Linking geophysics and soil function modelling - two examples

iSOIL - "Interactions between soil related sciences - Linking geophysics, soil science and digital soil mapping" is a Collaborative Project (Grant Agreement number 211386) co-funded by the Research DG of the European Commission within the RTD activities of the FP7 Thematic Priority Environment. The iSOIL project aims at reliable mapping of soil properties and soil functions with various methods including geophysical, spectroscopic and monitoring techniques. The general procedure contains three steps (i) geophysical monitoring, (ii) generation of soil property maps and (iii) process modelling. The objective of this work is to demonstrate the methodological procedure on two different examples. Example A focuses on the turnover conditions for soil organic matter (SOM) since many soil functions in a direct or indirect way depend on SOM and SOM depletion is amongst the worst soil threats. Example B deals with the dynamics of soil water and the direct influence on crop biomass production. The applied CANDY model (Franko et al. 1995) was developed to describe dynamics of soil organic matter and mineral nitrogen as well as soil water and temperature. The new module PLUS extends CANDY to simulate crop biomass production based on environmental influences (Krüger et al. 2011). The methodological procedure of example A illustrates a model application for a field site in the Czech Republic using generated soil maps from combined geophysical data. Modelling requires a complete set of soil parameters. Combining measured soil properties and data of geophysical measurements (electrical conductivity and gamma spectrometry) is the basis for digital soil mapping which provided data about clay, silt and sand as well as SOC content. With these data pedotransfer functions produce detailed soil input data (e.g. bulk and particle density, field capacity, wilting point, saturated conductivity) for the rooted soil profile. CANDY calculated different indicators for SOM and gave hints about potential hot spots where local adaptations of agricultural management would be required to improve soil functions. Example B realizes a soil function modelling with an adapted model parameterization based on data of ground penetration radar (GPR). This work shows an approach to handle heterogeneity of soil properties with geophysical data used for modelling. The field site in Austria is characterised by highly heterogenic soil with fluvioglacial gravel sediments. The variation of thickness of topsoil above a sandy subsoil with gravels strongly influences the soil water balance. GPR detected exact soil horizon depth between topsoil and subsoil. The extension of the input data improves the model performance of CANDY PLUS for plant biomass production. Both examples demonstrate how geophysics provide a surplus of data for agroecosystem modelling which identifies and contributes alternative options for agricultural management decisions.