Acta Geophysica最新文献

{"title":"Analysis of channel shifting and its impact on morphometric parameters of Sone river basin, Bihar, India","authors":"Ankit Ranjan,&nbsp;Thendiyath Roshni","doi":"10.1007/s11600-025-01562-0","DOIUrl":"10.1007/s11600-025-01562-0","url":null,"abstract":"<div><p>Controlling the natural force of rivers and predicting associated natural disasters pose significant challenges. However, conducting comprehensive monitoring of river course variations and morphological changes is crucial for implementing effective management plans and mitigation measures for rivers. This study aims to investigate changes in the course of the Sone river and its implications on the morphometric features of the surrounding basin. Using DEM data and Landsat satellite imagery from 2005 to 2020 at 5-year intervals, the Digital Shoreline Analysis System (DSAS) tool was employed to analyze river migration and parameters Net River Migration (NRM), End Point Rate (EPR), and Linear Regression Rate (LRR) were computed. The statistical result of the study revealed a westward shift in the river channel with the maximum NRM erosion value of –5174.52 m along with an EPR of –956.04 m/year and LRR of –451.87 m/year. Erosion and accretion areas were identified using ArcGIS, showing significant erosion trends from 2010 to 2020. The morphometric analysis encompassed the quantification of variables associated with linear, areal, and relief aspects. A low bifurcation ratio of 1.90 indicates limited structural control, heightening the risk of flooding. The elongated shape of the basin, combined with low drainage density and increased overland flow length leads to prolonged concentration periods. Additionally, the hypsometric curve portrays the river basin as an old and eroded basin. Overall, this study underscores the potential of the DSAS tool in assessing channel migration and its impact on basin morphometry, offering insights into potential water availability issues throughout the basin.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3531 - 3547"},"PeriodicalIF":2.1,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145143667","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":"Spatial variability of sediment grain size across stream orders in the headwater catchment of Omi River Basin, southwestern Nigeria","authors":"Joy Chimemela Igbozurike,&nbsp;Adewale Oluwagbenga Adeyefa,&nbsp;Rotimi Oluseyi Obateru,&nbsp;Adeyemi Oludapo Olusola","doi":"10.1007/s11600-025-01560-2","DOIUrl":"10.1007/s11600-025-01560-2","url":null,"abstract":"<div><p>Sediment grain sizes vary with channel material and morphology, hydraulic processes and environmental controls in the basin and may influence basin ecological health. In this study, we assessed the variation in particle size distribution across stream orders and along the longitudinal profile of the Omi River basin in Ibadan, southwestern Nigeria. The basin was partitioned into upstream, midstream and downstream segments along the longitudinal profile. Forty (40) reaches were sampled across the first-, second-, and third-order streams. Sediments from the riverbed were collected at the reaches using a sediment grabber and analyzed for particle sizes using standard laboratory techniques. Fine-grained sediments (75–210 µm) exhibit dominance across the stream orders, although it is intermixed with silt and pebbles in the mid-stream and occasioned by silt downstream. We identified no significant difference in particle size distribution across stream orders (<i>X</i>² (16) = 13.234, <i>p</i> &gt; 0.05) and along the river longitudinal profile (<i>X</i>² (16) = 21.963, <i>p</i> &gt; 0.05) due to the dominance of fine sand. Further, a significant variation in the distribution of sand (F_(2,37) = 8.981, <i>p</i> &lt; 0.05) and clay (F_(2,37) = 4.110, <i>p</i> &lt; 0.05) particle size components along the longitudinal profile was obtained. The prevalence of fine-grained sediments suggests that the basin may be experiencing considerable soil erosion and sediment transport, impacting water quality, stream stability, and aquatic ecosystems. Therefore, we recommend further research on the sediment grain size dynamics relative to river water quality and channel geometry in the basement complex terrain of humid tropical environments.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3513 - 3529"},"PeriodicalIF":2.1,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145143212","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":"Critical peak acceleration characteristics of a slope against actions of P and S waves with different incident directions","authors":"Feng Xiong,&nbsp;Jinzhong Sun,&nbsp;Shengwen Qi,&nbsp;Anyang Shao,&nbsp;Saichao Han","doi":"10.1007/s11600-025-01555-z","DOIUrl":"10.1007/s11600-025-01555-z","url":null,"abstract":"<div><p>There are many potential seismic sources around a slope in earthquake zones. Thus, the seismic waves could come to the slope from arbitrary directions. However, few researches have been conducted on the influences of seismic wave incident directions on slope seismic resistance. In this paper, the concept of critical peak acceleration (CPA) of seismic ground motion acting on a slope was proposed to characterize the slope seismic resistance, and the CPA was confirmed in light of penetration of the plastic zones in the slope body. The CPAs of Panlongyuan loess slope located in Baoji City against actions of seismic waves of simple harmonic P waves and S waves with different incident directions were