Geo-Temporal Signatures of Physicochemical and Heavy Metals Pollution in Groundwater of Khulais Region—Makkah Province, Saudi Arabia

Khan, Mohd Yawar Ali; Kashouty, Mohamed El; Gusti, Waleed; Kumar, Amit; Subyani, Ali M.; Alshehri, Ahmed

doi:10.3389/fenvs.2021.800517

Cited by 17 publications

(16 citation statements)

References 39 publications

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“…Groundwater and surface water are worsening [1][2][3][4][5][6]. Water consumption and demand in the industrial, municipal, and agricultural sectors in SA have skyrocketed as a result of recent developments [7,8]. Ouda et al [9] stated that the supply-demand gap was 11,423 million m 3 /year during 2010.…”

Section: Introductionmentioning

confidence: 99%

Morphometric Determination and Digital Geological Mapping by RS and GIS Techniques in Aseer–Jazan Contact, Southwest Saudi Arabia

Khan

ElKashouty

Subyani

et al. 2023

Water

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The hydrological characteristics of the watershed in the southern Aseer and northern Jazan regions of Saudi Arabia (SA) were identified by integrated remote sensing (RS) and geographic information system (GIS) techniques using Shuttle Radar Topography Mission (SRTM) and Landsat data. For this purpose, the Wadi Ishran, Wadi Baysh, Wadi Itwad, Wadi Tabab, and Wadi Bayd drainage basins were extracted. Wadi Ishran is the largest, and Wadi Tabab is the smallest. Stream order and bifurcation ratio show that the Itwad and Bayd basins are permeable and of high aquifer potentiality. The multisupervised classification found seven rock units that were spread out in different ways across the basins. The areas with the highest vegetation were in the southeast, the centre, and the northwest. The bands’ ratios show more iron-rich sediments in the northeast and southwest. This paper’s outcomes serve as the basis for planning and managing groundwater resources. It finds potential groundwater zones, determines the risk of flooding, and chooses places where harvesting can be undertaken.

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Section: Introductionmentioning

confidence: 99%

Morphometric Determination and Digital Geological Mapping by RS and GIS Techniques in Aseer–Jazan Contact, Southwest Saudi Arabia

Khan

ElKashouty

Subyani

et al. 2023

Water

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“…To date, numerous algal bloom models have been developed to analyse the key driving factors of harmful algal blooms (HABs). Most of these models used traditional data‐driven statistical models, such as linear regression, multiple linear regression and logistic regression, which are difficult to meet the requirements of current research (Khan et al, 2022; Wang et al, 2021). Besides, process‐based dynamic models often required lengthy calibration periods.…”

Section: Introductionmentioning

confidence: 99%

Identification of driving factors for chlorophyll‐a in multi‐stable shallow lakes of China employing machine learning methods

Qu,

Wang,

Kumar

et al. 2023

Ecohydrology

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Due to the rapid increase in urbanization and anthropogenic activity in the lake catchment, nutrients like phosphorus and nitrogen are abundant in urban sewage, leading to lake eutrophication and promoting algal blooms. Chlorophyll‐a (Chl‐a) is an important indicator of algal blooms; thus, predicting concentration is vital for lake restoration and management. Literature reveals that most of the previous studies of Chl‐a prediction required multiple variables and considerable computation. Thus, it is crucial to scientifically identify the key drivers of Chl‐a in Taihu Lake for the formulation of effective environmental management measures. In this study, a long‐term dataset (1991–2015) and Daniel trend test method were employed to analyse the trend of meteorological and water quality indicators in Taihu Lake in China. The redundancy of variables was eliminated by using the rank correlation method, combined with prior knowledge that provides a solid foundation for the analysis of the driving factors of Chl‐a. Four machine learning models, named Extreme Gradient Boosting (XGBoost), random forest (RF), support vector regression (SVR) and gradient boosting decision tree (GBDT), were employed to predict the concentration of Chl‐a in different regions of Taihu Lake. The result shows that the XGBoost model outperformed the other three models in terms of R2 (>0.90) and root mean square error (RMSE) (3.69–8.40). Finally, based on the predictions of the concentration of Chl‐a using the XGBoost model, the SHapley Additive exPlanation (SHAP) framework was utilized to analyse the key factors influencing Chl‐a concentration. Finding of this study suggests that the XGBoost model performed best and could be applied to the overall stretches of Taihu Lake and other lakes in China; model prediction will be helpful in providing a zoning decision‐making approach for the rational protection of the lake environment and the prevention of algal bloom hazards.

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“…The recent advancements in SA have led to a significant increase in water use and demand across the industrial, municipal, and agricultural sectors [43,44]. According to the findings in [45], the disparity between supply and demand amounted to 11,423 million m 3 per year in 2010.…”

Section: Introductionmentioning

confidence: 99%

Hydrogeology and Hydrogeochemistry of Saline Groundwater Seepage Zones in Wadi Bani Malik Basin, Jeddah, Saudi Arabia: Impacts on Soil and Water Resources

ElKashouty,

Khan,

Alharbi

et al. 2023

Water

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The water seepage zone affects dryland salinity, soil sodicity, land degradation, waterlogging, and rainfall pollution. The priority in terms of the remediation measures was determining the cause of the seepages. Nine water and six soil samples were collected from the Al Tayseer area of the Wadi Bani Malik, Jeddah, Saudi Arabia (SA). The water samples were analyzed for major and toxic metals. For the soil samples, granulometric analysis and infiltration rate analysis were performed. The total dissolved solids (TDS) in water seepages ranged from 1880 to 54,499, whereas boron (B) and iron (Fe) values ranged from 1.9 to 38 mg/L and 0.02 and 0.47 mg/L, respectively. These concentrations were the same for the aquifer in Lake Al Misk, confirming that groundwater infiltration from the lake area was the main reason for the water seepage. The concentrations of silica (Si), aluminum (Al), cobalt (Co), nickel (Ni), zinc (Zn), arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), and lead (Pb) were low, indicating that there was no contamination. The nitrate (NO32−) value ranged from 2.2 to 35 mg/L, indicating agricultural wastewater contribution. According to the granulometric examination, most sediment was sand, followed by gravel, with few fine-grain particles. The infiltration rate ranged from 85 to 864 cm/d, indicating significant leakage. The percentage of ferrugination, ferromagnesian, OH-bearing, and carbonate (CO₃2−) minerals is determined by the 4/2, 5/6, and 6/7 band ratios.

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Geo-Temporal Signatures of Physicochemical and Heavy Metals Pollution in Groundwater of Khulais Region—Makkah Province, Saudi Arabia

Cited by 17 publications

References 39 publications

Morphometric Determination and Digital Geological Mapping by RS and GIS Techniques in Aseer–Jazan Contact, Southwest Saudi Arabia

Morphometric Determination and Digital Geological Mapping by RS and GIS Techniques in Aseer–Jazan Contact, Southwest Saudi Arabia

Identification of driving factors for chlorophyll‐a in multi‐stable shallow lakes of China employing machine learning methods

Hydrogeology and Hydrogeochemistry of Saline Groundwater Seepage Zones in Wadi Bani Malik Basin, Jeddah, Saudi Arabia: Impacts on Soil and Water Resources

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