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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 18, issue 7 | Copyright
Nat. Hazards Earth Syst. Sci., 18, 2057-2079, 2018
https://doi.org/10.5194/nhess-18-2057-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 27 Jul 2018

Research article | 27 Jul 2018

Development and assessment of uni- and multivariable flood loss models for Emilia-Romagna (Italy)

Francesca Carisi1, Kai Schröter2, Alessio Domeneghetti1, Heidi Kreibich2, and Attilio Castellarin1 Francesca Carisi et al.
  • 1University of Bologna, DICAM, Water Resources, Bologna, Italy
  • 2GFZ German Research Centre for Geosciences, Section 5.4 Hydrology, Potsdam, Germany

Abstract. Flood loss models are one important source of uncertainty in flood risk assessments. Many countries experience sparseness or absence of comprehensive high-quality flood loss data, which is often rooted in a lack of protocols and reference procedures for compiling loss datasets after flood events. Such data are an important reference for developing and validating flood loss models. We consider the Secchia River flood event of January 2014, when a sudden levee breach caused the inundation of nearly 52km2 in northern Italy. After this event local authorities collected a comprehensive flood loss dataset of affected private households including building footprints and structures and damages to buildings and contents. The dataset was enriched with further information compiled by us, including economic building values, maximum water depths, velocities and flood durations for each building. By analyzing this dataset we tackle the problem of flood damage estimation in Emilia-Romagna (Italy) by identifying empirical uni- and multivariable loss models for residential buildings and contents. The accuracy of the proposed models is compared with that of several flood damage models reported in the literature, providing additional insights into the transferability of the models among different contexts. Our results show that (1) even simple univariable damage models based on local data are significantly more accurate than literature models derived for different contexts; (2) multivariable models that consider several explanatory variables outperform univariable models, which use only water depth. However, multivariable models can only be effectively developed and applied if sufficient and detailed information is available.

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By analyzing a comprehensive loss dataset of affected private households after a recent river flood event in northern Italy, we tackle the problem of flood damage estimation in Emilia-Romagna (Italy). We develop empirical uni- and multivariable loss models for the residential sector. Outcomes highlight that the latter seem to outperform the former and, in addition, results show a higher accuracy of univariable models based on local data compared to literature ones derived for different contexts.
By analyzing a comprehensive loss dataset of affected private households after a recent river...
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