Tidal marshes serve as important “blue carbon” ecosystems that sequester large amounts of carbon with limited area. While much attention has been paid to the spatial variability of sedimentation within salt marshes, less work has been done to characterize spatial variability in marsh soil carbon density. Soil properties in marshes vary spatially with several parameters, including marsh platform elevation, which controls inundation depth, and proximity to the marsh edge and tidal creek network, which control variability in relative sediment supply. We used lidar to extract these morphometric parameters from tidal marshes to map soil organic carbon at the meter scale. Fixed volume soil samples were collected in 2021 at four northeast U.S. tidal marshes with distinctive morphologies to aid in building predictive models. Tidal creeks were delineated from 1-m resolution topobathy lidar data using a semi-automated workflow in GIS. Log-linear multivariate regression models were developed to predict soil organic content, bulk density, and carbon density as a function of predictive metrics at each site and across sites. Results show that modeling salt marsh soil characteristics with morphometric inputs works best in marshes with single connected creek network morphologies. Distance from tidal creeks was the most significant model predictor. Addition of distance to the inlet and tidal range as regional metrics significantly improves cross-site modeling. Our mechanistic approach results in predicted total marsh carbon stocks comparable to previous studies but captures important meter level variation. Further, we provide motivation to continue rigorous mapping of soil carbon at fine spatial resolutions.

Astronomical variations in tidal magnitude can strongly modulate the severity of coastal flooding on daily, monthly, and interannual timescales. Here, we present a new quasi-nonstationary skew surge joint probability method (qn-SSJPM) that estimates interannual fluctuations in flood hazard caused by the 18.6 and quasi 4.4-year modulations of tides. We demonstrate that qn-SSJPM-derived storm tide frequency estimates are more precise and stable compared with the standard practice of fitting an extreme value distribution to measured storm tides, which is often biased by the largest few events within the observational period. Applying the qn-SSJPM in the Gulf of Maine, we find significant tidal forcing of winter storm season flood hazard by the 18.6-year nodal cycle, whereas 4.4-year modulations and a secular trend in tides are small compared to interannual variation and long-term trends in sea-level. The nodal cycle forces decadal oscillations in the 1% annual chance storm tide at an average rate of ±13.5 mm/y in Eastport, ME; ±4.0 mm/y in Portland, ME; and ±5.9 mm/y in Boston, MA. Currently (in 2020), nodal forcing is counteracting the sea-level rise-induced increase in flood hazard; however, in 2025, the nodal cycle will reach a minimum and then begin to accelerate flood hazard increase as it moves toward its maximum phase over the subsequent decade. Along the world’s meso-to-macrotidal coastlines, it is therefore critical to consider both sea-level rise and tidal non-stationarity in planning for the transition to chronic flooding that will be driven by sea-level rise in many regions over the next century.

Non-linear turbidity-discharge relationships are explored in the context of sediment sourcing and event-driven hysteresis using long-term (≥12 year) turbidity observations from the tidal freshwater and saline estuary of the Hudson River. At four locations spanning 175 km, turbidity generally increased with discharge but did not follow a constant log-log dependence, in part due to event-driven adjustments in sediment availability. Following major sediment inputs from extreme precipitation and discharge events in 2011, turbidity in the tidal river increased by 20-50% for a given discharge. The coherent shifts in the turbidity-discharge relationship along the tidal river over the subsequent 2 years suggest that the 2011 events increased sediment availability for resuspension. In the saline estuary, changes in the sediment-discharge relationship were less apparent after the high discharge events, indicating that greater background turbidity due to internal sources make event-driven inputs less important in the saline estuary at interannual time scales.

Observations and modeling are used to assess potential impacts of sediment releases due to dam removals on the Hudson River estuary. Watershed sediment loads are calculated based on sediment-discharge regressions for gauges covering 80% of the watershed area. The annual average sediment load to the estuary is 1.2 Mt, of which about 0.6 Mt comes from tributaries entering below the head of tides. Sediment yield varies inversely with watershed area, with regional trends that are consistent with differences in substrate erodibility. Geophysical and sedimentological surveys in five subwatersheds of the Lower Hudson were conducted to characterize the mass and composition of sediment trapped behind dams. Impoundments were classified as 1) active sediment traps, 2) run-of-river sites not actively trapping, and 3) dammed natural lakes and spring-fed ponds. Based on this categorization and impoundment attributes from the dam inventory database, the total mass of impounded sediment in the Lower Hudson watershed is estimated as 3.1 Mt. Assuming that roughly half of the impounded sediment is typically released downstream with dam removal, then the potential inputs represent less than 2 years of annual watershed supply. Modeling of simulated dam removals shows that modest suspended sediment increases occur in the estuary within about a tidal excursion of the source tributary, primarily during discharge events. Transport in the estuary depends strongly on settling velocity, but fine particles, which are important for accretion in tidal wetlands, deposit broadly along the estuary rather than primarily near the source.