Journal of Earth System Science最新文献

This study presents a pioneering approach that combines artificial intelligence and a nature-inspired optimization algorithm to predict soil unconfined compressive strength (UCS). The traditional laboratory-based method of UCS measurement, involving soil sample preparation, is time-consuming, labour-intensive, and prone to low accuracy. In this work, we propose a non-destructive soil UCS measurement technique utilizing robust AI-based models based on ensemble learning and hybrid learning techniques. Support vector machine (SVM) coupled with particle swarm optimization (PSO), extreme gradient boost (XGB), K-nearest neighbour (KNN), and nature-inspired optimization algorithm-based six hybrid ANFIS models, employing input features from experimental data, were adopted for UCS prediction. Model performance was assessed using standard metrics such as root mean square error, mean absolute error, variance account factor (VAF), expanded uncertainty (U₉₅), and coefficient of determination (R²) between predicted and actual unconfined compressive strength. The study employed 274 data points generated in our laboratory. Sensitivity analysis and Pearson correlation techniques were employed to select relevant elements as input features. Fine content, coarse content, liquid limit, plastic limit, plasticity index, and cohesion of soil were identified as the most effective configurations for accurate soil UCS predictions. XGB demonstrated the highest prediction efficiency in the training and testing phase, achieving an impressive R² of 99.2 and 96.8%, respectively. The results also emphasize the importance of the selected features. The experimental validation accuracy of 97% for the developed XGB model, whose data were not used during model calibration and verification, confirmed the generalization capability of the models. This study provides valuable insights for policymakers and industry stakeholders, facilitating optimized soil unconfined strength management practices.

This contribution presents for the first time a digital elevation map and 1:50,000 scale geological map of Sitagota syncline, Khairagarh Group, which is spread in around 1000 km² area in the north Bastar Craton (survey of India toposheets 64 C/11 and C/15). We report for the first time, exposures of Algoma-type banded iron formation, intertrappean shale, and oxide and sulphide mineralization in Mangikhuta basalt. Mafic enclaves are reported in the Dongargarh granite. Geochemistry and petrogenetic study of Mangikhuta and Kotima volcanics of Khairagarh Group is presented. Although field investigation and digital elevation map reveal Khairagarh volcano-sedimentary sequence underwent more than one phase of orogeny, the ubiquitous presence of very low-grade metamorphic mineral assemblages in volcanic rocks indicates they did not undergo high P–T transformation and most of the alteration and metamorphism took place at near-surface conditions. Our tectonomagmatic model proposes the occurrence of a rift basin in the north Bastar Craton from 2.46 to 2.2 Ga, resulting in sedimentation and high-Mg basalt to basaltic-andesite magmatism. The genesis of Sitagota syncline is attributed to closure and deformation of this rift basin due to compressive forces, probably related to Paleoproterozoic Dongargarh Kotri mobile belt and Mesoproterozoic central Indian tectonic zone. Tectonomagmatic and geochronological similarity of Khairagarh Group to Lower Wyloo Group of Ashburton basin in Pilbara Craton and Hekpoort and Ongeluk basalt formations of Transvaal basin in Kaapvaal Craton indicates Bastar Craton was part of Vaalbara supercontinent in Paleoproterozoic times.

The Coimbatore corporation area is comprised of very densely occupied residential and commercial buildings which are prone to future earthquakes. Probabilistic Seismic Hazard Analysis (PSHA) was carried out for the study region using the Classical Cornell approach and the logic-tree approach. A combination of 45 linear/fault sources and an areal source with a 500 km radius has been considered for the study. An updated earthquake catalogue has been compiled from various works of literature and authorized organizations. The collected earthquake catalogue of various magnitude scales has been homogenized into a uniform moment magnitude scale (left({M}_{w}right)). Fore-shocks and after-shocks have been removed from independent events using one of the declustering algorithms. The seismicity parameters have been evaluated using the Guttenberg–Richter recurrence law. A hybrid GMPE composed of three attenuation relationships was used to obtain the ground motion parameters for the study region. The contour maps of Peak Ground Acceleration (PGA) and Peak Spectral Acceleration (PSA) for the bed-rock condition have been presented in terms of 10 and 2% Probability of Exceedance (PoE) for the return period of 475 and 2475 yr, respectively. The Uniform Hazard Response Spectra (UHRS) for Coimbatore city has been compared with (IS 1893-I-(2016) Criteria for earthquake resistant design of structures. Part 1: General provisions and buildings; Bureau of Indian Standards). As a result of deaggregation, the predominant hazard has been found within a 100 km distance and no hazards have been observed from a long distance as a controlling scenario from the analysis.

