ICBM regional model for estimations of dynamics of agricultural soil carbon pools

Swedish arable land covers 3 Mha and its topsoil contains about 300 Mton C. The mineral soils seem to be close to steady-state, but the organic soils (about 10% of total arable land) have been estimated to lose ca. 1 Mton/year. We have devised a conceptual model (ICBMregion), using national agricultural crop yield/manuring statistics and allometric functions to calculate annual C input to the soil together with a five-parameter soil carbon model (ICBMr), calibrated using long-term field data. In Sweden, annual yield statistics are reported for different crops, for each of eight agricultural regions. Present topsoil carbon content and regional distribution of soil types have recently been measured. We use daily weather station data for each region together with crop type (bulked from individual crop data) and soil type to calculate an annual soil climate parameter for each crop/soil type permutation in each region. We use 14 soil types and 9 crop types, which gives 126 parameter sets for each year and region, each representing a fraction of the region's area. For each year, region, crop and soil type, ICBMregion calculates the change in young and old soil carbon per hectare, and sums up the changes to, e.g., national changes. With eight regions, we will have 1008 parameter sets per year, which easily can be handled, and what-if scenarios as well as comparisons between benchmark years are readily made. We will use the model to compare the soil C pools between the IPCC benchmark year 1990 and the present. In principle, we use inverse modelling from the sampled, recent soil C pools to estimate those in 1990. In the calculations, soil climate and yield for each year from 1990 onwards are taken into account. Then we can project soil C balances into the future under different scenarios, e.g., business as usual, land use change or changes in agricultural crops or cultivation practices. Projections of regional climate change are also available, so we can quite easily make projections of soil C dynamics under, e.g., different climate scenarios. We can follow the dynamic effects of carbon sequestration efforts – and estimate their efficiency. The approach is conceptually simple, fairly complete, and can easily be adapted to different needs and availability of data. However, perhaps the greatest advantage is that the results from this comprehensive approach used for, e.g., a 10-year period, can be condensed into a very simple spreadsheet model for calculating effects of management/land use changes on C stocks in agricultural soils.