Predicting Loss of Life in Cases of Dam Failure and Flash Flood

This paper improves upon previous attempts to predict loss of life (LOL) from severe flooding events. An expression for LOL in terms of warning time (WT), the size of the population at risk (PAR), and the forcefulness of the flood waters (Force) is derived from the historical record of dam failures and flash flood cases via logistic regression. There is no evidence for an effect of prior flooding experience or an interaction between WT and PAR, as has been suggested elsewhere. Guidelines are suggested for the proper use of the final equations and the findings are discussed in relation to a theoretical model of flood fatalities.     

Mortality Patterns of Hydro‐Geomorphologic Disasters

Social impacts caused by floods and landslides in Portugal in the period of 1865–2010 are gathered in the DISASTER database. This database contains 1,902 hydro‐geomorphologic cases that caused 1,248 fatalities (81% and 19% associated with floods and landslides, respectively). The use of the DISASTER database allowed for: (i) the analysis of the frequency and the temporal evolution of fatal floods and landslides; (ii) the analysis of the spatio‐temporal distribution of fatalities; (iii) the identification of the most deadly flood and landside types; (iv) the verification of gender tendencies in mortalities; and (v) the evaluation of individual and societal risk. The highest number of flood and landslide cases and related mortalities occurred in the period of 1935–1969. After this period, the number of flood and landslide mortalities decreased, although landslide fatalities remained higher than those registered in the period of 1865–1934. The occurrence of flood fatalities was widespread in the country, with an important cluster in the Lisbon region and in the Tagus valley, while fatalities caused by landslides mainly occurred in the north of the Tagus valley. Flash floods caused the majority of fatalities associated with floods, while falls and flows were responsible for the highest number of fatalities associated with landslides. Males were found to have the highest frequency of fatalities. In the case of floods, the majority of fatalities were found both outdoors and inside of buildings in rural areas while fatalities inside buildings were dominant in landslide cases, mostly in rural areas.     

Flood Risk Assessment in the Netherlands: A Case Study for Dike Ring South Holland

Large parts of the Netherlands are below sea level. Therefore, it is important to have insight into the possible consequences and risks of flooding. In this article, an analysis of the risks due to flooding of the dike ring area South Holland in the Netherlands is presented. For different flood scenarios the potential number of fatalities is estimated. Results indicate that a flood event in this area can expose large and densely populated areas and result in hundreds to thousands of fatalities. Evacuation of South Holland before a coastal flood will be difficult due to the large amount of time required for evacuation and the limited time available. By combination with available information regarding the probability of occurrence of different flood scenarios, the flood risks have been quantified. The probability of death for a person in South Holland due to flooding, the so‐called individual risk, is small. The probability of a flood disaster with many fatalities, the so‐called societal risk, is relatively large in comparison with the societal risks in other sectors in the Netherlands, such as the chemical sector and aviation. The societal risk of flooding appears to be unacceptable according to some of the existing risk limits that have been proposed in literature. These results indicate the necessity of a further societal discussion on the acceptable level of flood risk in the Netherlands and the need for additional risk reducing measures.     

Low‐Probability Flood Risk Modeling for New York City

The devastating impact by Hurricane Sandy (2012) again showed New York City (NYC) is one of the most vulnerable cities to coastal flooding around the globe. The low‐lying areas in NYC can be flooded by nor'easter storms and North Atlantic hurricanes. The few studies that have estimated potential flood damage for NYC base their damage estimates on only a single, or a few, possible flood events. The objective of this study is to assess the full distribution of hurricane flood risk in NYC. This is done by calculating potential flood damage with a flood damage model that uses many possible storms and surge heights as input. These storms are representative for the low‐probability/high‐impact flood hazard faced by the city. Exceedance probability‐loss curves are constructed under different assumptions about the severity of flood damage. The estimated flood damage to buildings for NYC is between US$59 and 129 millions/year. The damage caused by a 1/100‐year storm surge is within a range of US$2 bn–5 bn, while this is between US$5 bn and 11 bn for a 1/500‐year storm surge. An analysis of flood risk in each of the five boroughs of NYC finds that Brooklyn and Queens are the most vulnerable to flooding. This study examines several uncertainties in the various steps of the risk analysis, which resulted in variations in flood damage estimations. These uncertainties include: the interpolation of flood depths; the use of different flood damage curves; and the influence of the spectra of characteristics of the simulated hurricanes.     

