Acta Geophysica最新文献

For risk assessment and management, accurate solute transport modeling is essential because groundwater contamination affects drinking water and ecosystems. In this study, a solute transport model incorporating adsorption, dispersion, and homogeneous flow across different geological formations is developed and compared to improve groundwater contamination prediction accuracy. Under realistic boundary circumstances, solute transport is examined with a uniform source concentration at one end of the geological formation and zero mass flux at the other. Analytical solutions are produced via the Laplace transform, whereas numerical solutions are produced by finite difference methods. The model’s performance is evaluated using the Normalized Root Mean Square Error (NRMSE), Global Performance Indicator (GPI), and statistical tests including two-way ANOVA and t-tests. The unique temporal and spatial concentration patterns found in gravel, silt and clay are effectively represented by the model. Significant variations in solute behavior among geological formations were confirmed by statistical studies and NRMSE values varied from 0.004 to 0.05 across formations. The impact of hydrological conditions on solute distribution is illustrated graphically; clay exhibits higher retention and slower migration than silt and gravel. The model accurately forecasts solute transport and emphasizes the essential function that geological characteristics play in pollution retention. In addition to offering helpful suggestions for groundwater monitoring, pollution prevention, and sustainable water management, it offers insightful information for further reactive transport study.

This study presents a theoretical and numerical investigation into the role of the vertical gravity gradient (VGG) in the analytical downward continuation of surface gravity data for geoid determination. Several VGG computation techniques, including integral-based, FFT-based, and integrated second vertical derivative (ISVD)-based methods, are evaluated using synthetic, noise-contaminated gravity disturbances at (1'times 1') and (2'times 2') resolutions. Among these, ISVD-based methods consistently demonstrate better numerical stability and accuracy. A new iterative downward continuation approach is proposed, which uses VGG values computed on the reference ellipsoid. Its performance is compared to the conventional Taylor series expansion and Poisson integral methods. While the Poisson integral achieves slightly better accuracy (2.1 mGal) when optimally regularized, the proposed iterative method attains comparable accuracy (2.4 mGal) using a simpler regularization strategy- fixed truncation after the second iteration. The proposed method also outperforms the Taylor approach under the same regularization conditions. The results further indicate that higher-resolution input data do not necessarily improve downward continuation accuracy; instead, they can amplify high-frequency noise beyond the signal bandwidth. These findings offer practical guidance for selecting VGG computation methods, regularization strategies, and spatial resolutions in geoid modeling applications.

This study examines the structural characteristics of the Cerro Prieto and Indiviso Faults within the Colorado River Delta, Baja California, México, through seismic reflection, seismicity, magnetic, and gravimetric analyses. The Cerro Prieto Transform Fault, a critical component of the Pacific-North American plate boundary, traverses the Mexicali Valley and northern Gulf of California, within the study area. A key objective is to determine whether the Indiviso Fault existed prior to or originated during the 2010 Mw 7.2 El Mayor–Cucapah earthquake. Results confirm the Indiviso Fault as a pre-existing structure reactivated during the event. Gravimetric and magnetic anomalies and seismicity delineate their obliquity to the Cerro Prieto Fault and intersection with the Wagner Basin, challenging prior models of the Cerro Prieto Fault's trajectory. Tectonic activity along the La Mesa and Santa Clara Faults correlates with significant subsidence beneath the Ciénega de Santa Clara. Seismic profiles reveal buried faults, such as Yurimori and Pangas Viejas, that lack surface expression. Post-earthquake deformation transitioned from the Cerro Prieto Fault to the Indiviso Fault, resembling slip-transfer processes observed in the San Andreas Fault system. Declining seismicity along the Cerro Prieto Fault contrasts with diffuse regional activity, underscoring the role of transform faults in accommodating interplate motion. Aftershocks were concentrated beneath sedimentary lowlands, while surface ruptures predominantly occurred in mountainous areas, influenced by lithostatic stress conditions. The primary rupture initiated along the northern Indiviso Fault zone, where differential stress reactivated pre-existing structures. Another aspect supporting this interpretation is that historical seismicity also shows a trend along the Indiviso Fault. The relocation of these identified two significant events that occurred in 1934 (Mw 6.5 and 6.3), as well as the 1935 event (Mw 5.7), distributed along this structure. This evidence indicates that the Indiviso Fault already existed and was tectonically active since that time. However, it is noteworthy that, prior to the EMC event, virtually no seismic activity was recorded in the region. These findings contribute to the understanding of fault reactivation, transform fault dynamics, and regional seismic hazard assessments.

