Acta Geophysica最新文献

{"title":"Multi-site magnetometer observations of the magnetic disturbances due to the Tonga volcanic explosion of January 15, 2022: statistical analyses","authors":"Leonid F. Chernogor","doi":"10.1007/s11600-026-01877-6","DOIUrl":"10.1007/s11600-026-01877-6","url":null,"abstract":"<div><p>For the first time, a statistical study has been conducted on the geomagnetic bay-like and quasi-periodic disturbances based on the datasets collected at 19 recording stations participating in INTERMAGNET Magnetic Observatories. In order to identify the disturbances from the volcanic explosion, a preliminary analysis has been used of the state of space weather during the catastrophic Tonga volcanic explosion of January 15, 2022. We summarize the main results as follows: The non-monotony of the variations in the strength of <i>Y</i> and <i>Z</i> geomagnetic field components increased appreciably on the day of the explosion as compared to the variations observed during the days used as a quiet time reference, while the eastward component of the geomagnetic field exhibited up to a 70 nT increase in variability. The duration and time delay of the bay-like disturbances increased with distance from the volcano, while their amplitude decreased. The propagation speeds of the bay-like disturbances at various observatories were determined to be in the 732–1325 m/s range. Four groups of time delays of quasi-periodic disturbances have been identified in a simultaneous analysis for the first time; they correspond to the apparent speeds of a few hundred km/s, 287–378 m/s, 212–233 m/s, and 130 m/s. The time delay in each group increased with distance away from the volcano. The agreement between theoretical estimates and the observational data testifies to the adequacy of the mechanism adopted for the generation of the disturbances.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147796779","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":"Advancement in forecasting rainfall-runoff process: application of a novel hybrid FMD-SVR-ABC modeling technique","authors":"Redvan Ghasemlounia,&nbsp;Amin Gharehbaghi,&nbsp;Farshad Ahmadi","doi":"10.1007/s11600-026-01878-5","DOIUrl":"10.1007/s11600-026-01878-5","url":null,"abstract":"<div><p>The prediction of monthly rainfall-runoff time series has a significant influence in planning and developing water resources projects. Thus, in this research, a novel advanced coupled predictive disintegration-optimization-based model is developed to improve the forecasting exactness of the mean monthly river’s runoff. The suggested estimation model is a coupled version of the feature mode decomposition (FMD) algorithm and support vector regression (SVR) model optimized with artificial bee colony (ABC) metaheuristic algorithm, <i>i.e.,</i> hybrid FMD-SVR-ABC model. Its performance is tested on monthly Barandouzchay River’s runoff (<i>BCRR</i>_<i>m</i>) watershed in Urmia City, West Azerbaijan Province from Sep 1971 to Aug 2022. In the FMD-based approaches, the optimal amount of mode number for the rainfall time series measured is 5. Using the partial autocorrelation function (PACF) technique, the number of predictor variables is determined as 9. Comparison plots and performance assessment criteria attest that the recommended model under the optimum predictor and meta-parameters tuned, provides better forecasting results with coefficient of determination (<i>R</i>^<i>2</i>) of 0.82, root mean square error (<i>RMSE</i>) of 2.67 (m³/s), mean bias error (<i>MBE</i>) of 0.22 (m³/s), Nash–Sutcliffe efficiency (<i>NSE</i>) of 0.8. Comparatively, the individual SVR model leads to the <i>R</i>^<i>2</i> of 0.36, <i>RMSE</i> of 5.39 (m³/s), <i>MBE</i> of 2.23 (m³/s), and <i>NSE</i> of 0.23. Integrating with FMD and ABC algorithms lessens the <i>RMSE</i> value in the single SVR (as the benchmark model) by 27.8% and 15.7%, respectively. Therefore, the suggested hybrid model can be operated as an ingenious, sensible, and precise predictive model for the evaluation of the sequential rainfall-runoff rivers data, mainly the peak flows in different hydro-climatic regimes.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147797125","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 music-driven hybrid optimization approach for simultaneous pre-stack seismic inversion: a case study","authors":"Ravi Kant,&nbsp;Md Sultanul Arefin,&nbsp;S. P. Maurya","doi":"10.1007/s11600-026-01881-w","DOIUrl":"10.1007/s11600-026-01881-w","url":null,"abstract":"<div><p>This study introduces a novel music-inspired hybrid optimization approach for simultaneous pre-stack seismic inversion, aimed at enhancing the accuracy and efficiency of subsurface property estimation. The proposed method, termed hybrid harmony search optimization (HHSO), combines the global search ability of harmony search optimization (HSO) with the local refinement efficiency of the quasi-Newton method (QNM). While HSO has shown effectiveness in global optimization, its convergence rate can be slow. The integration with QNM addresses this limitation by accelerating convergence and refining the inversion results more effectively. The HHSO algorithm is evaluated using both synthetic and real seismic datasets. For synthetic noise