How useful are complex flood damage models?

Schröter, Kai; Kreibich, Heidi; Vogel, Kristin; Riggelsen, Carsten; Scherbaum, Frank

doi:10.1002/2013wr014396

Cited by 155 publications

(243 citation statements)

References 46 publications

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“…[16,17,19] Before the results of the second approach will be described in more detail, it had to be clarified whether the split sampled model FLEMO2013split was even able to calculate losses of the 2013 flood and hence if the subsequent applied FLEMO2013 model was generally reliable. The results of the model performance are also summarized in Table 6 (centre).…”

Section: Comparison Of the Modelled And Reported Building Flood Lossesmentioning

confidence: 99%

“…in [8,[10][11][12][13][14][15][16]. In this context, studies of [16][17][18][19] confirm that multifactorial models can estimate flood losses more reliably than traditional depth-damage functions.…”

Section: Introductionmentioning

confidence: 99%

“…It is furthermore usually assumed that the relation between damage influencing parameters and losses are truly identical in all regions [8,12]. There are only few studies dealing with the assessment of flood loss model transferability (e.g., [9,[15][16]38]) hinting that the underlying assumptions of model transferability might not be valid. For instance, [16] revealed, 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.…”

Section: Introductionmentioning

confidence: 99%

“…There are only few studies dealing with the assessment of flood loss model transferability (e.g., [9,[15][16]38]) hinting that the underlying assumptions of model transferability might not be valid. For instance, [16] revealed, 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. [9] clearly demonstrated that loss models are better transferable if the underlying empirical data are taken from region similar or near to the study area.…”

Section: Introductionmentioning

confidence: 99%

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Assessment of flood loss model transferability considering changes in precaution of flood-affected residents in Germany

et al. 2016

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Abstract. Common models that are used for flood loss assessments today rarely include multiple loss influencing factors, e.g. private precautionary measures, which is increasingly gaining attention in the course of the changes towards an integrated flood risk management. Furthermore, these models are often transferred to other flood events or regions without knowing to what extent this results in reliable estimates. Since data on explanatory variables and losses are often missing, model validation is scarcely performed. The aim of this study was therefore to investigate whether the multifactorial flood loss model FLEMO can be transferred in time and space, using the examples of the August 2002 and May/June 2013 flood events in Germany, with particular consideration of changes in property-level mitigation measures and loss reduction effects for residential buildings. The study revealed that the spatio-temporal transferability of flood loss models remains highly uncertain, since the models could only partially reproduce changes in property-level mitigation measures. This indicates that flood loss influencing processes and factors are still not yet sufficiently understood and represented in models due to complex interrelations and different flood and site specific characteristics. More research on changes in loss explanatory parameters and standardised data collection is needed to enhance the understanding of damage processes and to improve flood loss model validation.

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Section: Comparison Of the Modelled And Reported Building Flood Lossesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessment of flood loss model transferability considering changes in precaution of flood-affected residents in Germany

et al. 2016

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“…Flood management is multifaceted, affected by the interplay of several climatologic, hydrologic, socioeconomic and environmental factors, involving various stakeholders, competing alternatives and different tradeoffs [1,2]. While the focus of conventional flood management was more on economy and society, sustainable flood management (SFM) intends to incorporate the economic, social and environmental risk of flooding in concert.…”

Section: Introductionmentioning

confidence: 99%

Sustainability-Based Flood Hazard Mapping of the Swannanoa River Watershed

2017

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An integrated framework is presented for sustainability-based flood hazard mapping of the Swannanoa River watershed in the state of North Carolina, U.S. The framework uses a hydrologic model for rainfall-runoff transformation, a two-dimensional unsteady hydraulic model flood simulation and a GIS-based multi-criteria decision-making technique for flood hazard mapping. Economic, social, and environmental flood hazards are taken into account. The importance of each hazard is quantified through a survey to the experts. Utilizing the proposed framework, sustainability-based flood hazard mapping is performed for the 100-year design event. As a result, the overall flood hazard is provided in each geographic location. The sensitivity of the overall hazard with respect to the weights of the three hazard components were also investigated. While the conventional flood management approach is to assess the environmental impacts of mitigation measures after a set of feasible options are selected, the presented framework incorporates the environmental impacts into the analysis concurrently with the economic and social influences. Thereby, it provides a more sustainable perspective of flood management and can greatly help the decision makers to make better-informed decisions by clearly understanding the impacts of flooding on economy, society and environment.

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Tree‐based flood damage modeling of companies: Damage processes and model performance

Sieg

Vogel

Merz

et al. 2017

Water Resources Research

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Reliable flood risk analyses, including the estimation of damage, are an important prerequisite for efficient risk management. However, not much is known about flood damage processes affecting companies. Thus, we conduct a flood damage assessment of companies in Germany with regard to two aspects. First, we identify relevant damage‐influencing variables. Second, we assess the prediction performance of the developed damage models with respect to the gain by using an increasing amount of training data and a sector‐specific evaluation of the data. Random forests are trained with data from two postevent surveys after flood events occurring in the years 2002 and 2013. For a sector‐specific consideration, the data set is split into four subsets corresponding to the manufacturing, commercial, financial, and service sectors. Further, separate models are derived for three different company assets: buildings, equipment, and goods and stock. Calculated variable importance values reveal different variable sets relevant for the damage estimation, indicating significant differences in the damage process for various company sectors and assets. With an increasing number of data used to build the models, prediction errors decrease. Yet the effect is rather small and seems to saturate for a data set size of several hundred observations. In contrast, the prediction improvement achieved by a sector‐specific consideration is more distinct, especially for damage to equipment and goods and stock. Consequently, sector‐specific data acquisition and a consideration of sector‐specific company characteristics in future flood damage assessments is expected to improve the model performance more than a mere increase in data.

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How useful are complex flood damage models?

Cited by 155 publications

References 46 publications

Assessment of flood loss model transferability considering changes in precaution of flood-affected residents in Germany

Assessment of flood loss model transferability considering changes in precaution of flood-affected residents in Germany

Sustainability-Based Flood Hazard Mapping of the Swannanoa River Watershed

Tree‐based flood damage modeling of companies: Damage processes and model performance

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