A coupled system based on Differential Evolution for the determination of Rainfall intensity equations

Abstract

ABSTRACT Rainfall intensity equations are fundamental in hydrological studies of road design, which require a project rainfall definition to estimate the project flow and the subsequent design of the hydraulic structure. This paper develops an integrated framework for rainfall intensity equations analyses from global optimization via Differential Evolution. The code was specially developed to facilitate the Gumbel model adjustment in the frequency analysis of annual series, as well as the intensity-duration-frequency model fit, without prior knowledge about the parameters of both models. The developed system was evaluated by using Markov chain Monte Carlo simulation, that search efficiently the model parameter space in pursuit of posterior samples and the posterior prediction uncertainty for both models. The results indicate that simulations are shown to be in good agreement with the measured flow and precipitation data. The optimal parameters obtained with the developed framework agreed with the maximum a-posteriori value of the Monte Carlo simulations. The paper illustrates explicitly the benefits of the method using real-world precipitation data collected for a hydrologic study of a highway design.

Keywords

• Precipitation
• Rainfall intensity equations
• Global optimization
• Differential Evolution
• Highway design