This paper presents a comprehensive comparative analysis of Global Navigation Satellite System (GNSS) module performance in both static and dynamic Unmanned Aerial Vehicle (UAV) environments, focusing on four major satellite navigation systems: GPS, BeiDou, NavIC, and Galileo. Two separate test scenarios is conducted here. In the dynamic test, the M8N GPS and 7Semi L89-based BeiDou modules is simultaneously mounted on a drone and evaluated using predefined waypoints in Mission Planner software. Results showed that the GPS module exhibited more stable and responsive roll, pitch, and yaw tracking during high-speed maneuvers and BeiDou module provides superior horizontal positioning accuracy due to its utilization of multiple orbital planes (MEO, GEO, IGSO). In the static evaluation, NEO M8 (GPS), PX1125S-01D (NavIC), and 7Semi L89-based Galileo modules were assessed. The NavIC-enabled PX1125S-01D demonstrated the highest positioning accuracy and the most consistent signal strength in an open-field setup in the Indian region. Galileo offeres low DOP values and excellent accuracy in multi-satellite environments, while GPS maintained reliable performance with broader global coverage. To address the limitation of short-duration trials, an extended 3-h static experiment was carried out, which confirmed NavIC’s superior stability and further emphasized the effect of long-term observation on evaluating constellation reliability. Key performance metrics such as HDOP, VDOP, GDOP, CEP, and 3DRMS are measured for assessment. The findings indicate that no single system is optimal for all use cases: NavIC and BeiDou excel in precise navigation under favorable signal conditions, while GPS provides dependable performance in fast-changing and globally diverse environments. A hybrid GNSS configuration that integrates the strengths of multiple systems could significantly enhance UAV navigation accuracy and stability across varying operational contexts.

The Gutenberg–Richter law describes an exponential relationship between earthquake magnitude and frequency, with the b value as a key parameter for quantifying the relative occurrence of large versus small earthquakes. Accurate estimation of the b value is important for various seismological applications, particularly in identifying asperities, i.e., areas of strong coupling between subducting and overriding plates in the subduction zones. The challenge in mapping spatiotemporal variations of the b value and resolving their spatial heterogeneity is small data sets for which the estimation error is large. To balance the two opposite goals, the smallest estimation error and the largest spatial resolution, we propose the overlapping window algorithm. This method partitions seismic data into overlapping windows, allowing for a more detailed characterization of spatial variations in the b value. We applied the algorithm to the 1998–2024 seismicity in the Japan subduction zone, revealing significant b value patterns that can be interpreted in terms of the locked asperity distributions before and after the largest earthquakes. These patterns suggest that the b value changes reflect plate coupling preceding and following major seismic events. The changing shapes of the small b value patches suggest areas where a strong earthquake is likely to occur. In particular, a future m9 earthquake initiated off the coast of Hokkaido and extending to the area off the coast of Honshu seems likely. Our results demonstrate that this approach, when combined with other methods, provides insight into stress redistribution and locked asperity locations, offering a tool for estimation of location and size of possible future large events.