A generalized forward modelling equation to calculate the magnetic anomalies of a randomly magnetized finite-strike listric fault source is derived using Poisson's relation. This new equation combines both analytic and numeric approaches to realize forward modelling of the anomalous source in any component. Polynomial functions are adopted to simulate the geometry of the curved fault plane between the displaced hanging wall and the footwall of the fault morphology. The utility of the derived equation is epitomized with a theoretical model of a limited-strike listric fault morphology by computing the anomaly in the vertical, horizontal and total field components. It is demonstrated that the magnitude of the anomalous field (in any component) does not remain the same but changes with the profile offset, albeit the anomalous source remains the same. The effect of structure dimensionality (2D vs. 2^1/2D) on the magnitude of the anomalous field is also discussed.

Interpretation of vertical electrical sounding (VES) data is inherently difficult due to its ambiguity and non-linear characteristics. Conventional least square-based methods rely on a well-defined apriori model, constrained by ground information (available borehole logs and field observations of exposed lithological sections) for meaningful interpretations. In this work, a back-propagation neural network-based model was developed to estimate layer resistivities and thickness from given apparent resistivities. The model was trained and validated on noise-infused synthetic datasets. Since the effectiveness and generalisation of any model depend on its hyperparameter settings, we investigated effective methods for estimating hyperparameters such as learning rate, momentum, model architecture and learning rate scheduling parameters. It is well known that the optimal values of hyperparameters are not entirely independent of each other. Thus, any change in one hyperparameter changes the optimal range of all other hyperparameters, and thus, tuning any hyperparameter individually is futile. This warrants a joint hyperparameter tuning along with network architecture, which was carried out using a modified version of meta-heuristic black hole algorithm. The modifications include randomly flipping one or more coordinates of the population stars (solutions) whose cost function was above a threshold value decided by a mutation rate parameter. This helped in boosting the exploration capability of the algorithm and prune trajectories with higher cost functions. It is demonstrated that with a finely tuned neural network model, reasonable resistivity model parameters which interpret the ground conditions fairly well could be obtained. The model was tested on resistivity-sounding data with associated borehole lithologs and was found to be giving reasonable results. The same model was used to estimate the overburden thickness consisting of topsoil and deposited silts in Bhadradri–Kothagudem district, India. The layer thickness was consistent with those seen in cutbanks in the area. The methods of optimal hyperparameter set estimation are not exclusive to this model and can be used to train models accomplishing other geophysical tasks.

Abstract

This paper investigates the initiation and evolution of polygonal crack patterns in desiccating soil layers with varying thicknesses and grain sizes, both with and without a secondary saturated sand layer placed beneath the soil layer. Single-layer experiments involved soil samples within a specific range of grain sizes (0–100, 100–300, 300–500, and 500–850 μm), maintaining soil layer depths at 10, 20, 30, 40, 50, and 60 mm. In double-layer experiments, a saturated sand layer was introduced below the soil layer to check the role of relative layer thickness on crack patterns. Time-lapse photography captured surface crack development during desiccation, allowing for the measurement of geometric parameters like crack width, crack intensity factor (CIF), and intersection angle (CIA). The single-layer models indicate an increase in crack width and CIF with greater layer thicknesses, while CIA decreases with increased layer thickness. Additionally, experiments with finer grain sizes exhibit relatively wider cracks, along with higher CIF and CIA. In double-layer models with varying thicknesses of individual layers, crack growth is found to be independent of the upper soil layer's thickness. Instead, crack propagation is controlled by the lower sand layer, as the supply of water from the lower sand layer to the upper soil layer facilitates prolonged desiccation, resulting in larger CIF values. Using digital image processing and the box-counting method, we calculated the fractal dimensions (D) of the cracks were calculated. D demonstrates positive relationships with grain size in both single- and double-layer experiments, suggesting a self-similar evolution of crack patterns in the models with coarse-grained soil.

Research highlights

• The role of basal water-rich sand layer in the growth of mud-cracks is investigated.

• Layer thickness and grain size are two additional variables during the experiments.

• Single mud-layer experiments were used to compare the double-layer experiments.

• Basal wet-sand delays desiccation, resulting in a higher crack intensity factor.

• Finer grains produce denser cracks irrespective of the imposed variables.

