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Wetland shorelines around the world are susceptible to wave erosion. Previous work has suggested that the lateral erosion rate of their cliff-like edges can be predicted as a function of intercepting waves, and yet numerous field studies have shown that other factors, for example, tidal currents or mass wasting of differing soil types, induce a wide range of variability. Our objective was to isolate the unique effects of wave heights, wavelengths, and water depths on lateral erosion rates and then synthesize a mechanistic understanding that can be applied globally. We found a potentially universal relationship, where the lateral erosion rates increase exponentially as waves increase in height but decrease exponentially as waves become longer in length. These findings suggest that wetlands and other sheltered coastlines likely experience outsized quantities of erosion, as compared to oceanic-facing coastlines. 

A broadly accepted paradigm is that vegetation reduces coastal dune erosion. However, we show that during an extreme storm event, vegetation surprisingly accelerates erosion. In 104-m-long beach-dune profile experiments conducted within a flume, we discovered that while vegetation initially creates a physical barrier to wave energy, it also (i) decreases wave run-up, which creates discontinuities in erosion and accretion patterns across the dune slope, (ii) increases water penetration into the sediment bed, which induces its fluidization and destabilization, and (iii) reflects wave energy, accelerating scarp formation. Once a discontinuous scarp forms, the erosion accelerates further. These findings fundamentally alter the current understanding of how natural and vegetated features may provide protection during extreme events. 

Coastal risk reduction features are often built to protect infrastructure and ecosystems from damaging waves, sea level rise, and shoreline erosion. Engineers often use predictive numerical modeling tools, such as Delft3D to help design optimal intervention strategies. Still, their use by coastal managers for optimizing the design of living shorelines in complex geomorphic environments has been limited. In this study, the Delft3D modeling suite is used to help select the optimum living shoreline structure for a complex inlet and bay system at Carancahua Bay, Texas. To achieve this goal, an extensive array of sensors was deployed to collect hydrodynamic and geotechnical data in the field, and historical shoreline changes were assessed using image analysis. The measured data were then used to parameterize and validate the baseline Delft3D model. Using this validated model, the hydrodynamics resulting from a series of structural alternatives were simulated and compared. The results showed that the mouth of this complex inlet has widened greatly since the 1800s due to wave erosion and sea level rise. The analysis of the structural alternatives showed it was not advisable to attempt a return of the inlet to its historical extent, but rather to create a hybrid design that allowed for limited flow to continue through a secondary inlet. The numerical modeling effort helped to identify how to best reduce wave and flow energy. This study provides a template for the application of Delft3D as a tool for living shoreline design selection under complex shallow-estuary and inlet dynamics. 

Abstract Tropical cyclones play an increasingly important role in shaping ecosystems. Understanding and generalizing their responses is challenging because of meteorological variability among storms and its interaction with ecosystems. We present a research framework designed to compare tropical cyclone effects within and across ecosystems that: a) uses a disaggregating approach that measures the responses of individual ecosystem components, b) links the response of ecosystem components at fine temporal scales to meteorology and antecedent conditions, and c) examines responses of ecosystem using a resistance–resilience perspective by quantifying the magnitude of change and recovery time. We demonstrate the utility of the framework using three examples of ecosystem response: gross primary productivity, stream biogeochemical export, and organismal abundances. Finally, we present the case for a network of sentinel sites with consistent monitoring to measure and compare ecosystem responses to cyclones across the United States, which could help improve coastal ecosystem resilience.