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Developing accurate landscape‐scale aboveground biomass (AGB) maps is critical to understanding coastal deltaic wetland resilience, as AGB influences stability and elevation dynamics in herbaceous wetlands. Here we used AVIRIS‐NG imaging spectrometer (or "hyperspectral") data from NASA's 2021 Delta‐X mission in coastal Louisiana to map seasonal changes in herbaceous AGB across two deltaic basins with contrasting sediment delivery and hydrologic regimes: the Atchafalaya (active) and Terrebonne (inactive). We assessed the impact of atmospheric effects on our retrievals, as high water vapor content in August 2021 caused significant noise in the 880–1,000 and 1,080–1,200 nm near‐infrared (NIR) wavelengths. We hypothesized that correcting these wavelengths with our conditional Gaussian interpolation algorithm would improve AGB estimates due to their association with plant canopy water content. We empirically assessed the performance of the corrected spectra on AGB estimates using Partial Least Squares Regression (PLSR), finding that the corrected NIR bands attained high variable importance and reduced estimation errors. Our Random Forest regression approach based on the corrected spectra attained equivalent error metrics via leave‐one‐out‐cross‐validation as the PLSR models (R2 = 0.43, mean absolute error = 257.3 g/m2) while greatly improving the AGB maps' visual quality, having better captured variability while reducing noise and discontinuities in AGB estimates across flightlines. The maps show differing seasonal growth, with the Atchafalaya and Terrebonne Basins' AGB increasing from means of 4.3–9.4 and 4.6–8.9 Mg/ha, respectively. We demonstrated that imaging spectroscopy can be applied to assess herbaceous biomass stocks, growth patterns, and resilience in coastal ecosystems. Plain Language Summary: Developing accurate landscape‐scale aboveground biomass (AGB) maps is critical to understanding the sustainability of coastal deltaic systems, as plant biomass aids in a wetland maintaining its elevation in the face of relative sea level rise. Here we use imaging spectroscopy, or "hyperspectral" remote sensing, to map wetland biomass across seasons in coastal Louisiana. In doing so, we correct for the noise caused by high atmospheric water vapor content in important infrared bands, thereby improving our biomass models. We test empirical and machine learning models for estimating wetland biomass, determining that a machine learning regression model using our corrected data delivers the best model metrics and map quality. We thus map AGB in April and August 2021, across the Atchafalaya and Terrebonne Basins. Our maps show various seasonal growth patterns, with the Atchafalaya and Terrebonne Basins' herbaceous AGB increasing from means of 4.3–9.4 and 4.6–8.9 Mg/ha, respectively. Key Points: We developed an interpolation algorithm to correct noise in near‐infrared bands that improved wetland aboveground biomass (AGB) estimatesWe assessed model approaches and mapped wetland AGB in coastal Louisiana with a machine learning algorithm for March and August 2021The active Atchafalaya and inactive Terrebonne Basins' AGB increased from means of 4.3–9.4 and 4.6–8.9 Mg/ha, respectively [ABSTRACT FROM AUTHOR]

• A total wetland extent of 2950 km2 was mapped during a period of peak biomass in September 2017 for the coastal wetlands of southern Louisiana • The mapped extent demonstrated considerable differences (793.7 km2) from currently available estimates of wetland area. • Total herbaceous biomass at the study site was estimated at 1,396,969.2 Mg during a period of peak biomass and total woody vegetation biomass was estimated at 27,667,232.1 Mg. • Herbaceous biomass increased by 108.9% between a period of low to high biomass, underlining the dynamic nature of the wetlands and the influence of seasonality on wetland function. [ABSTRACT FROM AUTHOR]

Aboveground biomass (AGB) plays a critical functional role in coastal wetland ecosystem stability, with high biomass vegetation contributing to organic matter production, sediment accretion potential, and the surface elevation's ability to keep pace with relative sea level rise. Many remote sensing studies have employed either imaging spectrometer or synthetic aperture radar (SAR) for AGB estimation in various environments for assessing ecosystem health and carbon storage. This study leverages airborne data from NASA's Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) to assess their unique capabilities in combination to estimate AGB in coastal deltaic wetlands. Here we develop AGB models for emergent herbaceous and forested wetland vegetation in coastal Louisiana. In addition to horizontally emitted, vertically received (HV) backscatter, SAR parameters are expressed by the Freeman–Durden polarimetric decomposition components representing volume and double-bounce scattering. The imaging spectrometer parameters include normalized difference vegetation index (NDVI), reflectance from 290 visible-shortwave infrared (VSWIR) bands, the first derivatives from those bands, or partial least squares (PLS) x-scores derived from those data. Model metrics and cross-validation indicate that the integrated models using the Freeman-Durden components and PLS x-scores improve AGB estimates for both wetland vegetation types. In our study domain over Louisiana's Wax Lake Delta (WLD), we estimated a mean herbaceous wetland AGB of 3.58 Megagrams/hectare (Mg/ha) and a total of 3551.31 Mg over 9.92 km2, and a mean forested wetland AGB of 294.78 Mg/ha and a total of 27,499.14 Mg over 0.93 km2. While the addition of SAR-derived values to imaging spectrometer data provides a nominal error decrease for herbaceous wetland AGB, this combination significantly improves forested wetland AGB prediction. This integrative approach is particularly effective in forested wetlands as canopy-level biochemical characteristics are captured by the imaging spectrometer in addition to the variable structural information measured by the SAR. [ABSTRACT FROM AUTHOR]

