Hydrological connectivity in coastal deltas is important for delivering flow, sediment, and nutrients to the island interiors. The roughness of island vegetation limits connectivity, but how important is the spatial distribution of vegetation? Using hydrodynamic modeling, we test the influence of vegetated percent cover, patch size, and stem density on the discharge-fraction allocated to the islands of an idealized delta complex, modeled after Wax Lake Delta. We find that heterogeneity has negligible effects when vegetation is relatively sparse but is important when vegetation is relatively dense and covers less than a "disconnectivity" threshold of 40-50% of the islands, near the theoretical percolation limit. Below this threshold, preferential flow paths develop in the islands, which alter the hydraulics and residence time distribution of the delta complex and enhance potential sediment transport with respect to model runs with uniform vegetation. Patchiness has hydrogeomorphic and biogeochemical implications, which should be considered when modeling deltaic systems.Plain Language Summary Coastal river deltas are vulnerable regions of tremendous economic and ecological importance. The long-term sustainability of deltaic systems depends in part on the delivery of water, sediment, and nutrients to the interior of deltaic islands. The vegetated wetlands within these islands are typically hot spots of land growth and biological nutrient removal, which can counteract land loss and prevent the expansion of coastal oxygen-depleted zones. Increasing the amount of island vegetation is known to decrease the fraction of flow that enters the islands, but it has yet to be shown how the spatial arrangement of vegetation patches affects this channel-island "hydrological connectivity." In the present study, we numerically model flows in a simplified river delta to determine the influence of three vegetation characteristics on connectivity: the percentage of the island covered by patches, patch size, and patch density (how tightly packed the vegetation is within each patch). We find that all three characteristics can increase connectivity when compared to similar model runs with spatially uniform vegetation. More specifically, the spatial configuration becomes important when patches are dense and cover less than 40-50% of the deltaic islands. The results of this study have implications for our ability to model the success of restoration projects.

Hydrologic connectivity controls the lateral exchange of water, solids, and solutes between rivers and floodplains, and is critical to ecosystem function, water treatment, flood attenuation, and geomorphic processes. This connectivity has been well‐studied, typically through the lens of fluvial flooding. In regions prone to heavy rainfall, the timing and magnitude of lateral exchange may be altered by pluvial flooding on the floodplain. We collected measurements of flow depth and velocity in the Trinity River floodplain in coastal Texas (USA) during Tropical Storm Imelda (2019), which produced up to 75 cm of rainfall locally. We developed a two‐dimensional hydrodynamic model at high resolution for a section of the Trinity River floodplain inspired by the compound flooding of Imelda. We then employed Lagrangian particle routing to quantify how residence times and particle velocities changed as flooding shifted from rainfall‐driven to river‐driven. Results show that heavy rainfall initiated lateral exchange before river discharge reached flood levels. The presence of rainwater also reduced floodplain storage, causing river water to be confined to a narrow corridor on the floodplain, while rainwater residence times were increased from the effect of high river flow. Finally, we analyzed the role of floodplain channels in facilitating surface‐water connectivity by varying model resolution in the floodplain. While the resolution of floodplain channels was important locally, it did not affect as much the overall floodplain behavior. This study demonstrates the complexity of floodplain hydrodynamics under conditions of heavy rainfall, with implications for sediment deposition and nutrient removal during floods.

Due to widespread advancements in computing power and accessibility in the 21st century, researchers studying the Earth's surface are now able to probe questions regarding the movement of matter and energy through landscapes at unprecedented scales and resolution. The availability of remote sensing imagery and physics-based numerical models have revolutionized the study of large-scale geophysical systems (Balsamo et al., 2018), and enabled simulation of full-scale experiments regarding the effects of different processes on the function and form of landscapes. A number of numerical models have been developed to study the movement of water, sediment, and other materials using finite-volume (FVM) and finite element (FEM) approaches, and hydrodynamic models in particular have proven to be useful tools for advancing our understanding of hydrological transport

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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.