Optimizing an estuarine water quality monitoring program through an entropy-based hierarchical spatiotemporal Bayesian framework-Reference-Cited by-同舟云学术

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Optimizing an estuarine water quality monitoring program through an entropy-based hierarchical spatiotemporal Bayesian framework

Published:2013-10 Issue:10 Volume:49 Page:6933-6945
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resour. Res.

Author:

Alameddine Ibrahim¹²,Karmakar Subhankar³,Qian Song S.¹⁴,Paerl Hans W.⁵,Reckhow Kenneth H.¹

Affiliation:

1. Nicholas School of the Environment, Duke University; Durham North Carolina

2. Nicholas School is the Environmental Science and Policy Division; American University of Beirut; Beirut Lebanon

3. Centre for Environmental Science and Engineering; Indian Institute of Technology Bombay; Mumbai India

4. Department of Environmental Science; The University of Toledo; Ohio

5. Institute of Marine Sciences; University of North Carolina at Chapel Hill; Morehead City North Carolina

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/wrcr.20509/fullpdf

Reference83 articles.

1. Application of an entropy-based Bayesian optimization technique to the redesign of an existing monitoring network for single air pollutants;Ainslie;J. Environ. Manag.,2009

2. A Bayesian changepoint-threshold model to examine the effect of TMDL implementation on the flow-nitrogen concentration relationship in the Neuse River basin;Alameddine;Water Res.,2011

3. Information theory-based approach for location of monitoring water level gauges in polders;Alfonso;Water Resour. Res.,2010a

4. Optimization of water level monitoring network in polder systems using information theory;Alfonso;Water Resour. Res.,2010b

5. Hierarchical Modeling and Analysis for Spatial Data

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