Results in Earth Sciences最新文献

Groundwater is essential for efficient management of groundwater to prevent the deterioration of its quality. The objective of this study is to evaluate the vulnerability of the primary campus of (Olusegun Agagu University of Science and Technology) OAUSTECH in Okitipupa, Ondo State, Nigeria. This was done by analysing the GOD index and the Dar Zarrouk parameters of conductance and transverse resistance. A total of 24 Vertical Electrical Sounding (VES) data points were gathered, with AB/2 values varying from 200 to 225. These data points were then analysed utilising partial curve matching and computer iteration techniques to determine geoelectric characteristics, including resistivity and thickness. The computed characteristics, longitudinal conductance and transverse resistance, suggest that the aquifer's ability to defend against contamination in the research area is generally insufficient. The longitudinal conductance values range from 0.02 to 0.6, with most values below 0.1. Using the GOD method, the study shows that the GOD index value varies from 0.2 to 0.6, with an average of 0.325, suggesting a moderate to high level of vulnerability in the groundwater. The association between the GOD index and longitudinal conductance results in a 60 % accuracy in predicting groundwater susceptibility. This research emphasises that the groundwater within the main campus of OAUSTECH is moderately to highly vulnerable.

Far–field tectonics can often be overlooked when studying orogens, particularly when much of the deformation occurs near the loading loci. As stresses are propagated further from the loading into the craton, whether compressional, extensional, or shear, faults and fractures within the basement often act as pathways for stress transmission, traveling along these pre-existing planes of weakness, or creating new. The Appalachian Basin in the eastern United States is a classic foreland basin example that showcases far-field tectonic influence on deposition and structure. This study characterizes the structural architecture of the basement along the western Appalachian Basin margin by analyzing well log data from 2,662 wells to create structure, isopach, trend surface, and residual maps of Late Cambrian through Upper Ordovician strata (Knox through Black River). Fourteen lineaments interpreted as faults were delineated, creating two series of horsts and grabens. The northeast–southwest faults are related to structures that formed during Keweenawan extension, and the northwest–southeast faults are related to structures that formed during the Grenville Orogeny. Both sets of faults stem from the Precambrian basement and are shown to have been reactivated during the Blountian Tectophase of the Taconian Orogeny (Black Riverian deposition), creating localized thinning and thinning adjacent to the lineaments. Furthermore, these faults appear to have undergone additional reactivation since the deposition of these strata in a transtensional regime to create the observed horst and graben structures. Overall, far–field tectonics plays an important role in understanding the geologic history of a basin.

This study addresses the pressing global water challenge by focusing on a typical basement complex area experiencing acute water shortage. Indiscriminate well siting without reliable hydrogeological maps has resulted in failed attempts to address water shortages. To overcome these challenges, this research aims to enhance the accuracy and reliability of groundwater potential assessments by incorporating crucial groundwater-related factors.

The Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) method was adopted due to its ability to improve multi-criteria decision-making (MCDM) techniques for effective groundwater resource management. Unlike TOPSIS, FTOPSIS better reflects decision-makers' intentions, especially concerning geological boundaries and natural phenomena. To achieve the objectives of the study, geophysical and remote sensing datasets were utilized. The study employed the electrical resistivity method, utilising the Vertical Electrical Sounding (VES) technique with the Schlumberger array while the remote sensing data used were the Digital Elevation Model (DEM) image and Landsat ETM image which were processed to generate key groundwater conditioning factors. These factors were integrated using the FTOPSIS algorithm. This algorithm facilitated the calculation of the groundwater potential indices by assigning weights based on their level of significance to influencing groundwater potential in order to generate the groundwater potential map (GPM). The GPM was classified into five zones of varying groundwater potential, with very low and low potential occupying 74 % of the total area. Validation with well data yielded an impressive 79 % accuracy, showcasing the model's enhanced precision. Beyond improved accuracy, the study's implications extend to practical applications in groundwater resource management. By providing a clearer understanding of groundwater potentiality, the research can inform more robust decision-making frameworks, promoting sustainable water use not only in the study area but also in similar geological settings of the world.

Determining the degree of an aquifer’s susceptibility to pollutants is an important tool for policy planning in subterranean water administration and conservation. In this work, subterranean water vulnerability was appraised with the use of DRASTIC methodology, which employs seven parameters: depth to groundwater (D); net groundwater recharge (R); aquifer media (A); soil media (S); topography (T); influence of vadose zone (I); and hydraulic conductivity (C). Different ratings were given to each parameter based on the hydro-geological and geo-electrical information obtained from the study area. Geo-electrostratigraphic data was acquired with vertical electrical soundings and electrical resistivity tomography surveys. The results demonstrated the existence of geoelectrical layers with variable resistivities ranging from high to low, with variable curve types. Longitudinal conductance measures indicated moderate subterranean water protective capacity. Analysis of DRASTIC vulnerability indices showed that the aquifer indicated moderate to high vulnerability to contamination. Vulnerability maps were generated to indicate locations of high vulnerability, the goal being to prevent indiscriminate haphazard and wildcat abstraction of groundwater in such locations. The quality category index (QCI) generated for the DRASTIC model indicated that underground water susceptivity is dependent on all 7 parameters employed in the model, with the most critical determinants being the depth to aquifer (D), net recharge (R), aquifer media (A), and impact of the vadose zone (I). The work recommends that anthropogenic activities that could contaminate groundwater resource be halted as the resource is indicated by DRASTIC models as being vulnerable.

