Identifier
etd-0916103-154052
Degree
Master of Science (MS)
Department
Environmental Sciences
Document Type
Thesis
Abstract
Eutrophication is a process by which a waterbody progresses from its origin to its extinction. During this period, there is a gradual accumulation of nutrients and organic biomass, accompanied by a decrease in average depth of the water due to sediment accumulation, and an increase in primary productivity, usually in the form of dense algal blooms. Cultural eutrophication occurs when humans, through their various activities, greatly accelerate this process. Eutrophication can cause loss in species diversity, fish kills, and decrease the aesthetic value of a waterbody. The EPA is trying to prevent cultural eutrophication by setting standards for water quality criteria for each of the fourteen ecoregions in the United States. Nutrients are the most common pollutants affecting waterbodies. The EPA considers total phosphorous and total nitrogen as the two causal variables and chlorophyll a and Secchi depth as the two early indicator response variables. There are models that predict the relationship of chlorophyll a to phosphorous and chlorophyll a to nitrogen, but there are very few that combine phosphorous and nitrogen to predict chlorophyll a at a cross-sectional level. This study is concerned with fitting a linear model for the prediction of chlorophyll a, using phosphorous and nitrogen, for the fourteen ecoregions. Six combinations of the three variables have been tested (because of the different methods used to obtain each variable) to find out which model is the best with respect to model fit, number of observations, and geographical coverage. The best model can then be used in further studies to determine eutrophication end points at smaller and more homogeneous divisions of the ecoregion for better management of water quality in lakes.
Date
2003
Document Availability at the Time of Submission
Release the entire work immediately for access worldwide.
Recommended Citation
Das, Anindita, "Regional water quality models for the prediction of eutrophication endpoints" (2003). LSU Master's Theses. 1496.
https://repository.lsu.edu/gradschool_theses/1496
Committee Chair
E. Corad Lamon III
DOI
10.31390/gradschool_theses.1496