Arabian Journal of Geosciences最新文献

This study’s primary goal was to determine the statistical assessment of the rainfall trend in relation to agricultural productivity and productivities in the Gondia district of Central India’s groundwater resources. Using data from eight hydrological stations, the long-term time series covering rainfall trends from 1971 to 2019 is applied using the non-parametric when working with annual rainfall data and agricultural data, and in demonstrating how the distribution of rainfall influences agriculture sectors, Mann–Kendall and Sen’s slope estimator is employed. A variety of techniques have been employed to examine the rainfall, including the use of GPS and GIS software to display the type of rainfall. Seasonal statistical study using Z-values revealed that average rainfall decreased (− 0.128), post-monsoon rainfall decreased (− 0.053), and pre-monsoon rainfall decreased (− 0.9), whereas monsoon rainfall increased (0.022), and winter rainfall increased (0.003), indicating a growing trend. Ground water parameters suggest that Ca + + (196.23 to 244.96) is found greater in Deori Tahsil than in other areas. Chloride levels (14.00–613.91) were highest throughout the area. The highest number of samples (68.29%) belongs to the medium salinity water group, while roughly 26.83% of samples fall into the high salinity water category. The lowest salinity groundwater percentage (4.88%) is classified as such. The Gondia district’s management and agricultural productivity will undoubtedly benefit from this research. In addition to catastrophe management and long-term planning, it can be used to ascertain the type of rainfall experienced in different districts.

The study here focuses on the range and extent of selected heavy metals found in contaminated soils of automobile workshop sites in one of the better-planned and environmentally aware cities of northern India. Soil samples from four motor markets in Chandigarh were analyzed for heavy metals. Multivariate statistical analysis and Pb isotopic source apportionment were done to understand better the source of the heavy metals including Pb in the soils. Results showed that the decreasing average metal concentrations (mg kg⁻¹) were in the following order: Mn (547) > Zn (217) > Cu (95) > Pb (94) > Ni (37) > Cr (34) > Cd (1.4). The Pb concentration had a minimum value of 32.98 mg kg⁻¹ and a maximum value of 565.20 mg kg⁻¹. Among the analyzed heavy metals, the mean I_geo ranged from − 1.32 (Cr) to 3.5 (Cd) with Cd also having the highest enrichment. Similarly, high contamination of the affected soils was indicated as the pollution load index (PLI) value ranged from 1.07 to 2.58. Principal component analysis of the heavy metal data extracted four components with Pb having the highest loading factor in the fourth component. Similarly, in cluster analysis, the metals Cd, Pb, Cu, Ni, Cr, and Zn had the least interelement distance between them signifying their common anthropogenic source. Lead isotopic analysis of the soils revealed that the ²⁰⁸Pb/²⁰⁴Pb ratio ranged between 37.16 and 38.71, the ²⁰⁷Pb/²⁰⁴Pb between 15.56 and 15.69, and the ²⁰⁶Pb/²⁰⁴Pb ratio between 17.30 and 18.34. The plot between the ²⁰⁷Pb/²⁰⁶Pb and ²⁰⁸Pb/²⁰⁶Pb ratios showed that Pb in the soils could be from vehicular exhausts and not from coal combustion.

This study is aimed at assessing the contamination levels, ecological risk, and mitigation strategies of potentially toxic metals in volcanic soils of Njombe-Penja Banana Plain. Soil samples were collected and analyzed by inductively coupled plasma-mass spectrometry (ICP-MS). Results show that the concentrations of Cd (0.05–2.80 mg/kg), Co (12.30–78.90 mg/kg), Cr (44–142 mg/kg), Cu (22.20–251 mg/kg), Hg (0.06–0.19 mg/kg), Ni (35.20–139 mg/kg), Pb (5.80–48.70 mg/kg), Ba (199–469.17 mg/kg), Sr (25.30–509 mg/kg), V (91–284 mg/kg), and Zn (54.80–1010 mg/kg) exceed the geochemical threshold values. Pollution indices such as contamination degree (C_d 11.62–79.97) and pollution load index (PLI 0.56–2.80) indicate soil contamination. Nemerow integrated pollution index (NIPI 0.17–20.67), enrichment factor (EF 0.04–9.43), geo-accumulation index (Igeo − 3.39–4.84), and modified degree of contamination (mC_d 0.78–5.32) suggest moderate to very high pollution levels in soil ecosystem. Potential ecological risk index (Er 0.77–857.14; RI 117.41–1095.39) and modified hazard quotient (mHQ 0.10–4.11) show low to very high ecological risk of potentially toxic metals with probably toxic and biological effects on humans and biota. Natural and anthropogenic activities are major sources of soil contamination and toxic metallic pollution of volcanic soils. This study suggests that proper focus should be placed on monitoring the point and non-point sources of toxic metals entering soils from domestic and agricultural practices. This research work serves as a warning to companies and farmers about potentially toxic metal pollution of volcanic soils in Njombe-Penja Banana Plain.

