Coastal wetlands are nourished by rivers and periodical tidal flows through complex, interconnected channels.However, in hydrodynamic models, channel dimensions with respect to model grid size and uncertainties in topography preclude the correct propagation of tidal and riverine signals. It is therefore crucial to enhance channel geomorphic connectivity and simplify sub-channel features based on remotely-sensed networks for practical computational applications. Here, we utilize channel networks derived from diverse remote sensing imagery as a baseline to build a ~10 m resolution hydrodynamic model that covers the Wax Lake Delta and adjacent wetlands (~ 360 km 2 ) in coastal Louisiana, USA. In this richly-gauged system, intensive calibrations are conducted with 18 synchronous field-observations of water levels taken in 2016, and discharge data taken in 2021. We modify channel geometry, targeting realism in channel connectivity. The results show that a minimum channel depth of 2 m and a width of four grid elements (approximatively 40m) are required to enable a realistic tidal propagation in wetland channels. The optimal depth for tidal propagation can be determined by a simplified cost function method that evaluates the competition between flow travel time and alteration of the volume of the channels. The integration of high spatial-resolution models and remote sensing imagery provides a general framework to improve models performance in salt marshes, mangroves, deltaic wetlands, and tidal flats.

Abstract. Coastal marsh survival relies upon to their ability to increase their elevation and offset sea level rise. It is therefore fundamental to realistically model the sediment fluxes between marshes, tidal channels and bays. Traditionally, numerical models have been calibrated and validated using in-situ measurements located in 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 recent NASA Delta-X airborne mission are used. UAVSAR provides vertical water level change on the marshland, and was used to adjust the bathymetry and calibrate the 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 provide 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 and scales along coastal Louisiana using Delft3D. The coupling enabled a spatial evaluation of model performance not possible using simple point measurements. Some limitations were highlighted in the remote sensing imagery and the numerical models that need to be accounted for when comparing the results. Overall, the study shows that calibration of numerical models and their general quality will greatly benefit from remote sensing.

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