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Author Rosenzweig, C.; Jones, J.W.; Hatfield, J.L.; Ruane, A.C.; Boote, K.J.; Thorburn, P.; Antle, J.M.; Nelson, G.C.; Porter, C.; Janssen, S.; Asseng, S.; Basso, B.; Ewert, F.; Wallach, D.; Baigorria, G.; Winter, J.M. url  doi
openurl 
  Title The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and pilot studies Type Journal Article
  Year 2013 Publication Agricultural and Forest Meteorology Abbreviated Journal (up) Agricultural and Forest Meteorology  
  Volume 170 Issue Pages 166-182  
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  Series Volume Series Issue Edition  
  ISSN 0168-1923 ISBN Medium  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur, IPCC-AR5 Approved no  
  Call Number MA @ admin @ Serial 4927  
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Author Teixeira, E.I.; Fischer, G.; van Velthuizen, H.; Walter, C.; Ewert, F. url  doi
openurl 
  Title Global hot-spots of heat stress on agricultural crops due to climate change Type Journal Article
  Year 2013 Publication Agricultural and Forest Meteorology Abbreviated Journal (up) Agricultural and Forest Meteorology  
  Volume 170 Issue Pages 206-215  
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  Series Volume Series Issue Edition  
  ISSN 0168-1923 ISBN Medium  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur, IPCC-AR5 Approved no  
  Call Number MA @ admin @ Serial 4929  
Permanent link to this record
 

 
Author Watson, J.; Challinor, A. url  doi
openurl 
  Title The relative importance of rainfall, temperature and yield data for a regional-scale crop model Type Journal Article
  Year 2013 Publication Agricultural and Forest Meteorology Abbreviated Journal (up) Agricultural and Forest Meteorology  
  Volume 170 Issue Pages 47-57  
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  Series Volume Series Issue Edition  
  ISSN 0168-1923 ISBN Medium  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur, IPCC-AR5 Approved no  
  Call Number MA @ admin @ Serial 4930  
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Author Balkovič, J.; van der Velde, M.; Schmid, E.; Skalský, R.; Khabarov, N.; Obersteiner, M.; Stürmer, B.; Xiong, W. url  doi
openurl 
  Title Pan-European crop modelling with EPIC: Implementation, up-scaling and regional crop yield validation Type Journal Article
  Year 2013 Publication Agricultural Systems Abbreviated Journal (up) Agricultural Systems  
  Volume 120 Issue Pages 61-75  
  Keywords EPIC; large-scale crop modelling; model performance testing; EU; climate-change; high-resolution; organic-carbon; growth-model; wheat yield; water; calibration; impacts; productivity; simulations  
  Abstract Justifiable usage of large-scale crop model simulations requires transparent, comprehensive and spatially extensive evaluations of their performance and associated accuracy. Simulated crop yields of a Pan-European implementation of the Environmental Policy Integrated Climate (EPIC) crop model were satisfactorily evaluated with reported regional yield data from EUROSTAT for four major crops, including winter wheat, rainfed and irrigated maize, spring barley and winter rye. European-wide land use, elevation, soil and daily meteorological gridded data were integrated in GIS and coupled with EPIC. Default EPIC crop and biophysical process parameter values were used with some minor adjustments according to suggestions from scientific literature. The model performance was improved by spatial calculations of crop sowing densities, potential heat units, operation schedules, and nutrient application rates. EPIC performed reasonable in the simulation of regional crop yields, with long-term averages predicted better than inter-annual variability: linear regression R-2 ranged from 0.58 (maize) to 0.91 (spring barley) and relative estimation errors were between +/- 30% for most of the European regions. The modelled and reported crop yields demonstrated similar responses to driving meteorological variables. However, EPIC performed better in dry compared to wet years. A yield sensitivity analysis of crop nutrient and irrigation management factors and cultivar specific characteristics for contrasting regions in Europe revealed a range in model response and attainable yields. We also show that modelled crop yield is strongly dependent on the chosen PET method. The simulated crop yield variability was lower compared to reported crop yields. This assessment should contribute to the availability of harmonised and transparently evaluated agricultural modelling tools in the EU as well as the establishment of modelling benchmarks as a requirement for sound and ongoing policy evaluations in the agricultural and environmental domains. (C) 2013 The Authors. Published by Elsevier Ltd. All rights reserved.  
  Address 2016-06-01  
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  Language English Summary Language Original Title  
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  ISSN 0308-521x ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4737  
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Author Dono, G.; Cortignani, R.; Doro, L.; Giraldo, L.; Ledda, L.; Pasqui, M.; Roggero, P.P. url  doi
openurl 
  Title Adapting to uncertainty associated with short-term climate variability changes in irrigated Mediterranean farming systems Type Journal Article
  Year 2013 Publication Agricultural Systems Abbreviated Journal (up) Agricultural Systems  
  Volume 117 Issue Pages 1-12  
  Keywords changed climate variability; dsp; epic; adaptation; water management; irrigation; simulating impacts; co2 concentration; crop production; productivity; maize; yield; growth; model; photosynthesis; agriculture  
  Abstract Short-term perspectives appear to be relevant in formulating adaptation measures to changed climate variability (CCV) as a part of the European Rural Development Policy (RDP). Indeed, short-run CCV is the variation that farmers would perceive to such an extent that a political demand would be generated for adapting support measures. This study evaluates some relevant agronomic and economic impacts of CCV as modelled in a near future time period at the catchment scale in a rural district in Sardinia (Italy). The effects of CCV are assessed in relation to the availability of irrigation water and the irrigation needs of maize. The Environmental Policy Integrated Climate (EPIC) model was used to simulate the impact of key climatic variables on the irrigation water requirements and yields of maize. A three-stage discrete stochastic programming model was then applied to simulate management and economic responses to those changes. The overall economic impact of a simulated CCV was found to be primarily caused by reduced stability in the future supply of irrigation water. Adaptations to this instability will most likely lead to a higher level of groundwater extraction and a reduction in the demand for labour. Changed climate variability will most likely reduce the income potential of small-scale farming. The most CCV-vulnerable farm typologies were identified, and the implications were discussed in relation to the development of adaptation measures within the context of the Common Agricultural Policy of European Union. (C) 2013 Elsevier Ltd. All rights reserved.  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 0308521x ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4489  
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