Identifying low impact development strategies for flood mitigation using a fuzzy-probabilistic approach

Low impact development (LID) includes strategies and practices that are designed to control surface runoff at its sources in a sustainable way. The performance of these strategies has been frequently addressed through curve number approach. This approach however subjects to a great deal of uncertainties owing to uncertain nature of curve numbers and temporal/spatial variability of flood events. This paper represents a novel methodology to deal with both inherent flood uncertainties and epistemic uncertainties identifying optimal LID strategies for flood mitigation. The proposed methodology integrates a great variety of mathematical tools including copula functions, MCS method, hydrological and hydraulic models, NSGA-II algorithm as well as ANN and fuzzy set theory. The obtained results from a case study clearly demonstrate that the proposed methodology not only presents cost-effective measures, but also can simultaneously handle both inherent and epistemic uncertainties in flood risk management.