Arabian Journal of Geosciences最新文献

This study applied geostatistical and machine learning models, namely ordinary cokriging (OCK) and the support machine vector (SVM) algorithm, for mineral mapping of a gold prospect at Tikondi (East, Cameroon). For this purpose, five hundred and fifty (550) soil samples were collected and analyzed for Au, Ag, Zn, Fe, Cu, Pb, As, Sb, W and Bi. OCK and SVM models were validated using numerical and graphical methods of validation. Results showed that the gold grade ranged from 1 to 2480 ppb, with an average value of 9.973 ppb. The principal component analysis (PCA) demonstrated that bismuth (Bi) has the strongest association with gold grades. For OCK, the histogram of errors indicated a solid assessment when the root mean square error (RMSE = 21.41), mean absolute error (MAE = 4.76) and correlation coefficient (R = 0.841) indicated that OCK is a decent model, but with certain values poorly predicted. The confusion matrix and ROC measurement indicated clearly that SVM was a robust and efficient predictor for prospect mapping.

The airborne gamma-ray spectrometric (AGS) data of the north Wadi Qena area were used to map the radioactive potentiality and uranium migration. Examination of the potassium (K), equivalent uranium (eU), equivalent thorium (eTh), and ternary maps displayed the areas of potential radioactivity. The results of uranium favorability (U₂) index revealed that the granitic rocks, Rakhiyat, Esna, and Sudr formations, have high uranium potential. On the other hand, the computed uranium migration maps (original uranium (U_o), migrated uranium (U_m), uranium migration rate (P%), eU-eTh/3.5, and eU point anomaly) allowed the delineation of migration patterns (inward and outward) for all the rock units of the area under study. The inward uranium migration distinguished the Sudr, Esna, and Rakhiyat formations, while the other rocks displayed outward uranium migration. The investigation of geological structural data indicated that the research area was influenced by NNW-SSE, NE-SW, NNE-SSW, ENE-WSW, and WNW-ESE trends. These structures most likely had a significant influence on uranium movement and migration (in and out) of the rocks in the current study area.

Coastal cities face increasing flood risks due to urban expansion and climate change. This study simulates flood hydrographs in the Netravathi River watershed using the HEC-HMS hydrological model to improve flood management in Mangalore, Karnataka, which has experienced severe floods recently. The SCS curve number (CN) method was selected for its efficacy in estimating surface runoff across diverse land use and soil types. GIS tools analyzed spatial data on soil types, drainage, and land cover changes from 1990 to 2021, enhancing runoff forecast accuracy. Model calibration optimized parameters with historical flood events, and validation used independent past flood events. Validation showed a strong correlation between observed and simulated runoff hydrographs, particularly during peak discharge periods. A high Nash–Sutcliffe Efficiency (0.89) and low Percentage Bias (0.65%) demonstrate the model’s accuracy. The coefficient of determination (0.86) confirms the model’s predictive capability. The HEC-HMS model effectively forecasts streamflows in ungauged catchments within the Netravathi sub-basin using measured rainfall data, enabling more precise planning and management of water resource developments.

Given the uncertainty in earthquake forecasting, seismic hazard analysis has been considered to be the better method to estimate site-specific response spectra in seismic design. This research addresses a seismic hazard study for the Sarcheshmeh Copper Site in the Kerman Province, in southeast Iran. The first part of this paper includes an evaluation of seismotectonic and seismicity conditions throughout the study area. The second part addresses the seismic hazard analysis procedure followed by the determination of design ground motion parameters which is finally expressed in terms of peak ground acceleration in deterministic and probabilistic schemes. The peak ground acceleration (PGA) was obtained for the 75-, 475-, and 2475-year return period spectrum. (Kijko and Sellevoll’s in Bull Seismol Soc Am 79(3):645 654, 1989) method was used for the evaluation of seismicity parameters, and the SEISRISK III computer program was used to conduct the probabilistic seismic hazard analysis. Finally, the third part is devoted to the development of the earthquake design spectrum obtained by dynamic ground response analysis. Site response analysis program, EERA (Equivalent-linear Earthquake site Response Analysis), which implements an equivalent linear approach, was used for one-dimensional ground response analyses. The subsurface conditions including the geometry of the soil layers and their dynamic properties were extracted from the geotechnical investigations. Based on the results, the PGA values for the 75-, 475-, and 2475-year return period spectrum are 0.087, 0.302, and 0.425, respectively. This paper can provide guidance on conducting seismic hazard analyses at other sites. Also, the results could be used for earthquake-resistant design of civil engineering infrastructures of the studied area.

