Quantifying the Accuracy, Uncertainty, and Sensitivity of Soil Geochemical Multisurface Models

Area of Science:

• Environmental Chemistry
• Geochemistry
• Soil Science

Background:

• Geochemical multisurface models are crucial for understanding metal partitioning and speciation.
• Previous evaluations of model parameter uncertainty and sensitivity in soils were insufficient.

Purpose of the Study:

• To quantify uncertainty and sensitivity of model parameters and input values for metal speciation in diverse soils.
• To establish improved generic parameters for the nonideal competitive adsorption-Donnan (NICA-Donnan) model.
• To assess the impact of simplified soil property inputs on model accuracy.

Main Methods:

• Utilized statistical tools and diverse soil data to evaluate the NICA-Donnan model coupled with the generalized two-layer model.
• Quantified uncertainty in model parameters, input values, and speciation predictions for Cadmium (Cd), Copper (Cu), and Zinc (Zn).
• Determined sensitivity to model parameters and input values, identifying key influential factors.

Main Results:

• Established new generic NICA-Donnan parameters that significantly enhanced model accuracy, particularly for Zn.
• Observed uncertainty levels followed the trend Cu < Cd < Zn.
• Organic matter (OM) was identified as the primary binding surface, with affinity parameters being most influential.
• A simplified scenario using assumptions about OM fractionation and metal-oxide surface area had negligible impact on model accuracy and uncertainty.

Conclusions:

• The developed generic parameters offer improved accuracy for metal speciation modeling in soils.
• Mechanistic multisurface models can be adopted more broadly for environmental applications with reliable performance measures.
• Simplified soil characterization approaches are viable without compromising model accuracy, facilitating wider use.