Abstract

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 52 km2 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.

Highlights

  • According to analyses of the Centre for Research on the Epidemiology of Disasters (CRED), hydrological disasters are the most frequently recorded natural calamities occurring worldwide in the last 2 decades

  • The CRED findings about the increasing amount of economic loss starting from the second half of 20th century agree with the analyses carried out by the Intergovernmental Panel on Climate Change (IPCC), which highlighted that flood damages in the past 10 years were 10 times higher than in the period 1960–1970 (IPCC, 2001, 2014)

  • Our study focuses on a real inundation event that occurred in Italy in 2014 and was caused by a breach in the right embankment of the Secchia River during an intense, yet not extreme, flood event

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Summary

Introduction

According to analyses of the Centre for Research on the Epidemiology of Disasters (CRED), hydrological disasters (i.e., natural disasters caused by river and coastal floods, flash floods, rainstorms) are the most frequently recorded natural calamities occurring worldwide in the last 2 decades (see, e.g., Guha-Sapir and CRED, 2015). Some authors (see Merz et al, 2013; Chinh et al, 2016; Hasanzadeh Nafari et al, 2016, 2017; Kreibich et al, 2017; Spekkers et al, 2014) developed multiparameter damage models including more than one predictive variable, chosen among other hydraulic parameters (e.g., streamflow velocity, duration of the inundation), resistance performance, precautionary measures, and people’s awareness of and experience with floods (Meyer et al, 2013) These models were shown to outperform univariable loss models, under the condition that sufficiently large and detailed damage datasets are provided (Merz et al, 2013; Schröter et al, 2016). – Third, we investigate the relationship between damages to buildings and damages to contents, developing an empirical damage model for the latter

Study area and inundation event
Flood loss and hydrodynamic data
Damages to contents
Hydrodynamic characterization of the inundation event
Damage models
Rhine Atlas damage model
Models developed on Secchia dataset
Comparison of literature and empirical damage models
Validation of locally derived damage models
Modeling flood loss to contents
Conclusions

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