Utilizing Bayesian hierarchical techniques, regional-scale eutrophication models were developed for use in the Total Maximum Daily Load (TMDL) process. The Bayesian tree-based (BTREED) approach allows association of multiple environmental stressors with biological responses, and quantification of uncertainty sources in the water quality model. Simple parametric models are often inadequate for describing complex datasets; the BTREED approach partitions the dataset, and describes the localized subsets of data with linear models, thereby providing a comprehensive representation of stressor and response interactions. Nutrient criteria data for lakes, ponds and reservoirs across the United States were obtained from the Environmental Protection Agency (U.S. EPA) National Nutrient Criteria Database. Model estimation was accomplished by randomly splitting the composite dataset into training and test sets, and using the training dataset in model estimation, and the test dataset to evaluate and validate the model. Mean squared error was reported for both training and test data of the highest log-likelihood models. The Bayesian approach to regional-scale eutrophication models is also beneficial from a decision-theoretic perspective. Predictions regarding the variable of interest are quantified by probability distributions, providing the decision maker with valuable information about the distribution of the biological response conditional on the stressors, and information about the model error.
| Identifer | oai:union.ndltd.org:LSU/oai:etd.lsu.edu:etd-07082004-120520 |
| Date | 09 July 2004 |
| Creators | Freeman, Angelina |
| Contributors | E. Conrad Lamon, III, Ralph Portier, Craig Stow, Michael Wascom, Edward Overton |
| Publisher | LSU |
| Source Sets | Louisiana State University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lsu.edu/docs/available/etd-07082004-120520/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached herein a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to LSU or its agents the non-exclusive license to archive and make accessible, under the conditions specified below and in appropriate University policies, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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