High resolution 3D modeling of soil organic carbon in a complex agricultural landscape using continuous depth functions

Soil organic carbon (SOC) is a key element of agroecosystems functioning and has a crucialimpact on global carbon storage at world scale. SOC spatial variability and temporaldynamics are strongly affected by natural and anthropogenic processes occurring at thelandscape scale, such as soil redistribution in the lateral and vertical dimensions by tillage anderosion processes. This study aims at modeling SOC distribution in A-horizons, at highspatial resolution, for an area of 1 000 ha in a complex agricultural landscape (NW France).The study site is characterized by high short distance heterogeneity due to an importantdiversity of soils (with varying redoximorphic conditions, depth), soil parent material(Aeolian loam cover, granite, hard and soft schist), topography, land use (annual crops,temporary or permanent grasslands) and hedge density. We used learning methods based onsoil point data, characterized by soil description, SOC content and bulk densitymeasurements. 200 points were selected using conditioned Latin hypercube sampling in orderto cover the whole range of ancillary variables (elevation, Modified Compound TopographicIndex, K emissions and land use). This sampling strategy enables to select a limited numberof sampling sites coverering the study site heterogeneity. Additive sampling was designed toinvestigate SOC distribution near hedges (112 points sampled at fixed distances along 14transects crossing hedges). Predictive environmental data consisted in the data used in theconditioned Latin hypercube sampling, at which were added topographic attributes derivatedfrom the DEM and geological variables. We will discuss the ability of our model to captureand predict the SOC, considering the general SOC distribution trend at the landscape scaleand the finer SOC distribution in landscape, at hedgerow proximity. The SOC 3-D mapobtained will be used as soil data input in a soil evolution model, coupling SOC dynamics andsoil erosion modeling.