Assessment of flood risk in Mediterranean catchments: an approach based on Bayesian networks

M. Julia Flores, Rosa F Ropero, Rafael Rumi

Abstract:

National and international technical reports have demonstrated the increase of extreme event occurrences which becomes
more dangerous in coastal areas due to their higher population density. In Spain, flood and storm events are the main
reasons for compensation according to the National Insurance Consortium. The aim of this paper is to model the risk of
flooding in a Mediterranean catchment in the South of Spain. A hybrid dynamic object-oriented Bayesian network (OOBN)
was learnt based on mixture of truncated exponential models, a scenario of rainfall event was included, and the final model
was validated. OOBN structure allows the catchment to be divided into five different units and models each of them
independently. It transforms a complex problem into a simple and easily interpretable model. Results show that the model
is able to accurately watch the evolution of river level, by predicting its increase and the time the river needs to recover
normality, which can be defined as the river resilience.