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Author |
Klosterhalfen, A.; Herbst, M.; Weihermueller, L.; Graf, A.; Schmidt, M.; Stadler, A.; Schneider, K.; Subke, J.-A.; Huisman, J.A.; Vereecken, H. |
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Title |
Multi-site calibration and validation of a net ecosystem carbon exchange model for croplands |
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Journal Article |
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Year |
2017 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
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Volume |
363 |
Issue |
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Pages |
137-156 |
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Keywords |
AgroC; Soil respiration; Carbon balance; Winter wheat; Grassland; NEE; LOLIUM-PERENNE L; SOIL HETEROTROPHIC RESPIRATION; LAND-SURFACE MODELS; EDDY-COVARIANCE; WINTER-WHEAT; CARBOHYDRATE CONTENT; TURNOVER MODEL; ROTHC MODEL; ROOT RATIOS; CO2 EFFLUX |
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Abstract |
Croplands play an important role in the carbon budget of many regions. However, the estimation of their carbon balance remains difficult due to diversity and complexity of the processes involved. We report the coupling of a one-dimensional soil water, heat, and CO2 flux model (SOILCO2), a pool concept of soil carbon turnover (RothC), and a crop growth module (SUCROS) to predict the net ecosystem exchange (NEE) of carbon. The coupled model, further referred to as AgroC, was extended with routines for managed grassland as well as for root exudation and root decay. In a first step, the coupled model was applied to two winter wheat sites and one upland grassland site in Germany. The model was calibrated based on soil water content, soil temperature, biometric, and soil respiration measurements for each site, and validated in terms of hourly NEE measured with the eddy covariance technique. The overall model performance of AgroC was sufficient with a model efficiency above 0.78 and a correlation coefficient above 0.91 for NEE. In a second step, AgroC was optimized with eddy covariance NEE measurements to examine the effect of different objective functions, constraints, and data-transformations on estimated NEE. It was found that NEE showed a distinct sensitivity to the choice of objective function and the inclusion of soil respiration data in the optimization process. In particular, both positive and negative day- and nighttime fluxes were found to be sensitive to the selected optimization strategy. Additional consideration of soil respiration measurements improved the simulation of small positive fluxes remarkably. Even though the model performance of the selected optimization strategies did not diverge substantially, the resulting cumulative NEE over simulation time period differed substantially. Therefore, it is concluded that data transformations, definitions of objective functions, and data sources have to be considered cautiously when a terrestrial ecosystem model is used to determine NEE by means of eddy covariance measurements. (C) 2017 Elsevier B.V. All rights reserved. |
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2017-11-09 |
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0304-3800 |
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CropM, ft_MACSUR |
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MA @ admin @ |
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5216 |
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Author |
Yin, X.G.; Kersebaum, K.C.; Kollas, C.; Manevski, K.; Baby, S.; Beaudoin, N.; Ozturk, I.; Gaiser, T.; Wu, L.H.; Hoffmann, M.; Charfeddine, M.; Conradt, T.; Constantin, J.; Ewert, F.; de Cortazar-Atauri, I.G.; Giglio, L.; Hlavinka, P.; Hoffmann, H.; Launay, M.; Louarn, G.; Manderscheid, R.; Mary, B.; Mirschel, W.; Nende, C.; Pacholskin, A.; Palosuo, T.; Ripoche-Wachter, D.; Rotter, R.P.; Ruget, F.; Sharif, B.; Trnka, M.; Ventrella, D.; Weigel, H.J.; Olesen, J.E.; Yin, X.; Kersebaum, K.C.; Kollas, C.; Manevski, K.; Baby, S.; Beaudoin, N.; Ozturk, I.; Gaiser, T.; Wu, L.; Hoffmann, M.; Charfeddine, M.; Conradt, T.; Constantin, J.; Ewert, F.; de Cortazar-Atauri, I.G.; Giglio, L.; Hlavinka, P.; Hoffmann, H.; Launay, M.; Louarn, G.; Manderscheid, R.; Mary, B.; Mirschel, W.; Nende, C.; Pacholskin, A.; Palosuo, T.; Ripoche-Wachter, D.; Roetter, R.P.; Ruget, F.; Sharif, B.; Trnka, M.; Ventrella, D.; Weigel, H.-J.; Olesen, J.E. |
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Title |
Performance of process-based models for simulation of grain N in crop rotations across Europe |
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Journal Article |
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Year |
2017 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
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Volume |
154 |
Issue |
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Pages |
63-77 |
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Keywords |
Calibration, Crop model, Crop rotation, Grain N content, Model evaluation, Model initialization; Climate-Change; Winter-Wheat; Nitrogen-Fertilization; Agroecosystem; Models; Multimodel Ensembles; Yield Response; Use Efficiency; Soil-Moisture; Oilseed Rape; Elevated Co2 |
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Abstract |
