Search Results (8)

Characterized by frequent earthquakes and a dense population, Yunnan Province, China, faces significant seismic hazards and is a hot place for earthquake forecasting research. In a previous study, we evaluated the performance of the b value for 5-year seismic forecasting during 2000–2019 and made a forward prediction of M ≥ 5.0 earthquakes in 2020–2024. In this study, with the forecast period having passed, we first revisit the results and assess the forward prediction performance. Then, the background seismicity rate, which may also offer valuable long-term forecasting information, is incorporated into earthquake prediction for Yunnan Province. To assess the effectiveness of the prediction, the Molchan Error Diagram (MED), Probability Gain (PG), and Probability Difference (PD) are employed. Using a 25-year catalog, the spatial b value and background seismicity rate across five temporal windows are calculated, and 86 M ≥ 5.0 earthquakes as prediction samples are examined. The predictive performance of the background seismicity rate and b value is comprehensively tested and shown to be useful for 5-year forecasting in Yunnan. The performance of the b value exhibits a positive correlation with the predicted earthquake magnitude. The synergistic effect of combining these two predictors is also revealed. Finally, using the threshold corresponding to the maximum PD, we integrate the forecast information of background seismicity rates and the b value. A forward prediction is derived for the period from January 2025 to December 2029. This study can be helpful for disaster preparedness and risk management in Yunnan Province, China. Full article

There have been reports about anomalies in mobile geomagnetic data before earthquakes; however, whether it can be used as an indicator for identifying potential earthquake areas was not be explored. In this study, we propose two parameters for earthquake forecasting based on annual mobile geomagnetic observation data. The spatial horizontal and three components’ changes are calculated in each year and then used to forecast moderate–large earthquakes (M ≥ 5.0) in southwest China in the subsequent period. It is found that earthquakes are more likely to occur in low H- or F-value regions. We statistically assess their forecasting performance by using Molchan’s error diagram, and the results indicate that there is considerable precursory information in the spatial H and F values. It is concluded that mobile geomagnetic observations might be useful in middle-term earthquake forecasts in the study area. We discuss the physical mechanisms of H and F values to explain their reasonability. The methodology proposed in this study could be helpful in finding out the optimal solution for annual mobile geomagnetic measurements for middle-term earthquake forecasting. Full article

Systematic measurements of water temperature are lacking but useful in understanding the relationship between water temperature and earthquakes. Based on the water temperature data, geological structure, borehole structure, and temperature gradient in the Jinjia well, Southwest China, we systematically analysed the water temperature changes related to earthquakes. The water temperature of the Jinjia well recorded the coseismic changes caused by the Wenchuan M7.9 and Panzhihua M6.1 earthquakes in 2008. We also found abnormal changes in the water temperature, after which moderate to strong earthquakes occurred in the surrounding region. The preseismic abnormal changes of the Jinjia well were rising-recovery (rising to a high value and continuing for a period of time before decreasing or quickly recovering), with the range of 0.007–0.07 °C. The maximum change (0.07 °C) occurred before the M7.9 Wenchuan earthquake in 2008. According to the Molchan error diagram, the most likely time for an earthquake to occur is within approximately 4 months after the water temperature exceeds the threshold temperature. In the Jinjia well, the installation depth of the temperature sensor affected the correlation between the temperature changes and earthquakes with a seismic energy density above 10⁻³ J·m⁻³. The shorter the distance between the sensor and the fault, the higher the probability of water temperature changes related to earthquakes. Full article

