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Author Castañeda-Vera, A.; Leffelaar, P.A.; Álvaro-Fuentes, J.; Cantero-Martínez, C.; Mínguez, M.I. url  doi
openurl 
  Title Selecting crop models for decision making in wheat insurance Type Journal Article
  Year (up) 2015 Publication European Journal of Agronomy Abbreviated Journal European Journal of Agronomy  
  Volume 68 Issue Pages 97-116  
  Keywords aquacrop; ceres-wheat; cropsyst; wofost; model choice; rainfed semi-arid areas; radiation use efficiency; water deficit; use efficiency; management-practices; farming systems; field-capacity; soil; yield; evaporation; photosynthesis; transpiration; irrigation  
  Abstract In crop insurance, the accuracy with which the insurer quantifies the actual risk is highly dependent on the availability on actual yield data. Crop models might be valuable tools to generate data on expected yields for risk assessment when no historical records are available. However, selecting a crop model for a specific objective, location and implementation scale is a difficult task. A look inside the different crop and soil modules to understand how outputs are obtained might facilitate model choice. The objectives of this paper were (i) to assess the usefulness of crop models to be used within a crop insurance analysis and design and (ii) to select the most suitable crop model for drought risk assessment in semi-arid regions in Spain. For that purpose first, a pre-selection of crop models simulating wheat yield under rainfed growing conditions at the field scale was made, and second, four selected models (Aquacrop, CERES-Wheat, CropSyst and WOFOST) were compared in terms of modelling approaches, process descriptions and model outputs. Outputs of the four models for the simulation of winter wheat growth are comparable when water is not limiting, but differences are larger when simulating yields under rainfed conditions. These differences in rainfed yields are mainly related to the dissimilar simulated soil water availability and the assumed linkages with dry matter formation. We concluded that for the simulation of winter wheat growth at field scale in such semi-arid conditions, CERES-Wheat and CropSyst are preferred. WOFOST is a satisfactory compromise between data availability and complexity when detail data on soil is limited. Aquacrop integrates physiological processes in some representative parameters, thus diminishing the number of input parameters, what is seen as an advantage when observed data is scarce. However, the high sensitivity of this model to low water availability limits its use in the region considered. Contrary to the use of ensembles of crop models, we endorse that efforts be concentrated on selecting or rebuilding a model that includes approaches that better describe the agronomic conditions of the regions in which they will be applied. The use of such complex methodologies as crop models is associated with numerous sources of uncertainty, although these models are the best tools available to get insight in these complex agronomic systems. (C) 2015 Elsevier B.V. All rights reserved.  
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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 1161-0301 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4710  
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Author Wallach, D. url  doi
openurl 
  Title Developing skills: how to train adaptive modelers Type Journal Article
  Year (up) 2015 Publication Advances in Animal Biosciences Abbreviated Journal Advances in Animal Biosciences  
  Volume 6 Issue 01 Pages 52-53  
  Keywords capacity building; skills development; training; integrated modeling  
  Abstract  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2040-4700 ISBN Medium Article  
  Area Expedition Conference  
  Notes Hub, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4683  
Permanent link to this record
 

 
Author Kim, Y.; Seo, Y.; Kraus, D.; Klatt, S.; Haas, E.; Tenhunen, J.; Kiese, R. doi  openurl
  Title Estimation and mitigation of N₂O emission and nitrate leaching from intensive crop cultivation in the Haean catchment, South Korea Type Journal Article
  Year (up) 2015 Publication Science of the Total Environment Abbreviated Journal Science of the Total Environment  
  Volume 529 Issue Pages 40-53  
  Keywords Agriculture; Air Pollutants/*analysis; Air Pollution/prevention & control/*statistics & numerical data; Crops, Agricultural; *Environmental Monitoring; Fertilizers; Nitrogen Dioxide/*analysis; Republic of Korea; LandscapeDNDC; Mitigation strategies; N2O; Nitrate leaching; Water quality  
