Document Type

Thesis - Open Access

Award Date

2021

Degree Name

Master of Science (MS)

Department / School

Agricultural and Biosystems Engineering

First Advisor

John T. McMaine

Keywords

Algae, Lake Water Quality, Regression Model, Remote Sensing

Abstract

Excessive algal growth in freshwater lakes can negatively impact ecosystems, recreation, and human health. Though algae are a natural part of freshwater ecosystems, elevated nutrient loading from anthropogenic and natural sources can lead to algal blooms. Both algae and blue-green algae (BGA) are responsible for algal blooms; however, BGA (cyanobacteria) is more dangerous. The first objective of this research was to prepare a conceptual model to understand how various environmental variables affect algae. This conceptual model was used to choose the environmental variables that help increase or decrease algae in the water environment. The second objective was to develop empirical equations to identify how the environmental variables are helping algal increase or decrease. Lake Mitchell, near Mitchell, SD, was chosen as a case study to collect the data of the environmental variables. Along with the total algae (Total algae = Chlorophyll-a + Phycocyanin), five variables: (1) conductivity, (2) temperature, (3) fluorescent dissolved organic matter, (4) ammonium, and (5) dissolved oxygen, were collected. Algae concentrations can change temporally, vertically within the water column, and spatially across lakes and thus, a four-dimensional approach was used to accurately quantify algal

Library of Congress Subject Headings

Algal blooms -- Remote sensing.
Algal blooms -- Mathematical models.
Algal blooms -- South Dakota -- Mitchell, Lake.
Water quality -- South Dakota -- Mitchell, Lake.
Water quality management -- South Dakota -- Mitchell, Lake.

Number of Pages

96

Publisher

South Dakota State University

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Rights Statement

In Copyright