EARLY HEARING DETECTION AND INTERVENTION VIRTUAL CONFERENCE
MARCH 2-5, 2021
(Virtually the same conference, without elevators, airplane tickets, or hotel room keys)
5/25/2021 | 2:00 PM - 3:30 PM | COUPLING HIGH-FREQUENCY SENSING AND 2-D NUMERICAL MODELLING TO ANALYZE NITRATE DYNAMICS IN A LARGE RIVER | Virtual Platform
COUPLING HIGH-FREQUENCY SENSING AND 2-D NUMERICAL MODELLING TO ANALYZE NITRATE DYNAMICS IN A LARGE RIVER
Effective management of water quality requires a detailed understanding of how point-source nitrate pollution is dispersed and cycled in large rivers. While numerical models have been helpful, the reliability of model predictions is limited by the quality of calibration data, which is rarely recorded at the same temporal frequencies at which cycling and dispersion occur. In this study, we integrate 15-minute nitrate data from four sensors along a 33 km stretch of the Kansas River, the world’s largest prairie river. During a six-month period, nitrogen waste was strategically released by local authorities into the Kansas River, providing a unique contamination event. We utilized this event and the associated sensing data to simulate the dispersion and cycling of nitrogen in the river using an unsteady 2-D ecohydraulics model. Numerical model results validate sensing data and indicate an elevated degree of uptake and lateral turbulent mixing in response to the waste release. Further, calibrating model performance with high-frequency data helped simulate dispersion and cycling at novel timescales not possible with traditional grab-sampling. Our study demonstrates the utility of sensors and modeling to transform our understanding of nitrate dynamics in rivers.
- Flow
- Models
- Nutrient cycling
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Presenters/Authors
AMIRREZA ZARNAGHSH
(), University of Kansas, azarnaghsh@ku.edu;
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Michelle Catherine Kelly
(), Michigan Technological University, mckelly1@mtu.edu;
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Admin Husic
(), University of Kansas, ahusic@ku.edu;
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Amy Burgin
(), University of Kansas, burginam@ku.edu;
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