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High Resolution Mapping of Nitrate Loads of a Reservoir Using an Uncrewed Surface Vehicle: 2 Potential opportunities and Challenges
  • +3
  • Kwang-Hun Lee,
  • Shahid Ali,
  • Yena Kim,
  • Kitack Lee,
  • Sae Yun Kwon,
  • Jonghun Kam
Kwang-Hun Lee
Division of Environmental Science and Engineering, Pohang University of Science and 9 Technology
Shahid Ali
Division of Environmental Science and Engineering, Pohang University of Science and 9 Technology
Yena Kim
Division of Environmental Science and Engineering, Pohang University of Science and 9 Technology
Kitack Lee
Institute for Convergence Research and Education in Advance Technology, Yonsei University, Pohang University of Science and Technology
Sae Yun Kwon
Division of Environmental Science and Engineering, Pohang University of Science and 9 Technology, Institute for Convergence Research and Education in Advance Technology, Yonsei University, Pohang University of Science and Technology
Jonghun Kam
Division of Environmental Science and Engineering, Pohang University of Science and 9 Technology, Institute for Convergence Research and Education in Advance Technology, Yonsei University, Pohang University of Science and Technology

Corresponding Author:[email protected]

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Abstract

Reliable nutrient load estimation of a reservoir is challenging due to inconsistent spatial extent and temporal frequency of water quality and quantity. This study aims to collect consistent spatial extent and temporal frequency of water depths and nitrate concentrations of a reservoir in South Korea using uncrewed surface vehicle (USV). In this study, reservoir nitrate loads were estimated using four methods to examine how spatial variation in water depth and nitrate concentrations affected load estimates. Based on dual measurements of water depth and nitrate concentration, reservoir nitrate loads across 30 sampling dates (0.7 million tons of fresh water on average) ranged from one to four tons. Results showed that a point measurement of water depths and nitrate concentrations can cause up to -17% of underestimation of nitrate loads, particularly after intense rainfall events. This study highlights potential opportunities and  challenges of the USV-based dual monitoring systems for water quality and quantity.
30 Oct 2023Submitted to ESS Open Archive
03 Nov 2023Published in ESS Open Archive