This study investigated the circulation patterns associated with rainfall variations across Nigeria’s different climatic zones (2000–2022). Data was acquired from MERRA2, gridded ERSST5 provided by the NOAA, and observation data records obtained from the Climatic Research Unit (CRU). Principal Component Analysis (PCA) was employed to compare different precipitation types, while the Multinomial Logistic Regression Model was employed to examine the influence of SSTa on precipitation presenting regression coefficients with a significance level set at p < 0.05. Five distint standard precipitation index (SPI) classes: very dry, dry, normal, wet and very wet were categorised using prcipitation data. Analysis was done in R-studio and involved data preparation, model training, and evaluation, with emphasis on interpreting the coefficients to discern the impact of SST anomalies on precipitation for each specified level. The results show that TOP, AVP, LSP, and CNP varied: spatially, the northern region received low moisture budget from the Atlantic Ocean while the temporal distribution of precipitation across different climatic zones indicate high variability in precipitation across these zones. The mean SSTa in the WAf region were predominantly positive (0.5 and 1). The lowest (highest) global SST values were prevalent during the DJF (JJA) season(s) whereas, the monthly distribution of SSTa for the WAf region reveal neutral (2000–2016) and El Niño (2016–2022) episodes. The analysis of NIF values indicates a varied but generally stronger relationship between WAf SST anomalies and precipitation types compared to nino3.4 SST versus precipitation types. As a signal for prediction of seasonal and spatial distribution of precipitation across Nigeria’s different climatic zones, this outcome can support planning for food security, water and biodiversity conservation, and climate change adaptation and mitigation.

The development of a detailed strategy to mitigate the negative consequences of any natural calamities depends on accurately identifying sensitive zones where natural hazards frequently happen. In the present investigations, three widely utilized probabilistic approaches viz., frequency ratio (FR), statistical index (SI), and weighting factor (WF) have been utilized for prediction of flsh flood susceptibility zones in the Coochbehar urban and peri-urban area (CUPUA) (area = 26.22 km²). Ten flash flood conditioning factors have been used in this assessment based on previous literatures and experts' opinions. In the FR model, 29.40 % area is observed in the high and very high flood zones, whereas 36.27 % and 31.16 % area is identified in SI and WF model, respectively. The FR model demonstrates that five conditioning factors, viz., topographic position index (TPI), land use and land cover (LULC), normalized difference vegetation index (NDVI), distance to drainage (DtD) and rainfall were highly impacted in flash flood prediction (FFP) analysis; in SI model, LULC is the major influencing parameter, and in WF model LULC, rainfall, NDVI, and distance to road (DtR) are the effective parameters. The success rate curve of the FR, SI and WF models manifest SI model has highest training (AUC=0.903) and prediction (AUC=0.925) accuracy, and FR and WF also have very good accuracy as their AUC values are 0.899 and 0.877 (in success rate curve) and 0.900 and 0.881 (in prediction rate curve). Therefore, the application of probabilistic approaches in this active flash flood-prone region is excellently performed, and the results of this study will help hydrologists, engineers, and water management administrators to control the areas that are extremely susceptible to flash floods and reduce possible damages.

Escalating air pollution in urban areas is a matter of concern, and deteriorating air quality is having numerous impacts on human health and the environment. Kolkata is one of the most densely populated and highly polluted cities in India. The aim of this work is to predict the concentration of ambient PM_2.5 using different air pollutants and meteorological parameters as predictor variables by using statistical and different Machine Learning techniques as well as to understand the influence of other air pollutants and meteorological factors in ambient PM_2.5 prediction. Different advanced machine learning algorithms like Random Forest Regression, decision trees, k-nearest Neighbour, Support Vector Regression, Ridge Regression, Lasso Regression, and XGBoost have been used, and the results show that the XGBoost model exhibits higher linearity between predictions and observations, among other models. Moreover seasonal variation of the most influential factor for prediction of PM_2.5 is also noticed during the analysis. This work adds to the broader comprehension of the convergence of environmental science, public health, and machine learning and it offers significant perspectives for sustainable urban planning and pollution control tactics in rapidly expanding metropolitan areas such as Kolkata.

