Modelling of grassland fluxes in Europe: Evaluation of two biogeochemical models

International audience

英语. Two independently developed simulation models – the grassland-specific PaSim and the biome-generic Biome-BGC MuSo (BBGC MuSo) – linking climate, soil, vegetation and management to ecosystem biogeochemical cycles were compared in a simulation of carbon (C) and water fluxes. The results were assessed against eddy-covariance flux data from five observational grassland sites representing a range of conditions in Europe: Grillenburg in Germany, Laqueuille in France with both extensive and intensive management, Monte Bondone in Italy and Oensingen in Switzerland. Model comparison (after calibration) gave substantial agreement, the performances being marginal to acceptable for weekly- aggregated gross primary production and ecosystem respiration (R2_ 0.66 _ 0.91), weekly evapotrans- piration (R2_ 0.78 _ 0.94), soil water content in the topsoil (R2_ 0.1 _0.7) and soil temperature (R2_ 0.88 _ 0.96). The bias was limited to the range _13 to 9 g C m_2 week_1 for C fluxes (_11 to 8 g C m_2week_1 in case of BBGC MuSo, and _13 to 9 g C m_2 week_1 in case of PaSim) and _4 to 6 mm week_1 for water fluxes (with BBGC MuSo providing somewhat higher estimates than PaSim), but some higher relative root mean square errors indicate low accuracy for prediction, especially for net ecosystem exchange The sensitivity of simulated outputs to changes in atmospheric carbon dioxide concentration ([CO2]), temperature and precipitation indicate, with certain agreement between the two models, that C outcomes are dominated by [CO2] and temperature gradients, and are less due to precipitation. ET rates decrease with increasing [CO2] in PaSim (consistent with experimental knowledge), while lack of appropriate stomatal response could be a limit in BBGC MuSo responsiveness. Results of the study indicate that some of the errors might be related to the improper representation of soil water content and soil temperature. Improvement is needed in the model representations of soil processes (especially soil water balance) that strongly influence the biogeochemical cycles of managed and unmanaged grasslands.