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Author |
Ventrella, D.; Giglio, L.; Charfeddine, M.; Dalla Marta, A. |
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Title |
Consumptive use of green and blue water for winter durum wheat cultivated in Southern Italy |
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Journal Article |
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Year |
2015 |
Publication |
Italian Journal of Agrometeorology |
Abbreviated Journal |
Italian Journal of Agrometeorology |
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Volume |
20 |
Issue |
1 |
Pages |
33-44 |
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Keywords |
irrigation; water productivity; model simulation; climate change; climate-change scenarios; air co2 enrichment; impact; footprint; irrigation; simulation; yield; agriculture; variability; resources |
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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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CropM, ft_macsur |
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MA @ admin @ |
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4653 |
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Rötter, R.P.; Palosuo, T.; Kersebaum, K.C.; Angulo, C.; Bindi, M.; Ewert, F.; Ferrise, R.; Hlavinka, P.; Moriondo, M.; Nendel, C.; Olesen, J.E.; Patil, R.H.; Ruget, F.; Takác, J.; Trnka, M. |
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Title |
Simulation of spring barley yield in different climatic zones of Northern and Central Europe: A comparison of nine crop models |
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Journal Article |
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Year |
2012 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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133 |
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23-36 |
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Keywords |
climate; crop growth simulation; model comparison; spring barley; yield variability; uncertainty; change impacts; nitrogen dynamics; high-temperature; soil-moisture; elevated co2; ceres-wheat; data set; growth; drought; sensitivity |
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In this study, the performance of nine widely used and accessible crop growth simulation models (APES-ACE, CROPSYST, DAISY, DSSAT-CERES, FASSET, HERMES, MONICA, STICS and WOFOST) was compared during 44 growing seasons of spring barley (Hordeum vulgare L) at seven sites in Northern and Central Europe. The aims of this model comparison were to examine how different process-based crop models perform at multiple sites across Europe when applied with minimal information for model calibration of spring barley at field scale, whether individual models perform better than the multi-model mean, and what the uncertainty ranges are in simulated grain yields. The reasons for differences among the models and how results for barley compare to winter wheat are discussed. Regarding yield estimation, best performing based on the root mean square error (RMSE) were models HERMES, MONICA and WOFOST with lowest values of 1124, 1282 and 1325 (kg ha(-1)), respectively. Applying the index of agreement (IA), models WOFOST, DAISY and HERMES scored best having highest values (0.632, 0.631 and 0.585, respectively). Most models systematically underestimated yields, whereby CROPSYST showed the highest deviation as indicated by the mean bias error (MBE) (-1159 kg ha(-1)). While the wide range of simulated yields across all sites and years shows the high uncertainties in model estimates with only restricted calibration, mean predictions from the nine models agreed well with observations. Results of this paper also show that models that were more accurate in predicting phenology were not necessarily the ones better estimating grain yields. Total above-ground biomass estimates often did not follow the patterns of grain yield estimates and, thus, harvest indices were also different. Estimates of soil moisture dynamics varied greatly. In comparison, even though the growing cycle for winter wheat is several months longer than for spring barley, using RMSE and IA as indicators, models performed slightly, but not significantly, better in predicting wheat yields. Errors in reproducing crop phenology were similar, which in conjunction with the shorter growth cycle of barley has higher effects on accuracy in yield prediction. (C) 2012 Elsevier B.V. All rights reserved. |
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2016-10-31 |
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0378-4290 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4803 |
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Siebert, S.; Ewert, F.; Rezaei, E.E.; Kage, H.; Grass, R. |
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Title |
Impact of heat stress on crop yield-on the importance of considering canopy temperature |
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Journal Article |
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2014 |
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Environmental Research Letters |
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Environ. Res. Lett. |
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9 |
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4 |
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Keywords |
heat stress; crop yield; temperature; soil moisture; modelling; wheat; rye; harvest index; wheat yields; climate-change; winter-wheat; grain number; extreme heat; maize; variability; irrigation; drought |
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Increasing crop productivity while simultaneously reducing the environmental footprint of crop production is considered a major challenge for the coming decades. Even short episodes of heat stress can reduce crop yield considerably causing low resource use efficiency. Studies on the impact of heat stress on crop yields over larger regions generally rely on temperatures measured by standard weather stations at 2 m height. Canopy temperatures measured in this study in field plots of rye were up to 7 degrees C higher than air temperature measured at typical weather station height with the differences in temperatures controlled by soil moisture contents. Relationships between heat stress and grain number derived from controlled environment studies were only confirmed under field conditions when canopy temperature was used to calculate stress thermal time. By using hourly mean temperatures measured by 78 weather stations located across Germany for the period 1994-2009 it is estimated, that mean yield declines in wheat due to heat stress during flowering were 0.7% when temperatures are measured at 2 m height, but yield declines increase to 22% for temperatures measured at the ground. These results suggest that canopy temperature should be simulated or estimated to reduce uncertainty in assessing heat stress impacts on crop yield. |
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2016-10-31 |
