Search Results (39)

This research focused on studying the soil improvement ability provided by the roots of smooth cordgrass, Spartina alterniflora, flourishing in the dredged soil of the Sabine Refuge Marsh Creation Project in the coastal area of Louisiana, USA. Vane shear tests were conducted in the created marshland to obtain the in situ undrained shear strength of the soil vegetated with Spartina alterniflora. Direct shear tests were performed on undisturbed rooted soil samples to investigate the overall effect of the roots on soil shear strength. Laboratory tensile tests were conducted on the roots of Spartina alterniflora to estimate their tensile strength. In this research, the W&W model and the fiber bundle model (FBM), were adopted, and modified ones were proposed to study the correlation between root-enhanced soil cohesion and the nominal tensile strength of the roots. The model outcomes were compared with field and laboratory measurements. The research results showed that the roots of Spartina alterniflora significantly increased soil shear strength, with an increase in cohesion of up to 130% at one location. The increases varied at different locations depending on the root area ratio (RAR), soil sample depth, and root tensile strength. Full article

Driven by the need to expand urban/industrial complexes, and/or mitigate anticipated environmental impacts (e.g., tropical storms), many coastal countries have long implemented large-scale land reclamation initiatives. Some areas, like coastal Louisiana, USA, have relied heavily on restoration activities (i.e., beneficial use of dredged material) to counter extensive long-term wetland loss. Despite these prolonged engagements, the quantifiable benefits of these activities have lacked comprehensive documentation. Therefore, this study leveraged remote sensing data and advanced machine learning techniques to enhance the classification and evaluation of restoration efficacy within the wetlands adjacent to the Mississippi River’s Southwest Pass (SWP). By utilizing air- and space-borne imagery, land and water data were extracted and used to compare land cover changes during two distinct restoration periods (1978 to 2008 and 2008 to 2020) to historical trends. The classification methods employed achieved an overall accuracy of 85% with a Cohen’s kappa value of 0.82, demonstrating substantial agreement beyond random chance. To further assess the success of the SWP reclamation efforts in a global context, broad-based land cover data were generated using biennial air- and space-borne imagery. Results show that restoration activities along SWP have resulted in a significant recovery of degraded wetlands, accounting for approximately a 30 km² increase in land area, ranking among the most successful land reclamation projects in the world. The findings from this study highlight beneficial use of dredged material as a critical component in large-scale, recurring restoration activities aimed at mitigating degradation in coastal landscapes. The integration of remote sensing and machine learning methodologies provides a robust framework for monitoring and evaluating restoration projects, offering valuable insights into the optimization of ecosystem services. Overall, the research advocates for a holistic approach to coastal restoration, emphasizing the need for continuous innovation and adaptation in restoration practices to address the dynamic challenges faced by coastal ecosystems globally. Full article

The exchange of water, sediment, and nutrients in wetlands occurs through a complex network of channels and overbank flow. Although optical sensors can map channels at high resolution, they fail to identify narrow intermittent channels colonized by vegetation. Here we demonstrate an innovative application of rapid-repeat interferometric synthetic aperture radar (InSAR) to study hydrologic connectivity and tidal influences in Louisiana’s coastal wetlands, which can provide valuable insights into water flow dynamics, particularly in vegetation-covered and narrow channels where traditional optical methods struggle. Data used were from the airborne UAVSAR L-band sensor acquired for the Delta-X mission. We applied interferometric techniques to rapid-repeat (~30 min) SAR imagery of the southern Atchafalaya basin acquired during two flights encompassing rising-to-high tides and ebbing-to-low tides. InSAR coherence is used to identify and differentiate permanent open water channels from intermittent channels in which flow occurs underneath the vegetation canopy. The channel networks at rising and ebbing tides show significant differences in the extent of flow, with vegetation-filled small channels more clearly identified at rising-to-high tide. The InSAR phase change is used to identify locations on channel banks where overbank flow occurs, which is a critical component for modeling wetland hydrodynamics. This is the first study to use rapid-repeat InSAR to monitor tidal impacts on water flow dynamics in wetlands. The results show that the InSAR method outperforms traditional optical remote sensing methods in monitoring water flow in vegetation-covered wetlands, providing high-resolution data to support hydrodynamic models and critical support for wetland protection and management. Full article

