Contribution of GIS techniques and pollution indices in the assessment of metal pollution in agricultural soils irrigated with wastewater: case of the Day River, Beni Mellal (Morocco)

Abstract

Wastewater irrigation and intensive agricultural practices are two of the major sources of soil pollution throughout the world. The aim of this study was to evaluate the levels of metal pollution in ground samples collected in the city of Beni Mellal, Morocco due to wastewater in the Day River. We collected 35 samples of agricultural soils at a sampling depth of 0–30 cm. As a first step, all samples were analyzed to determine some of the physicochemical characteristics of the soil samples (organic matter [OM], clay mineralogy [CaCO3], pH, electrical conductivity, texture) and the levels of specific metallic elements (As, Cr, Cu, Cd, Ni, Pb, Zn, and Fe). The results revealed that the analyzed soils had a clayey to silty-clay texture and alkaline pH; were rich in OM and carbonates; and had elevated levels of metallic elements (in mg/kg: As, 8.24; Cr, 77.77; Cu, 87.40; Cd, 4.89; Ni, 42.33; Pb, 109.66; Zn, 75.98; Fe: 26,248.18), all of which, with the exception of Ni, were higher than local background values. In addition, the concentrations of Pb and Cd considerably exceeded the limit values set by the World Health Organization and the Food and Agriculture Organization. To comprehensively assess the degree of pollution, we calculated a wide range of pollution indices, such as the geoaccumulation index (Igeo), enrichment factor (EF), contamination factors (CF), pollution load index (PLI), and potential ecological risk assessment (RI), using geochemical background values. The results showed that the levels of contamination in the soils under investigation ranged from moderate to high levels, suggesting an anthropogenic source. Analysis of the spatial distribution of the heavy metals showed high concentrations in the center and upstream part of Day River, with concentrations gradually decreasing downstream with the flow of wastewater. Statistical analyses were carried out to identify the relationship between the presence of heavy metals in the soils and the possible sources using principal component analysis and hierarchical clustering analysis methods and the Pearson correlation coefficient. The results of these analyses showed a significant and positive correlation between the presence of all heavy metals, indicating an identical or similar source, and also revealed that the contamination is related to the type of irrigation system, intensive agriculture practices, and soil properties (pH, OM, CaCO3). These results provide valuable geochemical data to support land-use managers, policy-makers, and environmental organizations in their efforts to monitor and decrease the accumulation of heavy metals in soils.