Miguel Laverde, Gerald Corzo-Perez, Dimitri Solomantine
Friday 3 july 2015
12:48 - 12:51h at Oceania Foyer (level 0)
Themes: (T) Flood risk management and adaptation, (ST) Flooding along in rivers and coasts, Poster pitches
Parallel session: Poster pitches: 15L. Flood Risk - Flooding
Decisions on flood risk are usually based over stationary environment conditions and deterministic approaches to represent flood hazard. The natural behaviour of the processes and the way to represent it, are highly uncertain. In recent years, probabilistic methods to represent this uncertainty has become popular to get a better understanding of the flow process chain recognizing the uncertainties of the physical process modelled. However, uncertainty analysis is not usually taken into account within flood risk assessment. In this paper, we explore the role of the uncertainty analysis into the flood risk management and the new challenges to be considered in a dynamic environment. In addition, a stochastic framework to assess the flood risk is presented in order to determinate the impact of aleatory and epistemic uncertainties into a robust flood damage chain. The flood model is a coupled probabilistic system integrated by distributed hydrological model and two dimensional hydrodynamic model. This methodology uses a Monte Carlo framework structured in two levels representing different sources of uncertainty (aleatory and epistemic uncertainty). In the first level, aleatory uncertainty is analysed due the increase of frequency and magnitude in the rainfall and changes in the behaviour of social distribution. The second level explores the epistemic uncertainty as a product of individual uncertainties in the hydrological and hydrodynamic model and its implication in the flood hazard. This analysis also explores uncertainties in extreme value statistics caused by the type of distribution function. We close this paper argue in favour of uncertainty analysis in flood risk assessment in order to improve the flood risk analysis and support better-informed decision making.