Integrated Approach to Total Maximum Daily Load Development for Neuse River Estuary using Bayesian Probability Network Model (Neu-BERN)-Reference-Cited by-同舟云学术

Integrated Approach to Total Maximum Daily Load Development for Neuse River Estuary using Bayesian Probability Network Model (Neu-BERN)

Published:2003-07 Issue:4 Volume:129 Page:271-282
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Borsuk Mark E.¹,Stow Craig A.²,Reckhow Kenneth H.³

Affiliation:

1. Post-Doctoral Research Assistant, Dept. of Systems Analysis, Integrated Assessment, and Modelling (SIAM), Swiss Federal Institute for Environmental Science and Technology (EAWAG), P.O. Box 611, 8600 Dübendorf, Switzerland (corresponding author).

2. Dept. of Environmental Health Sciences, Arnold School of Public Health, Univ. of South Carolina, Columbia, SC 29208; formerly, Visiting Assistant Professor of Water Resources, Nicholas School of the Environment and Earth Sciences, Duke Univ., PO Box 90328, Durham, NC 27708-0328.

3. Professor of Water Resources, Nicholas School of the Environment and Earth Sciences, Duke Univ., PO Box 90328, Durham, NC 27708-0328.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%290733-9496%282003%29129%3A4%28271%29

Reference61 articles.

1. Alperin M. J. Clesceri E. J. Wells J. T. Albert D. B. McNinch J. E. and Martens C. S. (2000). “Sedimentary processes and benthic-pelagic coupling.” Neuse River Estuary Modeling and Monitoring Project Stage 1 Rep. No. 325-B Water Resources Research Institute of the University of North Carolina Raleigh NC 63–105.

2. Barnett V. and O’Hagan A. (1997). Setting environmental standards Chapman and Hall London.

3. Borsuk M. E. (2001). “A probability network model to support water quality decision making for the Neuse River Estuary North Carolina.” PhD dissertation Duke University Durham N.C.

4. A Bayesian hierarchical model to predict benthic oxygen demand from organic matter loading in estuaries and coastal zones

Cited by 74 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. How Bayesian networks are applied in the subfields of climate change: Hotspots and evolution trends;Environmental Modelling & Software;2024-01

2. Use of a Bayesian network as a decision support tool for watershed management: a case study in a highly managed river-dominated estuary;Environmental Monitoring and Assessment;2023-05-26

3. Transforming Conservation;2022-12-06

4. Use of a Bayesian network as a decision support tool for watershed management: A case study in a highly managed river-dominated estuary;2022-08-09

5. Simulating algal dynamics within a Bayesian framework to evaluate controls on estuary productivity;Ecological Modelling;2021-05