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    Consideration of Climate Variability and Change in Agricultural Water Resources Planning

    Source: Journal of Water Resources Planning and Management:;2007:;Volume ( 133 ):;issue: 003
    Author:
    Kelly Brumbelow
    ,
    Aris Georgakakos
    DOI: 10.1061/(ASCE)0733-9496(2007)133:3(275)
    Publisher: American Society of Civil Engineers
    Abstract: Although agriculture and its use of water resources are obviously sensitive to climatic conditions, past research has seldom identified the effects of climate variability and climate change on the fully developed relationship between crop yield and irrigation. There is potentially great value in understanding the role of climatic uncertainty on this relationship because of the dependence of agriculture on irrigation and the scale of water consumption for irrigation. Probability distributions of crop-water production functions (CWPF-PDs) are demonstrated as being useful encapsulations of the climate-yield-irrigation relationship for decisions at various levels of time and space. Combined with reliable climate teleconnections or climate forecasts, CWPF-PDs can be a central decision support tool for questions of risk and reliability. For long planning horizons, potential climate change predicted by multiple general circulation models (GCMs) can be assessed in the context of agricultural water resources. By analysis of changes in the CWPF-PDs, conclusions regarding the efficacy and sustainability of water resources and agricultural policies can be made. A semihypothetical case study for the Lake Victoria Basin in East Africa is used to illustrate these methodologies, and potential future climate impacts as predicted by the CGCM1, ECHAM3, and HadCM2 GCMs are discussed.
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      Consideration of Climate Variability and Change in Agricultural Water Resources Planning

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    http://yetl.yabesh.ir/yetl1/handle/yetl/40082
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    contributor authorKelly Brumbelow
    contributor authorAris Georgakakos
    date accessioned2017-05-08T21:08:14Z
    date available2017-05-08T21:08:14Z
    date copyrightMay 2007
    date issued2007
    identifier other%28asce%290733-9496%282007%29133%3A3%28275%29.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/40082
    description abstractAlthough agriculture and its use of water resources are obviously sensitive to climatic conditions, past research has seldom identified the effects of climate variability and climate change on the fully developed relationship between crop yield and irrigation. There is potentially great value in understanding the role of climatic uncertainty on this relationship because of the dependence of agriculture on irrigation and the scale of water consumption for irrigation. Probability distributions of crop-water production functions (CWPF-PDs) are demonstrated as being useful encapsulations of the climate-yield-irrigation relationship for decisions at various levels of time and space. Combined with reliable climate teleconnections or climate forecasts, CWPF-PDs can be a central decision support tool for questions of risk and reliability. For long planning horizons, potential climate change predicted by multiple general circulation models (GCMs) can be assessed in the context of agricultural water resources. By analysis of changes in the CWPF-PDs, conclusions regarding the efficacy and sustainability of water resources and agricultural policies can be made. A semihypothetical case study for the Lake Victoria Basin in East Africa is used to illustrate these methodologies, and potential future climate impacts as predicted by the CGCM1, ECHAM3, and HadCM2 GCMs are discussed.
    publisherAmerican Society of Civil Engineers
    titleConsideration of Climate Variability and Change in Agricultural Water Resources Planning
    typeJournal Paper
    journal volume133
    journal issue3
    journal titleJournal of Water Resources Planning and Management
    identifier doi10.1061/(ASCE)0733-9496(2007)133:3(275)
    treeJournal of Water Resources Planning and Management:;2007:;Volume ( 133 ):;issue: 003
    contenttypeFulltext
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