数据匮乏地点的风暴潮评估:rio panuco,墨西哥

IF 0.2 Q4 WATER RESOURCES
R. Meza-Padilla , C.M. Appendini , A. Pedrozo-Acuña , F. González-Villarreal
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引用次数: 1

摘要

热带气旋引发的风暴潮是造成热带地区洪涝灾害的主要原因。然而,风暴潮的估计受到热带气旋测量和历史资料缺乏的限制。在墨西哥尤其如此,因为数据非常稀缺。因此,本研究提出了一种在历史资料不足的地区估算不同回归期热带气旋风暴潮值的替代方法。所选择的框架包括水动力模型的实施,以重现由海岸上热带气旋的存在引起的平均海平面高度。为此,我们使用了1980-2010年期间在大西洋产生的合成事件(120个事件),并将其限制在墨西哥Panuco河口周围100公里的圆形区域(22.26°N, 97.78°W),以及1951年至2012年期间发生的历史事件(25个)。这些事件的风场被用作水动力模型的强迫,以便确定感兴趣点的最大风暴潮。所得资料可作更可靠的极值分析,以确定不同回归期的风暴潮水平。结果表明,该方法在将合成事件与历史信息结合使用时是有用的,以便在数据有限的地区增加设计值的可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluación de la marea de tormenta en sitios con escasez de datos: río Pánuco, México

Storm surge from tropical cyclones is the main cause of flood induced damage in tropical regions. Nevertheless, storm surge estimations are limited by the scarcity of measurements and historical information of tropical cyclones. This is particularly true in Mexico because data is very scarce. Thus, this research presents an alternative method for estimating storm surge values from tropical cyclones for different return periods, in areas with insufficient historical information. The selected framework consists on the implementation of hydrodynamic models to reproduce the mean sea level elevation induced by the presence of tropical cyclones on the coast. For this, we used synthetic events (120 events) generated in the Atlantic Ocean during the defined time period between 1980–2010 and limited to a 100 km circular region around the mouth of the Panuco River in Mexico (22.26°N, 97.78°W), together with historical events (25) occurring between 1951 and 2012. The wind fields of these events are used as forcing for a hydrodynamic model in order to define the maximum storm surge at the point of interest. The obtained information allows for a more reliable extreme value analysis to determine storm surge levels for different return periods. The results demonstrate the usefulness of this methodology for using synthetic events in combination with historical information, in order to increase the reliability of the design values in areas with limited data.

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