Article(id=1224799661366591959, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1224799656396345456, articleNumber=null, orderNo=null, doi=10.12284/hyxb2022118, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1624377600000, receivedDateStr=2021-06-23, revisedDate=1644768000000, revisedDateStr=2022-02-14, acceptedDate=null, acceptedDateStr=null, onlineDate=1769944594947, onlineDateStr=2026-02-01, pubDate=1656604800000, pubDateStr=2022-07-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769944594947, onlineIssueDateStr=2026-02-01, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769944594947, creator=13701087609, updateTime=1769944594947, updator=13701087609, issue=Issue{id=1224799656396345456, tenantId=1146029695717560320, journalId=1149651085930835976, year='2022', volume='44', issue='7', pageStart='1', pageEnd='176', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769944593762, creator=13701087609, updateTime=1769996013782, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1225015327654821950, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1224799656396345456, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1225015327654821951, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1224799656396345456, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=122, endPage=136, ext={EN=ArticleExt(id=1224799661685359070, articleId=1224799661366591959, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Research on temporal and spatial variations of global tsunami based on complete catalog data, columnId=1194652705852465724, journalTitle=Haiyang Xuebao, columnName=Article, runingTitle=null, highlight=null, articleAbstract=

Tsunami is one of the disasters that seriously endanger the safety of human life and property among natural disasters. In the context of global warming and increasing economic development, more and more people, infrastructure and wealth are exposed to tsunami disasters, greatly increasing the risk and vulnerability of personal and property safety in coastal and delta areas. The analysis of temporal and spatial variation of historical tsunami disasters can help us understand the evolutionary laws of tsunami disasters, and provides a useful reference for more accurate disaster warning, disaster prevention and control, etc. A study on the temporal and spatial variation of global tsunami by extracting complete and homogeneous data is conducted in this paper. The results show that: (1) for 0.1 m≤RH<0.5 m, 0.5 m≤RH<1 m, 1 m≤RH<5 m, 5 m≤RH<10 m, 10 m≤RH<20 m and 20 m≤RH intervals, the tsunami catalogues can be considered complete since 1963, 1940, 1950, 1946, 1922 and 1885 respectively; (2) from time changes it can be seen that there is a certain increasing trend in the occurrence of global tsunamis. Approximately 7 more wave runup events are observed every year. At the same time, in different intensity intervals, the frequency of tsunamis has different changes. In the intervals of 0.1 m≤RH<0.5 m, 0.5 m≤RH<1 m, and 1 m≤RH<5 m, the tsunami have a certain periodicity, showing two obvious peaks, but when the RH is greater than 5 m, the periodicity of the tsunami is no longer obvious, and it shows a clear increasing trend at this time; (3) there is a certain increasing trend in the occurrence of tsunamis in East Asia, South Pacific, South America, and Indian Ocean. However, in North America, there is a decreasing trend, and there is no significant change in Europe; (4) except for North America, tsunami events in other regions show a good power law distribution relationship, indicating that the occurrence of tsunamis follows certain self-organized critical behavior. In comparison, small tsunami events are more likely to occur in Europe, while tsunami events in East Asia and the Indian Ocean are more prone to various types of tsunami events, of which large tsunami events occupy a larger portion.

, correspAuthors=Changxiu Cheng, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2022 Pratacultural Science. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Lixin Ning, Chun Hui, Changxiu Cheng), CN=ArticleExt(id=1224799663904145981, articleId=1224799661366591959, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=基于完整目录数据的全球海啸时空分异研究, columnId=1149698756456657529, journalTitle=海洋学报, columnName=论文, runingTitle=null, highlight=null, articleAbstract=

海啸是自然灾害中对人类生命财产安全有严重威胁的灾难之一。随着全球气候变化和全球化贸易日益增强,越来越多的人口和经济暴露于海啸灾害。历史海啸灾害的时空分异分析可以帮助我们认识海啸灾害的演变规律,为灾害预警、灾害防控等提供有益参考。本文通过提取具有完整性和同质性的数据(爬高高度(RH))进行全球海啸的时空分异规律研究,结果表明:(1)对于0.1 m≤RH<0.5 m、0.5 m≤RH<1 m、1 m≤RH<5 m、5 m≤RH<10 m、10 m≤RH<20 m和20 m≤RH的间隔,海啸目录分别自1963年、1940年、1950年、1946年、1922年和1885年以来可以被认为是完整的;(2)全球海啸发生有一定的增加趋势,大约每年会多观测到7次波浪爬高事件。在0.1 m≤RH<5 m区间内,海啸发生呈现一定的周期性。当RH大于5 m时,表现出明显的增加趋势;(3)西北太平洋区域、南太平洋区域、东南太平洋区域、印度洋区域海啸发生有一定的增加趋势,而在北美区域则呈减少趋势,东北大西洋区域无显著变化;(4)除北美区域外,其他区域的海啸发生遵循一定的自组织临界行为,相比来说,东北大西洋区域更容易发生小的海啸事件,而西北太平洋区域和印度洋区域更容易发生各种强度的海啸事件。

