This harmonized set of soil parameter estimates for Central Africa, comprising Burundi, the Democratic Republic of the Congo and Rwanda, was derived from the Soil and Terrain Database for Central Africa (SOTERCAF ver. 1.0) and the ISRIC-WISE soil profile database, using standardized taxonomy-based pedotransfer (taxotransfer) procedures.
The land surface of Central Africa, comprising some 2.4 million km2, has been characterized using 244 unique SOTER units, corresponding with 504 polygons. Each SOTER unit may consist of up to 6 soil components; each of these has been characterized by a representative profile. The main soil units mapped for the region have been characterized using 167 real profiles, selected by soil experts as being regionally representative for these units. The associated soil analytical data have been derived from soil survey reports.
Gaps in the measured soil data have been filled using a scheme of using a step-wise procedure that uses taxotransfer rules. These rules were developed using some 5672 soil profiles, held in the ISRIC-WISE database, having similar FAO soil unit names as those reported in the primary SOTERCAF database.
Parameter estimates are presented by soil unit for fixed depth intervals of 0.2 m to 1 m depth for: organic carbon, total nitrogen, C/N ratio, pH(H2O), CECsoil, CECclay, base saturation, effective CEC, aluminium saturation, CaCO3 content, gypsum content, exchangeable sodium percentage (ESP), electrical conductivity of saturated paste (ECe), bulk density, content of sand, silt and clay, content of coarse fragments (less than 2 mm), and available water capacity (-33 kPa to -1.5 MPa). These attributes have been identified as being useful for agro-ecological zoning, land evaluation, crop growth simulation, modelling of soil carbon stocks and change, and analyses of global environmental change.
The current parameter estimates should be seen as best estimates based on the current selection of soil profiles and data clustering procedure. Taxotransfer rules have been flagged to provide an indication of the possible confidence in the derived data.