  Abstract Considering intensive agricultural management practices and environmental conditions, the LandscapeDNDC model was applied for simulation of yields, N2O emission and nitrate leaching from major upland crops and temperate deciduous forest of the Haean catchment, South Korea. Fertilization rates were high (up to 314 kg N ha(-1) year(-1)) and resulted in simulated direct N2O emissions from potato, radish, soybean and cabbage fields of 1.9 and 2.1 kg N ha(-1) year(-1) in 2009 and 2010, respectively. Nitrate leaching was identified as the dominant pathway of N losses in the Haean catchment with mean annual rates of 112.2 and 125.4 kg N ha(-1) year(-1), causing threats to water quality and leading to substantial indirect N2O emissions of 0.84 and 0.94 kg N ha(-1) year(-1) in 2009 and 2010 as estimates by applying the IPCC EF5. Simulated N2O emissions from temperate deciduous forest were low (approx. 0.50 kg N ha(-1) year(-1)) and predicted nitrate leaching rates were even negligible (≤0.01 kg N ha(-1) year(-1)). On catchment scale more than 50% of the total N2O emissions and up to 75% of nitrate leaching originated from fertilized upland fields, only covering 24% of the catchment area. Taking into account area coverage of simulated upland crops and other land uses these numbers agree well with nitrate loads calculated from discharge and concentration measurements at the catchment outlet. The change of current agricultural management practices showed a high potential of reducing N2O emission and nitrate leaching while maintaining current crop yields. Reducing (39%) and splitting N fertilizer application into 3 times was most effective and lead to about 54% and 77% reducing of N2O emission and nitrate leaching from the Haean catchment, the latter potentially contributing to improved water quality in the Soyang River Dam, which is the major source of drinking water for metropolitan residents.  
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  Language English Summary Language Original Title  
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  ISSN 0048-9697 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4684  
Permanent link to this record
 

 
Author Mitter, H.; Heumesser, C.; Schmid, E. url  doi
openurl 
  Title Spatial modeling of robust crop production portfolios to assess agricultural vulnerability and adaptation to climate change Type Journal Article
  Year (up) 2015 Publication Land Use Policy Abbreviated Journal Land Use Policy  
  Volume 46 Issue 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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  Language English Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 0264-8377 ISBN Medium Article  
  Area Expedition Conference  
  Notes TradeM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4675  
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Author Vosough Ahmadi, B.; Shrestha, S.; Thomson, S.G.; Barnes, A.P.; Stott, A.W. url  doi
openurl 
  Title Impacts of greening measures and flat rate regional payments of the Common Agricultural Policy on Scottish beef and sheep farms Type Journal Article
  Year (up) 2015 Publication Journal of Agricultural Science Abbreviated Journal J. Agric. Sci.  
  Volume 153 Issue 04 Pages 676-688  
  Keywords CAP reform; models; level; water; Agriculture  
  Abstract The latest Common Agricultural Policy (CAP) reforms could bring substantial changes to Scottish farming communities. Two major components of this reform package, an introduction of environmental measures into the Pillar 1 payments and a move away from historical farm payments towards regionalized area payments, would have a significant effect on altering existing support structures for Scottish farmers, as it would for similar farm types elsewhere in Europe where historic payments are used. An optimizing farm-level model was developed to explore how Scottish beef and sheep farms might be affected by the greening and flat rate payments under the current CAP reforms. Nine different types of beef and sheep farms were identified and detailed biophysical and financial farm-level data for these farm types were used to parameterize the model. Results showed that the greening measures of the CAP did not have much impact on net margins of most of the beef and sheep farm businesses, except for ‘Beef Finisher’ farm types where the net margins decreased by 3%. However, all farm types were better off adopting the greening measures than not qualifying for the greening payments through non-compliance with the measures. The move to regionalized farm payments increased the negative financial impact of greening on most of the farms but it was still substantially lower than the financial sacrifice of not adopting greening measures. Results of maximizing farm net margin, under a hypothetical assumption of excluding farm payments, showed that in most of the mixed (sheep and cattle) and beef suckler cattle farms the optimum stock numbers predicted by the model were lower than actual figures on farm. When the regionalized support payments were allocated to each farm, the proportion of the mixed farms that would increase their stock numbers increased whereas this proportion decreased for beef suckler farms and no impact was predicted in sheep farms. Also under the regionalized support payments, improvements in profitability were found in mixed farms and sheep farms. Some of the specialized beef suckler farms also returned a profit when CAP support was added.  
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  Language English Summary Language Original Title  
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  ISSN 0021-8596 1469-5146 ISBN Medium Article  
  Area Expedition Conference  
  Notes LiveM Approved no  
  Call Number MA @ admin @ Serial 4654  
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