The objective of this paper is to verify a research hypothesis that there exist certain types of atmospheric circulation for which short-term hydrologic ensemble predictions, with lead times ranging from a few minutes to a few hours, are skilful. In the aftermath of the scrutiny, the forecaster will have the information on what skills to expect in case of a given atmospheric circulation type. Herein, atmospheric circulation is not considered as an input variable in the process of issuing short-term hydrologic forecasts, but it characterises favourable and unfavourable meteorological background for these prognoses to perform well. Short-term (up to 3 h into the future) multimodel ensemble predictions of water levels in the upper Nysa Kłodzka river basin (southwestern Poland) were computed using HydroProg, one of the hydrologic ensemble prediction systems. Nash-Sutcliffe efficiency (NSE) statistics of those forecasts was computed and juxtaposed with 40 types of atmospheric circulation. The latter types were based on the combination of direction of advection, the cyclonality index and the humidity type. The experiment was conducted between 1 September 2013 and 3 December 2016, when the HydroProg system was working in real time. The hydrologic multimodel ensemble prediction was based on up to six ensemble members. Forecasts were issued at 11 sites within the basin, had 12 intermediate 15-minute steps (lead time ranged from 15 to 180 min) and were updated every 15 min. It was found that the most skilful short-term water level predictions, classified according to a widely accepted classification into good or satisfactory prognoses (NSE (ge) 0.36), were associated with the wet humidity type, with prevailing northerly advection of air masses. Although meteorological conditions, during which short-term multimodel ensemble predictions perform well, were identified, the relation was not quantitative (statistical) but rather qualitative (based on prediction ranking in relation to circulation types). It presents some meteorological background for good or satisfactory short-term hydrologic prognoses, but cannot be used as a variable for refining these forecasts.

This study introduces a Composite Integrated Meteorological Drought Index (CIMDI), based on combination of other well-known indices: Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Standardized Precipitation Temperature Index (SPTI) utilizing a hybrid weighting scheme based on steady-state probabilities and mean squared correlation. The index was constructed using 41 years (January 1981–December 2021) monthly climatic data from 21 meteorological stations in Punjab region of Pakistan aims to provide a robust, balanced, and an integrated measure of assessment for the meteorological drought. CIMDI’s performance was measured by a variety of statistical error and efficiency measures. It positioned an RMSE of 0.34, which is significantly lower than SPEI (0.98), and SPTI 0.41 at station Gujrat, thus reflecting a better prediction result. In terms of accuracy, the mean absolute error for CIMDI was 0.41, as compared to 1.44 (SPEI), 0.47 (SPTI) at station Jhang. The Standard Error of Estimate value for CIMDI was 0.34, also less than SPTI (0.41) and SPEI (0.98) at station Gujrat, thus proving that it can be said to have a better fit. The correlation coefficient (r) was found to be greater than 0.90 despite being positive for SPI and SPTI and was moderate for SPEI (e.g., > 0.59 and > 0.77 at Sargodha and Rawalpindi and Jhelum, respectively). Trend analysis with Mann–Kendall test showed cluster increasing trends for drought occurrence for several stations used for drought trends, namely Sargodha (p = 0.001), Rawalpindi (p = 0.0022), Jhang (p = 0.0126), and Bhakkar (p = 0.0311) which indicated increasing severity of drought in respective areas. CIMDI also obtained an efficiency (EF) value of 0.39 substantially higher values in comparison with the negative values obtained from SPEI which was ((-)0.77) and SPTI ((-)0.76) showing better performance in acts of estimating drought intensity at station Faisalabad. Its confidence level reached 0.38, preceding it for a higher reliability with the real drought condition capturing in a better way. In addition, CIMDI allowed for smoother transitions between months, less noise in classification and no abrupt shifts as is common in individual indices. It showed consistent results in both arid, semiarid, and humid zones-‘proving’ that it is spatially adaptive. Overall, CIMDI shows great advancements in accuracy, stability, and reliability, a tool that can aid drought monitoring, early warning, and climate resilient planning in areas at risk.

