The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
W Wouter J Botzen - One of the best experts on this subject based on the ideXlab platform.
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adoption of individual Flood Damage mitigation measures in new york city an extension of protection motivation theory
Risk Analysis, 2019Co-Authors: W Wouter J Botzen, Howard Kunreuther, Jeffrey Czajkowski, Hans De MoelAbstract:This study offers insights into factors of influence on the implementation of Flood Damage mitigation measures by more than 1,000 homeowners who live in Flood-prone areas in New York City. Our theoretical basis for explaining Flood preparedness decisions is protection motivation theory, which we extend using a variety of other variables that can have an important influence on individual decision making under risk, such as risk attitudes, time preferences, social norms, trust, and local Flood risk management policies. Our results in relation to our main hypothesis are as follows. Individuals who live in high Flood risk zones take more Flood-proofing measures in their home than individuals in low-risk zones, which suggests the former group has a high threat appraisal. With regard to coping appraisal variables, we find that a high response efficacy and a high self-efficacy play an important role in taking Flood Damage mitigation measures, while perceived response cost does not. In addition, a variety of behavioral characteristics influence individual decisions to Flood-proof homes, such as risk attitudes, time preferences, and private values of being well prepared for Flooding. Investments in elevating one's home are mainly influenced by building code regulations and are negatively related with expectations of receiving federal disaster relief. We discuss a variety of policy recommendations to improve individual Flood preparedness decisions, including incentives for risk reduction through Flood insurance, and communication campaigns focused on coping appraisals and informing people about Flood risk they face over long time horizons.
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economic assessment of mitigating Damage of Flood events cost benefit analysis of Flood proofing commercial buildings in umbria italy
Geneva Papers on Risk and Insurance-issues and Practice, 2017Co-Authors: W Wouter J Botzen, Erika Monteiro, Francisco Estrada, Giulia Pesaro, Scira MenoniAbstract:Floods are among the costliest natural disasters worldwide. Integrated Flood risk management approaches involving both public and private measures have been proposed to cope with trends in Flood risk. These approaches are hampered by a lack of information about the cost-effectiveness of private Flood Damage mitigation measures. This study examines the economic desirability of Flood-proofing different types of commercial buildings in Umbria, which is a Flood-prone region in Europe. A cost–benefit analysis (CBA) is applied, which uses empirical information on Flood Damages to a variety of commercial activities. The CBA accounts for a diversity of uncertainties, including those of Flood Damage statistics and related Flood-proofing benefits derived from bootstrap methods. Results show that, on average, dry Flood-proofing is economically attractive for certain categories of commercial buildings. The Flood probability and uncertainty of Damage are key factors driving CBA results. Implications of our findings for policymakers and insurers are discussed.
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effectiveness of Flood Damage mitigation measures empirical evidence from french Flood disasters
Global Environmental Change-human and Policy Dimensions, 2015Co-Authors: J K Poussin, W Wouter J Botzen, J C J H AertsAbstract:A B S T R A C T Recent destructive Flood events and projected increases in Flood risks as a result of climate change in many regions around the world demonstrate the importance of improving Flood risk management. Flood-proofing of buildings is often advocated as an effective strategy for limiting Damage caused by Floods. However, few empirical studies have estimated the Damage that can be avoided by implementing such Flood Damage mitigation measures. This study estimates potential Damage savings and the costeffectiveness of specific Flood Damage mitigation measures that were implemented by households during major Flood events in France. For this purpose, data about Flood Damage experienced and household Flood preparedness were collected using a survey of 885 French households in three Floodprone regions that face different Flood hazards. Four main conclusions can be drawn from this study. First, using regression analysis results in improved estimates of the effectiveness of mitigation measures than methods used by earlier studies that compare mean Damage suffered between households who have, and who have not, taken these measures. Second, this study has provided empirical insights showing that some mitigation measures can substantially reduce Damage during Floods. Third, the effectiveness of the mitigation measures is very regional dependent, which can be explained by the different characteristics of the Flood hazard in our sample areas that experience either slow onset river Flooding or more rapid flash and coastal Flooding. Fourth, the cost-efficiency of the Flood Damage mitigation
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evaluating the effectiveness of Flood Damage mitigation measures by the application of propensity score matching
Natural Hazards and Earth System Sciences, 2014Co-Authors: Paul Hudson, Heidi Kreibich, W Wouter J Botzen, Philip Bubeck, J C J H AertsAbstract:Abstract. The employment of Damage mitigation measures (DMMs) by individuals is an important component of integrated Flood risk management. In order to promote efficient Damage mitigation measures, accurate estimates of their Damage mitigation potential are required. That is, for correctly assessing the Damage mitigation measures' effectiveness from survey data, one needs to control for sources of bias. A biased estimate can occur if risk characteristics differ between individuals who have, or have not, implemented mitigation measures. This study removed this bias by applying an econometric evaluation technique called propensity score matching (PSM) to a survey of German households along three major rivers that were Flooded in 2002, 2005, and 2006. The application of this method detected substantial overestimates of mitigation measures' effectiveness if bias is not controlled for, ranging from nearly EUR 1700 to 15 000 per measure. Bias-corrected effectiveness estimates of several mitigation measures show that these measures are still very effective since they prevent between EUR 6700 and 14 000 of Flood Damage per Flood event. This study concludes with four main recommendations regarding how to better apply propensity score matching in future studies, and makes several policy recommendations.
