High-resolution soil organic carbon mapping at the field scale in Southern Belgium (Wallonia)

Abstract

• A Gradient Boosting machine method predicted SOC contents for agricultural fields in Wallonia with 77% accuracy. • We constructed a covariate to quantify the carbon input to soils integrating main crops and cover crops. • The final map shows patterns of SOC content at field scale with distinctive differences between adjacent fields. • Different environmental covariates shape the distribution of SOC at different spatial scales. Accurate soil organic carbon content estimation is critical as a proxy for carbon sequestration, and as one of the indicators for soil health. Here, we collected 497 soil samples during 2015 and 2019, as well as five environmental covariates (organic carbon (OC) input from the crops, normalized difference vegetation index (NDVI), elevation, clay content and precipitation) at a resolution of 30 m. We then aggregated these to represent agricultural fields and compiled a soil organic carbon (SOC) content map for the agricultural soils of Wallonia using Gradient Boosting Machine. We calculated OC input from both main crops and cover crops for each individual field. As the cover crops do not occur in the agricultural census, we identified cover crops based on long time-series of NDVI values obtained from the Google Earth Engine platform. The quality of the SOC predictions was assessed by validation data and we obtained an R 2 of 0.77. The Empirical Mode Decomposition indicated that OC input and NDVI were the dominant factors at field scale, whereas the remaining covariates determined the distribution of SOC at the scale of the entire Walloon region. The SOC map showed an overall northwest to southeast trend i.e. an increase in SOC contents up to the Ourthe river followed by a decrease further to the South. The map shows both regional trends in SOC and effects of differences in land use and/or management (including crop rotation and frequency of cover crops) between individual fields. The field-scale map can be used as a benchmark and reference to farmers and agencies in maintaining SOC contents at an appropriate level and optimizing decisions for sustainable land use.