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1748-9326 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4814 |
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Persson, T.; Kværnø, S.; Höglind, M. |
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Impact of soil type extrapolation on timothy grass yield under baseline and future climate conditions in southeastern Norway |
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Journal Article |
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2015 |
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Climate Research |
Abbreviated Journal |
Clim. Res. |
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65 |
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71-86 |
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climate change scenarios; crop modelling; forage grass; lingra; soil properties; spatial variability; phleum pretense; poaceae; simulation-model; nutritive-value; systems simulation; catimo model; crop models; growth; nitrogen; scale; productivity; regrowth |
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Interactions between soil properties and climate affect forage grass productivity. Dynamic models, simulating crop performance as a function of environmental conditions, are valid for a specific location with given soil and weather conditions. Extrapolations of local soil properties to larger regions can help assess the requirement for soil input in regional yield estimations. Using the LINGRA model, we simulated the regional yield level and variability of timothy, a forage grass, in Akershus and Ostfold counties, Norway. Soils were grouped according to physical similarities according to 4 sets of criteria. This resulted in 66, 15, 5 and 1 groups of soils. The properties of the soil with the largest area was extrapolated to the other soils within each group and input to the simulations. All analyses were conducted for 100 yr of generated weather representing the period 1961-1990, and climate projections for the period 2046-2065, the Intergovernmental Panel on Climate Change greenhouse gas emission scenario A1B, and 4 global climate models. The simulated regional seasonal timothy yields were 5-13% lower on average and had higher inter-annual variability for the least detailed soil extrapolation than for the other soil extrapolations, across climates. There were up to 20% spatial intra-regional differences in simulated yield between soil extrapolations. The results indicate that, for conditions similar to these studied here, a few representative profiles are sufficient for simulations of average regional seasonal timothy yield. More spatially detailed yield analyses would benefit from more detailed soil input. |
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0936-577x 1616-1572 |
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CropM, ft_macsur |
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MA @ admin @ |
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4674 |
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Waha, K.; Müller, C.; Rolinski, S. |
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Separate and combined effects of temperature and precipitation change on maize yields in sub-Saharan Africa for mid- to late-21st century |
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Journal Article |
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2013 |
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Global and Planetary Change |
Abbreviated Journal |
Global and Planetary Change |
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106 |
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1-12 |
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climate change; wet season; water stress; temperature stress; hierarchical cluster analysis; global vegetation model; climate-change; southern africa; east-africa; part i; food; heat; agriculture; variability; impacts |
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Maize (Zea mays L) is one of the most important food crops and very common in all parts of sub-Saharan Africa. In 2010 53 million tons of maize were produced in sub-Saharan Africa on about one third of the total harvested cropland area (similar to 33 million ha). Our aim is to identify the limiting agroclimatic variable for maize growth and development in sub-Saharan Africa by analyzing the separated and combined effects of temperature and precipitation. Under changing climate, both climate variables are projected to change severely, and their impacts on crop yields are frequently assessed using process-based crop models. However it is often unclear which agroclimatic variable will have the strongest influence on crop growth and development under climate change and previous studies disagree over this question. We create synthetic climate data in order to study the effect of large changes in the length of the wet season and the amount of precipitation during the wet season both separately and in combination with changes in temperature. The dynamic global vegetation model for managed land LPJmL is used to simulate maize yields under current and future climatic conditions for the two 10-year periods 2056-2065 and 2081-2090 for three climate scenarios for the A1b emission scenario but without considering the beneficial CO2 fertilization effect. The importance of temperature and precipitation effects on maize yields varies spatially and we identify four groups of crop yield changes: regions with strong negative effects resulting from climate change (<-33% yield change), regions with moderate (-33% to -10% yield change) or slight negative effects (-10% to +6% yield change), and regions with positive effects arising from climate change mainly in currently temperature-limited high altitudes (>+6% yield change). In the first three groups temperature increases lead to maize yield reductions of 3 to 20%, with the exception of mountainous and thus cooler regions in South and East Africa. A reduction of the wet season precipitation causes decreases in maize yield of at least 30% and prevails over the effect of increased temperatures in southern parts of Mozambique and Zambia, the Sahel and parts of eastern Africa in the two projection periods. This knowledge about the limiting abiotic stress factor in each region will help to prioritize future research needs in modeling of agricultural systems as well as in drought and heat stress breeding programs and to identify adaption options in agricultural development projects. On the other hand the study enhances the understanding of temperature and water stress effects on crop yields in a global vegetation model in order to identify future research and model development needs. (C) 2013 Elsevier B.V. All rights reserved. |
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0921-8181 |
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CropM, ft_macsur |
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MA @ admin @ |
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4508 |
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