Coastal salt marshes are heterogeneous, spatially complex ecosystems. The degree of hydrological connectivity in these systems can be a significant driver in the flux of energy, organisms, and nutrients across the marsh landscape. In tidally driven systems, the frequency and magnitude of hydrological connection events results in the creation of a matrix of intermittently connected coastal wetland habitats, some of which may be hydrologically isolated or partially drained at any given time. Previous approaches to understanding landscape-level hydrologic connectivity patterns have required either intensive long-term monitoring or spatially explicit modeling. In this paper, we first describe a 13-month field study in the Guadalupe Estuary of the Texas Gulf Coast that linked hydrological connectivity patterns between a saltwater pond to water levels in an adjacent tidal creek and nearby San Antonio Bay. We next describe the integration of these field data with high-resolution digital elevation models and environmental parameters to develop a spatially explicit model that is a Simulation of Landscape-level Oscillations in Salt Marsh Hydroperiod (SLOSH). We evaluated the ability of SLOSH to simulate trends in landscape-level patterns of hydrological connectivity between a tidal creek and an inland marsh pond. Magnitude and periodicity of simulated and observed water-level fluctuations in the pond were similar. Highest creek water levels, resulting in high frequency and duration of hydrological connectivity with the pond, corresponded with the highest bay water levels, which occurred during September and October. Lowest creek water levels, resulting in low frequency and duration of hydrological connectivity, corresponded with the lowest bay water levels, which occurred during December through February. By simulating the pulsing structure of salt marsh hydrology, SLOSH creates the foundation on which to assess how additional drivers (precipitation, wind, freshwater inflows, etc.) can influence coastal marsh hydrology and overall ecology.

© 2019 Todd M. Swannack, Jeffrey R. Wozniak, William E. Grant, and Stephen E. Davis III