• hydraulic properties;
  • conductivity;
  • water retention;
  • pedotransfer

[1] In hydrologic studies, especially those using dynamic unsaturated zone moisture modeling, calculations based on property transfer models informed by hydraulic property databases are often used in lieu of measured data from the site of interest. Reliance on database-informed predicted values has become increasingly common with the use of neural networks. High-quality data are needed for databases used in this way and for theoretical and property transfer model development and testing. Hydraulic properties predicted on the basis of existing databases may be adequate in some applications but not others. An obvious problem occurs when the available database has few or no data for samples that are closely related to the medium of interest. The data set presented in this paper includes saturated and unsaturated hydraulic conductivity, water retention, particle-size distributions, and bulk properties. All samples are minimally disturbed, all measurements were performed using the same state of the art techniques and the environments represented are diverse.