Are We Adapting to Floods? Evidence from Global Flooding Fatalities

There has been a growing interest in understanding whether and how people adapt to extreme weather events in a changing climate. This article presents one of the first empirical analyses of adaptation to flooding on a global scale. Using a sample of 97 countries between 1985 and 2010, we investigate the extent and pattern of flood adaptation by estimating the effects of a country's climatological risk, recent flood experiences, and socioeconomic characteristics on its flood‐related fatalities. Our results provide mixed evidence on adaptation: countries facing greater long‐term climatological flooding risks do not necessarily adapt better and suffer fewer fatalities; however, after controlling for the cross‐country heterogeneity, we find that more recent flooding shocks have a significant and negative effect on fatalities from subsequent floods. These findings may suggest the short‐term learning dynamics of adaptation and potential inefficacy of earlier flood control measures, particularly those that promote increased exposure in floodplains. Our findings provide important implications for climate adaptation policy making and climate modeling.     

A Probabilistic Model of the Economic Risk to Britain's Railway Network from Bridge Scour During Floods

Scour (localized erosion by water) is an important risk to bridges, and hence many infrastructure networks, around the world. In Britain, scour has caused the failure of railway bridges crossing rivers in more than 50 flood events. These events have been investigated in detail, providing a data set with which we develop and test a model to quantify scour risk. The risk analysis is formulated in terms of a generic, transferrable infrastructure network risk model. For some bridge failures, the severity of the causative flood was recorded or can be reconstructed. These data are combined with the background failure rate, and records of bridges that have not failed, to construct fragility curves that quantify the failure probability conditional on the severity of a flood event. The fragility curves generated are to some extent sensitive to the way in which these data are incorporated into the statistical analysis. The new fragility analysis is tested using flood events simulated from a spatial joint probability model for extreme river flows for all river gauging sites in Britain. The combined models appear robust in comparison with historical observations of the expected number of bridge failures in a flood event. The analysis is used to estimate the probability of single or multiple bridge failures in Britain's rail network. Combined with a model for passenger journey disruption in the event of bridge failure, we calculate a system‐wide estimate for the risk of scour failures in terms of passenger journey disruptions and associated economic costs.     

Public Perception of the Risks of Floods: Implications for Communication

Floods in the U.S. kill an average of 162 people each year and cause $3.4 billion in property damage. Flood control programs have been successful in lowering, but not eliminating, the risks to lives and property. Since the late 1960s, the federal government has emphasized flood insurance as a primary tool for improving location and flood-proofing decisions, as well as for reimbursing flood losses. Since only 12.7% of houses in flood plain areas are covered by flood insurance, the program has been ineffective. We interviewed people living in three communities that had recently been flooded. Most people had little knowledge of the cause of floods or what could be done to prevent damage. People who work and who are better educated know more and are more likely to have flood insurance. Current government publications about flood risks are not likely to be understood by those at risk. There is little effective communication about the nature and magnitude of the risks and what individuals can do to protect their lives and property and lower their financial risks. The risk management program should both emphasize communication and enforcement of the current law requiring people at risk who hold federally funded loans to be insured.     

A Probabilistic Analysis of Surface Water Flood Risk in London

Flooding in urban areas during heavy rainfall, often characterized by short duration and high‐intensity events, is known as “surface water flooding.” Analyzing surface water flood risk is complex as it requires understanding of biophysical and human factors, such as the localized scale and nature of heavy precipitation events, characteristics of the urban area affected (including detailed topography and drainage networks), and the spatial distribution of economic and social vulnerability. Climate change is recognized as having the potential to enhance the intensity and frequency of heavy rainfall events. This study develops a methodology to link high spatial resolution probabilistic projections of hourly precipitation with detailed surface water flood depth maps and characterization of urban vulnerability to estimate surface water flood risk. It incorporates probabilistic information on the range of uncertainties in future precipitation in a changing climate. The method is applied to a case study of Greater London and highlights that both the frequency and spatial extent of surface water flood events are set to increase under future climate change. The expected annual damage from surface water flooding is estimated to be to be £171 million, £343 million, and £390 million/year under the baseline, 2030 high, and 2050 high climate change scenarios, respectively.     

