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    Receiving Water Quality Models for TMDL Development and Implementation

    Source: Journal of Hydrologic Engineering:;2019:;Volume ( 024 ):;issue: 002
    Author:
    René A. Camacho; Zhonglong Zhang; Xiaobo Chao
    DOI: 10.1061/(ASCE)HE.1943-5584.0001723
    Publisher: American Society of Civil Engineers
    Abstract: Water quality models are critical tools for the development of total maximum daily loads (TMDLs) and for the evaluation of water quality management alternatives by stakeholders and state environmental protection agencies. Currently there is a large availability of water quality models that can be used to support TMDL studies, and the selection of a particular model requires a good understanding of the model limitations, capabilities, and data requirements. The ASCE/Environmental and Water Resources Institute (EWRI) TMDL Analysis and Modeling Task Committee was established in part to produce guidance documentation to help modelers to identify and implement existing modeling approaches to address some of the most important causes of water quality impairment in the United States, including eutrophication, toxic chemicals, and metals. This paper presents a review of existing mathematical models to evaluate eutrophication processes, including carbon and nutrient cycling, phytoplankton dynamics, and dissolved oxygen availability, as well as a review of mathematical models to simulate the fate and transport of toxic chemicals and mercury. The paper also discusses the main capabilities and limitations of 11 widely used water quality models in the United States. Modelers can use this information to support more informed model selections and to facilitate an effective and successful application of models in TMDL studies.
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      Receiving Water Quality Models for TMDL Development and Implementation

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4255043
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    contributor authorRené A. Camacho; Zhonglong Zhang; Xiaobo Chao
    date accessioned2019-03-10T12:11:10Z
    date available2019-03-10T12:11:10Z
    date issued2019
    identifier other%28ASCE%29HE.1943-5584.0001723.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4255043
    description abstractWater quality models are critical tools for the development of total maximum daily loads (TMDLs) and for the evaluation of water quality management alternatives by stakeholders and state environmental protection agencies. Currently there is a large availability of water quality models that can be used to support TMDL studies, and the selection of a particular model requires a good understanding of the model limitations, capabilities, and data requirements. The ASCE/Environmental and Water Resources Institute (EWRI) TMDL Analysis and Modeling Task Committee was established in part to produce guidance documentation to help modelers to identify and implement existing modeling approaches to address some of the most important causes of water quality impairment in the United States, including eutrophication, toxic chemicals, and metals. This paper presents a review of existing mathematical models to evaluate eutrophication processes, including carbon and nutrient cycling, phytoplankton dynamics, and dissolved oxygen availability, as well as a review of mathematical models to simulate the fate and transport of toxic chemicals and mercury. The paper also discusses the main capabilities and limitations of 11 widely used water quality models in the United States. Modelers can use this information to support more informed model selections and to facilitate an effective and successful application of models in TMDL studies.
    publisherAmerican Society of Civil Engineers
    titleReceiving Water Quality Models for TMDL Development and Implementation
    typeJournal Paper
    journal volume24
    journal issue2
    journal titleJournal of Hydrologic Engineering
    identifier doi10.1061/(ASCE)HE.1943-5584.0001723
    page04018063
    treeJournal of Hydrologic Engineering:;2019:;Volume ( 024 ):;issue: 002
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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