Abstract: By transforming fixed nitrogen (N) into nitrogen gas, the biochemical processes that support denitrification provide a function critical to maintaining the integrity of ecosystems subjected to increased loading of N from anthropogenic sources. The Louisiana coastal region receives high nitrate (NO3 −) concentrations (>100µM) from the Mississippi–Ohio–Missouri River Basin and is also an area undergoing high rates of wetland loss. Ongoing and anticipated changes in the Louisiana coastal region promise to alter biogeochemical cycles including the net rate of denitrification by ecosystems. Projecting what these changes could mean for coastal water quality and natural resources requires an understanding of the magnitude and patterns of variation in denitrification rates and their connection to estuarine water quality at large temporal and spatial scales under current conditions. We compile and review denitrification rates reported in 32 studies conducted in a variety of habitats across coastal Louisiana during the period 1981– 2008. The acetylene inhibition and 15N flux were the preferred techniques (95%); most of the studies used sediment slurries rather than intact sediment cores. There are no estimates of denitrification rates using the N2/Ar ratio and isotope pairing techniques, which address some of the problems and limitations of the acetylene inhibition and 15N flux techniques. These studies have shown that sediments from estuaries, lakes, marshes, forested wetlands, and the coastal shelf region are capable of high potential denitrification rates when exposed to high NO3 − concentrations (>100µM). Maximum potential denitrification rates in experimental and natural settings can reach values >2500µmolm2 h−1. The lack of contemporary studies to understand the interactions among critical nitrogen transformations (e.g., organic matter mineralization, immobilization, aquatic plant assimilation, nitrification, nitrogen fixation, dissimilatory nitrate reduction to ammonium (DNRA) and anaerobic ammonium oxidation (annamox) limits our understanding of nitrogen cycling in coastal Louisiana, particularly the role of respiratory and chemolithoautotrophic denitrification in areas undergoing wetland restoration. [Copyright &y& Elsevier]

Located at the mouth of large rivers, coastal deltaic floodplains are important ecosystems for trapping sediment and removing excess nitrogen introduced to the river through agricultural and urban runoff. Hydrological connectivity (the percent of river channel water interacting with floodplain wetlands), water age (the time elapsed since water entered the system via the main river channel) and water temperature have strong impacts on the biogeochemical processes controlling the fate of sediment and nutrients at continental margins. A Delft3D hydrodynamic model was used to explore the role of river and tide forcings, hydrogeomorphology, and vegetation roughness on hydrological connectivity, water age, and water temperature of a young, prograding river delta in coastal Louisiana, Wax Lake Delta. Across a simulation period of January to June 2015, an average of 39.9% of river flow entered the delta floodplains and water within the floodplains had an average water age of 0.8 days. In winter and spring, floodplain zones with higher sediment surface elevations (supratidal hydrogeomorphic zones) were characterized by increased water age and warmer water temperatures compared to subtidal floodplains and channels. Our experimental models indicate that the presence of wetland vegetation decreases hydrological connectivity by preventing flow of water into deltaic floodplain, but increases water age by retaining water within the floodplains. Despite small amplitudes (~30 cm), tides create hourly exchange between channels and floodplains, which decreases water age in floodplains, but has little impact on average connectivity. Our results emphasize the role of both hydrological forcings (river and tides) and ecosystem features (vegetation and sediment surface elevation) in regulating channel-floodplain interactions in deltaic systems. Evaluated against field data, which is often difficult to collect at high spatial and temporal frequency in floodplains, this model performs well, highlighting the utility of numerical models in capturing landscape-scale hydrodynamics. Image 1 • Hydrogeomorphic zones in coastal deltaic floodplains exhibit hydrologic differences. • Warmest temperatures and oldest water age in supratidal and intertidal floodplains. • River stage, tides, and vegetation roughness control channel-floodplain exchange. • Channel-floodplain connectivity increases from the delta apex to the delta front. [ABSTRACT FROM AUTHOR]