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Pohanková, E., Hlavinka, P., Kersebaum, K. C., Dubrovský, M., Fischer, M., Balek, J., et al. (2015). Pilot study: Field crop rotations modeling under present and future conditions in the Czech Republic using HERMES model (Vol. 5).
Abstract: The aim of this study is to compare the water and organic material balance, yields and other aspects estimated within crop rotations by the Hermes crop model for present and future climatic conditions in the Czech Republic. Moreover, this is a pilot study for the complex and continuous crop rotations modeling (using both single crop models and ensembles) in connection with transient climate change scenarios. For this purpose, three locations representing important agricultural regions of the Czech Republic (with different climatic conditions) were selected. The crop rotation (including spring barley, silage maize, winter wheat, winter rape, and winter wheat in the listed order) was simulated from 1981-2080. The period 1981-2010 was covered by measured meteorological data, and the period 2011-2080 was represented by a transient synthetic weather series from the weather generator M&Rfi. The generated data was based on five circulation models representing an ensemble of 18 CMIP3 global circulation models to preserve to a large degree the uncertainty of the original ensemble. Two types of crop management were compared, and the influences of soil quality, increasing atmospheric CO2 and magnitude of adaptation measure (in the form of sowing date changes) were also considered. According to the results, if a “dry” scenario (such as GFCM21) would occur, then all the C3 crops produced in drier regions would be devastated in a significant number of seasons; for example, by the 2070s, up to 19.5%, 21.5% and 47.0% of seasons with winter rape, spring barley and winter wheat, respectively, would have a yield level below 50% of the present yield. Negative impacts are likely even on premium-quality soils regardless of the use of a flexible sowing date and accounting for increasing CO2 concentrations. Moreover, in some cases, the use of catch crops can have negative impacts, exacerbating the soil water deficit for the subsequent crops. This study (submitted to Climate Research journal) will be used as a pilot for subsequent activities. In this area, following calculations (the same set of stations and updated climate scenarios) using growth models ensemble (currently includes 12 modeling approaches) started to estimate uncertainty aspects. Consequently, the analysis within wider range of conditions (across continents) and farming methods will be conducted. No Label
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Zimmermann, A. (2015). Crop yield trends and variability in the EU (Vol. 5).
Abstract: Agreeing that increased future global food demand will have to be met by production intensification rather than land use expansion (e.g. Hertel, 2011), scientists have moved to empirically analyse the causes for differences between potentially attainable yields and actually realized yields – the yield gap (e.g. van Ittersum et al., 2013, Neumann et al., 2010). In the long run, we aim at disentangling the effects of biophysical, economic and political impacts and farmers’ response to them on crop yields by analysing yield gaps at regional scale in the European Union. Apart from generally improving our understanding of yield gaps and their drivers in the EU, our analysis will contribute to the integration of economic and biophysical models at a later stage of our research. As a first step towards an advanced yield gap analysis, the current paper will give an overview of yield developments in the EU27. The overview will be based on regional yield trend and yield variability estimates derived from socioeconomic panel data from the Farm Accountancy Data Network (FADN). The analysis will continue and extend the work of Ewert et al. (2005) and Reidsma et al. (2009) in terms of drawing on single farm instead of country level/farm type data, including the new EU member states and most recent years (until 2011). The EU-wide analysis of yield trends and variability will serve as a basis for the later analysis of yield gaps. No Label
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Zander, P. (2015). Scenarios of regional agricultural land use under climate change for 4 case study regions in Northern Germany (Vol. 5).
Abstract: Agricultural land use in Northern Germany is characterized by a gradient of decreasing precipitation from west to east. Climate change is expected to increase temperature and decrease summer precipitation. In the context of a nationally funded project we aim to analyze climate change adaptation strategies for agricultural land use. The research is focused in 4 study regions from Eastern to Western Germany. The presented modelling approach analyses agricultural land use under climate change and for three policy scenarios (business as usual, biodiversity and climate protection). The biodiversity and climate protection scenarios each reserve area for specific scenario objectives: 10% for specific biodiversity measures and 20% for N-fixing legumes in case of the climate protection scenario. All scenarios are executed for three time steps representing year 2010, 2020 and 2030 with a constant yield increase, extrapolated from past observations. Building on IACS data for a farm typology and expert assessments of current and future land use options, we applied a linear programming farm model. Prices are exogenous and derived from CAPRI model runs for 2020 and 2030. First preliminary results show strong impacts of price assumptions and yield assessments. This results in 2020 in lower gross margins for a number of crops and finally to higher set aside areas in eastern Germany. For 2030 input–output price relations are more favourable for farmers and thus lead to lower set aside areas. No Label
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Yin, X. (2015). Effects of climatic factors, drought risk and irrigation requirement on maize yield in the northeast farming region of China over 1961 to 2010 (Vol. 5).
Abstract: The Northeast Farming Region (NFR) is the most important and the largest rain-fed maize production region in China, accounting for 30% of China’s maize. We investigated the effects of climatic factors, drought risk and irrigation requirement on maize yield in different maize growth phases during 1961 to 2010 using a statistical analysis of observed yield from 44 stations in NFR. We divided the maize growing season into four growth phases, comprising seeding, vegetative, flowering and maturity. The dual crop coefficient was used to calculate crop evapotranspiration and soil water balance during the maize growing season. The effects of mean temperature, radiation, effective rainfall, water deficit, drought stress days, actual crop evapotranspiration (ETa) and irrigation requirement in different growth phases were included in the statistical model to predict maize yield. During the period 1961 to 2010, mean temperature increased significantly in all growth phases in NFR, while radiation decreased significantly in southern NFR in the seeding, vegetative and flowering phases. Effective rainfall increased in the seeding and vegetative phases leading to less water deficit, whereas decreased effective rainfall in the flowering and maturity phases enhanced water deficit. More days with drought stress were concentrated in western NFR where larger volumes of irrigation were needed. Our results indicate that the increase of mean temperature in the seeding and maturity phases was beneficial for maize yield, higher ETa in each growth phase would lead to yield increase, but too high rainfall would damage maize yield. The results also show that water deficit and drought stress days had significant negative effects on maize yield, and the absence of irrigation would manifest such effects on maize production in NFR. Therefore, the development of irrigation and drainage systems is highly needed for ensuring the stability of maize production in NFR. In addition, other adaptation measures like introducing new cultivars and optimizing soil and crop management to better conserve soil water would be beneficial for future maize production. No Label
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Woolnough, S. (2015). Climate Modelling and Sub-seasonal to Seasonal Prediction: Opportunities and Challenges (Vol. 5).
Abstract: Dr Steve Woolnough is a Principal Research Fellow in the Climate directorate of the National Centre for Atmospheric Science, and leads their Tropical Group. His interests are in the variability of the Tropical Climate System on intraseasonal to seasonal timescales, and the representation of the tropical climate system in weather and climate prediction models. He is a member of three international panels of the WMO including the Steering Group of their sub-seasonal to seasonal prediction project. Dr Woolnough will discuss the current state of climate modelling and introduce some of the uncertainties in prediction of regional climate change, and the opportunities to narrow these uncertainties. He will also discuss the current state of sub-seasonal to seasonal prediction and introduce the WCRP/WWRP Sub-seasonal Prediction Project, a new WMO project to promote research into and application of operational prediction systems. No Label
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