded. Probabilistic hazard and risk models have been developed for earthquake, tropical cyclone wind and storm surge, tsunami and river flooding worldwide, for volcanic ash in the Asia-Pacific region and for agricultural drought in parts of Africa. The impact of climate change on wind hazard and risk in the Caribbean and on agricultural drought in Africa has also been modelled. The individual models that constitute the Global Risk Assessment (2015) are described in more detail in the hazard, exposure, and vulnerability model tabs.

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scope Global

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Global Volcano Model (GVM)

Provided by: Global Volcano Model Network

The Global Volcano Model project is developing an integrated global database system on volcanic hazards, vulnerability and exposure, with the aim of making this globally accessible and involving the international volcano community and users in a partnership to design, develop, analyse and maintain the database system. The Global Volcano Model is a component of the Global Assessment Report model.

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scope Global

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HAZUS-MH

Provided by: United States Federal Emergency Management Agency

HAZUS-MH uses Geographic Information Systems (GIS) technology to estimate physical, economic and social impacts of disasters. It graphically illustrates the limits of identified high-risk locations due to earthquake, hurricane and floods. Users can then visualize the spatial relationships between populations and other more permanently fixed geographic assets or resources for the specific hazard being modelled, a crucial function in the pre-disaster planning process. HAZUS is used for mitigation and recovery, as well as preparedness and response. Government planners, GIS specialists and emergency managers use HAZUS to determine losses and the most beneficial mitigation approaches to take to minimize them. It can be used in the assessment step in the mitigation planning process, which is the foundation for a community's long-term strategy to reduce disaster losses and break the cycle of disaster damage, reconstruction and repeated damage. HAZUS can support the evaluation of some hazards that are not included as models in the current HAZUS software.

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scope National

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InaSAFE

Provided by: BNPB, AIFDR and GFDRR

InaSAFE is free software that produces realistic natural hazard impact scenarios for better planning, preparedness and response activities. InaSAFE was conceived and initially developed by the Indonesia's National Disaster Management Agency (BNPB) and the Australian Government, through the Australia-Indonesia Facility for Disaster Reduction (AIFDR) and the World Bank - Global Facility for Disaster Reduction and Recovery (World Bank-GFDRR). InaSAFE is a plugin that takes exposure inputs (population, buildings) and hazard inputs (tsunami inundation depth) from any Openstreetmap data or software, then uses simple vulnerability functions to calculate an output. InaSAFE was conceived and initially developed by the Indonesia's National Disaster Management Agency (BNPB) and the Australian Government, through the Australia-Indonesia Facility for Disaster Reduction (AIFDR) and the World Bank - Global Facility for Disaster Reduction and Recovery (World Bank-GFDRR).

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scope Global

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INFORM

Provided by: Inter-Agency Standing Committee (IASC) and the European Commission

INFORM is a global tool for understanding the risk of humanitarian crises and has been applied to 191 countries. The INFORM index balances the hazard and exposure dimension on one side, and the vulnerability and the lack of coping capacity dimensions on the other side. Hazard dependent factors are treated in the hazard and exposure dimension, while hazard independent factors are divided into two dimensions: the vulnerability dimension that considers the strength of the individuals and households relative to a crisis situation, and the lack of coping capacity dimension that considers factors of institutional strength. The INFORM model adopts the three aspects of vulnerability reflected in the UNISDR definition. The aspects of physical exposure and physical vulnerability are integrated in the hazard and exposure dimension, the aspect of fragility of the socio-economic system becomes INFORM’s vulnerability dimension while lack of resilience to cope and recover is treated under the lack of coping capacity dimension. The split of vulnerability into three components is particularly useful for tracking the results of disaster reduction strategies over time.

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scope Global

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Japan Tsunami Model

Provided by: Willis Re

The Japan earthquake risk has been rigorously investigated and modelled but the complexity of modelling tsunami has led to a significant gap in the industry’s ability to quantify risk for severe earthquake events. The Willis Japan Tsunami Model is another vital step towards closing this gap . The model combines tsunami loss information with earthquake shaking damage output. It provides both Willis Re and its clients the means to quantify and manage risk from these extreme events, where historically losses have been little understood.

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scope National

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KatRisk models

Provided by: KatRisk

KatRisk is a catastrophe modelling company focused on flood and wind risk. They develop event based probabilistic models to quantify portfolio aggregate losses and exceedience probability curves. Their aim is to develop models that fully correlate all sources of flood loss including explicit consideration of tropical cyclone rainfall and storm surge. To initiate this development, they have built track sets and wind models for Atlantic Basin hurricanes and Northwest Pacific Typhoons. Free demonstration versions of these models are available online.