searched by load increasing method with Flac^3D software. Accordingly, the influences of seismic wave incident directions were discussed. The results show that seismic wave incident direction has significant effects on the CPAs of the slope. The CPAs of the slope against the actions of seismic waves coming from the back of the slope are relatively smaller, so the slope is more prone to failure. Therefore, the seismic wave incident direction should be considered in the analysis of slope dynamic stability. In addition, the CPAs of slopes against P waves are also different from those against S waves. So, to evaluate the stability of a slope subjected to a real seismic wave, the seismic phases of incident waves should not be ignored. The research of this paper reveals the effects of seismic wave incident directions on the slope CPAs and paves a way for the probability analysis of seismic-induced landslides.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3159 - 3175"},"PeriodicalIF":2.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145143435","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":"Peak flow forecasting in Mahanadi River Basin using a novel hybrid VMD-FFA-RNN approach","authors":"Sanjay Sharma,&nbsp;Sangeeta Kumari","doi":"10.1007/s11600-025-01567-9","DOIUrl":"10.1007/s11600-025-01567-9","url":null,"abstract":"<div><p>Accurate prediction of peak streamflow is essential to mitigate the flood damages in watershed area. This study focuses on improving peak streamflow prediction using hybrid machine learning models in Mahanadi River Basin, India. In the hybrid model, variational mode decomposition (VMD) is used to decompose the original discharge data into various intrinsic model functions (IMFs) and firefly algorithm (FFA) is used to optimise the train/test split and hyperparameters of recurrent neural network (RNN) in two stages. The use of IMFs with original discharge data and dual stage parameter optimisation process makes this approach novel. The results show that the hybrid VMD-FFA-RNN model performed better than all other models, showing greater performance during both training and testing periods. This improved performance can be attributed to its modified structural algorithm. Furthermore, comparative analysis using statistical performance indicators, such as root mean square error (RMSE), indicates a notable 76.50% and 46.63% improvement in prediction accuracy compared to the simple RNN and VMD-RNN models, respectively. Therefore, the developed hybrid model presents a capable alternative for future time series forecasting applications, offering enhanced accuracy and reliability in peak streamflow prediction in the Mahanadi River Basin, India, and potentially in similar watershed systems.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3495 - 3512"},"PeriodicalIF":2.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145143433","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":"Establishment of near-surface Q model using a shallow neural network","authors":"Jizhong Wu,&nbsp;Jing Gao,&nbsp;Kexin Wang,&nbsp;Ying Shi","doi":"10.1007/s11600-025-01569-7","DOIUrl":"10.1007/s11600-025-01569-7","url":null,"abstract":"<div><p>Due to insufficient compaction of the overlying strata, near-surface layers are classified as unconsolidated formations. These layers exhibit complex velocity structures and significant attenuation, which severely impair the resolution of deep seismic data. In practical seismic data processing, obtaining a detailed near-surface Q field is essential for improving the imaging resolution of medium- to deep-depth layers. Currently, seismic data from uphole surveys are commonly used to generate near-surface Q fields. However, this approach faces challenges such as high per-well costs and low well density, making it insufficient for constructing a detailed near-surface Q field. To address these issues, this study employs a BP neural network, leveraging its powerful nonlinear fitting capabilities to establish a functional relationship between input data—including velocity, position, and travel time derived from seismic data—and Q values. This method offers an efficient and high-precision approach for predicting near-surface Q fields, overcoming the limitations of conventional methods that typically suffer from low fitting accuracy and high data requirements. By implementing this approach, we successfully derived the near-surface Q field from a field dataset and performed absorption compensation. The results of this application validate the effectiveness of the proposed method.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3373 - 3383"},"PeriodicalIF":2.1,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145143434","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":"Experimental study of multicomponent shallow seismic exploration: a case study of Quaternary in Tianjin City, China","authors":"Guangcai Li,&nbsp;Jun Matsushima,&nbsp;Baowei Zhang,&nbsp;Xiaojiang Wang,&nbsp;Jianxun Liu","doi":"10.1007/s11600-025-01565-x","DOIUrl":"10.1007/s11600-025-01565-x","url":null,"abstract":"<div><p>As the quick urbanization and construction requirement, investigating and identifying the different scale faults and fractures and fluid related layers in shallow urban subsurface are of great significance. However, the conventional P-wave only module may present limited resolution in shallow layers and difficult to identify the fluid layers alone, thus unable to satisfy some high-resolution urban shallow engineering