Flood frequency analysis based on Gaussian Copula

Abstract

Flood duration, volume, and peak flow are important considerations in flood risk analysis and management of hydraulic structures. The conventional flood frequency analysis assumed that the marginal distribution functions of flood parameters follow a certain pattern. However, such assumption is impractical because a flood event is multivariate and the flood parameter distributions can be different. These discrepancies were addressed using bivariate joint distributions and copula function which allow flood parameters having different marginal distributions to be analysed simultaneously. The analysis used hourly stream flow data for 45 years recorded at the Rantau Panjang gauging station on the Johor River in Malaysia. It was found that flood duration and volume are best fitted by the Generalized Extreme Value distribution while peakflow by the Generalized Pareto. Inference Function for Margins (IFM) method was applied to model the joint distributions of correlated flood variables for each pair and the results showed that all the calculated ? values were in acceptable range of Gaussian Copula. By horizontally cutting the joint cumulative distribution function, a set of contour lines were obtained for Gaussian Copula which represented the occurrence probabilities for the joint variables. Also the joint return period for pair of flood variables were calculated.