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Remote Sensing Monitoring of Neuse River Estuary for Potential Water Quality Changes

Ranasinghe, Sachini Madhusha
http://orcid.org/0000-0002-1251-2981
http://rave.ohiolink.edu/etdc/view?acc_num=kent1673052772273808

Abstract Details

2023, MS, Kent State University, College of Arts and Sciences / Department of Earth Sciences.
The Neuse River Estuary is a shallow open estuary located at the southern margin of the Albemarle-Pamlico Sound complex in North Carolina. Nutrient oversaturation due to the delivery of excessive nutrient-rich alluvial flux, weak tidal activity, and long water residence times have led to eutrophication and the growth of seasonal algal blooms. The problem has become more severe over the past few decades leading to many environmental and social health concerns. These outcomes emphasize the need for regular monitoring of phytoplankton, growth rate, water quality change, and control strategies. Satellite remote sensing studies provide a great solution for continuous water quality monitoring as a relatively cost-effective tool with high spatial and weekly to daily cloud-free temporal resolution. This research applies the Kent State University (KSU) Varimax-rotated Principal Component Analysis (VPCA) developed by Ortiz et al. (2013) to study the seasonal succession of phytoplankton and water quality parameters in the Neuse River Estuary by using Sentinel - 2 A/B Multi-Spectral Instrument (MSI) images from 2019 to 2021. The spectral signals in the water column were decomposed into six components using coherent, linearly correlated information in the visible and near-infrared spectral ranges. The components are then identified by comparing their spectral shape against standard spectral libraries. The study collaborated with the Neuse River Estuary Modeling and Monitoring program for the field-based water quality and cell count data, which was used in conjunction with remote sensing observations. We evaluated the applicability of the KSU VPCA method through a three-day average model. It identified two phytoplankton assemblages (Diatoms/Dinoflagellates/Chlorophytes and Cryptophytes) and two minerals (Goethite and Muscovite) that are successfully matched with the field observations. Secondly, we separated three phytoplankton-related (Dinoflagellates, Diatoms, and Chlorophyllide-b) and three mineral-based (Gypsum, Hematite, Chlorite) components by averaging multiple images over three years from 2019 to 2021 showing the fall to spring succession of phytoplankton in the Neuse Estuary. Results showed a dominant dinoflagellate population in the upper estuary, while diatoms dominated the lower estuary. Overall, phytoplankton density was low in winter but increased with the spring rainfall in response to nutrient flux delivered with alluvial input. The seasonal succession of the phytoplankton population was mainly controlled by the primary Neuse River channel input, while isolated small-scale blooms were influenced by nutrient input from tributaries. In conclusion, the KSU VPCA method was successful in identifying major phytoplankton groups, suspended minerals, and algal blooms with high spatial sensitivity. The temporal resolution of Sentinel- 2 derived products was significantly affected in summer due to intense cloud cover and the sun glint. The three-year averaging model showed a higher sensitivity to component identification than the three-day average model with greater statistical significance. We identified six critical factors that determine the output quality of remote sensing and KSU VPCA derived component identification in this optically complex coastal water body: cloud cover, sun glint, radiometric resolution, spatial resolution, the temporal resolution of the satellite sensor and the radiometric resolution of standard spectral libraries. With the hyperspectral sensors and detailed spectral standards, the KSU VPCA method can develop further as a powerful tool in aquatic remote sensing.
Joseph Ortiz, Prof (Advisor)
He Yin, Dr (Committee Member)
Allyson Tessin, Dr (Committee Member)
97 p.
Aquatic Sciences; Environmental Geology; Environmental Science; Geology
Aquatic Remote Sensing, Neuse River Estuary, Water Quality, Sentinel 2, KSU VPCA

Recommended Citations

Citations

  • Ranasinghe, S. M. (2023). Remote Sensing Monitoring of Neuse River Estuary for Potential Water Quality Changes [Master's thesis, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1673052772273808

    APA Style (7th edition)

  • Ranasinghe, Sachini. Remote Sensing Monitoring of Neuse River Estuary for Potential Water Quality Changes. 2023. Kent State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1673052772273808.

    MLA Style (8th edition)

  • Ranasinghe, Sachini. "Remote Sensing Monitoring of Neuse River Estuary for Potential Water Quality Changes." Master's thesis, Kent State University, 2023. http://rave.ohiolink.edu/etdc/view?acc_num=kent1673052772273808

    Chicago Manual of Style (17th edition)

kent1673052772273808
© 2022, some rights reserved.Creative Commons License Remote Sensing Monitoring of Neuse River Estuary for Potential Water Quality Changes by Sachini Madhusha Ranasinghe is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by Kent State University and OhioLINK.