Arabian Journal of Geosciences最新文献

The causes of mass movement, which occurred on the 5^th October 2021 at Tongo-Gadima and damage grouting drainage infrastructure of the national road, are examined in this paper, in order to set up the novel procedure for investigating landslide in an area with limited inventory geotechnical data. They are evaluated by estimating the annual precipitation on 12-year period and analyzing the relevant geotechnical parameters: water content, degree of saturation, consistency limits, grain size distribution, linear shear strength, uniaxial compressive strength, compressibility test on samples collected on the field in order to understand the behavior of lateritic soil exposed under rainfall as well as zonation of slopes. This investigation will, in turn, enable the stakeholders to implement appropriate mitigation measures across the landslide-induce area. The main characteristics such as concave slope, shallow slid surface occurrence, and rotational trend of Tongo-Gadima landslide were influenced by high annual rainfall reaching the average of 1540 mm. The zonation analysis identified steeping slope (> 20°) called escarpment landscape. High values of water content and degree of saturation induced the swelling behavior of unsaturated soil. It has high plasticity in the lower and median set made up of more than 30% fine clay. The internal friction angle and material cohesion showed poor characteristic 35° and 0.11 bar respectively. The low uniaxial compressive strength ranging between 1.77 and 7.87 MPa suggests that the complete meteoric weathering of rock and the C_c/(1 + e₀) > 0.20 ratio confirms the very compressible property of soil. The evidence of thixotropic rheoliquefier pattern of the clay matric mixed with gravel and sand is detrimental when meteoric water infiltration transforms the material into landslide-prone mud under constraint. Poor drainage has considerably increased water saturation of clay particles in the prism of rupture and weak mechanical properties of soil have been at the origin of landslide in Tongo-Gadima. Instrumentation and monitoring of slope are the first action to be taken to mitigate landslide in the region.

Abstract

This research presents the concrete tunnel-pile interaction behaviors under dynamic loading considering dry local sand in Bangladesh. For this reason, the shake table test has been conducted in the BUET (Bangladesh University of Engineering and Technology) concrete laboratory considering the relative densities of the dry local sand of 27%, 41%, and 55%. The dynamic loading is of sinusoidal form with frequencies of 1 Hz, 3 Hz, 5 Hz, and 7 Hz for the peak ground acceleration of 0.05 g. The interactive performance of the tunnel-pile model is evaluated in terms of the tunnel moment, tunnel strain, and displacements. The numerical simulation is performed by using the finite element-based code PLAXIS3D. The validation results of PLAXIS3D with the previous studies are found to be approximately 5% which shows a reasonable agreement. The experimental results of the tunnel-pile interaction model are compared to the previous field studies and numerical analysis to obtain the ranges of variations of results of (1 ~ 4.2)% and (5 ~ 10)%, respectively. The interaction zone shows the maximum SRSS (square root sum of squares) responses of the tunnel strain and moment based on the experimental study due to the influence of piles on the tunnel body. In addition, the SRSS vertical displacement of sand shows the lower value to compare the tunnel lateral and vertical displacements due to the higher damping of the sand than the tunnel and piles with caps.

Google Earth Engine (GEE) serves as a versatile platform for processing and visualising geospatial datasets, with its primary aim being to provide an open platform for planetary-scale geospatial analysis. Over time, GEE has proven itself as a valuable and robust tool, offering access to a wide array of imagery within a single consolidated system. Its cloud computing environment and computational power eradicate the need to store, process and analyse vast amount of satellite imagery on local computers. GEE has the potential to address some of the challenges associated with earth observation and geospatial applications, particularly in developing countries. Its development has lessened the reliance on high-speed processors and extensive storage capacities. Moreover, GEE presents users with a unique opportunity to conduct analyses with minimal financial investment and equipment requirements. The platform has showcased its capability to perform spatial and temporal analyses on global-scale data at significantly accelerated computational speed, rendering it an attractive tool for the scientific community, offering both versatility and accessibility. Its application spread across various sectors including crop inventory, vegetation mapping and monitoring, land cover mapping, disaster management, hydrological studies, urban planning and management, wetland conservation and management, climate change analysis and forestry analysis. For researchers in developing countries, who often grapple with challenges related to data accessibility, funding for computer hardware and software and resource limitations, GEE opens up new avenues. However, despite its potential, the utilization of GEE in developing countries has fallen short of expectations. Therefore, it is crucial for developing countries to fully leverage this platform to accelerate their sustainable development.

