A comparison of selected global disaster risk assessment results

We compare country risk rankings derived from two recently published global disaster risk analyses. One set of country rankings is based on the Disaster Risk Index (DRI) developed by the United Nations Environment Program (UNEP) Division of Early Warning and Assessment Global Resource Information Database project under a contract to the United Nations Development Program (UNDP). The other is based on an index of disaster mortality risk developed by the Global Natural Disaster Risk Hotspots project implemented by Columbia University, the World Bank and associated partners. We convert data from these sources into two comparable indexes of disaster mortality risk and rank countries according to the resulting values for a set of natural hazards common to both studies. The country rankings are moderately correlated, ranging from .41 to .56 for individual hazards to .31 for multi-hazard mortality risks. We identify the top 25 countries according to the mortality risk values we recomputed from each study’s results to show the degree to which countries are highly ranked in common. The numbers of countries common to both lists for individual hazards range from 7 to 16 out of 25. The correspondence among the top 25 ranked countries is lowest for earthquakes and floods. Only 6 out of 25 countries are common to both lists in the multi-hazard case. We suggest that while the convergence in the results for some hazards is encouraging, more work is needed to improve data and methods, particularly with respect to assessing the role of vulnerability in the creation of risk and the calculation of multi-hazard risks. The views expressed are the authors’ and do not necessarily reflect those of SM2 Consulting Multi-Hazards and Risk Holistic Solutions or the United Nations Development Program.     

Earthquake-and-landslide events are associated with more fatalities than earthquakes alone

Natural hazards are natural processes of the complex Earth system and may interact and affect each other. Often a single hazard can trigger a subsequent, different hazard, such as earthquakes triggering landslides. The effect of such cascading hazards has received relatively little attention in the literature. The majority of previous research has focused on single hazards in isolation, and even multi-hazard risk assessment currently does not account for the interaction between hazards, therefore ignoring potential amplification effects. Global earthquake-and-landslide fatality data were used to model cascading events to explore relationships between the number of fatalities during single and cascading events and covariates. A multivariate statistical approach was used to model the relationship between earthquake fatalities and several covariates. The covariates included earthquake magnitude, gross domestic product, slope, poverty, health, access to cities, exposed population to earthquake shaking, building strength and whether a landslide was triggered or not. Multivariate regression analysis showed the numbers of earthquake fatalities are significantly affected by whether a subsequent landslide is triggered or not.     

Is multi-hazard mapping effective in assessing natural hazards and integrated watershed management?

Natural hazards are often studied in isolation.However,there is a great need to examine hazards holistically to better manage the complex of threats found in any region.Many regions of the world have complex hazard landscapes wherein risk from individual and/or multiple extreme events is omnipresent.Extensive parts of Iran experience a complex array of natural hazards-floods,earthquakes,landslides,forest fires,subsidence,and drought.The effectiveness of risk mitigation is in part a function of whether the complex of hazards can be collectively considered,visualized,and evaluated.This study develops and tests individual and collective multihazard risk maps for floods,landslides,and forest fires to visualize the spatial distribution of risk in Fars Province,southern Iran.To do this,two well-known machine-learning algorithms-SVM and MARS-are used to predict the distribution of these events.Past floods,landslides,and forest fires were surveyed and mapped.The locations of occurrence of these events(individually and collectively) were randomly separated into training(70%) and testing(30%) data sets.The conditioning factors(for floods,landslides,and forest fires) employed to model the risk distributions are aspect,elevation,drainage density,distance from faults,geology,LULC,profile curvature,annual mean rainfall,plan curvature,distance from man-made residential structures,distance from nearest river,distance from nearest road,slope gradient,soil types,mean annual temperature,and TWI.The outputs of the two models were assessed using receiver-operating-characteristic(ROC) curves,true-skill statistics(TSS),and the correlation and deviance values from each models for each hazard.The areas-under-the-curves(AUC) for the MARS model prediction were 76.0%,91.2%,and 90.1% for floods,landslides,and forest fires,respectively.Similarly,the AUCs for the SVM model were 75.5%,89.0%,and 91.5%.The TSS reveals that the MARS model was better able to predict landslide risk,but was less able to predict flood-risk patterns and forest-fire risk.Finally,the combination of flood,forest fire,and landslide risk maps yielded a multi-hazard susceptibility map for the province.The better predictive model indicated that 52.3% of the province was at-risk for at least one of these hazards.This multi-hazard map may yield valuable insight for land-use planning,sustainable development of infrastructure,and also integrated watershed management in Fars Province.     

