Improving Accuracy of IDF Curves Using Long- and Short-Duration Separation and Multi-Objective Genetic Algorithm

Multi-objective genetic algorithm (MOGA) and cumulative distribution function (CDF) are used to improve the accuracy of IDF curve. Rainfall durations are divided into short- and long-duration using root mean squared error (RMSE) and relative root mean squared error (RRMSE) between rainfall quantiles by IDF curve and at-site frequency analysis. RMSE could be used for estimating parameters of relatively long-duration, and RRMSE for short-duration. The compromised solutions could be ahieved through MOGA with two multi-objective functions. The duration separating technique called C0MBI_1 is suggested and the comparison with the five different parameter estimation methods provides COMBI_1 is superior to the other methods.