Lithology identification is a fundamental task in seismic reservoir characterization. However, existing studies have primarily focused on optimizing single algorithms, with limited systematic comparisons of ensemble models and hyperparameter optimization strategies. To address this issue, this study, based on well seismic data from the North Sea F3 block, integrates recursive feature elimination with cross-validation (RFECV), the Near-Miss Synthetic Minority Oversampling Technique (NM-SMOTE) sampling strategy, and four mainstream hyperparameter optimization methods to evaluate the performance of random forest, XGBoost, LightGBM, CatBoost, and stacking ensemble method. NM-SMOTE (Near-Miss SMOTE) effectively alleviates the class imbalance problem by synthesizing minority sandstone samples and retaining key mudstone samples that are closest to the minority class (while reducing the majority class size), thereby improving the reliability of minority class recognition. Fivefold cross-validation was employed, using well log lithology interpretation as ground truth for validation. The results indicate that Optuna achieves the best balance between efficiency and accuracy, outperforming Bayesian optimization and grid search in terms of test accuracy, training time, and model stability. CatBoost achieves the highest prediction accuracy (area under the receiver operating characteristic curve, AUC = 0.91), demonstrating clear sandstone–mudstone boundaries and superior continuity in predictions. These findings provide a reliable basis and methodological support for the selection and optimization of intelligent lithology identification models under complex geological conditions.

An experimental investigation was undertaken to examine the temporal evolution of turbulence characteristics and higher-order flow correlations for a discharge of 0.0176 m³/s in a rigid bank, mobile bed channel. Three-dimensional velocity components were captured using an Acoustic Doppler Vectrino Profiler to facilitate detailed turbulence analysis. Turbulent kinetic energy (TKE) exhibits its minimum and maximum values close to the outer and inner bend, respectively, at the upstream and apex regions, while at the downstream, the higher TKE occurs at the center. Near the bed, the TKE flux shows downstream-downward flux transport toward the inner bend. The TKE budget indicated that, in the near bed region, the TKE production rate and diffusion rate exhibited both positive and negative tendencies, whereas the TKE dissipation rate was positive, and the pressure energy diffusion rate showed a negative tendency. The eddy size, computed using the Taylor microscale with in the inertial subrange, increases at the inner and center points at the upstream. At the apex and downstream locations, it is located at the center points of the bend. The turbulence indicator states that the level of local turbulence is more dominant at the outer bend points. The second order streamwise–vertical and streamwise–lateral correlations indicate a sign reversal, confirming the existence of secondary flow. Third order correlations can be helpful to confirm the streamwise–downward flux, which shows the characteristics of sweep events responsible for the bed movement. The fourth order correlations indicated strong characteristics of turbulence intermittency behavior. The results of the current study are applicable to the selected case of the modeled river reach and can be extended to natural sinuous rivers by considering the limitations. The current study provides significant understanding of flow turbulence and can be helpful to hydraulic engineers for designing structures in an asymmetric sinuous channel qualitatively.

Due to the increasingly negative impacts of drought, which affects water resources, agricultural activities, and all sectors, there is a need to analyze the drought trend to understand its effects and mitigate them comprehensively. This research aims to spatiotemporally analyze the drought trend based on the well-known Standardized Precipitation Index (SPI) at different timescales using classical and innovative trend analysis methodologies, including Mann–Kendall (MK), Sen’s slope (SS), and newly proposed Frequency Innovative Trend Analysis method (F-ITA) over the Antalya basin, Türkiye with monthly precipitation data from 1969 to 2022 for the first time in the literature. Also, the research calculates the slope and actual trends using SS and ITA methodologies along with the drought classifications and frequencies, providing a deeper understanding of the drought patterns and their variability. This research generally indicated an increasing trend in drought events for SPI-3 and SPI-6 based on classical methods and F-ITA graphs for specific stations. However, F-ITA for SPI-12 showed a significant drought trend across all stations, with increased drought frequencies; for example, Alanya station exhibited a monotonic increasing trend, with the frequencies of MD, SD, ED, and EXD approximately doubling over the study period. The spatial distribution of slopes computed by SS and ITA and their respective actual trends exhibited significant parallels, resulting in more frequent drought events and an increased drought trend in the southern parts of the region near the coast. The southern and southeastern parts of the study area exhibited the highest trends and slopes. In summary, analyzing drought trends and their spatio-temporal distribution provides critical and crucial insights for sustainable water resources management and agriculture, and guides policymakers in developing effective adaptation and mitigation strategies.