Arabian Journal of Geosciences最新文献

Soil erosion is a pressing natural phenomenon confronting nations all over the world. The study's objectives are to establish an evaluation model of soil erosion in the Paguyaman Watershed, Gorontalo, Indonesia, using the Analytic Hierarchy Process (AHP). Eight different factors, slope, elevation, slope length, annual rainfall, average wind speed clay ratio, NDVI, and NDMI were considered in this study. Each factor has been assigned a weight, and maps have been created using a Geographic Information System and remote sensing tools. The combined map of all maps indicates the intensity of soil erosion in five separate classes: very high (0.07%), high (18.90%), moderate (46.69%), low (5.94%), and very low (0%). The high and moderate class is the dominant study area, which shows that the area is at high risk of soil erosion. Slope (0.24), NDVI (0.23), and annual rainfall (0.15) were found to be the dominant factors influencing the soil erosion risk. According to the AUC ROC value of 0.762, the soil erosion risk map has an overall success rate of 76.2%. The findings of this study may be used by policymakers to adopt suitable conservation programs to prevent soil erosion or to advocate soil conservation acts.

Watersheds are the basic planning units. Topography is one of the predominant controlling factors which augment erosion. Tuirial watershed in Mizoram is one such area witnessing severe soil erosion due to rugged sedimentary terrain with heavy precipitation which needs immediate action to prioritize at the sub-watershed level. Analytical hierarchy process (AHP) and compound value methods were utilized to compute through erosional parameters of morphometry, average annual soil loss (AALS), sediment transport index (STI), and sediment production rate (SPR). The compound index value below 7.5 in sw1, sw2, sw4, and sw6 which contribute 25.88% of the total area were given the highest priority. The values between 7.55 and 8.5 of sw3, sw5, sw10, and sw14 are under moderate priority zones which comprise 29.36% of the total basin. Similarly, the compound index values above 8.5 of sw7, sw8, sw9, sw11, sw12, and sw13 with 44.74% of the total area are under the least priority zone. The weightage of erosional parameters for prioritization of sub-watershed was judged by a multi-criteria decision analysis (MCDA)-based analytical hierarchy process (AHP). This study revealed that the combination of morphometric features and geo-environment parameters ranking of the compound value (Cv) and analytical hierarchy process (AHP) to determine highly influencing factors of soil loss risks are the most suited methods to the prioritize at the sub-watershed level.

Climate change is one of the main factors that caused scarcity of fresh water phenomenon all over the world. The lack of water in major parts of Iraq affected all sectors that use water and cause obvious damages to ecosystems. Karbala province suffers from frequent water scarcity due to water scarcity and abnormally high temperatures. In the present study, remote sensing and GIS were applied to quantify water scarcity and evaluate its effects on vegetation in this fragile semiarid ecosystem. Analysis of hydrological data of the study area was carried out during 2013 to 2022 to compute water availability and shortage based on the criteria and requirements of water sector and environmental management in Iraq. Remotely sensed Landsat 8 images data were applied to measure changes on vegetation and the effects of water scarcity. Soil Adjusted Vegetation Index (SAVI) was employed to identify vegetation and detect its change. Results showed that the area witnessed decreasing in water availability compared to the reference year. Maximum available water reached 1977.535 million ({text{m}}^{3}) in 2013, while the minimum of 859.227 million ({text{m}}^{3}) was observed in 2022. The maximum and minimum vegetation area reached 535.610 ({text{km}}^{2}) and 430.605 ({text{km}}^{2}) in 2013 and 2022, respectively. Results indicated that all the years posterior to the reference year experienced water scarcity and vegetation damage, where the maximum and minimum water scarcity rates were 56% and 8% in 2022 and 2016, respectively. The maximum impact of water scarcity rate on vegetation was ca. 20% in both years 2015 and 2022. Water scarcity is constantly increasing over time, thus evaluating its impacts and forecasting its future specification will support decision-makers to take the necessary measures to mitigate its effects.

