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Korhonen, P., Palosuo, T., Höglind, M., Persson, T., van Oijen, M., Jego, G., et al. (2016). Intercomparison of models for simulating timothy yield in Northern countries. The multiple roles of grassland in the European bioeconomy. General Meeting of the European Grassland Federation, 26. Trondheim, Norway.
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Schäfer, A. S. (2014). Landwirtschaftliche Erträge und ihre ökonomischen Einflussfaktoren. B.Sc., B.Sc.. Bachelor's thesis, University of Bonn, Bonn.
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Högner, K. (2013). Improving the methodology for global agricultural water availability and identifying hot spots for potential dam sites in East-Africa. M.Sc., M.Sc.. Master's thesis, Potsdam Institute for Climate Impact Research, .
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Zhao, G., Hoffmann, H., Van Bussel, L., Enders, A., Specka, X., Sosa, C., et al. (2014). Weather data aggregation’s effects on simulation of cropping systems: a model, production system and crop comparison. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Interactions of climate, soil and management practices in cropping systems can be simulated at different scales to provide information for decision making. Low resolution simulation need less effort, but important details could be lost through data aggregation effects (DAEs). This paper aims to provide a general method to assess the DAEs on weather data and the simulation of cropping systems, and further investigate how the DAEs vary with changing crop models, crops, variables and production systems. A 30-year continuous cropping system was simulated for winter wheat and silage maize and potential, water-limited and water-nitrogen-limited production situations. Climate data of 1 km resolution and aggregations to resolutions of 10 to 100 km was used as input for the simulations. The data aggregation narrowed the variation of weather data and DAEs increased with increasingly coarser spatial resolution, causing the loss of hot spots in simulated results. Spatial patterns were similar across different resolutions. Consistent with DAEs on weather data, the DAEs on simulated yield (0 to 1.2 t ha-1 for winter wheat and 0 to 1.7 t ha-1 for silage maize), evapotranspiration (3 to 45 mm yr-1 for winter wheat and 4 to 40 mm yr-1 for silage maize), and water use efficiency (0.02 to 0.25 kg m-3 for winter wheat and 0.04 to 0.4 kg m-3 for silage maize), increased with coarser spatial resolution. Thus, if spatial information is needed for local management decisions, higher resolution is needed to adequately capture the spatial heterogeneity or hot spots in the region.
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Sinabel, F., & Brouwer, F. (2014). TradeM theme progress overview. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: TradeM is one theme of MACSUR and the major focus is on enhancing existing economic models and inspiring researchers to further develop and use models and tools. After establishing an inventory of models at the beginning of the project the next stage was used to prepare for the analysis in regional pilot studies. Case studies for three regions in Europe (North, Centre, South) are used to showcase the state of the art of agricultural modelling of climate change and food security in specific regional contexts and policy environments. In parallel efforts stakeholder participation processes are initiated, learning workshops and capacity building. Moreover, steps are to develop and test new concepts on economics for use in integrated assessment approaches dealing with risk and uncertainty.
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