| Records |
| Author |
Gabaldón-Leal, C.; Lorite, I.J.; Mínguez, M.I.; Lizaso, J.I.; Dosio, A.; Sanchez, E.; Ruiz-Ramos, M. |
Title  |
Strategies for adapting maize to climate change and extreme temperatures in Andalusia, Spain |
Type |
Journal Article |
| Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
| Volume |
65 |
Issue |
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Pages |
159-173 |
| Keywords |
climate change; impact; adaptation; maize; crop model; regional climate model; extreme temperature; elevated carbon-dioxide; iberian peninsula; future climate; mediterranean environment; crop productivity; model simulations; pollen viability; european climate; bias correction; change impacts |
| Abstract |
Climate projections indicate that rising temperatures will affect summer crops in the southern Iberian Peninsula. The aim of this study was to obtain projections of the impacts of rising temperatures, and of higher frequency of extreme events on irrigated maize, and to evaluate some adaptation strategies. The study was conducted at several locations in Andalusia using the CERES-Maize crop model, previously calibrated/validated with local experimental datasets. The simulated climate consisted of projections from regional climate models from the ENSEMBLES project; these were corrected for daily temperature and precipitation with regard to the E-OBS observational dataset. These bias-corrected projections were used with the CERES-Maize model to generate future impacts. Crop model results showed a decrease in maize yield by the end of the 21st century from 6 to 20%, a decrease of up to 25% in irrigation water requirements, and an increase in irrigation water productivity of up to 22%, due to earlier maturity dates and stomatal closure caused by CO2 increase. When adaptation strategies combining earlier sowing dates and cultivar changes were considered, impacts were compensated, and maize yield increased up to 14%, compared with the baseline period (1981-2010), with similar reductions in crop irrigation water requirements. Effects of extreme maximum temperatures rose to 40% at the end of the 21st century, compared with the baseline. Adaptation resulted in an overall reduction in extreme T-max damages in all locations, with the exception of Granada, where losses were limited to 8%. |
| Address |
2016-06-01 |
| Corporate Author |
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Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0936-577x 1616-1572 |
ISBN |
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Medium |
Article |
| Area |
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Expedition |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4738 |
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| Author |
Murat, M.; Malinowska, I.; Hoffmann, H.; Baranowski, P. |
| Title |
Statistical modelling of agrometeorological time series by exponential smoothing |
Type |
Journal Article |
| Year |
2016 |
Publication |
International Agrophysics |
Abbreviated Journal |
International Agrophysics |
| Volume |
30 |
Issue |
1 |
Pages |
57-65 |
| Keywords |
exponential smoothing; meteorological time series; statistical forecasting; daily temperature records; weighted moving averages; climate-change; prediction; forecasts; state; weather |
| Abstract |
Meteorological time series are used in modelling agrophysical processes of the soil-plant-atmosphere system which determine plant growth and yield. Additionally, longterm meteorological series are used in climate change scenarios. Such studies often require forecasting or projection of meteorological variables, eg the projection of occurrence of the extreme events. The aim of the article was to determine the most suitable exponential smoothing models to generate forecast using data on air temperature, wind speed, and precipitation time series in Jokioinen (Finland), Dikopshof (Germany), Lleida (Spain), and Lublin (Poland). These series exhibit regular additive seasonality or non-seasonality without any trend, which is confirmed by their autocorrelation functions and partial autocorrelation functions. The most suitable models were indicated by the smallest mean absolute error and the smallest root mean squared error. |
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Place of Publication |
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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 |
0236-8722 |
ISBN |
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Medium |
Article |
| Area |
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Expedition |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4728 |
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| Author |
van Bussel, L.G.J.; Ewert, F.; Zhao, G.; Hoffmann, H.; Enders, A.; Wallach, D.; Asseng, S.; Baigorria, G.A.; Basso, B.; Biernath, C.; Cammarano, D.; Chryssanthacopoulos, J.; Constantin, J.; Elliott, J.; Glotter, M.; Heinlein, F.; Kersebaum, K.-C.; Klein, C.; Nendel, C.; Priesack, E.; Raynal, H.; Romero, C.C.; Rötter, R.P.; Specka, X.; Tao, F. |
| Title |
Spatial sampling of weather data for regional crop yield simulations |
Type |
Journal Article |
| Year |
2016 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
| Volume |
220 |
Issue |
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Pages |
101-115 |
| Keywords |
Regional crop simulations; Winter wheat; Upscaling; Stratified sampling; Yield estimates; climate-change scenarios; water availability; growth simulation; potential impact; food-production; winter-wheat; model; resolution; systems; soil |
| Abstract |
Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50,100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management data for regional simulations of crop yields is still needed. |
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Thesis |
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Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0168-1923 |
ISBN |
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Medium |
Article |
| Area |
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Expedition |
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Conference |
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| Notes |
CropM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4673 |
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| Author |
Mitter, H.; Heumesser, C.; Schmid, E. |
| Title |
Spatial modeling of robust crop production portfolios to assess agricultural vulnerability and adaptation to climate change |