Challenges of analyzing multi-hazard risk: a review

Many areas of the world are prone to several natural hazards, and effective risk reduction is only possible if all relevant threats are considered and analyzed. However, in contrast to single-hazard analyses, the examination of multiple hazards poses a range of additional challenges due to the differing characteristics of processes. This refers to the assessment of the hazard level, as well as to the vulnerability toward distinct processes, and to the arising risk level. As comparability of the single-hazard results is strongly needed, an equivalent approach has to be chosen that allows to estimate the overall hazard and consequent risk level as well as to rank threats. In addition, the visualization of a range of natural hazards or risks is a challenging task since the high quantity of information has to be depicted in a way that allows for easy and clear interpretation. The aim of this contribution is to give an outline of the challenges each step of a multi-hazard (risk) analysis poses and to present current studies and approaches that face these difficulties.     

A spatial analysis of integrated risk: vulnerability of ecosystem services provisioning to different hazards in the Czech Republic

Ecosystem services are important to maintain the human well-being. However, their provisioning has been under the increasing pressure from both natural and socio-economic changes. This paper aims to assess the most significant hazards, such as water quality, nitrogen deposition, erosion, floods, invasive species, urbanisation and contaminated sites affecting delivery of ecosystem services in the Czech Republic. Using the multi-hazard assessment, the integrated risk index for ecosystem service provisioning was proposed. The spatial analysis based on this approach was then applied to the Czech Republic as a case study. The results showed that about 48% of the area falls into the very low risk category followed by 30%, 21%, and 1% for low, medium and high categories, respectively. Forest and wetland ecosystems were estimated to have the highest proportion of their total area among the highest risk values. Moreover, we found that the national parks appeared to have the highest proportion of medium- and high-risk classes among the natural areas. The approach presented in this study should aggregate the existing knowledge on ecosystem services and hazards and thus monitor the integrated risk. The results are intended to help with various planning and management decisions at both the national and regional levels and to bring more attention on the most problematic hot-spots.     

Hydrological hazards in Russia: origin,classification, changes and risk assessment

Hydrological extreme events pose an imminent risk to society and economics. In this paper, various aspects of hydrological hazards in Russia are analysed at different scales of risk assessment. It is shown that the number of hydrological and meteorological hazards in Russia has been growing every year. The frequency of economic losses associated with extreme low flow in this century has increased by factor five compared to the last decade of the previous century. With regard to floods, an interesting spatial patter can be observed. On the one hand, the number of floods in the Asian part of the country has increased, whereas on the other hand, the number and intensity of floods in estuarine areas in the European part of Russia have significantly reduced since the middle of the twentieth century, especially in the 2000s. This decrease can be attributed to runoff flooding in the mouths of regulated rivers, with an effective system of flood and ice jam protection. The analysis shows that there is an 8–12-year periodicity in the number of flood occurrences and that flood surges have intensified over the last 110 years, especially on the European territory of Russia. An integrated index that accounts for flood hazards and socio-economic vulnerability was calculated for each region of Russia. A classification of flood risk was also developed, taking into account more than 20 hydrological and social–economic characteristics. Based on these characteristics, hazard and vulnerability maps for entire Russia were generated which can be used for water management and the development of future water resources plans.

     

A review of multiple natural hazards and risks in Germany

Although Germany is not among the most hazard-prone regions of the world, it does experience various natural hazards that have caused considerable economic and human losses in the past. Moreover, risk due to natural hazards is expected to increase in several regions of Germany if efficient risk management is not able to accommodate global changes. The most important natural hazards, in terms of past human and economic damage they caused, are storms, floods, extreme temperatures and earthquakes. They all show a pronounced spatial and temporal variability. In the present article, a review of these natural hazards, associated risks and their management in Germany is provided. This review reveals that event and risk analyses, as well as risk management, predominantly focus on one single hazard, generally not considering the cascading and conjoint effects in a full multi-hazard and risks approach. However, risk management would need integrated multi-risk analyses to identify, understand, quantify and compare different natural hazards and their impacts, as well as their interactions.     

