Self-organizing maps of typhoon tracks allow for flood forecasts up to two days in advance

doi:10.1038/s41467-020-15734-7

淡江大學機構典藏 > 工學院 > 水資源及環境工程學系暨研究所 > 期刊論文 > Item 987654321/120223

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题名:	Self-organizing maps of typhoon tracks allow for flood forecasts up to two days in advance
作者:	Chang, Li-Chiu;Chang, Fi-John;Yang, Shun-Nien;Tsai, Fong-He;Chang, Ting-Hua;Herricks, Edwin E.
关键词:	Self-organizing maps;typhoon tracks;flood forecasts
日期:	2020-04-24
上传时间:	2021-03-17 12:11:26 (UTC+8)
摘要:	Typhoons are among the greatest natural hazards along East Asian coasts. Typhoon-related precipitation can produce flooding that is often only predictable a few hours in advance. Here, we present a machine-learning method comparing projected typhoon tracks with past trajectories, then using the information to predict flood hydrographs for a watershed on Taiwan. The hydrographs provide early warning of possible flooding prior to typhoon landfall, and then real-time updates of expected flooding along the typhoon’s path. The method associates different types of typhoon tracks with landscape topography and runoff data to estimate the water inflow into a reservoir, allowing prediction of flood hydrographs up to two days in advance with continual updates. Modelling involves identifying typhoon track vectors, clustering vectors using a self-organizing map, extracting flow characteristic curves, and predicting flood hydrographs. This machine learning approach can significantly improve existing flood warning systems and provide early warnings to reservoir management.
關聯:	Nature Communications 11, 1983
DOI:	10.1038/s41467-020-15734-7
显示于类别:	[水資源及環境工程學系暨研究所] 期刊論文

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