Development of Statistical Models for Maximum Daily Rainfall in Upper Northern Region of Thailand
The upper northern region of Thailand is the originated place of all the major tributaries of the Chao Phraya River in central Thailand. Hence, the extreme precipitation event occurred on many days continuously in upper northern part was directly found to be the cause of widespread flooding in sever...
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| Main Authors: | , |
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| Language: | English |
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Science Faculty of Chiang Mai University
2019
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| Subjects: | |
| Online Access: | http://it.science.cmu.ac.th/ejournal/dl.php?journal_id=6260 http://cmuir.cmu.ac.th/jspui/handle/6653943832/66178 |
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| Institution: | Chiang Mai University |
| Language: | English |
| Summary: | The upper northern region of Thailand is the originated place of all the major tributaries of the Chao Phraya River in central Thailand. Hence, the extreme precipitation event occurred on many days continuously in upper northern part was directly found to be the cause of widespread flooding in several areas especially in the central parts. This paper focuses on the statistical modeling development of the annual maxima of daily (AMR1) and 2-day (AMR2) rainfall data in upper north Thailand based on a generalized extreme value (GEV) distribution. AMR1 and AMR2 for the years from 1957 to 2012 in the rainy season were modelled for sixteen locations in the upper northern region. The study found that only the Pua Nan location was being a GEV model in which the location parameter changes depending on quadratic trend while the others were being stationary GEV models from AMR1. For AMR2 only the Ngao Lampang location was being a GEV model in which the location parameter changes depending on linear trend while the others were being stationary GEV. The 95% confidence interval estimations of daily rainfalls return level for various return periods of the Nan River and Yom River were higher than that of other locations. Information obtained from our study is very useful for agencies involved in water management in terms of strategic planning and also scarce rainfalls prevention related to public safety, among others. |
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