Successful simulation-based environmental studies and relevant mapping applications rely on accurate predictions of soil hydraulic parameters from readily available soil properties. Progress in the latter area has been stagnant for at least 10 years - the base data used in such estimations has not changed much in over 30 years - which have compromised our ability to simulate environmentally relevant processes. This project has identified two reasons for this: (1) soil hydraulic properties measured in the laboratory poorly represent hydraulic properties at the field scale for reasons that are not yet well understood; and (2) conventional approaches to estimate soil hydraulic properties are primarily based on properties of the solid constituents of disturbed soil samples, while hydrological processes in the field are governed dominantly by the 3D void system of the undisturbed, structured soil. The aims of this project are to advance the scientific frontier on each of these identified areas by contributing to i) the understanding and quantification of 3D soil pore geometry; and ii) translating laboratory soil data into field-effective soil hydraulic properties. Existing international data as well as extensive dual-scale data collection campaigns will serve as the necessary soil data and validation on field moisture regime. Novel mathematical concepts, non-invasive geophysical measurements, and X-ray computed tomography imaging will be coupled with traditional measurements to generate the necessary data pool. Cutting edge machine learning tools will be used to quantify data relationships and the predictive power of the new types of data, and 2D/3D simulation modelling will be used to quantify the benefit from the new findings in the context of 2 selected field-sites, using existing and ongoing field data collection campaigns. The study promises to provide new, improved foundations for parameterizing environmental studies.
Project leader: Attila Nemes
Institution: NIBIO - NORSK INSTITUTT FOR BIOØKONOMI