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Bellocchi, G. |
Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Fuzzy-logic based multi-site crop model evaluation |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-5 |
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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 |
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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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MA @ admin @ |
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2120 |
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Ferrise, R.; Bindi, M.; Acutis, M.; Bellocchi, G. |
Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Fuzzy-logic based multi-site crop model evaluation in Europe |
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2016 |
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Berlin (Germany) |
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International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany |
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MA @ admin @ |
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4916 |
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Sanz-Cobena, A.; Sánchez-Martín, L.; García-Torres, L.; Vallejo, A. |
Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Gaseous emissions of N2O and NO and NO3 − leaching from urea applied with urease and nitrification inhibitors to a maize (Zea mays) crop |
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Journal Article |
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2012 |
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Agriculture, Ecosystems and Environment |
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Agric. Ecosyst. Environ. |
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149 |
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64-73 |
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Urease inhibitor; Nitrogen losses; Irrigation; Nitrification |
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Urea has become the predominant source of synthetic nitrogen (N) fertilizer used throughout the world. Among the various available mitigation tools, urease inhibitors like NBPT have the most potential to improve efficiency of urea by reducing N losses, mainly via ammonia volatilization. However, there is a lack of information on the effect of N-(n-butyl) thiophosphoric triamide (NBPT) on other N losses such as gaseous emissions of N2O and NO and NO3− leaching. A two-year field experiment using irrigated maize (Zea mays) crop was carried out under Mediterranean conditions to evaluate the effectiveness of urea coated with NBPT (0.4%, w/w) alone and with both NBPT and nitrification inhibitor dicyandiamide (DCD) (0.4 and 3%, w/w, respectively) to mitigate N2O–N, NO–N and NO3−–N losses. The different treatments of U, U+NBPT and U+NBPT+DCD were applied to the maize crop in 2009 and then in 2010. The 2010 maize crop followed a fallow period, during which the 2009 crop residues were incorporated into the soil. Two different irrigation regimes were followed each year. In 2009, irrigation was controlled for the first 2 weeks following urea fertilization; whereas, the 2010 crop period was characterized by increased irrigation in the same period. After each treatment application, measurements of the changes in soil mineral N, gaseous emissions of N2O and NO, nitrate leaching and biomass production were made. N2O emissions were effectively abated by NBPT and NBPT+DCD and were reduced by 54 and 24%, respectively, in 2009. A reduction in nitrification rate by the inhibitors was also observed during 2009. In 2010 cropping period, NBPT reduced N2O emissions by 4%; while the combination of NBPT and DCD treatment reduced N2O emission by 43%. Yield-scaled N2O emissions were reduced by 50 and 18% by NBPT and the mixture of NBPT+DCD, respectively, in 2009. Applying inhibitors did not have any significant effect on yield-scaled N2O emissions in the 2010 crop period. Total NO losses from urea were 2.25 kg NO–N ha−1 in the 2009 crop period and 5 times lower in the following year; this may provide an indicator of the prevalence of nitrification as the main process in the production of N2O in the 2009 maize crop. Most of the NO3− was lost within the fallow period (i.e. 92, 81 and 75% of the total NO3− leached for U, U+NBPT and U+NBPT+DCD, respectively), so the incorporation of crop residues was not as effective as expected at reducing these N losses. Our study suggests that the effectiveness of NBPT and combination of NBPT+DCD in reducing N losses from applied urea is influenced by management practices, such as irrigation, and climatic conditions. |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4593 |
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Köchy, M.; Banse, M.; Tiffin, R.; Ewert, F.; Rötter, R.; Van den Pol-van Dasselaar, A.; Brouwer, F.; Sinabell, F.; Jorgenson, J.; Sætnan, E.; Kipling, R. |
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General outline of plans for an extension phase of MACSUR |
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2014 |
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FACCE MACSUR has indicated a possible extension of funding by two years until May 2017 (phase 2).For phase 2, hub and theme coordinators suggest the following main activities, that will be discussed during the remainder of the meeting and in the coming months.Evolution, upscaling, and transfer of knowledge gained in regional case studies.Assessment of additional scenarios of socio-economic and climate trends.Further development of an interdisciplinary scientific community.Extending scaling methods for crop models to the European and global scale.Intensification of feed quality and animal health modelling with climate change.Economic models from farm to global level capable of reflecting climate change. |
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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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MA @ admin @ |
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5084 |
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Cantelaube, P.; Jayet, P. |
Title ![sorted by Title field, ascending order (up)](img/sort_asc.gif) |
Geographical downscaling of outputs provided by an economic farm model calibrated at the regional level |
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Journal Article |
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2012 |
Publication |
Land Use Policy |
Abbreviated Journal |
Land Use Policy |
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29 |
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35-44 |
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Downscaling; Land use; Spatial statistics; Farm-groups; Farm Accountancy Data Network; FADN |
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There is a strong need for accurate and spatially referenced information regarding policy making and model linkage. This need has been expressed by land users, and policy and decision makers in order to estimate both spatially and locally the impacts of European policy (like the Common Agricultural Policy) and/or global changes on farm-groups. These entities are defined according to variables such as altitude, economic size and type of farming (referring to land uses). European farm-groups are provided through the Farm Accountancy Data Network (FADN) as statistical information delivered at regional level. The aim of the study is to map locally farm-group probabilities within each region. The mapping of the farm-groups is done in two steps: (1) by mapping locally the co-variables associated to the farm-groups, i.e. altitude and land uses; (2) by using regional FADN data as a priori knowledge for transforming land uses and altitude information into farm-groups location probabilities within each region. The downscaling process focuses on the land use mapping since land use data are originally point information located every 18 km. Interpolation of land use data is done at 100 m by using co-variables like land cover, altitude, climate and soil data which are continuous layers usually provided at fine resolution. Once the farm-groups are mapped, European Policy and global changes scenarios are run through an agro-economic model for assessing environmental impacts locally. |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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4582 |
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