The purpose of this study is to comprehend the sea level rise pattern around Tuvalu. This objective is accomplished by investigating the relative monthly average mean sea levels (MSL) recorded by tide gauges. In addition to the historical and contemporary tide gauges located in Tuvalu, we analyze the MSL data also from tide gauges in Pacific islands and atolls, as well as the long-term trend tide gauges in Honolulu and Sydney, to enhance and reinforce the findings. The analysis is complemented by information on subsidence obtained from the global positioning system (GPS) monitoring. The significant increase in sea level observed at Tuvalu’s current tide gauge is attributed more to multidecadal oscillations, significantly affecting short-term records, and the subsidence of the tide gauge, rather than the global thermosteric contribution. The residual rate of sea level rise is likely influenced by other factors, such as changes in circulation within the lagoon or other local anthropogenic biases. The suggested analysis aligns with prior research, reinforcing the perspective that the sea levels are gently rising and the surfaced area of Pacific islands and atolls is not diminishing, contrary to inaccuracies found in selective studies that emphasize certain data while disregarding others.

Northwest Ethiopia (east Gojjam) has envisioned developing its Climate Resilient Green Economy strategy through the use of renewable energy sources. However, harvesting wind, solar, and geothermal energy is below the satisfactory level. Therefore, this paper aims to model and assess the potential of renewable energy to improve energy accessibility in the rural areas of northwest Ethiopia. Wind, cloud cover, temperature, and radiation data were obtained from the European Centre of Medium Range Weather Forecast (ECMWF) model. Logarithmic power-law interpolation, radiation flux, and irradiance power modeling are applied to this work. The study area model results indicated that the annual wind potential is limited for implementation. A minimum and maximum value of solar energy is found at 5.30 kWm⁻² during summer and 9.75 kWm⁻² during spring, respectively. The average value of the total energy flux for geothermal energy exploration is found 1500.00 Wm⁻². Generally, the south and southwest parts of northwest Ethiopia have the potential to implement geothermal energy. Solar energy plantation is encouraged in the whole parts of the study area excluding Choke Mountain. Hence, a renewable energy implementation plan for energy resource management through a stakeholder engagement platform is required to convert this research into a project.

The detrimental effects of rapid industrialization, urbanization, and the discharge of domestic and agricultural waste are threatening the serene beauty of the Taihu Lake Basin (TLB). Recognizing the urgent need to preserve the lake and improve its water quality, both the central and provincial governments have implemented stringent and noteworthy laws and policies, including the Environmental Impact Assessment (EIA) Law in 2018, the amendment of the Environmental Protection Law (EPL) in 2015, and the introduction of the Environmental Protection Tax Law (EPTL) in 2018. This study uncovers some promising findings which indicate that despite a 17% increase in the non-agricultural population in the area since 2000, which is below the national average of 31%, there has been a noticeable rise in various contaminants in the TLB water, including total phosphorus (TP), potassium permanganate (CODMn), and total nitrogen (TN). Remarkably, this study reveals that despite the challenges posed by water pollution, the situation in the TLB is beyond control. Through enhanced monitoring, supervision, inter-departmental collaboration, and the streamlining of the EIA process, the pollution hazards can be addressed to restore the pristine state of the lake.

We present an integrated site investigation of a proposed estate with a view to generating baseline data required for safe design and construction of structures and groundwater schemes, installation and protection of utilities, and post-construction environmental issues. An electrical resistivity survey involving 1D and 2D imaging techniques was involved. The 1D resistivity imaging involved the Schlumberger Vertical Electrical Sounding (VES) with half current electrode spacing of 1–125 m, whose data were interpreted for layer resistivities and thicknesses using segment-by-segment curve matching and 1D forward modeling with W-Geosoft/WinSev 5.1 code. The 2D dipole-dipole resistivity imaging utilized 20 m dipole length and an expansion factor (n) ranging from 1 to 5. The 2D data were inverted to 2D resistivity images with DIPRO software. The 1D and 2D interpretation models delineated five subsurface layers comprising topsoil, fill, laterite, weathered basement, and fresh basement. The weathered basement is the main aquifer with thicknesses ranging from 11.9 to 64.4 m with prospect for groundwater development. The essentially lateritic subsoils in the upper 10 m with resistivity values generally > 450 Ωm are adjudged moderately to highly competent. The low-porosity/permeability lateritic layer overlying the weathered layer aquifer constitutes a sealant against infiltrating pollutant with the groundwater significantly protected. Except within the stream channel, the soils/subsoils are practically non-corrosive.