The Use of Individual and Societal Risk Criteria Within the Dutch Flood Safety Policy—Nationwide Estimates of Societal Risk and Policy Applications

The Dutch government is in the process of revising its flood safety policy. The current safety standards for flood defenses in the Netherlands are largely based on the outcomes of cost‐benefit analyses. Loss of life has not been considered separately in the choice for current standards. This article presents the results of a research project that evaluated the potential roles of two risk metrics, individual and societal risk, to support decision making about new flood safety standards. These risk metrics are already used in the Dutch major hazards policy for the evaluation of risks to the public. Individual risk concerns the annual probability of death of a person. Societal risk concerns the probability of an event with many fatalities. Technical aspects of the use of individual and societal risk metrics in flood risk assessments as well as policy implications are discussed. Preliminary estimates of nationwide levels of societal risk are presented. Societal risk levels appear relatively high in the southwestern part of the country where densely populated dike rings are threatened by a combination of river and coastal floods. It was found that cumulation, the simultaneous flooding of multiple dike rings during a single flood event, has significant impact on the national level of societal risk. Options for the application of the individual and societal risk in the new flood safety policy are presented and discussed.     

Mortality Risks Induced by Economic Expenditures

Existing evidence shows that lower incomes are associated with higher mortality risks. This paper examines the implications for fatalities when the relationship is interpreted as an induced relationship, meaning that lower incomes will on average lead to higher mortality risks. A model is developed for estimating the number of fatalities possibly induced by economic expenditures. This model accounts for different allocations of the expenditures on family units with varying income levels. Illustrative calculations provide insights about the possible significance of fatalities induced by economic expenditures. These results suggest that some expensive regulations and programs intended to save lives may actually lead to increased fatalities. Important caveats to reduce the likelihood of misinterpreting or misusing the results are included.     

Insurability and Mitigation of Flood Losses in Private Households in Germany

In Germany, flood insurance is provided by private insurers as a supplement to building or contents insurance. This article presents the results of a survey of insurance companies with regard to eligibility conditions for flood insurance changes after August 2002, when a severe flood caused 1.8 billion euro of insured losses in the Elbe and the Danube catchment areas, and the general role of insurance in flood risk management in Germany. Besides insurance coverage, governmental funding and public donations played an important role in loss compensation after the August 2002 flood. Therefore, this article also analyzes flood loss compensation, risk awareness, and mitigation in insured and uninsured private households. Insured households received loss compensation earlier. They also showed slightly better risk awareness and mitigation strategies. Appropriate incentives should be combined with flood insurance in order to strengthen future private flood loss mitigation. However, there is some evidence that the surveyed insurance companies do little to encourage precautionary measures. To overcome this problem, flood hazards and mitigation strategies should be better communicated to both insurance companies and property owners.     

Examining the 100‐Year Floodplain as a Metric of Risk,Loss, and Household Adjustment

An understudied, but central aspect in understanding flood impacts is the way we conceptualize, identify, and delineate risk. The 100‐year floodplain is the longstanding metric in the United States for determining and acting upon the possibility of an area being inundated. This spatial delineation guides local planning and development decisions, triggers insurance purchases and other household adjustments, and serves as the fundamental indicator for whether it is safe to build a structure on a particular site. However, increasing evidence suggests that the 100‐year floodplain is neither accurate nor sufficient in guiding communities and household decisions to mitigate the adverse economic impacts of floods. In this perspective, we examine the effectiveness of the 100‐year floodplain as an appropriate marker of risk. First, we review existing studies on location and flood damage. Next, we apply these concepts to repetitive flood losses data in Harris County, Texas. We conclude that the apparent inability of the floodplain designation to effectively capture the likelihood of property damage and potential loss of human life in coastal areas has left potentially millions of property owners unaware of the flood risk and unprepared to mitigate their adverse impacts. Relying on traditional 100‐year floodplain boundaries, local decision makers are hampered in their ability to ensure community development occurs in a resilient manner. Finally, we set forth an agenda for future research to better capture the conditions associated with flood risk and account for the large percentage of damage outside the designated floodplain.     