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factors of influence on Flood Damage mitigation behaviour by households
Environmental Science & Policy, 2014Co-Authors: J K Poussin, W Wouter J Botzen, J C J H AertsAbstract:Based on a literature review, this paper proposes and empirically tests an extended version of the Protection Motivation Theory (PMT) of individual disaster preparedness. A survey was completed by 885 households in three Flood-prone regions in France. Regression models provide insights into the factors of influence on the implementation of three categories of Flood risk mitigation measures and households’ intentions to implement (additional) measures. Although the results differ per category, the overall findings show that threat appraisals have a small effect on mitigation behaviour, while coping appraisals have a more important influence. Several variables that have been added to the PMT framework appear to be influential in households’ preparedness decisions, such as: Flood experience; local Flood risk management policies and incentives; and the social network. Based on these results, two policy recommendations are made for increasing individual Flood preparedness: improving communication campaigns on Flood Damage mitigation measures, and providing additional financial incentives.
Heidi Kreibich - One of the best experts on this subject based on the ideXlab platform.
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Flood Damage modeling on the basis of urban structure mapping using high resolution remote sensing data
Water, 2014Co-Authors: Tina Gerl, Mathias Bochow, Heidi KreibichAbstract:The modeling of Flood Damage is an important component for risk analyses, which are the basis for risk-oriented Flood management, risk mapping, and financial appraisals. An automatic urban structure type mapping approach was applied on a land use/land cover classification generated from multispectral Ikonos data and LiDAR (Light Detection And Ranging) data in order to provide spatially detailed information about the building stock of the case study area of Dresden, Germany. The multi-parameter Damage models FLEMOps (Flood Loss Estimation Model for the private sector) and regression-tree models have been adapted to the information derived from remote sensing data and were applied on the basis of the urban structure map. To evaluate this approach, which is suitable for risk analyses, as well as for post-disaster event analyses, an estimation of the Flood losses caused by the Elbe Flood in 2002 was undertaken. The urban structure mapping approach delivered a map with a good accuracy of 74% and on this basis modeled Flood losses for the Elbe Flood in 2002 in Dresden were in the same order of magnitude as official Damage data. It has been shown that single-family houses suffered significantly higher Damages than other urban structure types. Consequently, information on their specific location might significantly improve Damage modeling, which indicates a high potential of remote sensing methods to further improve risk assessments.
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evaluating the effectiveness of Flood Damage mitigation measures by the application of propensity score matching
Natural Hazards and Earth System Sciences, 2014Co-Authors: Paul Hudson, Heidi Kreibich, W Wouter J Botzen, Philip Bubeck, J C J H AertsAbstract:Abstract. The employment of Damage mitigation measures (DMMs) by individuals is an important component of integrated Flood risk management. In order to promote efficient Damage mitigation measures, accurate estimates of their Damage mitigation potential are required. That is, for correctly assessing the Damage mitigation measures' effectiveness from survey data, one needs to control for sources of bias. A biased estimate can occur if risk characteristics differ between individuals who have, or have not, implemented mitigation measures. This study removed this bias by applying an econometric evaluation technique called propensity score matching (PSM) to a survey of German households along three major rivers that were Flooded in 2002, 2005, and 2006. The application of this method detected substantial overestimates of mitigation measures' effectiveness if bias is not controlled for, ranging from nearly EUR 1700 to 15 000 per measure. Bias-corrected effectiveness estimates of several mitigation measures show that these measures are still very effective since they prevent between EUR 6700 and 14 000 of Flood Damage per Flood event. This study concludes with four main recommendations regarding how to better apply propensity score matching in future studies, and makes several policy recommendations.
