The potential benefits of using artificial intelligence for monthly rainfall forecasting for the Bowen Basin, Queensland, Australia

被引:9
作者
Abbot, J. [1 ]
Marohasy, J. [1 ]
机构
[1] Cent Queensland Univ, Ctr Plant & Water Sci, Noosa, Qld, Australia
来源
WATER RESOURCES MANAGEMENT VII | 2013年 / 171卷
关键词
rainfall; neural network; forecast; Southern Oscillation index Interdecadal Pacific Oscillation; coal; mining; SEASONAL RAINFALL; ENSO;
D O I
10.2495/WRM130261
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The Bowen Basin contains the largest coal reserves in Australia. Prolonged heavy rainfall during the 2010-2011 wet-season severely affected industry operations with an estimated economic loss of A$5.7 billion(3.8 pound billion). There was no explicit warning of the exceptionally wet conditions in the seasonal forecast from the Australian Bureau of Meteorology, which simply suggested a 50-55% probability of above median rainfall for the Bowen Basin. In this study, the value of using neural networks, a form of artificial intelligence, to forecast monthly rainfall for the town of Nebo in the Bowen Basin is explored. Neural networks facilitate the input of multiple climate indices and the exploration of their non-linear relationships. Through genetic optimisations of input variables related to temperatures, including atmospheric temperatures and sea surface temperatures expressed through the Inter-decadal Pacific Oscillation and Nino 3.4, it is possible to develop monthly rainfall forecasts for Nebo superior to the best seasonal forecasts from the Bureau of Meteorology. As neural networks employ far superior technology for exploring the patterns and relationships within historical data including climate indices they are to be preferred.
引用
收藏
页码:287 / 297
页数:11
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