Articles | Volume 21, issue 1
Research article
16 Jan 2024
Research article |  | 16 Jan 2024

Coupling numerical models of deltaic wetlands with AirSWOT, UAVSAR, and AVIRIS-NG remote sensing data

Luca Cortese, Carmine Donatelli, Xiaohe Zhang, Justin A. Nghiem, Marc Simard, Cathleen E. Jones, Michael Denbina, Cédric G. Fichot, Joshua P. Harringmeyer, and Sergio Fagherazzi

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Cited articles

Allen, J., Somerfield, P., and Gilbert, F.: Quantifying uncertainty in high-resolution coupled hydrodynamic-ecosystem models, J. Mar. Syst., 64, 3–14,, 2007. a
Allison, M. A., Kineke, G. C., Gordon, E. S., and Goni, M. A.: Development and reworking of a seasonal flood deposit on the inner continental shelf off the Atchafalaya River, Cont. Shelf Res., 20, 2267–2294,, 2000. a
Balogun, A.-L., Yekeen, S. T., Pradhan, B., and Althuwaynee, O. F.: Spatio-temporal analysis of oil spill impact and recovery pattern of coastal vegetation and wetland using multispectral satellite landsat 8-OLI imagery and machine learning models, Remote Sens., 12, 1225,, 2020. a
Bates, P. D.: Flood inundation prediction, Annu. Rev. Fluid Mech., 54, 287–315,, 2022. a
Bevington, A. E. and Twilley, R. R.: Island edge morphodynamics along a chronosequence in a prograding deltaic floodplain wetland, J. Coast. Res., 34, 806–817,, 2018. a
Short summary
This study shows that numerical models in coastal areas can greatly benefit from the spatial information provided by remote sensing. Three Delft3D numerical models in coastal Louisiana are calibrated using airborne SAR and hyperspectral remote sensing products from the recent NASA Delta-X mission. The comparison with the remote sensing allows areas where the models perform better to be spatially verified and yields more representative parameters for the entire area.
Final-revised paper