VFRC Publications - Page 32

Digital mapping of soil nutrients for the Republics of Burundi and Rwanda María Ruipérez González1 , Bas Kempen1, Prem S. Bindraban2, Sandra Wolters1, Cyrille Hicintuka3, Marcien Nibasumba4, Zacharie Nzohabonayo5, John Wendt6, Oscar Nduwimana5, John Veerkamp7 1 4 ISRIC – World Soil Information, Wageningen, The Netherlands, 2 VFRC, Washington D.C., USA, 3ISABU – Institute des Sciences Agronomiques du Burundi, Bujumbura, Burundi, Mininistère de l’Agriculture et de l’Elevage, Bujumbura, Burundi, 5IFDC, Bujumbura, Burundi, 6 IFDC – East and Southern Africa Division, Nairobi, Kenya7IFDC, Kigali, Rwanda Abstract Results Lack of awareness about soil fertility constraints is a major limitation to developing sound liming and fertilizer recommendations in sub-Saharan Africa. Detailed maps of soil nutrient concentrations and soil acidity can help to identify areas with soil fertility constraints. For this purpose, maps of primary (P, K), secondary (Ca, Mg, S) and micronutrients (Cu, Zn, B), as well as pH, soil acidity (Al+H), effective CEC and organic matter were generated for the 0-20 cm soil layer by means of digital soil mapping using random forest models at a 250 m spatial resolution for Burundi and Rwanda. The models explained between 20 and 45% of the variation in the data. Twelve soil nutrient maps were generated for each country. Fig. 2 shows examples for Ca, S, Cu and B. Covariates related to climate and terrain proved to be the best predictors. A continuous growth of the VFRC network with partners from the agricultural and environmental fields is foreseen, while participation of partners from the health sector, the food and chemical industries, as well as national and international development organizations and policy will be essential for a balanced representation of required expertise. We are, therefore, looking for partners and endeavor to catalyze a global dialogue on R&D of, and the need for, innovative fertilizers. We therefore invite you to join VFRC in its effort and look forward to partnering with you. Fig. 2. Predicted secondary (Ca, S) and micronutrients (Cu, B) for the 0-20 cm layer. Objective To update the currently available soil nutrient maps of Burundi and Rwanda in terms of resolution and soil variables, including micronutrients, to support soil fertility management programs. Methodology      Around 1000 field observations of soil fertility parameters for each country were used to calibrate random forests models (Fig. 1). Over 100 environmental GIS data layers representing land cover, soil, terrain and climate were used as covariates in the models (Fig. 1). Model calibration and mapping was done for each country separately. A kriging step was added if the model residuals showed