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| Type: | Resource | |
| Storage: | The size of this resource is 1.2 MB | |
| Created: | Aug 07, 2024 at 10:18 p.m. | |
| Last updated: | Sep 10, 2024 at 2:31 p.m. | |
| DOI: | 10.4211/hs.5ee190b481c749fb8398f182742720f1 | |
| Citation: | See how to cite this resource | |
| Content types: | Single File Content |
| Sharing Status: | Published |
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Abstract
This dataset contains Acoustic Doppler Current Profiler (ADCP) data collected near Erie, PA, in Lake Erie during the summer of 2019. The ADCP was deployed in an upward-looking configuration from August 9 to September 9, 2019, at a depth of 5.80 meters, and it recorded 3D water velocities and temperatures. The data collection aimed to support assessments of Cladophora and benthic algae and to validate hydrodynamic models in the region. The deployment location is specified at 42.18863 degrees north latitude and -79.98218 degrees west longitude. The U.S. Environmental Protection Agency funded this project under the Great Lakes Restoration Initiative, with the U.S. Geological Survey (USGS) and Michigan State University (MSU) conducting the data collection, processing, and quality assurance. Data quality was ensured through rigorous checks, with velocity measurement accuracy at 1% of the measured value, and temperature sensor accuracy at ±0.1 ℃. This dataset provides valuable insights for environmental and hydrodynamic studies in Lake Erie, contributing to a better understanding of water flow patterns and temperature variations essential for ecological assessments and management practices.
The ADCP data was used in the following paper:
Saeed Memari, Mantha S. Phanikumar, Vishnu Boddeti, Narendra Das; Turbidity assessment in coastal regions combining machine learning, numerical modeling, and remote sensing. Journal of Hydroinformatics 2024; jh2024110. doi: https://doi.org/10.2166/hydro.2024.110
Subject Keywords
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Content
readme.txt
Title: Acoustic Doppler Current Profiler (ADCP) data collected near Erie, PA, Lake Erie, 2019 Description: This dataset contains data collected from a bottom-deployed, upward-looking Acoustic Doppler Current Profiler (ADCP, 2.0 MHz Nortek Aquadopp HR Profiler) deployed in Erie, PA, during the summer of 2019. The ADCP recorded 3D water velocities from early August until early September 2019. Additionally, water temperature at the depth of the ADCP deployment was recorded during this period. Data Variables and Descriptions: Year: Year of the data point measurement. Month: Month of the data point measurement (Eastern Standard Time). Day: Day of the data point measurement. Hour: Hour of the data point measurement. Minute: Minute of the data point measurement. Second: Second of the data point measurement. Temperature: Water temperature recorded by the ADCP at the deployment depth (°C). U Velocity Components (u_1.21 m to u_5.21 m): Eastward water velocity components at varying depths from 1.21 meters to 5.21 meters (m/s). V Velocity Components (v_1.21 m to v_5.21 m): Northward water velocity components at varying depths from 1.21 meters to 5.21 meters (m/s). W Velocity Components (w_1.21 m to w_5.21 m): Vertical water velocity components at varying depths from 1.21 meters to 5.21 meters (m/s). Measurement Units and Resolution: Temperature: °C, resolution of 0.1°C. Velocity Components (U, V, W): Meters per second (m/s), resolution of 0.005 m/s. System/Setup Information: Cell Size (depth cell size): 0.25 m Blank (blanking distance): 0.46 m First Cell Range: 0.46 m Number of Cells: 9 Beam Angle: 20 degrees Data Collection Details: The ADCP was configured to collect data at specific depth intervals, capturing both horizontal (U, V) and vertical (W) velocity components. The setup information includes the measurement cell size, blanking distance, and beam angle, which are critical for interpreting the data accurately. Deployment and Data Usage: This dataset can be used to analyze water currents, temperature variations, and other hydrodynamic parameters in the deployment area during the specified period. The data can support studies in physical oceanography, sediment transport, and environmental monitoring. Contact Information: For questions or additional information about this dataset, please contact Saeed Memari at memarisa@msu.edu.
Related Resources
| This resource is referenced by | Saeed Memari, Mantha S. Phanikumar, Vishnu Boddeti, Narendra Das; Turbidity assessment in coastal regions combining machine learning, numerical modeling, and remote sensing. Journal of Hydroinformatics 2024; jh2024110. doi: https://doi.org/10.2166/hydro.2024.110 |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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