Strain rates have been included in multiplicative hybrid modelling of the long-term spatial distribution of earthquakes in New Zealand (NZ) since 2017. Previous modelling has shown a strain rate model to be the most informative input to explain earthquake locations over a fitting period from 1987 to 2006 and a testing period from 2012 to 2015. In the present study, three different shear strain rate models have been included separately as covariates in NZ multiplicative hybrid models, along with other covariates based on known fault locations, their associated slip rates, and proximity to the plate interface. Although the strain rate models differ in their details, there are similarities in their contributions to the performance of hybrid models in terms of information gain per earthquake (IGPE). The inclusion of each strain rate model improves the performance of hybrid models during the previously adopted fitting and testing periods. However, the hybrid models, including strain rates, perform poorly in a reverse testing period from 1951 to 1986. Molchan error diagrams show that the correlations of the strain rate models with earthquake locations are lower over the reverse testing period than from 1987 onwards. Smoothed scatter plots of the strain rate covariates associated with target earthquakes versus time confirm the relatively low correlations before 1987. Moreover, these analyses show that other covariates of the multiplicative models, such as proximity to the plate interface and proximity to mapped faults, were better correlated with earthquake locations prior to 1987. These results suggest that strain rate models based on only a few decades of available geodetic data from a limited network of GNSS stations may not be good indicators of where earthquakes occur over a long time frame. Full 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. Full article

To verify the relationship between AETA (Acoustic and Electromagnetics to Artificial Intelligence (AI)) electromagnetic anomalies and local earthquakes, we have performed statistical studies on the electromagnetic data observed at AETA station. To ensure the accuracy of statistical results, 20 AETA stations with few data missing and abundant local earthquake events were selected as research objects. A modified PCA method was used to obtain the sequence representing the signal anomaly. Statistical results of superposed epoch analysis have indicated that 80% of AETA stations have significant relationship between electromagnetic anomalies and local earthquakes. These anomalies are more likely to appear before the earthquakes rather than after them. Further, we used Molchan’s error diagram to evaluate the electromagnetic signal anomalies at stations with significant relationships. All area skill scores are greater than 0. The above results have indicated that AETA electromagnetic anomalies contain precursory information and have the potential to improve local earthquake forecasting. Full article

In order to clarify ultra-low-frequency (ULF) seismomagnetic phenomena, a sensitive geomagnetic network was installed in Kanto, Japan since 2000. In previous studies, we have verified the correlation between ULF magnetic anomalies and local sizeable earthquakes. In this study, we use Molchan’s error diagram to evaluate the potential earthquake precursory information in the magnetic data recorded in Kanto, Japan during 2000–2010. We introduce the probability gain (PG′) and the probability difference (D′) to quantify the forecasting performance and to explore the optimal prediction parameters for a given ULF magnetic station. The results show that the earthquake predictions based on magnetic anomalies are significantly better than random guesses, indicating the magnetic data contain potential useful precursory information. Further investigations suggest that the prediction performance depends on the choices of the distance (R) and size of the target earthquake events (Es). Optimal R and Es are about (100 km, 10^8.75) and (180 km, 10^8.75) for Seikoshi (SKS) station in Izu and Kiyosumi (KYS) station in Boso, respectively. Full article

Most earthquakes are considered to be caused by stress accumulating in and subsequently releasing from the crust. To extract non-linear and non-stationary earthquake-induced signals associated with stress accumulation, the Hilbert–Huang transform was utilized to filter long-term movements, short-term noise, and frequency-dependent (annual and semi-annual) variations from surface displacements measured by the global positioning system (GPS) in Taiwan. Earthquake-related surface displacements were expressed as horizontal directions (i.e., GPS azimuths) using the north–south and east–west components of residual GPS data to bypass influences resulted from the inhomogeneous nature of the crust. Analytical results showed that the relationships between earthquake occurrence and the aligned GPS azimuth passed the statistical test of the Molchan’s error diagram. Aligned GPS azimuths were in agreement with direction of earthquake-related P axes for 81% (26/32) studied events. Areas with the highest paralleling orientations of GPS azimuths appeared around epicenters several days to weeks before earthquake occurrence. Durations from aligned GPS azimuths to earthquake occurrence are roughly proportional to earthquake magnitude. Similar variations of the GPS azimuths were observed in GPS data containing or excluding co-seismic dislocation (i.e., one day before) in the temporal and spatial domain. These suggest that the aligned GPS azimuth could be a promising anomalous phenomenon for studying crustal deformation before earthquakes. Full article