, correspAuthors=程昌秀, authorNote=null, correspAuthorsNote=
程昌秀(1973-),教授,研究方向为自然灾害、时空数据分析。E-mail:
, copyrightStatement=版权所有©《海洋学报》编辑部 2022, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=4PPUVisPmesvxLqxeEt8iw==, magXml=EN0u3Ep7Hm0i1ZL+x8YPJA==, pdfUrl=null, pdf=AcL4CCnUAQiwukwB3XchjA==, pdfFileSize=2794624, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=QwH1k4i+i8Ey65CyI3zdlg==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=WPA4m8jQg+47kQlxFB8l5w==, mapNumber=null, authorCompany=null, fund=null, authors=

宁立新(1991-),男,山东省济南市人,主要从事时空大数据研究。E-mail:

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a. Albarello method calculation results, where Tc represents complete results, Tu and Tl are uncertain results; b. Steep method analysis results, in vertical axis, $\lambda=\dfrac{1}{n}\displaystyle\sum x_i$, x is the number of times in the sampling time period, T is the sampling time period

, figureFileSmall=OSvVFfsWda6VJAtM1ndGxQ==, figureFileBig=apbke03dIa9M9Jyuv2RMCg==, tableContent=null), ArticleFig(id=1225366134053060649, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224799661366591959, language=CN, label=图3, caption=全球海啸目录的完整性分析结果

a. Albarello方法计算结果,其中Tc代表完整结果,Tu和Tl为不确定性结果;b. Steep方法分析结果,纵轴中$\lambda=\dfrac{1}{n}\displaystyle\sum x_i$,其中x为采样时间段内的事件数目,T为采样时间段

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基于完整目录数据的全球海啸时空分异研究
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宁立新 1, 2, 3 , 惠春 1, 2 , 程昌秀 1, 2, *
海洋学报 | 论文 2022,44(7): 122-136
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海洋学报 | 论文 2022, 44(7): 122-136
基于完整目录数据的全球海啸时空分异研究
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宁立新1, 2, 3 , 惠春1, 2, 程昌秀1, 2, *
作者信息
  • 1.北京师范大学 环境演变与自然灾害教育部重点实验室,北京 100875
  • 2.北京师范大学 地理科学学部,北京 100875
  • 3.山东农业大学 信息科学与工程学院,山东 泰安 271018
  • 宁立新(1991-),男,山东省济南市人,主要从事时空大数据研究。E-mail:

通讯作者:

程昌秀(1973-),教授,研究方向为自然灾害、时空数据分析。E-mail:
Research on temporal and spatial variations of global tsunami based on complete catalog data
Lixin Ning1, 2, 3 , Chun Hui1, 2, Changxiu Cheng1, 2, *
Affiliations
  • 1. Key Laboratory of Environmental Change and Natural Disaster City, Beijing Normal University, Beijing 100875, China
  • 2. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
  • 3. College of Information Science and Engineering, Shandong Agricultural University, Taian 271018, China
出版时间: 2022-07-01 doi: 10.12284/hyxb2022118
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海啸是自然灾害中对人类生命财产安全有严重威胁的灾难之一。随着全球气候变化和全球化贸易日益增强,越来越多的人口和经济暴露于海啸灾害。历史海啸灾害的时空分异分析可以帮助我们认识海啸灾害的演变规律,为灾害预警、灾害防控等提供有益参考。本文通过提取具有完整性和同质性的数据(爬高高度(RH))进行全球海啸的时空分异规律研究,结果表明:(1)对于0.1 m≤RH<0.5 m、0.5 m≤RH<1 m、1 m≤RH<5 m、5 m≤RH<10 m、10 m≤RH<20 m和20 m≤RH的间隔,海啸目录分别自1963年、1940年、1950年、1946年、1922年和1885年以来可以被认为是完整的;(2)全球海啸发生有一定的增加趋势,大约每年会多观测到7次波浪爬高事件。在0.1 m≤RH<5 m区间内,海啸发生呈现一定的周期性。当RH大于5 m时,表现出明显的增加趋势;(3)西北太平洋区域、南太平洋区域、东南太平洋区域、印度洋区域海啸发生有一定的增加趋势,而在北美区域则呈减少趋势,东北大西洋区域无显著变化;(4)除北美区域外,其他区域的海啸发生遵循一定的自组织临界行为,相比来说,东北大西洋区域更容易发生小的海啸事件,而西北太平洋区域和印度洋区域更容易发生各种强度的海啸事件。