levels up to 30%, HHSO delivers significantly improved estimations of acoustic impedance (<span>({Z}_{p})</span>), shear impedance (<span>({Z}_{text{s}})</span>), and density (<span>(rho)</span>) compared to HSO and QNM methods. Application to real data also shows consistent improvements, with HHSO achieving higher correlations to well-log data (<span>({Z}_{p})</span> = 0.91, <span>({Z}_{text{s}})</span> = 0.89, and <span>(rho)</span> = 0.92) and reducing inversion errors from 1.4 to 0.25. Moreover, HHSO preserves the frequency content of the seismic signal more effectively, which is crucial for maintaining the integrity of seismic data. When applied to full seismic sections, HHSO produces smoother and more continuous images of the subsurface, aiding in the identification of geological features such as layer continuity and sand facies zones. These findings highlight the potential of HHSO as a robust and efficient tool for seismic inversion and reservoir characterization, offering an optimal balance between global exploration and local precision.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147796972","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":"Increase in atmospheric freezing level height in Romania over the 1980–2024 period","authors":"Adrian Piticar,&nbsp;Alexandru Tudor","doi":"10.1007/s11600-026-01874-9","DOIUrl":"10.1007/s11600-026-01874-9","url":null,"abstract":"<div><p>Freezing Level Height (FLH) is the upper boundary in the free atmosphere where water transitions from a liquid or gaseous state to a solid, and it can serve as a valuable indicator of climate change. This research aims to investigate the climatology and changes in FLH across 41 major Romanian cities over a 45-year period (1980–2024). Monthly FLH data were retrieved from the latest ERA5 reanalysis gridded dataset (0.25° × 0.25° horizontal spatial resolution) for each city included in the study. Grid-cell data were directly matched to city centroids. For each city, the ERA5 grid cell whose center was closest to the city centroid was selected for analysis. ArcGIS 10.3.1 software and box-and-whisker plots were used to produce FLH climatologies. Changes in FLH were analyzed using the non-parametric Mann–Kendall test and Sen’s slope estimator. The main findings indicated that cities in southern, southeastern, and western Romania exhibited the highest FLH values across all temporal scales. As expected, higher-elevation cities recorded the lowest FLH values. The seasonal distribution of FLH revealed that the lowest levels occurred in winter, while the highest were observed in summer. FLH during the winter months had a median value ranging from 750 to 1000 m, while in summer, the median ranged from 3250 to 3650 m. The seasonal and annual distributions of FLH data revealed that summer exhibited a wider range of values, particularly for those below the first quartile across the analyzed locations. The trend analysis revealed a clear and statistically significant increase in FLH across all regions of Romania, ranging from 7.44 to 9.26 m per year (on an annual time scale), with only a few non-significant trends observed in winter and spring. The spatiotemporal analysis of changes revealed substantial spatial variability in the magnitude of trends. The strongest trends were observed in summer, while the weakest increases occurred in spring, particularly in central regions. On an annual scale, the most pronounced changes were recorded in the eastern and southeastern areas of Romania.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147796624","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":"Projecting global mean total column water vapor through 2050 using univariate and multivariate time series models","authors":"Tahir Durhasan,&nbsp;Md. Najmul Mowla,&nbsp;Mehmet Bilgili","doi":"10.1007/s11600-026-01847-y","DOIUrl":"10.1007/s11600-026-01847-y","url":null,"abstract":"<div><p>Water vapor strongly influences climate and hydroclimate extremes, and total column water vapor (TCWV) typically increases by about 6–7% per 1 K (Clausius–Clapeyron scaling). This study presents a forecasting framework that combines the seasonal autoregressive integrated moving average (SARIMA) model and long short-term memory (LSTM) networks to project global monthly mean TCWV through 2050. Historical TCWV and near-surface air temperature (<span>(T_{2m})</span>) data from ERA5 (1970–2024) were used to train both univariate and multivariate configurations, with the latter incorporating <span>(T_{2m})</span> to reflect its thermodynamic coupling with atmospheric moisture. Projections were conducted under multiple climate scenarios (CMIP5 and CMIP6) to assess TCWV sensitivity to future emission trajectories. Results show that the multivariate LSTM model outperforms both SARIMA and univariate LSTM baselines, achieving the lowest forecasting error (MAPE = 0.5736 %, RMSE = 0.1811 <span>(hbox {kg}, hbox {m}-{2})</span>, <span>(R = 0.9881)</span>). Under the CMIP6 SSP5− 8.5 scenario, TCWV is projected to increase from 25.63 <span>(hbox {kg}, hbox {m}-{2})</span> in 2024 to 27.08 <span>(hbox {kg}, hbox {m}-{2})</span> by 2050. In the independent test phase, the multivariate LSTM provides a slight improvement over SARIMA (RMSE: 0.1811 vs. 0.1845  kg m<span>(^{-2})</span>). Across the CMIP5/CMIP6 pathways considered, the projected 2050 global mean TCWV spans 25.96–27.08 kg m<span>(^{-2})</span>, indicating higher sensitivity under stronger warming scenarios. The historical record also indicates a marked acceleration in the global TCWV trend, increasing from +0.039 kg m<span>(^{-2})</span> decade<span>(^{-1})</span> (1970–2000) to +0.434 kg m<span>(^{-2})</span> decade<span>(^{-1})</span> (2001–2024). These findings underscore the effectiveness of deep learning and multivariate integration in enhancing long-term hydroclimatic forecasting.