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scope Global

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RiskLink

Provided by: Risk Management Solutions (RMS)

RMS models risk in nearly 100 countries, allowing insurers, reinsurers, and other stakeholders to analyse the probability of loss from catastrophic events. Their models are built using detailed data reflecting localized variations in hazard, and databases capturing property and human exposures.

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scope Global

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Riskscape (NZ)

Provided by: NIWA and GNS

RiskScape software is developed through scientific collaboration between National Institute of Water and Atmospheric Research Ltd (NIWA) and GNS Science, organisations affiliated with New Zealand's Natural Hazards Research Platform. RiskScape provides a modular framework to estimate impacts and losses for assets exposed to natural hazards. The software combines hazard, asset and vulnerability modules through a data selection process to quantify a range of economic and social consequences. This approach helps practitioners make informed decisions on natural hazard management activities. RiskScape tools enable users to build their own hazard and asset modules, then import these for impact and loss modelling. User developed modules can be used independently or in combination with RiskScape provided modules. A planned vulnerability module builder will enable users to be completely self-sufficient in module development. Although designed for New Zealand, RiskScape is easily adapted for use anywhere in the world.

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scope National

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RQE®

Provided by: CoreLogic EQECAT

EQECAT's catastrophe risk models incorporate scientific research, deep engineering knowledge, claims and exposure data, combined with advanced mathematics and statistics to produce catastrophe risk. Innovative and highly integrated applications help clients perform a variety of crucial activities such as understanding risk correlation at the site, as well as policy, account, and portfolio level; pricing and managing risk from the site, policy, account, and portfolio level; communicating risk to important stakeholders, including rating agencies, regulators, shareholders, and counterparties. EQECAT has 180 natural hazard software models for 96 countries, which spans six continents.

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scope Global

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Sobek 1D/2D Model

Provided by: Deltares

Deltares assesses flood risks by carrying out integrated risk analyses looking into both the probability and impact of flooding. They estimate flood probability by confronting water levels and waves with the height and strength of levees. Simulations with our Sobek 1D/2D model show the possible extent and impacts of flooding. Deltares maps the vulnerability of an area in case of flooding and studies the effects of climate change and spatial planning on flood risk. They also assess economic damage, possible casualties and environmental impacts of floods.

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scope Global

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Tropical Cyclone Risk Model (TCRM)

Provided by: Geoscience Australia

Geoscience Australia's Tropical Cyclone Risk Model (TCRM) is a statistical and parametric model of tropical cyclone behaviour, designed to simulate the impact of one or many tropical cyclone events. It can be used to simulate many thousands of years of activity to determine the annual exceedance probability of cyclonic winds, or alternatively to examine the impact of a single event on a community. TCRM has been designed to allow hazard researchers to examine the range of sensitivity to the many parameterised tropical cyclone models in use around the world. It is an open-source software application, envisaged to serve as a standard for comparison to other tropical cyclone hazard models.

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scope Global to local

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Verisk Maplecroft Natural Hazards Risk Atlas 2015

Provided by: Verisk Maplecroft

Verisk Maplecroft’s Natural Hazards Risk Atlas 2015 calculates the risks of natural hazards within 198 countries and assesses resilience during and after the occurrence of a natural hazard. The Atlas includes sub-national mapping of each index allowing the identification of natural hazards risks down to local levels, enabling risk managers to pinpoint risks to individual assets such as factories, refineries or pipelines. It provides a country scorecards providing a summary of the major natural hazards exposure of each country and enable the easy comparison of risks. In addition, Verisk Maplecroft has also analysed the potential for economic disruption from natural hazards, by compiling a sub-national map of economic exposure to the 12 natural hazards featured in the Atlas. Index views compare this risk across all 198 countries to consider the absolute economic values exposed to natural hazards and also how this exposure compares to a country's total economic output. Verisk Maplecroft has also designed a Socio-economic Resilience Index which assesses the factors that combine to increase the chance that occurrences of natural hazards will become major natural disasters.

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scope Global to local

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World Risk Index

Provided by: UNU-EHS and the Alliance Development Works/Bündnis Entwicklung Hilft (BEH)

The WorldRiskIndex calculates the risk of becoming the victim of a disaster resulting from an extreme natural event for 171 countries. It is a tool used to assess and estimate the disaster risk of a country and aims to demonstrate that not only the magnitude or intensity of a natural event influences disaster risk, but a multitude of different factors, such as the political and institutional structures, the state of infrastructure or the nutrition situation, economic and environmental conditions of a country determine whether a natural hazard will turn into a disaster. It consists of four components: exposure, susceptibility, coping capacities and adaptive capacities. The Index is calculated from 28 indicators using data that is available worldwide and accessible to the public.

