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Zhao, G.; Siebert, S.; Enders, A.; Rezaei, E.E.; Yan, C.; Ewert, F. |
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Title |
Demand for multi-scale weather data for regional crop modeling |
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Journal Article |
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Year |
2015 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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Volume |
200 |
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Pages |
156-171 |
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Keywords |
multi-scale; spatial heterogeneity; spatial resolution; crop model; climate variability; climate-change scenarios; integrated assessment; large-scale; phenological development; agricultural systems; spatial-resolution; data aggregation; european-union; winter-wheat; input data |
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Abstract  |
A spatial resolution needs to be determined prior to using models to simulate crop yields at a regional scale, but a dilemma exists in compromising between different demands. A fine spatial resolution demands extensive computation load for input data assembly, model runs, and output analysis. A coarse spatial resolution could result in loss of spatial detail in variability. This paper studied the impact of spatial resolution, data aggregation and spatial heterogeneity of weather data on simulations of crop yields, thus providing guidelines for choosing a proper spatial resolution for simulations of crop yields at regional scale. Using a process-based crop model SIMPLACE (LINTUL2) and daily weather data at 1 km resolution we simulated a continuous rainfed winter wheat cropping system at the national scale of Germany. Then we aggregated the weather data to four resolutions from 10 to 100 km, repeated the simulation, compared them with the 1 km results, and correlated the difference with the intra-pixel heterogeneity quantified by an ensemble of four semivariogram models. Aggregation of weather data had small effects over regions with a flat terrain located in northern Germany, but large effects over southern regions with a complex topography. The spatial distribution of yield bias at different spatial resolutions was consistent with the intra-pixel spatial heterogeneity of the terrain and a log-log linear relationship between them was established. By using this relationship we demonstrated the way to optimize the model resolution to minimize both the number of simulation runs and the expected loss of spatial detail in variability due to aggregation effects. We concluded that a high spatial resolution is desired for regions with high spatial environmental heterogeneity, and vice versa. This calls for the development of multi-scale approaches in regional and global crop modeling. The obtained results require substantiation for other production situations, crops, output variables and for different crop models. (C) 2014 Elsevier B.V. All rights reserved. |
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0168-1923 |
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CropM, ft_macsur |
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MA @ admin @ |
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4753 |
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Author |
Hoveid, Ø. |
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Title |
An economist’s wish list for soil and crop modelling |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-25 |
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A requirement for successful integration of soil, crop and economic models is a relevant interface of the three. Economic farming models deal with choice of crops, crop management during growing season and stock management after harvest. With detailed daily weather information the state of the soil might be simulated so that a suitable sowing date can be estimated. Moreover with rational beliefs with respect to future crop prices, and with a crop model which responds to management, the management during the growing season might be optimized with respect to choice of cultivar, fertilization and irrigation. So far, as reflected by Müller and Robertson (2014), predictions of future crop yields according to crop models take only to small extent such farmer responses into account, and might therefore overestimate the responses of crop harvests to climate.Comparison of soil, crop and economic simulations with observed weather and crop outcomes might lead to estimation/calibration of unobserved parameters in all models. Such exercises need generic soil, crop and economic models which do not leave modelling outcomes to the crop modeller’s or economist’s discretion. 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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2140 |
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Wallach, D.; Rivington, M. |
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Identification and quantification of differences between models |
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Report |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C4.2.2 |
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A major goal of crop model inter-comparison is model improvement, and an important intermediate step toward that goal is understanding in some detail how models differ, and the consequences of those differences. This report is intended as a first attempt at describing possible techniques for relating differences between model outputs to specific aspects of the models. No Label |
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MA @ admin @ |
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2101 |
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Author |
Rötter, R.P.; Tao, F.; Höhn, J.G.; Palosuo, T. |
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Title |
Use of crop simulation modelling to aid ideotype design of future cereal cultivars |
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Journal Article |
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Year |
2015 |
Publication |
Journal of Experimental Botany |
Abbreviated Journal |
J. Experim. Bot. |
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Volume |
66 |
Issue |
12 |
Pages |
3463-3476 |
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Keywords |
Breeding/*methods; Climate Change; *Computer Simulation; Ecotype; Edible Grain/*growth & development; *Models, Theoretical; cereals; climate extremes; crop growth simulation; ensemble modelling; future cultivars; genetic modelling; ideotype breeding; model improvement; model-aided design |
