Probabilistic characterization of flood hazard using bivariate analysis based on copulas

Abstract

This study presents an innovative approach to obtain flood hazard maps where hydrological input (synthetic flood design event) to a 2D hydraulic model has been defined by generating flood peak discharges and volumes from a bivariate statistical analysis, through the use of copulas. Synthetic hydrographs were generated by means two different approaches: an indirect one, where rainfall were generated by a stochastic bivariate rainfall generator to be entered a distributed conceptual rainfall-runoff model that consisted of a soil moisture routine and a flow routing routine; and a direct one, where stochastic generation of flood peaks and flow volumes have been obtained via copulas, which describe and model the correlation between these two variables independently of the marginal laws involved fitted on flood recorded data. Finally, to highlight the advantages of the presented approach, flood risk maps derived by bivariate models are compared to maps from conventional univariate analysis. The procedure is applied to a real case study located in the southern part of Sicily, Italy, where flood hazard maps have been obtained and compared.