Predicting runoff is vital for effectively planning and managing water resources within a watershed or river basin. This research aims to compare the effectiveness of two distinct approaches in predicting daily runoff within the Koyna River basin in India from 1999 to 2011. The approaches examined are an artificial intelligence-based data-driven model, specifically an artificial neural network (ANN), and a conceptual-based model, the Natural Resource Conservation Service Curve Number (NRCS-CN) method. The ANN model employs a data-driven approach that utilizes historical runoff data to train the model, allowing it to capture nonlinear relationships and complexities in runoff dynamics. In contrast, the NRCS-CN method uses a conceptual-based approach, relying on empirical relationships and soil cover complex data to estimate runoff. The performance of both models was evaluated using the coefficient of determination (R²) as a key metric. The study highlights a significant difference in predictive performance between the two methodologies. The NRCS-CN method achieved an R² of 0.37, whereas the ANN model significantly improved the predictive accuracy, achieving an R² of 0.88. This substantial increase demonstrates the ANN model’s superior ability to capture the complexities of daily runoff dynamics compared to the NRCS-CN method. In conclusion, the findings strongly advocate for the efficacy of the data-driven ANN model over the conceptual-based NRCS-CN model for daily runoff prediction. The superior performance of the ANN model provides valuable insights for enhancing water resource management through advanced artificial intelligence techniques. These results suggest that integrating AI-driven models can significantly improve the accuracy and reliability of runoff predictions, thereby supporting more effective water resource planning and management.

Borehole instability problems have caused non-productive time while drilling operations in the Nahr Umr shale formation. The drilling difficulties, including stuck pipe, caving, and tight holes, have been identified as significant problems in this formation. This study aims to comprehend the causes of wellbore failure and choose the most suitable drilling strategy. In this regard, a mechanical earth model (MEM) was performed using open-hole wireline logging measurements from the offset wells data. Those data included gamma ray, density log, compressional wave velocity, shear wave velocity, neutrons porosity, and image log. Moreover, there were also measured data such as leak-off tests and modular formation dynamics testers that were applied to validate the model’s accuracy.

The analysis exhibited that the leading cause of wellbore instability problems was improper mud weight (10.6 ppg). In addition, inappropriate drilling practices and the heterogeneity of the Nahr Umr formation have magnified the risk of drilling problems. The MEM outcome proved that the mud weight should be 11.6–13.5 ppg to safely drill a vertical well. Thus, this work can be applied as a cost-effective tool when designing future neighboring deviated wells.

This study aims to investigate the impact of the increasing age of vetiver grass on the factor of safety (FS) of slopes. Data were gathered from previous studies to establish a mathematical relationship between root cohesion—a key factor influencing FS—and the plant’s age. Finite element modeling using PLAXIS 2D software was conducted on a 45-degree slope to calculate FS in the absence and presence of vetiver grass at ages 5, 10, 15, and 20 years. Results indicate that root cohesion (c_r) and root area ratio (RAR) significantly affect FS values. Over 20 years, soil cohesion increased by 67%, and the FS of a 45-degree slope improved by 6.7%. A constant internal friction angle (K) was considered to create a graph for calculating root cohesion values across different ages with varying K values. Additionally, a simple mathematical model was developed to predict root cohesion based on plant age, considering other critical factors such as RAR. The study also found that while root cohesion increases with age, the rate of increase diminishes over time. Overall, the shear strength of rooted soil enhances with higher RAR and mobilized tensile strength of roots. This research highlights the substantial role of vetiver grass in improving slope stability, providing valuable insights for the application of vetiver in soil conservation and slope stabilization projects.