期刊論文
| 學年 | 108 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2020-04-24 |
| 作品名稱 | Self-organizing maps of typhoon tracks allow for flood forecasts up to two days in advance |
| 作品名稱（其他語言） | |
| 著者 | Li-Chiu Chang; Fi-John Chang; Shun-Nien Yang; Fong-He Tsai; Ting-Hua Chang; Edwin E. Herricks |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | Nature Communications 11, 1983 |
| 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. |
| 關鍵字 | Self-organizing maps;typhoon tracks;flood forecasts |
| 語言 | en |
| ISSN | 2041-1723 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | 國內 |
| 通訊作者 | |
| 審稿制度 | 是 |
| 國別 | GBR |
| 公開徵稿 | |
| 出版型式 | ,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/120223 ) |