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A major challenge of the 21st century is to achieve food supply security under a changing climate and roughly a doubling in food demand by 2050 compared to present, the majority of which needs to be met by the cereals wheat, rice, maize, and barley. Future harvests are expected to be especially threatened through increased frequency and severity of extreme events, such as heat waves and drought, that pose particular challenges to plant breeders and crop scientists. Process-based crop models developed for simulating interactions between genotype, environment, and management are widely applied to assess impacts of environmental change on crop yield potentials, phenology, water use, etc. During the last decades, crop simulation has become important for supporting plant breeding, in particular in designing ideotypes, i.e. ‘model plants’, for different crops and cultivation environments. In this review we (i) examine the main limitations of crop simulation modelling for supporting ideotype breeding, (ii) describe developments in cultivar traits in response to climate variations, and (iii) present examples of how crop simulation has supported evaluation and design of cereal cultivars for future conditions. An early success story for rice demonstrates the potential of crop simulation modelling for ideotype breeding. Combining conventional crop simulation with new breeding methods and genetic modelling holds promise to accelerate delivery of future cereal cultivars for different environments. Robustness of model-aided ideotype design can further be enhanced through continued improvements of simulation models to better capture effects of extremes and the use of multi-model ensembles. |
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2016-10-31 |
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0022-0957 1460-2431 |
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Review |
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CropM, ft_macsur |
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MA @ admin @ |
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4804 |
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Siczek, A.; Horn, R.; Lipiec, J.; Usowicz, B.; Łukowski, M. |
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Title |
Effects of soil deformation and surface mulching on soil physical properties and soybean response related to weather conditions |
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Journal Article |
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Year |
2015 |
Publication |
Soil and Tillage Research |
Abbreviated Journal |
Soil and Tillage Research |
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153 |
Issue |
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175-184 |
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straw mulch; soil temperature; soil matric potential; soil penetration resistance; soybean biomass; seed and protein yield; water productivity; bulk-density; management-practices; crop production; n-2 fixation; compaction; growth; nitrogen; yield; straw; temperature |
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A field experiment was conducted on Haplic Luvisol developed from loess to assess the effects of soil deformation and straw mulch on soil water status (matric potential), temperature, penetration resistance, soybean growth, seed yield and yield components including straw, protein and oil in 2006-2008. Water use efficiencies related to the amount of rainfall during the growing seasons were calculated for seeds and total above ground biomass. The soil deformation levels (main plots) comprised the following trials: non-compacted (NC, 0 tractor pass), moderately compacted (MC, 3 passes), and strongly compacted (SC, 5 passes). A uniform seedbed in all plots was prepared by harrowing before planting. The main plots included sub-plots without and with surface wheat straw mulch (0.5 kg m(-2)) and the corresponding trials were NC + M, MC + M, SC + M. The amount and distribution of rainfall during the growing season differed among the experimental years with extended drought at bloom-full seed (R2-R6) stages in 2006, good water supply in 2007, and alternative periods with relatively high and low rainfalls in 2008. The effect of soil deformation on matric potential was influenced by weather conditions, soybean growth phase, mulching and depth. The differences were greatest in 2007 and 2008 at R7-R8 growth stages. With increasing deformation level from NC to SC matric potential for 0-15 cm depth during these stages significantly decreased from -401 to -1184 kPa in 2007 and from -1154 to -1432 kPa in 2008. On mulched soil, the corresponding ranges were from -541 to -841 klpa and from -748 to -1386 kPa, respectively. In the dry summer 2006, the differences were smaller and less consistent. Irrespective of soil deformation level, mulching reduced soil temperature in most growth phases but most pronounced initially. Most yield components increased from NC to MC during the experiments which could be attributed to enhanced root water and nutrient uptake rates and decreased from MC to SC due to high soil strength that restrained root growth down to deeper depth. The yields of seeds, straw, protein and oil as well as water productivity of soybean seed and biomass were improved by mulching in 2007-2008. This improvement was more pronounced in 2007 when the mean yield of seeds, protein and oil were significantly greater by 16, 29 and 11%, respectively and was attributed to positive alterations in soil water retention. These results indicate the possibilities of improvement in soybean performance by identifying allowable amount of traffic and mulching practices at planting depending on weather fluctuations during the growing season. Since rainfall and air temperature distribution in 2007 are close to those averaged over a long period of time, the use of straw mulch may positively affect soybean performance and yields excluding anomalously dry years. The positive effect of straw mulch can be enhanced by moderate soil deformation combined with seedbed loosening before planting to avoid constraining effect of soil structure on crop establishment. (C) 2015 Elsevier B.V. All rights reserved. |
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0167-1987 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
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4732 |
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