Tsunami in the last 15 years: a bibliometric analysis with a detailed overview and future directions
Tsunami in the last 15 years: a bibliometric analysis with a detailed overview and future directions
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DOI：
10.1007/s11069-020-04454-2
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发表时间：
2021-01-02
期刊：
影响因子：
3.7
通讯作者：
Abraham, Ajith
中科院分区：
文献类型：
--
作者：
Jain, Nikita;Virmani, Deepali;Abraham, Ajith
在过去的十五年里，海啸科学发展迅速。三大海啸：2004年的印度洋海啸、2011年的东北海啸和2018年的帕鲁海啸是海啸科学史上的重要里程碑。正如前面提到的，所有三场海啸都不是没有发出任何警告，就是没有收到警报。吸取的各种经验教训、随后提出的数值模型、2004 年海啸损失调查结果都体现在解决方案中。然而，错误的解决方案导致了 2011 年东北事件的灾难性影响。在接下来的几年中，提出并实施了对预警系统和社区准备框架的许多改进。这些贡献和新发现为海啸科学进步带来了多方面的进步。随后，2018年发生的巴鲁海啸再次造成大量人员伤亡和财产损失。预警系统和社区似乎没有为这场非地震海啸做好准备。海啸科学实践和解决方案将发生重大变化。 2018 年海啸是有关古海啸记录、损害评估和震源发现方面讨论和研究最多的事件之一。在新时代，机器学习和深度学习在与海啸科学相关的所有领域都盛行。本文介绍了 Scopus 和 Web of Science (WoS) 对海啸研究的 15 年完整文献计量分析。以进展故事情节的形式对主要引用的文献进行审查，强调需要进行多学科研究来设计和提出实用的解决方案。
In the last fifteen years, tsunami science has progressed at a rapid pace. Three major tsunamis: The Indian Ocean in 2004, the 2011 Tohoku tsunami, and the 2018 Palu tsunami were significant landmarks in the history of tsunami science. All the three tsunamis, as mentioned, suffered from either no warning or poor reception of the alerts issued. Various lessons learned, consequent numerical models proposed, post-2004 tsunami damage findings manifested into solutions. However, the misperceived solutions led to a disastrous impact of the 2011 Tohoku event. In the following years, numerous improvements in warning systems and community preparedness frameworks were proposed and implemented. The contributions and new findings have added multi-fold advancements to tsunami science progress. Later, the 2018 Palu tsunami happened and again led to a massive loss of life and property. The warning systems and community seemed un-prepared for this non-seismic tsunami. A significant change is to take place in tsunami science practices and solutions. The 2018 tsunami is one of the most discussed and researched events concerning the palaeotsunami records, damage assessment, and source findings. In the new era, using machine learning and deep learning prevails in all the fields related to tsunami science. This article presents a complete 15-year bibliometric analysis of tsunami research from Scopus and Web of Science (WoS). The review of majorly cited documents in the form of a progressing storyline has highlighted the need for multidisciplinary research to design and propose practical solutions.