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Rome''s monumental centre has often been inundated by Tiber River. In the last decades of the 19th century, river walls were erected to protect Rome from floods so that the last significant flood, which occurred in 1937, caused only marginal damages. Although the probability of inundation of the city seems to be now substantially reduced, the evaluation of the residual risk is still worthwhile. With this aim, rainfall, rainfall–runoff, river flood propagation and street flooding processes are simulated in detail to produce the inundation scenarios analysed by the Monte Carlo method. The study shows that severe floods, having a return period greater than 180 years, overtop both the left and right river banks and inundate the northern outskirts of Rome, while extreme events, with 1000 years return period, submerge large parts of the monumental centre of Rome. [Copyright &y& Elsevier]

Abstract: Rome is at risk from flooding when extreme events with a return period of about 200years occur. For this reason, an accurate real-time flood forecasting system may be a useful non-structural countermeasure. Two different approaches are considered to develop a real-time forecasting system capable of predicting hourly water levels at Ripetta stream gauging station in Rome. The first is an adaptive, conceptual model (TFF model), which consists of a rainfall-runoff model that simulates the contribution of 41 ungauged sub-basins (covering approximately 30% of the catchment area) of the Tiber River and a hydraulic model to route the flood through the hydrographic network. The rainfall-runoff model is calibrated online during each flood event at every time step via an adaptive procedure while the flood routing model parameters were calibrated offline and held constant during the forecast. The second approach used is a data-driven one through the application of an artificial neural network (TNN model). Feedforward networks trained with backpropagation and Bayesian regularization were developed using a continuous historical dataset. Both models were used to forecast the most recent significant floods that occurred in Rome (November 2005 and December 2008) with lead times of 12 and 18h. The results show good performance using both models when compared with observations for a series of absolute and relative performance measures as well as a visual inspection of the hydrographs. At present both models are suitable for real-time forecasting and the power of an integrated approach is still to be investigated. [Copyright &y& Elsevier]