A novel multiscale biophysical model to predict the fate of ionizable compounds in the soil-plant continuum

Abstract

Soil pollution from emerging contaminants poses a significant threat to water resources management and food production. The development of numerical models to describe the reactive transport of chemicals in both soil and plant is of paramount importance to elaborate mitigation strategies. To this aim, in the present study, a multiscale biophysical model is developed to predict the fate of ionizable compound in the soil-plant continuum. The modeling framework connects a multi-organelles model to describe processes at the cell level with a semi-mechanistic soil-plant model, which includes the widely used Richards-based solver, HYDRUS. A Bayesian probabilistic framework is used to calibrate and assess the capability of the model in reproducing the observations from an experiment on the translocation of five pharmaceuticals in green pea plants. Results show satisfactory fitting performance and limited predictive uncertainty. The subsequent validation with the cell model indicates that the estimated soil-plant parameters preserve a physically realistic meaning, and their calibrated values are comparable with the existing literature values, thus confirming the overall reliability of the analysis. Model results further suggest that pH conditions in both soil and xylem play a crucial role in the uptake and translocation of ionizable compounds.

Keywords: Bayesian analysis; Green pea; Ionizable compounds; Modeling; Pharmaceuticals; Soil-plant continuum.