Arabian Journal of Geosciences最新文献

In the northwestern Himalayas, including Jammu and Kashmir (J&K), frequent landslides pose significant risks, necessitating proactive zoning to mitigate potential damage through effective land-use planning. Fourteen causative and two triggering factors, such as slope, aspect, curvature, relative relief (RR), terrain ruggedness index (TRI), geomorphon, dissection index (Di), lithology, structural tectonic, drainage density (Dd), stream power index (SPI), topographic wetness index (TWI), land use land cover (LULC), road density (Rd), earthquake density (Ed), and rainfall density (Rd), were selected based on terrain conditions to assess landslide susceptibility. Utilizing frequency ratio (FR) and information value (IV) approaches, a comprehensive landslide susceptibility mapping (LSM) study covered 54,922 km², incorporating 6669 landslide instances. This dataset was split into 70% (4659 landslides) for modeling and 30% (2010 landslides) for validation. The landslide susceptibility map, classified into five categories (very low, low, moderate, high, and very high), delineates varying proportions of the study area. Using the FR approach, these zones cover 12.9% (7063 km²), 25.7% (14,101 km²), 25.6% (14,049 km²), 24.7% (13,586 km²), and 11.1% (6123 km²) of the area, respectively. Meanwhile, employing the IV approach, the coverage percentages are 5.7% (3119 km²), 11.0% (6063 km²), 20.1% (11,057 km²), 38.9% (21,373 km²), and 24.1% (13,310 km²). Validation using receiver operating characteristic curves revealed high correlations for both FR (AUC: 0.809) and IV (AUC: 0.778) models, indicating their effectiveness. The FR model, characterized by simplicity and higher accuracy, outperformed the IV model, offering valuable insights for local, regional, and governments in land-use planning, disaster prevention, and mitigation efforts.

Changes in trends and variabilities of precipitation, temperature, and evaporation are some of the pronounced effects of climate change. This study assessed the effects of precipitation and temperature trends and variabilities on soil moisture storage. Forty-one years’ historical data on precipitation, temperature, and soil moisture were collected for four agrarian local government areas in southern and northern Nigeria. Trend changes and variabilities were analyzed using the Mann Kendall, modified Mann Kendall, Palmer drought severity index, standardized precipitation evaporation index, standardized precipitation index, and temperature indices. Observed precipitation in the northern part experienced very significant decrease and both the southern and northern divides experienced significant temperature increase over the last four decades. However, the temperature indices including hottest days (TXx), summer day (SU35), and diurnal temperature range (DTR) indicated northern Nigeria experienced more extreme temperature increase and thus more drought than southern Nigeria. The northern part had averages TXx, SU35, and DTR of 39.66 °C, 66.49 days, and 17.99 °C, while the southern part had 33.61 °C, 0.075 days, and 9.47 °C, respectively. The continuous increase in temperature and precipitation decrease are attributable to climate change caused by ozone layer depletion. Low precipitation and high temperature resulted to significant reduction of soil moisture storage in northern Nigeria, while soil moisture reductions were limited in southern Nigeria. Effects of temperature and precipitation trends on soil moisture trends therefore emphasize the need for proper water management, continuous soil moisture conservation, and intense irrigation practices, to enhance food production and security.

The introduction of unmanned aerial vehicles (UAVs) and their deployment as tools for terrain information gathering has prompted discussions regarding the quality of the resulting products and the potential for their extended applications in geomatics. This study specifically focuses on evaluating the utilization and capabilities of UAV photogrammetry in generating topographic maps, with a primary emphasis on assessing the accuracy of these maps. An area of approximately 2.65 km² of the New Administrative Capital in Cairo, Egypt, was captured using a DJI M300 RTK drone. Agisoft Metashape and Pix4Dmapper software were used to process digital images to produce orthophotos and digital surface models. The precision of direct geo-referencing was evaluated by utilizing common tie points extracted by the user and the onboard GPS camera positions recorded during flight. Horizontal and vertical RMSEs were measured at 0.069 m and 0.593 m for Pix4Dmapper and 0.062 m and 0.548 m for Agisoft Metashape, respectively. Notably, direct geo-referencing exhibited lower accuracy, particularly in the vertical dimension. In the 7-GCP scenario, when combined with indirect geo-referencing, both software packages achieved the highest accuracy, with radial RMSEs of 0.023 m and 0.054 m and vertical RMSEs of 0.038 m and 0.052 m, respectively, corresponding to a pixel size of 1.7–2.2 times the ground sampling distance (GSD). In summary, this study affirms the efficacy of utilizing UAV photogrammetry in creating digital maps, orthophotos, contour lines, digital terrain models, digital surface models, and line maps, all aligning with globally recognized standards.

This research utilized various data types, including remote sensing (RS), aeromagnetic (AM), vertical electrical sounding (VES), and hydrogeological (HG) information, to create a groundwater potential map (GPM) of the Ogbomoso region in southwestern Nigeria. The lineaments obtained from the RS and AM results were merged to produce the lineament density (LD) map of the Ogbomoso area. One hundred and sixty-five VES data were collected for this study. The Ogbomoso area has a distinct geoelectric sequence that consists of various layers. These include the topsoil, weathered/saprolite, saprock, fractured basement, and fresh basement rock. Eight groundwater conditioning factors (GwCFs) were considered to ensure an accurate assessment of the groundwater potential (GP) in the Ogbomoso area. Stepwise weight assessment ratio analysis (SWARA), a multicriteria decision analysis (MCDA) technique, was used to assign weights to each GwCFs. The given weight was normalized, and a coefficient of coherence was established. SWARA helped characterize GP in the Ogbomoso area into different categories. It was discovered that there is a 0.63-degree correlation between well locations and GPM produced for the Ogbomoso area. This confirms that the SWARA modeling technique is reliable for predicting groundwater potential in any typical basement complex terrain worldwide.

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.