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Zhao, G.; Hoffmann, H.; Van Bussel, L.; Enders, A.; Specka, X.; Sosa, C.; Yeluripati, J.; Tao, F.; Constantin, J.; Teixeira, E.; Grosz, B.; Doro, L.; Zhao, Z.; Nendel, C.; Raynal, H.; Eckersten, H.; Haas, E.; Kuhnert, M.; Lewan, E.; Bach, M.; Kersebaum, K.-C.; Roggero, P.P.; Rötter, R.; Wallach, D.; Krauss, G.; Siebert, S.; Gaiser, T.; Kiese, R.; Wang, E.; Ewert, F. |
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Title |
Weather data aggregation’s effects on simulation of cropping systems: a model, production system and crop comparison |
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2014 |
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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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FACCE MACSUR Mid-term Scientific Conference |
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3(S) Sassari, Italy |
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FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
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Call Number |
MA @ admin @ |
Serial |
5141 |
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Dirnböck, T.; Bezák, P.; Dullinger, S.; Haberl, H.; Lotze-Campen, H.; Mirtl, M.; Peterseil, J.; Redpath, S.; Singh, S.J.; Travis, J.; Wijdeven, S.M.J. |
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Title |
Critical Scales for Long-Term Socio-ecological Biodiversity Research |
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Book Chapter |
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Year |
2013 |
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123-138 |
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TradeM |
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Springer |
Place of Publication |
Dordrecht |
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Singh, S.J.; Haberl, H.; Chertow, M.; Mirtl, M.; Schmid, M. |
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Long Term Socio-Ecological Research |
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Human-environment interactions (2) |
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MA @ admin @ |
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2390 |
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Porter, J.R.; Soussana, J.-F.; Fereres, E.; Long, S.; Mohren, F.; Peltonen-Sainio, P.; von Braun, J. |
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Title |
European Perspectives: An Agronomic Science Plan for Food Security in a Changing Climate |
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Book Chapter |
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2012 |
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CropM |
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Co-Published With Imperial College Press |
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Hillel, D.; Rosenzweig, C. |
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Handbook of Climate Change and Agroecosystems: Global and Regional Aspects and Implications |
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ICP Series on Climate Change Impacts, Adaptation, |
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MA @ admin @ |
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2732 |
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Olesen, J.E.; Niemeyer, S.; Ceglar, A.; Roggero, P.-P.; Lehtonen, H.; Schönhart, M.; Kipling, R. |
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Section 5.3. Agriculture |
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Book Chapter |
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2017 |
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223-243 |
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European Environmental Agency |
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Copenhagen, Denmark |
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Climate change, impacts and vulnerability in Europe 2016. An indicator-based report |
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EEA Report (1/2017) |
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CropM, LiveM, TradeM |
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MA @ admin @ |
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4964 |
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Reidsma, P.; Bakker, M.M.; Kanellopoulos, A.; Alam, S.J.; Paas, W.; Kros, J.; W. de Vries, W. |
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Title |
Impacts of climate and socio-economic change at farm and landscape level in the Netherlands: climate smart agriculture |
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2015 |
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CropM |
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Climate-smart agriculture 2015. Global Science Conference. Montpellier, France, 2015-03-15 to 2015-03-18 |
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no |
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Call Number |
MA @ admin @ |
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2745 |
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