Journal of Seismology最新文献

{"title":"Prediction of the Effective Acceleration-to-Velocity (EPA/EPV) Ratio Using Hyperparameter-Optimized and Physically Interpretable Machine Learning Models Based on Regional Seismic Data","authors":"Tugce Tetik,&nbsp;Pınar Cihan","doi":"10.1007/s10950-026-10455-8","DOIUrl":"10.1007/s10950-026-10455-8","url":null,"abstract":"<div><p>Accurate characterization of ground-motion intensity measures is essential for seismic hazard assessment and performance-based earthquake engineering. Although peak-based measures such as PGA and PGV are widely used, their sensitivity to transient spikes limits their ability to represent sustained seismic energy demand. In contrast, Effective Peak Acceleration (EPA) and Effective Peak Velocity (EPV), derived from averaged spectral ordinates over defined period ranges, provide a more physically consistent representation for evaluating ground-motion frequency characteristics. Therefore, the EPA/EPV ratio offers a relatively robust indicator of effective seismic demand. This study develops machine learning models to predict the EPA/EPV ratio using a regional strong-motion dataset from Türkiye consisting of 18,250 records from 747 earthquakes. Source, path, and site parameters, including magnitude, rupture geometry, distance measures, and Vs₃₀, were used as predictors. Five machine learning algorithms, including Random Forest, Gradient Boosting Regression, XGBoost, LightGBM, and CatBoost, were evaluated under baseline conditions and three hyperparameter optimization strategies: Grid Search, Random Search, and Bayesian Optimization. The results show that boosting-based algorithms outperform the bagging-based model in predicting the EPA/EPV ratio. Among all tested configurations, the Bayesian Optimization-tuned CatBoost model achieved the best overall performance, with R² = 0.809, r = 0.900, and RMSE = 1.593. Wilcoxon signed-rank test results confirmed that the observed performance improvements after optimization were statistically significant. SHAP-based analyses further revealed that Vs₃₀, rupture width, and source-station distance metrics are the most influential predictors. Overall, the proposed framework provides a reliable and physically interpretable data-driven approach for predicting effective ground-motion parameters.</p></div>","PeriodicalId":16994,"journal":{"name":"Journal of Seismology","volume":"30 5","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149035036","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multi-reference event approach to earthquake relocation: insights from the West Bohemia Swarm Zone (Czech Republic, 2000–2025)","authors":"Diana Konrádová,&nbsp;Jana Doubravová,&nbsp;Bohuslav Růžek,&nbsp;Jan Burjánek","doi":"10.1007/s10950-026-10452-x","DOIUrl":"10.1007/s10950-026-10452-x","url":null,"abstract":"<p>The intraplate West Bohemia region represents one of the most prominent areas of recurrent earthquake swarm activity in Central Europe, with ongoing seismicity observed through 2025. We relocated this activity using the new multi-reference event (MRE) method and compared the results with GrowClust (GC) relative locations. The MRE approach provides precise relative locations even for small events and can be applied efficiently to long-term, large catalogs. Its key advantage lies in the ability to incrementally incorporate new events without reprocessing the entire dataset, making it suitable for continuous and real-time monitoring. The comparison demonstrates that the newly developed MRE approach produces results that are consistent with those of the established GC method. Both methods produce a consistent image of the southern and northern parts of the swarm, while the central segment of the active Nový Kostel seismic zone shows the strongest differences. The MRE results are sensitive to the quality of reference event locations, occasionally leading to scattered clusters where input locations are less reliable. In contrast, GC systematically sharpens the seismicity distribution and produces more compact structures. Overall, these results provide the first comprehensive view of the relocated seismicity in the West Bohemia region, extended through 2025, and reveal characteristic migration trends in the activity.