Landslide susceptibility zonation is a widely studied method for assessing the likelihood of landslides in specific areas. This study focuses on the Ranikhola watershed in the Sikkim Himalaya and utilizes the Frequency Ratio (FR) and Modified Information Value (MIV) methods to analyse landslide susceptibility. To enhance the susceptibility mapping a novel approach for the FR and MIV is introduced where the factor classes of higher importance were utilized. The study further evaluates a methodology that incorporates weighted ranking of landslide conditioning factor classes using FR and MIV indexes to generate landslide susceptibility maps (LSM). The landslide inventory comprises 124 landslides identified through satellite imagery from Q-GIS quick maps, ESRI base map, Google Earth, and Sentinel 2 A & B. Sixteen conditioning factors are considered, including elevation, slope angle, aspect, curvature, drainage characteristics, vegetation index, geology, soil type, rainfall, road density, and land use. The LSI and LSM are derived from these factors. The LSM created using traditional FR and MIV methods show that 9.55% and 5.96% of the watershed area fall within the High Susceptibility Zone (HSZ) and Very High Susceptibility Zone (VHSZ), respectively. However, the novel approach reveals that 11.54% and 10.29% of the study area fall within the HSZ and VHSZ. The weighted ranking method indicates that 16.22% of the Ranikhola watershed area is within the HSZ and VHSZ. The models are evaluated using the area under the receiver operating characteristic curve (AUC), with FR and MIV methods producing AUC values of 0.77 and 0.68, respectively. The new approach improves the AUC of the MIV method to 0.76, while the FR method remains relatively unchanged. The weighting method outperforms other FR and MIV methods, with an AUC of 0.90. Correlation analysis of the condition factors suggests that profile curvature, slope, stream power index, and topographic wetness index are the most influential factors, positively impacting each other and contributing to higher landslide susceptibility. The study emphasizes the importance of incorporating weighted ranking of landslide conditioning factor classes to create LSM, rather than relying on the total landslide susceptibility index (LSI) of factors. The findings provide valuable data for future large-scale investigations and efforts to enhance hazard preparedness in the Ranikhola watershed.

The purpose of this work was to undertake a systematic assessment of the approaches used to improve the accuracy of land cover maps from Sentinel-2 satellite images when utilizing supervised cell–based classification, as reported in articles published between 2015 and 2021. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) technique were utilized for this purpose. This involved searching for peer-reviewed articles relating to the review’s topic, which returned 551 articles. This was followed by sorting and filtering and, last, the exclusion and inclusion of articles based on specific criteria. This process resulted in nine articles, and their contents were examined from three perspectives: data preprocessing, classification model inputs, and classification techniques. Regardless of the differences like the targeted land cover classes, the number of training samples, and the classification model inputs, the results highlighted the importance of several factors in improving classification accuracy, including spatial resolution integration, data derivation (such as indices), and the selection of atmospheric correction and classification algorithms. All of these characteristics, however, are tied to the nature of the study area; that is, what is good for one area may not be acceptable for another. The study ends by summarizing the key conclusions and offering a workable strategy, as a general frame of reference, for classifying Sentinel-2 images in which the characteristics of the study region are carefully considered to achieve higher classification accuracy. This is based on the results and other pertinent references.

The Dahal Hit cavern in Central Saudi Arabia is the only locality where the Tithonian Hith Anhydrite Formation is exposed in the Middle East. In 2010, a 28.5-m interval in the 90-m-thick Hith Formation was logged and described in the cavern as part of a study to evaluate its sedimentological and sequence-stratigraphic architecture and to identify potential high-permeability layers within the seal of the world’s most prolific petroleum system. Seven facies types were interpreted as reflecting sabkha (subaerial) or salina (subaqueous) settings, and their vertical stacking patterns revealed that the logged interval consists of three transgressive–regressive cycles and part of a fourth cycle. The cavern was revisited in 2016 but only to find that the water level had risen by about 50 m rendering further geological studies impossible. The higher level of the water suggests that the cavern was flooded by the flow in the subsurface of treated sewage water released into a former quarry. The quarry is situated about 10 km southeast of the cavern, and the storage of water in it started in 2008. The flow pathways to the Dahal Hit cavern are apparently well-connected karsts, caverns, and high-permeability flow zones present in dolomite layers.