时空分异  /  完整性分析  /  幂律  /  海啸

Tsunami is one of the disasters that seriously endanger the safety of human life and property among natural disasters. In the context of global warming and increasing economic development, more and more people, infrastructure and wealth are exposed to tsunami disasters, greatly increasing the risk and vulnerability of personal and property safety in coastal and delta areas. The analysis of temporal and spatial variation of historical tsunami disasters can help us understand the evolutionary laws of tsunami disasters, and provides a useful reference for more accurate disaster warning, disaster prevention and control, etc. A study on the temporal and spatial variation of global tsunami by extracting complete and homogeneous data is conducted in this paper. The results show that: (1) for 0.1 m≤RH<0.5 m, 0.5 m≤RH<1 m, 1 m≤RH<5 m, 5 m≤RH<10 m, 10 m≤RH<20 m and 20 m≤RH intervals, the tsunami catalogues can be considered complete since 1963, 1940, 1950, 1946, 1922 and 1885 respectively; (2) from time changes it can be seen that there is a certain increasing trend in the occurrence of global tsunamis. Approximately 7 more wave runup events are observed every year. At the same time, in different intensity intervals, the frequency of tsunamis has different changes. In the intervals of 0.1 m≤RH<0.5 m, 0.5 m≤RH<1 m, and 1 m≤RH<5 m, the tsunami have a certain periodicity, showing two obvious peaks, but when the RH is greater than 5 m, the periodicity of the tsunami is no longer obvious, and it shows a clear increasing trend at this time; (3) there is a certain increasing trend in the occurrence of tsunamis in East Asia, South Pacific, South America, and Indian Ocean. However, in North America, there is a decreasing trend, and there is no significant change in Europe; (4) except for North America, tsunami events in other regions show a good power law distribution relationship, indicating that the occurrence of tsunamis follows certain self-organized critical behavior. In comparison, small tsunami events are more likely to occur in Europe, while tsunami events in East Asia and the Indian Ocean are more prone to various types of tsunami events, of which large tsunami events occupy a larger portion.

