Are flood damage models converging to “reality”? Lessons learnt from a blind test

Abstract

Abstract. Effective flood risk management requires a realistic estimation of flood losses. However, available flood damage estimates are still characterized by significant levels of uncertainty, questioning the capacity of flood damage models to depict real damages. With a joint effort of eight international research groups, the objective of this study was to compare, in a blind-validation test, the performances of different models for the assessment of the direct flood damage to the residential sector at the building level (i.e. microscale). The test consisted of a common flood case study characterized by high availability of hazard and building data but with undisclosed information on observed losses in the implementation stage of the models. The nine selected models were chosen in order to guarantee a good mastery of the models by the research teams, variety of the modelling approaches, and heterogeneity of the original calibration context in relation to both hazard and vulnerability features. By avoiding possible biases in model implementation, this blind comparison provided more objective insights on the transferability of the models and on the reliability of their estimations, especially regarding the potentials of local and multivariable models. From another perspective, the exercise allowed us to increase awareness of strengths and limits of flood damage modelling, which are summarized in the paper in the form of take-home messages from a modeller's perspective.

Residential flood loss estimated from Bayesian multilevel models

“…Additionally, flood preparedness evolved over time, documented, for example, by Kienzler et al (2015) and Thieken et al (2016) for Germany. Economic situations may also change the relative value of exposed assets and its recover or repair costs (Penning-Rowsell, 2005;Kron, 2005). Such changes are challenging to include in loss models, however.…”

On the implementation of the French methodology for flood damage assessment to economic activities.

“…Regarding the transferability of the damage model, literature shows that the performance of foreign models can be affected by high levels of error, with overestimation from two to eleven times (Molinari et al, 2020, Scorzini andFrank, 2017). So, for the Italian case study, the overestimation of 3.15 times is not unacceptable.…”

Cost–benefit analysis of flood mitigation measures: a case study employing high-performance hydraulic and damage modelling

“…Damage estimation was limited to direct damage to residential buildings and agriculture in order to implement models specifically calibrated in the context under investigation and to avoid the spatial transfer of foreign models. This could have compromised the reliability of damage estimation (Cammerer et al 2013;Molinari et al 2020), above all in absence of data for validation. Exhaustiveness of damage assessment is also limited here by the disregard of systemic and indirect damages like loss of property value because of the flood, damages due to business disruption, ripple effects and others.…”

“…The latter is a synthetic micro-scale multi-variable model that presents the advantage of an explicit formulation and a user-friendly implementation, still implicitly maintaining the dependence of the original model from a large number of hazard ( 6) and vulnerability ( 18) parameters. The INSYDE model has been validated for the 2002 flood in Lodi by Molinari et al (2020). Galliani et al (2020) demonstrated that the use of simple-INSYDE leads to comparable results and does not decrease much the accuracy of the damage forecast compared to the full version of the model.…”