Impoundment and increased flood duration are some of the most common stressors to declining forested wetlands in coastal Louisiana, USA. One type of restoration that has shown itself to be cost-effective is spoil bank gapping. This type of hydrologic restoration has occurred within the Lac des Allemands swamp of Barataria Basin. After 60 years of impoundment, the hydrogeomorphic processes in the study area were improved. The study area included eight paired 625 m² sites. Basal area growth over the 7-year period varied between 5.93% and 14.39%, with an average of 8.31%, or just over 1% wood growth per year. Post-restoration basal areas indicate that all our study areas are improving. Pooled together, the 2018–2023 years had significantly higher net production than the pre-project 2017 growing season. The distribution between leaf and wood production was remarkably similar within species types across years, with leaf production consistently exceeding wood production, particularly due to Taxodium distichum. Canopy cover has increased by 20 percent since project construction, and as a result, herbaceous cover tends to decrease over time. Full article

Visible Infrared Imaging Radiometer Suite (VIIRS) and Advanced Baseline Imager (GOES-R ABI) flood products have been widely used by the National Weather Service (NWS) for river flood monitoring, and by the Federal Emergency Management Agency (FEMA) for rescue and relief efforts. Some water bodies, like wetlands, are detected as water but not marked as permanent or normal water, which may result in their misclassification as floodwaters by VIIRS and GOES-R flood products. These water bodies generally do not cause significant property damage or fatalities, but they can complicate the identification of truly hazardous floods. This study utilizes the severe Louisiana flood event caused by Hurricane Ida to demonstrate how to differentiate wetlands from real-hazard flooding. Since Hurricane Ida made landfall in 2021, and there was no major flood event in 2022, VIIRS and ABI flood data from 2021 and 2022 were selected. The difference in annual total flooding days between 2021 and 2022 was calculated and combined with long-time flood frequency to distinguish non-hazard floodwaters due to wetlands identified from real-hazard floods caused by the hurricane. The results were compared with the wetlands from the change detection analysis. The confusion matrix analysis indicated an accuracy of 91.58%, precision of 89.97%, and F1-score of 76.63% for the VIIRS flood products. For the GOES-R ABI flood products, the confusion matrix analysis yielded an accuracy of 86.88%, precision of 97.49%, and F1-score of 75.21%. The accuracy and F1-score values for the GOES-R ABI flood products are slightly lower than those for the VIIRS flood products, possibly due to their lower spatial resolution, but still within a feasible range. Full article

Coastal wetlands are vulnerable to accelerated sea-level rise, yet knowledge about their extent and distribution is often limited. We developed a land cover classification of wetlands in the coastal plains of the southern United States along the Gulf of Mexico (Texas, Louisiana, Mississippi, Alabama, and Florida) using 6161 very-high (2 m per pixel) resolution WorldView-2 and WorldView-3 satellite images from 2012 to 2015. Area extent estimations were obtained for the following vegetated classes: marsh, scrub, grass, forested upland, and forested wetland, located in elevation brackets between 0 and 10 m above sea level at 0.1 m intervals. Sea-level trends were estimated for each coastal state using tide gauge data collected over the period 1983–2021 and projected for 2100 using the trend estimated over that period. These trends were considered conservative, as sea level rise in the region accelerated between 2010 and 2021. Estimated losses in vegetation area due to sea level rise by 2100 are projected to be at least 12,587 km², of which 3224 km² would be coastal wetlands. Louisiana is expected to suffer the largest losses in vegetation (80%) and coastal wetlands (75%) by 2100. Such high-resolution coastal mapping products help to guide adaptation plans in the region, including planning for wetland conservation and coastal development. Full article