Flood risk mapping and analysis using an integrated framework of machine learning models and analytic hierarchy process

In this study, a new approach of machine learning (ML) models integrated with the analytic hierarchy process (AHP) method was proposed to develop a holistic flood risk assessment map. Flood susceptibility maps were created using ML techniques. AHP was utilized to combine flood vulnerability and exposure criteria. We selected Quang Binh province of Vietnam as a case study and collected available data, including 696 flooding locations of historical flooding events in 2007, 2010, 2016, and 2020; and flood influencing factors of elevation, slope, curvature, flow direction, flow accumulation, distance from river, river density, land cover, geology, and rainfall. These data were used to construct training and testing datasets. The susceptibility models were validated and compared using statistical techniques. An integrated flood risk assessment framework was proposed to incorporate flood hazard (flood susceptibility), flood exposure (distance from river, land use, population density, and rainfall), and flood vulnerability (poverty rate, number of freshwater stations, road density, number of schools, and healthcare facilities). Model validation suggested that deep learning has the best performance of AUC = 0.984 compared with other ensemble models of MultiBoostAB Ensemble (0.958), Random SubSpace Ensemble (0.962), and credal decision tree (AUC = 0.918). The final flood risk map shows 5075 ha (0.63%) in extremely high risk, 47,955 ha (5.95%) in high-risk, 40,460 ha (5.02%) in medium risk, 431,908 ha (53.55%) in low risk areas, and 281,127 ha (34.86%) in very low risk. The present study highlights that the integration of ML models and AHP is a promising framework for mapping flood risks in flood-prone areas.     

Probabilistic Modeling of Flood Hazard and its Risk Assessment for Eastern Region of India

This article models flood occurrence probabilistically and its risk assessment. It incorporates atmospheric parameters to forecast rainfall in an area. This measure of precipitation, together with river and ground parameters, serve as parameters in the model to predict runoff and subsequently inundation depth of an area. The inundation depth acts as a guide for predicting flood proneness and associated hazard. The vulnerability owing to flood has been analyzed as social vulnerability $(V_S)$, vulnerability to property $(V_P)$, and vulnerability to the location in terms of awareness $(V_A)$. The associated risk has been estimated for each area. The distribution of risk values can be used to classify every area into one of the six risk zones—namely, very low risk, low risk, moderately low risk, medium risk, high risk, and very high risk. The prioritization regarding preparedness, evacuation planning, or distribution of relief items should be guided by the range on the risk scale within which the area under study falls. The flood risk assessment model framework has been tested on a real‐life case study. The flood risk indices for each of the municipalities in the area under study have been calculated. The risk indices and hence the flood risk zone under which a municipality is expected to lie would alter every day. The appropriate authorities can then plan ahead in terms of preparedness to combat the impending flood situation in the most critical and vulnerable areas.     

Toward Probabilistic Prediction of Flash Flood Human Impacts

This article focuses on conceptual and methodological developments allowing the integration of physical and social dynamics leading to model forecasts of circumstance‐specific human losses during a flash flood. To reach this objective, a random forest classifier is applied to assess the likelihood of fatality occurrence for a given circumstance as a function of representative indicators. Here, vehicle‐related circumstance is chosen as the literature indicates that most fatalities from flash flooding fall in this category. A database of flash flood events, with and without human losses from 2001 to 2011 in the United States, is supplemented with other variables describing the storm event, the spatial distribution of the sensitive characteristics of the exposed population, and built environment at the county level. The catastrophic flash floods of May 2015 in the states of Texas and Oklahoma are used as a case study to map the dynamics of the estimated probabilistic human risk on a daily scale. The results indicate the importance of time‐ and space‐dependent human vulnerability and risk assessment for short‐fuse flood events. The need for more systematic human impact data collection is also highlighted to advance impact‐based predictive models for flash flood casualties using machine‐learning approaches in the future.     

A Probabilistic Framework for Risk Analysis of Widespread Flood Events: A Proof‐of‐Concept Study

This article presents a flood risk analysis model that considers the spatially heterogeneous nature of flood events. The basic concept of this approach is to generate a large sample of flood events that can be regarded as temporal extrapolation of flood events. These are combined with cumulative flood impact indicators, such as building damages, to finally derive time series of damages for risk estimation. Therefore, a multivariate modeling procedure that is able to take into account the spatial characteristics of flooding, the regionalization method top‐kriging, and three different impact indicators are combined in a model chain. Eventually, the expected annual flood impact (e.g., expected annual damages) and the flood impact associated with a low probability of occurrence are determined for a study area. The risk model has the potential to augment the understanding of flood risk in a region and thereby contribute to enhanced risk management of, for example, risk analysts and policymakers or insurance companies. The modeling framework was successfully applied in a proof‐of‐concept exercise in Vorarlberg (Austria). The results of the case study show that risk analysis has to be based on spatially heterogeneous flood events in order to estimate flood risk adequately.     

