Assessing flood risk for a rural detention area

Förster, Saskia; Kuhlmann, B. von; Lindenschmidt, K.-E.; Bronstert, Axel

doi:10.5194/nhess-8-311-2008

Cited by 102 publications

(109 citation statements)

References 18 publications

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“…1). Inundation duration is an important variable for estimating flood damage to agricultural crops (Förster et al, 2008;Tapia-Silva et al, 2011), but its importance for building damage may have been underestimated so far. Compared to former studies using this data set, such as Thieken et al (2005), this study shows that tree-based models are very effective in identifying the important damage influencing variables and their interactions.…”

Section: Discussionmentioning

confidence: 99%

Multi-variate flood damage assessment: a tree-based data-mining approach

Merz

Kreibich

Lall

2013

Nat. Hazards Earth Syst. Sci.

225

288

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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 damageinfluencing 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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Section: Discussionmentioning

confidence: 99%

Multi-variate flood damage assessment: a tree-based data-mining approach

Merz

Kreibich

Lall

2013

Nat. Hazards Earth Syst. Sci.

225

288

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“…Further, flood impact varies between sectors. For example, flood damage to residential buildings is strongly dependent on the water depth of a flood, whereas for damage to agricultural crops the time of flooding and the duration of the flood are decisive (Förster et al, 2008). A pragmatic reason for using economic sectors as classification criterion is that economic data which are needed for estimating the value of elements at risks are usually aggregated according to economic sectors.…”

Section: Commonly Adopted Classification Approachesmentioning

confidence: 99%

“…Table 3. Examples of damage influencing factors considered in different flood damage assessments (adapted/extended from Gissing and Blong, 2004;Kelman and Spence, 2004;Merz, 2006;Förster et al, 2008).…”

Section: Damage Functionsmentioning

confidence: 99%

Review article "Assessment of economic flood damage"

Merz

Kreibich

Schwarze

et al. 2010

Nat. Hazards Earth Syst. Sci.

1,104

1,095

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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 floodCorrespondence to: B. Merz (bmerz@gfz-potsdam.de) damage assessment could trigger subsequent methodological improvements in other natural hazard areas with comparable time-space properties.

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“…Consequently the main expected damages were anticipated to be on the agricultural sector 343 and were calculated based on a formula developed by Forster et al, (2008 …”

Section: Flood Damage Evaluation 336mentioning

confidence: 99%