摘要：Flood loss models are one important source of uncertainty in flood risk assessments. Many countries experience sparseness or absence of comprehensive high-qualityflood loss data, which is often rooted in a lack of protocolsand reference procedures for compiling loss datasets afterflood events. Such data are an important reference for developing and validating flood loss models. We consider theSecchia River flood event of January 2014, when a suddenlevee 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 householdsincluding building footprints and structures and damages tobuildings 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 tacklethe problem of flood damage estimation in Emilia-Romagna(Italy) by identifying empirical uni- and multivariable lossmodels for residential buildings and contents. The accuracyof the proposed models is compared with that of several flooddamage models reported in the literature, providing additional insights into the transferability of the models amongdifferent contexts. Our results show that (1) even simple univariable damage models based on local data are significantlymore accurate than literature models derived for differentcontexts; (2) multivariable models that consider several explanatory variables outperform univariable models, whichuse only water depth. However, multivariable models canonly be effectively developed and applied if sufficient anddetailed information is available.
