Document Type : Research Paper
Authors
1 Associate Professor, Faculty of Agriculture, Isfahan University of Technology, Iran
2 MSc Student, Faculty of Agriculture, Tarbiat Modares University, Iran
3 MSc Student, Faculty of Agriculture, Isfahan University of Technology, Iran
Abstract
There are two parametric and nonparametric approaches for frequency analysis of hydrological data. Current methods of frequency analysis are based on the parametric methods. Moments, maximum likelihood and probability weighted moments are from various parametric methods for frequency analysis. In this research, maximum likelihood and L-moment methods are used for precipitation frequency analysis. L-moment is a new method for frequency analysis and one of the specific kinds of probability weighted moments. The results of frequency analysis with L-moment are compared with maximum likelihood method and kernel functions of nonparametric methods of normal, log-normal, rectangular and triangular kernel function. In this research, monthly and annual precipitations are fitted to thirteen distribution functions such as Logistic, Generalized Extreme Value and etc. with estimation of L-moment and maximum likelihood methods. The results showed that L-moment parametric method is best fitted to monthly and annual data due to mean relative deviation and mean square relative deviation goodness of fit tests compared to maximum likelihood parametric method. The L-moment parametric method is also best fitted to Boushehr, Jask and Mashhad annual data due to mean relative deviation and mean square relative deviation goodness of fit tests compared to kernel nonparametric methods with rectangular, triangular and normal functions. Therefore, L-moment method is a suitable method for frequency analysis of other hydrological parameters such as flood and drought for planning of water resource management and hydrological analysis.
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