Adaptability and transferability of flood loss functions in residential areas

Abstract

Abstract. Flood loss modeling is an important component within flood risk assessments. Traditionally, stage-damage functions are used for the estimation of direct monetary damage to buildings. Although it is known that such functions are governed by large uncertainties, they are commonly applied – even in different geographical regions – without further validation, mainly due to the lack of data. Until now, little research has been done to investigate the applicability and transferability of such damage models to other regions. In this study, the last severe flood event in the Austrian Lech Valley in 2005 was simulated to test the performance of various damage functions for the residential sector. In addition to common stage-damage curves, new functions were derived from empirical flood loss data collected in the aftermath of recent flood events in the neighboring Germany. Furthermore, a multi-parameter flood loss model for the residential sector was adapted to the study area and also evaluated by official damage data. The analysis reveals that flood loss functions derived from related and homogenous regions perform considerably better than those from more heterogeneous datasets. To illustrate the effect of model choice on the resulting uncertainty of damage estimates, the current flood risk for residential areas was assessed. In case of extreme events like the 300 yr flood, for example, the range of losses to residential buildings between the highest and the lowest estimates amounts to a factor of 18, in contrast to properly validated models with a factor of 2.3. Even if the risk analysis is only performed for residential areas, more attention should be paid to flood loss assessments in future. To increase the reliability of damage modeling, more loss data for model development and validation are needed.

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

“…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. Yet it is concluded that a temporal and spatial transferability of models is necessarily linked to an adjustment of the input data regarding the vulnerability of elements at risk and study site characteristics.…”

“…As a measure for acceptable loss estimations and rating tool for the overall model accuracy, a bootstrap procedure with 10,000 random samples with replacement was applied to all reported building loss data. In accordance with [38] and [9], the 2.5th and 97.5th percentile of the total, mean and median building loss were hence calculated to obtain a 95 % confidence interval of the reported building loss records. Eventually, all modelled building losses that fell within this bootstrap interval were assumed to be acceptable.…”

“…Yet, due to limited or even missing loss data, validation is only rarely performed [8]. Examples of a (successful) model validation are the investigations of [18-19, 38, 47-48], who all positively validated the flood loss model FLEMO (either for residential buildings, the commercial sector or further developments of that model) as well as [9,15].…”

“…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.…”

“…They are used for loss predictions of future flood events, cost-benefit analyses regarding flood protection plans, vulnerability assessments, land-use planning, risk analyses and mapping as well as calculations of reconstruction aid and settling claims by the federal government and (re-)insurance companies [7][8]. These models are often based on susceptibility functions, which predominantly relate the hazard parameter water depth to corresponding direct economic losses of different elements at risk, for example, residential buildings [8][9][10]. These depthdamage functions have been accepted internationally as a standard approach for estimating flood losses for a long time, but recent studies confirm that flood damage to residential buildings is controlled by further factors that either increase (impact parameters, e.g.…”