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how useful are complex Flood Damage models
Water Resources Research, 2014Co-Authors: Kai Schroter, Heidi Kreibich, Kristin Vogel, Carsten Riggelsen, Frank Scherbaum, Bruno MerzAbstract:We investigate the usefulness of complex Flood Damage models for predicting relative Damage to residential buildings in a spatial and temporal transfer context. We apply eight different Flood Damage models to predict relative building Damage for five historic Flood events in two different regions of Germany. Model complexity is measured in terms of the number of explanatory variables which varies from 1 variable up to 10 variables which are singled out from 28 candidate variables. Model validation is based on empirical Damage data, whereas observation uncertainty is taken into consideration. The comparison of model predictive performance shows that additional explanatory variables besides the water depth improve the predictive capability in a spatial and temporal transfer context, i.e., when the models are transferred to different regions and different Flood events. Concerning the trade-off between predictive capability and reliability the model structure seem more important than the number of explanatory variables. Among the models considered, the reliability of Bayesian network-based predictions in space-time transfer is larger than for the remaining models, and the uncertainties associated with Damage predictions are reflected more completely.
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multi variate Flood Damage assessment a tree based data mining approach
Natural Hazards and Earth System Sciences, 2013Co-Authors: Bruno Merz, Heidi Kreibich, Upmanu LallAbstract:Abstract. The usual approach for Flood Damage assessment consists of stage-Damage functions which relate the relative or absolute Damage for a certain class of objects to the inundation depth. Other characteristics of the Flooding situation and of the Flooded object are rarely taken into account, although Flood Damage is influenced by a variety of factors. We apply a group of data-mining techniques, known as tree-structured models, to Flood Damage assessment. A very comprehensive data set of more than 1000 records of direct building Damage of private households in Germany is used. Each record contains details about a large variety of potential Damage-influencing characteristics, such as hydrological and hydraulic aspects of the Flooding situation, early warning and emergency measures undertaken, state of precaution of the household, building characteristics and socio-economic status of the household. Regression trees and bagging decision trees are used to select the more important Damage-influencing variables and to derive multi-variate Flood Damage models. It is shown that these models outperform existing models, and that tree-structured models are a promising alternative to traditional Damage models.
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comparative Flood Damage model assessment towards a european approach
Natural Hazards and Earth System Sciences, 2012Co-Authors: Brenden Jongman, Heidi Kreibich, J C J H Aerts, Heiko Apel, Jose I Barredo, Paul D Bates, Luc Feyen, A Gericke, Jeffrey C Neal, Philip J WardAbstract:Abstract. There is a wide variety of Flood Damage models in use internationally, differing substantially in their approaches and economic estimates. Since these models are being used more and more as a basis for investment and planning decisions on an increasingly large scale, there is a need to reduce the uncertainties involved and develop a harmonised European approach, in particular with respect to the EU Flood Risks Directive. In this paper we present a qualitative and quantitative assessment of seven Flood Damage models, using two case studies of past Flood events in Germany and the United Kingdom. The qualitative analysis shows that modelling approaches vary strongly, and that current methodologies for estimating infrastructural Damage are not as well developed as methodologies for the estimation of Damage to buildings. The quantitative results show that the model outcomes are very sensitive to uncertainty in both vulnerability (i.e. depth–Damage functions) and exposure (i.e. asset values), whereby the first has a larger effect than the latter. We conclude that care needs to be taken when using aggregated land use data for Flood risk assessment, and that it is essential to adjust asset values to the regional economic situation and property characteristics. We call for the development of a flexible but consistent European framework that applies best practice from existing models while providing room for including necessary regional adjustments.
J C J H Aerts - One of the best experts on this subject based on the ideXlab platform.
