Graduation Term

2022

Degree Name

Master of Science (MS)

Committee Chair

Wondwosen Seyoum

Abstract

Surface drinking water infrastructure is an integral part of the development and sustainability of societies around the world. However, these surface freshwater resources have been a challenge to monitor due to the vast number of in-situ samples needed to accurately quantify constituents, expenses of equipment, coordination of personnel, and laboratory costs. Lake Bloomington and Evergreen Lake (Hudson, Illinois) are two vital surface water features that serve as the drinking water reservoirs for the Bloomington, IL. Both reservoirs are within agricultural watersheds, with watershed inputs typically being high in turbidity and nitrate.

We utilized an Unmanned Aerial Vehicle (UAV) coupled with a five-band multispectral sensor to monitor two water quality parameters in the lakes: turbidity and chlorophyll-a (chl-a, an indicator of algae). By using the UAV, along with in-situ data collected the same day as the flight, we aim to answer the following questions: (1) What are the optical properties of the lakes water quality parameters of chl-a and turbidity? (2) What is the spatial and temporal variation of chl-a and turbidity within the lakes?

Results showed that at nearly 6 cm resolution, greater than 80% coverage can be produced at each sample site and regularly above 90% coverage of the area can be obtained. Through several proprietary algorithms, we were able to explain 70% of the variation of chl-a in the lakes using UAV data. Although algorithms were created for turbidity, the algorithms were only able to explain less than 20% percent of the variation of the observed samples. This poor correlation may be due to low concentrations of turbidity observed in the lakes. This research demonstrated the potential of using UAV-based multispectral sensor for monitoring chl-a in small reservoirs.

Access Type

Thesis-Open Access

DOI

https://doi.org/10.30707/ETD2022.20220705065051850022.999988

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