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  • 1
    Article
    Article
    Language: English
    In: Power Engineering International, July-August, 2014, Vol.22(7), p.50(6)
    Keywords: Wind Power -- Supply And Demand ; Electric Generators -- Usage ; Vibration Control -- Planning
    ISSN: 1069-4994
    Source: Cengage Learning, Inc.
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  • 2
    Language: English
    In: Agriculture, ecosystems & environment, 2011, Vol.142(1), pp.6-17
    Description: Agricultural systems and problems of sustainability are complex, covering a range of organisational levels and spatial and temporal scales. Integrated assessment (IA) and modelling (IAM) is an attempt to capture complex multi-scale problems. Scale changes and model linking methods (referred to as scaling methods) are important in dealing with these problems but they are often not well understood. The present study aims to analyse scaling methods used in the recently developed multi-scale IA model SEAMLESS-IF which is applied to two case studies of complex agri-environmental problems. The analysis is based on a classification of up- and down-scaling methods which is extended for the purpose of this study. Our analysis shows that scale changes refer to different spatial, temporal and functional scales with changes in extent, resolution, and coverage rate. Accordingly, SEAMLESS-IF uses a number of different scaling methods including data extrapolation, aggregation and disaggregation, sampling, nested simulation and employs descriptive response functions and technical coefficients derived from explanatory models. Despite the satisfactory results obtained from SEAMLESS-IF, a comparative quantitative analysis of alternative scaling methods is still pending and requires further attention. Improved integration of scaling methods may also help to overcome limitations of IA models related to high data demand, complexity of models and scaling methods considered, and the accumulation of uncertainty due to the use of multiple models. In the case studies, the most challenging scaling problem refers to the appropriate consideration of the farm level as intermediate level between the field and market levels. Among the scaling methods analysed, summary models are hardly applied. This is because they are often unavailable due to limited systems understanding and because they may differ depending on the question at stake. The classification of scaling methods used has been helpful to structure this analysis. ; p. 6-17.
    Keywords: Case Studies ; Models ; Markets ; Quantitative Analysis ; Farms ; Uncertainty
    ISSN: 0167-8809
    Source: AGRIS (Food and Agriculture Organization of the United Nations)
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  • 3
    Language: English
    In: Agriculture, Ecosystems and Environment, 2011, Vol.142(1), pp.1-5
    Keywords: Agriculture ; Environmental Sciences
    ISSN: 0167-8809
    E-ISSN: 1873-2305
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  • 4
    Language: English
    In: Agriculture, Ecosystems and Environment, June 15, 2012, Vol.153, p.57(8)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.agee.2012.03.004 Byline: Amit Kumar Srivastava (a), Thomas Gaiser (a), Heiko Paeth (b), Frank Ewert (c) Keywords: Climate change; SRES emission scenarios; Tuber crops; Yield; Moist savanna; Benin Abstract: a* EPIC model for Yam was used to assess the climate change impact on its yield. a* Response of major soils in study area was analyzed in relation to climate change. a* Reduced rainfall and nitrogen deficiency was the major constraint in yield decline. Author Affiliation: (a) University of Bonn, Institute of Crop Science and Resource Conservation, D-53115 Bonn, Germany (b) Geographical Institute, University of Wurzburg, Am Hubland, Wurzburg 97074, Germany (c) University of Bonn, Institute of Crop Science, Katzenburgweg 5, 53115 Bonn, Germany Article History: Received 14 August 2011; Revised 5 March 2012; Accepted 7 March 2012
    Keywords: Climate Change -- Environmental Aspects ; Climate Change -- Analysis ; Crop Yields -- Environmental Aspects ; Crop Yields -- Analysis ; Global Temperature Changes -- Environmental Aspects ; Global Temperature Changes -- Analysis
    ISSN: 0167-8809
    Source: Cengage Learning, Inc.
