The fluxes of dissolved organic carbon (DOC) through tidal marsh‐influenced estuaries remain poorly quantified and have been identified as a missing component in carbon‐cycle models. The extreme variability inherent to these ecosystems of the land‐ocean interface challenge our ability to capture DOC‐concentration dynamics and to calculate accurate DOC fluxes. In situ discrete and continuous measurements provide high‐quality estimates of DOC concentration, but these strategies are constrained spatially and temporally and can be costly to operate. Here, field measurements and high‐spatial‐resolution remote sensing were used to train and validate a predictive model of DOC‐concentration distributions in the Plum Island Estuary (PIE), a mesotidal saltmarsh‐influenced estuary in Massachusetts. A large set of field measurements collected between 2017 and 2023 was used to develop and validate an empirical algorithm to retrieve DOC concentration with a ±15% uncertainty from Sentinel‐2 imagery. Implementation on 141 useable images produced a 6‐year time series (2017–2023) of DOC distributions along the thalweg. Analysis of the time series helped identify river discharge, tidal water level (WL), and a marsh enhanced vegetation index 2 as predictors of DOC distribution in the estuary, and facilitated the training and validation of a simple model estimating the distribution. This simple model was able to predict DOC along the PIE thalweg within ±16% of the in situ measurements. Implementation for three years (2020–2022) illustrated how this type of remote‐sensing‐informed models can be coupled with the outputs hydrodynamic models to calculate DOC fluxes in tidal marsh‐influenced estuaries and estimate DOC export to the coastal ocean.
This content will become publicly available on January 1, 2025
Abstract. Coastal marsh survival relies on the ability to increase elevation and offset sea level rise. It is therefore important to realistically model sediment fluxes between marshes, tidal channels, and bays as sediment availability controls accretion. Traditionally, numerical models have been calibrated and validated using in situ measurements at a few locations within the domain of interest. These datasets typically provide temporal information but lack spatial variability. This paper explores the potential of coupling numerical models with high-resolution remote sensing imagery. Products from three sensors from the NASA Delta-X airborne mission are used. Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) provides vertical water level change on the marshland and was used to adjust the bathymetry and calibrate water fluxes over the marsh. AirSWOT yields water surface elevation within bays, lakes, and channels, and was used to calibrate the Chezy bottom friction coefficient. Finally, imagery from AVIRIS-NG provides maps of total suspended solids (TSS) concentration that were used to calibrate sediment parameters of settling velocity and critical shear stress for erosion. Three numerical models were developed at different locations along coastal Louisiana using Delft3D. The coupling enabled a spatial evaluation of model performance that was not possible using simple point measurements. Overall, the study shows that calibration of numerical models and their general performance will greatly benefit from remote sensing.
more » « less- Award ID(s):
- 2224608
- PAR ID:
- 10507469
- Publisher / Repository:
- Biogeosciences Discussion
- Date Published:
- Journal Name:
- Biogeosciences
- Volume:
- 21
- Issue:
- 1
- ISSN:
- 1726-4189
- Page Range / eLocation ID:
- 241 to 260
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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