مجله ژئوفیزیک ایران

مجله ژئوفیزیک ایران

Uncertainty estimation in earthquake magnitude determination using high-rate GPS data with Bootstrap method

نوع مقاله : مقاله پژوهشی‌

نویسندگان
1 M.Sc., Department of Geomatics Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
2 Associate Professor, Department of Geomatics Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
چکیده
Accurate analysis of earthquake magnitude and evaluation of its associated uncertainty are fundamental topics in seismology and disaster management. In this study, the earthquake magnitudes were estimated using high-rate GPS data for three major events: the 2011 Tohoku earthquake (Mw 9.1), the 2021 Chignik earthquake (Mw 8.2), and the 2018 Anchorage earthquake (Mw 7.1). The final estimated magnitudes using the proposed method were approximately Mw 9.25 for Tohoku, Mw 8.27 for Chignik, and Mw 7.08 for Anchorage, closely aligning with official reports. High-rate GPS data, due to their ability to precisely capture real-time crustal displacements, were utilized as the primary data source. These data provided valuable information on maximum displacement, dominant period, and epicentral distance, and were employed for estimating earthquake magnitude and analyzing uncertainty. To analyze the data, combinations of different GPS stations were used to minimize the impact of noisy data and achieve more stable results. The application of the Bootstrap statistical method reduced uncertainty values significantly from approximately 0.0039 to 0.0011 for Tohoku, 0.0031 to 0.0019 for Chignik, and 0.004 to 0.0015 for Anchorage. These results demonstrate the statistical robustness and effectiveness of the proposed approach. Compared to conventional seismic methods, which suffer from data clipping and saturation for large magnitudes, the high-rate GPS method provided stable and unbiased magnitude estimates without signal saturation issues. The findings underscore the importance of expanding GPS networks in tectonically active regions, integrating seismic and GPS data, and employing advanced algorithms for data processing. Furthermore, the research emphasizes the role of comprehensive data analysis in improving early earthquake warning systems. By incorporating high-rate GPS data with traditional seismic data, the precision and reliability of early warning systems can be significantly enhanced, ultimately reducing the potential for loss of life and property. Additionally, this study highlights the necessity of strengthening infrastructure resilience and investing in advanced monitoring technologies. In conclusion, this research successfully demonstrates that high-rate GPS data, combined with the Bootstrap method, can accurately estimate earthquake magnitudes, reduce uncertainty, and enhance the reliability of seismic assessments. These findings contribute to the development of more effective earthquake early warning systems and risk mitigation strategies.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Uncertainty estimation in earthquake magnitude determination using high-rate GPS data with Bootstrap method

نویسندگان English

Sara Bahrami Asl 1
Khalil Bakhtiari Asl 1
Khosro Moghtased- Azar 2
1 M.Sc., Department of Geomatics Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
2 Associate Professor, Department of Geomatics Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
چکیده English

Accurate analysis of earthquake magnitude and evaluation of its associated uncertainty are fundamental topics in seismology and disaster management. In this study, the earthquake magnitudes were estimated using high-rate GPS data for three major events: the 2011 Tohoku earthquake (Mw 9.1), the 2021 Chignik earthquake (Mw 8.2), and the 2018 Anchorage earthquake (Mw 7.1). The final estimated magnitudes using the proposed method were approximately Mw 9.25 for Tohoku, Mw 8.27 for Chignik, and Mw 7.08 for Anchorage, closely aligning with official reports. High-rate GPS data, due to their ability to precisely capture real-time crustal displacements, were utilized as the primary data source. These data provided valuable information on maximum displacement, dominant period, and epicentral distance, and were employed for estimating earthquake magnitude and analyzing uncertainty. To analyze the data, combinations of different GPS stations were used to minimize the impact of noisy data and achieve more stable results. The application of the Bootstrap statistical method reduced uncertainty values significantly from approximately 0.0039 to 0.0011 for Tohoku, 0.0031 to 0.0019 for Chignik, and 0.004 to 0.0015 for Anchorage. These results demonstrate the statistical robustness and effectiveness of the proposed approach. Compared to conventional seismic methods, which suffer from data clipping and saturation for large magnitudes, the high-rate GPS method provided stable and unbiased magnitude estimates without signal saturation issues. The findings underscore the importance of expanding GPS networks in tectonically active regions, integrating seismic and GPS data, and employing advanced algorithms for data processing. Furthermore, the research emphasizes the role of comprehensive data analysis in improving early earthquake warning systems. By incorporating high-rate GPS data with traditional seismic data, the precision and reliability of early warning systems can be significantly enhanced, ultimately reducing the potential for loss of life and property. Additionally, this study highlights the necessity of strengthening infrastructure resilience and investing in advanced monitoring technologies. In conclusion, this research successfully demonstrates that high-rate GPS data, combined with the Bootstrap method, can accurately estimate earthquake magnitudes, reduce uncertainty, and enhance the reliability of seismic assessments. These findings contribute to the development of more effective earthquake early warning systems and risk mitigation strategies.

کلیدواژه‌ها English

High- rate GPS, Bootstrap, earthquake magnitude
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