Verification of attenuation models based on strong ground motion data in Northern Thailand
© 2020 Elsevier Ltd Within the last decade, the number of earthquake events in Northern Thailand has significantly increased. At least, two major earthquakes have occurred in this region: the 2011 Mw 6.8 Tarlay Earthquake and the 2014 Mw 6.3 Mae Lao Earthquake. The lack of understanding on appropria...
Saved in:
Main Authors: | , , , |
---|---|
Other Authors: | |
Format: | Article |
Published: |
2020
|
Subjects: | |
Online Access: | https://repository.li.mahidol.ac.th/handle/123456789/53513 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Mahidol University |
id |
th-mahidol.53513 |
---|---|
record_format |
dspace |
spelling |
th-mahidol.535132020-03-26T11:43:05Z Verification of attenuation models based on strong ground motion data in Northern Thailand Weeradetch Tanapalungkorn Lindung Zalbuin Mase Panon Latcharote Suched Likitlersuang Bengkulu University Chulalongkorn University Mahidol University Agricultural and Biological Sciences Earth and Planetary Sciences Engineering © 2020 Elsevier Ltd Within the last decade, the number of earthquake events in Northern Thailand has significantly increased. At least, two major earthquakes have occurred in this region: the 2011 Mw 6.8 Tarlay Earthquake and the 2014 Mw 6.3 Mae Lao Earthquake. The lack of understanding on appropriate attenuation models to represent a specific region becomes a major issue if strong ground motion data is not available. This paper aims to determine an appropriate attenuation model for Northern Thailand based on seven recorded earthquake events in the region. Nine attenuation models, including ground motion prediction equations (GMPEs) from both NGA-West1 and NGA-West2 (Next Generation Attenuation Relationships for Western US), were employed to predict peak ground acceleration (PGA) and spectral acceleration (SA) during the selected earthquake events. Ground motion data during the events from twenty nearby seismic stations were collected for verifying the predictions from each attenuation model. Goodness of fit test and root mean square error (RMSE) were evaluated for each attenuation model prediction. The results show that the NGA-West2 are the most appropriate attenuation models to predict ground motion in Northern Thailand. As a consequence of verifying these attenuation models, it is hoped that further development of Thailand's seismic design standards for seismic hazard analysis of specific regions such as Northern Thailand can be based on more accurate, appropriately selected models. 2020-03-26T04:26:08Z 2020-03-26T04:26:08Z 2020-06-01 Article Soil Dynamics and Earthquake Engineering. Vol.133, (2020) 10.1016/j.soildyn.2020.106145 02677261 2-s2.0-85081738635 https://repository.li.mahidol.ac.th/handle/123456789/53513 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85081738635&origin=inward |
institution |
Mahidol University |
building |
Mahidol University Library |
continent |
Asia |
country |
Thailand Thailand |
content_provider |
Mahidol University Library |
collection |
Mahidol University Institutional Repository |
topic |
Agricultural and Biological Sciences Earth and Planetary Sciences Engineering |
spellingShingle |
Agricultural and Biological Sciences Earth and Planetary Sciences Engineering Weeradetch Tanapalungkorn Lindung Zalbuin Mase Panon Latcharote Suched Likitlersuang Verification of attenuation models based on strong ground motion data in Northern Thailand |
description |
© 2020 Elsevier Ltd Within the last decade, the number of earthquake events in Northern Thailand has significantly increased. At least, two major earthquakes have occurred in this region: the 2011 Mw 6.8 Tarlay Earthquake and the 2014 Mw 6.3 Mae Lao Earthquake. The lack of understanding on appropriate attenuation models to represent a specific region becomes a major issue if strong ground motion data is not available. This paper aims to determine an appropriate attenuation model for Northern Thailand based on seven recorded earthquake events in the region. Nine attenuation models, including ground motion prediction equations (GMPEs) from both NGA-West1 and NGA-West2 (Next Generation Attenuation Relationships for Western US), were employed to predict peak ground acceleration (PGA) and spectral acceleration (SA) during the selected earthquake events. Ground motion data during the events from twenty nearby seismic stations were collected for verifying the predictions from each attenuation model. Goodness of fit test and root mean square error (RMSE) were evaluated for each attenuation model prediction. The results show that the NGA-West2 are the most appropriate attenuation models to predict ground motion in Northern Thailand. As a consequence of verifying these attenuation models, it is hoped that further development of Thailand's seismic design standards for seismic hazard analysis of specific regions such as Northern Thailand can be based on more accurate, appropriately selected models. |
author2 |
Bengkulu University |
author_facet |
Bengkulu University Weeradetch Tanapalungkorn Lindung Zalbuin Mase Panon Latcharote Suched Likitlersuang |
format |
Article |
author |
Weeradetch Tanapalungkorn Lindung Zalbuin Mase Panon Latcharote Suched Likitlersuang |
author_sort |
Weeradetch Tanapalungkorn |
title |
Verification of attenuation models based on strong ground motion data in Northern Thailand |
title_short |
Verification of attenuation models based on strong ground motion data in Northern Thailand |
title_full |
Verification of attenuation models based on strong ground motion data in Northern Thailand |
title_fullStr |
Verification of attenuation models based on strong ground motion data in Northern Thailand |
title_full_unstemmed |
Verification of attenuation models based on strong ground motion data in Northern Thailand |
title_sort |
verification of attenuation models based on strong ground motion data in northern thailand |
publishDate |
2020 |
url |
https://repository.li.mahidol.ac.th/handle/123456789/53513 |
_version_ |
1763488368956538880 |