Cite this article：
Yuan, W., Jing, B., Xu, H. et al. A Dynamic Early Warning Model for Flash Floods Based on Rainfall Pattern Identification. Int J Disaster Risk Sci 15, 769–788 (2024). https://doi.org/10.1007/s13753-024-00593-3
基于降雨雨型识别的山洪动态预警模型
Wenlin Yuan, Bohui Jing, Hongshi Xu, Yanjie Tang & Shuaihu Zhang
摘要：
山洪是山区和丘陵地区最具破坏性的自然灾害之一。本研究针对山洪预警中忽视降雨雨型随机性和不确定性的问题，提出了一种山洪灾害动态预警模型，以提高预警精度。文章基于相似性理论和特征降雨雨型数据库，提出了降雨雨型的动态识别方法。特征降雨雨型是通过对历史降雨数据进行K-均值聚类方法而构建的。随后，本文基于降雨雨型实时修正和 HEC-HMS（美国陆军工程兵团水文工程中心开发的水文模拟系统）模型的洪水模拟，提出了山洪灾害动态预警模型。为了验证所提出模型的有效性，本文选择了中国三个小流域作为案例进行研究。结果表明，所提出方法识别出的降雨雨型与实测降雨过程具有很高的相关性。随着实测降雨量信息的增加，对识别出的降雨雨型进行动态修正，在 t = 4、t = 5 和 t = 6 时，相应的洪水预报的纳什-苏特克利夫效率系数（NSE）超过0.8，从而提高了山洪预警的准确性。同时，本文所提出的模型还延长了山洪预报的预见期，并具有很高的准确性。对于新县流域6小时和滕州流域8小时历时降雨，所提出的模型分别在降雨结束前2小时和3小时发出准确预警（预警精度超0.90）。本文所提出的模型可为山区和丘陵流域的山洪灾害管理提供技术支持。
关键词：
中国；动态预警模型；山洪；HEC-HMS模型；降雨雨型识别
A Dynamic Early Warning Model for Flash Floods Based on Rainfall Pattern Identification
Wenlin Yuan, Bohui Jing, Hongshi Xu, Yanjie Tang & Shuaihu Zhang
Abstract：
Flash floods are one of the most devastating natural hazards in mountainous and hilly areas. In this study, a dynamic warning model was proposed to improve the warning accuracy by addressing the problem of ignoring the randomness and uncertainty of rainfall patterns in flash flood warning. A dynamic identification method for rainfall patterns was proposed based on the similarity theory and characteristic rainfall patterns database. The characteristic rainfall patterns were constructed by k-means clustering of historical rainfall data. Subsequently, the dynamic flood early warning model was proposed based on the real-time correction of rainfall patterns and flooding simulation by the HEC-HMS (Hydrologic Engineering Center’s Hydrologic Modeling System) model. To verify the proposed model, three small watersheds in China were selected as case studies. The results show that the rainfall patterns identified by the proposed approach exhibit a high correlation with the observed rainfall. With the increase of measured rainfall information, the dynamic correction of the identified rainfall patterns results in corresponding flood forecasts with Nash-Sutcliffe efficiency (NSE) exceeding 0.8 at t = 4, t = 5, and t = 6, thereby improving the accuracy of flash flood warnings. Simultaneously, the proposed model extends the forecast lead time with high accuracy. For rainfall with a duration of six hours in the Xinxian watershed and eight hours in the Tengzhou watershed, the proposed model issues early warnings two hours and three hours before the end of the rainfall, respectively, with a warning accuracy of more than 0.90. The proposed model can provide technical support for flash flood management in mountainous and hilly watersheds.
Keywords：
China, Dynamic early warning model, Flash foods, HEC-HMS model, Rainfall pattern identifcation
文章链接：
https://link.springer.com/article/10.1007/s13753-024-00593-3