work. To ameliorate this problem and test the real effectiveness, we present experimental study of seismic multicomponent exploration in Tianjin City. P-wave vibroseis for excitation and three-component detectors for receiving are carried out for three survey lines. From the data analysis, we find generally the layers in the P-wave profile have a good match to the ones in the converted profiles. Furthermore, small-scale structures including faults are presenting in the converted profiles, while they are unable to recognize in the conventional P-wave profile. The deduced fluid layer presents in the P-wave profile while disappearing in the converted profiles, the layer is thus conjectured to be fluid relative. Limited by the resolution, the P-wave profile is unable to separate the shallow formation, while the converted profiles have this ability and can separate it clearly. These results show the converted wave profiles ravel higher resolution and thus have obvious advantages in uncovering the small-scale structures including faults and fractures, and thin layers. Integrating the three-component data are helpful and can effectively mitigate ambiguity of seismic interpretation work. It can be an effective supplementary method for major urban engineering work such as infrastructure site selection and dam survey.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3359 - 3371"},"PeriodicalIF":2.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145143303","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":"Evaluation of IMERG precipitation product in the investigation of drought events in the Kermanshah Province","authors":"Morteza Gheysouri,&nbsp;Ataollah Kavian,&nbsp;Mahin Kalehhouei,&nbsp;María Fernández-Raga,&nbsp;Jesus Rodrigo-Comino","doi":"10.1007/s11600-025-01558-w","DOIUrl":"10.1007/s11600-025-01558-w","url":null,"abstract":"<div><p>Our world is facing new challenges due to the prolonged drought events that have occurred over the past decade. These events are affecting ecosystem services and Earth surface processes adding unpredictable responses to be managed. In this study, a comprehensive evaluation of integrated multi-satellite retrieval (IMERG) global precipitation measurement products was conducted to determine the drought situation in semi-arid and arid areas. Predicted precipitation values from the final IMERG from 2001 to 2020 were used to evaluate 3, 6, and 12 months of drought in 13 meteorological stations in the Kermanshah Province, a representative study area. The results showed that IMERG has a relatively good performance in detecting the spatial patterns of heavy and low precipitation, so that in the northern stations, where the rainfall amount is higher, IMERG has shown good performance. The drought results obtained from IMERG show that the SPI-3 index is close to the station data; therefore, the average of RMSE, <i> R</i>², and <i>E</i>_NS of the 3 month time step data is equal to 0.7, 0.5, and 0.6 compared to SPI-6 and 12 data. The results of drought frequency showed that drought intensity in the Kermanshah Province was higher than that in SPI-3 at 12 and 6 months, whereas the 3 month drought frequency closely matched that of the station data. In examining the time step of the drought event, it was found that the IMERG data showed the drought 1–2 years earlier than the station data, which can be used to evaluate early droughts. In this case, we demonstrated that the SPI-3 drought index obtained from IMERG data was the best indicator of drought. The overall findings indicate that IMERG data are able to simulate droughts earlier than station data and can be a useful tool for drought monitoring and disaster management in semi-arid and arid regions. This research can be applied in the use of satellite precipitation products for regional drought management.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 3","pages":"2669 - 2682"},"PeriodicalIF":2.3,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143879647","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":"Acoustic impedance inversion using anisotropic total variation with structure-guidance and smoothly clipped absolute deviation penalty","authors":"Yue Zhang,&nbsp;Guowei Zhu,&nbsp;Lei Zhang,&nbsp;Yufei Gong,&nbsp;Guixin Zhang","doi":"10.1007/s11600-025-01533-5","DOIUrl":"10.1007/s11600-025-01533-5","url":null,"abstract":"<div><p>The post-stack seismic acoustic impedance (AI) inversion is an important method for estimating subsurface lithological parameters. Post-stack seismic inversion based on total variation (TV) regularization is widely used to recover AI from noisy seismic data. However, TV has inherent biases and does not incorporate geological structure information, leading to lower inversion accuracy. To address this issue, we propose a new seismic AI inversion method. It is based on anisotropic total variation with structure-guidance and smoothly clipped absolute deviation penalty (SGSATV). First, smoothly clipped absolute deviation (SCAD) penalty is introduced into the anisotropic total variation (ATV) framework. Then, dip information from post-stack data is extracted using structural tensors and then incorporated into the inversion framework. Finally, an objective function with seismic matching term, SGSATV constraint, and initial model constraint is constructed. For the optimization problem, the objective functional is solved within the split Bregman framework. Numerical examples and field data demonstrate that the proposed method preserves geological edges and achieves higher inversion accuracy in geologically complex areas.