Izrar Ahmed

Hydrogeological vulnerability and pollution risk mapping of the Saq and overlying aquifers using the DRASTIC model and GIS techniques, NW Saudi Arabia

AbstractSaq and overlying aquifers serve as important sources of water supply for agricultural and domestic usage in Saudi Arabia. Due to urbanization and growth in the agricultural sector, groundwater resources are over-exploited and are prone to quality deterioration. The aquifer vulnerability technique helps delineate areas according to the susceptibility to groundwater contamination. Various parameters pertaining to the surface and subsurface environment were synthesized to represent the data variation in the 3D horizon. Estimates of the parameters, such as recharge, soil media, and vadose zone, were obtained based on modified criteria to account for data variability. Statistical analysis indicates that the input parameters are independent and contribute individually to the vulnerability index. For vulnerability assessment, the DRASTIC model was considered due to the large number of data input parameters. Based on the vulnerability index, the study area is classified into low to very high vulnerability classes. To assess the human interaction on the groundwater environment, the land-use pattern was included as an additional input layer. Sensitivity analyses helped to compute the influence of the input layers on the vulnerability index and the model calibration through revised weights. The model validity tests were performed by comparing the NO3, SO4 and Cl concentration with the different vulnerability zones. The aquifer vulnerability maps developed in the present study may serve as an important tool for effective groundwater resource management.

A combined hydrochemical-statistical analysis of Saq aquifer, northwestern part of the Kingdom of Saudi Arabia

The present study includes detailed hydrochemical assessment of groundwater resources of Saq aquifer. The Saq aquifer covers a large area (about 375,000 km2) and lies in the arid region with low annual rainfall and extremely high evaporation. In the study area, groundwater serves as the major source for agricultural activity and for domestic usages. A total of 295 groundwater samples collected and were analyzed for physico-chemical parameters such as hydrogen ion concentration (pH), total dissolved solids (TDS) and electrical conductivity (EC), sodium (Na+), potassium (K+), magnesium (Mg2+), and calcium (Ca2+), bicarbonate (HCO3) chloride (Cl−), sulfate (SO42−) and nitrate (NO3). The goal and challenge for the statistical overview was to delineate chemical distributions in a complex, heterogeneous set of data spanning over a large geographic range. After de-clustering to create a uniform spatial sample distribution with 295 samples, histograms and quantile-quantile (Q-Q) plots were employed to delineate subpopulations that have coherent chemical affinities. The elements showing significantly higher positive correlation are: TDS with EC; Ca with EC, TDS; Mg and EC, TDS, Ca, K; Cl and EC, TDS, Mg, Na, Ca; SO4 and EC, TDS, Ca, Cl, Na, Mg. The distribution of major ions in the groundwater is Na+ > Ca++ > Mg++ > K+ and Cl− > SO4−2>HCO3−>NO3−. Ionic abundance plot of alkalis with Ca and Mg is suggestive of mix type trends of concentrations as evident by moderate correlation (r = 0.57). About 60% of the total samples have alkalis abundance and rests have more Ca + Mg concentrations than alkalis. Taking both results of cluster tree and geochemical features of variables into consideration, the authors classify the elements into two major groups, the first includes TDS, Na, EC, Cl, Ca, SO4, and Mg, where the relationship within the group are strong. The second group includes K, HCO3, pH, and NO3. This group has close relationship with group 1 demonstrate that, the increase in the concentration to some elements could be the same. Some of the analyzed parameters approach a normal distribution, as both their skewnesses and kurtoses reach close to “0”. The study revealed that, all of the element pairs exhibit positive relations.

Evaluation of metals that are potentially toxic to agricultural surface soils, using statistical analysis, in northwestern Saudi Arabia

Abstract Heavy metals in agricultural soils enter the food chain when taken up by plants. The main purpose of this work is to determine metal contamination in agricultural farms in northwestern Saudi Arabia. Fifty surface soil samples were collected from agricultural areas. The study focuses on the geochemical behavior of As, Cd, Co, Cr, Cu, Hg, Pb and Zn, and determines the enrichment factor and geoaccumulation index. Multivariate statistical analysis, including principle component analysis and cluster analysis, is also applied to the acquired data. The study shows considerable variation in the concentrations of the analyzed metals in the studied soil samples. This variation in concentration is attributed to the intensity of agricultural activities and, possibly, to nearby fossil fuel combustion activities, as well as to traffic flows from highways and local roads. Multivariate analysis suggests that As, Cd, Hg and Pb are associated with anthropogenic activities, whereas Co, Cr, Cu and Zn are mainly controlled by geogenic activities. Hg and Pb show the maximum concentration in the analyzed samples as compared to the background concentration.