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Ewert, F.; Rötter, R.P.; Bindi, M.; Webber, H.; Trnka, M.; Kersebaum, K.C.; Olesen, J.E.; van Ittersum, M.K.; Janssen, S.; Rivington, M.; Semenov, M.A.; Wallach, D.; Porter, J.R.; Stewart, D.; Verhagen, J.; Gaiser, T.; Palosuo, T.; Tao, F.; Nendel, C.; Roggero, P.P.; Bartošová, L.; Asseng, S. |
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Title |
Crop modelling for integrated assessment of risk to food production from climate change |
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Journal Article |
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Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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Volume |
72 |
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Pages |
287-303 |
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Keywords |
uncertainty; scaling; integrated assessment; risk assessment; adaptation; crop models; agricultural land-use; change adaptation strategies; farming systems simulation; agri-environmental systems; enrichment face experiment; high-temperature stress; change impacts; nitrogen dynamics; atmospheric co2; spring wheat |
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Abstract  |
The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches. |
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1364-8152 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4521 |
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Author |
De Sanctis, G.; Roggero, P.P.; Seddaiu, G.; Orsini, R.; Porter, C.H.; Jones, J.W. |
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Title |
Long-term no tillage increased soil organic carbon content of rain-fed cereal systems in a Mediterranean area |
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Journal Article |
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Year |
2012 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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40 |
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18-27 |
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Keywords |
N fertilization; C dynamics; DSSAT; Wheat; Maize; Weed fallow; sandy loam soil; cropping systems; agricultural systems; climate-change; winter-wheat; sequestration; matter; model; fertilization; dynamics |
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Abstract |
The differential impact on soil organic carbon (SOC) of applying no tillage (NT) compared to conventional tillage (CT, i.e. mouldboard ploughing), along with three rates of nitrogen (N) fertilizer application (0,90 and 180 kg ha(-1) y(-1)), was studied under rain-fed Mediterranean conditions in a long-term experiment based on a durum wheat-maize rotation, in which crop residues were left on the soil (NT) or incorporated (CT). Observed SOC content following 8 and 12 years of continuous treatment application was significantly higher in the top 10 cm of the soil under NT than CT, but it was similar in the 10-40 cm layer. NT grain yields for both maize and durum wheat were below those attained under CT (on average 32% and 14% lower respectively) at a given rate of N fertilizer application. Soil, climate and crop data over 5 years were used to calibrate DSSAT model in order to simulate the impact of the different management practices over a 50-year period. Good agreement was obtained between observed and simulated values for crops grain yield, above-ground biomass and observed SOC values. Results from the simulations showed that under NT the weeds growing during the intercrop fallow period made a significant contribution to the observed SOC increase. When the contribution of the weed fallow was considered, NT significantly increased SOC in the top 40 cm of the soil at an average rate of 0.43, 0.31 and 0.03 t ha(-1) per year, respectively for 180,90 and 0 kg N ha(-1) year(-1), within the simulated 50 years. Under CT, a significant SOC increase was simulated under N180 and a significant decrease when no fertilizer was supplied. |
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1161-0301 |
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article |
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CropM |
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MA @ admin @ |
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4469 |
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Author |
Eitzinger, J.; Thaler, S.; Schmid, E.; Strauss, F.; Ferrise, R.; Moriondo, M.; Bindi, M.; Palosuo, T.; Rotter, R.; Kersebaum, K.C.; Olesen, J.E.; Patil, R.H.; Saylan, L.; Caldag, B.; Caylak, O. |
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Title |
Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria |
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Journal Article |
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Year |
2013 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
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151 |
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6 |
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813-835 |
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Keywords |
simulate yield response; climate-change scenarios; central-europe; nitrogen dynamics; high-temperature; future climate; elevated co2; soil; growth; variability |
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Abstract |
The objective of the present study was to compare the performance of seven different, widely applied crop models in predicting heat and drought stress effects. The study was part of a recent suite of model inter-comparisons initiated at European level and constitutes a component that has been lacking in the analysis of sources of uncertainties in crop models used to study the impacts of climate change. There was a specific focus on the sensitivity of models for winter wheat and maize to extreme weather conditions (heat and drought) during the short but critical period of 2 weeks after the start of flowering. Two locations in Austria, representing different agro-climatic zones and soil conditions, were included in the simulations over 2 years, 2003 and 2004, exhibiting contrasting weather conditions. In addition, soil management was modified at both sites by following either ploughing or minimum tillage. Since no comprehensive field experimental data sets were available, a relative comparison of simulated grain yields and soil moisture contents under defined weather scenarios with modified temperatures and precipitation was performed for a 2-week period after flowering. The results may help to reduce the uncertainty of simulated crop yields to extreme weather conditions through better understanding of the models’ behaviour. Although the crop models considered (DSSAT, EPIC, WOFOST, AQUACROP, FASSET, HERMES and CROPSYST) mostly showed similar trends in simulated grain yields for the different weather scenarios, it was obvious that heat and drought stress caused by changes in temperature and/or precipitation for a short period of 2 weeks resulted in different grain yields simulated by different models. The present study also revealed that the models responded differently to changes in soil tillage practices, which affected soil water storage capacity. |