The Lower and Middle Benue Trough is an intra-continental rifted basin with most rocks concealed by thick sediments and vegetation. Geological field mapping is very difficult resulting in high uncertainties. Remote sensing and geophysical techniques can assist in refining lithological boundaries and detecting buried geological features such as intrusive bodies, which can be very useful in interpreting the structural history of a basin. The main aim of our study is to re-process and interpret aeromagnetic and multispectral satellite datasets to understand the evolution of the Benue Trough. We used high-resolution aeromagnetic data and, Landsat 8 and ASTER data sets to interpret surface and near-surface lithologies, particularly igneous bodies, within the Benue Trough, Nigeria, with the aim of better constraining the basin evolution in time and space. A matched bandpass filter was applied to the aeromagnetic data to separate shallow/near-surface (residual) anomalies from deep (regional) anomalies. The result of the residual anomaly was further filtered by derivative-based filters to delineate surface/near-surface igneous bodies. The satellite remote sensing datasets were processed and enhanced, and diagnostic mineral spectral signatures related to geology were interpreted. A spectral angle mapping (SAM) supervised classification was used to map various lithologies and their boundaries. The delineated igneous bodies (volcanic rocks, plugs, dykes, bosses, and sills) are concentrated along the SE margin of the Trough where they intruded along a major NE-SW trend; but changes in the intrusion style are interpreted to relate to specific stages in the basin history. We suggest that the initial magma emplacement was controlled by structures mostly along the SE margin of an asymmetric basin, but the rifting locus later migrated towards the centre of the present basin.

The city of Setúbal is situated 30 km southeast of Lisbon, Portugal, and has experienced significant impacts from various earthquakes, including the one that occurred in 1858. This earthquake serves as an example of a nearby earthquake that caused significant social and structural damage, reaching a intensity of IX-VIII on the Modified Mercalli scale. Despite an average recurrence period of 3000–11000 years, as suggested by several authors, the Alcochete-Pinhal Novo-Setúbal fault (APSF) could potentially cause significant social, structural and economic impacts in future events. Several authors have reported on the APSF with slight variations in its outline, as it traverses multiple urbanized areas. The aim of this study was to locate the APSF in the Setúbal region and, to the best extent possible, determine its orientation and vertical offsets. 24 passive refraction microtremor tests (ReMi) and 145 horizontal-to-vertical (H/V) spectral ratios were employed to compute the variation of transverse wave velocity (V_S) with depth and to compute the fundamental frequency (F₀) and other natural frequency (F₁) of the soils when present. Horizontal sections of V_S and the spatial distribution of peak frequencies reveal alignments that can be related to the presence of the APSF fault zone. Considering all the alignments identified in this paper, two areas with distinct orientations for the APSF zone were proposed: one with a NNE-SSW strike and another with a NNW-SSE orientation. The lower values calculated for the fault plane dip (maximum of 5º) in the APSF area suggest a minimal vertical displacement, potentially corresponding to a strike-slip fault.

The Paleozoic, Mesozoic and Cenozoic successions of the Zagros Fold and Thrust Belt (ZFTB) of Iran are endowed with prolific petroleum systems. The Sarchahan―Dalan/Kangan(.) petroleum system is responsible for giant accumulations of gas in the Paleozoic series. The Mesozoic series contains the largest volume of hydrocarbon accumulations in the ZFTB. The main petroleum systems in the Jurassic succession are Sargelu―Surmeh(!), Hanifa―Surmeh(!) and Diyab―Surmeh(!) petroleum systems. The Cretaceous succession holds the Garau―Fahliyan(!), Kazhdumi―Sarvak/Ilam(!) and Middle Sarvak―Mishrif(!) petroleum systems. The Cenozoic series contains the Pabdeh―Asmari(!) petroleum system, which is partially active over limited areas of the ZFTB. Occurrence and evolution of these petroleum systems were basically controlled by the tectono-stratigraphic evolution of the ZFTB. The tectonic history of the ZFTB is characterized by three distinct phases including continental rifting (i.e., Early Permian), passive margin development (i.e., Triassic to Jurassic) and continental collision (i.e., Cretaceous to recent). These phases not only controlled the geometry and spatial distribution of essential elements (i.e., source, reservoir and seal rocks), but also greatly impacted the hydrocarbon generation/migration/accumulation processes associated in each petroleum system. Exploration in the ZFTB has resulted in the discovery of 125 oil fields (with proved reserves of ∼157 billion barrels of oil) and 57 gas fields (with natural gas reserves of ∼191 trillion cubic feet). The Oligo-Miocene Asmari and the Cenomanian-Santonian Sarvak/Ilam carbonates are the main oil-producing intervals. The Asmari carbonates, hosting >45 % of Iranian oil reserves, are the most prolific oil reservoir in the ZFTB (e.g., daily production from the Asmari reservoir of Ahwaz Field reaches 700,000 barrels). On the other hand, more than 90 % of gas reserves in the ZFTB are accumulated in the Permo-Triassic Dalan/Kangan carbonates (e.g., at supergiant gas fields including South Pars, Kish, North Pars and Golshan). Asymmetric folds provide the most important type of hydrocarbon traps in the ZFTB and stratigraphic traps remain to be explored in the future.