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Author |
Angulo, C.; Rötter, R.; Trnka, M.; Pirttioja, N.; Gaiser, T.; Hlavinka, P.; Ewert, F. |
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Title |
Characteristic ‘fingerprints’ of crop model responses to weather input data at different spatial resolutions |
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Journal Article |
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Year |
2013 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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Volume |
49 |
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Pages |
104-114 |
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Keywords |
crop model; weather data resolution; aggregation; yield distribution; climate-change scenarios; areal unit problem; simulation-model; winter-wheat; system model; impacts; europe; yield; productivity; precipitation |
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Abstract |
Crop growth simulation models are increasingly used for regionally assessing the effects of climate change and variability on crop yields. These models require spatially and temporally detailed, location-specific, environmental (weather and soil) and management data as inputs, which are often difficult to obtain consistently for larger regions. Aggregating the resolution of input data for crop model applications may increase the uncertainty of simulations to an extent that is not well understood. The present study aims to systematically analyse the effect of changes in the spatial resolution of weather input data on yields simulated by four crop models (LINTUL-SLIM, DSSAT-CSM, EPIC and WOFOST) which were utilized to test possible interactions between weather input data resolution and specific modelling approaches representing different degrees of complexity. The models were applied to simulate grain yield of spring barley in Finland for 12 years between 1994 and 2005 considering five spatial resolutions of daily weather data: weather station (point) and grid-based interpolated data at resolutions of 10 km x 10 km; 20 km x 20 km; 50 km x 50 km and 100 km x 100 km. Our results show that the differences between models were larger than the effect of the chosen spatial resolution of weather data for the considered years and region. When displaying model results graphically, each model exhibits a characteristic ‘fingerprint’ of simulated yield frequency distributions. These characteristic distributions in response to the inter-annual weather variability were independent of the spatial resolution of weather input data. Using one model (LINTUL-SLIM), we analysed how the aggregation strategy, i.e. aggregating model input versus model output data, influences the simulated yield frequency distribution. Results show that aggregating weather data has a smaller effect on the yield distribution than aggregating simulated yields which causes a deformation of the model fingerprint. We conclude that changes in the spatial resolution of weather input data introduce less uncertainty to the simulations than the use of different crop models but that more evaluation is required for other regions with a higher spatial heterogeneity in weather conditions, and for other input data related to soil and crop management to substantiate our findings. Our results provide further evidence to support other studies stressing the importance of using not just one, but different crop models in climate assessment studies. (C) 2013 Elsevier B.V. All rights reserved. |
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1161-0301 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4598 |
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Author |
Rusu, T.; Moraru, P.I.; Bogdan, I.; Pop, A.; Coste, C.; Marin, D.I.; Mihalache, M. |
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Title |
Impacts of climate change on agricultural technology management in the Transylvanian Plain, Romania |
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Journal Article |
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Year |
2013 |
Publication |
Scientific Papers, Series A. Agronomy |
Abbreviated Journal |
Scientific Papers, Series A. Agronomy |
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Lvi |
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113-118 |
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Keywords |
climate monitoring; agricultural technology management; Transylvanian Plain |
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Abstract |
The Transylvanian Plain, Romania is an important region for agronomic productivity. However, limited soils data and adoption of best management practices hinder land productivity. Soil temperatures of the Transylvanian Plain were evaluated using a set of twenty datalogging stations positioned throughout the plain. Each station stores electronic data of ground temperature on 3 different levels of depth (10, 30 and 50 cm), of soil humidity at a depth of 10 cm, of the air temperature at 1 meter and of precipitation. Monitoring the thermal and hydric regime of the area is essential in order to identify and implement sets of measures of adjustment to the impact of climatic changes. After analyzing the recorded data, thermic and hydric, in the Transylvanian Plain, we recommend as optimal sowing period, advancing those known in the literature, with 5 days for corn and soybeans, and maintaining the same optimum period for sunflower and sugar beet. Water requirements are provided in an optimum, of 58.8 to 62.1% for the spring weeding crops during the growing season, thus irrigation is necessary to ensure optimum production potential. The amount of biological active degrees registered in Transylvanian Plain shows the necessity to reconstruct crop zoning, known in the literature, for the analyzed crops: wheat, corn, soy, sunflower and sugar beet. |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4614 |
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Lorite, I.J.; García-Vila, M.; Santos, C.; Ruiz-Ramos, M.; Fereres, E. |
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Title |
AquaData and AquaGIS: Two computer utilities for temporal and spatial simulations of water-limited yield with AquaCrop |
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Journal Article |
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Year |
2013 |
Publication |
Computers and Electronics in Agriculture |
Abbreviated Journal |
Computers and Electronics in Agriculture |
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Volume |
96 |
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227-237 |
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Keywords |
software tool; aquacrop; crop simulation model; geographic information system; spatial aggregation; fao crop model; irrigation management; iberian peninsula; southern spain; climate models; impacts; program; europe; system |
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Abstract |
