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Title: Measuring Estuarine Total Exchange Flow From Discrete Observations
Abstract

The exchange between estuaries and the coastal ocean is a key dynamical driver impacting nutrient and phytoplankton concentrations and regulating estuarine residence time, hypoxia, and acidification. Estuarine exchange flows can be particularly challenging to monitor because many systems have strong vertical and lateral velocity shear and sharp gradients in water properties that vary over space and time, requiring high‐resolution measurements in order to accurately constrain the flux. The total exchange flow (TEF) method provides detailed information about the salinity structure of the exchange, but requires observations (or model resolution) that resolve the time and spatial co‐variability of salinity and currents. The goal of this analysis is to provide recommendations for measuring TEF with the most efficient spatial sampling resolution. Results from three realistic hydrodynamic models were investigated. These model domains included three estuary types: a bay (San Diego Bay), a salt‐wedge (Columbia River), and a fjord (Salish Sea). Model fields were sampled using three different mooring strategies, varying the number of mooring locations (lateral resolution) and sample depths (vertical resolution) with each method. The exchange volume transport was more sensitive than salinity to the sampling resolution. Most (>90%) of the exchange flow magnitude was captured by three to four moorings evenly distributed across the estuarine channel with a minimum threshold of 1–5 sample depths, which varied depending on the vertical stratification. These results can improve our ability to observe and monitor the exchange and transport of water masses efficiently with limited resources.

 
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Award ID(s):
2122420
NSF-PAR ID:
10376605
Author(s) / Creator(s):
 ;  ;  ;  ;  
Publisher / Repository:
DOI PREFIX: 10.1029
Date Published:
Journal Name:
Journal of Geophysical Research: Oceans
Volume:
127
Issue:
10
ISSN:
2169-9275
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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