Multistep outflow experiments to derive a soil hydraulic database for forest soils

P>Forest soils are under-represented throughout the existing soil hydraulic databases. Classical measurement methods for the hydraulic soil characteristics are very time-consuming and are not suited for routine application in the course of soil survey. We are presently engaged in establishing a database of the hydraulic properties of forest soils using multistep outflow experiments together with an inverse optimization of the Mualem/van Genuchten parameters from the tension and outflow measurements. The lower boundary in the multistep outflow experiments was modified such that, firstly, the experiment can be conducted as fast as possible and hence can be incorporated in the framework of routine soil monitoring. Secondly, the experimental design should be identical for a large texture range and therefore allow for a statistical comparison of the hydraulic properties of a broad variety of soils. Thirdly, the experiments must be designed such that they yield sufficient measurements for a unique and stable inverse parameter estimation. The inverse parameter estimates of the presently available 141 multistep outflow experiments were compared with predictions of two pedotransfer functions. For most soil samples, the PTF predictions differed highly from the MSO estimates. Reasons for this are, among others, insufficient hydraulic measurements included in the datasets used for establishing the PTFs and, specifically, insufficient information on water retention/conductivity in the range of the air entry value. Here, the MSO experiments can provide much more detailed information on the water retention and conductivity curves because they yield measurements over a continuous pressure range and are conducted such that the pressure range of the air entry value is covered by sufficient tension and outflow measurements. The presented research aims to: (i) introduce the measurement of soil hydraulic properties in an ongoing soil monitoring campaign, (ii) complement existing soil hydraulic databases with data from forest soils, and (iii) enhance the reliability of soil hydraulic databases through a standardization of the measuring approaches.