Coastal wetlands provide a wealth of ecosystem services, including improved water quality, protection from storm surges, and wildlife habitat. Louisiana’s wetlands, however, are threatened by development, pollution, and relative sea level rise (RSLR)—the combination of sea level rise and subsidence rates. Despite widespread wetland loss, areas such as the Wax Lake and Atchafalaya river deltas are in fact growing due to their sediment loads, resulting in a complex of both degradation and aggradation along the Louisiana coast. In order to understand and model how coastal wetlands are responding to RSLR, there is a need for improved vegetation mapping, biomass estimation, and landscape-scale study of accretionary processes. AVIRIS-NG offers high spatial and spectral resolution data that can be integrated with external datasets—including from in situ measurements, monitoring stations, and other remote sensing platforms—to study these distributions and processes. Spectra derived from AVIRIS-NG imagery were used to parameterize Multiple Endmember Spectral Mixture Analysis (MESMA) for mapping vegetation functional types in addition to partial least squares regression (PLSR) models for plant aboveground biomass (AGB). The historical Landsat record complemented this analysis by deriving maps of change in wetland health and sediment availability through time. Each of these remotely sensed parameters were investigated to determine their combined relationship to Louisiana’s coastal accretion rates. In quantifying landscape-scale processes that impact wetland accretion, this research aids the assessment of coastal resiliency in the face of sea level rise. Further, the investigated imaging spectroscopy methods pertaining to vegetation mapping, biomass estimation, and accretionary modeling will inform future studies under the global Surface Biology and Geology mission.

Formed by Mississippi River sediments, south Louisiana is a flat, low-lying coastal region with high-clay content soils and heavy annual precipitation that is particularly susceptible to damage caused by extreme storms and flooding. In August 2016, a stationary storm system caused over 50 cm of rain to fall across much of southeast Louisiana. Largely rural, the major trends in the hard-hit Amite River Basin have been conversion of agricultural land to forest beginning in the mid-20th century and rapid urbanization and development spurred by economic and population growth in the Baton Rouge area following the oil boom of the 1970s, as well as later waves of migration following Hurricane Katrina and the 2016 floods. This analysis examines the effects of spatially and temporally changing land use on runoff and flooding within the watershed and is part of a larger research project which seeks to also quantify the relative impacts of changes in precipitation and planform geometry. To quantify the effects of land-use change on flooding, runoff curve number (CN) maps were created using NRCS soil type data and USGS land cover data. Areas with a higher CN experience less interception and infiltration of surface water and the flood risk is consequently greater. While CN for the Basin overall dropped from 86 to 79 between 1938 and 2018, CN dropped from 82 to 70 in rural areas due to reforestation and increased from 86 to 90 in the southern portion of the Basin due to urbanization. These data were then input into the HEC-HMS and coupled 1D/2D HEC-RAS components of a numerical model of the Amite River Basin. Flooding behavior under different design storms and land cover conditions was then observed and quantified. In examining the major contributing factors to flooding in south Louisiana, this research project aims to create a more comprehensive understanding of flooding and propose potential mitigation strategies and design interventions for alleviating the worst effects.