Title page for ETD etd-0916103-154052


Type of Document Master's Thesis
Author Das, Anindita
Author's Email Address adas1@lsu.edu
URN etd-0916103-154052
Title Regional Water Quality Models for the Prediction of Eutrophication Endpoints
Degree Master of Science (M.S.)
Department Environmental Studies
Advisory Committee
Advisor Name Title
E. Corad Lamon III Committee Chair
Margaret A. Reams Committee Member
Michael W. Wascom Committee Member
Walter R. Keithly Committee Member
Keywords
  • kolmogorov-smirnov test
  • nutrient criteria database
  • dummy variable
  • residuals
  • cook's distance
Date of Defense 2003-07-25
Availability unrestricted
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.
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