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ARS Home » Pacific West Area » Riverside, California » U.S. Salinity Laboratory » Contaminant Fate and Transport Research » Research » Publications at this Location » Publication #179019


item Kelleners, Thijs
item Soppe, R.
item Ayars, James
item Simunek, Jirka
item Skaggs, Todd

Submitted to: Vadose Zone Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/9/2004
Publication Date: 7/18/2005
Citation: Kelleners, T.J., Soppe, R.W., Ayars, J.E., Simunek, J., Skaggs, T.H. 2005. Inverse analysis of upward water flow in a groundwater table lysimeter. Vadose Zone Journal. Vol 4: 558-572 (2005)

Interpretive Summary: Environmental impact and irrigation water management studies often rely on numerical models to predict water flow and chemical movement in soils. The predictions of these models are sensitive to the input of the soil hydraulic parameters. In this study, we estimated soil hydraulic parameters using an inverse modeling approach and examined the sensitivity of model simulations to the estimated parameters. The results will benefit scientists and engineers seeking to understand and predict the movement of water and chemicals in agricultural systems.

Technical Abstract: The accuracy of numerical water flow models for the vadose zone depends on the estimation of the soil hydraulic properties. In this study, the hydraulic parameters for a silty clay soil in a large lysimeter were determined through inverse modeling of a fallow period with upward water flow from a shallow groundwater table. Parameter uniqueness was studied by simulating a hypothetical soil with known hydraulic properties under comparable conditions. Sensitivity analysis showed that the pressure head h(z,t), the volumetric water content q(z,t), and the cumulative bottom flux Q(t) were least sensitive to the residual volumetric water content qr and the pore-connectivity parameter l in the van Genuchten-Mualem (VGM) model. Parameter response surfaces showed that least squares fitting with q(z,t) data is more likely to result in a unique hydraulic parameter set than least squares fitting with h(z,t) or Q(t) data. With only q(z,t) in the objective function, the least squares minimization algorithm was capable of finding the correct soil hydraulic parameters, provided that qr and l were fixed, and provided that multiple initial parameter estimates were used. The protocol that was developed for the hypothetical soil was subsequently applied to the actual groundwater table lysimeter. The soil hydraulic parameters for the lysimeter were determined for two (x,y) locations using q(z,t) data as measured by capacitance sensors. The variability in the optimized inverse of the air-entry value a and the saturated hydraulic conductivity Ks in the VGM model was relatively high because of the high parameter correlation between these parameters. The optimized soil hydraulic properties can be used to study capillary rise from the groundwater table.