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    Automated Linear and Nonlinear Reservoir Approaches for Estimating Annual Base Flow

    Source: Journal of Hydrologic Engineering:;2012:;Volume ( 017 ):;issue: 004
    Author:
    Arpana Rani Datta
    ,
    Tirupati Bolisetti
    ,
    Ram Balachandar
    DOI: 10.1061/(ASCE)HE.1943-5584.0000450
    Publisher: American Society of Civil Engineers
    Abstract: Three automated base flow separation techniques based on linear and nonlinear reservoir approaches are used to identify the seasonal variation of base flow and to quantify the annual base flow for three subwatersheds of the Essex region in Southwestern Ontario, Canada. Significant differences in annual base flow estimated by linear and nonlinear reservoir algorithms are observed. In the nonlinear reservoir approach, the recession parameter is considered to be a seasonally variable parameter. The nonlinear reservoir approach fits streamflow recession better than the linear reservoir approach. The steeper slopes of seasonal flow duration curves in the 90% to 100% flow exceedance range show that the groundwater contribution to streamflow is relatively small in the study area. The precipitation-streamflow relationships show faster response of base flow during the period of high recharge. All of the methods show similar base flow estimation during the period of high evapotranspiration losses. The nonlinear reservoir approach represents the base flow response to precipitation better than the other methods. Therefore, the annual base flow estimated by the nonlinear reservoir approach is considered as the most reasonable estimation for the formulation of water budget of the study area. The method quantifies the occurrence of average annual baseflow as 34% of average annual streamflow.
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      Automated Linear and Nonlinear Reservoir Approaches for Estimating Annual Base Flow

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    http://yetl.yabesh.ir/yetl1/handle/yetl/63332
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    • Journal of Hydrologic Engineering

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    contributor authorArpana Rani Datta
    contributor authorTirupati Bolisetti
    contributor authorRam Balachandar
    date accessioned2017-05-08T21:49:09Z
    date available2017-05-08T21:49:09Z
    date copyrightApril 2012
    date issued2012
    identifier other%28asce%29he%2E1943-5584%2E0000470.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/63332
    description abstractThree automated base flow separation techniques based on linear and nonlinear reservoir approaches are used to identify the seasonal variation of base flow and to quantify the annual base flow for three subwatersheds of the Essex region in Southwestern Ontario, Canada. Significant differences in annual base flow estimated by linear and nonlinear reservoir algorithms are observed. In the nonlinear reservoir approach, the recession parameter is considered to be a seasonally variable parameter. The nonlinear reservoir approach fits streamflow recession better than the linear reservoir approach. The steeper slopes of seasonal flow duration curves in the 90% to 100% flow exceedance range show that the groundwater contribution to streamflow is relatively small in the study area. The precipitation-streamflow relationships show faster response of base flow during the period of high recharge. All of the methods show similar base flow estimation during the period of high evapotranspiration losses. The nonlinear reservoir approach represents the base flow response to precipitation better than the other methods. Therefore, the annual base flow estimated by the nonlinear reservoir approach is considered as the most reasonable estimation for the formulation of water budget of the study area. The method quantifies the occurrence of average annual baseflow as 34% of average annual streamflow.
    publisherAmerican Society of Civil Engineers
    titleAutomated Linear and Nonlinear Reservoir Approaches for Estimating Annual Base Flow
    typeJournal Paper
    journal volume17
    journal issue4
    journal titleJournal of Hydrologic Engineering
    identifier doi10.1061/(ASCE)HE.1943-5584.0000450
    treeJournal of Hydrologic Engineering:;2012:;Volume ( 017 ):;issue: 004
    contenttypeFulltext
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