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The behaviour of individuals, businesses, and government entities before, during, and immediately after a disaster can dramatically affect the impact and recovery time. However, existing risk-assessment methods rarely include this critical factor. In this Perspective, we show why this is a concern, and demonstrate that although initial efforts have inevitably represented human behaviour in limited terms, innovations in flood-risk assessment that integrate societal behaviour and behavioural adaptation dynamics into such quantifications may lead to more accurate characterization of risks and improved assessment of the effectiveness of risk-management strategies and investments. Such multidisciplinary approaches can inform flood-risk management policy development.

The behaviour of individuals, businesses, and government entities before, during, and immediately after a disaster can dramatically affect the impact and recovery time. However, existing risk-assessment methods rarely include this critical factor. In this Perspective, we show why this is a concern, and demonstrate that although initial efforts have inevitably represented human behaviour in limited terms, innovations in flood-risk assessment that integrate societal behaviour and behavioural adaptation dynamics into such quantifications may lead to more accurate characterization of risks and improved assessment of the effectiveness of risk-management strategies and investments. Such multidisciplinary approaches can inform flood-risk management policy development.

Given the series of large-scale flood disasters that have occurred in recent years, there is a growing recognition among community leaders, businesses, insurers, governments and international donors of the need to invest in risk reduction measures before such events happen. Due to the costs of risk reduction measures, these actions need to be justified and as a result there is an increasing need to utilize decision-support tools, which can help to make the case for action to reduce disaster risks and build flood resilience when faced with limited resources. Across stakeholders, the specific objectives from the use of decision-support tools include (i) demonstrating the efficiency of the action ex-ante (before the flood); (ii) aiding in the selection of a particular intervention in enhancing community flood resilience from a suite of possible options; (iii) helping communities make the right choice when faced with limited investments; (iv) demonstrating the benefits of donor funding of community flood resilience projects; and (v) monitoring the successes and weaknesses of past interventions to generate lessons learned for future work. Typically, discussion on decision-support for disaster risk reduction (DRR) in floods (as well as for other hazards) has focused on cost-benefit analysis (CBA), however there are a number of other tools available to support decision-making. These include cost-effectiveness analysis (CEA), multi-criteria analysis (MCA) and robust-decision-making approaches (RDMA), which have been applied to similar problems, and can also be used to aid decision-making regarding flooding. This white paper provides an overview of the opportunities and challenges of applying these different tools, and guides the reader to select among them. Selection depends on the desired objective, circumstances, data available, timeframe to perform analyses, level of detail, and other considerations. We first focus on the CBA decision-tool, as this has been the mainstay

Many issues need to be considered when deciding how best to help protect a community from floods. In this paper, Zurich flood resilience alliance members examine methodologies that can support the decision-making process to help those when and where it matters most.

Given the series of large-scale flood disasters that have occurred in recent years, there is a growing recognition among community leaders, businesses, insurers, governments and international donors of the need to invest in risk reduction measures before such events happen. Due to the costs of risk reduction measures, these actions need to be justified and as a result there is an increasing need to utilize decision-support tools, which can help to make the case for action to reduce disaster risks and build flood resilience when faced with limited resources. Across stakeholders, the specific objectives from the use of decision-support tools include (i) demonstrating the efficiency of the action ex-ante (before the flood); (ii) aiding in the selection of a particular intervention in enhancing community flood resilience from a suite of possible options; (iii) helping communities make the right choice when faced with limited investments; (iv) demonstrating the benefits of donor funding of community flood resilience projects; and (v) monitoring the successes and weaknesses of past interventions to generate lessons learned for future work. Typically, discussion on decision-support for disaster risk reduction (DRR) in floods (as well as for other hazards) has focused on cost-benefit analysis (CBA), however there are a number of other tools available to support decision-making. These include cost-effectiveness analysis (CEA), multi-criteria analysis (MCA) and robust-decision-making approaches (RDMA), which have been applied to similar problems, and can also be used to aid decision-making regarding flooding. This white paper provides an overview of the opportunities and challenges of applying these different tools, and guides the reader to select among them. Selection depends on the desired objective, circumstances, data available, timeframe to perform analyses, level of detail, and other considerations. We first focus on the CBA decision-tool, as this has been the mainstay

