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学者姓名：荣棉水
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Abstract ：
The noise horizontal-to-vertical spectral ratio (NHV) has been applied for inverting subsurface velocity structures, but the non-uniqueness issue in the inversion remains prominent. Parameter sensitivity analysis is crucial for understanding the extent to which parameters influence inversion results, providing reasonable value ranges for each parameter, and offering rational constraints to mitigate the non-uniqueness of solutions. This study takes 636 sites from the KiK-net network as benchmark sites and employs the Monte Carlo method based on Toro's statistical model to generate 200 random samples for each site's shear wave velocity (V-S), compressional wave velocity (V-P), layer thickness (h), and density (rho) parameters. These random samples are then combined into six scenarios, serving as the stochastic site models for uncertainty analysis. Finally, based on the diffuse field assumption (DFA) for NHV forward modeling, the NHVs and their standard deviations are calculated for each scenario. The standard deviations of NHV are further utilized to conduct a sensitivity analysis of soil layer parameter uncertainties' impact on NHV. The results indicate: 1) The NHV peak frequency (f(peak)) is most sensitive to the V-S and h combination, followed by the V-S and rho combination. Among single-parameter scenarios, fpeak is most sensitive to V-S, followed by h, and relatively insensitive to V(P )and rho. 2) The NHV peak amplitude (Apeak) is most sensitive to the V-S and rho combination, followed by the V(S )and h combination. Among singleparameter scenarios, Apeak is most sensitive to V-S, approaching the sensitivity level of the V-S and h combination, followed by rho, and relatively insensitive to h and V-P. 3) Within the 0.1-50 Hz frequency band, the NHV curve is most sensitive to the V-S and h combination, followed by the V-S and rho combination, and the singleparameter V-S scenario. Among single-parameter scenarios, the NHV curve is secondly sensitive to h, while its sensitivity to V-P and rho is relatively low. The sensitivity patterns of NHV to soil parameters revealed in this study are widely applicable, providing effective constraints for NHV inversion, assisting in optimizing parameter combinations, assessing the feasibility of inversion schemes and the credibility of results, and offering beneficial insights for improving the efficiency of the inversion process.
Keyword ：
Soil properties Soil properties Monte Carlo simulation technique Monte Carlo simulation technique Noise horizontal-to-vertical spectral ratio Noise horizontal-to-vertical spectral ratio Uncertainty Uncertainty Cluster analysis Cluster analysis (NHV) (NHV)
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| GB/T 7714 | Wang, Jixin , Li, Xiaojun , Rong, Mianshui et al. Influence of soil parameter uncertainties on site ambient noise horizontal to vertical spectral ratio modeling [J]. | SOIL DYNAMICS AND EARTHQUAKE ENGINEERING , 2024 , 187 . |
| MLA | Wang, Jixin et al. "Influence of soil parameter uncertainties on site ambient noise horizontal to vertical spectral ratio modeling" . | SOIL DYNAMICS AND EARTHQUAKE ENGINEERING 187 (2024) . |
| APA | Wang, Jixin , Li, Xiaojun , Rong, Mianshui , Zhao, Qingxu , Kong, Xiaoshan . Influence of soil parameter uncertainties on site ambient noise horizontal to vertical spectral ratio modeling . | SOIL DYNAMICS AND EARTHQUAKE ENGINEERING , 2024 , 187 . |
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Abstract ：
The seismic activity in the north-south seismic belt of China is among the highest in the world. Predicting instrumental intensity and magnitude after an earthquake mitigates regional seismic disasters. The standard workflow for prediction involves building empirical formulas using characteristic parameters of the initial arrival seismic wave, but this method has limitations in accuracy. Recent data-driven models have shown promise in predicting instrument intensity and magnitude. Still, this is currently done mainly on a single-task basis and does not consider whether a multi-task model can utilize complementary information from different tasks to improve overall performance. This study proposes a data-driven multi-task model called SeismNet, which can simultaneously predict instrument intensity and magnitude. We tested the effectiveness of SeismNet using ground motion records of the north-south seismic belt of China. The model can predict instrument intensity and magnitude more rapidly and accurately than the baseline and single-task models, with increasing accuracy as the input seismic wave duration increases. We also tested the method on three destructive earthquake events (Ms > 6.5) that occurred in China and found that at 3 s after the P-wave arrival, the prediction is almost consistent with the observation. Overall, this study offers a new method for improving earthquake prediction accuracy in the North-South seismic belt of China.
