Acta Geophysica最新文献

{"title":"Shoreline delineation and change analysis in response to sea level rise and coastal bathymetry along the coast of Visakhapatnam, India using high-resolution optical imagery","authors":"Ibrahim Shaik,&nbsp;Mohammed Suhail,&nbsp;Pullaiahgari Venkata Nagamani","doi":"10.1007/s11600-024-01341-3","DOIUrl":"10.1007/s11600-024-01341-3","url":null,"abstract":"<div><p>Coastal morphology is persistently changing in structure and environment because of natural and anthropogenic effects. Consequently, determining the spatiotemporal variability of coastal areas has become a significant source of concern. The study focuses on automatic delineation of the shoreline using edge detection algorithms; quantification of the morphological changes using a digital shoreline analysis system (DSAS); and retrieval of coastal bathymetry using linear wave dispersion relation from optical imagery for the period 2005–2020. The Canny algorithm shows efficiency in detecting shoreline precisely (95.6%). The highest erosions for net shoreline movement (NSM) are −31.71 m and −50.43 m/yr for end point rate (EPR) during 2014–2017, whereas the maximum accretions for NSM are 25.37 m and 8.64 m/yr for EPR during 2011–2014. The linear regression rate (LRR) and weighted linear regression (WLR) measure shoreline shift over a 15-year period, with the maximum rates of accretion and erosion being 1.01 m/yr and −1.02 m/yr, respectively. Shoreline prediction was carried out using the Kalman filter model for the year 2021 and was concurrently validated with field DGPS measurements. The retrieved bathymetry over the study area agrees with in situ bathymetry data with a mean bias error (MBE) of 0.39, a correlation coefficient (<i>r</i>) of 0.821, and a coefficient of determination (<i>R</i>²) of 0.742. The study also illustrates the effects of changes in mean sea level (MSL) height and coastal bathymetry on coastal morphology. Coastal bathymetry shows an inverse relationship (<i>r</i> = −0.765) with NSM, whereas MSL height shows a positive relationship with NSM (<i>r</i> = 0.403).</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"72 6","pages":"4453 - 4472"},"PeriodicalIF":2.3,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140593517","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 flood forecasting using satellite precipitation product and machine learning approach in Bagmati river basin, India","authors":"Ajit Kumar,&nbsp;Vivekanand Singh","doi":"10.1007/s11600-024-01332-4","DOIUrl":"10.1007/s11600-024-01332-4","url":null,"abstract":"<div><p>Real-time flood forecasting is crucial for early flood warnings. It relies on real-time hydrological and meteorological data. Satellite Precipitation Products offer real-time global precipitation estimates and have emerged as a suitable option for rainfall input in flood forecasting models. This study first compared the daily Satellite Precipitation Products of Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) with observed rainfall data of India Meteorological Department from the year 2001 to 2009 using contingency tests. Rainfall data of IMERG are used to build four Real-time flood forecasting models based on machine learning: feedforward neural network (FFNN), extreme learning machine (ELM), wavelet-based feedforward neural network, and wavelet-based extreme learning machine. The models consider the IMERG gridded data at 1 h resolution as input to predict water level at Hayaghat gauging station of Bagmati River with lead times from 1 h to 10 days. These models have been trained and tested with the observed water level data. The model performance was also evaluated using various statistical criteria. Results showed good correlation between IMERG and observed data with a probability of detection of 85.42%. Overall, wavelet-based models outperformed their singular counterparts. Among the singular models, the FFNN model performed better than ELM with satisfactory predictions up to 5 days of lead time. For a 7 days lead time, only wavelet-based-FFNN performs well, whereas none of the models produced satisfactory results for 10 days lead time.