Review article "Assessment of economic flood damage"

By B. Merz, Heidi Kreibich, Reimund Schwarze, A. Thieken. 2010

1,259 citations recorded by the source corpus.

Abstract. Damage assessments of natural hazards supply crucial information to decision support and policy development in the fields of natural hazard management and adaptation planning to climate change. Specifically, the estimation of economic flood damage is gaining greater importance as flood risk management is becoming the dominant approach of flood control policies throughout Europe. This paper reviews the state-of-the-art and identifies research directions of economic flood damage assessment. Despite the fact that considerable research effort has been spent and progress has been made on damage data collection, data analysis and model development in recent years, there still seems to be a mismatch between the relevance of damage assessments and the quality of the available models and datasets. Often, simple approaches are used, mainly due to limitations in available data and knowledge on damage mechanisms. The results of damage assessments depend on many assumptions, e.g. the selection of spatial and temporal boundaries, and there are many pitfalls in economic evaluation, e.g. the choice between replacement costs or depreciated values. Much larger efforts are required for empirical and synthetic data collection and for providing consistent, reliable data to scientists and practitioners. A major shortcoming of damage modelling is that model validation is scarcely performed. Uncertainty analyses and thorough scrutiny of model inputs and assumptions should be mandatory for each damage model development and application, respectively. In our view, flood risk assessments are often not well balanced. Much more attention is given to the hazard assessment part, whereas damage assessment is treated as some kind of appendix within the risk analysis. Advances in flood damage assessment could trigger subsequent methodological improvements in other natural hazard areas with comparable time-space properties.

Subfields: Economics and Econometrics, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/7a2da7c02f6b058b3c836823d5272d6b49c01619

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Citations in the corpus

Assessing flood risk at the global scale: model setup, results, and sensitivity (2013, background): “Generally, uncertainties in absolute flood risk estimates are large (Apel et al 2008, Merz et al 2010, De Moel and Aerts 2011), whilst estimates of relative changes in risk under different scenarios are more robust (e.g. Bubeck et al 2011).”
Review Article: Economic evaluation of flood damage to agriculture – review and analysis of existing methods (2013, background): “Among these sectors, agriculture is frequently considered to be of minor importance compared to industrial or residential sectors, for example, because at the same level of exposure, total damage may be comparatively lower (Merz et al., 2010).”
Review article: assessing the costs of natural hazards - state of the art and knowledge gaps (2013, background): “Several such overviews of cost assessment methods exist for ﬂoods (e.g. Penning-Rowsell and Fordham, 1994; Smith, 1994; Meyer and Mess-ner, 2005; Messner et al., 2007; Merz et al., 2010).”
Uncertainty in flood damage estimates and its potential effect on investment decisions (2015, background): “Flood damage assessment is an essential aspect of flood risk management (Merz et al., 2010).”
Global exposure to river and coastal flooding - long term trends and changes (2012, background): “relationships between flood depth and relative damage per area unit, in combination with land-cover data of the flooded area (Smith, 1994; Merz et al., 2010).”
The Monetary Benefit of Early Flood Warnings in Europe (2015, positive): “Estimating the economic value of a forecasting system as a whole is far more complicated (Benson and Clay, 2004; Bockstael et al., 2000; Merz et al., 2010; Parker, 2003) as it depends on: the starting point (e.g. what type of forecasting system already exists); the spatial and temporal dimensions…”
Building treatments for urban flood inundation models and implications for predictive skill and modeling efficiency (2012, background): “Moreover, flood inundation models play a central role in the evaluation, selection and in some cases the implementation of these measures [11,28].”
Survey of computational intelligence as basis to big flood management: challenges, research directions and future work (2018, methodology): “BNs have been applied in assessment of economic flood and debris damage (Merz, Kreibich, Schwarze, & Thieken, 2010).”
Decision-tree analysis of factors influencing rainfall-related building structure and content damage (2014, methodology): “0026) 1 Average claim size (acs) Total damage per day per district divided by number of claims per day per district (euros) 43–80 520 (1024) 12–28 282 (674) 1 Rainfall-related variables Maximum rainfall intensity (rmax) Maximum intensity of rainfall event at the buildingweighted centroid of a distri”
Regional disaster impact analysis: comparing Input-Output and Computable General Equilibrium models (2015, neutral): “2Please consult Merz et al. (2010) and Jongman et al. (2012) for a complete explanation of the use of depth–damage curves for disaster risk assessments.”
Perception and Communication of Flood Risks: A Systematic Review of Empirical Research (2013, background): “Zhai GF, Sato T, Fukuzono T, Ikeda S, Yoshida K. Willingness to pay for flood risk reduction and its determinants in Japan.”
The safe development paradox: An agent-based model for flood risk under climate change in the European Union (2020, methodology): “The latter variable describes the relation between inundation depth and damage to the value of exposure (de Moel et al., 2015; Merz et al., 2010; Ward et al., 2013).”