• Low fractal dimensions in course-grained soils imply a self-similar crack pattern.

The Koum Basin is a North Cameroonian intracontinental basin that is part of the upper Benue Trough, notably the Yola arm. The sediments of this basin were examined to determine paleoenvironmental and paleoclimatic interpretations, which were based mostly on sedimentology and mineralogical evolution in its central part. The examined materials are dominated by claystone and siltstones of varied colours, which are, for the most part, carbonated, and a few layers of fine to medium sandstone and conglomerate. The bulk organic geochemistry enabled the designation of type III kerogen, indicating a terrestrial origin of organic matter, which shows predominantly immature issues. The bulk mineralogy development exhibits no significant changes and is dominated by phyllosilicate (25.66%), calcite (24.5%), plagioclase (19.36%), and quartz (19.31%). Smectite, illite, and vermiculite dominate clay mineral fraction, with only low quantities of kaolinite and chlorite. The diagenesis influence is low to moderate, as shown by moderate illitization and chloritization as well as T_max values. The deposition occurred in a globally semi-arid climate, as evidenced by the permanent occurrence of smectite, punctuated by short periods of drier and humid weather.

This comprehensive study aims to investigate the cloudburst events that occurred in the Indian Himalayan Region (IHR) during the year 2022, focusing on their characteristics, structure and dynamics. Cloudburst events have been observed in different states of the Himalayan region, with their unique geographical features, and are susceptible to extreme weather phenomena, which pose significant challenges to the local communities and infrastructure. A majority of cloudburst events occur within the folds of valleys of the Indian Himalayas, where elevations range from 325 to 4073 m. As the year 2022 witnessed frequent cloudburst events in the IHR (Himachal Pradesh recorded around 24 cloudburst events, Uttarakhand recorded 18 and Jammu and Kashmir recorded 24 events), an attempt is being made for the comprehensive analysis of the role of atmospheric dynamics to result in such extreme events in the valley region. The analysis clearly advocates that certain atmospheric phenomena, such as frontal boundaries like temperature, humidity, convective available potential energy, convective inhibition, or atmospheric disturbances, can act as triggers for cloud burst events. The spatial distribution of different thermodynamic parameters during the previous day, event day and the day after the cloudburst events are also analysed to quantify the role of atmospheric dynamics in the temporal distribution. This study has highlighted the importance of low-level jets and moisture transport in forming the convective systems that lead to cloudbursts over the Himalayan region due to wind patterns.

Abstract

In this paper, gravity dataset acquired from a recent ground survey spanning 3500 km² in parts of Mahakoshal–Vindhyan Basin, central India, has been analysed with an aim to evaluate gravity anomalies and assess structural attributes that could identify potential areas for mineral exploration. The Bouguer gravity anomaly exhibits a total variation of 41 mGal with a prominent high in ENE–WSW axis demarcating the Mahakoshal Fold belt, whereas, a low gravity anomaly (–48 to –59 mgal) is predominantly observed over Vindhyan basin. Various geophysical processing techniques identify absence of deformations in the Vindhyan basin. The data analysis shows the presence of ultramafic intrusives, a few anomalous zones corresponding to shear and fault zones in Mahakoshal, trending in multiple directions (E–W, ENE–WSW, NE–SW, and N–S). These tectonic features significantly impacted the development of the Mahakoshals and Vindhyans. Derivative-based anomaly maps reveal three distinguished high-gradient fault zones in the north, east and south of the Mahakoshal belt. In the southeast of the Mahakoshal belt, a prominent low gravity anomaly of shear zone, probably caused by rifting, is delineated. The depths of anomaly sources are estimated using spectral analysis, Euler solutions, Werner solutions, and analytical maxima solutions. Furthermore, 2D forward modelling of gravity data along a specific profile aid in constructing a schematic evolutionary model for the Mahakoshal and Vindhyan regions in the study area. Notably, the present work reveals distinct curvilinear sheared basement zones in the southeastern Mahakoshal belt, suggesting potential zones for future mineral exploration through integrated studies.

Highlights

• The paper presents the geophysical anomalies of a ground gravity dataset acquired at a station density of 2.5 km² over 3500 km² in segments of Vindhyans and Mahakoshals.

• Gravity data evaluation discerns the presence of high-density ultramafic rock as well as a distinctive anomalous shear zone controlled by supracrustal faults within the Proterozoic Mahakoshal Fold belt.

• Based on the geophysical characteristics and structural assessments, three potential target zones have been identified for future mineral exploration.