Bayesian approach to estimating margin of safety for total maximum daily load development

Journal of Environmental Management

Volumn 92, Issue 3, 2011, Pages 910-918

  Patil, Abhijit ^a   Deng, Zhi Qiang ^a  

^a LOUISIANA STATE UNIVERSITY   (United States)

Author keywords

Bayesian approach; Dissolved oxygen; Margin of safety; TMDL; Uncertainty

Indexed keywords

BAYESIAN NETWORKS; DISSOLUTION; MAXIMUM LIKELIHOOD ESTIMATION; RIVERS; STATISTICS; UNCERTAINTY ANALYSIS;

BAYESIAN APPROACHES; BAYESIAN UPDATING; LOAD DEVELOPMENT; MARGIN OF SAFETY; PROBABILITY: DISTRIBUTIONS; STANDARD DEVIATION; TOTAL MAXIMUM DAILY LOAD; TOTAL UNCERTAINTIES; UNCERTAINTY; UPDATING APPROACHES;

DISSOLVED OXYGEN;

DISSOLVED OXYGEN;

BAYESIAN ANALYSIS; DISSOLVED OXYGEN; PROBABILITY; SAFETY; SEASONALITY; UNCERTAINTY ANALYSIS;

ARTICLE; BAYES THEOREM; PROBABILITY; RISK ASSESSMENT; RIVER; SUMMER; UNITED STATES;

AMITE RIVER; LOUISIANA; UNITED STATES;

EID: 78650521844     PISSN: 03014797     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jenvman.2010.10.049     Document Type: Article

References (28)

1. Ajami N.K., Duan Q., Sorooshian S. An integrated hydrologic Bayesian multimodel combination framework: confronting input, parameter, and model structural uncertainty in hydrologic predictions. Water Resources Research 2007, 43:W01403.
2. Ayyub B.M. Uncertainty Modeling and Analysis in Civil Engineering 1998, Chapman & Hall CRC Press.
3. Benjamin J.R., Cornell C.A. Probability, Statistics and Decision for Civil Engineers 1970, McGraw-Hill Book Company.
4. Bobba G.A., Singh V.P., Bengtsson L. Application of environmental models to different hydrological systems. Ecological Modeling 2000, 125:15-49.
5. Borsuk M.E., Stow C.A., Reckhow K.H. Predicting the frequency of water quality standard violations: a probabilistic approach for TMDL development. Environmental Science and Technology 2002, 36(10):2109-2115.
6. Borsuk M.E., Stow C.A., Reckhow K.H. Integrated approach to total maximum daily load development for Neuse river estuary using Bayesian probability network model. Journal of Water Resources Planning and Management 2003, 129(4):271-282.
7. Borsuk M.E., Stow C.A., Reckhow K.H. A Bayesian network of eutrophication models for synthesis, prediction and uncertainty analysis. Ecological Modeling 2004, 173:219-239.
8. Campbell E., Fox P. A Bayesian approach to parameter estimation and pooling nonlinear flood even models. Water Resources Research 1999, 35(1):211-220.
9. Dilks D.W., Canale R.P., Meier P.G. Development of Bayesian Monte Carlo techniques for water quality model uncertainty. Ecological Modeling 1992, 62:149-162.
10. Freedman P.L., Nemura A.D., Dilks D.W. Viewing total maximum daily load as a process, not a singular value: adaptive watershed management. Journal of Environmental Engineering 2004, 130(6):695-702.
11. Hamed M.M., El-Beshry M.Z. Uncertainty analysis in dissolved oxygen modeling in streams. Environmental Management 2004, 34(2):233-244.
12. Kanso A., Gromaire M.-C., Gaume E., Tassin B., Chebbo G. Bayesian approach for the calibration of models: application to an urban stormwater pollution model. Water Science and Technology 2003, 47(4):77-84.
13. Kavetski D., Franks S.W., Kuczera G. Confronting input uncertainty in environmental modeling. Calibration of environmental models. AGU Water Science and Application Series 2002, 6:49-68.
14. Kavetski D., Kuczera G., Franks S.W. Bayesian analysis of input uncertainty in hydrological modeling. Water Resources Research 2006, 42:W03407.
15. Kuczera G., Kavetski D., Franks S., Thyer M. Towards a Bayesian total error analysis of conceptual rainfall-runoff models: characterizing model error using storm-dependent parameters. Journal of Hydrology 2006, 331:161-177.
16. Moriasi D.N., Arnold J.G., VanLiew M.W., Bingner R.L., Harmel R.D., Veith T.L. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of ASABE 2007, 50(3):885-900.
17. Nash J.E., Sutcliffe J.V. River forecasting through conceptual model: part I a discussion of principles. Journal of Hydrology 1970, 10(3):282-290.
18. Neapolitan R.E. Probabilistic Reasoning in Expert Systems: Theory and Algorithms 1990, Wiley, New York.
19. NRC Assessing the TMDL Approach to Water Quality Management, National Research Council 2001, National Academy Press, Washington, D.C.
20. Park M.-H., Stenstrom M.K. Using satellite imagery for stormwater pollution management with Bayesian networks. Water Research 2006, 40:3429-3438.
21. Patil A., 2009. An Uncertainty-based Approach to the Total Maximum Daily Load Development, A Dissertation Submitted to Louisiana State University.
22. Pearl J. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference 1988, Morgan Kaufmann, San Mateo, CA.
23. Schaefli B., Talamba D.B., Musy A. Quantifying hydrological modeling error through a mixture of normal distributions. Journal of Hydrology 2007, 332:303-315.
24. Singh V.P., Jain S.K., Tyagi A. Risk and Reliability Analysis - a Handbook for Civil and Environmental Engineers 2007, American Society of Civil Engineers Press.
25. Stow C.A., Roessler C., Borsuk M.E., Bowen J.D., Reckhow K.H. Comparison of estuarine water quality models for total maximum daily load development in Neuse river estuary. Journal of Water Resource Planning and Management 2003, 129(4):307-314.
26. Usda Ars State Soil Geographic (STATSGO) Data Base: Data Use Information 1994.
27. US EPA Draft Guidance For Water Quality-based Decisions: the TMDL Process 1999, Rep. 841-D-99-001, United States Environmental Protection Agency, EPA, Washington, D.C. second ed.
28. US EPA Impaired Waters and Total Maximum Daily Loads, United States Environmental Protection Agency 2009, http://www.epa.gov/OWOW/tmdl.