| Records |
| Author |
Angulo, C.; Gaiser, T.; Rötter, R.P.; Børgesen, C.D.; Hlavinka, P.; Trnka, M.; Ewert, F. |
| Title |
‘Fingerprints’ of four crop models as affected by soil input data aggregation |
Type |
Journal Article |
Year  |
2014 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
| Volume |
61 |
Issue |
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Pages |
35-48 |
| Keywords |
crop model; soil data; spatial resolution; yield distribution; aggregation; us great-plains; climate-change; integrated assessment; simulating wheat; yields; scale; productivity; uncertainty; variability; responses |
| Abstract |
• Systematic analysis of the influence of spatial soil data resolution on simulated regional yields and total growing season evapotranspiration. • The responses of four crop models of different complexity are compared. • Differences between models are larger than the effect of the chosen spatial soil data resolution. • Low influence of soil data resolution due to: high precipitation amount, methods for calculating water retention and method of data aggregation. The spatial variability of soil properties is an important driver of yield variability at both field and regional scale. Thus, when using crop growth simulation models, the choice of spatial resolution of soil input data might be key in order to accurately reproduce observed yield variability. In this study we used four crop models (SIMPLACE<LINTUL-SLIM>, DSSAT-CSM, EPIC and DAISY) differing in the detail of modeling above-ground biomass and yield as well as of modeling soil water dynamics, water uptake and drought effects on plants to simulate winter wheat in two (agro-climatologically and geo-morphologically) contrasting regions of the federal state of North-Rhine-Westphalia (Germany) for the period from 1995 to 2008. Three spatial resolutions of soil input data were taken into consideration, corresponding to the following map scales: 1:50 000, 1:300 000 and 1:1 000 000. The four crop models were run for water-limited production conditions and model results were evaluated in the form of frequency distributions, depicted by bean-plots. In both regions, soil data aggregation had very small influence on the shape and range of frequency distributions of simulated yield and simulated total growing season evapotranspiration for all models. Further analysis revealed that the small influence of spatial resolution of soil input data might be related to: (a) the high precipitation amount in the region which partly masked differences in soil characteristics for water holding capacity, (b) the loss of variability in hydraulic soil properties due to the methods applied to calculate water retention properties of the used soil profiles, and (c) the method of soil data aggregation. No characteristic “fingerprint” between sites, years and resolutions could be found for any of the models. Our results support earlier recommendation to evaluate model results on the basis of frequency distributions since these offer quick and better insight into the distribution of simulation results as compared to summary statistics only. Finally, our results support conclusions from other studies about the usefulness of considering a multi-model approach to quantify the uncertainty in simulated yields introduced by the crop growth simulation approach when exploring the effects of scaling for regional yield impact assessments. |
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English |
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| ISSN |
1161-0301 |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4511 |
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| Author |
Legarrea, S.; Velázquez, E.; Aguado, P.; Fereres, A.; Morales, I.; Rodríguez, D.; Del Estal, P.; Viñuela, E. |
| Title |
Effects of a photoselective greenhouse cover on the performance and host finding ability of Aphidius ervi in a lettuce crop |
Type |
Journal Article |
| Year |
2014 |
Publication |
BioControl |
Abbreviated Journal |
BioControl |
| Volume |
59 |
Issue |
3 |
Pages |
265-278 |
| Keywords |
aphidius ervi; macrosiphum euphorbiae; uv-absorbing net; parasitoid; sadie; spatial distribution; integrated pest-management; natural enemies; plastic films; mosaic-virus; insect pests; count data; pea aphid; uv; parasitoids; hymenoptera |
| Abstract |
In the search for a durable pest control management, biological control agents and photoselective covers are suitable candidates to be implemented in greenhouse crops. In this work, we studied the effects of a 50 mesh photoselective cover compared to a standard with similar characteristics but without UV-absorbing additives on the performance of Aphidius ervi Haliday (Hymenoptera: Braconidae), a widely used parasitoid to control aphids in vegetable crops. Four field experiments were conducted in La Poveda Experimental Farm (Central Spain) where a lettuce crop was grown during the years 2008-2010. Lettuce plants were infested by Macrosiphum euphorbiae (Thomas) (Hemiptera: Aphididae) and the parasitoid A. ervi was released and monitored throughout the crop cycle to evaluate any constraint in its performance produced by UV-absorbing nets. The ability of A. ervi to find and parasitize the host was not modified by the photoselective cover during the four seasons studied. Thus, we suggest that both strategies could be combined in the context of IPM in vegetable crops where this natural enemy is released. |
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English |
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1386-6141, 1573-8248 |
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Article |
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CropM |
Approved |
no |
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MA @ admin @ |
Serial |
4509 |
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| Author |
Elliott, J.; Deryng, D.; Müller, C.; Frieler, K.; Konzmann, M.; Gerten, D.; Glotter, M.; Flörke, M.; Wada, Y.; Best, N.; Eisner, S.; Fekete, B.M.; Folberth, C.; Foster, I.; Gosling, S.N.; Haddeland, I.; Khabarov, N.; Ludwig, F.; Masaki, Y.; Olin, S.; Rosenzweig, C.; Ruane, A.C.; Satoh, Y.; Schmid, E.; Stacke, T.; Tang, Q.; Wisser, D. |
| Title |
Constraints and potentials of future irrigation water availability on agricultural production under climate change |
Type |
Journal Article |
| Year |
2013 |
Publication |
Proceedings of the National Academy of Sciences of the United States of America |
Abbreviated Journal |
Proc. Natl. Acad. Sci. U. S. A. |
| Volume |
111 |
Issue |
9 |
Pages |
3239-3244 |
| Keywords |
Agricultural Irrigation/economics/*methods; Agriculture/economics/*methods; Carbon Dioxide/analysis; *Climate Change; Computer Simulation; Forecasting; *Models, Theoretical; Water Supply/*statistics & numerical data; adaptation; agriculture; hydrology; uncertainty |
| Abstract |
We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400-1,400 Pcal (8-24% of present-day total) when CO2 fertilization effects are accounted for or 1,400-2,600 Pcal (24-43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20-60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600-2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required. |
| Address |
2016-10-31 |
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English |
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0027-8424 1091-6490 |
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Article |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4790 |
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| Author |
Angulo, C.; Rötter, R.; Trnka, M.; Pirttioja, N.; Gaiser, T.; Hlavinka, P.; Ewert, F. |
| Title |
Characteristic ‘fingerprints’ of crop model responses to weather input data at different spatial resolutions |
Type |
Journal Article |
| Year |
2013 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
| Volume |
49 |
Issue |
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Pages |
104-114 |
| 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 |
| 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 |
ISBN |
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Article |
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| Notes |
CropM, ftnotmacsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4598 |
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| Author |
Nendel, C.; Wieland, R.; Mirschel, W.; Specka, X.; Guddat, C.; Kersebaum, K.C. |
| Title |
Simulating regional winter wheat yields using input data of different spatial resolution |
Type |
Journal Article |
| Year |
2013 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
| Volume |
145 |
Issue |
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Pages |
67-77 |
| 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 |
| Abstract |
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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English |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
0378-4290 |
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Article |
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CropM, ftnotmacsur |
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no |
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MA @ admin @ |
Serial |
4498 |
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