Uncertainty propagation with numerical models for flow and transport in the unsaturated zone

Uncertainty propagation with numerical models for flow and transport in the unsaturated zone is studied using vector state-space methods. The output uncertainty is the result of spatially, randomly varying parameters describing the soil hydraulic properties. An efficient state covariance propagation method is proposed, based on first-order linearization of the system dynamics. The approach has been previously used with groundwater flow models, and this paper contributes an original generalization for unsaturated flow, including solute transport. Comparisons are made with Monte Carlo simulations of infiltration in two soils with distinctly different soil properties. For coefficients of variation of the parameters less than 0.3 the two methods agree well. The linearization method is found to be faster due to its analytical nature. The results are a promising first step for future research on parameter estimation and optimization, using the state-space linearization approach.

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