temporal and spatial variation  /  completeness analysis  /  power law  /  tsunami
宁立新, 惠春, 程昌秀. 基于完整目录数据的全球海啸时空分异研究. 海洋学报, 2022 , 44 (7) : 122 -136 . DOI: 10.12284/hyxb2022118
Lixin Ning, Chun Hui, Changxiu Cheng. Research on temporal and spatial variations of global tsunami based on complete catalog data[J]. Haiyang Xuebao, 2022 , 44 (7) : 122 -136 . DOI: 10.12284/hyxb2022118
海啸是自然灾害中对人类生命财产安全有严重威胁的灾害之一。其成因复杂,多由海底地震、火山喷发、滑坡、泥石流等海底地形突变引发,是具有超长波长和周期的大洋行波[1]。当行波接近海岸浅水区时,波长变短,振幅陡涨,可形成20 m以上、含有巨大能量的“水墙”。受海底地形、海岸线几何形状及波浪特性的控制,海啸波浪爬高会每隔数分钟或数十分钟就重复1次,摧毁堤岸、淹没土地、夺走生命财产,破坏力极大。2004年12月发生在苏门答腊岛附近的海底地震引发的海啸不仅袭击了地震震中附近的印度尼西亚、泰国、缅甸等国家,而且海啸波经过长途跋涉,奔袭了数千千米以外的印度、斯里兰卡、马尔代夫等国家,共造成约30万人死亡,8 000人失踪,近200万人无家可归,经济损失达60亿美元左右[2];2011年3月日本宫城县东北外海地震引发巨大海啸并造成核泄漏,造成约1.5万人死亡,经济损失达1 200亿~2 350亿美元。
近些年来,自然灾害的研究引起相关学者的广泛关注,其中的自然灾害时空分异规律是地理学和灾害领域的核心内容之一[3-4]。近几十年来,我国学者先后从不同角度开展了我国自然灾害的时空分异规律的研究工作。然而,进行自然灾害时空分异规律的研究多关注于山火[5-6]、地震[7]、风暴[8-9]、暴雨[10-12]和干旱[13-14]等。进一步检索发现,为数不多的有关海啸时空分异规律的研究工作主要集中在美国、俄罗斯、日本等国,其工作也主要是围绕某海啸案例或某特定区域展开,如太平洋区域[15]、日本区域[16]。除了针对特定海啸和区域进行研究外,也有极少数从全球角度出发开展海啸时空分异规律的研究[17-19]
因此,本研究通过整理已有的海啸目录数据,提取具有完整性和同质性的数据进行全球海啸的时空分异规律研究,进一步丰富和完善对海啸灾害的认知体系,可以帮助我们认识海啸灾害的演变规律,而且其是认识灾害、预测灾害的前提,为更准确地进行灾害预警、灾害防控等提供有益参考[20]
美国海洋和大气管理局的国家环境信息中心(National Centers for Environmental Information, NCEI)为地球物理研究提供了各种长期的科学数据集,例如海啸、固体地球物理以及海洋地质等的数据集[21]。经过多年的积累,其海啸数据库已大大扩展,服务于海啸研究而存档的数据类型也极其丰富,海啸数据库由全球历史海啸数据库、海啸沉积物和代理数据库、深海评估报告和潮汐仪记录数据等组成,该数据库是目击者陈述和仪器记录的汇编。其中,全球历史海啸数据库包含了自公元前2000年以来的2 600多个海啸事件记录和26 000多个波浪爬高记录,包括位置、传播时间、到达时间、水位、可信度、死亡和受伤情况等。在过去的几十年里,该数据库通过仔细检查海啸与历史事件的匹配程度而得到了显著的改进。
已有较多研究针对波浪爬高记录数据进行了相关的研究,例如:Geist和Parsons[22]通过分析全球海啸事件目录确定海啸发生率的瞬态变化是否与通常假设的泊松过程一致;Ning等[23]分析了此数据的时空完整性。因此,在本研究中也基于此数据进行时空分异规律研究。选择了从公元前2000年到2017年的26 691次海啸波浪爬高记录。在海啸记录表中,为所有海啸事件分配了可靠性分数,范围从−1(错误输入)到4(确定的海啸)不等。根据先前的研究,可靠性为3或4的事件可以被认为是确定的海啸事件,而可靠性为−1、0、1或2的事件则被认为是未经确认的海啸事件[22]。因此,选择可靠性标记为3或4的海啸事件,通过比较和整合海啸事件表中和波浪爬高事件表中的事件,建立了公元前2000年至2017年可靠的波浪爬高事件数据库,包括25 327条波浪爬高数据。经过删除波浪爬高高度为空值和零值的记录(此数据无意义)之后,获得22 271个波浪爬高数据。经过去除无确切位置的波浪爬高记录之后,最终选择了21 981个的海啸波浪爬高数据。基于国产地理信息平台KQGIS软件展示数据的空间分布,结果如图1所示。
