A Delft3D morphodynamic model for Barataria Bay, Louisiana, USA is used to quantify a plausible range of land change in response to a proposed sediment diversion under a range of environmental drivers. To examine the influence of environmental drivers, such as Mississippi River water hydrographs, mineral and organic sediment loading, sea level rise rates, subsidence, and a projected implementation (or operation) date, 240 multi-decadal (2020–2100) numerical experiments were used. The diversion was assumed to begin operation in 2025, 2030, or 2035. The experiments revealed persistent benefits of the sediment diversion through 2100. Start data of 2025 result in a median net positive land change of 32 km² by 2100; whereas the 90th, and 10th percentiles are 69 and 10 km². A delay in the operation date of the diversion to 2030 or 2035 would reduce the net positive land change by approximately 15–20% and 20–30%, respectively.

Accelerating rates of global sea level rise (SLR) are a primary land loss driver today for coastal wetlands. Predictive models to anticipate rates and locations of land loss typically incorporate smoothed SLR projections that lack interannual variability. Here we utilize a biophysical numerical model to examine the impact of randomly generated sea-level variability derived from tide gauge observations on projections of wetland loss timing and magnitude to 2100 for a deltaic subbasin (Barataria Basin) of the Mississippi River Delta in Louisiana, USA. We demonstrate that periods of enhanced SLR rate that have been observed as a SLR hotspot on the US Atlantic and Gulf Coasts in recent decades can irreversibly accelerate land loss by several decades relative to state-of-the-art smooth SLR projections. These trends are even more negative when marsh edge erosion induced by storms is included in model projections. Our projections also demonstrate a limited or no ability of marsh ecotypes to backstep to accommodate these regional interannual accelerations. Our results emphasize the importance of (1) identifying other oceanographically linked regional hotspots in SLR, and (2) modifying SLR projections to accommodate this variability in coastal protection and restoration planning.