</p>","PeriodicalId":16994,"journal":{"name":"Journal of Seismology","volume":"30 5","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148986903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Velocity changes in the Haichenghe fault zone in Liaoning, China revealed by S-coda of repeating microearthquakes","authors":"Qingshan Sun,&nbsp;Zihao Li,&nbsp;Liang Wang,&nbsp;Zhihong Zhang,&nbsp;Zhenpeng Yang,&nbsp;Zhengdong Cui","doi":"10.1007/s10950-026-10454-9","DOIUrl":"10.1007/s10950-026-10454-9","url":null,"abstract":"<div><p>Monitoring temporal seismic velocity changes within active fault zones provides critical insights into crustal stress evolution and earthquake nucleation processes. Leveraging high-density observational data from the Liaoning Seismic Network and the Haicheng Dense Array, we identified 37 repeating sequences (comprising 89 events) and applied coda wave interferometry (CWI) to measure relative seismic velocity changes within the fault zone. Velocity variations show substantial overall dispersion, with their stability jointly governed by sequence duration and epicentral distance. A limited number of continual-type sequences indicate a steady slip process at a depth of approximately 10 km, whereas the predominant burst-type sequences reflect rapid adjustments in the localized fault stress state. The coexistence of these distinct sequence types underscores the pronounced heterogeneity of deep deformation within the fault zone. Notably, although sequence S36 exhibited a pre-seismic velocity increase of ~ 0.1% prior to the <i>M</i>_L 3.7 earthquake, this anomaly failed to achieve statistical significance after accounting for background noise and applying multiple-testing corrections. This study demonstrates that monitoring seismic precursors using repeating earthquakes is limited by methodological and observational constraints. Combined, these limitations restrict the detection of long-term repeating sequences and statistically significant pre-seismic velocity changes.</p></div>","PeriodicalId":16994,"journal":{"name":"Journal of Seismology","volume":"30 5","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10950-026-10454-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heterogeneous mantle beneath the Indo-Burmese Wedge inferred from null splitting analysis: Tectonic implications","authors":"Satyapriya Biswal,&nbsp;Debasis D. Mohanty","doi":"10.1007/s10950-026-10450-z","DOIUrl":"10.1007/s10950-026-10450-z","url":null,"abstract":"<div><p>Null measurements from the splitting of core-mantle refracted phases at 17 broadband seismic stations located in the Indo-Burmese Wedge (IBW) are analyzed to reveal important information on the geometry and intensity of seismic anisotropy in this highly heterogeneous region. These observations highlight the significance of intricate large-scale tectonic processes controlling the deformation patterns. The present study emphasizes the importance of null measurements, which are often overlooked or under-emphasized in research, and achieves a methodical interpretation of their distribution that can greatly improve our understanding of the anisotropic structure, including its geometry, intensity, and heterogeneity. The origin and occurrences of null measurements in a highly anisotropic medium like IBW are investigated, considering the back-azimuthal distribution of events, source polarization, and the rotation of the fast and slow axes. We identified the empirical relations of null measurements with the significant splitting parameters obtained from the same IBW region and categorized them according to their origin. Our effort makes sense in understanding the reasons for null occurrences in a highly anisotropic medium (IBW), though nulls are common in the isotropic medium. The origin and characterization of nulls lead to an unstable subsurface condition beneath the IBW, which could be attributed to a combined effect of collisional tectonics, asthenospheric drag due to absolute plate motion, and coherent lithospheric strain derived from oblique convergence.</p></div>","PeriodicalId":16994,"journal":{"name":"Journal of Seismology","volume":"30 5","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A real-time seismic intensity prediction model based on long short-term memory neural network","authors":"Xu Zheng,&nbsp;Zhang Hui,&nbsp;Jiaolei Zhang","doi":"10.1007/s10950-026-10453-w","DOIUrl":"10.1007/s10950-026-10453-w","url":null,"abstract":"<div><p>Real-time seismic intensity prediction enables the estimation of the maximum potential impact of an earthquake by analyzing P-waves before the arrival of destructive S-waves. This capability allows earthquake early warning systems to implement timely measures aimed at reducing potential damage. Among the various parameters used in seismic analysis, the peak P-wave displacement amplitude has proven effective for estimating peak ground motion. However, relying on one or several predefined