Temporal flood incidence forecasting for Segamat River (Malaysia) using autoregressive integrated moving average modelling
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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018
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| Online Access: | http://psasir.upm.edu.my/id/eprint/74094/1/Temporal%20flood%20incidence%20forecasting%20for%20Segamat%20River%20%28Malaysia%29%20using%20autoregressive%20integrated%20moving%20average%20modelling.pdf |
| _version_ | 1796979680578895872 |
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| author | Razak, Nurhafiza Aris, Ahamd Zaharin Ramli, Mohammad Firuz Looi, Ley Juen Juahir, Hafizan |
| author_facet | Razak, Nurhafiza Aris, Ahamd Zaharin Ramli, Mohammad Firuz Looi, Ley Juen Juahir, Hafizan |
| author_sort | Razak, Nurhafiza |
| collection | UPM |
| description | 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. |
| first_indexed | 2024-03-06T10:12:28Z |
| format | Article |
| id | upm.eprints-74094 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:12:28Z |
| publishDate | 2018 |
| publisher | Wiley |
| record_format | dspace |
| spelling | upm.eprints-740942020-04-27T15:47:24Z http://psasir.upm.edu.my/id/eprint/74094/ Temporal flood incidence forecasting for Segamat River (Malaysia) using autoregressive integrated moving average modelling Razak, Nurhafiza Aris, Ahamd Zaharin Ramli, Mohammad Firuz Looi, Ley Juen Juahir, Hafizan 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. Wiley 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/74094/1/Temporal%20flood%20incidence%20forecasting%20for%20Segamat%20River%20%28Malaysia%29%20using%20autoregressive%20integrated%20moving%20average%20modelling.pdf 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 https://onlinelibrary.wiley.com/doi/epdf/10.1111/jfr3.12258 10.1111/jfr3.12258 |
| spellingShingle | Razak, Nurhafiza Aris, Ahamd Zaharin Ramli, Mohammad Firuz Looi, Ley Juen Juahir, Hafizan Temporal flood incidence forecasting for Segamat River (Malaysia) using autoregressive integrated moving average modelling |
| title | Temporal flood incidence forecasting for Segamat River (Malaysia) using autoregressive integrated moving average modelling |
| title_full | Temporal flood incidence forecasting for Segamat River (Malaysia) using autoregressive integrated moving average modelling |
| title_fullStr | Temporal flood incidence forecasting for Segamat River (Malaysia) using autoregressive integrated moving average modelling |
| title_full_unstemmed | Temporal flood incidence forecasting for Segamat River (Malaysia) using autoregressive integrated moving average modelling |
| title_short | Temporal flood incidence forecasting for Segamat River (Malaysia) using autoregressive integrated moving average modelling |
| title_sort | temporal flood incidence forecasting for segamat river malaysia using autoregressive integrated moving average modelling |
| url | http://psasir.upm.edu.my/id/eprint/74094/1/Temporal%20flood%20incidence%20forecasting%20for%20Segamat%20River%20%28Malaysia%29%20using%20autoregressive%20integrated%20moving%20average%20modelling.pdf |
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