Global sensitivity analysis for a prediction model of soil solute transfer into surface runoff

Abstract

The solute transfer from soil to surface runoff has been recognized as a major source of non-point source pollution, and it is of great significance to predict the solute transfer process using a modeling approach. Tong et al. (2010) developed a two-layer soil mixing model with a soil mixing layer and a layer of ponding-runoff water on soil surface. The model has three critical parameters, i.e., depth dmix of the soil mixing layer and incomplete mixing parameters α and γ that determine solute concentration in the ponding-runoff layer and the soil layer beneath the soil mixing layer, respectively. Using the variance-based Sobol’s methods, a global sensitivity analysis (GSA) was performed for this model to determine importance or influence of the three parameters to the model prediction of solute transfer from soil to surface runoff αCw(t). The GSA evaluated the time-varying first order index (FOI), second order index (SOI), third order index (DOI), total order index (TOI), and TOI-FOI for cases 1, 2 and 3, i.e., initially unsaturated soil with controlled sub-surface drainage, initially saturated soil with controlled sub-surface drainage, and initially saturated soil with restricted sub-surface drainage. The FOIs of α and dmix varied oppositely, and the interactions between α and dmix became stronger with time for three cases. For cases 1 and 2, γ was important for the predicted αCw(t), which was the most important at later time, and it had strong interactions with α and dmix. γ was found to be the most sensitive and important parameter for the predicted αCw(t) all the time for case 1. However, in case 3, γ was not sensitive to the predicted αCw(t), with almost no interactions of γ with α or dmix, where γ can be set as a constant.