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0021-8596 |
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CropM |
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MA @ admin @ |
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4601 |
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Author |
Jing, Q.; Bélanger, G.; Baron, V.; Bonesmo, H.; Virkajärvi, P. |
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Title |
Simulating the Nutritive Value of Timothy Summer Regrowth |
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Journal Article |
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Year |
2013 |
Publication |
Agronomy Journal |
Abbreviated Journal |
Agronomy Journal |
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105 |
Issue |
3 |
Pages |
563 |
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Keywords |
varying n nutrition; cation-anion difference; spring growth; swine manure; leaf-area; nitrogen; yield; model; digestibility; dynamics |
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Abstract |
The process-based grass model, CATIMO, simulates the spring growth and nutritive value of timothy (Phleum pratense L.), a forage species widely grown in Scandinavia and Canada, but the nutritive value of the summer regrowth has never been simulated. Our objective was to improve CATIMO for simulating the N concentration, neutral detergent fiber (NDF), in vitro digestibility of NDF (dNDF), and in vitro true digestibility of dry matter (IVTD) of summer regrowth. Daily changes in summer regrowth nutritive value were simulated by modifying key crop parameters that differed from spring growth. More specifically, the partitioning fraction to leaf blades was increased to increase the leaf-to-weight ratio, and daily changes in NDF and dNDF of leaf blades and stems were reduced. The modified CATIMO model was evaluated with data from four independent experiments in eastern and western Canada and Finland. The model performed better for eastern Canada than for the other locations, but the nutritive value attributes of the summer regrowth across locations (range of normalized RMSE = 8-25%, slope < 0.17, R-2 < 0.10) were not simulated as well as those of the spring growth (range of normalized RMSE = 4-16%, 0.85 < slope < 1.07, R-2 > 0.61). These modeling results highlight knowledge gaps in timothy summer regrowth and prospective research directions: improved knowledge of factors controlling the nutritive value of the timothy summer regrowth and experimental measurements of leaf-to-weight ratio and of the nutritive value of leaves and stems. |
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0002-1962 |
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CropM, LiveM |
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MA @ admin @ |
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4493 |
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Author |
Nendel, C.; Wieland, R.; Mirschel, W.; Specka, X.; Guddat, C.; Kersebaum, K.C. |
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Title |
Simulating regional winter wheat yields using input data of different spatial resolution |
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Journal Article |
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2013 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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145 |
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67-77 |
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Keywords |
monica; agro-ecosystem model; dynamic modelling; scaling; input data; climate-change; crop yield; nitrogen dynamics; food security; mineral nitrogen; soil-moisture; scaling-up; model; maize; water |
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The success of using agro-ecosystem models for the high-resolution simulation of agricultural yields for larger areas is often hampered by a lack of input data. We investigated the effect of different spatially resolved soil and weather data used as input for the MONICA model on its ability to reproduce winter wheat yields in the Federal State of Thuringia, Germany (16,172 km(2)). The combination of one representative soil and one weather station was insufficient to reproduce the observed mean yield of 6.66 +/- 0.87 t ha(-1) for the federal state. Use of a 100 m x 100 m grid of soil and relief information combined with just one representative weather station yielded a good estimator (7.01 +/- 1.47 t ha(-1)). The soil and relief data grid used in combination with weather information from 14 weather stations in a nearest neighbour approach produced even better results (6.60 +/- 1.37 t ha(-1)); the same grid used with 39 additional rain gauges and an interpolation algorithm that included an altitude correction of temperature data slightly overpredicted the observed mean (7.36 +/- 1.17 t ha(-1)). It was concluded that the apparent success of the first two high-resolution approaches over the latter was based on two effects that cancelled each other out: the calibration of MONICA to match high-yield experimental data and the growth-defining and -limiting effect of weather data that is not representative for large parts of the region. At the county and farm level the MONICA model failed to reproduce the 1992-2010 time series of yields, which is partly explained by the fact that many growth-reducing factors were not considered in the model. (C) 2013 Elsevier B.V. All rights reserved. |
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0378-4290 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4498 |
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