Water Retention of Salt-Affected Soils: Quantitative Estimation Using Soil Survey Information

Abstract

Soil water retention (SWR) at −0.1, −33, −1500, and −150000 kPa matric potentials and available water content (AWC) were estimated from information available from 729 horizons of salt-affected soils in the Hungarian Detailed Soil Hydrophysical Database. Soil characteristics of the 1:10,000 scale Hungarian soil maps were used as input parameters. Ordinal and nominal (categorical) variables: texture, organic matter content, calcium carbonate content, soluble salt content, pH, and soil subtype classes of the soil map were used to develop a new prediction method based on the CHAID classification tree. Results of the model development were compared with results using conventional prediction methods (classification tree (CRT) and multiple linear regression (MLR)). Four types of pedotransfer rules were established by classification tree methods. The first rule uses continuous-type input parameters, the second uses soil taxonomical information in addition, the third and fourth one uses categorical-type input parameters. In addition, continuous pedotransfer functions (point estimations) were established as well. Results show that the root mean square error (RMSE) of the developed method is between 1.25 vol% (150000 kPa) and 6.40 vol% (−33 kPa). With the mentioned available input parameters, for salt-affected soils the prediction reliability is similar with categorical and continuous-type information. To predict SWR from categorical-type information the CHAID method is advisable. In the case of continuous-type input parameters MLR is suggested, based on this study. The established hydropedologic methods can be readily used to prepare available water content maps for the topsoil of salt affected soils based on solely soil survey information. Supplemental materials are available for this article. Go to the publisher's online edition of Arid Land Research and Management to view the free supplemental file.