Experimental Evidence Against the Paradigm of Mortality Risk Aversion

This article deals with the question of how societal impacts of fatal accidents can be integrated into the management of natural or man‐made hazards. Today, many governmental agencies give additional weight to the number of potential fatalities in their risk assessments to reflect society's aversion to large accidents. Although mortality risk aversion has been proposed in numerous risk management guidelines, there has been no evidence that lay people want public decisionmakers to overweight infrequent accidents of large societal consequences against more frequent ones of smaller societal consequences. Furthermore, it is not known whether public decisionmakers actually do such overweighting when they decide upon the mitigation of natural or technical hazards. In this article, we report on two experimental tasks that required participants to evaluate negative prospects involving 1–100 potential fatalities. Our results show that neither lay people nor hazard experts exhibit risk‐averse behavior in decisions on mortality risks.     

Prevention,Adaptation, and Threat Denial: Flooding Experiences in the Netherlands

Delta areas such as the Netherlands are more and more at risk of future flooding due to global climate change. Motivating residents living in flood-prone areas to effectively cope with local floods may lead to minimization of material losses and loss of life. The aim of this research was to investigate whether the extent to which residents had been exposed to flooding in the past was a key factor in motivating residents to effectively cope with future flooding. We also focused on the psychological variables that mediated this relationship. We conducted a survey (N = 516) among flood victims and nonvictims. We assessed subjective experiences due to past flooding, affective and cognitive appraisals, and coping responses. Results show that victims reported stronger emotions (negative and positive), and the receipt of more social support due to past flooding than did nonvictims. Moreover, victims worry more about future flooding, perceive themselves as more vulnerable to future flooding, perceive the consequences of future flooding as more severe, and have stronger intentions to take adaptive actions in the future than nonvictims. Structural equation modeling reveals that the latter effect was fully mediated by specific experiences and appraisals. Insights into factors and processes that have the potential to motivate residents to effectively cope with future floods may prove helpful in developing interventions to inform residents how to act effectively in case of an imminent flood.     

Assessing and Preventing Serious Incidents with Behavioral Science: Enhancing Heinrich’s Triangle for the 21st Century

ABSTRACT

The rate of occupational injuries has been declining annually, but the rate of decline for fatalities has not kept a similar pace. Behavior-based safety (BBS) contributes to reducing personal injuries, and can be applied to preventing serious incidents. To address serious injuries with greater confidence requires a change in perspective on the causes of fatalities and serious injuries. Heinrich’s safety triangle helps describe the ratio between minor incidents and major incidents, but is not adequate in helping to predict serious incidents. Adding a special subset to the safety triangle can assist safety practitioners in predicting and influencing such events. Extending the triangle to include more foundational root causes, such as leadership shortcomings and system failures, will expand the scope of the behavior analysis, and including greater specificity about the precursors to serious incidents will help the precision of the behavior analysis. The implications of the expanded triangle for amplifying the effectiveness of BBS for reducing serious incidents are discussed.     

A Risk-Based Method for Modeling Traffic Fatalities

We describe a risk-based analytical framework for estimating traffic fatalities that combines the probability of a crash and the probability of fatality in the event of a crash. As an illustrative application, we use the methodology to explore the role of vehicle mix and vehicle prevalence on long-run fatality trends for a range of transportation growth scenarios that may be relevant to developing societies. We assume crash rates between different road users are proportional to their roadway use and estimate case fatality ratios (CFRs) for the different vehicle-vehicle and vehicle-pedestrian combinations. We find that in the absence of road safety interventions, the historical trend of initially rising and then falling fatalities observed in industrialized nations occurred only if motorization was through car ownership. In all other cases studied (scenarios dominated by scooter use, bus use, and mixed use), traffic fatalities rose monotonically. Fatalities per vehicle had a falling trend similar to that observed in historical data from industrialized nations. Regional adaptations of the model validated with local data can be used to evaluate the impacts of transportation planning and safety interventions, such as helmets, seat belts, and enforcement of traffic laws, on traffic fatalities.