Acta Geophysica最新文献

{"title":"Trend analysis of hydro-climatic parameters in Sonbeel: evaluating Asia’s second largest seasonal wetland","authors":"Ningthoukhongjam Rita Devi,&nbsp;Briti Sundar Sil","doi":"10.1007/s11600-025-01568-8","DOIUrl":"10.1007/s11600-025-01568-8","url":null,"abstract":"<div><p>Wetlands are vital aquatic ecosystems that provide unique benefits to humans but are significantly impacted by climate change. Variations in temperature and rainfall can alter their health and functionality. This study focuses on Sonbeel, Asia’s second-largest seasonal wetland, to assess the trends in five hydro-climatic parameters: maximum and minimum temperatures, potential evapotranspiration (PET), rainfall, and groundwater level (GWL). The analysis employs Sen’s slope estimator and multiple trend detection methods to evaluate the temporal variability and magnitude of these trends. Among the different trend detection methods, the Innovative Trend Analysis method proves effective in identifying long-term non-monotonic trends by distinguishing between low, medium, and high value trends objectively. The study reveals a notable increase in both PET and temperatures over the study period. Conversely, trends for rainfall and GWL are declining seasonally. Specifically, temperature and PET trends are rising, while GWL is decreasing. Rainfall trends also show a decrease, which aligns with the GWL trends. To investigate the potential seasonal relationships between meteorological parameters and GWL, the study compares the trend statistics of these variables. Overall, Sonbeel’s rising temperatures and shifting rainfall patterns highlight the significant impact of climate change on this wetland. These findings underscore the importance of monitoring hydro-climatic factors to understand and address the effects of climate change on wetland ecosystems.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3567 - 3599"},"PeriodicalIF":2.1,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145144183","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":"Advancements in integrated seismic vulnerability assessment using geophysical approaches","authors":"Rerisa Al Hanipa,&nbsp;Thomas Mustafa Kamal,&nbsp;Muhammad Haikal Fikri,&nbsp;Lindung Zalbuin Mase,&nbsp;Rena Misliniyati,&nbsp;Fepy Supriani,&nbsp; Refrizon","doi":"10.1007/s11600-025-01573-x","DOIUrl":"10.1007/s11600-025-01573-x","url":null,"abstract":"<div><p>This study presents a map of seismic vulnerability distribution in Bengkulu City. Our study stands out for its unique approach, which begins by collecting geotechnical data from as many as 211 research locations. The analysis was conducted to obtain earthquake vulnerability values by developing an integrated approach that combines geophysical methods and seismic vulnerability analysis. The data used in this analysis include amplification parameters, natural frequency, dominant period and sediment thickness. The research results include geophysical parameter value distribution maps, seismic susceptibility distribution maps, sediment thickness distribution maps, statistical parameters, and empirical correlation graphs between shear wave velocity on bedrock from previous research data and shear wave velocity predictions. The results also show that this integrated approach can improve the accuracy of earthquake vulnerability assessment and assist in developing more effective mitigation strategies. This research has significant implications for improving the safety and quality of life of people living in earthquake-prone areas.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 5","pages":"4037 - 4057"},"PeriodicalIF":2.1,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144893948","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":"Exploring the seasonal variability and nexus between urban air pollution and urban heat islands in Lahore, Pakistan","authors":"Muhammad Nasar-u-Minallah,&nbsp;Mehwish Jabeen,&nbsp;Nusrat Parveen,&nbsp;Muhammad Abdullah,&nbsp;Mohamed Hassan Fathima Nuskiya","doi":"10.1007/s11600-025-01574-w","DOIUrl":"10.1007/s11600-025-01574-w","url":null,"abstract":"<div><p>In urban settings, the interplay between air pollution and the effects of urban heat islands (UHIs) has a substantial impact on the health of residents as well as the delicate equilibrium of urban ecology and climate. Lahore faces severe environmental issues, notably high levels of urban air pollution stemming from industrial, vehicle, and agricultural practices emissions and urban warming due to urbanization, land use, and local climate change. This study aimed to use remotely sensed data to analyze the seasonal variations in nighttime surface urban heat island intensity (SUHII) as extracted from the MODIS satellite. Furthermore, the study examined the potential use of Sentinel-5 satellite imagery for pollution analysis through the seasonal distribution of significant air pollutants, such as carbon monoxide (CO), sulfur dioxide (SO₂), and nitrogen dioxide (NO₂). These pollutants were extracted from the European TROPOspheric Monitoring Instrument (TROPOMI) from March 2019 to February 2023. In comparison with rural areas, the study found that the concentration of pollutants in urban areas is substantially higher. The findings of the research