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    Moment-Based Method for Identification of Pollution Source in Rivers 

    Source: Journal of Environmental Engineering:;2015:;Volume ( 141 ):;issue: 010
    Author(s): Yangbin Tong; Zhiqiang Deng
    Publisher: American Society of Civil Engineers
    Abstract: Identification of unknown pollution sources is essential to environmental protection and emergency response. This paper presents a moment-based method for identification of source location and quantity of accidental pollution ...
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    VART Model–Based Method for Estimation of Instream Dissolved Oxygen and Reaeration Coefficient 

    Source: Journal of Environmental Engineering:;2012:;Volume ( 138 ):;issue: 004
    Author(s): Vahid Zahraeifard; Zhiqiang Deng
    Publisher: American Society of Civil Engineers
    Abstract: Dissolved oxygen (DO) is essential to maintaining flora and fauna in aquatic ecosystems. The DO replenishment through the surface reaeration mechanism is commonly described using the reaeration coefficient (
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    Event Flow Hydrograph–Based Method for Modeling Sediment Transport 

    Source: Journal of Hydrologic Engineering:;2013:;Volume ( 018 ):;issue: 008
    Author(s): Bhuban Ghimire; Zhiqiang Deng
    Publisher: American Society of Civil Engineers
    Abstract: A simple method, called the hydrograph-based method, is presented for estimating sediment transport during flood events in rivers. The method is characterized by the following features: (1) widely available flow hydrographs ...
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    How Reliable Are ANN, ANFIS, and SVM Techniques for Predicting Longitudinal Dispersion Coefficient in Natural Rivers? 

    Source: Journal of Hydraulic Engineering:;2016:;Volume ( 142 ):;issue: 001
    Author(s): Roohollah Noori; Zhiqiang Deng; Amin Kiaghadi; Fatemeh Torabi Kachoosangi
    Publisher: American Society of Civil Engineers
    Abstract: Determination of longitudinal dispersion coefficient (LDC) using artificial intelligence (AI) techniques can improve environmental management strategies for river systems. However, the uncertainty involved in AI models has ...
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    How Reliable Are ANN, ANFIS, and SVM Techniques for Predicting Longitudinal Dispersion Coefficient in Natural Rivers? 

    Source: Journal of Hydraulic Engineering:;2016:;Volume ( 142 ):;issue: 001
    Author(s): Roohollah Noori; Zhiqiang Deng; Amin Kiaghadi; Fatemeh Torabi Kachoosangi
    Publisher: American Society of Civil Engineers
    Abstract: Determination of longitudinal dispersion coefficient (LDC) using artificial intelligence (AI) techniques can improve environmental management strategies for river systems. However, the uncertainty involved in AI models has ...
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