Perego, A., Giussani, A., Sanna, M., Fumagalli, M., Carozzi, M., Alfieri, L., et al. (2013). The ARMOSA simulation crop model: overall features, calibration and validation results. Italian Journal of Agrometeorology, 3, 23–38.
Abstract: ARMOSA is a dynamic simulation model which was developed to simulate crop growth and development, water and nitrogen dynamics under different pedoclimatic conditions and cropping systems in the arable land. The model is meant to be a tool for the evaluation of the impact of different crop management practices on soil nitrogen and carbon cycles and groundwater nitrate pollution. A large data set collected over three to six years from six monitoring sites in Lombardia plain was used to calibrate and validate the model parameters. Measured meteorological data, soil chemical and physical characterizations, crop-related data of different cropping systems allowed for a proper parameterization. Fit indexes showed the reliability of the model in adequately predicting crop-related variables, such as above ground biomass (RRMSE=11.18, EF=0.94, r=0.97), Leaf Area Index maximum value (RRMSE=8.24, EF=0.37, r=0.72), harvest index (RRMSE=19.4, EF=0.32, r=0.74), and crop N uptake (RRMSE=20.25, EF=0.69, r=0.85). Using two different one-year data set from each monitoring site, the model was calibrated and validated, getting to encouraging results: RRMSE=6.28, EF=0.52, r=0.68 for soil water content at different depths, and RRMSE=34.89, EF=0.59, r=0.75 for soil NO3-N content along soil profile. The simulated N leaching was in full agreement with measured data (RRMSE=26.62, EF=0.88, r=0.98).
|
Sándor, R., Ma, S., Acutis, M., Barcza, Z., Ben, T., H., Doro, L., et al. (2014). Uncertainty in simulating biomass yield and carbon-water fluxes from Euro-Mediterranean grasslands under climate changes..
|
Perego, A., Sanna, M., Giussani, A., Chiodini, M. E., Fumagalli, M., Pilu, S. R., et al. (2014). Designing a high-yielding maize ideotype for a changing climate in Lombardy plain (northern Italy). Science of The Total Environment, 499, 497–509.
Abstract: The expected climate change will affect the maize yields in view of air temperature increase and scarce water availability. The application of biophysical models offers the chance to design a drought-resistant ideotype and to assist plant breeders and agronomists in the assessment of its suitability in future scenarios. The aim of the present work was to perform a model-based estimation of the yields of two hybrids, current vs ideotype, under future climate scenarios (2030-2060 and 2070-2100) in Lombardy (northern Italy), testing two options of irrigation (small amount at fixed dates vs optimal water supply), nitrogen (N) fertilization (300 vs 400 kg N ha(-1)), and crop cycle durations (current vs extended). For the designing of the ideotype we set several parameters of the ARMOSA process-based crop model: the root elongation rate and maximum depth, stomatal resistance, four stage-specific crop coefficients for the actual transpiration estimation, and drought tolerance factor. The work findings indicated that the current hybrid ensures good production only with high irrigation amount (245-565 mm y(-1)). With respect to the current hybrid, the ideotype will require less irrigation water (-13%, p<0.01) and it resulted in significantly higher yield under water stress condition (+15%, p<0.01) and optimal water supply (+2%, p<0.05). The elongated cycle has a positive effect on yield under any combination of options. Moreover, higher yields projected for the ideotype implicate more crop residues to be incorporated into the soil, which are positively correlated with the SOC sequestration and negatively with N leaching. The crop N uptake is expected to be adequate in view of higher rate of soil mineralization; the N fertilization rate of 400 kg N ha(-1) will involve significant increasing of grain yield, and it is expected to involve a higher rate of SOC sequestration.
|
Perego, A., Sanna, M., Bellocchi, G., & Acutis. (2014). Simulazione di flussi di carbonio da ecosistemi pratensi: applicazione del modello colturale ARMOSA al sito di Laqueuille (Francia)..
|
Ma, S., Acutis, M., Barcza, Z., Ben, T., H., Doro, L., Hidy, D., et al. (2014). The grassland model intercomparison of the MACSUR (Modelling European Agriculture with Climate Change for Food Security) European knowledge hub..
|