Carbon (C) emissions from anthropogenic land use have accelerated climate change. To reduce C emissions, dynamic models can be used to assess the impact of human drivers on terrestrial C sequestration. Model accuracy requires correct initialisation, since incorrect initialisation can influence the results obtained. Therefore, we sought to improve the initialisation of a process-based SOC model, RothC, which can estimate the effect of climate and land-use change on SOC. The most common initialisation involves running the model until equilibrium (‘spin-up run’), when the SOC pools stabilise (method 1). However, this method does not always produce realistic results. At our experimental sites, the observed SOC was not at equilibrium after 10 years, suggesting that the commonly used spin-up initialisation method assuming equilibrium might be improved. In addition to method 1, we tested two alternative initialisations for RothC that involved adjusting the total or individual SOC pool equilibrium values by regulating the C input during the entire spin-up initialisation period (method 2) and initialising each SOC pool with recently measured SOC values obtained by SOC fractionation (method 3). Analysis of the simulation accuracy for each model initialisation, quantified using the root mean square error (RMSE), indicated that a variant of method 2 that involved adjusting the equilibrium total SOC to observed values (method 2-T) generally showed less variation in the individual SOC pools and total SOC. Furthermore, as total SOC is the sum of all SOC pools, and because total SOC data are more readily available than the individual SOC pool data, we conclude that method 2-T is best for initialising RothC.