Calibration of variably saturated flow models with field monitoring data is complicated by the strongly nonlinear dependency of the unsaturated flow parameters on the water content. Combining predictions using various independent models, often called m>multimodel predictionm>, is becoming a popular modeling technique. The objective of this study was to compare different methods of multimodel simulation of the field soil water regime using pedotransfer functions (PTFs). We solved the Richards flow equation using HYDRUS-1D with parameter sets derived from 19 published PTFs and compared different methods of combining the simulation results from the 19 individual models by (i) using only the best model, (ii) using equal weights, (iii) regressing measured values to the results of the individual models, (iv) using singular-value decomposition (SVD) in the regression, (v) using Bayesian model averaging, and (vi) using weights derived from Akaike criteria. Data on soil water contents and basic soil properties at five depths along a 6-m transect in a layered loamy soil were used to calibrate the Richards equation and to develop the input for the PTFs. The SVD multimodel was the best method, with an accuracy of about 0.01 m3 m−3 at the 35-cm depth and about 0.005 m3 m−3 at greater depths for 30 d of monitoring and 13 mo of testing. This indicates that multimodeling in combination with monitoring of the soil water regime can be a viable approach to simulating water flow in the vadose zone.
