Cargando…
Assessing Earthquake Forecast Performance Based on b Value in Yunnan Province, China
Many studies have shown that b values tend to decrease prior to large earthquakes. To evaluate the forecast information in b value variations, we conduct a systematic assessment in Yunnan Province, China, where the seismicity is intense and moderate–large earthquakes occur frequently. The catalog in...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8229484/ https://www.ncbi.nlm.nih.gov/pubmed/34201205 http://dx.doi.org/10.3390/e23060730 |
_version_ | 1783712987269300224 |
---|---|
author | Wang, Rui Chang, Ying Miao, Miao Zeng, Zhiyi Chen, Hongyan Shi, Haixia Li, Danning Liu, Lifang Su, Youjin Han, Peng |
author_facet | Wang, Rui Chang, Ying Miao, Miao Zeng, Zhiyi Chen, Hongyan Shi, Haixia Li, Danning Liu, Lifang Su, Youjin Han, Peng |
author_sort | Wang, Rui |
collection | PubMed |
description | Many studies have shown that b values tend to decrease prior to large earthquakes. To evaluate the forecast information in b value variations, we conduct a systematic assessment in Yunnan Province, China, where the seismicity is intense and moderate–large earthquakes occur frequently. The catalog in the past two decades is divided into four time periods (January 2000–December 2004, January 2005–December 2009, January 2010–December 2014, and January 2015–December 2019). The spatial b values are calculated for each 5-year span and then are used to forecast moderate-large earthquakes (M ≥ 5.0) in the subsequent period. As the fault systems in Yunnan Province are complex, to avoid possible biases in b value computation caused by different faulting regimes when using the grid search, the hierarchical space–time point-process models (HIST-PPM) proposed by Ogata are utilized to estimate spatial b values in this study. The forecast performance is tested by Molchan error diagram (MED) and the efficiency is quantified by probability gain (PG) and probability difference (PD). It is found that moderate–large earthquakes are more likely to occur in low b regions. The MED analysis shows that there is considerable precursory information in spatial b values and the forecast efficiency increases with magnitude in the Yunnan Province. These results suggest that the b value might be useful in middle- and long-term earthquake forecasts in the study area. |
format | Online Article Text |
id | pubmed-8229484 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82294842021-06-26 Assessing Earthquake Forecast Performance Based on b Value in Yunnan Province, China Wang, Rui Chang, Ying Miao, Miao Zeng, Zhiyi Chen, Hongyan Shi, Haixia Li, Danning Liu, Lifang Su, Youjin Han, Peng Entropy (Basel) Article Many studies have shown that b values tend to decrease prior to large earthquakes. To evaluate the forecast information in b value variations, we conduct a systematic assessment in Yunnan Province, China, where the seismicity is intense and moderate–large earthquakes occur frequently. The catalog in the past two decades is divided into four time periods (January 2000–December 2004, January 2005–December 2009, January 2010–December 2014, and January 2015–December 2019). The spatial b values are calculated for each 5-year span and then are used to forecast moderate-large earthquakes (M ≥ 5.0) in the subsequent period. As the fault systems in Yunnan Province are complex, to avoid possible biases in b value computation caused by different faulting regimes when using the grid search, the hierarchical space–time point-process models (HIST-PPM) proposed by Ogata are utilized to estimate spatial b values in this study. The forecast performance is tested by Molchan error diagram (MED) and the efficiency is quantified by probability gain (PG) and probability difference (PD). It is found that moderate–large earthquakes are more likely to occur in low b regions. The MED analysis shows that there is considerable precursory information in spatial b values and the forecast efficiency increases with magnitude in the Yunnan Province. These results suggest that the b value might be useful in middle- and long-term earthquake forecasts in the study area. MDPI 2021-06-08 /pmc/articles/PMC8229484/ /pubmed/34201205 http://dx.doi.org/10.3390/e23060730 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Rui Chang, Ying Miao, Miao Zeng, Zhiyi Chen, Hongyan Shi, Haixia Li, Danning Liu, Lifang Su, Youjin Han, Peng Assessing Earthquake Forecast Performance Based on b Value in Yunnan Province, China |
title | Assessing Earthquake Forecast Performance Based on b Value in Yunnan Province, China |
title_full | Assessing Earthquake Forecast Performance Based on b Value in Yunnan Province, China |
title_fullStr | Assessing Earthquake Forecast Performance Based on b Value in Yunnan Province, China |
title_full_unstemmed | Assessing Earthquake Forecast Performance Based on b Value in Yunnan Province, China |
title_short | Assessing Earthquake Forecast Performance Based on b Value in Yunnan Province, China |
title_sort | assessing earthquake forecast performance based on b value in yunnan province, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8229484/ https://www.ncbi.nlm.nih.gov/pubmed/34201205 http://dx.doi.org/10.3390/e23060730 |
work_keys_str_mv | AT wangrui assessingearthquakeforecastperformancebasedonbvalueinyunnanprovincechina AT changying assessingearthquakeforecastperformancebasedonbvalueinyunnanprovincechina AT miaomiao assessingearthquakeforecastperformancebasedonbvalueinyunnanprovincechina AT zengzhiyi assessingearthquakeforecastperformancebasedonbvalueinyunnanprovincechina AT chenhongyan assessingearthquakeforecastperformancebasedonbvalueinyunnanprovincechina AT shihaixia assessingearthquakeforecastperformancebasedonbvalueinyunnanprovincechina AT lidanning assessingearthquakeforecastperformancebasedonbvalueinyunnanprovincechina AT liulifang assessingearthquakeforecastperformancebasedonbvalueinyunnanprovincechina AT suyoujin assessingearthquakeforecastperformancebasedonbvalueinyunnanprovincechina AT hanpeng assessingearthquakeforecastperformancebasedonbvalueinyunnanprovincechina |