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During a storm, as the beach profile is impacted by increased wave forcing and rapidly changing water levels, sand berms may help mitigate erosion of the backshore. However, the mechanics of berm morphodynamics have not been fully described. In this study, 26 trials were conducted in a large wave flume to explore the response of a near‐prototype berm to scaled storm conditions. Sensors were used to quantify hydrodynamics, sheet flow dynamics, and berm evolution. Results indicate that berm overtopping and offshore sediment transport were key processes causing berm erosion. During the morphological evolution of the beach profile, two sand bars were formed offshore that attenuated subsequent wave energy. The landward extent of that energy was confined to the seaward foreshore, inhibiting inundation of the backshore. Net offshore‐directed transport was dominant when infragravity motions increased in the swash zone. Conversely, the influence of incident‐band motions on sediment transport was relatively greater in the inner‐surf zone. Near‐bed flow velocities and sheet flow layer thicknesses were larger in the swash zone than in the inner‐surf zone. This paper also provides a valuable analysis between morphology‐estimated total sediment transport rates and rates derived from in situ measurements. Sheet flow dynamics dominated foreshore cross‐shore sediment processes, constituting the largest portion of the total sediment transport load throughout the berm erosion.

We mapped tidal wetland gross primary production (GPP) with unprecedented detail for multiple wetland types across the continental United States (CONUS) at 16‐day intervals for the years 2000–2019. To accomplish this task, we developed the spatially explicit Blue Carbon (BC) model, which combined tidal wetland cover and field‐based eddy covariance tower data into a single Bayesian framework, and used a super computer network and remote sensing imagery (Moderate Resolution Imaging Spectroradiometer Enhanced Vegetation Index). We found a strong fit between the BC model and eddy covariance data from 10 different towers (r²= 0.83,p< 0.001, root‐mean‐square error = 1.22 g C/m²/day, average error was 7% with a mean bias of nearly zero). When compared with NASA's MOD17 GPP product, which uses a generalized terrestrial algorithm, the BC model reduced error by approximately half (MOD17 hadr²= 0.45,p< 0.001, root‐mean‐square error of 3.38 g C/m²/day, average error of 15%). The BC model also included mixed pixels in areas not covered by MOD17, which comprised approximately 16.8% of CONUS tidal wetland GPP. Results showed that across CONUS between 2000 and 2019, the average daily GPP per m²was 4.32 ± 2.45 g C/m²/day. The total annual GPP for the CONUS was 39.65 ± 0.89 Tg C/year. GPP for the Gulf Coast was nearly double that of the Atlantic and Pacific Coasts combined. Louisiana alone accounted for 15.78 ± 0.75 Tg C/year, with its Atchafalaya/Vermillion Bay basin at 4.72 ± 0.14 Tg C/year. The BC model provides a robust platform for integrating data from disparate sources and exploring regional trends in GPP across tidal wetlands.