Intra-annual variability of marine floc morphology in southern North Sea coastal waters using in-situ high-resolution underwater imaging

SPM concentration and composition is an indicator for the balance between physical (turbulence) and biogeochemical processes (production, remineralization). High SPM concentration coincides with a dominance of mineral particles and the occurrence of biomineral flocs. These high turbidity zones, generally located nearshore or in estuaries, are characterized by strong tidal currents, intensive resuspension and settling, flocculation in phase with the tides and high primary productions. With decreasing SPM concentration, organic matter becomes more dominant and biological flocs, for example phytoplankton cells or aggregates, are getting more prominent. Physical processes are less important, and flocculation occurs on seasonal time scales. Measuring SPM concentration and particle size distribution (PSD) using laser diffraction techniques (e.g. LISST-100x) has been a standard component of Belgium’s monitoring for the past 20 years, resulting in a good knowledge of its spatial and temporal variability. However, despite its relevance to better understand and monitor the coastal pelagic environment, the PSD derived from laser diffraction do not provide insights into the origin (flocs, biological particles) and composition (mineral, organic matter) of the SPM. Yet, this information is crucial to better understand the SPM dynamics and to better predict the floc density and the fate and flux of minerals, carbon and pollutants. 

High-resolution underwater particle cameras are gaining popularity as they capture larger particles and provide data on their morphology and origin. By doing so and enabling researchers to visually see SPM, they offer a promising complement to laser diffraction-based instruments. This however doesn’t come without challenges, the main ones being related to image pre-processing (e.g. noise removal, histogram stretching, image reconstruction) and threshold definition as algorithms for particle detection and shape extraction may significantly impact PSD and derived parameters, requiring rigorous calibration and validation. 

In this study, we address these gaps by developing a processing system using underwater high-resolution particle imagery and applying it on a test case: the intra-annual morphological variability of marine flocs. Images were taken in-situ four kilometers off the Belgian coast during six oceanographic campaigns on board the RV Belgica between April 2023 and March 2024. An open-source user-friendly Python algorithm was developed to extract particles from images after validation in the lab against known-size particles. Floc morphologies were characterized using six shape indicators and were compared to in-situ SPM concentration, turbidity, LISST-100x and LISST-200x measurements as well as different parameters from water sample analyses taken at the same time.