The accurate estimation of crop grain nitrogen (N; N in grain yield) is crucial for optimizing agricultural N management, especially in crop rotations. In the present study, 12 process-based models were applied to simulate the grain N of i) seven crops in rotations, ii) across various pedo-climatic and agro-management conditions in Europe, under both continuous simulation and single year simulation, and for iv) two calibration levels, namely minimal and detailed calibration. Generally, the results showed that the accuracy of the simulations in predicting grain N increased under detailed calibration. The models performed better in predicting the grain N of winter wheat (Triticum aestivum L.), winter barley (Hordewn vulgare L.) and spring barley (Hordeum vulgare L.) compared to spring oat (Avena saliva L.), winter rye (Secale cereale L.), pea (Piswn sativum L.) and winter oilseed rape (Brassica napus L.). These differences are linked to the intensity of parameterization with better parameterized crops showing lower prediction errors. The model performance was influenced by N fertilization and irrigation treatments, and a majority of the predictions were more accurate under low N and rainfed treatments. Moreover, the multi-model mean provided better predictions of grain N compared to any individual model. In regard to the Individual models, DAISY, FASSET, HERMES, MONICA and STICS are suitable for predicting grain N of the main crops in typical European crop rotations, which all performed well in both continuous simulation and single year simulation. Our results show that both the model initialization and the cover crop effects in crop rotations should be considered in order to achieve good performance of continuous simulation. Furthermore, the choice of either continuous simulation or single year simulation should be guided by the simulation objectives (e.g. grain yield, grain N content or N dynamics), the crop sequence (inclusion of legumes) and treatments (rate and type of N fertilizer) included in crop rotations and the model formalism. |
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2017-06-12 |
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0308-521x |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4963 |
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Author |
Mittenzwei, K.; Persson, T.; Höglind, M.; Kværnø, S. |
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Title |
Combined effects of climate change and policy uncertainty on the agricultural sector in Norway |
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Journal Article |
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Year |
2017 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
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Volume |
153 |
Issue |
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Pages |
118-126 |
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Keywords |
Climate change; Norway; Agriculture; Policy uncertainty; Modelling; LINGRA; CSM-CERES-Wheat; DSSAT |
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Highlights • A framework to study climate and policy uncertainty in agriculture is presented. • Combining both sources of uncertainty has ambiguous effects on agriculture. • Uncertainty needs to be highlighted in modelling tools for policy analysis. Abstract Farmers are exposed to climate change and uncertainty about how that change will develop. As farm incomes, in Norway and elsewhere, greatly depend on government subsidies, the risk of a policy change constitutes an additional uncertainty source. Hence, climate and policy uncertainty could substantially impact agricultural production and farm income. However, these sources of uncertainty have, so far, rarely been combined in food production analyses. The aim of this study was to determine the effects of a combination of policy and climate uncertainty on agricultural production, land use, and social welfare in Norway. Output yield distributions of spring wheat and timothy, a major forage grass, from simulations with the weather-driven crop models, CSM-CERES-Wheat and, LINGRA, were processed in the a stochastic version Jordmod, a price-endogenous spatial economic sector model of the Norwegian agriculture. To account for potential effects of climate uncertainty within a given future greenhouse gas emission scenario on farm profitability, effects on conditions that represented the projected climate for 2050 under the emission scenario A1B from the 4th assessment report of the Intergovernmental Panel on Climate Change and four Global Climate Models (GCM) was investigated. The uncertainty about the level of payment rates at the time farmers make their management decisions was handled by varying the distribution of payment rates applied in the Jordmod model. These changes were based on the change in the overall level of agricultural support in the past. Three uncertainty scenarios were developed and tested: one with climate change uncertainty, another with payment rate uncertainty, and a third where both types of uncertainty were combined. The three scenarios were compared with results from a deterministic scenario where crop yields and payment rates were constant. Climate change resulted in on average 9% lower cereal production, unchanged grass production and more volatile crop yield as well as 4% higher farm incomes on average compared to the deterministic scenario. The scenario with a combination of climate change and policy uncertainty increased the mean farm income more than a scenario with only one source of uncertainty. On the other hand, land use and farm labour were negatively affected under these conditions compared to the deterministic case. Highlighting the potential influence of climate change and policy uncertainty on the performance of the farm sector our results underline the potential error in neglecting either of these two uncertainties in studies of agricultural production, land use and welfare. |
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0308521x |
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CropM, TradeM |
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MA @ admin @ |
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4986 |