parameters often fails to capture the complete information contained in the ground motion. Furthermore, the need to define a fixed time window can hinder continuous updating, which limits the effectiveness of early warnings. To address these challenges, this paper proposes a prediction model based on Long Short-Term Memory (LSTM) networks. The model is constructed using seismic data from the K-NET network spanning 2010–2021, with a case study based on the <i>M</i>_JMA7.3 earthquake event of March 2022 to validate the model’s performance. The proposed LSTM model demonstrates the ability to predict seismic intensity continuously at each time step following the arrival of the P-wave. The model achieves an impressive accuracy of 96.47% on the test set, reaching this level just 3 s after the P-wave arrival. This model significantly enhances the accuracy and continuity of intensity predictions compared to traditional methods and offers a robust foundation for earthquake early warning systems and emergency response strategies.</p></div>","PeriodicalId":16994,"journal":{"name":"Journal of Seismology","volume":"30 5","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time-dependent magnitude homogenization and its impact on seismic completeness, b-values, and aftershock productivity: insights from the New Zealand earthquake catalogue","authors":"Antonino D’Alessandro","doi":"10.1007/s10950-026-10451-y","DOIUrl":"10.1007/s10950-026-10451-y","url":null,"abstract":"<div><p>Earthquake catalogues commonly integrate heterogeneous magnitude scales whose relationships evolve in time and space, introducing systematic biases in statistical seismology. Here I quantify the impact of magnitude-scale heterogeneity using the GeoNet earthquake catalogue (New Zealand, 2003–2025). I develop a time-dependent magnitude homogenization framework based on moment tensor solutions, deriving a proxy moment magnitude <span>({M}_{w}^{*})</span> through sliding-window regressions. The relationship between catalogue magnitude and moment magnitude is strongly non-stationary, with significant temporal variations in both slope and intercept, as well as spatial differences across tectonic domains. These variations propagate directly into seismicity metrics. When evaluated on a common magnitude scale, the magnitude of completeness <span>({M}_{c})</span> is systematically higher than that inferred from the original catalogue, with local discrepancies exceeding one magnitude unit. Similarly, when both estimates are expressed on a common homogenized magnitude scale, residual b-value differences are generally modest but temporally and spatially structured, indicating that a substantial fraction of the apparent discrepancy is explained by the non-stationary magnitude transformation itself. The strongest effects are observed in clustering properties: although aftershock productivity follows an exponential scaling with magnitude in both representations, homogenized magnitudes yield a steeper productivity exponent (α ≈ 1.08 vs. 1.01) and a reduced branching proxy. These results demonstrate that magnitude heterogeneity introduces coherent, scale-dependent distortions in completeness, <i>b</i>-value, and clustering metrics, potentially leading to misinterpretation of seismicity patterns if not explicitly accounted for.</p></div>","PeriodicalId":16994,"journal":{"name":"Journal of Seismology","volume":"30 5","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10950-026-10451-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148926739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A local magnitude relation for the Philippines based on strong-motion records","authors":"Rhommel Grutas,&nbsp;Osamu Kamigaichi,&nbsp;Joshua Daniel Sumaoi,&nbsp;Winchelle Ian Sevilla","doi":"10.1007/s10950-026-10423-2","DOIUrl":"10.1007/s10950-026-10423-2","url":null,"abstract":"<div><p>The Philippine Strong Motion Network (PSMNet), established in 1992, is one of the primary seismic monitoring systems in the Philippines and consists of strong-motion accelerographs deployed to record earthquake ground motions. In this study, strong-motion records collected from 2019 to 2023 were analyzed to develop attenuation relations and local magnitude models tailored to Philippine seismic conditions. The dataset consists of 3,176 waveform records from 527 shallow earthquake events (<span>(varvec{M}_{varvec{w}} varvec{ge } varvec{5.0})</span>) recorded across the PSMNet. Peak ground displacement values were obtained from processed acceleration waveforms, and a two-step stratified regression analysis was applied to determine the