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11600-026-01847-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147796788","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":"Assessment of the effectiveness of riverbank filtration in a selected reach of Bharathapuzha River basin, Kerala, India","authors":"K. Nimisha,&nbsp;S. K. Pramada,&nbsp;D. Sathish Kumar","doi":"10.1007/s11600-026-01871-y","DOIUrl":"10.1007/s11600-026-01871-y","url":null,"abstract":"<div><p>In most developing countries, the rivers are contaminated with municipal, industrial, and agricultural waste. A suitable cost-effective method for treating polluted rivers is very much essential for sustainable development. Riverbank filtration (RBF) is a nature-based water treatment technique that utilizes induced infiltration from rivers into adjacent alluvial aquifers. A number of physical, chemical, and biological activities occur underground that improve the water quality. It helps in reducing conventional drinking water treatment costs. RBF has become common in northern parts of India and around the world, but it is still not familiar in southern India, especially in Kerala. The main aim of the present study is to find a suitable location for Riverbank filtration (RBF) in the Bharathapuzha River basin, Kerala, India. Three-dimensional groundwater flow model was developed using MODFLOW to simulate river--aquifer interactions, while pathogen transport was assessed using RT3D. A trial-and-error approach was used to determine the optimum location of pumping wells for RBF. The modelling results indicated that four wells could be constructed at an optimum distance of 130 m parallel to the river. It was also found that the pumping rate required per well is 125 m³/day for an effective RBF system. The results demonstrate that RBF is a technically viable and economically attractive drinking water supply option for monsoon-dominated coastal river basins of Kerala and offer a transferable framework for RBF site selection in similar tropical environments.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147738411","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":"Ensemble combining techniques to improve gridded satellite-based products in precipitation estimation","authors":"Ameneh Mianabadi,&nbsp;Ahmad Jafarzadeh,&nbsp;Mohsen Pourreza Bilondi,&nbsp;Sedigheh Anvari","doi":"10.1007/s11600-026-01844-1","DOIUrl":"10.1007/s11600-026-01844-1","url":null,"abstract":"<div><p>This study investigates the effectiveness of ensemble combining techniques in improving the accuracy of satellite-based gridded precipitation estimations in the Sirjan watershed, Iran. For this purpose, four satellite-based products (CHIRPS, MSWEP, PERSIANN-CDR, and PERSIANN-CCS-CDR) were analyzed over 25 years (1996–2020). Various ensemble combining techniques, including Simple Model Averaging (SMA), Weighted Averaging Model (WAM), Multi-Model Super Ensemble (MMSE), and Modified MMSE (M3SE), were implemented to generate new estimations of precipitation based on satellite-based products. The performance of the ensemble combining techniques was evaluated through a series of comparative tests. The findings indicate that the MMSE and M3SE significantly improve the accuracy of precipitation estimates compared to individual products, increasing the accuracy rate up to 48% at the annual scale. The results demonstrate that the ensemble combining techniques provide a more reliable classification of wet and dry days, resulting in a 1.1–2.6% increase in true detection. This study offers a robust framework for generating more reliable precipitation estimates in non-gauge regions.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147738889","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":"Spatiotemporal assessment of climate extremes and their linkage with lake-level variability in the Urmia Lake Basin","authors":"Mahdi Saghi-Jadid,&nbsp;Mohammad Ali Ghorbani,&nbsp;Ahmad Fakheri-Fard","doi":"10.1007/s11600-026-01837-0","DOIUrl":"10.1007/s11600-026-01837-0","url":null,"abstract":"<div><p>Precipitation and temperature extremes (PEs and TEs) are intensifying in many arid and semi-arid regions. Understanding these changes and their hydrological implications is increasingly critical for vulnerable basins. This study provides a comprehensive spatiotemporal assessment of climate extremes and their linkage with lake-level changes in the endorheic Urmia Lake Basin (ULB), northwestern Iran. Daily temperature and precipitation records from 17 stations (1990–2020) were used to compute 26 ETCCDI indices. Temporal trends and spatial patterns were examined using statistical