为了分析全球海啸的空间异质性,本研究将全球的海啸发生区分成了多个区域,通过比较不同区域海啸事件的时间变化以分析全球海啸发生的时空分异。NCEI基于海啸发生的频率、地球物理关系、偏远地区的风险以及政治理由提出了一个包含20个区域的全球海啸分区框架。但是,此分区过于详细,包含的小区域太多,无法满足本研究的需求。因此,本研究通过合并某些邻近区域重新定义了6个新分区(图2),即东北大西洋区域(EU)、印度洋区域(IN)、东南太平洋区域(SA)、北美区域(NA)、南太平洋区域(SP)和西北太平洋区域(EA)。通过分析不同区域中的可用波浪爬高数据,以分析不同区域海啸发生的时空分异。
通常,海啸目录包含两种类型的数据:相对较短的仪器记录数据和从文献中获得相对较长的宏观统计数据。由于数据收集方法和处理的异质性,海啸目录的完整性水平随着时间和空间的变化而变化[24]。由于战争等因素导致记录文档丢失,因此此类方案保存的宏观统计数据常常不完整,并且随着时间的推移,数据丢失的可能性随之增加。而仪器记录的数据由于潮汐仪等检测网络密度和分析方法的变化可能导致不同程度的完整性记录水平[25-26]。若直接进行历史灾害数据的分析可能出现偏差,因此,在进行任何科学研究之前评估目录的完整性、同质性和一致性至关重要[21-27]。对目录完整性水平的错误评估可能会对相应的研究造成有偏和不正确的错误结果,并进一步影响后续研究。完整的海啸目录(Tc)定义为海啸事件被完整和可靠记录下来的最低强度,该完整性依赖于空间、时间和海啸强度。了解Tc的完整性是一项必不可少的任务,而可靠的Tc估计更是预测海啸危险性和抗灾设计的关键参数。
目前大多数有关灾害目录完整性的分析方法多集中在地震领域,且已开发出多个确定地震目录完整性的分析方法,如古登堡−里希特关系[28-29]、基于概率的方法[30]、基于贝叶斯的方法[31-32]等。尽管目前已有较多估计地震目录完整性的分析方法,但尚未开发出专门针对海啸目录完整性分析的特定方法。由于大多数海啸是由于海底地震直接或间接引发,因此我们可以预期海啸发生的统计特征将与地震相似[22]。因此某些分析地震目录完整性的方法可能适用于海啸研究,但是不能证明海啸强度的分布服从幂律规律。其次,基于概率的方法和贝叶斯方法目前也不适用。相反一些统计方法[24, 33-34]可能有助于估计海啸目录的完整性程度。因此,为了评估海啸目录的完整性,采用两种统计方法提取海啸目录的完整部分,这为后续时空分异分析提供了一个完整且同质的海啸数据。
Albarello等[24]改进了Kafka和Levin[34]、Mulargia等[35]提出的半定性方法(简称Albarello方法),让我们能够对灾害事件的发生做出最严格的假设。该方法认为完整的、具有代表性的目录应存在跨度为△T的子目录,在△T内,海啸目录的记录周期能够跨越海啸的复发周期且能反映海啸发生的统计特征(假设R),同时海啸目录至少包含一个能代表实际海啸活动率的子目录(假设C),通过满足上述两个假设的条件概率和非条件概率的最大子目录被认为是完整的子目录,具体计算方法请参见文献[24, 36]。
Steep方法[33, 37-38]首先将海啸事件分为多个不同强度的间隔,每个强度间隔代表时间上的一个点过程。该统计估计的优点是样本均值的方差与样本中观察值的数量成反比。因此,通过获得足够数量的样本观测值,可以使方差尽可能小。前提是过程是平稳的,也就是说,它们保持等于每个观察值的平均方差。为了获得样本均值方差的可靠估计,我们假设泊松分布可以对海啸序列进行建模,具体计算方法参见文献[33, 37-38]。
为了估计不同强度间隔的海啸目录完整性,根据波浪爬高高度(Runup Height,RH)将全球波浪爬高事件分为6个高度间隔,分别为0.1 m≤RH<0.5 m、0.5 m≤RH<1 m、1 m≤RH<5 m、5 m≤RH<10 m、10 m≤RH<20 m和20 m≤RH。图3a显示了Albarello方法的分析结果,对于每个RH间隔,Tc报告了对应的完整性目录起始时间。结果表明,对于0.1 m≤RH<0.5 m、0.5 m≤RH<1 m、1 m≤RH<5 m、5 m≤RH<10 m、10 m≤RH<20 m和20 m≤RH的间隔,海啸目录分别自1963年、1940年、1950年、1946年、1922年和1885年以来可以被认为是完整的。一个值得注意的现象是,在3个RH间隔(0.5 m≤RH<1 m、1 m≤RH<5 m和5 m≤RH<10 m)中估计的完整性起始时间(1940年、1950年和1946年)较为相近,这意味着从完整性的角度考虑这些RH间隔时,可以认为目录是统一的。另外我们可以得出结论,海啸目录的完整性起始时间会随着RH的增加而向后追溯。同时,Steep方法的分析结果(图3b)与前述结果较为接近,两者共同印证了此结论的可靠性。
