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All Journal Civil Engineering Journal
Nipaporn Chutiman
Department of Mathematics, Faculty of Science, Mahasarakham University, Maha Sarakham 41150,
Civil Engineering, Building, Construction & Architecture

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Journal : Civil Engineering Journal

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Daily Maximum Rainfall Forecast Affected by Tropical Cyclones using Grey Theory Nipaporn Chutiman; Monchaya Chiangpradit; Butsakorn Kong-ied; Piyapatr Busababodhin; Chatchai Chaiyasaen; Pannarat Guayjarernpanishk
Civil Engineering Journal Vol 8, No 8 (2022): August
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2022-08-08-02

Abstract

This research aims to develop a model for forecasting daily maximum rainfall caused by tropical cyclones over Northeastern Thailand during August and September 2022 and 2023. In the past, the ARIMA or ARIMAX method to forecast rainfall was used in research. It is a short-term rainfall prediction. In this research, the Grey Theory was applied as it is an approach that manages limited and discrete data for long-term forecasting. The Grey Theory has never been used to forecast rainfall that is affected by tropical cyclones in Northeastern Thailand. The Grey model GM(1,1) was analyzed with the highest daily cumulative rainfall data during the August and September tropical cyclones of the years 2018–2021, from the weather stations in Northeastern Thailand in 17 provinces. The results showed that in August 2022 and 2023, only Nong Bua Lamphu province had a highest daily rainfall forecast of over 100 mm, while the other provinces had values of less than 70 mm. For September 2022 and 2023, there were five provinces with the highest daily rainfall forecast of over 100 mm. The average of mean absolute percentage error (MAPE) of the maximum rainfall forecast model in August and September is approximately 20 percent; therefore, the model can be applied in real scenarios. Doi: 10.28991/CEJ-2022-08-08-02 Full Text: PDF
Climate Forecasting Models for Precise Management Using Extreme Value Theory Pannarat Guayjarernpanishk; Monchaya Chiangpradit; Butsakorn Kong-ied; Nipaporn Chutiman
Civil Engineering Journal Vol 9, No 7 (2023): July
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2023-09-07-014

Abstract

The objective of this research was to develop a mathematical and statistical model for long-term prediction. The Extreme Value Theory (EVT) was applied to analyze the appropriate distribution model by using the peak-over-threshold approach with Generalized Pareto Distribution (GPD) to predict daily extreme precipitation and extreme temperatures in eight provinces located in the upper northeastern region of Thailand. Generally, each province has only 1–2 meteorological stations, so spatial analysis cannot be performed comprehensively. Therefore, the reanalysis data were obtained from the NOAA Physical Sciences Laboratory. The precipitation data were used for spatial analysis at the level of 25 square kilometers, which comprises 71 grid points, whereas the temperature data were used for spatial analysis at the level of 50 square kilometers, which includes 19 grid points. According to the analysis results, GPD was appropriate for the goodness of fit test with Kolmogorov-Smirnov Statistics (KS Test) according to the estimation for the return level in the annual return periods of 2 years, 5 years, 10 years, 25 years, 50 years, and 100 years, indicating the areas with daily extreme precipitation and extreme temperatures. The analysis results would be useful for supplementing decision-making in planning to cope with risk areas as well as in effective planning for resources and prevention. Doi: 10.28991/CEJ-2023-09-07-014 Full Text: PDF
Co-Authors Butsakorn Kong-ied Chatchai Chaiyasaen Monchaya Chiangpradit Pannarat Guayjarernpanishk Piyapatr Busababodhin