Prediction of soil water retention properties after stratification by combining texture, bulk density and the type of horizon

Among the numerous pedotransfer functions (PTFs) published, class-PTfs have received little attention because their accuracy is often considered limited. However, recent studies show that performance of class-PTFs can be similar to the more popular continuous-PTFs. In this study, we compare the performance of PTFs that were derived from a set of 456 horizons collected in France grouped by combinations of texture, bulk density and type of horizon (topsoil and subsoil). The performance of these class-PTFs was validated against water retained at -33 and -1500 kPa. Our results show that the best performance was obtained with class-PTFs that used both texture and bulk density (texture-structural class-PTFs). They also showed that incorporation of horizon type into the PTF did not improve prediction performance. Comparison of performance at -33 and -1500 kPa showed very little difference, thus indicating no bias according to the value of water potential. Finally, the class-PTFs developed are well suited for predicting water retention properties at the continental and national scales because only very basic soils data are available at these scales. A map of the available water capacity (AWC) was established for France using the 1:1 000 000 Soil Geographical Database of France and an averaged AWC of 104 mm was computed for France.