Applying stochastic simulation techniques to a deterministic vadose zone solute transport model

Abstract

Current models for simulation of water flow and solute transport through the vadose zone are limited in their applicability to field-scale problems. On the one hand, most of the models lack the capability to account for naturally existing soil spatial heterogeneity and complex (bio)chemical processes that many solutes undergo, and on the other, use of certain types of the existing models is often not economically feasible. In the present study, stochastic simulation techniques were applied to GLEAMS, a deterministic vadose zone solute transport model, to simulate soil water changes and nitrate (NO 3 −) concentrations at various depths in the top 1.2 m heterogeneous soil profiles of three research plots in southern Ohio. Simulations were conducted at three levels of complication: (1) single-value output was obtained for each plot by running GLEAMS with plot-based mean values of soil parameters; (2) a prediction band was formed from the output probability density function (pdf) with selected soil properties described by a multi-variate normal (MVN) random vector for each plot; and (3) with each plot decomposed into sub-environments, a prediction band was formed from all output pdfs obtained using MVNs for every sub-environment. Predicted and observed soil water contents and nitrate concentrations were compared to evaluate model performance. Overall, the predicted long-term means from all simulations fit the long-term means of field observations well. However, stochastic simulation at the sub-environment level showed two distinct merits over the other two approaches: (1) it better predicted variations in soil water content and nitrate concentration at a plot scale; and (2) it had the capability of locating high-risk areas at a sub-environment scale.