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Extreme Rainfall Analysis using L-moments Method | Seansak | งดใช้ระบบ 3-31 กค 66 Burapha Science Journal

Extreme Rainfall Analysis using L-moments Method

Kritiya Seansak, Arun Keawman, Atcharawan Shantapot, Piyapatr Busababodhin

Abstract


The aim of this study is to analyze the Generalized Extreme Value distribution (GEVD), Pareto type III distribution (3PD) and Generalized Logistic Distribution (GLO) with L-moment estimates on the extreme annual rainfall data at 25 weather stations in Northeast of Thailand.  The rainfall data gathered from 1984 to 2014.  The criterion for selected best model is relative root-mean-square error or RRMSE. The results indicate that best model for these regions are GLO, GEVD and 3PD with respect to 56%, 36% and 8%, respectively.  For the return level for 10, 25, 50 and 100 years return periods indicate that Tha-Tum weather station and Surin agromet weather station have highest return level than other station. Consequently, to solve and prevent the extreme rainfall problem, these stations should be the first considered.

 

Keywords :  Generalized Extreme Value Distribution, Pareto type III Distribution, Generalized Logistic Distribution,

                     L-moments, extreme annual rainfall


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