Deaggregation of multi-hazard damages,losses, risks,and connectivity: an application to the joint seismic-tsunami hazard at Seaside,Oregon

This paper presents a methodology to deaggregate the results of a multi-hazard damage analysis by extending the traditional multi-hazard damage analysis to consider both population characteristics and independent hazards. The methodology is applied to the joint seismic-tsunami hazard at Seaside, Oregon, considering four infrastructure systems: (1) buildings, (2) transportation network, (3) electric power network and (4) water supply network. Damages to all infrastructure systems are evaluated, and the networked infrastructures are used to inform parcel connectivity to critical facilities. US Census data and a probabilistic housing unit allocation method are implemented to assign detailed household demographic characteristics at the parcel level. Six dimensions of deaggregation are introduced: (1) spatial, (2) hazard type, (3) hazard intensity, (4) infrastructure system, (5) infrastructure component, and (6) housing unit characteristics. The damages, economic losses and risks, and connectivity to critical facilities are deaggregated across these six dimensions. The results show that deaggregated economic loss and risk plots can allow community resilience planners the ability to isolate high-risk events, as well as provide insights into the underlying driving forces. Geospatial representation of the results allows for the identification of both vulnerable buildings and areas within a community and is highlighted by the spatial pattern of parcel disconnection from critical facilities. The incorporation of population characteristics provides an understanding of how hazards disproportionately impact population subgroups and can aide in equitable resilience planning.

     

Economic risk maps of floods and earthquakes for European regions

Europe experiences different natural hazards and subsequent risks that have various effects on the development of its regions. The spatial significance of hazards can be expressed as an economic risk when combining hazard potential with vulnerability data. Two examples of European natural hazard maps on floods and earthquakes, as well as the resulting risk profiles of regions (combination of hazard potential and vulnerability) give a first impression on the spatial characters of hazards in Europe and their potential impact on further spatial development. The economic risk maps enable a view on the spatial dimension of the economic damage potential of flood and earthquakes, pointing out comparable situations across Europe with the aim to facilitate targeted responses and policies. The spatial character of a hazard is either defined by spatial effects that might occur in case of a disaster or by the possibility of spatial planning responses. The integration of the economic vulnerability of a region (regional GDP per capita, population density) leads to a classification of areas according to their economic risk or damage potential towards hazards. These synthetic risk profiles are presented as risk maps of European regions in administrative boundaries. Obtained information can be of interest for spatial planning and development strategies, e.g. economic risk profile of regions can influence the targets of investments and could thus be an important background for structural funding.     

A three-level framework for multi-risk assessment

The effective management of the risks posed by natural and man-made hazards requires all relevant threats and their interactions to be considered. This paper proposes a three-level framework for multi-risk assessment that accounts for possible hazard and risk interactions. The first level is a flow chart that guides the user in deciding whether a multi-hazard and risk approach is required. The second level is a semi-quantitative approach to explore if a more detailed, quantitative assessment is needed. The third level is a detailed quantitative multi-risk analysis based on Bayesian networks. Examples that demonstrate the application of the method are presented.     

Community-based disaster risk and vulnerability models of a coastal municipality in Bangladesh

Bangladesh is one of the most natural hazard-prone countries in the world with the greatest negative consequences being associated with cyclones, devastating floods, riverbank erosion, drought, earthquake, and arsenic contamination, etc. One way or other, these natural hazards engulfed every corner of Bangladesh. The main aim of this research paper is to carry out a multi-hazards risk and vulnerability assessment for the coastal Matlab municipality in Bangladesh and to recommend possible mitigation measures. To this aim, hazards are prioritized by integrating SMUG and FEMA models, and a participation process is implemented so as to involve community both in the risk assessment and in the identification of adaptation strategies. The Matlab municipality is highly vulnerable to several natural hazards such as cyclones, floods, and riverbank erosion. The SMUG is a qualitative assessment, while FEMA is a quantitative assessment of hazards. The FEMA model suggests a threshold of highest 100 points. All hazards that total more than 100 points may receive higher priority in emergency preparedness and mitigation measures. The FEMA model, because it judges each hazard individually in a numerical manner, may provide more satisfying results than the SMUG system. The spatial distributions of hazard, risk, social institutions, land use, and other resources indicate that the flood disaster is the top environmental problem of Matlab municipality. Hazard-specific probable mitigation measures are recommended with the discussion of local community. Finally, this study tries to provide insights into the way field research combining scientific assessments tools such as SMUG and FEMA could feed evidence-based decision-making processes for mitigation in vulnerable communities.     

