Abstract

Arsenic is considered a poison because of its seriously toxic effects on the human body; elevated concentrations of arsenic in drinking water have been reported in different parts of the world. Investigating the arsenic distributions in soil, surface water (SW), and groundwater (GW) is an interesting topic of research, along with probing its correlations with local factors of the ecosystem and other hydrogeochemical parameters. This study mainly aims to investigate the impacts of various factors on elevated arsenic concentrations in water and soil. The following factors are assessed for their relationship to the propagation of arsenic in Jianghan Plain, which is the study area: population density, pumping rate, rain, land use, surface elevation, water level, and heavy metal contamination. The arsenic contamination potential prediction map and categories were developed using GIS-based techniques, such as ordinary kriging and quantile methods. Then, the “raster calculator” tool was applied to verify the impacts of the abovementioned factors on arsenic concentration. Eighty-four single-factor, bi-factor, and multi-factor models were established to investigate the effective combinations among the factors. Land use and pumping rate were identified from the soil through an equal frequency tool, whereas water population density and pumping rate were obtained with high matching percentages. The arsenic concentrations varied in the ranges of 0.0001–0.1582 mg/L in GW, 0.0003–0.05926 mg/L in SW, and 1.820–46.620 mg/kg in soil sediment. The single factors showed the best equal frequency of arsenic concentration in water for population density (68.62%) and in soil for land use (65.57%) and pumping (63.66%). Statistical calculations with percentage frequency factors also depicted a positive trend. Arsenic was reported to have high correlations with Fe in GW (r2 = 0.4193), with EC in SW (r2 = 0.4817), and with Cu in soil (r2 = 0.623). It is observed that the alkaline behaviors of water bodies are associated with arsenic mobility. Elevated arsenic values were observed in grids along surface flows with high anthropogenic activities and urbanization. Additionally, low concentrations of Fe depicted reduced activities in aquifer systems. Filtering drinking water as well as controlling the suspected sources and factors affecting concentrations of arsenic in the three phases are options for reducing the health risks of the local populations.

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