also reveal the presence of a pronounced nocturnal surface urban heat island over Lahore, particularly in the downtown region, which is mostly composed of urban land use, densely populated areas, high vehicle emissions, and industrial and power generation locations. Summertime is when the SUHII is highest. However, the chosen pollutants also serve as an urban pollution island (UPI) that limits the areas that have higher SUHII. The UHI indicator exhibits a significant positive correlation with pollutants such as CO and NO₂ and a weak positive correlation with SO₂ in urban environments. Urban heat and air pollution have detrimental effects on human health as well as ecology, so this study is crucial for determining the ecological state of the fastest-growing megacity Lahore. This study is noteworthy because, without a regular network of monitoring points, it creatively uses Sentinel-5 satellite data to analyze pollution and air quality over wide areas. This study contributes to a comprehensive understanding of UHI-pollution dynamics and implications, which in turn informs urban planning and policies for urban air quality adaptation and urban environment management.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3699 - 3719"},"PeriodicalIF":2.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145142461","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":"Estimating the near-surface Q factors through the enhanced spectral ratio method utilizing data from an uphole survey","authors":"Jizhong Wu,&nbsp;Ying Shi","doi":"10.1007/s11600-025-01575-9","DOIUrl":"10.1007/s11600-025-01575-9","url":null,"abstract":"<div><p>The quality factor Q is a crucial physical parameter that quantitatively describes the absorption and attenuation characteristics of formation media with respect to seismic waves. Accurately determining the quality factor Q is significant for improving the resolution of seismic data. The near-surface strata is more shallowly buried and less compacted by the overlying layers. Compared to the deeper strata, the near-surface strata absorbs seismic wave energy more strongly, which directly impacts seismic data resolution and Q value calculation. A common method for obtaining the surface Q factor is through the uphole survey, which is known for its simplicity and low cost. However, the accuracy of estimating the near-surface Q factor is compromised due to variations in seismic wavelets and geophone coupling responses, leading to considerable uncertainty in the survey results of near-surface absorption structures. In this study, the impact of actual data and model data on source wavelet differences and geophone coupling response differences was analyzed. A near-surface Q factor estimation method was proposed, grounded in the conventional spectral ratio method, which simultaneously addresses the effects of source wavelet differences and geophone coupling response differences. Field data application from a work area in eastern China demonstrates the effectiveness of the proposed method.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 5","pages":"4023 - 4036"},"PeriodicalIF":2.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144893991","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":"Geology and seismicity of Tushka area (Egypt): a role of pore pressure in triggering earthquakes","authors":"Khaled Omar,&nbsp;Mohamed El-Amin,&nbsp;Ezzat Mohamed El-Amin,&nbsp;Haggag Hamed Mohamed,&nbsp;Saleh Qaysi,&nbsp;Hamada Saadalla,&nbsp;Hazem Badreldin,&nbsp;Ashraf Adly,&nbsp;Ahmed Hamed","doi":"10.1007/s11600-025-01564-y","DOIUrl":"10.1007/s11600-025-01564-y","url":null,"abstract":"<div><p>The general plan for the development of Upper Egypt was suggested by the Egyptian government in 2014. This plan calls for the building of several massive projects, including new cities and tourist destinations around the Red Sea coast, and developing Aswan, Luxor and Abu Simbel cities. All accounting for overcome the dense population and trying to raise the national income sectors. Tushka project, located southwest of Lake Nasser, appears to be the most promising initiative for the southern region of Upper Egypt. For the first time, water from Lake Nasser started to reach the Tushka depressions in 1998 when the lake's water level rose over 178 m. Up to the end of 2001, water kept flowing into the depressions. In order to lessen the possibility of downstream degradation to the Nile valley brought on by unusual flooding, these depressions were utilized to discharge surplus water from the Lake Nasser maximum storage level as a natural flood diversion basin. Approximately, 374 earthquakes with magnitudes ranging from <span>({M}_{L})</span>= 0.8 to <span>({M}_{L})</span>= 3.9 have been reported in the region since 1982. Studies have been conducted on the seismic conditions and the role of Lake Nasser water in triggering the seismic activity in the research area. The focal mechanism solution for the greatest earthquake, which occurred on March 7, 2013, with a magnitude of <span>({M}_{L})</span>=3.9, revealed that normal faulting with strike slip component was the main reason for the earthquake. The frequency magnitude relationship of the data acquired provides a reasonably good match to guarantee that conclusion. The new data from the present research may be used to assess the seismic hazard and gain a better knowledge of the seismic activity in the Tushka area.