Type |
Journal Article |
| Year |
2015 |
Publication |
Land Use Policy |
Abbreviated Journal |
Land Use Policy |
| Volume |
46 |
Issue |
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Pages |
75-90 |
| Keywords |
climate change impact; adaptation; agricultural vulnerability; portfolio optimization; agricultural policy; agri-environmental payment; adaptive capacity; change impacts; risk-aversion; land-use; ecosystem services; change scenarios; europe; policy; future; water |
| Abstract |
Agricultural vulnerability to climate change is likely to vary considerably between agro-environmental regions. Exemplified on Austrian cropland, we aim at (i) quantifying climate change impacts on agricultural vulnerability which is approximated by the indicators crop yields and gross margins, (ii) developing robust crop production portfolios for adaptation, and (iii) analyzing the effect of agricultural policies and risk aversion on the choice of crop production portfolios. We have employed a spatially explicit, integrated framework to assess agricultural vulnerability and adaptation. It combines a statistical climate change model for Austria and the period 2010-2040, a crop rotation model, the bio-physical process model EPIC (Environmental Policy Integrated Climate), and a portfolio optimization model. We find that under climate change, crop production portfolios include higher shares of intensive crop management practices, increasing average crop yields by 2-15% and expected gross margins by 3-18%, respectively. The results depend on the choice of adaptation measures and on the level of risk aversion and vary by region. In the semi-arid eastern parts of Austria, average dry matter crop yields are lower but gross margins are higher than in western Austria due to bio-physical and agronomic heterogeneities. An abolishment of decoupled farm payments and a threefold increase in agri-environmental premiums would reduce nitrogen inputs by 23-33%, but also crop yields and gross margins by 18-37%, on average. From a policy perspective, a twofold increase in agri-environmental premiums could effectively reduce the trade-offs between crop production and environmental impacts. (C) 2015 Elsevier Ltd. All rights reserved. |
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Thesis |
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Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0264-8377 |
ISBN |
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Medium |
Article |
| Area |
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Expedition |
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Conference |
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| Notes |
TradeM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4675 |
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| Author |
Wolf, J.; Ouattara, K.; Supit, I. |
| Title |
Sowing rules for estimating rainfed yield potential of sorghum and maize in Burkina Faso |
Type |
Journal Article |
| Year |
2015 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
| Volume |
214-215 |
Issue |
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Pages |
208-218 |
| Keywords |
crop modelling; maize; sorghum; sowing; WOFOST; yield potential; semiarid west-africa; pearl-millet cultivation; soil organic-matter; climate-change; planting dates; crop model; variability; water; adaptation; tillage |
| Abstract |
To reduce the dependence on local expert knowledge, which is important for large-scale crop modelling studies, we analyzed sowing dates and rules for maize (Zea mays L.) and sorghum (Sorghum bicolor (L)) at three locations in Burkina Faso with strongly decreasing rainfall amounts from south to north. We tested in total 22 methods to derive optimal sowing dates that result in highest water-limited yields and lowest yield variation in a reproducible and objective way. The WOFOST crop growth simulation model was used. We found that sowing dates that are based on local expert knowledge, may work quite well for Burkina Faso and for West Africa in general. However, when no a priori information is available, maize should be sown between Julian days 160 and 200, with application of the following criteria: (a) cumulative rainfall in the sowing window is >= 3 cm or available soil moisture content is >2 cm in the moderately dry central part of Burkina Faso, (b) cumulative rainfall in this period is >= 2 cm or available soil moisture content is >1 cm in the more humid regions in the southern part of Burkina Faso. Sorghum should also be sown between Julian days 160 and 200 with application of the following criteria: (a) in the dry northern part of Burkina Faso the long duration sorghum variety should be sown when cumulative rainfall is >2 cm in the sowing window, and the short duration sorghum variety should be sown later when cumulative rainfall is >= 3 cm, (b) in central Burkina Faso sowing should start when cumulative rainfall in this period is >= 2 cm or when available soil moisture content is >1 cm. Sowing date rules are shown to be generally crop and location specific and are not generic for West Africa. However, the required precision of the sowing rules appears to rapidly decrease with increasing duration and intensity of the rainy season. Sowing delay as a result of, for example, labour constraints, has a disastrous effect on rainfed maize and sorghum yields, particularly in the northern part of West Africa with low rainfall. Optimization of sowing dates can also be done by simulating crop yields in a time window of two months around a predefined sowing date. Using these optimized dates appears to result in a good estimate of the maximal mean rainfed yield level. (C) 2015 Elsevier B.V. All rights reserved. |
| Address |
2015-10-12 |
| Corporate Author |
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Thesis |
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Place of Publication |
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Editor |
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| Language |
English |
Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0168-1923 |
ISBN |
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Medium |
Article |
| Area |
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Expedition |
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Conference |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4702 |
| Permanent link to this record |