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"72 6","pages":"4431 - 4451"},"PeriodicalIF":2.3,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11600-024-01332-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140593506","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":"3D electrical resistivity investigation and subsurface imaging of the Kasane warm spring area, northwest Botswana","authors":"Sarah Babi,&nbsp;Bokani Nthaba,&nbsp;Boniface Kgosidintsi,&nbsp;Loago Molwalefhe,&nbsp;Elisha M. Shemang","doi":"10.1007/s11600-024-01334-2","DOIUrl":"10.1007/s11600-024-01334-2","url":null,"abstract":"<div><p>Electrical resistivity imaging survey was carried out at the warm spring site in Kasane, northwest Botswana, to investigate the subsurface distribution of geological structures and how they influence the existence of the warm spring. This investigation was carried out along eight 480-m-long parallel profiles with an electrode spacing of about 10 m and 50 m line spacing. We used a Pole–dipole electrode array to acquire the data. The data inversion employed in this study was based on the smoothness constrained nonlinear least-square inversion algorithm. 2D data inversion for all the eight 2D datasets was performed, and the eight 2D datasets were then collated into a single 3D data file before performing a 3D data inversion. The resultant 2D inversion models display the variation of electrical resistivity beneath the respective profiles; whereas, the resultant 3D models show the distribution of electrical resistivity in both the lateral and vertical directions. The 2D inversion results revealed two distinct anomalies with low resistivity values, e.g., &lt; 46.2 Ω m of the topmost layer indicating the presence of silty clays and relatively high resistivity material with resistivity values exceeding 249.3 Ω m, which was attributed to basalts. Also observed in the 2D inversion results are low-intermediate resistivity zones of about 46.2 Ω m extending to greater depths beyond the boundaries of the models, which are attributable to the existence of fluid-filled fractures/faults. The 3D inversion results resolved a laterally extensive high-resistivity basaltic unit, two NE–SW-trending vertical/near-vertical low-resistivity features which are attributable to fluid-filled fractures or faults, and a broad low-resistivity zone occurring beneath a depth of 40 m on the southeastern side of the study area, which is likely to be indicating part of the geothermal reservoir. The low-resistivity vertical/near-vertical features observed in this study are likely to be enabling the flow of geothermal fluids, and the high resistivity basaltic unit acts as a caprock overlying the reservoir.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"72 6","pages":"4139 - 4150"},"PeriodicalIF":2.3,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140593515","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":"Surface wave suppression through deformable convolutional wavelet transform network with residual dense blocks","authors":"Lei Gao,&nbsp;Haolong Hong,&nbsp;Dongsheng Liang,&nbsp;Fan Min","doi":"10.1007/s11600-024-01339-x","DOIUrl":"10.1007/s11600-024-01339-x","url":null,"abstract":"<div><p>Surface wave suppression plays a vital role in enhancing the quality of reflection seismic exploration. Convolutional neural networks (CNNs) can adaptively learn the characteristics of effective signals and surface waves. However, CNN has limited receptive fields and cannot effectively reuse features. When surface waves and effective signals overlap heavily, CNN struggles to preserve effective signals effectively. In this paper, we propose a deformable convolutional wavelet transform network (DCWTN) with residual dense blocks to suppress surface waves. DCWTN contains three types of modules: (1) The deformable convolution module (DCM) is designed to expand the receptive field and enhance seismic events continuity. (2) The wavelet transform enhancement module (WTEM) combines a wavelet transform and a residual dense block to suppress surface waves. It performs multi-scale feature extraction on surface waves according to their time–frequency characteristics to recover detailed information on overlapping parts. (3) The residual dense convolution module (RDCM) is designed for feature enhancement and further refinement of the acquired features. Experimental results show that DCWTN retains more effective signals than four popular methods.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"72 6","pages":"4151 - 4167"},"PeriodicalIF":2.3,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140593617","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":"Assessment of land use and land cover dynamics and its impact in direct runoff generation estimation using SCS CN method","authors":"Sivaprakasam Radhakrishnan Thiruchelve,&nbsp;Sundararaj Chandran,&nbsp;Veluswamy Kumar,&nbsp;Karuppiah Chandramohan","doi":"10.1007/s11600-024-01315-5","DOIUrl":"10.1007/s11600-024-01315-5","url":null,"abstract":"<div><p>The Madurai local planning authority, encompassing a land area of 726.34 sq. km, has encountered challenges of droughts and flash floods during the north–east monsoon season. These issues