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 5","pages":"3721 - 3736"},"PeriodicalIF":2.1,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144893918","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 deep learning-based method for enhancing isotropic reverse time migration in complex media","authors":"Yi Sun,&nbsp;Zhefeng Wei,&nbsp;Xiaofeng Jia,&nbsp;Chenghong Zhu","doi":"10.1007/s11600-025-01563-z","DOIUrl":"10.1007/s11600-025-01563-z","url":null,"abstract":"<div><p>In the field of geophysical exploration, reverse time migration (RTM) stands out as an effective seismic imaging technique, offering significant advantages in imaging complex geological structures. However, the seismic data collected in most cases of exploration contain complex geological anisotropy. Employing isotropic RTM methods for processing anisotropic seismic data may result in various issues, including artifacts and inaccuracies in structural imaging. We develop a convolutional neural network (CNN) model that improves isotropic RTM results by learning the results of anisotropic RTM, and the proposed U-net network with ResNet and SmoothL1 loss function can combine the advantages of the two migration methods. The input of the neural network is acoustic isotropic RTM images, and the label is the results of anisotropic RTM based on the tilted transversely isotropic (TTI) acoustic first-order velocity-stress equations. Validation and testing of complex models such as Marmousi model and SEG overthrust model have shown that the trained network effectively improves the imaging quality of isotropic RTM especially for dip structures and suppresses artifacts such as those caused by incomplete convergence of diffraction waves. The application of our CNN model to process isotropic RTM images produces enhanced results, with lower computational burden and implementation difficulty compared to anisotropic RTM methods.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 5","pages":"4003 - 4022"},"PeriodicalIF":2.1,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144894006","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":"Enhancing hydrological time series forecasting with a hybrid Bayesian-ConvLSTM model optimized by particle swarm optimization","authors":"Huseyin Cagan Kilinc,&nbsp;Sina Apak,&nbsp;Mahmut Esad Ergin,&nbsp;Furkan Ozkan,&nbsp;Okan Mert Katipoğlu,&nbsp;Adem Yurtsever","doi":"10.1007/s11600-025-01570-0","DOIUrl":"10.1007/s11600-025-01570-0","url":null,"abstract":"<div><p>Hydrological time series forecasting often relies on addressing the inherent uncertainties and complex temporal dependencies embedded in the data. This study presents an innovative hybrid framework, the Bayesian-ConvLSTM-PSO model, specifically designed to tackle these challenges. The framework synergistically combines 1D convolutional neural networks (CNNs), a convolutional Bayesian network, multi-head attention, and long short-term memory (LSTM) networks, with parameters optimized through particle swarm optimization (PSO). The fusion of the convolutional Bayesian network and 1D convolutional neural networks enhances feature robustness by capturing both probabilistic uncertainties and spatial patterns effectively. The multi-head attention model further amplifies this by focusing on the most relevant features, improving the learning process and ensuring better representation of complex temporal dependencies. The proposed model is rigorously tested on daily streamflow data from three flow measurement stations (FMS): Ahullu (D14A014), Kızıllı (D14A080), and Erenkaya (D14A127). Experimental results reveal that the Bayesian-ConvLSTM-PSO model achieves significant performance gains across various evaluation metrics, including root mean square error (RMSE), mean absolute error (MAE), determination coefficient (<i>R</i>²), Kling–Gupta efficiency (KGE), and bias factor (BF). Notably, the model demonstrates exceptional accuracy with an <i>R</i>² of 0.9950, a KGE of 0.9950, and a bias factor of 0.0003, surpassing the results of PSO-1D CNN-LSTM and benchmark models, such as DNN, DNN-LSTM, and 1D ConvLSTM. These compelling findings underscore the potential of the Bayesian-ConvLSTM-PSO framework as a robust and effective tool for applications in river engineering and hydrological time series forecasting.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3549 - 3566"},"PeriodicalIF":2.1,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11600-025-01570-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145144768","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":"An integrated three-dimensional water and multilayer sediment quality model for Tokyo Bay","authors":"Morteza Jedari Attari","doi":"10.1007/s11600-025-01548-y","DOIUrl":"10.1007/s11600-025-01548-y","url":null,"abstract":"<div><p>The aim of this study is to develop, combine, and optimize a three-dimensional water quality and sediment transport model with a bed module. This bed model incorporates a layered model that defines both dissolved and solid phases in vertically layered dimensions. To calibrate the integrated model, a comprehensive dataset consisting of water