Abstract
Flood frequency analysis (FFA) is needed for the design of water engineering and hydraulic structures. The choice of an appropriate frequency distribution is one of the most important issues in FFA. A key problem in FFA is that no single distribution has been accepted as a global standard. The common practice is to try some candidate distributions and select the one best fitting the data, based on a goodness of fit criterion. However, this practice entails much calculation. Sometimes generalized distributions, which can specialize into several simpler distributions, are fitted, for they may provide a better fit to data. Therefore, the generalized gamma (GG) distribution was employed for FFA in this study. The principle of maximum entropy (POME) was used to estimate GG parameters. Monte Carlo simulation was carried out to evaluate the performance of the GG distribution and to compare with widely used distributions. Finally, the T-year design flood was calculated using the GG and compared with that with other distributions. Results show that the GG distribution is either superior or comparable to other distributions.
Highlights
Flood frequency analysis (FFA) is needed for the design of water engineering and hydraulic structures
The popular techniques for parameter estimation include the methods of maximizing in accord with the principle of maximum entropy (POME), in which the distribution maximum likelihood (ML) [7], moments (MM) [10] and L-moments [11]
L-moment method (LM) [11,17], while the parameters of NM and Log-Pearson type 3 distribution (LP3) distributions were estimated values of Root mean square error (RMSE) and Akaike information criterion (AIC) were computed for each model using Equations (17) and (18) and listed in by MM [18,19]
Summary
Flood frequency analysis (FFA) is needed for the design of water engineering and hydraulic structures. The popular techniques for parameter estimation include the methods ofprovide maximum sufficient flexibility to fit a large variety of data sets. The second issues is to estimate the parameters associated with to derive more generalized distributions using different constraints [12]. The popular techniques for parameter estimation include the methods of maximizing in accord with the principle of maximum entropy (POME), in which the distribution maximum likelihood (ML) [7], moments (MM) [10] and L-moments [11]. [12]The indicated can beare used to derive more distributions different constraints theory that the entropy method was reasonable and efficient for parameter estimation. The objective of this study was to the propose an data entropy generalized gamma the distribution parameter are determined, given observed and abased set of constraints. The T-year design flood values were calculated and compared based on different FFA distributions
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