Up-scaling of impact dependent loss distributions: a hybrid convolution approach for flood risk in Europe

This paper introduces a new method to up-scale dependent loss distributions from natural hazards to higher spatial levels, explicitly incorporating their dependency structure over the aggregation process. The method is applied for flood risk in Europe. Based on this “hybrid convolution” approach, flood loss distributions for nearly all European countries are calculated and presented. Such risk-based estimates of extreme event losses are useful for determining suitable risk management strategies on various spatial levels for different risk bearers. The method is not only applicable for natural disaster risk but can be extended for other cases as well, i.e., where comonotonic risks have to be “summed up” without loss of risk information.     

Multi-hazard susceptibility mapping based on Convolutional Neural Networks

Multi-hazard susceptibility prediction is an important component of disasters risk management plan. An effective multi-hazard risk mitigation strategy includes assessing individual hazards as well as their interactions. However, with the rapid development of artificial intelligence technology, multi-hazard susceptibility prediction techniques based on machine learning has encountered a huge bottleneck. In order to effectively solve this problem, this study proposes a multi-hazard susceptibility mapping framework using the classical deep learning algorithm of Convolutional Neural Networks (CNN). First, we use historical flash flood, debris flow and landslide locations based on Google Earth images, extensive field surveys, topography, hydrology, and environmental data sets to train and validate the proposed CNN method. Next, the proposed CNN method is assessed in comparison to conventional logistic regression and k-nearest neighbor methods using several objective criteria, i.e., coefficient of determination, overall accuracy, mean absolute error and the root mean square error. Experimental results show that the CNN method outperforms the conventional machine learning algorithms in predicting probability of flash floods, debris flows and landslides. Finally, the susceptibility maps of the three hazards based on CNN are combined to create a multi-hazard susceptibility map. It can be observed from the map that 62.43% of the study area are prone to hazards, while 37.57% of the study area are harmless. In hazard-prone areas, 16.14%, 4.94% and 30.66% of the study area are susceptible to flash floods, debris flows and landslides, respectively. In terms of concurrent hazards, 0.28%, 7.11% and 3.13% of the study area are susceptible to the joint occurrence of flash floods and debris flow, debris flow and landslides, and flash floods and landslides, respectively, whereas, 0.18% of the study area is subject to all the three hazards. The results of this study can benefit engineers, disaster managers and local government officials involved in sustainable land management and disaster risk mitigation.     

Methodology of natural risk assessment in Russia

The Russian Federation territory is prone to various natural hazards. The paper analyzes the most hazardous natural processes that may cause human deaths, injuries and health damage, as well as considerable economic loss. The history of studies in the assessment of different natural risk indices in the interests of particular end-users is described, and the conceptual instruments used in the assessment of natural risk indices are considered. The principle GIS-based methodical approaches to the assessment and mapping of natural risk are provided. The examples of estimation and mapping of natural risk are cited and their application by different end-users (i.e., state and municipal authorities, Ministry of Construction of Russia, Ministry of the Russian Federation for Civil Defence, Emergencies and Elimination of Consequences of Natural Disasters (Emercom of Russia)).     

Probabilistic winter storm risk assessment for residential buildings in Germany

Losses resulting from winter storms contribute a significant part to the overall losses among all natural hazards in most mid-latitude European countries. A realistic assessment of storm risk is therefore essential for prevention and coping measures. The paper presents a framework for probabilistic storm risk assessment for residential buildings which is exemplarily performed for Germany. Two different approaches are described, and results are presented. The hazard-based approach brings together hazard, vulnerability and building assets to calculate risk curves for each community. The storm-based approach uses loss information from past storm events to calculate statistical return periods of severe storms. As a result, a return period of 83 years to the most severe storm series in 1990 is calculated. Average annual losses of €170 million to residential buildings are calculated for all over Germany. The study demonstrates how the approaches complement each other and how validation is performed.     

