@article {bnh-3795,
	title = {Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures},
	journal = {Natural Hazards and Earth Systems Sciences},
	volume = {17},
	year = {2017},
	month = {07/2017},
	pages = {1047-1059},
	chapter = {1047},
	abstract = {<p><span>The damage triggered by different flood events costs the Italian economy millions of euros each year. This cost is likely to increase in the future due to climate variability and economic development. In order to avoid or reduce such significant financial losses, risk management requires tools which can provide a reliable estimate of potential flood impacts across the country. Flood loss functions are an internationally accepted method for estimating physical flood damage in urban areas. In this study, we derived a new flood loss function for Italian residential structures (FLF-IT), on the basis of empirical damage data collected from a recent flood event in the region of Emilia-Romagna. The function was developed based on a new Australian approach (FLFA), which represents the confidence limits that exist around the parameterized functional depth{\textendash}damage relationship. After model calibration, the performance of the model was validated for the prediction of loss ratios and absolute damage values. It was also contrasted with an uncalibrated relative model with frequent usage in Europe. In this regard, a three-fold cross-validation procedure was carried out over the empirical sample to measure the range of uncertainty from the actual damage data. The predictive capability has also been studied for some sub-classes of water depth. The validation procedure shows that the newly derived function performs well (no bias and only 10 \% mean absolute error), especially when the water depth is high. Results of these validation tests illustrate the importance of model calibration. The advantages of the FLF-IT model over other Italian models include calibration with empirical data, consideration of the epistemic uncertainty of data, and the ability to change parameters based on building practices across Italy.</span></p>},
	doi = {https://doi.org/10.5194/nhess-17-1047-2017},
	url = {http://www.nat-hazards-earth-syst-sci.net/17/1047/2017/},
	author = {Roozbeh Hasanzadeh Nafari and Mattia Amadio and Tuan Ngo and Jaroslav Mysiak}
}
