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Seifried, A.; Sinabell, F.; Mitter, H.; E., S. |
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Analysing stochastic dominance of soybean and maize production in Austria |
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2014 |
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TradeM |
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Lebensmittelversorgung, Lebensmittelsicherheit und Ernährungssouveränität Food security, safety and sovereignty, 24. Jahrestagung der Österreichischen Gesellschaft für Agrarökonomie, Wien, 2014-09-25 to 2014-09-26 |
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MA @ admin @ |
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2816 |
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Kersebaum, K.C.; Boote, K.J.; Jorgenson, J.S.; Nendel, C.; Bindi, M.; Frühauf, C.; Gaiser, T.; Hoogenboom, G.; Kollas, C.; Olesen, J.E.; Rötter, R.P.; Ruget, F.; Thorburn, P.J.; Trnka, M.; Wegehenkel, M. |
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Title |
Analysis and classification of data sets for calibration and validation of agro-ecosystem models |
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Journal Article |
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2015 |
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Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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72 |
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402-417 |
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field experiments; data quality; crop modelling; data requirement; minimum data; software; different climatic zones; soil-moisture sensors; spatial variability; nitrogen dynamics; crop models; systems simulation; wheat yields; elevated co2; growth; field |
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Experimental field data are used at different levels of complexity to calibrate, validate and improve agroecosystem models to enhance their reliability for regional impact assessment. A methodological framework and software are presented to evaluate and classify data sets into four classes regarding their suitability for different modelling purposes. Weighting of inputs and variables for testing was set from the aspect of crop modelling. The software allows users to adjust weights according to their specific requirements. Background information is given for the variables with respect to their relevance for modelling and possible uncertainties. Examples are given for data sets of the different classes. The framework helps to assemble high quality data bases, to select data from data bases according to modellers requirements and gives guidelines to experimentalists for experimental design and decide on the most effective measurements to improve the usefulness of their data for modelling, statistical analysis and data assimilation. (C) 2015 Elsevier Ltd. All rights reserved. |
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English |
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1364-8152 |
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CropM, ft_macsur |
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MA @ admin @ |
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4563 |
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Kopacz, M.; Twardy, S. |
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Analysis of changes of permanent grasslands in the Carpathians based on the example of upper Dunajec and Raba river catchments |
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Report |
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2013 |
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Water-Environment-Rural Areas |
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133 |
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91-133 |
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CropM |
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ITP Falenty |
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MA @ admin @ |
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2072 |
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Author |
Schönhart, M. |
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Title |
Analysis of climate change adaptation with bio-economic farm models: lessons from MACSUR regional pilot studies |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-58 |
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Integrated land use models (ILM) featuring agronomic and economic drivers of land use are frequently applied to serve the high information demand of stakeholders. This presentation results from collaboration among bio-economic farm modelers across the MACSUR regional pilot studies (www.macsur.eu) and shall compare and finally reveal good practice examples on the representation of climate change adaptation in bio-economic farm models. First results show a considerable diversity of approaches employed in the MACSUR regional pilot studies. All are programming models that optimize more or less elaborated forms of utility. All consider or plan to consider crop yield impacts from bio-physical crop models based on daily-resolution climate data. While some models include pest and diseases or livestock impacts, none take climate change impacts on market prices or interactions among farms into account so far. Clearly, adaptation options determine the solution space and are mainly expert-based in the regional case studies. Overall, the models are normative and analyze economically rational and optimal land use and management at the farm level, capable of showing the likely direction of differences in future management as a response to exogenous parameter changes (prices, yields, disease pressure, changed policy conditions, etc.). Such detailed models and their results may be applied in stakeholder interaction. Integrating the different direct and indirect effects of climate change, including the policy dimension, is the main contribution of farm level modelling of agricultural systems in the domain of climate change adaptation research. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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no |
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MA @ admin @ |
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2173 |
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Author |
Kuzniar, A.; Kowalczyk, A.; Kostuch, M. |
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Title |
Analysis of criteria for determination of less favored areas in the mountains |
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Conference Article |
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2013 |
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CropM |
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Priorities of sustainable rural development 2014-2020 in the light of scientific research. Institute of Technology and Life Sciences at Falenty, Poland., 2013-04-25 to 2013-04-26 |
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MA @ admin @ |
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2581 |
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