have arisen as a result of notable alterations in land use and the swift pace of urbanization. This comprehensive study aims to assess the effects of land use changes on direct runoff within the study area over a span of 40 years, from 1980 to 2020. This study attempted to understand the evolution of land use and land cover change in the Madurai LPA region over the past 2 decades and its corresponding impact on runoff generation. The study also predicted the trend of LULC in 2040. LANDSAT images from different years were acquired to create land use and land cover maps using ERDAS IMAGINE 9.1 and Arc GIS Version 10.1. Four hydrological soil groups were determined using data from the Madurai Atlas, and the surface runoff was calculated using the soil conservation service–curve number. The accuracy of the land use and land cover maps was evaluated using an error matrix and kappa index. LULC predictions for 2040 were made using the cellular automata and artificial neural network model. The analysis showed that agricultural land increased by 5.9% between 1980 and 2020, while forest cover decreased by 0.2% and urban settlements grew by 7.4% in the D hydrological soil group. The predicted land use for 2040 indicates that agricultural land will account for 54.1%, followed by 1% forest cover and 15.8% urban areas. The accuracy of the predicted land use map was validated using the 2020 map, with a 91% accuracy and a kappa coefficient of 0.8. The Madurai region has experienced a notable surge in urbanization, highlighting the urgency for effective flood management and the implementation of urban development strategies that prioritize the creation of green spaces and efficient storm water drainage systems.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"72 6","pages":"4415 - 4430"},"PeriodicalIF":2.3,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140593613","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":"GPS velocities and uniform slip rates across Siulak and Dikit segments: implication to segmentation and seismic moment deficits along Sumatran fault system","authors":"Ashar Muda Lubis,&nbsp;Indah Dwi Natasya,&nbsp;Lina Handayani,&nbsp;Agnis Triahadini,&nbsp;Muhammad Maruf Mukti","doi":"10.1007/s11600-024-01326-2","DOIUrl":"10.1007/s11600-024-01326-2","url":null,"abstract":"<div><p>The Siulak and Dikit segments of the Sumatran fault system, where historical major earthquakes of Ms 7.6 in 1909, Mw 7.2 in 1995 and Mw 6.6 in 2009 occurred, are distinctive and tectonically active, yet tectonic investigation such trench-parallel motions of both segments still is challenging to be better understand and important to constrain seismic hazard. We aim to better estimate slip rates as well as locking depths using GPS velocities and determine the cumulative energy stored at the segments. We processed raw GPS data from 31 GPS stations originating from the Indonesian continuous operating reference system (Ina-CORS), the Sumatran GPS array (SuGAr), and IGS networks for 2016–2021 including UNIB stations including two UNIB stations using GAMIT/GLOBK software. The daily GPS solutions were constrained into the ITRF-2014 frame, and the GPS velocities were translated into the Sunda Block. We modeled trench-parallel GPS velocities using 1-D screw dislocation elastic model following a Bayesian approach with Metropolis MCMC sampler to estimate optimum fault parameters. Our result inferred that estimated slip rates are 20.71 [− 2.20, + 2.95] mm/yr with a locking depth of 21.62 [− 11.98, + 14.16] km in the Siulak segment and 20.21 [− 2.42, + 2.95] mm/yr with a locking depth of 21.72 [− 13.10, + 14.77] km in the Dikit segment. Our analysis demonstrates both segments having a uniform slip rate, suggesting that the segments may share similar tectonic settings. In addition, the two segments are capable of generating a magnitude six to seven or greater earthquake if a single earthquake occurs in 50 to 200 years periods.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"72 6","pages":"3889 - 3902"},"PeriodicalIF":2.3,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140593776","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":"Integrated machine learning and remote sensing for groundwater potential mapping in the Mekong Delta in Vietnam","authors":"Huu Duy Nguyen,&nbsp;Quoc-Huy Nguyen,&nbsp;Dinh Kha Dang,&nbsp;Tien Giang Nguyen,&nbsp;Quang Hai Truong,&nbsp;Van Hong Nguyen,&nbsp;Petre Bretcan,&nbsp;Gheorghe Șerban,&nbsp;Quang-Thanh Bui,&nbsp;Alexandru-Ionut Petrisor","doi":"10.1007/s11600-024-01331-5","DOIUrl":"10.1007/s11600-024-01331-5","url":null,"abstract":"<div><p>Evaluating groundwater potential is critical for the socioeconomic