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scope Global

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Hazard models estimate the probability of occurrence of a specific hazard, in a specific future time period, as well as its intensity and area of impact. Natural hazard models replicate the physics of natural processes, including their propagation through the atmosphere (e.g. windstorm), the Earth's sub-surface (e.g. earthquake) and surface (e.g. flood), or a combination of all three. Hazard is estimated in terms of the occurrence, frequency and severity of the event(s).

Source: adapted from Michel-Kerjan et al. (2012)

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ANUGA

Provided by: Geoscience Australia and the Australian National University

The ANUGA hydrodynamic Inundation Model calculates the maximum water depth for the study area which is then provided as a map for use by emergency managers. An important capability of the software is that it can model the process of wetting and drying as water enters and leaves an area. This means that it is suitable for simulating water flow onto a beach or dry land and around structures such as buildings. ANUGA is currently being applied in a number of projects where impacts from tsunami events on coastal communities are simulated. Projects include Tsunami Impact modelling for Western Australia (with Fire and Emergency Services Authority) and support to the Australian Tsunami Warning System.

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scope National

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Flowroute-i ™

Provided by: Ambiental

The Ambiental flood model simulates the impact of rainfall, river and tidal water sources in complex environments, including mountainous regions and dense urban areas. It is also able to replicate flood events for cities and countries around the world, generate flood maps and flood risk data sets and assess flood defenses. The model can be used to explain what might happen if flood defenses are breached or sewers overflow, and what would happen if water is pumped out of the area or cannot escape.

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scope National

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NOAA Tsunami Models

Provided by: NOAA Center for Tsunami Research

The primary responsibility of the NOAA Center for Tsunami Research (NCTR) is to provide assistance to the Tsunami Warning Centers (TWC) in the form of Forecast modelling software products specifically designed to support the Tsunami Warning Center’s forecasting operations. In addition to this, the NCTR has traditionally been committed to Inundation modelling to assist coastal communities in their efforts to assess the risk, and mitigate the potential of tsunami hazard. The Method of Splitting Tsunami Model (MOST) developed by Titov of PMEL and Synolakis of University of Southern California aims to develop faster and more reliable forecasts of tsunamis propagating through the ocean and striking coastal communities. MOST is a suite of numerical simulation codes capable of simulating three processes of tsunami evolution: earthquake, transoceanic propagation, and inundation of dry land. The MOST model has been extensively tested against a number of laboratory experiments and was used for simulations of historical tsunamis.

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scope Global

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Oceanweather Tropical Cyclone models

Provided by: Oceanweather Inc.

The CYCLOPS system provides not only highly accurate day-day forecasts but also a unique probabilistic approach to support emergency response required in the face of a cyclone (typhoon, hurricane) threat, such as the evacuation decision. These models provide accurate day-day forecasts and data to support emergency response activities that are required in the face of a cyclone. In this regard, they can be used to take evacuation decisions. In addition, the models can be used to fine grid systems to accurately resolve tropical cyclones and other smaller scale weather systems.

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scope Global

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Tsunami Hazard Model

Provided by: Norwegian Geotechnical Institute (NGI)

The Probabilistic Tsunami Hazard Assessment (PTHA) calculates a set of synthetic earthquakes to obtain a distribution of possible run-up heights rather than one value per location. The analysis was constrained to tsunamis induced by earthquakes, which are expected to provide the largest contribution to tsunami risk. A fully probabilistic methodology has been developed in 2015 (used in the Global Assessment Report 2015), which quantifies the probability of the tsunami run-up height in various areas, combined with an amplification factor to estimate maximum shoreline water elevations. Individual tsunami inundation maps were developed for several thousand possible tsunami events with each event having a probability of occurrence (UNISDR, 2015).

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scope Global

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Tsunami model

Provided by: Geoscience Australia

Probabilistic and scenario tsunami hazard modelling measures the computation of probabilistic offshore waveheights, based on several thousands of scenario calculations. The model can be used to create inundation maps for several return periods of engineering interest and discuss their implications and use for infrastructure applications.

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Earthquake hazard model: GAR2015

Provided by: CIMNE

A fully probabilistic seismic hazard assessment at the global level, developed for the Global Assessment Report (2015) to estimate the order of magnitude of potential losses. The model identified the principal seismic sources based on geological and neotectonical information, to characterize the tectonic regions and seismic provinces. A set of stochastic earthquake scenarios were generated based on the information on past earthquakes included in the historical catalogues of NEIC-USGS (2014) and ISC-GEM. Ground motion prediction equations were assigned to model the probability distributions of ground motion intensity associated with a given earthquake magnitude. Hazard maps showing ground shaking were generated for representative events at a 5x5 km grid resolution.