Earth system models (ESMs) are a common tool for estimating local and global greenhouse gas emissions under current and projected future conditions. Efforts are underway to expand the representation of wetlands in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) by resolving the simultaneous contributions to greenhouse gas fluxes from multiple, different, sub-grid-scale patch-types, representing different eco-hydrological patches within a wetland. However, for this effort to be effective, it should be coupled with the detection and mapping of within-wetland eco-hydrological patches in real-world wetlands, providing models with corresponding information about vegetation cover. In this short communication, we describe the application of a recently developed NDVI-based method for within-wetland vegetation classification on a coastal wetland in Louisiana and the use of the resulting yearly vegetation cover as input for ELM simulations. Processed Harmonized Landsat and Sentinel-2 (HLS) datasets were used to drive the sub-grid composition of simulated wetland vegetation each year, thus tracking the spatial heterogeneity of wetlands at sufficient spatial and temporal resolutions and providing necessary input for improving the estimation of methane emissions from wetlands. Our results show that including NDVI-based classification in an ELM reduced the uncertainty in predicted methane flux by decreasing the model’s RMSE when compared to Eddy Covariance measurements, while a minimal bias was introduced due to the resampling technique involved in processing HLS data. Our study shows promising results in integrating the remote sensing-based classification of within-wetland vegetation cover into earth system models, while improving their performances toward more accurate predictions of important greenhouse gas emissions. Full article

Current land use and extensive modifications of natural ecosystems across the state of Louisiana are generally similar to those across the southeastern USA where rainfall supports forest ecosystems. Both intentional and unintentional consequences of ecosystem modifications from the scales of water and sediment movement across a field edge to state-wide loss of functional grasslands are legacies from previous development across the state. While major investments and large-scale, long-term plans are aspects of some continuing ecological issues across the state, small-scale, volunteer-led restoration of native grassland plant communities in the Louisiana Coastal Prairie illustrates the value associated with the restoration of natural ecosystem function in drastically disturbed environments. As is now becoming increasingly recognized, Louisiana grasslands represent less obvious components of forest, woodland, and wetland landscapes across the state, where they have contributed essential wildlife habitat, and ecosystem functions. These are now largely missing from many landscapes across the state and region. The strategic restoration of grassland functions combining novel native grass pastures and fully functional native grassland plant communities as landscape components could provide both economic and ecosystem benefits. Specific native grassland seed resources are needed for various restoration activities to enhance ecosystem function at a range of scales across the state and region. Full article

Deltaic landscapes go through cycles of birth, growth, decline, and death governed by intertwined geological, biological, and ecological processes. In this study, we tracked deltaic lobes in the Balize Mississippi River Delta, Louisiana, USA, over 28 years (1984–2012). Hydrologic and geomorphic patterns as well as sustained patterns of wetland plant richness, diversity, and biomass are described. Plant diversity and biomass were modeled by nMDS ordination. Taxa (53) were harvested and dried (116,706 g) from 965 (0.25 m²) plots and divided into three groups: I. four foundation species, corresponding to 78.9% of the total harvest; II. nine pioneer species, corresponding to 13.6% of the total harvest; and III. all other taxa, corresponding to 7.5% of the total harvest (eight miscellaneous grasses, eight miscellaneous sedges, and twenty-four miscellaneous herbs). Autogenic/allogenic processes (sedimentation, subsidence, plant colonization, and succession events) affected composition and biomass. Eleven important species were identified. Taxon richness increased on mudflats during primary succession (fifteen to twenty-five taxa per site), then declined to fewer than five taxa per site. The niche space theory explained patterns of community change, with a similar total biomass/yr (~500 g/m²/yr) at all study sites. Quantile regression analyses showed that the water quality and quantity of the Mississippi River influenced biomass, especially in springtime waters. Stochastic events (storms, herbivory, salt burn, and flood pulses) impacted biomass. Long-term studies like this are required in a future of climate unknowns. Full article