development of Vietnam. This research aims to assess the underground water potential in the country’s Mekong Delta using the machine learning (ML) such as support vector machines (SVM), CatBoost (CB), K-nearest neighbors (KNN), random forest (RF) and AdaBoost (ADB). The problem of exploitation of groundwater resources in the delta is aggravated due to global warming and growth of population. In total, 146 groundwater points and 14 drivers (namely elevation, aspect, curvature, slope distance to river and river density, land use, normalized difference built-up index, flow accumulation, rainfall, soil type, normalized difference vegetation index, stream power index, terrain roughness index, and topographic wetness index) were used to assess groundwater potential. Each proposed model was evaluated utilizing area under curve (AUC), root mean square error, coefficient of determination (<i>R</i>²), and mean absolute error. The findings showed that the RF outperformed the others in building of a groundwater potential map. In which, AUC value was estimated at 0.99 and <i>R</i>² value was estimated at 0.63 then came CB (AUC = 0.98, <i>R</i>² = 0.56), ADB (AUC = 0.92, <i>R</i>² = 0.50), SVM (AUC = 0.91, <i>R</i>² = 0.57), and KNN (AUC = 0.75, <i>R</i>² = 0.45). The results illustrate the power of ML in assessing groundwater potential and can support decision makers, planners, and local authorities responsible for sustainable groundwater planning in the Mekong Delta and beyond.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"72 6","pages":"4395 - 4413"},"PeriodicalIF":2.3,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140593606","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":"Inference of fracturing zones and degrees of fluid content in the Las Tres Virgenes volcanic complex based on an analysis of seismic anisotropy","authors":"Francisco Chacón-Hernández,&nbsp;Jose Oscar Campos-Enríquez,&nbsp;Francisco Ramón Zúñiga,&nbsp;Javier Lermo-Samaniego","doi":"10.1007/s11600-024-01327-1","DOIUrl":"10.1007/s11600-024-01327-1","url":null,"abstract":"<div><p>Anisotropy strength in the Tres Vírgenes Volcanic Complex, Baja California Sur, Mexico, is analyzed employing 558 seismic events collected from 2009 to 2013. It was possible to delineate zones and volumes with the highest fracture densities, which are mainly located between the El Viejo and El Azufre volcanoes and around the La Reforma–El Azufre fault system, near some other mapped faults in the area (e.g., El Azufre, El Partido, El Volcán, El Viejo 1, and El Viejo 2 faults); likewise toward the La Virgen volcano and around the La Virgen-El Campamento and El Volcán faults. Individual delay times reached values of up to 0.16 s and an anisotropy percentage of up to 10.3%, with a pervasive anisotropy observed from at least a hypocentral distance of 3.5 km. High fracturing levels are observed from a depth of 7.0 km. Differences between splitting delays and the dominant frequency peaks obtained from the fast S phases allowed considering fracture systems with different degrees of fluid contents. Fractures with minor fluid contents were assumed for delay times higher than 0.03 s with lower dominant frequency peaks (&lt; 1.0 Hz). Higher concentrations of fluid inclusions were assumed for splitting delays higher than 0.03 s but with larger dominant frequency peaks (&gt; 1.0 Hz). Fractures systems chemically sealed or impermeable sealing caps were assumed for low splitting delays (&lt; 0.02 s) with low dominant frequencies (&lt; 1.0 Hz). These different fracture systems seem to be observed at least from 5- to 6-km depth intervals. Likewise, an analysis of the fast polarization directions with respect to different depth ranges (spanning from 3.0 to 8.0 km) has allowed observations of a strong NW–SE regional fracture system accompanied by minor NE–SW fracture systems. However, noteworthy variations from NW–SE to NE–SW, N–S, and E–W in fast polarization directions in rose diagrams have been preferentially observed for those seismic events deeper than 4–5 and 5–6 km in some areas, which could be indicating the location of magmatic bodies that probably caused the reorientation on fracture systems by changes in the local stress field. These magmatic bodies might be supported by a decrease in the dominant frequency peaks (lower than 1.0 Hz), percentage of anisotropy (from 0.1 to 2.5%), and S-wave velocities (from 1.0 to 2.7 km/s), which seem to be located from the 4.0-km depth but more concentrated from the 5–6-km depth interval.