文献类型：期刊文献

英文题名：Development and evaluation of a rip current forecasting system for channel-type rip currents on a low-energy headland beach

作者：Sun, Yan[1,2];Liu, Lulu[1,2];Bian, Xiaodong[1,2];Zhu, Daoheng[1];Li, Zhiqiang[1]

机构：[1]Guangdong Ocean Univ, Coll Elect & Informat Engn, Zhanjiang, Peoples R China;[2]Guangdong Ocean Univ, Coll Chem & Environm Sci, Zhanjiang, Peoples R China

年份：2025

卷号：16

期号：1

外文期刊名：GEOMATICS NATURAL HAZARDS & RISK

收录：SCI-EXPANDED(收录号：WOS:001584960400001)、、EI(收录号：20254019273492)、Scopus(收录号：2-s2.0-105017632465)、WOS

基金：The authors would like to thank all the reviewers for their comments on this article. This work was supported by the National Natural Science Foundation of China [No. 42176167]; the Guangdong Basic and Applied Basic Research Foundation [No. 2024A1515011427]; the project of the Excellent Doctoral Thesis Cultivation Program of Guangdong Ocean University [No. 202431].

语种：英文

外文关键词：Channel-type rip currents; low-energy; numerical model; generalized additive model; warning system

外文摘要：A 34-day field observation was conducted on a headland beach in South China with a typical channel rip current system. The Delft3D model was applied to reproduce hydrodynamic conditions and extract rip currents, while a Generalized Additive Model (GAM) was used to capture and quantify the nonlinear interactions among environmental factors. By optimizing interaction terms, a comprehensive model was constructed, and a hybrid rip current warning system combining physical modelling and statistical analysis (NGRWS) was proposed. Results showed that rip currents in the study area were generally of low energy and persistent, being jointly controlled by multiple factors, with wave direction (WaveDir), significant wave height (SWH), and water level (WL) as the maindrivers. Using limited offshore environmental variables, the system achieved 6-h forecasts with errors <0.3 cm/s, correctly predicting 87% of rip events with false and missed alarm rates of 5% and 8%. A storm causing coastal erosion further provided evidence that the system has certain robustness, although recalibration remains necessary over time. In addition, while quantifying the contributions of environmental factors, the GAM also revealed potential cognitive blind spots under traditional empirical judgments. This study supports improved risk avoidance for beach users.