Keyword ：
Earthquake early warning Earthquake early warning Instrumental intensity Instrumental intensity North-South seismic belt of China North-South seismic belt of China Magnitude Magnitude Data-driven Data-driven
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| GB/T 7714 | Zhao, Qingxu , Rong, Mianshui , Wang, Jixin et al. An end-to-end multi-task network for early prediction of the instrumental intensity and magnitude in the north-south seismic belt of China [J]. | JOURNAL OF ASIAN EARTH SCIENCES , 2024 , 276 . |
| MLA | Zhao, Qingxu et al. "An end-to-end multi-task network for early prediction of the instrumental intensity and magnitude in the north-south seismic belt of China" . | JOURNAL OF ASIAN EARTH SCIENCES 276 (2024) . |
| APA | Zhao, Qingxu , Rong, Mianshui , Wang, Jixin , Li, Xiaojun . An end-to-end multi-task network for early prediction of the instrumental intensity and magnitude in the north-south seismic belt of China . | JOURNAL OF ASIAN EARTH SCIENCES , 2024 , 276 . |
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Abstract ：
The imaging of subsurface soil velocity structures from ambient noise inversion is a difficult problem. Few recording points and a simplified 1-D layered profile lead to important nonuniqueness. From our point of view, improving the reliability of processing methods of the observed data to obtain noise horizontal-to-vertical spectral ratio (NHV) curves and setting a complete model parameter space are important tasks to reduce the non-uniqueness of inversion. In this study, using a local site near the border of the Tonghai Basin, China, as a case study, we first demonstrate how to identify and mitigate the influence of industrial sources using surface observations to obtain more reliable NHV curves. Then, a new strategy to determine model parameter space is proposed, that is, stratifying soil layers based on the number of NHV peaks and determining the shear wave velocities, thicknesses, and their ranges based on the empirical relationship between sedimentary thickness and resonant frequency (h-fr). Subsequently, combining the model parameter space acquisition strategy with the NHV inversion, a novel NHV inversion approach is developed and applied to obtain the 2-D VS profile of the investigated Tonghai site. The inverted 2-D VS profile aligns favorably with the frequency-depth conversion results of the measured NHV curves (NHV-profiling) and the measured borehole profiles, affirming the reliability of the proposed NHV inversion method. Finally, by comparing the empirical transfer functions from the strong-motion recordings, we validated the applicability of the inverted models for characterizing site effects. The model parameter space acquisition strategy proposed in this paper and the analysis procedure of the observed data are also applicable to other study areas, which can provide a referable approach to quickly and effectively acquire the soil layer velocity structure of the site.
Keyword ：
Noise horizontal-to-vertical spectral ratio Noise horizontal-to-vertical spectral ratio Empirical relationship Empirical relationship (NHV) (NHV) Shear wave velocity Shear wave velocity Resonance frequency Resonance frequency Initial model Initial model
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| GB/T 7714 | Wang, Jixin , Rong, Mianshui , Li, Xiaojun . Inversion method of NHV based on novel model parameter space acquisition strategy and its application in the Tonghai basin site in Yunnan, China [J]. | HELIYON , 2024 , 10 (17) . |
| MLA | Wang, Jixin et al. "Inversion method of NHV based on novel model parameter space acquisition strategy and its application in the Tonghai basin site in Yunnan, China" . | HELIYON 10 . 17 (2024) . |
| APA | Wang, Jixin , Rong, Mianshui , Li, Xiaojun . Inversion method of NHV based on novel model parameter space acquisition strategy and its application in the Tonghai basin site in Yunnan, China . | HELIYON , 2024 , 10 (17) . |
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Abstract ：
The north-south seismic belt of China poses a high risk of earthquakes, necessitating the need for accurate and rapid prediction of intensity measures (IMs) to prevent and mitigate potential damage. We have developed a new multi-task model, CRAQuake, to predict IMs for the north-south seismic belt of China. Using initial arrival seismic waves recorded at a single station as input, CRAQuake simultaneously predicts six IMs without relying on pre-configured parameters such as earthquake source, path, and location. The model was trained on 4,281 sets of strong motion records data sets at 822 stations and tested to show highly correlated results with the target IMs. The prediction performance continues to improve as the input initial arrival seismic wave time window increases. CRAQuake promises to enhance the accuracy and timeliness of IMs prediction in the north-south seismic belt of China. The north-south seismic belt of China, a region at high risk for earthquakes, necessitates the accurate and rapid prediction of earthquake intensity measures (IMs) to minimize potential damage. We have developed a powerful tool, CRAQuake, to address this critical need. This advanced model leverages initial seismic waves recorded at a single station to simultaneously predict six different IMs without relying on preset information like earthquake source, path, or location. Trained on a vast data set of strong motion records from 822 stations, our testing has shown that CRAQuake's predictions are highly aligned with the actual IMs. Furthermore, increasing the time window of the initial seismic waves used as input significantly improves the model's prediction accuracy. With CRAQuake, we can look forward to more accurate and timely predictions of IMs in the north-south seismic belt of China, empowering us to better prepare for and respond to earthquakes. CRAQuake: a model for the simultaneous prediction of six different intensity measures based on data-driven techniques Model performance tested by earthquake events in the north-south seismic belt of China The model can improve accuracy and timeliness as the input seismic wave is continuously updated
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| GB/T 7714 | Zhao, Qingxu , Rong, Mianshui , Zhang, Bin et al. An All-In-One Rapid Prediction of Ground Motion Intensity Measures Hybrid Network for Multi-Task in the North-South Seismic Belt of China [J]. | EARTH AND SPACE SCIENCE , 2024 , 11 (10) . |
| MLA | Zhao, Qingxu et al. "An All-In-One Rapid Prediction of Ground Motion Intensity Measures Hybrid Network for Multi-Task in the North-South Seismic Belt of China" . | EARTH AND SPACE SCIENCE 11 . 10 (2024) . |
| APA | Zhao, Qingxu , Rong, Mianshui , Zhang, Bin , Li, Xiaojun . An All-In-One Rapid Prediction of Ground Motion Intensity Measures Hybrid Network for Multi-Task in the North-South Seismic Belt of China . | EARTH AND SPACE SCIENCE , 2024 , 11 (10) . |
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