Soil Organic Carbon Stock Maps for Belgium: standard deviation (1 km grid)

The Belgian soil organic carbon (SOC) stock map for topsoils (0-30 cm) was composed of 2 regional SOC stock maps. For the regional maps a different approach was used for agricultural land as compared to forest. The maps are based on digital soil mapping approaches using empirical models calibrated to predict the SOC stock and using covariates that are available at a sufficient resolution at the regional scale. All maps are strongly dependent on the Belgian Soil Map (texture and drainage parameters). The regional maps were compiled at a finer resolution (10 m x 10 m and 40 m x 40 m grid cells). Next they were joined (40 m x 40 m grid cells) and finally scaled up to the required 1 by 1 km grid cells. This was done using the following tools: block statistics (mean), mosaic to new raster (mean), project to raster, block statistics (mean), resample (nearest neighbor) and project raster. Given the different origin of the individual maps, the uncertainty varies between maps. For instance, a map of the 90 % confidence interval of the SOC stocks was produced for agricultural soils in Wallonia based on a Monte Carlo Approach taking into account both the measurement and the model uncertainty. For Flemish forest soils, spatial and analytical uncertainties were tasks into account using bootstrapping techniques. For Flemish agricultural soils, the uncertainty reported is the model uncertainty on point estimates for each data point, in which the estimated model parameters are simulated 1000 times as being independent normal distributed variables using their model estimation and standard error as distribution parameters. No additional uncertainty is tasks into account for the conversion functions that use the stochastic variables “bulk density”. The SOC stock maps are the first comprehensive map for Belgium integrating grasslands, croplands and forests. There are two versions of the SOC stock maps for Belgium: 1) resolution of 40 m x 40 m in the coordinate reference system Lambert72 and 2) resolution of 1 km x 1 km in the coordinate reference system WGS84. The metadata are available and allow assessing the uncertainties of the stock estimates in the different component maps.