Regional and Temporal Transferability of Multivariable Flood Damage Models

Abstract

Reliable flood damage assessment is important for decision-making in flood risk management.Flood damage assessment is often done with damage curves based only on water depth. These depthdamage curves are usually developed based on data from a specific location and specific flood conditions. Such depth-damage curves tend to be applied outside the scope of their validity. Validation studies show that in such cases depth-damage curve are not very reliable, probably due to excluded influencing variables. The expectation is that the inclusion of more variables in a damage function will improve its transferability. We compare multi-variable models based on Bayesian Networks and Random Forests developed on the basis of flood damage data sets from Germany and The Netherlands. The performance of the models is tested on a validation sub-set of both countries' data. The models are also updated with data from the other country and then tested again. The results show that the German models (BN/RF-FLEMOps) perform better in the Netherlands than the Dutch models (BN/RF-Meuse) perform in Germany. This is probably because the FLEMOps models are based on more heterogeneous data than the Meuse models. The FLEMOps models, therefore, are better able to capture damages processes from other events and in other locations. Model performance improves via updating the models with data from the location to which the model is transferred to. The results show that there is high potential to develop improved damage models, by training multi-variable models with heterogeneous data, for example from multiple flood events and locations.

Quantifying Flood Vulnerability Reduction via Private Precaution

“…The ATE estimates from FLEMOps+r and BN‐FLEMOps are 12,185 EUR and 14,687 EUR, respectively (Table ), which fall within the range of the empirical estimates (11,238–15,053 EUR). Both models have been developed through a combination of expert knowledge and analysis of empirical data and explicitly take into consideration the direct influence of private precaution (Elmer et al, ; Wagenaar et al, ). The rule‐based model FLEMOps+r considers precaution in the second model step together with contamination and recurrence interval.…”

“…The loss estimate is then determined using the mean as the prediction of the ensemble of trees. Also, Bayesian networks are used in flood loss estimation (Schröter et al, 2014;Vogel et al, 2014;Wagenaar et al, 2018). Bayesian networks are Directed Acyclic Graphs (DAG) constructed from assertion of dependencies and principle of conditional independence (Heckerman, 1998).…”

A Consistent Approach for Probabilistic Residential Flood Loss Modeling in Europe

“…The BN‐FLEMOps (see Figure ) has been developed for flood loss estimation on the level of individual residential buildings, that is, microscale applications, and was first presented by Wagenaar et al (). It estimates relative building loss of residential buildings, that is, the relation between the absolute building loss and the replacement value of the building.…”

“…Merz et al (), Kreibich et al () and Schröter et al () demonstrated that tree‐based model‐ensembles, such as Bagging Decision Trees or Random Forests, are suitable for flood loss modeling on the microscale (e.g., individual buildings) and the mesoscale (e.g., land use units), as they are able to capture nonlinear and nonmonotonous dependencies between predictor and response variables and they take interactions between the predictors into account. Bayesian networks were used to develop probabilistic, multivariable flood loss models (Sairam et al, ; Schröter et al, ; Vogel et al, ; Wagenaar et al, ) for estimating flood loss of residential buildings on the microscale. Ensemble and probabilistic approaches inherently provide quantitative information on uncertainty associated with the variability of input data and model structure.…”

“…The objective of this study is to develop a consistent approach for probabilistic flood loss modeling for residential buildings in Europe, which is based on the upscaling of the microscale multivariable flood loss model B ayesian N etwork ‐ F lood L oss E stimation MO del for the p rivate s ector (BN‐FLEMOps) presented in Wagenaar et al (). That is, the structure of the microscale BN‐FLEMOps model is preserved, and European‐wide proxy data are acquired and tested for the mesoscale application of the model.…”