Coucheney, E. (2015). Sensitivity of crop water and N stress to soil input data in regional cropyield simulations and the implications for data aggregation effects: a case study with the COUP-model (Vol. 5).
Abstract: The effects of aggregating soil input data on modelling crop yields at regional scale have been explored within the MACSUR- Crop M – WP3 scaling exercise for an ensemble of crop models 1. The models were run for the North Rhine-Westphalia region in Germany with an average climate time-series (30 years) and soil data at resolution 1 km to 100 km. Aggregation effects showed substantial differences between the models 1. This could be linked to differences in model structure and concepts and to different procedures for the parameterization of soil properties. A further analysis of the sensitivity of the outputs to key soil properties, for each ‘model – method of parameterization’, could help in understanding differences observed within the model ensemble. In this study, we explored the relationship between winter wheat yields, water and N-stress indexes and simple key-soil properties, based on the COUP-model 2 simulations. Soils were grouped into classes according to selected parameters (i.e. soil depth, soil texture and soil organic content). Preliminary results show that some of those soil classes are clearly associated with high water and / or N-stress and lower yields or with high inter-annual variation of the yield. As such they represent key factors explaining the spatial pattern of the simulated yield at the different resolutions. In addition we identified differences in the fractional area of those soil classes between high and low spatial resolutions (‘inherent errors’ due to data aggregation). How this may influence soil data aggregation effects on simulated yields will be further analyzed. No Label
|
Carter, T. (2015). Scenarios and related data for MACSUR2 Timothy Carter Finnish Environment (Vol. 5).
Abstract: Framing scenario selection (RCP/SSP)Ongoing scenario development in FP7 IMPRESSIONSSome examples of sources of data and scenarios No Label
|
Cortignani, R. (2015). Common Agricultural Policy and climate variability changes: an impact assessment of the first-pillar reform on an agricultural area of Grana Padano in different climate scenarios (Vol. 5).
Abstract: The reform of the Common Agricultural Policy it started in 2015 with several innovative aspects. Regarding the first pillar, such aspects are especially the convergence of the basic payments, the green payments and the coupled payments. In this regard seems interesting carry out analysis about to evaluate the policy impact considering the risks and opportunities due to climate change.In this study the impact of the convergence of basic payments, the introduction of the green payments and the coupled payments has been evaluated on dairy cattle farms in the Grana Padano area. The impact has been evaluated in different climate scenarios by economic, social and environmental indicators. The methodology used is the mathematical programming and especially a model of Discrete Stochastic Programming has been used to represents farms of the FADN database.The main results show that a significant part of the farms is affected by the diversification constraint that reduces the land devoted to corn silage. Farmers could cultivate corn silage after a principal crop (e.g. ryegrass) in order to avoid the diversification constraint, however, determining a negative impact on the use of environmental resources. To consider also that in the future there is an increase of corn silage yields with long cycle.Another result to underline is that which concerns the possibility of soybean cultivation in the ecological focus areas. In fact, considering the coupled payment provided for this crop, the ecological focus areas seem to be an important source of income for the farms.Finally, the analysis shows that the convergence of the basic payment will result in a reallocation of direct payments between farms with a significant impact on farm incomes. No Label
|
Bellocchi, G. (2015). Fuzzy-logic based multi-site crop model evaluation (Vol. 5).
Abstract: The most common way to evaluate simulation models is to quantify the agreement between observations and simulations via statistical metrics such as the root mean squared error and the linear regression coefficient of determination. It is agreed that the aggregation of metrics of different nature intro integrated indicators offers a valuable way to assess models. Expanded notions of model evaluation that have recently emerged, based on the trade-off between properties of the model and agreement between predictions and actual data under contrasting conditions, integrate sensitivity analysis measures and information criteria for model selection, as well as concepts of model robustness, and point to expert judgments to explore the importance of different metrics. As a FACCE MACSUR CropM-LiveM action, a composite indicator (MQIm: Model Quality Indicator for multi-site assessment) was elaborated, by a group of specialists, on metrics commonly used to evaluate crop models (with extension to grassland models) while also integrating aspects of model complexity and stability of performances. The indicator, based on fuzzy bounds applied to a set of weighed metrics, was first revised by a broader group of modellers and then assessed via questionnaire survey of scientists and end-users. We document a crop model evaluation in Europe and assess to what extent the MQIm reflects the main components of model quality and supports inferences about model performances. No Label
|
Köchy, M., Jorgenson, J., & Braunmiller, K. (2015). Overview of case studies (Vol. 6).
Abstract: MACSUR comprises 18 regional case studies for analysing the effects of climate change on agriculture with integrated inter-disciplinary models. Three case studies in Finland, Austria, and Italy have been selected as pilot studies because of their advancement in integration and representation of European farming systems and regions. No Label
|