The Kopili River, which is the largest south-bank tributary of the river Brahmaputra, is primarily responsible for the frequent floods in the Morigaon and Nagaon districts of Assam, a northeastern state of India. The area of Dharamtul in Morigaon district is particularly susceptible to floods every year. Therefore, the current study aims to examine the hydrological characteristics of the Kopili River at the Dharamtul site so that insights can be drawn regarding the annual flooding patterns in the region. In this research, historical time series data has been utilized to create a comprehensive hydrological database. The database includes information such as peak discharge, design discharge for different return periods (10 years, 25 years, 50 years, and 100 years), stage-discharge rating curve, return period, and annual hydrograph for the Kopili river at the selected site, which is also a designated gauge site for the Water Resource Department of the Government of Assam. The findings of this research will be valuable in formulating flood models and implementing flood mitigation measures in the region in the long run. Additionally, it will pave the way for further hydrological studies in the area.

In recent years, the problem of noise pollution in urban areas has gained significant attention due to its detrimental impact on the health of residents. The present study aims to determine the current noise pollution scenario and direct and indirect association between the influencing factors on health issues of residents in an urban environment. The study utilized a partial least square-structural equation modeling (PLS-SEM) approach to examine the hypotheses related to how individuals perceive noise pollution and its impact on their health. The research findings reveal that noise annoyance and noise sensitivity have a direct impact on noise induced health issues, while demographic characteristics and traffic noise have an indirect influence. Additionally, noise level monitoring was conducted during morning, afternoon, and evening hours to evaluate ambient noise levels and prepare noise maps. Analysis of the prepared noise maps revealed that many sampling locations show noise levels higher than, or close to, 70 dBA. The study aims to develop a decision-support tool that utilizes data on noise pollution levels and associated health issues to inform policy interventions for managing and controlling noise pollution in urban settings.

Climate change is impacting global rainfall patterns, subsequently affecting food security worldwide. This study aims to analyse long-term rainfall trends at finer spatial resolutions to understand the effects of changing rainfall patterns on agriculture and other socioeconomic activities. Point rain-gauge data presents limitations, such as non-uniform geographic coverage, issues of data continuity and availability, and lack of data in remote regions. These challenges make high-resolution spatial trend analysis using point gauge observations difficult. To overcome these limitations, the study utilizes the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data, which merges remote sensing data (radar and satellite observations) calibrated with rain-gauge datasets. The CHIRPS dataset, available at three temporal scales with a 5-km spatial resolution, is used for trend analysis and drought monitoring. The research evaluates rainfall trends over Haryana and its 77 tehsils (talukas) at seasonal and annual scales from 1981 to 2020. Trend analysis was conducted using the Mann–Kendall Test, Spearman’s coefficient test, and the magnitude of the trends was assessed using Sen’s slope estimate and linear regression. The findings reveal an increasing trend in both annual and monsoonal rainfall across Haryana and its 77 tehsils, except for Naraingarh tehsil in northern Haryana. The western part of Haryana shows a statistically significant increase in annual and monsoon rainfall. Conversely, winter and post-monsoon seasons exhibit a decreasing trend across almost all tehsils, while pre-monsoon rainfall shows a significant rising trend in the southern and southeastern tehsils. The annual and monsoon rainfall patterns have shifted, increasing by 6.26% and 6.68% respectively from the 1981–2010 WMO standard period to 1991–2020. These changing patterns suggest potential impacts on agricultural and economic activity management.

The present study is dedicated to analyzing Griffith crack transference within finitely thick and infinitely extending transversely isotropic strip. This strip is bounded by two parallel punches exerting a constant load distribution through Dirac delta functions, which are a consequence of plane waves propagating due to mechanical point loading. Moreover, the developed model employs coupled singular integral equations and Cauchy-type singularities. It is utilized to analyze the point load at the advancing crack tip, while leveraging Hilbert transformation properties to derive the stress intensity factor (SIF) under constant point loading in a closed analytical form. The investigation incorporates numerical computations and graphical representations to scrutinize the impact of various parameters, including crack length and speed, punch pressure, and different positions of the point load, on the SIF. These analyses are conducted for both transversely isotropic and isotropic material strips.

In this paper, k-means algorithm has been used to disaggregate seismic parameters to evaluate their inter-correlations. A goal is to quantify in a disaggregated way the weights and effects of each parameter with respect to other ones. From the database, about 4900.0 data, divided into 22.0 categories, have been collected. The main divisions regard the wave components in horizontal and vertical axis and the soil characteristics. The studied seismic zone is the “Norpirenaica oriental,” placed in the Pyrenees area between Spain and France, classified as a very high seismic hazard. Numerical and analytical analyses have been carried out to implement the algorithm. Preliminary analyses and results would quantify the role of the sand horizontal stratigraphy, the non-linear effects, the elasticity of the soil, and the energy damping phenomenon. Curves are plotted in stochastic distributions and elastic spectra accelerations. Results show good prediction for vertical spectral accelerations and for far and relative strong events. Rigorously, results are valid only for the studied seismogenic zone under predefined constrictions and ranges.