Origin and geochemical reaction paths of sabkha brines: Sabkha Jayb Uwayyid, eastern Saudi Arabia

Sabkhas are ubiquitous geomorphic features in eastern Saudi Arabia. Seven brine samples were taken from Sabkha Jayb Uwayyid in eastern Saudi Arabia. Brine chemistry, saturation state with respect to carbonate and evaporate minerals, and evaporation-driven geochemical reaction paths were investigated to delineate the origin of brines and the evolution of both brine chemistry and sabkha mineralogy. The average total dissolved solids in the sabkha brines is 243 g/l. The order of cation dominance is Na⁺   >>  Mg²⁺ >>  Ca²⁺>K⁺, while anion dominance is Cl⁻ >> SO₄ ²⁻ >> HCO₃ ⁻. Based on the chemical divide principle and observed ion ratios, it was concluded that sabkha brines have evolved from deep groundwater rather than from direct rainfall, runoff from the surroundings, or inflow of shallow groundwater. Aqueous speciation simulations show that: (1) all seven brines are supersaturated with respect to calcite, dolomite, and magnesite and undersaturated with respect to halite; (2) three brines are undersaturated with respect to both gypsum and anhydrite, while three brines are supersaturated with respect to both minerals; (3) anhydrite is a more stable solid phase than gypsum in four brines. Evaporation factors required to bring the brines to the halite phase boundary ranged from 1.016 to 4.53. All reaction paths to the halite phase boundary follow the neutral path as CO₂ is degassed and dolomite precipitates from the brines. On average, a sabkha brine containing 1 kg of H₂O precipitates 7.6 g of minerals along the reaction path to the halite phase boundary, of which 52% is anhydrite, 35.3% is gypsum, and 12.7% is dolomite. Bicarbonate is the limiting factor of dolomite precipitation, and sulfate is the limiting factor of gypsum and anhydrite precipitation from sabkha brines.     

Determination of regional land surface heat fluxes over a heterogeneous landscape of the Jiddah area of Saudi Arabia by using Landsat‐7 ETM data

In this study, a parameterization method based on Landsat‐7 Enhanced Thematic Mapper (ETM) data and field observations is presented and tested for deriving the regional land surface variables, vegetation variables and land surface heat fluxes over a heterogeneous landscape. As a case study, the method and two Landsat‐7 ETM images are applied to the Jiddah area of Saudi Arabia. The regional distribution maps of surface reflectance, normalized difference vegetation index, modified soil adjusted vegetation index (MSAVI), vegetation coverage, leaf area index, surface temperature, net radiation flux, soil heat flux, sensible heat flux and latent heat flux have been determined over the Jiddah area. The derived results have been validated by using the ‘ground truth’. The results show that the more reasonable regional distributions of land surface variables (surface reflectance, surface temperature), vegetation variables (MSAVI and vegetation coverage), net radiation, soil heat flux and sensible heat flux can be obtained by using the method proposed in this study. Further improvement of the method is also discussed. Copyright © 2006 John Wiley & Sons, Ltd.     

Paleoecology and paleoenvironment of the Middle–Upper Jurassic sedimentary succession,central Saudi Arabia

Four Middle–Upper Jurassic sections from central Saudi Arabia have been investigated to evaluate microfacies types and macro-invertebrate paleocommunities and to interpret their paleoecology and paleoenvironments. The studied Jurassic successions are part of the Middle–Upper Callovian Tuwaiq Mountain Limestone and the Middle–Upper Oxfordian Hanifa Formation. Three main facies were recorded, including mud-supported microfacies, grain-supported microfacies and boundstones. A data matrix comprising 48 macrobenthic species in 35 samples collected from four sections were grouped into fifteen assemblages and one poorly fossiliferous interval by means of a Q-mode cluster analysis. The recorded macrofaunal assemblages have been subdivided into low-stress and high-stress on the basis of hydrodynamic conditions, substrate type, nutrient supply and hypoxia. The low-stress assemblages occur in (a) high-energy paleoenvironments with firm substrates; (b) high-energy shoals with unstable substrates of low cohesion and in (c) low-energy open marine environments with soft-substrates. The moderate- to high-stress assemblages occur in (a) oligotrophic environments with reduced terrigenous input in shelf lagoonal or in restricted inner ramp settings; (b) low-energy, soft substrate environments with hypoxia below the sediment–water interface; and, in (c) high-energy shoals and shelf lagoonal environments. The temporal distribution patterns of epifaunal and infaunal bivalve taxa are controlled by variations in water energy, substrate characteristics and productivity level. The reported litho- and biofacies confirmed that the Callovian Tuwaiq Mountain Limestone and the Oxfordian Hanifa Formation were deposited across wide spectrum of depositional environments, ranging from restricted lagoon to moderately deeper open marine basin, and providing the perfect conditions for macrofossils.     

