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Hjelkrem, A.-G.R.; Höglind, M.; van Oijen, M.; Schellberg, J.; Gaiser, T.; Ewert, F. |
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Title |
Sensitivity analysis and Bayesian calibration for testing robustness of the BASGRA model in different environments |
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Journal Article |
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Year |
2017 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
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359 |
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80-91 |
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Keywords |
Metropolis-hasting; Morris method; Reducing complexity; Robustness |
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Abstract |
Highlights • The parameters to be fixed were consistent across sites. • Model calibration must be performed separately for each specific case. • Possible to reduce model parameters from 66 to 45. • Strong model reductions must be avoided. • The error term for the training data were characterised by timing (phase shift). Abstract Proper parameterisation and quantification of model uncertainty are two essential tasks in improvement and assessment of model performance. Bayesian calibration is a method that combines both tasks by quantifying probability distributions for model parameters and outputs. However, the method is rarely applied to complex models because of its high computational demand when used with high-dimensional parameter spaces. We therefore combined Bayesian calibration with sensitivity analysis, using the screening method by Morris (1991), in order to reduce model complexity by fixing parameters to which model output was only weakly sensitive to a nominal value. Further, the robustness of the model with respect to reduction in the number of free parameters were examined according to model discrepancy and output uncertainty. The process-based grassland model BASGRA was examined in the present study on two sites in Norway and in Germany, for two grass species (Phleum pratense and Arrhenatherum elatius). According to this study, a reduction of free model parameters from 66 to 45 was possible. The sensitivity analysis showed that the parameters to be fixed were consistent across sites (which differed in climate and soil conditions), while model calibration had to be performed separately for each combination of site and species. The output uncertainty decreased slightly, but still covered the field observations of aboveground biomass. Considering the training data, the mean square error for both the 66 and the 45 parameter model was dominated by errors in timing (phase shift), whereas no general pattern was found in errors when using the validation data. Stronger model reduction should be avoided, as the error term increased and output uncertainty was underestimated. |
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0304-3800 |
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CropM, LiveM, ft_macsur |
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MA @ admin @ |
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5010 |
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Knox, J.; Daccache, A.; Hess, T.; Haro, D. |
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Title |
Meta-analysis of climate impacts and uncertainty on crop yields in Europe |
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Journal Article |
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Year |
2016 |
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Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
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11 |
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113004 |
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Future changes in temperature, rainfall and soil moisture could threaten agricultural land use and crop productivity in Europe, with major consequences for food security. We assessed the projected impacts of climate change on the yield of seven major crop types (viz wheat, barley, maize, potato, sugar beet, rice and rye) grown in Europe using a systematic review (SR) and meta-analysis of data reported in 41 original publications from an initial screening of 1748 studies. Our approach adopted an established SR procedure developed by the Centre for Evidence Based Conservation constrained by inclusion criteria and defined methods for literature searches, data extraction, meta-analysis and synthesis. Whilst similar studies exist to assess climate impacts on crop yield in Africa and South Asia, surprisingly, no comparable synthesis has been undertaken for Europe. Based on the reported results (n = 729) we show that the projected change in average yield in Europe for the seven crops by the 2050s is +8%. For wheat and sugar beet, average yield changes of +14% and +15% are projected, respectively. There were strong regional differences with crop impacts in northern Europe being higher (+14%) and more variable compared to central (+6%) and southern (+5) Europe. Maize is projected to suffer the largest negative mean change in southern Europe (−11%). Evidence of climate impacts on yield was extensive for wheat, maize, sugar beet and potato, but very limited for barley, rice and rye. The implications for supporting climate adaptation policy and informing climate impacts crop science research in Europe are discussed. |
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1748-9326 |
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CropM, TradeM, ft_macsur |
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MA @ admin @ |
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5011 |
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Mitter, H.; Schmid, E.; Sinabell, F. |
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Title |
Integrated modelling of protein crop production responses to climate change and agricultural policy scenarios in Austria |
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Journal Article |
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2015 |
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Climate Research |
Abbreviated Journal |
Clim. Res. |
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65 |
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205-220 |
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Climate change impact; Adaptation; Soybean; EPIC; Common Agricultural Policy; Land use |
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Climate and policy changes are likely to affect protein crop production and thus trade balances in Europe, which is highly dependent on imports. Exemplified for Austrian cropland, we developed an integrated modelling framework to analyze climate change and policy scenario impacts on protein crop production and environmental outcomes. The integrated modelling framework consists of a statistical climate change model, a crop rotation model, the bio-physical process model EPIC, and the economic bottom-up land use optimization model BiomAT. EPIC is applied to simulate annual dry matter crop yields for different crop management practices including crop rotations, fertilization intensities, and irrigation, as well as for 3 regional climate change scenarios until 2040 at a 1 km grid resolution. BiomAT maximizes total gross margins by optimizing land use choices and crop management practices subject to spatially explicit cropland endowments. The model results indicate that changes in agricultural policy conditions, cropland use, and higher flexibility in crop management practices may reduce protein import dependence under changing climatic conditions. Expanding protein crop production is most attractive in south-eastern Austria with its Central European continental climate where maize is most often replaced in crop rotations. However, the acreage of protein crops is limited by agronomically suitable cropland. An intended side effect is the reduction of nitrogen fertilizer inputs by about 0.1% if total protein crop production increases by 1%. |
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0936-577x |
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TradeM, ft_macsur |
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MA @ admin @ |
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5012 |
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Author |
Sinabell, F. |
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Wirtschaftliche Herausforderungen für die Landwirtschaft |
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2016 |
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5 |
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11-13 |
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Irdning-Donnersbachtal |
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Umweltökologisches Symposium. Landwirtschaft 2030 - Auswirkungen auf Boden, Wasser und Luft, 5. – 6. April 2016, Irdning-Donnersbachtal |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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5013 |
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Author |
Mitter, H.; Schönhart, M.; Meyer, I.; Mechtler, K.; Schmid, E.; Sinabell, F.; Bachner, G. |
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Title |
Agriculture |
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Book Chapter |
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2015 |
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121-144 |
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Vienna |
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Steininger, K.; König, M.; Bednar-Friedl, B.; Kranzl, L.; Loibl, W.; Prettenthaler, F. |
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Economic Evaluation of Climate Change Impacts. Development of a Cross-Sectoral Framework and Results for Austria |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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5014 |
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