Recent advancements in modeling the movement and groundwater infiltration of heavy metals in agricultural soils: A bibliometric research study

Abstract

Heavy metal contamination of soil and groundwater is one of the most significant global issues affecting food security and food safety. Alarming statistics report high levels of soil contamination worldwide and several studies have documented the mechanisms by which plants bioaccumulate heavy metals. This bibliometric research study is the first step toward summarising the existing scientific literature and suggesting next steps for evaluating advances in modelling the transport of heavy metals in agricultural soils and their leaching into groundwater. Several numerical models have validated the phenomenon. For example, the multiple linear regression (MLR) model is effective in predicting mercury (Hg), lead (Pb), cadmium (Cd), arsenic (As), zinc (Zn) and nickel (Ni), but not copper (Cu) and chromium (Cr). In comparison, the models constructed by Random Forest (RF) and Gradient Boosted Machine (GBM) were able to predict the bioaccumulation factors of Zn, Cu, Ni, Cr, Hg and Cd well. Furthermore, most studies report high heavy metal concentrations in the study areas, exceeding international standards several times, indicating the absence of public control policies. This review highlights that future studies must address several persistent limitations; for example, many authors suggest using bioavailable heavy metal content instead of total content. However, the authors of this review believe that this report provides new insights for policymaking related to heavy metal pollution in soil-crop ecosystems and food security.