Abstract

This paper discusses the geochemical constraints on genesis of dispersed mineralized quartz-fluorite veins (QFV) at south west Sinai Peninsula, Egypt. These veins range from colorless to pale to deep violet in color and extend continuously and/or discontinuously in NE-SW, E-W, N-S, and NW-SE trends. They exhibit varying thicknesses ranging from a few centimeters to approximately 0.3 m. The scanning electron microscope (SEM) analysis has revealed the existence of secondary uranium minerals, notably kasolite Pb(UO₂)SiO₄.(H₂O), in association with other minerals such as galena (PbS), atacamite (Cu₂Cl(OH)₃), and fluorite (CaF₂) within the quartz-fluorite veins (QFV). Furthermore, the SEM analysis indicates a significant presence of fluorine incorporated into the biotite lattice of the host granitic rocks. Geochemically, there is a reasonable difference between the host granitic rocks and QFV, especially, silica and alumina contents. Also, some trace elements experienced enrichment in QFV such as Cu, U, Pb and Ag. The chondrite normalized pattern of QFV rare earth elements (REE) shows conspicuous negative Tb anomalies while the host rocks showed negative Eu anomalies. It is noticeable that there is a closed relation between uranium and fluorine in QFV. The Th/U ratios are < 1 in QFV samples indicating that the QFV had not been derived from magmatic origin. Furthermore, the REE and the mineral assemblages of QFV imply to hydrothermal origin (meteoric water) at shallow depth and low temperature < 200 °C under oxidation condition (epithermal genesis).

Pre-seismic stress-induced electric charges might be generated in the fault zone for producing the electromagnetic (EM) precursors. The peroxy defect (PD) theory has been considered to interpret the generation of stress-induced charges. The critical-earthquake (CE) model has been applied to explain the underground electric currents. It is necessary to explore both the presence of PD in the seismogenic zone of earthquakes and the production of EM precursors based on the CE model. First, we study the relationship between the PD theory and the seismogenic zone. Secondly, we examine the CE model based on the estimates of the depth ranges for generating stress-induced charges/currents for yielding an average normal stress that is strong enough to generate the electric charges and depth-dependent electric properties of fault zones. Results show that the dip angle and faulting type are significant factors in influencing the depth ranges that are similar for thrust and strike-slip faults and wider for normal faults. For a same depth range, the ability of producing electric currents is almost the same for thrust and strike-slip faults, but lower for normal faults. The underground spatial distribution of resistivity may control the stress-induced currents. The permeability barrier or transition layer also influences the stress-induced charges. The low-resistivity lower crust would reduce the up-going p-holes and thus is not beneficial for generating ground currents as expected by the CE model.

Abstract

The geochemical and mineralogical investigations conducted on a core retrieved from a paleolake in Faiyum Depression, Egypt, reveal a variation in two precipitation patterns; these are the Ethiopian African Monsoon (EAM) at the Nile Headwaters and the Mediterranean winter rains. The heavy mineral assemblage, and the geochemical characteristics, exhibit significant shifts in clastic input to the paleolake. These variations suggest shifting in the sources of sediment, with an East African origin during the African Humid Period (AHP) and in the Late Holocene, and a White Nile source during the Late Pleistocene and Middle Holocene. Geochemical data is additionally utilized in the determination of variations in the properties of the paleo-water (paleo-salinity and paleo-productivity). The paleo-water of Faiyum Lake exhibited characteristics of a substantial freshwater body during the Early to Mid-Holocene. During the subsequent period, there was a sudden drop in the lake level, accompanied by a subsequent rise in salinity due to hydrological modifications.

This study was carried out in the weathering profile on gneiss in the Mandoga area (south Cameroon plateau), on the petrological characterization of the weathered phases. Gneiss is made up of quartz, feldspars, biotite, muscovite, garnet, kyanite, and zircon, with negative Eu anomaly (Eu/Eu* = 0.63). The profile shows three groups of phases: coarse saprolite at the bottom of the weathering horizon, the phases of the fine saprolite, and those of the uppermost part of the weathering profile. The mineralogical composition differs from the coarse saprolite to the top soil. All phases comprised kaolinite, quartz, and goethite. They characterize a pedoclimatic environment-rich in water, favorable to the stability of hydrated minerals. The negative Eu anomaly in all phases reflects the lithodependance of horizons at the expense of the gneiss, the parent rock. The Ce anomalies are linked to the pedodynamic conditions. In the same way, the behavior of REE in the different phases confirms the variation of the geochemical processes of the two pedodynamic domains. The phases from the fine saprolite are enriched in LREE than in HREE and match an overlapping of geochemical pedodynamic processes. Thus, the phases are marked by the geochemical signature along the weathering profile.