The relevance of in-situ and laboratory characterization of sandy soil hydraulic properties for soil water simulations

Field water flow processes can be precisely delineated with proper sets of soil hydraulic properties derived from in situ and/or laboratory experiments. In this study we analyzed and compared soil hydraulic properties obtained by traditional laboratory experiments and inverse optimization tension infiltrometer data along the vertical direction within two typical Podzol profiles with sand texture in a potato field. The main goal was to identify proper sets of hydraulic parameters and to evaluate their relevance on hydrological model performance for irrigation management purposes. Tension disc infiltration experiments were carried out at four and five different depths for both profiles at consecutive negative pressure heads of 12, 6, 3 and 0.1cm. At the same locations and depths undisturbed samples were taken to determine Mualem–van Genuchten (MVG) hydraulic parameters (θr, residual water content, θs, saturated water content, α and n, shape parameters and Kls, lab saturated hydraulic conductivity) in the laboratory. Results demonstrated horizontal differences and vertical variability of hydraulic properties. The tension disc infiltration data fitted well in inverse modeling using Hydrus 2D/3D in combination with final water content at the end of the experiment, θf. Four MVG parameters (θs, α, n and field saturated hydraulic conductivity Kfs) were estimated (θr set to zero), with estimated Kls and α values being relatively similar to values from Wooding’s solution which used as initial value and estimated θs corresponded to (effective) field saturated water content, θf. The laboratory measurement of Kls yielded 2–30 times higher values than the field method Kfs from top to subsoil layers, while there was a significant correlation between both Ks values (r=0.75). We found significant differences of MVG parameters θs, n and α values between laboratory and field measurements, but again a significant correlation was observed between laboratory and field MVG parameters namely Ks, n, θs (r⩾0.59). Assessment of the parameter relevance in 1-D model simulations, illustrated that the model over predicted and under predicted top soil-water content using laboratory and field experiments data sets respectively. The field MVG parameter data set resulted in better agreement to observed soil-water content as compared to the laboratory data set at nodes 10 and 20cm. However, better simulation results were achieved using the laboratory data set at 30–60cm depths. Results of our study do not confirm whether laboratory or field experiments data sets are most appropriate to predict soil water fluctuations in a complete soil profile, while field experiments are preferred in many studies.