Debris flood risk assessment for Mosquito Creek, British Columbia, Canada

Mosquito Creek drains a 15.5 km² watershed on the North Shore Mountains north of Vancouver, British Columbia, Canada, and flows through the densely urbanized District and then City of North Vancouver. Previous studies determined that the creek is subject to debris floods (hyperconcentrated flows). The National Research Council of Canada is applying multi-hazard risk assessment procedures for various regions in B.C. and chose Mosquito Creek as one of its target areas. As part of its natural hazard management plan, the District of North Vancouver (DNV) requested an assessment of debris flood hazards and associated risk to life. Using a combination of empirical methods, dendrochronology and some judgment, BGC Engineering Inc. assessed debris flood hazard extent, velocity and depth for estimated 100-, 200-, 500- and 2,500-year debris flow return periods. Based on the results from the hazard assessment, risk for individuals and groups living within the hazard area, including residential homes and a fire hall, was estimated. Compared to risk tolerance criteria accepted on an interim basis by the DNV, we estimate that societal risk exceeds tolerable standards and that individual risk exceeds tolerable standards for 10 homes. The results from the risk to loss of life study have prompted DNV to implement a series of risk reduction measures including installation of a debris containment net and watershed restoration measures.     

Large-scale assessment of avalanche and debris flow hazards in the Sakhalin region,Russian Federation

We explore the challenges of avalanche and debris flow hazard assessment for urban areas exposed in the Sakhalin region. Avalanches are a threat to more than 60 settlements in the region and debris flows to more than 30. Data are provided for avalanche and debris flow events that occurred in the Sakhalin region between 1928 and 2015. In this paper, the method for the design of hazard maps for snow avalanches and debris flows is described, providing the starting point for any planning constraints in general settlement planning schemes. These maps further allow conducting an assessment of avalanche and debris flow risk within a short time period for a larger territory and at minimum cost.

     

An ecosystem-based composite spatial model for floodplain vulnerability assessment: a case study of Artigas,Uruguay

Floods are natural processes that constitute a hazard to society when associated to improper land use. Anthropic activities in floodplains are a factor of vulnerability that converts a natural hazard into a threat factor, eventually leading to disaster. Nowadays, natural and social complex processes demand integrated assessments in order to improve their understanding, helping decision making over sustainable use of territory, as well as integrating society’s activity in ecosystems and potentials, restrictions and benefits that society obtain from them. In this context, the objective of this work was to build a composite vulnerability model for a floodplain under urban influence, using an integrated assessment approach. This model was based on three dimensions; threat, fragility and an ecosystem services provision. These dimensions were calculated using both primary and secondary information, and weights by specialists. Main results show that the area presents high vulnerability with an increasing gradient towards high and urbanized areas, associated with an important number and relevant ecosystem services. Also, a spatial heterogeneity of the three dimensions emerged, making evident this area’s complexity and the need of integrated assessments to approach it. The composite vulnerability model proposed presents an elevated potential for natural and social processes analysis in floodplains, which is crucial for these territory management. Moreover, these integrated dimensions could contribute to decision making in different levels, as well as generating important supplies for environmental management and land planning.

     

Spatially distributed rainfall information and its potential for regional landslide early warning systems

Hydrological extreme events pose an imminent risk to society and economics. In this paper, various aspects of hydrological hazards in Russia are analysed at different scales of risk assessment. It is shown that the number of hydrological and meteorological hazards in Russia has been growing every year. The frequency of economic losses associated with extreme low flow in this century has increased by factor five compared to the last decade of the previous century. With regard to floods, an interesting spatial patter can be observed. On the one hand, the number of floods in the Asian part of the country has increased, whereas on the other hand, the number and intensity of floods in estuarine areas in the European part of Russia have significantly reduced since the middle of the twentieth century, especially in the 2000s. This decrease can be attributed to runoff flooding in the mouths of regulated rivers, with an effective system of flood and ice jam protection. The analysis shows that there is an 8–12-year periodicity in the number of flood occurrences and that flood surges have intensified over the last 110 years, especially on the European territory of Russia. An integrated index that accounts for flood hazards and socio-economic vulnerability was calculated for each region of Russia. A classification of flood risk was also developed, taking into account more than 20 hydrological and social–economic characteristics. Based on these characteristics, hazard and vulnerability maps for entire Russia were generated which can be used for water management and the development of future water resources plans.