Acoustic remote sensing monitoring of morphological and sedimentological seabed evolution of small and medium-scale French estuaries

Estuarine benthic habitat quality health is integrated within the framework of the EU Water Directive and Marine Strategy Framework Directive. The long-term monitoring of small and medium-scale estuarine benthic habitat is based on recurrent observation of several factors, mainly bathymetry and seabed nature. Numerous studies have already addressed the performance and limitations of acoustic remote sensing and mapping techniques. However, most of these studies are limited to the marine and coastal domains and do not include the estuarine domain. Estuaries are considered as transitional domains, with various seabed morphologies (from rocky reefs to hydraulic dunes with anthropic modification overlap) and subtle granulometric variations of the seabed nature.

The objectives of our study are to explore the mapping performance of several acoustic remote sensing techniques and to determine which physical factors are the most representative of morphological and sedimentological characteristics of subtidal estuarine environment and of its evolution. The exploration of these cartographic variables has been performed for three small and medium-scale French estuaries: the Orne estuary, the Baie de Somme and the Belon estuary. These estuaries have been chosen to cover different morphological and sedimentological estuarine contexts.

Firstly, we evaluate the capacity of the main variables derived from bathymetry (slope, curvature, ruggedness) to map seabed morphology. We extend the variable exploration to the “Terrain Variable” GIS category and BTM (Benthic Terrain Modeler Toolbox) as well. Secondly, we explore the capacity of several cartographic variables, extracted from bathymetric, seabed acoustic backscatter and acoustic ground discrimination system (i.e. RoxAnn©), to map seabed sediment characteristics and variations. The seabed nature mapping is validated with ground truthing data, namely grab samples and seabed video profiles. Moreover, quantitative (D90, roughness, sorting) and qualitive information (apparent roughness of the seabed, benthic habitat) are extracted from the grab samples and seabed video profiles, respectively. The capacity of these variables to produce seabed nature maps is also explored.

Mapping results on the three areas are compared, in terms of mapping precision and reproducibility, and transposed into recommendations for small and medium-scale estuaries monitoring. The next step of the AUPASED project is he exploration of image analysis and machine learning classifications and their comparison to manual morphological and sedimentological maps produced.

The AUPASED project is funded by the AFB (French Agency for Biodiversity) as part of a convention between the AFB and the CNRS (UMR 6143, M2C).