Abstract
Process-based simulation models that predict crop growth, evapotranspiration, nitrate leaching or other environmental variables are commonly applied to assess their impact on agricultural crop production or the environment. Model inter-comparisons across a wide range of environments suggest that temperature relations are the most crucial for the success of individual models in capturing crop growth and yield formation at a specific site. For Siberia, where the annual temperature amplitude can easily exceed 80 K at some locations, temperature extremes are the most important challenge to the application of agro-ecosystem models. In this chapter, temperature-related algorithms of the dynamic simulation model MONICA are presented, including temperature dependencies of soil organic matter turn-over, plant photosynthesis and respiration, ontogenesis and the impacts of extremely high or low temperatures on crop growth. MONICA was developed to demonstrate the impact of the climate and management on crop yields and environmental variables on the plot scale and in smaller regions in Central Europe. Based on known biophysical processes, MONICA has the potential to assess the impacts of climate change and land management on crop yields, carbon balance and nitrogen efficiency in Siberia.
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Nendel, C. (2016). Simulating Temperature Impacts on Crop Production Using MONICA. In: Mueller, L., Sheudshen, A., Eulenstein, F. (eds) Novel Methods for Monitoring and Managing Land and Water Resources in Siberia. Springer Water. Springer, Cham. https://doi.org/10.1007/978-3-319-24409-9_22
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DOI: https://doi.org/10.1007/978-3-319-24409-9_22
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