A hybrid Box-Jenkins and decomposition model for drought forecasting in Kuala Terengganu
Drought is a global phenomenon which adversely affects the sustainability of one nation which encompasses three prominent aspects such as economic, social and environmental. Due to that, it has immensely attracted the awareness of environmentalists, ecologists, hydrologists, meteorologists, geologis...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2013
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| Online Access: | http://eprints.utm.my/id/eprint/44616/5/HoMeeChyongMFS2013.pdf http://eprints.utm.my/id/eprint/44616/ |
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| Summary: | Drought is a global phenomenon which adversely affects the sustainability of one nation which encompasses three prominent aspects such as economic, social and environmental. Due to that, it has immensely attracted the awareness of environmentalists, ecologists, hydrologists, meteorologists, geologists and agricultural scientists. Therefore, drought forecasting is essential for several key players particularly the governments to evaluate the drought occurrence in order to give early warning for preparedness and mitigation measures. In this study, a hybrid Box-Jenkins and decomposition model based on standardized precipitation index (SPI) was developed to forecast drought in Kuala Terengganu. Monthly rainfall data of rain gauge station, Setor JPS Kuala Terengganu for period January 1982 to January 2012 was used in this study. Multiplicative decomposition method was employed to identify and isolate the underlying components of SPI time series for multiple time scales using Minitab 16.0. Then the isolated components were gone through the four-step iterative procedure of Box-Jenkins which are identification, estimation, diagnostic checking and forecasting. After that, the forecasted values of components were reassembled in order to gain a forecast based on the time series decomposition. The forecasting performance of the hybrid model was compared with the Box-Jenkins model. Two statistical measurements, mean absolute error (MAE) and mean squared error (MSE) were applied in this study to measure the accuracy of the forecasting models. In brief, the accuracy measure results indicated that the hybrid model can prevail over the Box-Jenkins model. |
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