Effective soil hydraulic parameters of soil vegetation atmosphere transfer (SVAT) models can be derived in a cost-efficient way by inverse modeling. Nevertheless, a serious drawback of SVAT models based on Richards’ equation is that they require as many as five unexploited correlated hydraulic parameters. To reduce the feasible parameter space, we propose a method to prevent nonphysical combinations of soil hydraulic parameter sets obtained by optimization. We adopt the soil hydraulic analytical model by Kosugi because it enables the feasible parameter space to be reduced by predicting parameter σ from R m, which are the variance and mean of the log-transformed soil pore radius, respectively. To further decrease the parameter space, we derive two models to predict saturated hydraulic conductivity, K s, from three or four Kosugi soil water retention parameters, respectively. These two models are based on the combination of the Hagen-Poiseuille and Darcy equations that use three semiempirical parameters (τ 1, τ 2, and τ 3) calibrated on large UNSODA and HYPRES databases. Our derived models are compared with a version of the Mishra and Parker (1990. Ground Water. 28:775–777) K s model being modified to account for the parameters of Kosugi’s relationships. The results show that the uncertainties of the developed K s model are comparable to the uncertainties of K s measurements. Moreover, the developed K s model outperforms the Mishra and Parker model. Therefore, the developed method will enable one to substantially reduce the feasible range of the inverted Kosugi’s hydraulic parameters.
1Department of Biological and Agricultural Engineering, Texas A&M University, College Station, Texas, USA.
2Department of Agriculture, Division of Agricultural, Forest and Biosystems Engineering-University of Napoli Federico II, Naples, Italy.
3Departamento de Ingeniería en Geomática e Hidráulica-Universidad de Guanajuato, Guanajuato, Mexico.
4Université de Lyon, CNRS, UMR 5023 LEHNA, ENTPE, F-69518, Vaulx-en-Velin, France.
Address for correspondence: Dr. Joseph Alexander Paul Pollacco, PhD, Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX 77843, USA; E-mail: firstname.lastname@example.org
The authors report no conflicts of interest.
Received December 7, 2012.
Accepted for publication June 26, 2013.