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