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Temporal flood incidence forecasting for Segamat River (Malaysia) using autoregressive integrated moving average modelling


Citation

Razak, Nurhafiza and Aris, Ahamd Zaharin and Ramli, Mohammad Firuz and Looi, Ley Juen and Juahir, Hafizan (2018) Temporal flood incidence forecasting for Segamat River (Malaysia) using autoregressive integrated moving average modelling. Journal of Flood Risk Management, 11. 794 - 804. ISSN ESSN: 1753-318X

Abstract

Accurate and efficient flood forecasting system can improve the emergency rescue plans and help avoid the loss of lives. This study aims to identify the trends in rainfall and streamflow in Segamat River (Malaysia) by using Mann–Kendall trend analysis, to develop time series flood forecasting model by the application of autoregressive integrated moving average (ARIMA) modelling approach. The accuracy of the optimal ARIMA model was verified by Spearman's rank correlation and linear regression analysis. The best ARIMA model was ARIMA (0, 1, 2). Trend analysis indicates that there was a trend of significant increase in rainfall rates at Kemelah Station and significant decrease at the Bandar Segamat Station, whereas streamflows at Bandar Segamat showed a trend of significant decrease. There was also a trend of decrease in streamflow over the study period. The applications of statistical modelling are beneficial to relevant authorities in understanding the flood patterns, trends and their potential risk.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Environmental Studies
DOI Number: https://doi.org/10.1111/jfr3.12258
Publisher: Wiley
Keywords: ARIMA model; Food; Mann–Kendall trend analysis; Rainfall; Segamat; Spearman’s rank correlation analysis; Statistics; Streamflow
Depositing User: Nida Hidayati Ghazali
Date Deposited: 27 Apr 2020 15:47
Last Modified: 27 Apr 2020 15:47
Altmetrics: https://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1111/jfr3.12258
URI: http://psasir.upm.edu.my/id/eprint/74094
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