The crop simulation model AquaCrop, recently developed by FAO can be used for a wide range of purposes. However, in its present form, its use over large areas or for applications that require a large number of simulations runs (e.g., long-term analysis), is not practical without developing software to facilitate such applications. Two tools for managing the inputs and outputs of AquaCrop, named AquaData and AquaGIS, have been developed for this purpose and are presented here. Both software utilities have been programmed in Delphi v. 5 and in addition, AquaGIS requires the Geographic Information System (GIS) programming tool MapObjects. These utilities allow the efficient management of input and output files, along with a GIS module to develop spatial analysis and effect spatial visualization of the results, facilitating knowledge dissemination. A sample of application of the utilities is given here, as an AquaCrop simulation analysis of impact of climate change on wheat yield in Southern Spain, which requires extensive input data preparation and output processing. The use of AquaCrop without the two utilities would have required approximately 1000 h of work, while the utilization of AquaData and AquaGIS reduced that time by more than 99%. Furthermore, the use of GIS, made it possible to perform a spatial analysis of the results, thus providing a new option to extend the use of the AquaCrop model to scales requiring spatial and temporal analyses. (C) 2013 Elsevier B.V. All rights reserved. |
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0168-1699 |
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CropM |
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MA @ admin @ |
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4609 |
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Leclère, D.; Jayet, P.-A.; de Noblet-Ducoudré, N. |
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Title |
Farm-level Autonomous Adaptation of European Agricultural Supply to Climate Change |
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Journal Article |
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2013 |
Publication |
Ecological Economics |
Abbreviated Journal |
Ecol. Econ. |
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87 |
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1-14 |
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climate change; agriculture; europe; residual impact; autonomous adaptation; water use efficiency; modeling; land-use; integrated assessment; future scenarios; change impacts; model; vulnerability; performance; emissions; nitrogen; lessons |
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The impact of climate change on European agriculture is subject to a significant uncertainty, which reflects the intertwined nature of agriculture. This issue involves a large number of processes, ranging from field to global scales, which have not been fully integrated yet. In this study, we intend to help bridging this gap by quantifying the effect of farm-scale autonomous adaptations in response to changes in climate. To do so, we use a modelling framework coupling the STICS generic crop model to the AROPAj microeconomic model of European agricultural supply. This study provides a first estimate of the role of such adaptations, consistent at the European scale while detailed across European regions. Farm-scale autonomous adaptations significantly alter the impact of climate change over Europe, by widely alleviating negative impacts on crop yields and gross margins. They significantly increase European production levels. However, they also have an important and heterogeneous impact on irrigation water withdrawals, which exacerbate the differences in ambient atmospheric carbon dioxide concentrations among climate change scenarios. (c) 2012 Elsevier B.V. All rights reserved. |
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0921-8009 |
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TradeM |
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MA @ admin @ |
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4606 |
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Author |
Humblot, P.; Jayet, P.A.; Clerino, P.; Leconte-Demarsy, D.; Szopa, S.; Castell, J.F. |
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Title |
Assessment of ozone impacts on farming systems: a bio-economic modeling approach applied to the widely diverse French case |
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Journal Article |
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Year |
2013 |
Publication |
Ecological Economics |
Abbreviated Journal |
Ecol. Econ. |
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85 |
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50-58 |
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ozone; bio-economic modeling; agricultural production; land use; greenhouse gas; carbon sequestration; abatement costs; climate-change; crops; agriculture; eu; emissions; benefits; level |
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As a result of anthropogenic activities, ozone is produced in the surface atmosphere, causing direct damage to plants and reducing crop yields. By combining a biophysical crop model with an economic supply model we were able to predict and quantify this effect at a fine spatial resolution. We applied our approach to the very varied French case and showed that ozone has significant productivity and land-use effects. A comparison of moderate and high ozone scenarios for 2030 shows that wheat production may decrease by more than 30% and barley production may increase by more than 14% as surface ozone concentration increases. These variations are due to the direct effect of ozone on yields as well as to modifications in land use caused by a shift toward more ozone-resistant crops: our study predicts a 16% increase in the barley-growing area and an equal decrease in the wheat-growing area. Moreover, mean agricultural gross margin losses can go as high as 2.5% depending on the ozone scenario, and can reach 7% in some particularly affected regions. A rise in ozone concentration was also associated with a reduction of agricultural greenhouse gas emissions of about 2%, as a result of decreased use of nitrogen fertilizers. One noteworthy result was that major impacts, including changes in land use, do not necessarily occur in ozone high concentration zones, and may strongly depend on farm systems and their adaptation capability. Our study suggests that policy makers should view ozone pollution as a major potential threat to agricultural yields. (C) 2012 Elsevier B.V. All rights reserved. |
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0921-8009 |
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TradeM |
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MA @ admin @ |
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4604 |
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