quality parameters in Tokyo Bay (Japan) was utilized. Tokyo Bay is known for its heavy eutrophication, which results in the accumulation of soft-organic sediment in inner parts, particularly near the head of the bay. One key focus of this study was to investigate near-bed–water conditions and their impact on oxygen depletion, nutrient cycling, primary production, and overall water quality. The results obtained from simulating particulate organic carbon content ratio on the sediment surface were found to be consistent with observed values. Additionally, accurate simulations of other water quality parameters were successfully achieved using this developed model. This developed model proves to be a valuable tool for future studies aimed at improving environmental management strategies within Tokyo Bay. The sophisticated modeling of hypoxic and anoxic conditions in inner parts of the bay, which pose chronic threats to benthic life and severely deteriorate water quality, provides valuable insights for analyzing the consequences of various scenarios related to anthropogenic actions. This model can assist researchers and policymakers in making informed decisions regarding environmental management strategies within Tokyo Bay.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 3","pages":"2683 - 2724"},"PeriodicalIF":2.3,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879510","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":"Three-dimensional joint inversion of potential field datasets constrained by cross-gradient and depth weighting","authors":"Adrián Misael León-Sánchez,&nbsp;Elsa Leticia Flores-Márquez,&nbsp;Andrés Tejero-Andrade","doi":"10.1007/s11600-025-01561-1","DOIUrl":"10.1007/s11600-025-01561-1","url":null,"abstract":"<div><p>A three-dimensional cross-gradient joint inversion algorithm for potential datasets is presented. For the necessary forward gravity and magnetic modeling, the gravitational attraction and the total-field anomaly produced by a three-dimensional volume constituted by rectangular prisms is computed. Due to the imposition of a cross-gradient constraint on our joint inversion strategy, we use a slightly modified version of the nonlinear conjugate gradient methodology to solve for the model parameters. In order to counteract the natural decay implicit in the model responses, we impose a depth weighting on our objective function. To test the proposed algorithm, we first develop the individual and joint inversion of synthetic gravity and magnetic datasets. Finally, we carry out individual and joint inversions of potential field data acquired at La Primavera Geothermal Field, Jalisco, México. Our results show stable minimization processes of our objective function. Additionally, the calculated models reproduce their respective geophysical data for both individual and joint inversion experiments.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3385 - 3404"},"PeriodicalIF":2.1,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11600-025-01561-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145144100","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":"The October 09, 2023, Osku earthquake: seismological and morphotectonic evidence for transtensional deformation along the Azarshahr–Tabriz fault zone of northwestern Iran","authors":"Saeid Rahimzadeh,&nbsp;Noorbakhsh Mirzaei,&nbsp;Mehrdad Pakzad,&nbsp;Milad Kaboli","doi":"10.1007/s11600-025-01559-9","DOIUrl":"10.1007/s11600-025-01559-9","url":null,"abstract":"<div><p>The October 09, 2023, M_N 3.9, earthquake occurred near the NE-trending Azarshahr–Tabriz fault zone, in the Osku region of northwestern Iran, typically characterized as a stable continental region. Because of the lack of M_N ≥ 3.0 earthquake along this fault zone during the instrumental time period, there is serious ambiguity regarding its kinematics. The only earthquake contributed to this fault zone is a historical earthquake dated 1641 (Ms ~ 6.8) that its meizoseismal area corresponds to the Azarshahr–Tabriz fault zone. The 2023 earthquake has provided a good opportunity to reconsider the seismotectonic of this fault zone and try to understand its kinematics by analysis of the earthquake source mechanism. Strong ground motions recorded at nearby accelerometry stations show northeastward rupture directivity. The relocated epicenter of the 2023 Osku earthquake is located in a zone of transtensional structure formed within a left-stepping releasing stepover. The focal mechanism solution of the Osku earthquake indicates strike-slip faulting with a normal component, consistent with the existing releasing stepover. Structural elements of the Osku stepover may cause moderate-magnitude earthquakes, similar to the experience of earthquakes on the Hayward–Rodgers Creek fault stepover, in Francisco, California, and the Nima County fault stepover in central Qinghai–Tibet Plateau, China. This is a key issue in determining potential seismic sources for earthquake hazard analyses and risk assessments, especially for the Khosrowshahr–Osku region, with a population of ~ 180,000.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3177 - 3194"},"PeriodicalIF":2.1,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145144061","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}