Estimation of design flood using EWT and ENE metrics and uncertainty analysis under non-stationary conditions

Abstract

Concepts of Expected Waiting Time (EWT) and Expected Number of Exceedances (ENE) have been presented in much literature for estimating the Design Flood (DF) under non-stationary conditions. The parameters of the EWT and ENE are generally no less than four, which inevitably leads to the uncertainty of the DF estimation. In this paper, the Bayesian method is proposed to analyze the impact of parameter estimation uncertainty on the EWT- and ENE-based estimation of the DF and Corresponding Design Reliability (CDR). In addition, a comparison analysis between the EWT and ENE is conducted in terms of the DF and CDR with or without a consideration being given to the impact of parameter uncertainty. In the case of giving no consideration to the impact of parameter uncertainty, the experiment results indicate that the EWT-based estimations are less than that of ENE in terms of DF and CDR in the case of a decreasing trend. While in the case of an increasing trend, the EWT-based estimations are bigger than that of ENE. In the case of considering the impact of parameter uncertainty, results in the case study show that the distribution of the EWT-based estimations of DF and CDR are left shifted compared to that of the ENE. Overall, the EWT-based estimations are significantly different from that of ENE in terms of DF and CDR. Therefore, it is necessary and open for further discussions about which metric will be optimal between the EWT and ENE for estimating the DF under non-stationarity.