and geostatistical approaches. Results show notable increases in heat- and dryness-related indices (TXx, TN90p, SU, GSL, CDD) and heavy precipitation indices (R10mm, R20mm, Rx1day, SDII, R99p). A structural break around 2008 indicated a transition toward more intense extremes, accompanied by a north–south contrast, with stronger flood tendencies in the north and intensified thermal stress in the south. TEs showed strong negative correlations with lake level (<i>r</i> =  − 0.66), whereas CWD displayed a moderate positive association (<i>r</i> = 0.50), indicating a stable climatic response to lake decline. Shifts in the behavior of the indices around the ecological threshold resulted from the influence of lake shrinkage on local climate. In linking coupled PEs and TEs with lake-level dynamics and associated feedbacks, this study provides an integrated framework that enhances our understanding of compound hydroclimatic risks and supports informed decision-making for the management of endorheic basins.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147737934","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":"Changes in seismic processes in small areas along San Andreas fault prior to M > 7.0 earthquakes, 1980–2025","authors":"Teimuraz Matcharashvili,&nbsp;Tamaz Chelidze","doi":"10.1007/s11600-026-01863-y","DOIUrl":"10.1007/s11600-026-01863-y","url":null,"abstract":"<div><p>Identification of changes in the dynamics of the seismic process foreshadowing the approach of a strong earthquake is a main problem of the modern Earth sciences. Revealing such precursory changes remains a difficult, but apparently solvable task based on current knowledge about earthquake generation and tectonic faulting. In the present work, assuming that seismic processes in the vicinity of a strong earthquake preparation area should differ from that in the other parts along the fault, we analyzed features of seismic processes in small areas (micro-catalogues) located along and near the San Andreas fault. Increments of cumulative times, distances and seismic energies were calculated. Based on increment data we compared spatial, temporal and energy characteristics of seismic processes in micro-catalogues and assessed their similarity/dissimilarity using Mahalanobis distance calculation. It was shown that dynamics of seismic processes in micro-catalogues located along the San Andreas fault undergo strong quantitative changes from 20 h to 8 days prior to strong &gt; M7.0 earthquakes. These changes were revealed in the form of the appearance of statistically significant dissimilarity of seismic processes compared to neighbouring areas. Significant differences (compared to other micro-catalogues) were found in the micro-catalogues where five out of six analyzed strongest earthquakes occurred within the considered period. The obtained differences between micro-catalogues may have the value of additional important precursory markers to predict strong earthquakes in California. The presented results will be potentially helpful in the development of warning systems to signal the approach of devastating earthquakes several hours or days before their occurrence.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147737758","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":"Elastic least-squares reverse time migration with curvelet-domain and structural tensor regularization","authors":"Mingqian Wang,&nbsp;Bingshou He,&nbsp;Yuzhao Lin","doi":"10.1007/s11600-026-01866-9","DOIUrl":"10.1007/s11600-026-01866-9","url":null,"abstract":"<div><p>Elastic least-squares reverse time migration improves the resolution and amplitude fidelity of multicomponent seismic imaging through iterative inversion of reflectivity models. However, conventional elastic least-squares reverse time migration still suffers from noise, artifacts, and instability due to the ill-posed nature of the inverse problem, especially in geologically complex settings. To address these challenges, a novel elastic least-squares reverse time migration method is proposed, incorporating structure tensor-guided total variation regularization and curvelet-domain sparsity constraints. The structure tensor extracts locally dominant orientations from image gradients. When combined with total variation regularization, it enables edge-preserving smoothing and enhances structural continuity while suppressing artifacts across structural boundaries. In addition, the curvelet transform provides a multiscale and multidirectional sparse representation of the reflectivity image, and the curvelet-domain constraint effectively reduces migration noise and artifacts. This hybrid regularization strategy restricts model updates to subspaces that are both structurally consistent and sparsely represented. Numerical experiments on a synthetic graben model and the SEG/EAGE overthrust model indicate that, compared with conventional methods, the proposed method effectively suppresses noise and artifacts, producing images with improved structural consistency and lower model error.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"74 3","pages":""},"PeriodicalIF":2.1,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147738089","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}