Spatial evaluation of pedotransfer functions using wavelet analysis.

If the predictions of an pedotransfer functions (PTFs) are distributed in space, then they require requires a spatial evaluation. Three aspects of performance can be considered in the evaluation of a spatially distributed PTF: i) the correlation of observed and predicted quantities across different spatial scales; ii) the reproduction of observed variance across different spatial scales; and, iii) the spatial pattern of the model error. Further, when there is more than one PTF available, we must be able to choose which is most appropriate for a particular spatial scale. In this study, we observed soil hydraulic properties (water-retention and saturated hydraulic conductivity) at 100 regularly spaced locations on a 5000-m transect in southern Italy; four published PTFs (referred to as Models V, S, W, and L) were then used to predict the hydraulic properties at the sampled locations. We used wavelet analysis to examine how the variances and correlations of the observed and predicted properties varied with spatial scale. We felt that this spatial analysis revealed insights otherwise not possible. While there was little evidence for scale-dependent model performance, the scale-dependent variances of the predicted variables quantities were generally underestimated. We presented an example of how Model V failed, in one instance, to predict water-retention, and suggested how the wavelet correlation between model error and ancillary variables could be used to improve the performance of this model. Using the scale-dependent concordance correlation, we felt that Model L ??? a local calibration ??? was the generally the best PTF for the prediction of water-retention and saturated hydraulic conductivity, and would be especially useful for management decisions on the transect at a coarse spatial scale.