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

Molinari, Daniela; Scorzini, Anna Rita; Arrighi, Chiara; Carisi, Francesca; Castelli, Fabio; Domeneghetti, Alessio; Gallazzi, Alice; Galliani, Marta; Grelot, Frédéric; Kellermann, Patric; Kreibich, Heidi; Mohor, Guilherme S.; Mosimann, Markus; Natho, Stephanie; Richert, Claire; Schroeter, Kai; Thieken, Annegret H.; Zischg, Andreas Paul; Ballio, Francesco (2020). Are flood damage models converging to “reality”? Lessons learnt from a blind test. Natural Hazards and Earth System Sciences, 20(11), pp. 2997-3017. Copernicus Publications 10.5194/nhess-20-2997-2020

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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.

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