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effectiveness of Flood Damage mitigation measures empirical evidence from french Flood disasters
Global Environmental Change-human and Policy Dimensions, 2015Co-Authors: J K Poussin, W Wouter J Botzen, J C J H AertsAbstract:A B S T R A C T Recent destructive Flood events and projected increases in Flood risks as a result of climate change in many regions around the world demonstrate the importance of improving Flood risk management. Flood-proofing of buildings is often advocated as an effective strategy for limiting Damage caused by Floods. However, few empirical studies have estimated the Damage that can be avoided by implementing such Flood Damage mitigation measures. This study estimates potential Damage savings and the costeffectiveness of specific Flood Damage mitigation measures that were implemented by households during major Flood events in France. For this purpose, data about Flood Damage experienced and household Flood preparedness were collected using a survey of 885 French households in three Floodprone regions that face different Flood hazards. Four main conclusions can be drawn from this study. First, using regression analysis results in improved estimates of the effectiveness of mitigation measures than methods used by earlier studies that compare mean Damage suffered between households who have, and who have not, taken these measures. Second, this study has provided empirical insights showing that some mitigation measures can substantially reduce Damage during Floods. Third, the effectiveness of the mitigation measures is very regional dependent, which can be explained by the different characteristics of the Flood hazard in our sample areas that experience either slow onset river Flooding or more rapid flash and coastal Flooding. Fourth, the cost-efficiency of the Flood Damage mitigation
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evaluating the effectiveness of Flood Damage mitigation measures by the application of propensity score matching
Natural Hazards and Earth System Sciences, 2014Co-Authors: Paul Hudson, Heidi Kreibich, W Wouter J Botzen, Philip Bubeck, J C J H AertsAbstract:Abstract. The employment of Damage mitigation measures (DMMs) by individuals is an important component of integrated Flood risk management. In order to promote efficient Damage mitigation measures, accurate estimates of their Damage mitigation potential are required. That is, for correctly assessing the Damage mitigation measures' effectiveness from survey data, one needs to control for sources of bias. A biased estimate can occur if risk characteristics differ between individuals who have, or have not, implemented mitigation measures. This study removed this bias by applying an econometric evaluation technique called propensity score matching (PSM) to a survey of German households along three major rivers that were Flooded in 2002, 2005, and 2006. The application of this method detected substantial overestimates of mitigation measures' effectiveness if bias is not controlled for, ranging from nearly EUR 1700 to 15 000 per measure. Bias-corrected effectiveness estimates of several mitigation measures show that these measures are still very effective since they prevent between EUR 6700 and 14 000 of Flood Damage per Flood event. This study concludes with four main recommendations regarding how to better apply propensity score matching in future studies, and makes several policy recommendations.
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factors of influence on Flood Damage mitigation behaviour by households
Environmental Science & Policy, 2014Co-Authors: J K Poussin, W Wouter J Botzen, J C J H AertsAbstract:Based on a literature review, this paper proposes and empirically tests an extended version of the Protection Motivation Theory (PMT) of individual disaster preparedness. A survey was completed by 885 households in three Flood-prone regions in France. Regression models provide insights into the factors of influence on the implementation of three categories of Flood risk mitigation measures and households’ intentions to implement (additional) measures. Although the results differ per category, the overall findings show that threat appraisals have a small effect on mitigation behaviour, while coping appraisals have a more important influence. Several variables that have been added to the PMT framework appear to be influential in households’ preparedness decisions, such as: Flood experience; local Flood risk management policies and incentives; and the social network. Based on these results, two policy recommendations are made for increasing individual Flood preparedness: improving communication campaigns on Flood Damage mitigation measures, and providing additional financial incentives.
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stimulating Flood Damage mitigation through insurance an assessment of the french catnat system
Environmental Hazards, 2013Co-Authors: J K Poussin, W Wouter J Botzen, J C J H AertsAbstract:Flood risk has increased in France in the last 20 years and is projected to increase further in the future due to climate change and increase in exposure. Since 1982, France has had a natural disasters insurance system (‘CatNat’) in place that covers Flood Damage. This insurance system has been combined with what are called ‘Risk Prevention Plans’ (PPRs) in order to stimulate the undertaking of Flood risk mitigation measures by communities and households. However, these schemes do not provide optimal incentives for Flood Damage reduction. This is confirmed by the results from a survey about Flood preparedness of 885 households who live in Flood-prone areas in France, which are presented in this paper. Moreover, this study provides suggestions for improvement, which are assessed on their potential economic, social and political implications. Among these suggestions are increasing the effectiveness of PPRs and increasing the incentives to apply and implement PPRs; improving the monitoring of the implementat...
