Estimating hydraulic properties of a fine-textured soil using a disc infiltrometer

Inverse optimization of parameters offers an economical means to infer soil hydraulic properties from in situ measurements of infiltration. We evaluated optimization strategies to inversely estimate soil hydraulic parameters using field measured tension disc infiltrometer data. We estimated the parameters n, alpha, and K-s of the van Genuchten-Mualem (VGM) model, and a piecewise representation of conductivity near saturation using a numerical inversion of Richards' equation. In addition to cumulative infiltration, optimizations included in the objective function water retention data, water contents from cores extracted after termination of infiltration, or transient measurements of water contents using time domain reflectometry (TDR) probes. Three-parameter fits to field data were nonunique because of a positive correlation between alpha and K-s. In contrast, fits of n and K-s with a estimated from separate fits to retention data improved parameter identifiability while not compromising the fit to measured infiltration. Inverse optimizations that included in the objective function both water retention and cumulative infiltration, led to excellent fits of this data when initial volumetric water contents were >0.23 cm(3) cm(-3). Close fits to cumulative infiltration were also obtained at lower water contents, however, water retention data was underestimated likely because of hysteresis. Optimizations of cumulative infiltration with final soil core water content or TDR data led to estimates of final water contents that closely approximated measured water contents. However, measured TDR water contents were poorly matched by simulations at early times. A piecewise loglinear interpolation of hydraulic conductivity near saturation improved fits to measured cumulative infiltration and water retention data as compared with using the VGM model at all pressure heads.