geometrical spreading and attenuation coefficients. Three high-pass filter cutoff periods (<span>(varvec{T}_{varvec{c}} varvec{= 5, 10,})</span> and <span>(varvec{20} varvec{s})</span>) were evaluated, producing corresponding magnitude models with RMSE values of 0.324, 0.305, and 0.297, respectively. Paired bootstrap tests indicate that the reductions in RMSE with increasing cutoff period are statistically significant, with the <span>(varvec{T}_{varvec{c}} varvec{=} varvec{20}text {s})</span> model showing the best overall performance. Independent validation using independent 2024 strong-motion data also demonstrated comparable predictive capability, with RMSE values ranging from 0.350 to 0.386. The proposed magnitude relations provide a region-specific framework for rapid earthquake magnitude estimation using strong-motion data and may support future improvements in real-time seismic monitoring and earthquake early warning applications in the Philippines.</p></div>","PeriodicalId":16994,"journal":{"name":"Journal of Seismology","volume":"30 5","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10950-026-10423-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148926772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Testing seismic hazard assessment: the 2025 Myanmar earthquake","authors":"Vladimir Kossobokov,&nbsp;Anastasia Nekrasova","doi":"10.1007/s10950-026-10449-6","DOIUrl":"10.1007/s10950-026-10449-6","url":null,"abstract":"<div><p>The M7.7 Mandalay earthquake in Myanmar occurred on 28 March 2025 at 12:50:54 local time, with an epicenter at 22.013°N, 95.922°E and a focal depth of 10 km. The event produced extreme to severe ground shaking affecting more than 7.5 million people. This earthquake ranks among the deadliest events since 2000 highlighting once again the limitations of Probabilistic Seismic Hazard Analysis (PSHA) and the existing global maps, whose estimates of ground shaking at Mandalay City were exceeded by a factor greater than 4. Notably, at the site of the main shock, the 2019 Global GEM Seismic Hazard Map provides peak ground acceleration estimates approximately 20% lower than those of the 1999 GSHAP Final Map, revealing substantial discrepancies between global models used for seismic risk assessment and disaster-prevention planning. Within the framework of the Global Test of Predictions conducted in real time since 1992, both the M8 and M8-MSc algorithms had identified the region as prone to a major earthquake of magnitude M7.5 + beginning in January 2021, with subsequent semiannual updates, most recently in January 2025, maintaining the alert through mid-2027. The MSc refinement further delineated a 390-km-long segment of the Myanmar Central Basin as the most probable area of occurrence, missing the epicenter of the M7.7 main shock by approximately 70 km. Although future relocation of the event may adjust these estimates, the earthquake contributes a confirmed “success” for the M8 algorithm and a “failure” for its MSc refinement in the ongoing real-time evaluation of intermediate-term seismic predictions. </p></div>","PeriodicalId":16994,"journal":{"name":"Journal of Seismology","volume":"30 5","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148926608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seismic site response under variable shear wave velocity models: application to Jamshedpur, India","authors":"Suryakant Kumar Sisodiya,&nbsp;Awdhesh Kumar Choudhary,&nbsp;Keshav Kumar Sharma,&nbsp;Shiv Shankar Kumar","doi":"10.1007/s10950-026-10447-8","DOIUrl":"10.1007/s10950-026-10447-8","url":null,"abstract":"<p>This study evaluates the influence of shear wave velocity (Vs) characterization on seismic site response in Jamshedpur, India. To understand these effects, a one-dimensional equivalent linear ground response analysis has been performed for three distinct shear wave velocity inputs: Vs profiles obtained from the MASW method, Vs profiles obtained from established correlations between Vs and SPT-N values, and the mean shear wave velocity measured for the top 30 m of ground (Vs30). Subsurface conditions at 15 locations were characterized using Multichannel Analysis of Surface Waves (MASW) surveys and borehole investigations. The estimated Vs30 values range from 213 to 493 m/s and were used to categorize and describe these sites according to NEHRP seismic site classification, and the majority of sites fall in seismic site class C, and a few fall in seismic site class D. Four recorded ground motions with PGA values of 0.1 g, 0.16 g, 0.28 g, and 0.41 g have been used to evaluate site behavior under varying