ASSESSING THE IMPACTS OF SURFACE HYDROLOGY ON THE SPATIOTEMPORAL VARIABILITY IN WETLAND ELEVATION DYNAMICS IN COASTAL LOUISIANA

Coastal Louisiana is rapidly losing land due to high rates of sea-level rise and compaction-driven subsidence that are not balanced by vertical accretion of coastal wetlands. Surface elevation change measurements are used for indirectly estimating subsidence rates; however, rates of surface elevation change are highly variable through space and time. To effectively forecast trends in coastal land loss and inform coastal restoration efforts, it is necessary to characterize the processes that impact variability in surface elevation change measurements. At 390 sites, we estimated average trends and temporal variability in (a) water depth to marsh, (b) salinity change and (c) surface elevation measurements using data collected by the Coastwide Reference Monitoring System. On average, we observe an increase in measured surface elevation at 85.8% of the sites, an increase in water depth to marsh 80% of the sites, and a decrease in salinity at 77% of the sites. Decreasing average salinity coupled with increasing average water depths suggest that freshwater fluxes are increasing through time.

We used the 10th, 25th, 75th, and 90th percentiles of the distributions of residuals to characterize temporal variability. The rates change in surface elevation, water depth to marsh and salinity at individual sites impact the observed temporal variability in each set of measurements. Absolute values of the 10th, 25th, 75th and 90th percentiles of residuals correlate positively with rates of change. Further, measured temporal variability in surface elevation change correlates positively with variability in water elevation to marsh and in salinity. While surface elevation change rates may be significantly influenced by subsurface compaction rates, these findings suggest that surface hydrology plays an important role in the observed temporal variability in surface elevation. Furthermore, the observed correlation between rates of change and temporal variability in recorded measurements underscores the necessity of characterizing spatiotemporal variability in addition to the commonly used average rates to forecast future states and extreme events in non-stationary coastal systems like Louisiana.