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3339 - 3358"},"PeriodicalIF":2.1,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145142813","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":"Hybrid machine learning for drought prediction at multiple time scales: a case study of Ağrı station, Türkiye","authors":"Hatice Citakoglu,&nbsp;Gaye Aktürk,&nbsp;Vahdettin Demir","doi":"10.1007/s11600-024-01501-5","DOIUrl":"10.1007/s11600-024-01501-5","url":null,"abstract":"<div><p>Drought is a prolonged period of significantly reduced precipitation, resulting in water scarcity and environmental stress. In this study, Ağrı province, situated in the eastern region of Türkiye, where most of the land cannot be irrigated and the livelihood is based on agriculture, was selected as the study area. Meteorological droughts in Ağrı province were forecasted using hybrid machine-learning models, leveraging monthly precipitation and temperature series from 1965 to 2022. The study employed the standardized precipitation index (SPI), relying solely on precipitation data, and the standardized precipitation evapotranspiration index (SPEI), which also considers both temperature and precipitation data. Various timescales, including 1M (1 month), 3M, 6M, 9M, and 12M, were taken into consideration. The best model for each hybrid model was determined using data at time points t, t-₁, t_-2, t_-3, and t_-4 for the relevant time series. The study combined ensemble least squares boosting algorithms (LSBoosting), adaptive network-fuzzy inference system (ANFIS), support vector machines (SVM), Gaussian process regression (GPR), and M5 model tree (M5Tree) approaches with the variational mode decomposition (VMD) technique to create hybrid models. The results indicate that certain models perform better at different timescales, with M5Tree and GPR generally providing higher accuracy. For instance, the M5Tree model achieved the lowest MAE (0.0714 and 0.0555) and RMSE (0.0909 and 0.0732) values for the _9MSPI and _12MSPI timescales, respectively, making it the best-performing model at these scales. Similarly, the GPR model stood out for the _1MSPI and _6MSPI scales with the lowest MAE values (0.1336 and 0.0736, respectively). Based on the performance criteria, the best hybrid model for the _1MSPI was the GPR approach. For the SPEI, except for _3MSPEI, the M5Tree approach showed the best performance at other timescales. However, since the prediction outcomes gave similar results according to classical performance criteria, a one-sided Wilcoxon sign rank test was applied to the outcomes of ANFIS, GPR, and M5Tree models for _3MSPEI, _6MSPI, _9MSPI, and _12MSPI. It has been determined that these three models are not superior to each other. Additionally, the one-sided Wilcoxon signed-rank test found no statistically significant difference between ANFIS, GPR, SVM, and M5Tree models for the _3MSPI. This research concluded that the performance of hybrid machine-learning methods applied to different timescales of SPI and SPEI varies.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 2","pages":"1643 - 1677"},"PeriodicalIF":2.3,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11600-024-01501-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143602234","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 new Eötvös correction algorithm for marine shipborne gravity survey with irregular nonlinear track","authors":"Shi Liu,&nbsp;Lin Wu,&nbsp;Menghan Xi,&nbsp;Guocheng Mao,&nbsp;Lifeng Bao,&nbsp;Yong Wang","doi":"10.1007/s11600-025-01547-z","DOIUrl":"10.1007/s11600-025-01547-z","url":null,"abstract":"<div><p>The Eötvös correction is a major factor affecting the accuracy of marine gravity survey. To mitigate the Eötvös correction error in irregular nonlinear navigation, we proposed a new Eötvös correction algorithm that emphasizes the optimization of velocity and course calculation intervals. Unlike traditional algorithms that solely rely on positional information, the new algorithm establishes a real-time correlation between the vehicle’s navigation state and position information through circular fitting. By comprehensively incorporating both navigation state and positional data, it optimizes the calculation of velocity and course, thereby enhancing the effectiveness of Eötvös correction while mitigating the impact from Global Navigation Satellite System (GNSS) position errors. Utilizing marine gravity measurements surveyed in the South China Sea, the root-mean-square error (RMSE) of discrepancies at gravity cross points processed by the new algorithm was 1.65 milli gals (mGal), outperforming other methods. Furthermore, as position errors escalate, it maintains high accuracy, with the RMSE staying within 2.33 mGal. In contrast, the results of the differential GNSS method exhibit significant fluctuations. While the track fitting method producing smooth results, it introduced distortion in the Eötvös correction due to over-smoothing. The results demonstrate that the proposed algorithm enhances the effectiveness and robustness of Eötvös correction, and is well-suited for marine gravity surveys conducted using irregular nonlinear navigation patterns, where course and velocity undergo real-time variations.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"73 4","pages":"3323 - 3338"},"PeriodicalIF":2.1,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145145417","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}