{"title":"Earthquake detection probabilities and completeness magnitude in the northern margin of the Ordos Block","authors":"Fan Zhang, Xiao-Zhong Yang, Feng-Zhi Cui","doi":"10.1007/s11770-024-1128-1","DOIUrl":null,"url":null,"abstract":"<p>The assessment of the completeness of earthquake catalogs is a prerequisite for studying the patterns of seismic activity. In traditional approaches, the minimum magnitude of completeness (<i>M</i><sub>C</sub>) is employed to evaluate catalog completeness, with events below <i>M</i><sub>C</sub> being discarded, leading to the underutilization of the data. Detection probability is a more detailed measure of the catalog’s completeness than <i>M</i><sub>C</sub>; its use results in better model compatibility with data in seismic activity modeling and allows for more comprehensive utilization of seismic observation data across temporal, spatial, and magnitude dimensions. Using the magnitude–rank method I and Maximum Curvature (MAXC) methods, we analyzed temporal variations in earthquake catalog completeness, finding that <i>M</i><sub>C</sub> stabilized after 2010, which closely coincides with improvements in monitoring capabilities and the densification of seismic networks. Employing the probability-based magnitude of completeness (PMC) and entire magnitude range (EMR) methods, grounded in distinct foundational assumptions and computational principles, we analyzed the 2010–2023 earthquake catalog for the northern margin of the Ordos Block, aiming to assess the detection I probability of earthquakes and the completeness of the earthquake catalog. The PMC method yielded the detection probability distribution for 76 stations in the distance–magnitude space. A scoring metric was designed based on station detection capabilities for small earthquakes in the near field. From the detection probabilities of stations, we inferred detection probabilities of the network for different magnitude ranges and mapped the spatial distribution of the probability-based completeness magnitude. In the EMR method, we employed a segmented model fitted to the observed data to determine the detection probability and completeness magnitude for every grid point in the study region. We discussed the sample dependency and low-magnitude failure phenomena of the PMC method, noting the potential overestimation of detection probabilities for lower magnitudes and the underestimation of <i>M</i><sub>C</sub> in areas with weaker monitoring capabilities. The results obtained via the two methods support these hypotheses. The assessment results indicate better monitoring capabilities on the eastern side of the study area but worse on the northwest side. The spatial distribution of network monitoring capabilities is uneven, correlating with the distribution of stations and showing significant differences in detection capabilities among different stations. The truncation effects of data and station selection affected the evaluation results at the edges of the study area. Overall, both methods yielded detailed descriptions of the earthquake catalog, but careful selection of calculation parameters or adjustments based on the strengths of different methods is necessary to correct potential biases.</p>","PeriodicalId":55500,"journal":{"name":"Applied Geophysics","volume":null,"pages":null},"PeriodicalIF":0.7000,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Geophysics","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s11770-024-1128-1","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
The assessment of the completeness of earthquake catalogs is a prerequisite for studying the patterns of seismic activity. In traditional approaches, the minimum magnitude of completeness (MC) is employed to evaluate catalog completeness, with events below MC being discarded, leading to the underutilization of the data. Detection probability is a more detailed measure of the catalog’s completeness than MC; its use results in better model compatibility with data in seismic activity modeling and allows for more comprehensive utilization of seismic observation data across temporal, spatial, and magnitude dimensions. Using the magnitude–rank method I and Maximum Curvature (MAXC) methods, we analyzed temporal variations in earthquake catalog completeness, finding that MC stabilized after 2010, which closely coincides with improvements in monitoring capabilities and the densification of seismic networks. Employing the probability-based magnitude of completeness (PMC) and entire magnitude range (EMR) methods, grounded in distinct foundational assumptions and computational principles, we analyzed the 2010–2023 earthquake catalog for the northern margin of the Ordos Block, aiming to assess the detection I probability of earthquakes and the completeness of the earthquake catalog. The PMC method yielded the detection probability distribution for 76 stations in the distance–magnitude space. A scoring metric was designed based on station detection capabilities for small earthquakes in the near field. From the detection probabilities of stations, we inferred detection probabilities of the network for different magnitude ranges and mapped the spatial distribution of the probability-based completeness magnitude. In the EMR method, we employed a segmented model fitted to the observed data to determine the detection probability and completeness magnitude for every grid point in the study region. We discussed the sample dependency and low-magnitude failure phenomena of the PMC method, noting the potential overestimation of detection probabilities for lower magnitudes and the underestimation of MC in areas with weaker monitoring capabilities. The results obtained via the two methods support these hypotheses. The assessment results indicate better monitoring capabilities on the eastern side of the study area but worse on the northwest side. The spatial distribution of network monitoring capabilities is uneven, correlating with the distribution of stations and showing significant differences in detection capabilities among different stations. The truncation effects of data and station selection affected the evaluation results at the edges of the study area. Overall, both methods yielded detailed descriptions of the earthquake catalog, but careful selection of calculation parameters or adjustments based on the strengths of different methods is necessary to correct potential biases.
评估地震目录的完整性是研究地震活动规律的先决条件。在传统方法中,采用最小震级完整性(MC)来评估震级目录的完整性,低于 MC 的事件会被舍弃,导致数据利用率不足。与 MC 相比,检波概率是对震级目录完整性更详细的衡量标准;使用检波概率可使地震活动建模中的模型与数据具有更好的兼容性,并可在时间、空间和震级维度上更全面地利用地震观测数据。利用震级秩方法 I 和最大曲率(MAXC)方法,我们分析了地震目录完整性的时间变化,发现 MC 在 2010 年后趋于稳定,这与监测能力的提高和地震台网的密集化密切相关。基于不同的基础假设和计算原理,我们采用基于概率的震级完整性(PMC)和整个震级范围(EMR)方法,分析了鄂尔多斯地块北缘 2010-2023 年的地震目录,旨在评估地震的检出率 I 和地震目录的完整性。PMC 方法得出了距离-震级空间中 76 个台站的检波概率分布。根据台站对近场小地震的探测能力,设计了一个评分标准。根据台站的探测概率,我们推断了不同震级范围的网络探测概率,并绘制了基于概率的完整性震级空间分布图。在 EMR 方法中,我们采用了一个与观测数据拟合的分段模型,以确定研究区域内每个网格点的探测概率和完整性震级。我们讨论了 PMC 方法的样本依赖性和低震级失效现象,注意到低震级的探测概率可能会被高估,而在监测能力较弱的地区,MC 可能会被低估。两种方法得出的结果都支持上述假设。评估结果表明,研究区域东侧的监测能力较强,而西北侧则较弱。网络监测能力的空间分布不均衡,与站点分布相关,不同站点之间的检测能力存在显著差异。数据和站点选择的截断效应影响了研究区域边缘的评估结果。总体而言,两种方法都对地震目录进行了详细描述,但有必要根据不同方法的优势仔细选择计算参数或进行调整,以纠正潜在的偏差。
期刊介绍:
The journal is designed to provide an academic realm for a broad blend of academic and industry papers to promote rapid communication and exchange of ideas between Chinese and world-wide geophysicists.
The publication covers the applications of geoscience, geophysics, and related disciplines in the fields of energy, resources, environment, disaster, engineering, information, military, and surveying.