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scope Global

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Tropical cyclonic wind and storm surge hazard model: GAR2015

Provided by: UNISDR, CIMNE

The tropical cyclonic strong wind and storm surge model use information from 2594 historical tropical cyclones, topography, terrain roughness, and bathymetry. The storm surge hazard models the sea water run-up height at the shore line as a consequence of the tangential stress exerted by strong winds and the lower atmospheric pressure. The historical tropical cyclones used in the cyclone wind and storm surge model are from five different oceanic basins: Northeast Pacific, Northwest Pacific, South Pacific, North Indian, South Indian and North Atlantic and the tracks were obtained from the IBTrACS database.

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scope Global

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Riverine flood hazard model: GAR2015

Provided by: CIMA Foundation and UNEP-GRID

The global flood hazard assessment used in the Global Assessment Report (2015) uses a probabilistic approach for modelling riverine flood major river basins around the globe. The model uses a global database of stream-flow data, merging different sources gathering more than 8000 stations over the globe. It then calculates the range of possible river flow discharges from very low to the maximum possible at series of locations along the river. The hazard maps are developed at 1kmx1km resolution.

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scope Global

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Volcanic ash fall hazard of Asia Pacific: GAR2015

Provided by: Geoscience Australia

Physical impact of ash fall is one of the many of consequences from a volcanic eruption. The model uses a framework for multi-scale Probabilistic Volcanic Ash Hazard Analysis (PVAHA) and the Volcanic Ash Probabilistic Assessment tool for Hazard and Risk (VAPAHR). The model was used in the 2015 Global Assessment Report to provide a broad overview of regional scale volcanic ash hazard in the Asia-Pacific region. This methodology does not consider the wind effect on volcanic ash dispersal.

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Exposure accounts for the people and properties identified, along with numerous specific characteristics such as the occupancy, construction type and age of buildings, as well as their replacement value. If fatalities and injuries are included in the risk model, then different scenarios characterizing the number of people in the buildings at different times of the day should also be included.

Source: adapted from Michel-Kerjan et al. (2012)

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CIMNE model

Provided by: International Center for Numerical Methods in Engineering (CIMNE)

The database structure is built to contain information on buildings and people from the country-level all the way down to the individual building. The global exposure database is developed at 1km spatial resolution at coastal areas and at 5km spatial resolution everywhere else on the globe. It includes economic value, number of residents, and construction type of residential, commercial and industrial buildings, as well as hospitals and schools. The database is based on a top-down approach where statistical information including socio-economic, building type, and capital stock at a national level are transposed onto the grids of 5x5 or 1x1 using geographic distribution of population data and gross domestic product (GDP) as proxies.

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scope Global

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National Exposure Information System (NEXIS)

Provided by: Geoscience Australia

The National Exposure Information System (NEXIS) is designed to provide comprehensive and nationally consistent exposure information to enable users to understand exposure of the Australian built environment to natural disaster. NEXIS currently maintains information about residential, commercial and industrial buildings . NEXIS uses publicly available data about buildings, demographics, economic information, surveys and statistical analysis to derive exposure information. In this model the exposure information can be aggregated to standard geographic areas and modelled for various hazard scenarios or using disaster footprints with severity zones.

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Vulnerability models typically replicate structural vulnerability through the use of vulnerability functions (or ‘curves’) that describe a probable damage severity or economic loss for a particular structural type when it is subjected to a hazard intensity. There exists a shortfall in social vulnerability models, but it can be estimated, to a limited extent, by using demographic and socio-economic data.

Source: adapted from Michel-Kerjan et al. (2012)

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Global Change & Vulnerability model

Provided by: United Nations Environment Programme (UNEP)/Global Integrated Data (GRID)

Within the topic Global Change & Vulnerability, UNEP/GRID-Geneva studies the links between environment degradation, climate change and disaster risk. Scientific studies are based on spatial analysis (GIS, remote sensing, statistical modelling), but also field data collection to generate advocacy tools and raise awareness. Data are made available using on-line interactive mapping and data distribution (SDI). Results are published in UN reports, scientific articles or in publication, conferences and exhibitions for the public at large.

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scope Global

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Human Vulnerability to Natural Disasters

Provided by: Johns Hopkins Bloomberg School of Public Health

The goals of the Human Vulnerability to Natural Disasters Project include assessing population risk to natural disasters and providing information on affected populations to decision makers in the post-disaster relief and rehabilitation context. In addition, the project aims to assess the relationship between socio-demographic and environmental characteristics in relation to vulnerability to different types of natural hazards and to evaluate how models of pre-disaster vulnerability, in particular estimates of populations at risk, can be incorporated into post-disaster assessments in order to derive less biased estimates of disaster impact.

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EDITED 12 NOV 2015 BY: PREVENTIONWEB EDITOR