Submerged aquatic vegetation (SAV) are highly efficient at carbon sequestration and, despite their relatively small distribution globally, are recognized as a potentially valuable component of climate change mitigation. However, SAV mapping in tidal marshes presents a challenge due to optically complex constituents in the water. The emergence and advancement of deep learning-based techniques in the field of habitat mapping with remote sensing imagery provides an opportunity to address this challenge. In this study, an analytical framework was developed to quantify the carbon sequestration of SAV habitats in the Atchafalaya River Delta Estuary from field and remote sensing observations using deep convolutional neural network (DCNN) techniques. A U-Net-based model, Wetland-SAV Network, was trained to identify the SAV percent cover (high, medium, and low) as well as other estuarine habitat types from Landsat 8/9-OLI data. The areal extent of SAV was up to 8% of the total area (47,000 ha). The habitat areas and habitat-specific carbon fluxes were then used to quantify the net greenhouse gas (GHG) flux of the study area for with/without SAV scenarios in a carbon balance model. The total net GHG flux was in the range of −0.13 ± 0.06 to −0.86 ± 0.37 × 10⁵ tonne CO₂e y⁻¹ and increased up to 40% (−0.23 ± 0.10 to −0.90 ± 0.39 × 10⁵ tonne CO₂e y⁻¹) when SAV was accounted for within the calculation. At the hectare scale, the inclusion of SAV resulted in an increase of ~60% for the net GHG sink in shallow areas adjacent to the emergent marsh where SAV was abundant. This is the first attempt at remotely mapping SAV in coastal Louisiana as well as a first quantification of net GHG flux at the scale of hectares to thousands of hectares, accounting for SAV within these sub-tropical coastal delta marshes. Remote sensing and deep learning models have high potential for mapping and monitoring SAV in turbid sub-tropical coastal deltas as a component of the increasing accuracy of net GHG flux estimates at small (hectare) and large (coastal basin) scales. Full article

Despite increased hurricane intensity, the U.S. Gulf of Mexico coast has experienced dramatic coastal population increase of 24.5% from 2000 to 2016. However, in areas of coastal Louisiana with dramatic wetland loss, parishes have experienced population declines and lower rates of population growth. Therefore, understanding the magnitude of the effect of wetland loss as a main driver of population loss in coastal Louisiana is critical. Using regression analysis, this study finds that wetland loss has a significant and persistent negative effect on population growth in coastal Louisiana. This effect resulted in a reduction in the population growth rate in coastal parishes over time. A counterfactual simulation was conducted to estimate the potential population size in the absence of wetland loss from 1990 to 2021. On average, the effect of 1 hectare of wetland lost causes a reduction of approximately 1000 persons. This indicates that for the year 2021, the population was approximately 18% lower than the population that would have existed in the absence of wetland loss. This research underscores the role of wetlands in providing direct and indirect benefits to people in coastal Louisiana that are ultimately reflected in its population levels. Full article

Coastal Louisiana is currently experiencing high rates of wetland loss and large-scale ecosystem restoration is being implemented. One of the largest and most novel restoration projects is a controlled sediment diversion, proposed to rebuild and sustain wetlands by diverting sediment- and nutrient-rich water from the Mississippi River. However, the impact of this proposed sediment diversion on the nutrient budget of the receiving basin is largely unknown. A water quality model was developed to investigate the impact of the planned Mid-Barataria Sediment Diversion on the nutrient budget of the Barataria Basin (herein referred to as ‘the Basin’). The model results indicate that the planned diversion will increase TN and TP pools by about 38% and 17%, respectively, even with TN and TP loadings that increase by >300%. Water quality model results suggest that the increase of nutrients in the basin will be mitigated by increased advection transport (i.e., decreased residence time from ~170 days to ~40 days, leading to greater flushing) and increased removal via assimilation, denitrification, and settling within the Basin. Advection transport resulted in higher TN removal in the Basin than other processes, such as uptake or denitrification. Approximately 25% of the additional TN loading and 30% of the additional TP loading were processed within the Basin through the assimilation of phytoplankton and wetland vegetation, denitrification, and burial in the sediment/soils. These nutrient budgets help to better understand how the planned large-scale sediment diversion project may change the future ecological conditions within the estuaries of coastal Louisiana and near-shore northern Gulf of Mexico. Full article

