Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Int J Environ Res Public Health. 2023 Feb 13;20(4):3253. doi: 10.3390/ijerph20043253.
Global warming is predicted to lead to a new geographic and spatial distribution of storm-surge events and an increase in their activity intensity. Therefore, it is necessary to detect storm-surge events in order to reveal temporal and spatial variations in their activity intensity. This study attempted to detect storm-surge events from the perspective of detecting outliers. Four common outlier-detection methods, the Pauta criterion (PC), Chauvenet criterion (CC), Pareto distribution (PD) and kurtosis coefficient (KC), were used to detect the storm-surge events from the hourly residual water level data of 14 tide gauges along the coasts of China. This paper evaluates the comprehensive ability of the four methods to detect storm-surge events by combining historical typhoon-storm-surge events and deep-learning target-detection-evaluation indicators. The results indicate that (1) all of the four methods are feasible for detecting storm surge events; (2) the PC has the highest comprehensive detection ability for storm-surge events (F1 = 0.66), making it the most suitable for typhoon-storm-surge detection in coastal areas of China; the CC has the highest detection accuracy for typhoon-storm-surge events (precision = 0.89), although the recall of the CC is the lowest (recall = 0.42), as only severe storm surges were detected. This paper therefore evaluates four storm-surge-detection methods in coastal areas of China and provides a basis for the evaluation of storm-surge-detection methods and detection algorithms.
全球变暖预计将导致风暴潮事件的新的地理和空间分布，并增加其活动强度。因此，有必要检测风暴潮事件，以揭示其活动强度的时间和空间变化。本研究试图从检测异常值的角度检测风暴潮事件。使用四种常见的异常值检测方法，即 Pauta 准则（PC）、Chauvenet 准则（CC）、Pareto 分布（PD）和峰度系数（KC），从中国沿海 14 个验潮站的每小时剩余水位数据中检测风暴潮事件。本文通过结合历史台风风暴潮事件和深度学习目标检测评估指标，评估了四种方法检测风暴潮事件的综合能力。结果表明：（1）四种方法都可以检测风暴潮事件；（2）PC 对风暴潮事件的综合检测能力最高（F1=0.66），最适合中国沿海地区的台风风暴潮检测；CC 对台风风暴潮事件的检测精度最高（精度=0.89），尽管 CC 的召回率最低（召回率=0.42），因为只检测到了严重的风暴潮。本文因此评估了中国沿海地区的四种风暴潮检测方法，为风暴潮检测方法和检测算法的评估提供了依据。
