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

  • M. Julia Flores
  • Rosa F. RoperoEmail author
  • Rafael Rumí
Original Paper


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.


Flood risk assessment Dynamic Bayesian networks Object-oriented Bayesian networks Mediterranean watershed 



This study was supported by the Spanish Ministry of Economy and Competitiveness through Projects TIN2016-77902-C3-1-P and TIN2016-77902-C3-3-P, and by the Regional Government of Andalusia through project P12-TIC-2541.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Computing Systems Department, SIMD I3AUniversity of Castilla-La ManchaAlbaceteSpain
  2. 2.Informatics and Environmental Research Group, Department of Biology and GeologyUniversity of AlmeríaAlmeríaSpain
  3. 3.Department of MathematicsUniversity of AlmeríaAlmeríaSpain

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