| Records |
| Author |
Wu, L.; Whitmore, A.P.; Bellocchi, G. |
| Title |
Modelling the impact of environmental changes on grassland systems with SPACSYS |
Type |
Journal Article |
| Year |
2015 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
| Volume |
6 |
Issue  |
01 |
Pages |
37-39 |
| Keywords |
grassland production; dynamic simulation model; primary production; ecosystem respiration |
| Abstract |
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English |
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| ISSN |
2040-4700 2040-4719 |
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Article |
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| Notes |
CropM, LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4655 |
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| Author |
Sándor, R.; Ma, S.; Acutis, M.; Barcza, Z.; Ben Touhami, H.; Doro, L.; Hidy, D.; Köchy, M.; Lellei-Kovács, E.; Minet, J.; Perego, A.; Rolinski, S.; Ruget, F.; Seddaiu, G.; Wu, L.; Bellocchi, G. |
| Title |
Uncertainty in simulating biomass yield and carbon–water fluxes from grasslands under climate change |
Type |
Journal Article |
| Year |
2015 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
| Volume |
6 |
Issue |
01 |
Pages |
49-51 |
| Keywords |
grassland productivity; carbon balance; model simulation; uncertainty; sensitivity |
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English |
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Series Title |
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Series Issue |
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Edition |
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| ISSN |
2040-4700 |
ISBN |
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Article |
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Conference |
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| Notes |
CropM, LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4651 |
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| Author |
Hlavinka, P.; Trnka, M.; Kersebaum, K.C.; Cermák, P.; Pohanková, E.; Orság, M.; Pokorný, E.; Fischer, M.; Brtnický, M.; Žalud, Z. |
| Title |
Modelling of yields and soil nitrogen dynamics for crop rotations by HERMES under different climate and soil conditions in the Czech Republic |
Type |
Journal Article |
| Year |
2014 |
Publication |
Journal of Agricultural Science |
Abbreviated Journal |
J. Agric. Sci. |
| Volume |
152 |
Issue |
02 |
Pages |
188-204 |
| Keywords |
winter oilseed rape; spring barley; central-europe; growth; simulation; wheat; adaptation; impact; water; agriculture |
| Abstract |
The crop growth model HERMES was used to model crop rotation cycles at 12 experimental sites in the Czech Republic. A wide range of crops (spring and winter barley, winter wheat, maize, potatoes, sugar beet, winter rape, oats, alfalfa and grass), cultivated between 1981 and 2009 under various soil and climatic conditions, were included. The model was able to estimate the yields of field crop rotations at a reasonable level, with an index of agreement (IA) ranging from 0.82 to 0.96 for the calibration database (the median coefficient of determination (R-2) was 0.71), while IA for verification varied from 0.62 to 0.93 (median R-2 was 0.78). Grass yields were also estimated at a reasonable level of accuracy. The estimates were less accurate for the above-ground biomass at harvest (the medians for IA were 0.76 and 0.72 for calibration and verification, respectively, and analogous medians of R-2 were 0.50 and 0.49). The soil mineral nitrogen (N) content under the field crops was simulated with good precision, with the IA ranging from 0.49 to 0.74 for calibration and from 0.43 to 0.68 for verification. Generally, the soil mineral N was underestimated, and more accurate results were achieved at locations with intensive fertilization. Simulated yields, soil N, water and organic carbon (C) contents were compared with long-term field measurements at Ne. mc. ice, located within the fertile Moravian lowland. At this station, all of the observed parameters were reproduced with a reasonable level of accuracy. In the case of the organic C content, HERMES reproduced a decrease ranging from c. 85 to 77 tonnes (t)/ha (for the 0-0.3 m soil layer) between the years 1980 and 2007. In spite of its relatively simple approach and restricted input data, HERMES was proven to be robust across various conditions, which is a precondition for its future use for both theoretical and practical purposes. |
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English |
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0021-8596 1469-5146 |
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Article |
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Conference |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4626 |
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| Author |
Ventrella, D.; Giglio, L.; Charfeddine, M.; Dalla Marta, A. |
| Title |
Consumptive use of green and blue water for winter durum wheat cultivated in Southern Italy |
Type |
Journal Article |
| Year |
2015 |
Publication |
Italian Journal of Agrometeorology |
Abbreviated Journal |
Italian Journal of Agrometeorology |
| Volume |
20 |
Issue |
1 |
Pages |
33-44 |
| Keywords |
irrigation; water productivity; model simulation; climate change; climate-change scenarios; air co2 enrichment; impact; footprint; irrigation; simulation; yield; agriculture; variability; resources |
| Abstract |
In this study at the regional scale, the model DSSAT CERES-Wheat was applied in order to simulate the cultivation of winter durum wheat (WW) and to estimate the green water (GW) and the blue water (BW) through a dual-step approach (with and without supplemental irrigation). The model simulation covered a period of 30 years for three scenarios including a reference period and two future scenarios based on forecasted global average temperature increase of 2 and 5 degrees C. The GW and BW contribution for evapo transpiration requirement is presented and analyzed on a distributed scale related to the Puglia region (Southern Italy) characterized by high evaporative demand of the atmosphere. The GW component was dominant compared to BW, covering almost 90% of the ETc of WW Under a Baseline scenario the weight BW was 11%, slightly increased in the future scenarios. GW appeared dependent on the spatial and temporal distribution of rainfall during the crop cycle, and to the hydraulic characteristics of soil for each calculation unit. After considering the effects of climate change on irrigation requirement of WW we carried out an example of analysis in order to verify the economic benefit of supplemental irrigation for WW cultivation. The probability that irrigation generates a negative or zero income ranged between 55 and 60% and climate change did not impact the profitability of irrigation for WW as simulated for the economic and agro-pedoclimatic conditions of Puglia region considered in this study. |
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English |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4653 |
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| Author |
Ruiz-Ramos, M.; Rodriguez, A.; Dosio, A.; Goodess, C.M.; Harpham, C.; Minguez, M.I.; Sanchez, E. |
| Title |
Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century |
Type |
Journal Article |
| Year |
2016 |
Publication |
Climatic Change |
Abbreviated Journal |
Clim. Change |
| Volume |
134 |
Issue |
1-2 |
Pages |
283-297 |
| Keywords |
regional climate model; bias correction; weather generator; circulation model; simulations; temperature; precipitation; ensemble; uncertainty; extremes |
| Abstract |
Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management. |
| Address |
2016-10-31 |
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English |
Summary Language |
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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 |
0165-0009 |
ISBN |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4805 |
| Permanent link to this record |
