The effects of projected changes in climate and atmospheric CO2 concentration on productivity and nitrogen (N) leaching of characteristic arable and pig farming rotations in Denmark were investigated with the FASSET simulation model. The LARS weather generator was used to provide climatic data for the baseline period (1961–90) and in combination with two regional circulation models (RCM) to generate climatic data under the Intergovernmental Panel on Climate Change (IPCC) A1B emission scenario for four different 20-year time slices (denoted by midpoints 2020, 2040, 2060 and 2080) for two locations in Denmark, differing in soil and climate, and representative of the selected production systems. The CO2 effects were modelled using projected CO2 concentrations for the A1B emission scenario. Crop rotations were irrigated (sandy soil) and unirrigated (sandy loam soil), and all included systems with and without catch crops, with field operation dates adapted to baseline and future climate change. Model projections showed an increase in the productivity and N leaching in the future that would be dependent on crop rotation and crop management, highlighting the importance of considering the whole rotation rather than single crops for impact assessments. Potato and sugar beet in arable farming and grain maize in pig farming contributed most to the productivity increase in the future scenarios. The highest productivity was obtained in the arable system on the sandy loam soil, with an increase of 20% on average in 2080 with respect to the baseline. Irrigation and fertilization rates would need to be increased in the future to achieve optimum yields. Growing catch crops reduces N leaching, but current catch crop management might not be sufficient to control the potential increase of leaching and more efficient strategies are required in the future. The uncertainty of climate change scenarios was assessed by using two different climate projections for predicting crop productivity and N leaching in Danish crop rotations, and this showed the consistency of the projected trends when used with the same crop model.
Journal of Agricultural Science, 2014, Vol 152, Issue 1, p. 75-92