A record of Holocene climate change from lake geochemical analyses in southeastern Arabia

Lacustrine sediments from southeastern Arabia reveal variations in lake level corresponding to changes in the strength and duration of Indian Ocean Monsoon (IOM) summer rainfall and winter cyclonic rainfall. The late glacial/Holocene transition of the region was characterised by the development of mega-linear dunes. These dunes became stabilised and vegetated during the early Holocene and interdunal lakes formed in response to the incursion of the IOM at approximately 8500 cal yr BP with the development of C3 dominated savanna grasslands. The IOM weakened ca. 6000 cal yr BP with the onset of regional aridity, aeolian sedimentation and dune reactivation and accretion. Despite this reduction in precipitation, the lake was maintained by winter dominated rainfall. There was a shift to drier adapted C4 grasslands across the dune field. Lake sediment geochemical analyses record precipitation minima at 8200, 5000 and 4200 cal yr BP that coincide with Bond events in the North Atlantic. A number of these events correspond with changes in cultural periods, suggesting that climate was a key mechanism affecting human occupation and exploitation of this region.     

Landslide susceptibility mapping using machine learning algorithms and comparison of their performance at Abha Basin,Asir Region,Saudi Arabia

The current study aimed at evaluating the capabilities of seven advanced machine learning techniques(MLTs),including,Support Vector Machine(SVM),Random Forest(RF),Multivariate Adaptive Regression Spline(MARS),Artificial Neural Network(ANN),Quadratic Discriminant Analysis(QDA),Linear Discriminant Analysis(LDA),and Naive Bayes(NB),for landslide susceptibility modeling and comparison of their performances.Coupling machine learning algorithms with spatial data types for landslide susceptibility mapping is a vitally important issue.This study was carried out using GIS and R open source software at Abha Basin,Asir Region,Saudi Arabia.First,a total of 243 landslide locations were identified at Abha Basin to prepare the landslide inventory map using different data sources.All the landslide areas were randomly separated into two groups with a ratio of 70%for training and 30%for validating purposes.Twelve landslide-variables were generated for landslide susceptibility modeling,which include altitude,lithology,distance to faults,normalized difference vegetation index(NDVI),landuse/landcover(LULC),distance to roads,slope angle,distance to streams,profile curvature,plan curvature,slope length(LS),and slope-aspect.The area under curve(AUC-ROC)approach has been applied to evaluate,validate,and compare the MLTs performance.The results indicated that AUC values for seven MLTs range from 89.0%for QDA to 95.1%for RF.Our findings showed that the RF(AUC=95.1%)and LDA(AUC=941.7%)have produced the best performances in comparison to other MLTs.The outcome of this study and the landslide susceptibility maps would be useful for environmental protection.     

Surface temperature forecast skill comparison for the west coast of Saudi Arabia

Given the growing interest of the general public in accessing commercial weather forecasts through various media outlets and the available impetuses for promoting tourism in Saudi Arabia (SA), a first attempt is made to present a forecast skill comparison for surface temperature in four cities (Wejh, Yenbo, Jeddah, and Gizan) along the west coast of SA, for the 61-day transitional period (from January 16 to March 16) between the December-January-February (DJF) and the March-April-May (MAM) seasons. A simple skill score comparison method is used to assess the next-day city forecasts for surface temperature from six commercial weather forecast providers based on the operational numerical weather prediction (NWP) model outputs. All the NWP model forecast providers performed better than the respective daily climatology (Clm) for each station. Depending upon the station and the provider, the absolute average maximum daily surface temperature difference between the forecasts and the observations was less than 2 °C. Daily surface temperature forecasts from two versions of an atmospheric-ocean general circulation model are also compared to assess their performance for these coastal locations.     

Mapping of bauxite mineral deposits in the northern region of Saudi Arabia by using Advanced Spaceborne Thermal Emission and Reflection Radiometer satellite data

Mineral deposit mapping is very essential for sustainable and eco-friendly exploitation of natural resources. The Kingdom of Saudi Arabia has abundant natural resources such as natural gas, oil and minerals. It reserves high quantity of minerals such as phosphates, bauxites, copper, gold and other industrial minerals. The red soil regions located in Hail and Qassim provinces of Saudi Arabia have rich amount of bauxite (major aluminum ore) deposits. In order to initiate the focus on mapping of mineral deposits along this area, standardized hyper-spectral analysis has been carried out by using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data. The spectral signature of gibbsite (major element in bauxite) samples is analyzed with reference to the spectral features of gibbsite in the visible near infrared and short-wave infrared bands electromagnetic spectrum. Advanced hyper-spectral transformations such as minimum noise fraction function and pixel purity index have been performed to identify the target end-member. The existence of the mineral is confirmed by comparing the spectral signatures of the end-member with the predefined spectral plots of ASTER and United States Geological Survey spectral libraries. Finally, the end-members are mapped and their abundance is estimated in 0–1 scale. The study has opened up new areas for mapping of bauxite deposits in the area and leads to eco-friendly exploitation of natural resources. It also validates the high potential of ASTER multispectral satellite data for the exploration and mapping of mineral resources.