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Author |
Siebert, S.; Webber, H.; Zhao, G.; Ewert, F.; Siebert, S.; Webber, H.; Zhao, G.; Ewert, F. |
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Title |
Heat stress is overestimated in climate impact studies for irrigated agriculture |
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Journal Article |
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Year |
2017 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
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12 |
Issue |
5 |
Pages |
054023 |
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Keywords |
heat stress; climate change impact assessment; irrigation; canopy temperature; CANOPY TEMPERATURE; WINTER-WHEAT; WATER-STRESS; CROP YIELDS; GROWTH; MAIZE; DROUGHT; UNCERTAINTY; ENVIRONMENT; PHENOLOGY |
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Climate change will increase the number and severity of heat waves, and is expected to negatively affect crop yields. Here we show for wheat and maize across Europe that heat stress is considerably reduced by irrigation due to surface cooling for both current and projected future climate. We demonstrate that crop heat stress impact assessments should be based on canopy temperature because simulations with air temperatures measured at standard weather stations cannot reproduce differences in crop heat stress between irrigated and rainfed conditions. Crop heat stress was overestimated on irrigated land when air temperature was used with errors becoming larger with projected climate change. Corresponding errors in mean crop yield calculated across Europe for baseline climate 1984-2013 of 0.2 Mg yr(-1) (2%) and 0.6 Mg yr(-1) (5%) for irrigated winter wheat and irrigated grain maize, respectively, would increase to up to 1.5 Mg yr (1) (16%) for irrigated winter wheat and 4.1 Mg yr (1) (39%) for irrigated grain maize, depending on the climate change projection/GCM combination considered. We conclude that climate change impact assessments for crop heat stress need to account explicitly for the impact of irrigation. |
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2017-06-22 |
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1748-9326 |
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CropM, ft_macsur |
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MA @ admin @ |
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5035 |
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Author |
Bai, H.; Tao, F. |
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Title |
Sustainable intensification options to improve yield potential and ecoefficiency for rice-wheat rotation system in China |
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Journal Article |
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Year |
2017 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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211 |
Issue |
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Pages |
89-105 |
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Keywords |
Adaptation; Agro-ecosystem; Climate smart agriculture; Impacts; Sustainable development; Yield gap; Past 3 Decades; Climate-Change; Winter-Wheat; Agricultural Systems; Cropping Systems; High-Temperature; Plain; Management; Cultivars; Maize |
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Agricultural production systems are facing the challenges of increasing food production while reducing environmental cost, particularly in China. To improve yield potential and eco-efficiency simultaneously for the rice-wheat rotation system in China, we investigated changes in potential yields and yield gaps based on the field experiment data from 1981 to 2009 at four representative agro-meteorological experiment stations, along with the Agricultural Production System Simulator (APSIM) rice-wheat model. We further optimized crop cultivar and sowing/transplanting date, and investigated crop yield, water and nitrogen use efficiency, and environment impact of the rice-wheat rotation system in response to water and nitrogen supply. We found that the yield gaps between potential yields and farmer’s yields were about 8101 kg/ha or 45.3% of the potential yield, which had been shrinking from 1981 to 2009. To improve yield potentials and eco-efficiency, the cultivars of rice and wheat that properly increase both radiation use efficiency and grain weight are promising. Rice cultivars breeding need to maintain the length of panicle development and reproductive phase. High-yielding wheat cultivars are characterized by medium vernalization sensitivity, low photoperiod sensitivity and short length of floral initiation phase. Proper shift in sowing date can alleviate the negative effect of climate risk. Intermittent irrigation scheme (irrigate until surface soil saturated when average water content of surface soil is < 50% of saturated water content) for rice, together with nitrogen application rate of 390-420 kg N/ha (180-210 kg N/ha for rice and 210 kg N/ha for wheat), is suggested for the rice-wheat rotation system to maintain high yield with high resource use efficiency. This suggested nitrogen application rates are lower than those currently used by many local farmers. Our findings are useful to improve yield potential and eco-efficiency for the rice-wheat rotation system in China. Furthermore, this study demonstrates an effective approach with crop modelling to design fanning system for sustainable intensification, which can be adapted to other farming systems and regions. |
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2017-08-28 |
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0378-4290 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
5174 |
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