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  • 5
    In: Nature Climate Change, 2012, Vol.2(3), p.153
    ISSN: 1758-678X
    E-ISSN: 1758-6798
    Source: Nature Publishing Group
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  • 6
    In: Global Change Biology, November 2015, Vol.21(11), pp.4031-4048
    Description: This study evaluates the impacts of projected climate change on irrigation requirements and yields of six crops (winter wheat, winter barley, rapeseed, grain maize, potato, and sugar beet) in Europe. Furthermore, the uncertainty deriving from consideration of irrigation, effects on crop growth and transpiration, and different climate change scenarios in climate change impact assessments is quantified. Net irrigation requirement () and yields of the six crops were simulated for a baseline (1982–2006) and three scenarios (B1, B2 and A1B, 2040–2064) under rainfed and irrigated conditions, using a process‐based crop model, . We found that projected climate change decreased of the three winter crops in northern Europe (up to 81 mm), but increased of all the six crops in the Mediterranean regions (up to 182 mm yr). Climate change increased yields of the three winter crops and sugar beet in middle and northern regions (up to 36%), but decreased their yields in Mediterranean countries (up to 81%). Consideration of effects can alter the direction of change in for irrigated crops in the south and of yields for C3 crops in central and northern Europe. Constraining the model to rainfed conditions for spring crops led to a negative bias in simulating climate change impacts on yields (up to 44%), which was proportional to the irrigation ratio of the simulation unit. Impacts on and yields were generally consistent across the three scenarios for the majority of regions in Europe. We conclude that due to the magnitude of irrigation and effects, they should both be considered in the simulation of climate change impacts on crop production and water availability, particularly for crops and regions with a high proportion of irrigated crop area.
    Keywords: Climate Change ; Co 2 Effects ; Crop Model ; Irrigation ; Lintul ; Simplace ; Water Availability ; Yield Change
    ISSN: 1354-1013
    E-ISSN: 1365-2486
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  • 7
    Language: English
    In: Agriculture, Ecosystems and Environment, Nov 1, 2012, Vol.162, p.24(12)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.agee.2012.07.018 Byline: Omonlola Nadine Worou (a), Thomas Gaiser (a), Kazuki Saito (b), Heiner Goldbach (a), Frank Ewert (a) Keywords: EPIC model; Rainfed lowland rice; Calibration; Soil moisture; Crop production, Iron toxicity Abstract: a* The crop model EPIC is applied to a representative site for rainfed lowland rice cropping. a* The model was parametrized using observed soil water characteristics and crop parameters. a* The model should be upgraded for 2 D for soil water status simulation. Author Affiliation: (a) University of Bonn, Institute of Crop Science and Resource Conservation, D-53115 Bonn, Germany (b) Africa Rice Center (AfricaRice), 01 BP 2031 Cotonou, Benin Article History: Received 20 February 2012; Revised 1 July 2012; Accepted 17 July 2012
    Keywords: Soil Moisture -- Models ; Fertilizers -- Models ; Fertilizer Industry -- Models ; Grain Industry -- Models
    ISSN: 0167-8809
    Source: Cengage Learning, Inc.
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  • 8
    Language: English
    In: Science, Jan 26, 2007, Vol.315(5811), p.459(1)
    ISSN: 0036-8075
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  • 9
    Language: English
    In: Science (New York, N.Y.), 09 April 2010, Vol.328(5975), pp.172-3
    Keywords: Agriculture ; Crops, Agricultural ; Food Supply
    ISSN: 00368075
    E-ISSN: 1095-9203
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  • 10
    Language: English
    In: Ecological modelling, 2016, Vol.322, pp.54-70
    Description: Modelling rangeland is essential for capturing changes at the large temporal and spatial scales at which these systems respond to climate and institutional changes and increasing population pressure, but rangeland models applicable to data sparse regions are rarely available. We developed and evaluated a novel rangeland model aimed at simulating rangeland at different stages of degradation using limited parameterisation and measurements.The developed model Linrange is a biophysical simulation model of the aboveground part of a mixed grass sward, combined with sub-models for evapotranspiration, soil water dynamics, and root development. Main processes of the biomass model are growth through a source/sink limited mechanism, reserve storage and remobilisation, basal area dynamics, winter dormancy. The grass sward is simulated based on average species characteristics of the dominating grass community.We show that a model based on simplified biophysical processes and a single set of parameters for a mixed sward can satisfactorily simulate mixed-species rangeland vegetation. The model also could reproduce year-to-year phytomass dynamics, including for exceptionally wet and dry years. Without calibrating specifically for it, the model was able to reproduce observed water-use efficiency values, indicating a good representation of the relationship between the main limiting factor, water, and productivity. By recalibrating the model using only five parameters associated with degradation, the accuracy of simulated degraded rangeland states was close to that of undegraded rangeland. We therefore consider the Linrange model a good tool for research on rangeland dynamics and degradation resulting from management and climate. We also point to directions of further model improvement, particularly regarding the modelling of parameter changes with degradation states. ; p. 54-70.
    Keywords: Degradation ; Grazing ; Biomass ; Sward ; Dynamic Model ; Basal Area ; Growth Models ; Vegetation ; Simulation Models ; Evapotranspiration ; Dormancy ; Soil Water ; Grasses ; Rangeland Model ; Population Growth ; Water Use Efficiency ; Semiarid Zones ; Rangelands ; Semi-Arid Grassland
    ISSN: 0304-3800
    Source: AGRIS (Food and Agriculture Organization of the United Nations)
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