| Title |
A Statistical Assessment of the Rip-current Hazard Index Developed by the Korea Hydrographic and Oceanographic Agency (KHOA) |
| Authors |
최준우(Choi, Junwoo);김종범(Kim, Jong-Beom) |
| DOI |
https://doi.org/10.12652/Ksce.2026.46.1.0061 |
| Keywords |
이안류; 이안류 위험지수; 국립해양조사원(KHOA); 실시간 경보시스템; 통계적 평가 Rip current; Rip current hazard index; Korea Hydrographic and Oceanographic Agency (KHOA); Real-time warning system; Statistical assessment |
| Abstract |
The Korea Hydrographic and Oceanographic Agency (KHOA) operates an observation based real time rip current warning system to reduce rip current related safety incidents. This study statistically evaluated the predictive performance of rip current risk indices produced by the system for nine beaches using four years of data collected from 2021 to 2024. The existing risk index was first converted into a probabilistic index representing occurrence probability, and classification performance and forecast skill were comprehensively assessed using the Brier Skill Score (BSS), Accuracy, Probability of Detection (POD), False Alarm Ratio (FAR), False Positive Rate(FPR), the Youden index, the ROC curve, and the Area Under the ROC Curve (AUC). The results showed that AUC values ranged from 0.92 to 0.99 at most beaches, indicating excellent classification performance, while BSS values were generally greater than 0.36, demonstrating improved skill relative to a climatological reference. In particular, Naksan, Gyeongpo, and Mangsang Beaches exhibited high BSS and AUC values, confirming robust predictive performance. In addition, when the warning threshold probability(critical probability) was appropriately selected (typically in the range of 0.35 to 0.40), Accuracy remained at 84 to 95 percent while the balance between POD and FPR improved, suggesting enhanced operational efficiency. The data driven verification procedure
proposed in this study, applied over multiple years, can contribute to establishing a methodology for evaluating rip current forecasts and to improving the reliability of rip current warning and forecasting systems. |