Estimation of soil hydraulic properties by pedotransfer functions (PTFs) can be an alternative to troublesome and expensive measurements. New approaches to develop PTFs are continuously being introduced, however, PTF applicability in locations other than those of data collection has been rarely reported. We used three databases were used to develop PTFs using artificial neural networks (NNs). Data from Hungary were used to derive national scale soil hydraulic PTFs. The HYPRES database was used to develop continental scale PTFs. Finally, a database containing mostly American and European data was used to develop intercontinental scale PTFs. For each database, 11 PTFs were developed that differed in detail of input data. Accuracy of the estimations was tested using independent Hungarian data. First, soil water retention at nine values of matric potential were estimated. Root mean squared residuals (RMSRs) using different inputs ranged from 0.02 to 0.06 m3 m-3 for national scale PTFs, while international scale PTFs had RMSRs from 0.025 to 0.088 m3 m-3. Estimated water retention curves (WRCs) were then used to simulate soil moisture time series of seven Hungarian soils. Root mean squared residuals during a growing season ranged from 0.065 to 0.07 m3 m-3, using different PTF estimates. Simulations using laboratory-measured WRCs had RMSR of 0.061 m3 m-3. Such small differences in the accuracy of simulations make international PTFs an alternative to national PTFs and measurements. However, testing of the international PTFs with a specific model for specific soil and land use remains desirable because of uncertainty in soil representation in such databases.
ASJC Scopus subject areas
- Soil Science