The present study investigates the Upper Cretaceous source rocks collected from well-x of the Anambra Basin in the southern Nigeria. Organic petrological analysis, bulk and molecular geochemistry, bulk carbon isotope, and compound specific isotope analysis of n-alkane (CSIA) were carried out with the aim of providing detailed information on the geochemical characteristics of the recently discovered crude oil and its potential source rocks, petroleum system, and a better understanding of the reasons behind abrupt seizure in the liquid hydrocarbon production from the ANAR X-oilfield of the basin. Based on petrographic and bulk geochemical results, the source rocks under study are primarily composed of type III organic matter and are in immature to marginally mature hydrocarbon generation stages. Molecular marker parameters also revealed that source rock deposition occurred in sub-oxic to oxic settings. While the major source input is the lacustrine algae in the source rocks, there were also minor contributions from terrigenous land plants. The studied source rocks are currently in the late oil to wet-gas generation windows based on basin modeling results. In addition, the previously postulated Upper Cretaceous (Mamu-Nkporo/Ajali) petroleum system (!) in the basin is supported by oil-source correlation. Two main reasons led to the abrupt seizure in liquid hydrocarbon production from the ANAR X-oilfield of the Anambra Basin: Higher thermal maturity attained by the producing source rock intervals, and the absence of oil producing liptinitic macerals. While vitrinites in the source rocks continue to produce gas, the liptinite macerals have been completely transformed to liquid hydrocarbons, and eventually to gas due to their instability at higher temperatures. In the Anambra Basin and other sedimentary basins in the southern Nigeria, the study will lower exploration risks and provide new exploration directions.

Wrap-faced embankments, a noteworthy innovation in geotechnical engineering, present a compelling solution for tackling diverse infrastructure challenges. This comprehensive study assesses their performance in various critical aspects, thereby unlocking their potential to revolutionize contemporary civil engineering endeavors. Notably, the response to acceleration amplification shows that these embankments exhibit adaptability to different surcharge loads, fostering stability while demonstrating a proportional relationship with base acceleration, particularly at elevated embankment levels. Moreover, their proficiency in reducing face displacement in response to surcharge pressure underscores their structural stability, especially under seismic influences. Furthermore, these embankments display versatility in adapting to strain variations, presenting an avenue for improved performance under dynamic loading conditions by adjusting surcharge loads and enhancing earthquake resistance with geotextiles. In the realm of pore water pressure response, their capability to manage increasing pressures with adjustments to backfill soil density further augments their suitability for dynamic loading conditions. Despite these strengths, they do necessitate tailored seismic design guidelines and consideration of deformation zones. Ultimately, wrap-faced embankments manifest advantages in seismic resilience, land acquisition efficiency, environmental compatibility, cost-effectiveness, agricultural land preservation, long-term performance, and minimal maintenance, effectively addressing various infrastructure challenges. With ongoing innovations in materials, design software, and construction techniques, their potential to enhance geotechnical engineering and infrastructure development remains promising and significant.

Understanding subsurface faults is crucial for hydrocarbon exploration and production. To assess fault seal effectively, a combination of artificial neural network (ANN) and the “Move” was employed. The study aims to compare ANN, known for its non-linear regression capabilities, and the “Move,” which analyzes multiple fault seal factors for fault seal prediction. The objectives of this study are to delineate hydrocarbon-bearing reservoirs, map faults and horizons, and characterize faults in terms of their orientation and throw. Lithology differentiation was achieved using gamma ray logs, while reservoir identification and correlation across wells relied on resistivity and gamma ray logs, as well as log response similarities. A network of faults and three horizons were mapped, identifying a faulted anticline as the likely hydrocarbon-bearing structure. The study utilized well log and three-dimensional seismic data in the “Move.” The ANN’s performance was assessed using different evaluation metrics. The “Move” indicated that fault planes exhibited moderate to good sealing capacity, with average shale gouge ratio values of 35%, 36%, and 44% across wells. Lithology juxtaposition included shale on sand, sand on sand, and shale on silt. The ANN model accurately predicted fault seals with 93% R² (coefficient of determination) success rate. Validation of the ANN results, compared to Move predictions, showed superior performance through a scatter plot analysis. This study demonstrated that machine learning techniques, when applied to well logs and seismic data, offer substantial potential for enhancing fault seal prediction in the petroleum industry.

