Flood damage curves: new insights from the 2010 flood in Veneto, Italy

Abstract

Flood damage modelling is becoming an essential component in flood risk management. However damage assessments are affected by large uncertainty, mainly related to the use of depth–damage functions. In some countries, where no site‐specific curves are available, a transfer of damage models developed from other areas is required, adding extra uncertainty in the modelling process. This paper discusses the transferability in space of damage curves from literature, with a focus on ‘function uncertainty’, pointing out, especially for mesoscale ones, the lack of detailed information in terms of flood and/or building characteristics that can allow to identify the conditions of applicability of the models. New site‐specific depth–damage functions are then developed for the residential sector, at meso‐ and microscale, based on damage data from the 2010 flood in Veneto, Italy. The application of the new curves reveals a better performance of the mesoscale model compared with the more detailed microscale one, probably due to the small extent of the inundated area.

Quantification of flood risk mitigation benefits: A building-scale damage assessment through the RASOR platform

“…The methodology adopted by Arrighi et al (2016a) had also a good performance in estimating the damages of the Veneto flood (northern Italy) when compared with observed losses (Scorzini and Frank, 2015). (Olsen et al, 2015) f with the advantage of having just one parameter to be calibrated,…”

Improving accuracy and quantifying uncertainty in flood loss estimations through the use of multi-model ensembles

“…These correspond to actual restoration costs that were collected and verified within the scope of the loss compensation process by the State. Further details can be found in Scorzini and Frank (2015). 10…”

“…similar type of asset, no spatial transferability required, validated with local evidence) would be available and unambiguously identifiable, but unfortunately, this is far from the case. The lack of an established procedure to select suitable flood loss models from the many available in the literature means that model selection is often done rather arbitrarily (Scorzini and Frank, 2015), which can negatively impact the quality of flood loss estimations and lead to suboptimal investment decisions based on model outcomes (Wagenaar et al, 2016). 25 A critical issue in flood loss modelling is uncertainty (Merz et al, 2004), which is usually high and can significantly contribute to overall uncertainty in flood risk analyses (de Moel and Aerts, 2011).…”

On the Influence of Input Data Quality to Flood Damage Estimation: The Performance of the INSYDE Model

“…The analysis is performed for the flood event, with an estimated return period of about 50 years, that occurred in 2010 in the municipality of Caldogno, northern Italy [10]. For this case study, the following detailed micro-scale data are available for about 300 damaged buildings:…”