Coastal forests along the southeastern Gulf of Mexico are known to be diminishing at an alarming rate. The live-oak dominant chenier forests of southeast Louisiana are amongst those exhibiting the steepest declines. The remnant stands have experienced numerous hurricanes and intense storm events in recent years, calling into question the current status and immediate future of this imperiled natural resource. Despite their noted ecological and physiographic importance, there is a lack within national geographic data repositories of accurate representations of forest loss and wetland extent for this region. Supervised machine learning algorithms in the Google Earth Engine were used to classify and process high-resolution National Agricultural Image Product (NAIP) datasets to create accurate (>90%) tree cover maps of the Louisiana Chenier Plains in Cameron and Vermilion Parishes. Data from three different years (2003, 2007, and 2019) were used to map 2302 km² along the southwestern coast of Louisiana. According to the analyses, there was a 35.73% loss of forest cover in this region between 2003 and 2019. A majority of the land-use change was from tree cover to saltmarsh, with losses in pastoral land also documented. We found variable rates of loss with respect to elevation. Forest cover losses corresponded strongly to rises in mean sea level. These findings deliver a baseline understanding of the rate of forest loss in this region, highlighting the reduction and potentially the eventual extirpation of this imperiled ecosystem. Full article

Atmospheric cold fronts can periodically generate storm surges and affect sediment transport in the Northern Gulf of Mexico (NGOM). In this paper, we evaluate water circulation spatiotemporal patterns induced by six atmospheric cold front events in the Wax Lake Delta (WLD) in coastal Louisiana using the 3-D hydrodynamic model ECOM-si. Model simulations show that channelized and inter-distributary water flow is significantly impacted by cold fronts. Water volume transport throughout the deltaic channel network is not just constrained to the main channels but also occurs laterally across channels accounting for about a quarter of the total flow. Results show that a significant landward flow occurs across the delta prior to the frontal passage, resulting in a positive storm surge on the coast. The along-channel current velocity dominates while cross-channel water transport occurs at the southwest lobe during the post-frontal stage. Depending on local weather conditions, the cold-front-induced flushing event lasts for 1.7 to 7 days and can flush 32–76% of the total water mass out of the system, a greater range of variability than previous reports. The magnitude of water flushed out of the system is not necessarily dependent on the duration of the frontal events. An energy partitioning analysis shows that the relative importance of subtidal energy (10–45% of the total) and tidal energy (20–70%) varies substantially from station to station and is linked to the weather impact. It is important to note that within the WLD region, the weather-induced subtidal energy (46–66% of the total) is much greater than the diurnal tidal energy (13–25% of the total). The wind associated with cold fronts in winter is the main factor controlling water circulation in the WLD and is a major driver in the spatial configuration of the channel network and delta progradation rates. Full article

This paper presents the results of a collaborative planning process to develop an integrated coastal restoration plan for Plaquemines Parish, Louisiana that recognizes the knowledge, experience, and priorities of residents and local stakeholders. To achieve this goal, the research team convened a broad group of stakeholders who live and work in Plaquemines Parish, including representatives of the seafood, navigation, and oil and gas industries, as well as residents, landowners, and those who are indigenous to the region, all of whom rely upon the ecosystem services provided by the wetlands, bays, and waterways for sustenance and wellbeing. Using a combination of local knowledge mapping and participatory modeling, the group worked with scientists to develop a restoration plan consisting of a suite of interlinked natural and nature-based solutions. The approach was intentionally interactive and iterative, creating a venue for open dialogue between residents, scientists, and resource users where no one source of knowledge was given primacy over another. Residents were able to contribute information regarding coastal restoration planning within their own communities, and a consensus plan for prioritizing restoration efforts in clusters was submitted for consideration as part of the State of Louisiana’s Coastal Master Plan process. Providing local stakeholders with direct access to scientists allowed their local knowledge to be translated into data products that could be more readily ingested into numerical models and other scientific planning tools. Full article