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"72 6","pages":"3863 - 3888"},"PeriodicalIF":2.3,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11600-024-01327-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140593615","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 3D surface wave attenuation method based on dispersion curve analysis and its application","authors":"Huo Yuanyuan,&nbsp;Yang Rui,&nbsp;Pan Jishun,&nbsp;Li Xin","doi":"10.1007/s11600-024-01318-2","DOIUrl":"10.1007/s11600-024-01318-2","url":null,"abstract":"<div><p>The thick loess sediments produce a lot of noise during seismic acquisition, typically surface wave. Conventional methods are difficult while suppressing 3D surface waves since they are hyperbolic in the far-array. This study proposed a new model-based, data-driven surface wave attenuation method, which uses dispersion curve analysis of surface wave and joint inversion based on genetic algorithm (GA) and conjugate gradient algorithm, to build an accurate surface wave model, and then to subtract the model data from seismic data to improve the signal to noise ratio (S/N ratio). Located in the southern part of the Ordos Basin, the Loess Plateau has the characteristics of large thickness of loess sedimentary layer, diverse geomorphology, complex geological conditions and developed surface waves. After applying the method to the field seismic data, numerical tests show that joint inversion of dispersion waves was stable, accurate, and efficient in multi-type models, including models with a low-velocity layer and with a high-velocity layer. The result showed that the 3D surface wave attenuation method is effective in surface wave suppression. The low-frequency information and the reflected signal are efficiently preserved. Seismic faces are more apparent for reservoir characterization. This method provided credible data for the exploration of the loess tableland area.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"72 6","pages":"4123 - 4138"},"PeriodicalIF":2.3,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140593713","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":"Elevating the possibilities of meshless groundwater flow modeling: a developed approach for parameter estimation and uncertainty quantification","authors":"Mahdi Khorashadizadeh,&nbsp;Siavash Abghari,&nbsp;Abolfazl Akbarpour,&nbsp;Ali Mohtashami,&nbsp;Seyed Arman Hashemi Monfared","doi":"10.1007/s11600-024-01287-6","DOIUrl":"10.1007/s11600-024-01287-6","url":null,"abstract":"<div><p>Groundwater modeling is often associated with uncertainties due to incomplete knowledge of the subsurface system or uncertainties arising from variability in model system processes and field conditions. So far, not much research has been conducted to investigate the uncertainty of the groundwater flow model. Studies in this field focus on statistical methods. Due to the need to investigate the uncertainty to obtain reliable results, this study presents an approach to evaluate the uncertainty parameters of the groundwater flow model. In this way, modified GLUE (MGLUE) method as the uncertainty assessment method is linked to the meshless local Petrov–Galerkin (MLPG) as the simulation model. The method (which is called MGLUE-MLPG) is applied to two aquifers. In the first aquifer, three parameters of the meshless flow model (parameters related to the numerical method e.g., sizes of the integration and weight subdomains and the amount of the penalty coefficient) are identified as uncertainty parameters. The results indicate that these three parameters have a high degree of uncertainty, so their coefficients of variation are 72.37, 19.92 and 51.55, respectively. In the second standard aquifer, in addition to the numerical parameters, the transmissivity coefficients (model parameters) in two different directions (horizontal and vertical directions) are taken into account in the uncertainty model. The results show more uncertainty for the numerical parameters and do not show many changes in the transmissivity coefficient parameter. This means that the box diagrams of these parameters are almost the same. After precise values have been reached, groundwater flow was simulated. The obtained results are so accurate as to indicate the importance of using this model for all aquifers. In the first aquifer, the root mean square error (RMSE) values for MGLUE-MLPG and finite element method (FEM) are 0.236 and 0.249 m, respectively. The second aquifer shows higher accuracy than the other numerical method, so the RMSE values for MGLUE-MLPG and PPCM are 0.0060 and 0.0121 m, respectively.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"72 6","pages":"4373 - 4393"},"PeriodicalIF":2.3,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140593741","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}