Modeling Annual Extreme Precipitation in upper Northern Region of Thailand
Panpharisa Khongthip* Manad Khamkong and Putipong Bookamana
Department of Statistics, Faculty of Science, Chiangmai University.
*Corresponding author. E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
The objective of this study is to find the model of extreme rainfall data in upper northern region of Thailand by using the generalized extreme value distribution (GEV) and estimate return level for various return periods. This is such a guidance that will help when making decisions to prevent or reduce the severity of flood in upper northern region of Thailand to expand to the central of Thailand. The methods used is to analyze and determine for the appropriate model for the annual maximum of monthly rainfall data for the year 1957 to 2009 from twenty-six stations in the upper north of Thailand which were obtained from the hydrology and water management centre for the upper north of Thailand. We provided an R program that is able to directly model a data for each station by using the GEV distribution with stationary, the GEV distribution in which the location parameter ? changes depending on linear trend and the GEV distribution in which the location parameter ? changes depending on quadratic trend and also estimate the return levels for various return periods. The study found that only the 17th station at Chiengkong district of Chiengrai province is GEV distribution in which the location parameter ? changes depending on linear trend and only two stations are GEV distribution in which the location parameter ? changes depending on quadratic trend, that is, the 14th station at Lee district of Lumpoon province and the 20th station at Muang district of Chiengrai province, respectively, and the rest are GEV distributions with stationary. Since the 23rd station at Masai district of Chiengrai has a highest return level for various return periods, so it should be the first consideration station in preventing or reducing the severity of floods. By the way, the 13rd station at Matha district of Lumpoon province which has a smallest return level for various return periods, should be the last consideration.
Keywords : generalized extreme value, model of extreme rainfall, return period, return level
