CFP last date
20 October 2026
Reseach Article

Rainfall Forecasting in Bangkok using ARIMA and ARIMAX Models: An Application to Flash Flood Risk

by Khin Muyar Kyaw, Pyae Phyo Kyaw, Si Thu Aung
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 143
Year of Publication: 2026
Authors: Khin Muyar Kyaw, Pyae Phyo Kyaw, Si Thu Aung
10.5120/ijca9038cdabb7ec

Khin Muyar Kyaw, Pyae Phyo Kyaw, Si Thu Aung . Rainfall Forecasting in Bangkok using ARIMA and ARIMAX Models: An Application to Flash Flood Risk. International Journal of Computer Applications. 187, 143 ( Sep 2026), 57-60. DOI=10.5120/ijca9038cdabb7ec

@article{ 10.5120/ijca9038cdabb7ec,
author = { Khin Muyar Kyaw, Pyae Phyo Kyaw, Si Thu Aung },
title = { Rainfall Forecasting in Bangkok using ARIMA and ARIMAX Models: An Application to Flash Flood Risk },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2026 },
volume = { 187 },
number = { 143 },
month = { Sep },
year = { 2026 },
issn = { 0975-8887 },
pages = { 57-60 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number143/rainfall-forecasting-in-bangkok-using-arima-and-arimax-models-an-application-to-flash-flood-risk/ },
doi = { 10.5120/ijca9038cdabb7ec },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2026-09-19T02:57:35.821957+05:30
%A Khin Muyar Kyaw
%A Pyae Phyo Kyaw
%A Si Thu Aung
%T Rainfall Forecasting in Bangkok using ARIMA and ARIMAX Models: An Application to Flash Flood Risk
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 143
%P 57-60
%D 2026
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Flash floods are among the natural disasters that cause the loss of human lives and property, damage infrastructure, and create economic and social hardships. Therefore, predicting flash floods remains an unsolved problem and requires substantial computational power and resources. Forecasting rainfall can help predict flash floods and serve as an initial value for hydrological model simulations of flash floods. In this study, the usability of both ARIMA and ARIMAX models is evaluated by predicting a year-long rainfall dataset. Both graphical point-of-view and MAE and RMSE calculations are provided, showing that both models performed well in predicting Bangkok rainfall data.

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Index Terms

Computer Science
Information Sciences

Keywords

Precipitation Forecasting ARIMA ARIMAX Residual analysis