The municipalities in the region of Araras/São Paulo present difficulties in the adequate disposal of waste, as they do not have resources to implement individual solutions, and the existing landfills in the region have a relatively short useful life. In line with the guidelines of the National Policy on Solid Waste (PNRS), which encourages consortium solutions to optimize infrastructure and to reduce costs, an intermunicipal consortium involving Araras and adjacent municipalities was proposed and the need for a minimum area of 40 hectares for installing a new intermunicipal sanitary landfill (ISL) was estimated. This study thus presents a low-cost methodology that integrates free geographic information systems (GIS) tools with multi-criteria decision analysis (MCDA) techniques to identify areas suitable for implementing the ISL. The approach was structured into three main stages: (i) application of restrictive criteria to exclude unsuitable areas; (ii) weighting of areas previously classified as suitable by elaborating four scenarios (environmental, economic, social, and balanced); and (iii) refinement of the pre-selected areas based on additional spatial and contextual criteria. Of the 33.5% of the territory considered suitable, the balanced scenario (scenario 4) highlighted 21.17% of the area as “Excellent,” allowing the pre-selection of ten locations, of which three were prioritized after refinement, culminating in the selection of Area 5 as the most favorable. The methodology proved to be effective, efficient, and innovative, by offering an accessible, adaptable, and technically robust structure for locating projects with high potential for environmental impact. Its differential lies in the flexibility provided by the creation of multiple scenarios, allowing managers to evaluate alternatives based on different priorities and to opt for more sustainable approaches. The ease of application of the techniques involved, combined with the possibility of prioritizing the criteria and replicability in other regions, reinforces the potential of this approach as a strategic tool in territorial planning and integrated waste management.

The present study mainly focuses on the geochemical analysis techniques of high (HPR), medium (MPR), and low (LPR) oxidized phosphate rocks, employing various techniques to uncover significant alterations in their chemical composition and mineralogical, morphological, and geometrical properties. The comprehensive analysis involves the measurement of major oxides and mineral phases using complete and XRD analyses, while optical microscopy is utilized to verify the minerals present. Additionally, the zeta sizer technique is employed to ascertain the size of representative samples. Within the Duwi Formation, it could be subdivided vertically into three remarkable informal lithostratigraphic units. Notably, HPR and MPR exhibit elevated P₂O₅ content (30.20 wt.% and 24.80 wt.%, respectively), contrasting with the decreased content in LPR (6.5 wt.%). These findings position HPR and MPR as promising high-reactive P fertilizers suitable for direct agricultural application and as valuable P fertilizer sources following nutrient balancing.

This study focuses on the assessment of geo-factor weights for the development of Geographic Information System (GIS)-based seismic hazard map, using a simplified Empirical Susceptibility Weights Approach (ESWA) and analytic hierarchy process (AHP) for Thiruvananthapuram city, a rapidly growing urban area in the southern Peninsular India (PI). The influencing factors related to the ground characteristics, contributing to the seismicity of the region considered as inputs for the development of the model/map, include the peak ground acceleration (PGA), geology, lineaments/faults, geomorphology, elevation, slope, soil distribution, and building density pertaining to the study area. The thematic factors and the classes within each factor are assigned respective weights and ranks, using a hybrid evaluation of ESWA and AHP methods for an unbiased estimation of susceptibility levels of attributes. Based on the thematic layer weights and rank values, Susceptibility Index (SI) was finally calculated by applying a weighted linear combination (WLC) model in GIS. These continuous numerical index values have been divided into different classes. The classification result implies that it provides distinctive distribution of risk levels varying from very low to high ranges in the seismic hazard mapping of Thiruvananthapuram city, and the PGA corresponding to the high-risk zone in the region had been estimated.

Vegetation plays an essential role in ecosystem processes, including control of soil erosion and carbon and water cycles. This study examines sudden changes in vegetation in Jharkhand, India, from 2001 to 2018 using the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) and Breaks For Additive Season and Trend (BFAST) algorithm. The results show that 69% of the land area experienced abrupt vegetation change. The main negative changes occurred in 2008, 2014, and 2015. Positive changes reached the peak in 2012 and 2013. Negative changes ranged from -0.4 to -0.001 while positive changes ranged from 0.001 to 0.4. The highest negative change was -0.1 to -0.05 and positive between 0.01 and 0.05. These findings emphasize significant environmental impacts and emphasize the need to improve soil and control to alleviate the ecosystem degradation and support sustainable development in Jharkhand.