The global proliferation of plastics and their degradation into microplastics (<5 mm) have created a pervasive environmental crisis with severe ecological and human health consequences. Despite the exponential growth in microplastic research over the past decade, standardized protocols are still lacking. The absence of consistent sampling, analysis, and reporting methods limits data comparability, interoperability, and harmonization across studies. This study conducted a systematic bibliographic review of 355 peer-reviewed articles published between 2010 and 2022 that investigated microplastics in freshwater as well as marine water and sediment environments. The goal was to evaluate methodological consistency, sampling instruments, measurement units, reported characteristics, and data-sharing practices to identify pathways toward harmonized and FAIR (Findable, Accessible, Interoperable, and Reusable) microplastic data. Results show that 80.6% of studies focused on marine environments, 18% on freshwater, and 1.4% on both. This highlights persistent data gaps in freshwater systems, which function as key transport pathways for plastics to the ocean. Most studies targeted water (59%) rather than sediment (41%) and were mostly based on single-time sampling, limiting long-term analyses. Surface layers (<1 m) were predominantly sampled, while deeper layers remain understudied. Nets, particularly Manta, neuston, and plankton nets were the dominant tools for water sampling, whereas grabs, corers, and metallic receptacles were used for sediments. However, variations in mesh size and sampling depth introduce substantial biases in particle size recovery and reduce comparability across studies. The most common units were counts/volume for water and counts/g dry weight for sediments, but more than ten unit expressions were identified, complicating conversions. Only 35% of studies reported all four key microplastic characteristics (color, polymer type, shape, and size), and less than 20% made datasets publicly available. To advance harmonization, we recommend the adoption of consistent measurement units, mandatory reporting of key metadata, and wider implementation of open data practices aligned with the FAIR principles. These insights provide a foundation for developing robust monitoring strategies and evidence-based management frameworks. This is especially important for freshwater systems, where data remain scarce, and policy intervention is urgently needed.

The Bonnet Carré Spillway is a large flood control structure that diverts Mississippi River floodwaters into Lake Pontchartrain and the Mississippi Sound to prevent flooding in southern Louisiana and New Orleans. When operating at full capacity, the Spillway releases water at a rate of 7080 m³/s. Spillway openings regularly last a month or more. The enormous amount of freshwater that is diverted through the Spillway impacts salinity and nutrients in the Mississippi Sound. The objective of this research is to use a hydrodynamic model to simulate the impact of Bonnet Carré Spillway openings on the salinity of the Mississippi Sound over multiple years. Specifically, four hypothetical simulations of Spillway openings are compared to simulations during the same time when the Spillway is closed. The results show by how much, for how long, and where salinity is impacted in the estuarine system. The maximum difference in salinity at any given location over the mapped dates between the non-opening and hypothetical opening scenarios varies between 22 and 30 in each year. Differences in salinity between the opening and non-opening scenarios begin to decline in the study area approximately 18 days after Spillway closure. Decreases in salinity in Lake Borgne persist over a year. The Bonnet Carré Spillway affects salinity mostly in Lake Borgne and along an east/west ribbon that embraces the Mississippi coastline. Decreases in salinity caused by Spillway openings are seen up to 200 km east of the Spillway. These results are important for planning management strategies for estuarine resources during Spillway openings.

This study develops and evaluates a simulation-optimization approach to mitigate the environmental impacts of freshwater pulses in brackish-water lakes whilst maximizing flood diversion benefits. Lake Pontchartrain, located downstream of the Mississippi River, Mississippi, United States, is a brackish-water ecosystem threatened by reducing salinity concentrations due to freshwater pulses from the flood diversion project on the Mississippi River. An adaptive neuro-fuzzy-inference-system-based model was developed as a data-driven model for simulating salinity distribution at a representative station of Lake Pontchartrain. Then, the data-driven model was used as the simulator in the optimization system. Both single-objective and multi-objective particle swarm optimizations were used to find the optimal solutions. Results show that the data-driven model is robust at simulating the salinity time series in the brackish-water ecosystem of Lake Pontchartrain. The Nash–Sutcliffe efficiency index of the data-driven model between measured and modelled salinity is 0.85, which means the model is reliable for applying in further simulations. The proposed optimal solutions for the environmental management of the lake indicate that because of the magnitude of the volume of freshwater released, environmental impacts at this location cannot be optimized through varying the timing and volume of the releases. This work presents a novel contribution to science through developing an optimization framework for mitigating the impacts of flood management on changes in salinity in brackish-water systems.