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low probability Flood risk modeling for new york city
Risk Analysis, 2013Co-Authors: J C J H Aerts, Ning Lin, W Wouter J Botzen, Kerry Emanuel, Hans De MoelAbstract: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.
Hans De Moel - One of the best experts on this subject based on the ideXlab platform.
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adoption of individual Flood Damage mitigation measures in new york city an extension of protection motivation theory
Risk Analysis, 2019Co-Authors: W Wouter J Botzen, Howard Kunreuther, Jeffrey Czajkowski, Hans De MoelAbstract:This study offers insights into factors of influence on the implementation of Flood Damage mitigation measures by more than 1,000 homeowners who live in Flood-prone areas in New York City. Our theoretical basis for explaining Flood preparedness decisions is protection motivation theory, which we extend using a variety of other variables that can have an important influence on individual decision making under risk, such as risk attitudes, time preferences, social norms, trust, and local Flood risk management policies. Our results in relation to our main hypothesis are as follows. Individuals who live in high Flood risk zones take more Flood-proofing measures in their home than individuals in low-risk zones, which suggests the former group has a high threat appraisal. With regard to coping appraisal variables, we find that a high response efficacy and a high self-efficacy play an important role in taking Flood Damage mitigation measures, while perceived response cost does not. In addition, a variety of behavioral characteristics influence individual decisions to Flood-proof homes, such as risk attitudes, time preferences, and private values of being well prepared for Flooding. Investments in elevating one's home are mainly influenced by building code regulations and are negatively related with expectations of receiving federal disaster relief. We discuss a variety of policy recommendations to improve individual Flood preparedness decisions, including incentives for risk reduction through Flood insurance, and communication campaigns focused on coping appraisals and informing people about Flood risk they face over long time horizons.
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low probability Flood risk modeling for new york city
Risk Analysis, 2013Co-Authors: J C J H Aerts, Ning Lin, W Wouter J Botzen, Kerry Emanuel, Hans De MoelAbstract: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$5 bn and 11 bn for a 1/500-year storm surge. An analysis of Flood risk in each of the five boroughs of NYC finds that Brooklyn and Queens are the most vulnerable to Flooding. This study examines several uncertainties in the various steps of the risk analysis, which resulted in variations in Flood Damage estimations. These uncertainties include: the interpolation of Flood depths; the use of different Flood Damage curves; and the influence of the spectra of characteristics of the simulated hurricanes.
Anders Levermann - One of the best experts on this subject based on the ideXlab platform.
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coastal Flood Damage and adaptation costs under 21st century sea level rise
Proceedings of the National Academy of Sciences of the United States of America, 2014Co-Authors: Jochen Hinkel, Daniel Lincke, Athanasios T Vafeidis, Mahe Perrette, Robert J Nicholls, Ben Marzeion, Xavier Fettweis, Cezar Ionescu, Anders LevermannAbstract:Coastal Flood Damage and adaptation costs under 21st century sea-level rise are assessed on a global scale taking into account a wide range of uncertainties in continental topography data, population data, protection strategies, socioeconomic development and sea-level rise. Uncertainty in global mean and regional sea level was derived from four different climate models from the Coupled Model Intercomparison Project Phase 5, each combined with three land-ice scenarios based on the published range of contributions from ice sheets and glaciers. Without adaptation, 0.2-4.6% of global population is expected to be Flooded annually in 2100 under 25-123 cm of global mean sea-level rise, with expected annual losses of 0.3-9.3% of global gross domestic product. Damages of this magnitude are very unlikely to be tolerated by society and adaptation will be widespread. The global costs of protecting the coast with dikes are significant with annual investment and maintenance costs of US$ 12-71 billion in 2100, but much smaller than the global cost of avoided Damages even without accounting for indirect costs of Damage to regional production supply. Flood Damages by the end of this century are much more sensitive to the applied protection strategy than to variations in climate and socioeconomic scenarios as well as in physical data sources (topography and climate model). Our results emphasize the central role of long-term coastal adaptation strategies. These should also take into account that protecting large parts of the developed coast increases the risk of catastrophic consequences in the case of defense failure.