基于前述研究成果,提取1940年以来0.1 m以上的波浪爬高事件作为完整记录的海啸数据,通过统计不同海啸强度区间各年份的波浪爬高频次以分析海啸发生的整体变化趋势,同时统计不同区域内的海啸发生情况以分析海啸发生的时空分异情况。
图4展示了全球海啸不同强度区间的发生频次曲线。整体来看,全球海啸波浪爬高事件主要有两次集中暴发(图4a),分别为1945−1965年间和2000−2015 年间,两阶段内全球观测的波浪爬高事件约占总研究期间的85%,其中2000−2015年间就发生了约总研究期间63%的海啸事件,尤其是2011年全球发生了5 972次波浪爬高事件(占总研究期间的33%)。从时间变化来看,全球海啸发生有一定的增加趋势,拟合曲线为y=6.942 9(x−1 940)−44.628,大约每年会多观测到7次波浪爬高事件。同时,在不同的强度间隔,海啸发生频次有不同的变化情况。0.1 m≤RH<0.5 m(图4b)区间内,海啸发生呈现一定的周期性(约45年),表现出明显的两个峰值,分别在1965年和2010年前后,此时年发生频次约为150次。0.5 m≤RH<1 m(图4c)和1 m≤RH<5 m(图4d)区间内,海啸发生仍表现出一定的周期性,具体情况与图4a较为相似。但当RH大于5 m时,海啸发生的周期性则不再明显,此时表现出明显的增加趋势。例如5 m≤RH<10 m区间,海啸发生的增加趋势约为每年1.68次,10 m≤RH<20 m区间和20 m≤RH区间,每年约分别增加1.41次和0.39次,增加趋势随着强度的增大有所减弱。
图5展示了西北太平洋区域不同强度区间海啸发生频次曲线。整体来看,西北太平洋区域海啸发生的频次变化较小(图5a),仅在2011年表现出明显的增加,这是因为2011年日本东北部太平洋发生了里氏9.0级地震,引发了巨大的海啸和波浪爬高。从时间变化来看,西北太平洋区域海啸发生有一定的增加趋势,大约每年会多观测到4次波浪爬高事件。同时,在不同的强度间隔,海啸发生频次有不同的变化情况。0.1 m≤RH<0.5 m(图5b)和0.5 m≤RH<1 m(图5c)区间内,海啸发生次数较多,变化不明显。但在RH≥1 m的各区间,海啸发生呈现显著的增加趋势。
图6展示了北美区域不同强度区间的海啸发生频次曲线。整体来看,北美区域的海啸发生表现出两个峰值区间,分别在1960年和2011年前后,这与1960年智利大海啸和2011年日本311地震海啸有直接关系。从时间变化来看,该地区海啸发生有一定的减少趋势,大约每年会少观测到0.2次波浪爬高事件。同时,在不同的强度间隔,海啸发生频次有不同的变化情况。0.1 m≤RH<0.5 m、0.5 m≤RH<1 m和1 m≤RH<5 m区间内,海啸发生次数呈现两个峰值。但在RH≥5 m的各区间,海啸发生则呈现减少趋势。
图7展示了南太平洋区域不同强度区间的海啸发生频次曲线。整体来看,南太平洋区域的海啸发生在2011年前后达到最大频次。从时间变化上表现出一定的增加趋势,大约每年会多发生0.86次波浪爬高事件。同时,在不同的强度间隔,海啸发生频次有不同的变化情况。0.1 m≤RH<0.5 m和0.5 m≤RH<1 m区间内,海啸发生次数呈现两个峰值。但在RH≥1 m的各区间,海啸发生呈现出明显的增加趋势。
图8展示了东南太平洋区域不同强度区间的海啸发生频次曲线。整体来看,东南太平洋区域的海啸发生在2011年前后达到最大频次。从时间变化上表现出一定的增加趋势,大约每年会多发生0.97次波浪爬高事件。同时,在不同的强度间隔,海啸发生频次有不同的变化情况。总体来说,该地区的海啸发生情况与南太平洋区域的海啸发生情况较为一致。
图9展示了印度洋区域不同强度区间的海啸发生频次曲线。整体来看,印度洋区域的海啸发生在2004年前后达到最大频次,这是因为2004年印度尼西亚苏门答腊岛附近发生了极为严重的海啸,波及范围远至非洲东海岸,给各个国家造成了巨大的人员伤亡和财产损失。从时间变化上表现出一定的增加趋势,大约每年会多发生1.46次波浪爬高事件。同时,在不同的强度间隔,海啸发生频次有不同的变化情况。总体来说,海啸发生在各强度区间呈现出明显的增加趋势。
图10展示了东北大西洋区域不同强度区间的海啸发生频次曲线。整体来看,东北大西洋区域的海啸发生较为一致,变化较小。从时间变化上表现出较弱的增加趋势,大约每年会多发生0.008 4次波浪爬高事件。在不同的强度间隔,海啸发生频次虽然有一定的变化,但变化较小。这可能与该地区观测的海啸事件少有关,以致于无法进行统计分析。
自然中,许多灾害发生的频次与强度呈现明显的幂律分布特征,如滑坡[39-40]、山火[41-42]、地震[8]等。许多研究认为,幂律行为是自组织临界行为的结果。目前难以对自组织临界行为进行严格的定义,但可认为是对一个复杂系统的输入几乎是恒定的,但其输出是一系列符合幂律分布情形的一系列事件[43-45]。计算公式为