Given the series of large-scale flood disasters that have occurred in recent years, there is a growing recognition among community leaders, businesses, insurers, governments and international donors of the need to invest in risk reduction measures before such events happen. Due to the costs of risk reduction measures, these actions need to be justified and as a result there is an increasing need to utilize decision-support tools, which can help to make the case for action to reduce disaster risks and build flood resilience when faced with limited resources. Across stakeholders, the specific objectives from the use of decision-support tools include (i) demonstrating the efficiency of the action ex-ante (before the flood); (ii) aiding in the selection of a particular intervention in enhancing community flood resilience from a suite of possible options; (iii) helping communities make the right choice when faced with limited investments; (iv) demonstrating the benefits of donor funding of community flood resilience projects; and (v) monitoring the successes and weaknesses of past interventions to generate lessons learned for future work. Typically, discussion on decision-support for disaster risk reduction (DRR) in floods (as well as for other hazards) has focused on cost-benefit analysis (CBA), however there are a number of other tools available to support decision-making. These include cost-effectiveness analysis (CEA), multi-criteria analysis (MCA) and robust-decision-making approaches (RDMA), which have been applied to similar problems, and can also be used to aid decision-making regarding flooding. This white paper provides an overview of the opportunities and challenges of applying these different tools, and guides the reader to select among them. Selection depends on the desired objective, circumstances, data available, timeframe to perform analyses, level of detail, and other considerations. We first focus on the CBA decision-tool, as this has been the mainstay

Many issues need to be considered when deciding how best to help protect a community from floods. In this paper, Zurich flood resilience alliance members examine methodologies that can support the decision-making process to help those when and where it matters most.

Major natural disasters in recent years have had high human and economic costs, and triggered record high post-disaster relief from governments and international donors. Given the current economic situation worldwide, selecting the most effective disaster risk reduction (DRR) measures is critical. This is especially the case for low- and middle-income countries, which have suffered disproportionally more economic and human losses from disasters. This article discusses a methodology that makes use of advanced probabilistic catastrophe models to estimate benefits of DRR measures. We apply such newly developed models to generate estimates for hurricane risk on residential structures on the island of St. Lucia, and earthquake risk on residential structures in Istanbul, Turkey, as two illustrative case studies. The costs and economic benefits for selected risk reduction measures are estimated taking account of hazard, exposure, and vulnerability. We conclude by emphasizing the advantages and challenges of catastrophe model-based cot-benefit analyses for DRR in developing countries.

Major natural disasters in recent years have had high human and economic costs, and triggered record high post-disaster relief from governments and international donors. Given the current economic situation worldwide, selecting the most effective disaster risk reduction (DRR) measures is critical. This is especially the case for low- and middle-income countries, which have suffered disproportionally more economic and human losses from disasters. This article discusses a methodology that makes use of advanced probabilistic catastrophe models to estimate benefits of DRR measures. We apply such newly developed models to generate estimates for hurricane risk on residential structures on the island of St. Lucia, and earthquake risk on residential structures in Istanbul, Turkey, as two illustrative case studies. The costs and economic benefits for selected risk reduction measures are estimated taking account of hazard, exposure, and vulnerability. We conclude by emphasizing the advantages and challenges of catastrophe model-based cot-benefit analyses for DRR in developing countries.

The behaviour of individuals, businesses, and government entities before, during, and immediately after a disaster can dramatically affect the impact and recovery time. However, existing risk-assessment methods rarely include this critical factor. In this Perspective, we show why this is a concern, and demonstrate that although initial efforts have inevitably represented human behaviour in limited terms, innovations in flood-risk assessment that integrate societal behaviour and behavioural adaptation dynamics into such quantifications may lead to more accurate characterization of risks and improved assessment of the effectiveness of risk-management strategies and investments. Such multidisciplinary approaches can inform flood-risk management policy development.