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Research Journal of Environmental Sciences
  Year: 2009 | Volume: 3 | Issue: 1 | Page No.: 62-70
DOI: 10.3923/rjes.2009.62.70
 
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A Comparison of Parametric and Nonparametric Density Functions for Estimating Annual Precipitation in Iran

P. Haghighat Jou, A.M. Akhoond-Ali, A. Behnia and R. Chinipardaz

Abstract:
The main purpose of this study is to compare parametric density functions with nonparametric Fourier series to estimate annual precipitation for five old rain gauge stations (Bushehr, Isfahan, Meshed, Tehran and Jask) in Iran. The parametric density functions include normal, two and three parameters log-normal, two parameter gamma, Pearson and log-Pearson type 3 and Gumbel extreme value type 1. The nonparametric approach is Fourier series method. Annual precipitation data from the mentioned stations were fitted to all density functions including Fourier series. Results showed that the Fourier series predict annual precipitation much better than other parametric methods. Thus, the Fourier series can be used as a better alternative approach for precipitation frequency analysis.
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How to cite this article:

P. Haghighat Jou, A.M. Akhoond-Ali, A. Behnia and R. Chinipardaz, 2009. A Comparison of Parametric and Nonparametric Density Functions for Estimating Annual Precipitation in Iran. Research Journal of Environmental Sciences, 3: 62-70.

DOI: 10.3923/rjes.2009.62.70

URL: https://scialert.net/abstract/?doi=rjes.2009.62.70

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