$ \ln N=-b\times {\rm{RH}} +a, $
式中,N为波浪爬高高度超过某特定高度的累计数量;ab为常数,其中b为累积分布图中的斜率,可以称为分形维数。
该关系可以用来在区域或全球范围内确定海啸的重现率,通过测算强度低的海啸发生率以预测大海啸的发生率[41, 45]。因此,本节以完整性海啸目录为基础,通过计算海啸发生的频次−浪高关系,表征全球及不同区域的海啸发生幂律关系,为认识海啸、预测海啸提供参考。
图11展示了全球和各区域波浪爬高频次−强度关系。可以发现,除全球和北美区域外,其他区域的海啸事件呈现出较好的幂律分布关系,说明海啸的发生遵循一定的自组织临界行为。其中,西北太平洋区域、南太平洋区域、东南太平洋区域、印度洋区域和东北大西洋区域得到的b值分别为−0.185 2、−0.312、−0.235 8、−0.167和−0.314 6,表明相比来说,东北大西洋区域更容易发生小的海啸事件,而西北太平洋区域和印度洋区域更容易发生各种类型的海啸事件,其中大的海啸事件占据较大部分。
历史海啸灾害的时空分异分析可以帮助我们认识海啸灾害的演变规律,作为认识灾害、预测灾害的前提,可为更准确的进行灾害预警、灾害防控等提供有益参考。本文提取具有完整性和同质性的数据进行全球海啸的时空分异规律研究,结果表明:(1)对于0.1 m≤RH<0.5 m、0.5 m≤RH<1 m、1 m≤RH<5 m、5 m≤RH<10 m、10 m≤RH<20 m和20 m≤RH的间隔条件,海啸目录分别自1963年、1940年、1950年、1946年、1922年和1885年以来可以被认为是完整的;(2)从时间变化来看,全球海啸发生有一定的增加趋势,大约每年会多观测到7次波浪爬高事件。同时,在不同的强度间隔条件,海啸发生频次有不同的变化情况。0.1 m≤RH<0.5 m、0.5 m≤RH<1 m和1 m≤RH<5 m区间内,海啸发生呈现一定的周期性,表现出两个明显的峰值,但当RH大于5 m时,海啸发生的周期性则不再明显,此时表现出明显的增加趋势;(3)在不同的区域海啸的变化有一定的差异。西北太平洋区域、南太平洋区域、东南太平洋区域、印度洋区域海啸发生有一定的增加趋势,大约每年会多观测到4次、0.86次、0.97次、1.46次波浪爬高事件。而在北美区域则呈减少趋势,东北大西洋区域无显著变化;(4)除北美区域外,其他区域的海啸事件呈现出较好的幂律分布关系,说明海啸的发生遵循一定的自组织临界行为。相比来说,东北大西洋区域更容易发生小的海啸事件,而西北太平洋区域和印度洋区域更容易发生各种类型的海啸事件,其中大的海啸事件占据较大部分。
  • 国家自然科学基金(41771537)
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2022年第44卷第7期
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doi: 10.12284/hyxb2022118
  • 接收时间:2021-06-23
  • 首发时间:2026-02-01
  • 出版时间:2022-07-01
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  • 收稿日期:2021-06-23
  • 修回日期:2022-02-14
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国家自然科学基金(41771537)
作者信息
    1.北京师范大学 环境演变与自然灾害教育部重点实验室,北京 100875
    2.北京师范大学 地理科学学部,北京 100875
    3.山东农业大学 信息科学与工程学院,山东 泰安 271018

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程昌秀(1973-),教授,研究方向为自然灾害、时空数据分析。E-mail:
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2种不同金属材料的力学参数

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Percentage of
total species (%)

Genus
种数
Number of
species
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Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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