shaking intensities. The findings showed that predicted site response is more site-sensitive to the selected Vs model. Surface acceleration increased from 0.20 to 0.35 g, 0.4 to 0.7 g, 0.7 to 1.2 g, and 1 to 1.5 g for 0.10 g, 0.16 g, 0.28 g, and 0.41 g input motion, respectively. Computed amplification ratios varied across the study area, ranging from 1.0 to 5.1. Peak spectral acceleration (PSA) showed substantial spatial variability and increased with shaking intensity, depending on site conditions, input motion, and Vs representation. PSA values ranged from 0.3681 to 9.5938 g under input PGA values of 0.10–0.41 g, indicating significant resonance induced amplification despite moderate earthquake shaking. MASW based profiles tended to predict higher amplification and spectral acceleration values at several locations for moderate to strong shaking, as they were able to represent local subsurface heterogeneity and near-surface variability. Empirical correlation based profiles tend to underestimate PSA values, while Vs30 performs reasonably for low PGA but fails to reflect site-specific heterogeneity at higher PGA. The results can provide essential guidance for microzonation, seismic hazard assessment, and earthquake-resilient urban planning in Jamshedpur.</p>","PeriodicalId":16994,"journal":{"name":"Journal of Seismology","volume":"30 5","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148926609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-time estimation of earthquake early warning magnitude using a hybrid dataset of observed and simulated P-wave onsets for the Himachal Himalaya (Mw 4.0–8.5)","authors":"Suraj Kumar Pal,&nbsp; Sandeep,&nbsp;Parveen Kumar,&nbsp; Monika,&nbsp;Pragya Singh,&nbsp;Vikas Singh,&nbsp;Himanshu Mittal","doi":"10.1007/s10950-026-10448-7","DOIUrl":"10.1007/s10950-026-10448-7","url":null,"abstract":"<div><p>The Himachal Himalaya, located in the northwestern segment of the Himalayan arc, is one of the most seismically active regions in the Indian Himalaya. This study aims to develop new magnitude scaling relations for this region utilizing a mixed dataset of observed and simulated P-wave onsets. This work employs modified semi empirical technique (MSET) to simulate ground motion records, particularly P-wave. This technique is validated for 3 different instrumentally recorded earthquakes with magnitude (<i>M</i>_<i>w</i>) ranging from 4.2 to 5.1. Further, we utilized this method to simulate 30 future scenario earthquakes ranging from <i>M</i>_<i>w</i> 5.0 to 8.5. The earthquake early warning parameters including average period (<i>τ</i>_<i>c</i>), peak displacement amplitude (<i>P</i>_<i>d</i>), and cumulative absolute velocity (<i>CAV</i>) are extracted from the P-wave onsets of 61 observed and 450 simulated records. Using this observed and simulated dataset, the developed magnitude scaling relations <i>τ</i>_<i>c</i>–<i>M</i>_<i>w</i>, <i>P</i>_<i>d</i>–<i>M</i>_<i>w</i>, and <i>CAV</i>–<i>M</i>_<i>w</i> are validated using the available instrumentally recorded event up to <i>M</i>_<i>w</i> 5.1, while their performance at larger magnitudes (<i>M</i>_<i>w</i> 5.0–8.5) are assessed using independently generated synthetic earthquake scenarios from the MSET. This latter validation represents a synthetic self-consistency assessment rather than observational validation. For the synthetic scenarios, the maximum magnitude differences (<i>M</i>_<i>wd</i>) between the cataloged (<i>M</i>_<i>wc</i>) and predicted (<i>M</i>_<i>wp</i>) magnitudes range from 0.18–0.42 for <i>τ</i>_<i>c</i>–<i>M</i>_<i>w</i>, 0.02–0.38 for <i>P</i>_<i>d</i>–<i>M</i>_<i>w</i>, and 0.01–0.53 for <i>CAV</i>–<i>M</i>_<i>w</i>, respectively. Additionally, the threshold values of various parameters are estimated as 2.0 s for <i>τ</i>_<i>c</i>, 0.13 cm for <i>P</i>_<i>d</i>, and 0.03 cm/s for <i>CAV</i>, respectively for onsite warnings of earthquakes with magnitude ≥ 6.0. Using the τ_c × <i>P</i>_<i>d</i> ≥ 1.0 s-cm criterion, several key sites are identified as highly prone to severe damage from large earthquakes. These sites are located at epicentral distance ranging from 50–500 km from the scenario earthquake location and are expected to receive the lead times between 6 and 166 s. This highlights the importance of longer lead times in the Himachal Himalaya for enabling timely early warnings and protective actions.</p></div>","PeriodicalId":16994,"journal":{"name":"Journal of Seismology","volume":"30 5","pages":""},"PeriodicalIF":1.3,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148926263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}