An alternative deterministic method for the spatial interpolation of water retention parameters

摘要

There are two approaches available for mapping water retention parametersover the study area using a spatial interpolation method. (1) Retentionmodels can be first fitted to retention curves available at samplinglocations prior to interpolating model parameters over the study area (theFI approach). (2) Retention data points can first be interpolated over thestudy area before retention model parameters are fitted (the IF approach).The current study compares the performance of these two approaches inrepresenting the spatial distribution of water retention curves. Standardgeostatistical interpolation methods, i.e., ordinary kriging and indicatorkriging, were used. The data used in this study were obtained from the LasCruces trench site database, which contains water retention data for 448soil samples. Three standard water retention models, i.e., Brooks and Corey(BC), van Genuchten (VG), and Kosugi (KSG), were considered. For each model,standard validation procedures, i.e., leave-one-out cross-validation andsplit-sample methods were used to estimate the uncertainty of the parametersat each sampling location, allowing for the computation of prediction errors(mean absolute error and mean error). The results show that the IF approachsignificantly lowered mean absolute errors for the VG model, while alsoreducing them moderately for the KSG and BC models. In addition, the IFapproach resulted in less bias than the FI approach, except when the BCmodel was used in the split-sample approach. Overall, IF outperforms FI forall three retention models in describing the spatial distribution ofretention parameters.