Modeling topsoil carbon sequestration in two contrasting crop production to set-aside conversions with RothC – Calibration issues and uncertainty analysis

Abstract

Model simulations of soil organic carbon turnover in agricultural fields have inherent uncertainties due to input data, initial conditions, and model parameters. The RothC model was used in a Monte Carlo based framework to assess the uniqueness of solution in carbon sequestration simulations. The model was applied to crop production to set-aside conversions in Iowa (sandy clay-loam soil, humid-continental climate) and Greece (clay-loam soil, Mediterranean). The model was initialized and calibrated with particulate organic carbon data obtained by physical fractionation. The calibrated values for the Iowa grassland were 5.05tCha−1, 0.34y−1, and 0.27y−1 for plant litter input and decomposition rate constants for resistant plant material (RPM) and humus, respectively, while for the Greek shrubland these were 3.79tCha−1, 0.21y−1, and 0.0041y−1, correspondingly. The model sensitivity analysis revealed that for both sites, predicted soil organic carbon content was most sensitive to the total plant litter input and the RPM rate. The Iowa soil was projected to sequester 17.5tCha−1 and the Greek soil 54tCha−1 over 100 years and the projected uncertainty was 65.6% and 70.8%, respectively. We propose this methodology to assess the factors affecting carbon sequestration in agricultural soils and quantify the uncertainties.