Uncertainty assessment applied to marine subsurface datasets

A recently released voxel model quantifying aggregate resources of the Belgian part of the North Sea includes lithological properties of all Quaternary sediments and modelling-related uncertainty. As the underlying borehole data come from various sources and cover a long time-span, data-related uncertainties should be accounted for as well. Applying a tiered data-uncertainty assessment to a composite lithology dataset with uniform, standardized lithological descriptions and rigorously completed metadata fields, uncertainties were qualified and quantified for positioning, sampling and vintage. The uncertainty on horizontal positioning combines navigational errors, on-board and off-deck offsets and underwater drift. Sampling-gear uncertainty evaluates the suitability of each instrument in terms of its efficiency of sediment yield per lithological class. Vintage uncertainty provides a likelihood of temporal change since the moment of sampling, using the mobility of fine-scale bedforms as an indicator. For each uncertainty component, quality flags from 1 (very uncertain) to 5 (very certain) were defined and converted into corresponding uncertainty percentages meeting the input requirements of the voxel model. Obviously, an uncertainty-based data selection procedure, aimed at improving the confidence of data products, reduces data density. Whether or not this density reduction is detrimental to the spatial coverage of data products, will depend on their intended use. At the very least, demonstrable reductions in spatial coverage will help to highlight the need for future data acquisition and to optimize survey plans. By opening up our subsurface model with associated data uncertainties in a public decision support application, policy makers and other end users are better able to visualize overall confidence and identify areas with insufficient coverage meeting their needs. Having to work with a borehole dataset that is increasingly limited with depth below the seabed, engineering geologists and geospatial analysts in particular will profit from a better visualization of data-related uncertainty

Stratigraphy, structure and evolution of the European continental margins

In the course of the last three decades fundamental marine geological research in Europe has grown to full maturity and has been thriving thanks to significant European financial support via collaborative research projects on a variety of topics, such as slope stability (e.g. COSTA, EUROMARGINS), gas hydrates (e.g. HYDRATECH, ANAXIMANDER), fluid flow (e.g. MEDIFLUX, CRIMEA), cold-water corals and deep biosphere (e.g. GEOMOUND, ECOMOUND, HERMES, HERMIONE, MiCROSYSTEMS), paleoceanography (e.g. MOCCHA), delta's (e.g. EURODELTA), source-to-sink studies (e.g. EUROSTRATAFORM), continental margin processes (e.g. OMARC, EURODOM, PROMESS), and the deep ocean floor (e.g. GEOSTAR, BIODEEP, MIDAS). Through these projects major progress was made in our understanding of fundamental processes governing the stratigraphy, structure and evolution of the European continental margins and surrounding ocean floors, including the interactions between geosphere, hydrosphere and biosphere

Picking Up the Pieces—Harmonising and Collating Seabed Substrate Data for European Maritime Areas

The poor access to data on the marine environment is a handicap to government decision-making, a barrier to scientific understanding and an obstacle to economic growth. In this light, the European Commission initiated the European Marine Observation and Data Network (EMODnet) in 2009 to assemble and disseminate hitherto dispersed marine data. In the ten years since then, EMODnet has become a key producer of publicly available, harmonised datasets covering broad areas. This paper describes the methodologies applied in EMODnet Geology project to produce fully populated GIS layers of seabed substrate distribution for the European marine areas. We describe steps involved in translating national seabed substrate data, conforming to various standards, into a uniform EMODnet substrate classification scheme (i.e., the Folk sediment classification). Rock and boulders form an additional substrate class. Seabed substrate data products at scales of 1:250,000 and 1:1 million, compiled using descriptions and analyses of seabed samples as well as interpreted acoustic images, cover about 20% and 65% of the European maritime areas, respectively. A simple confidence assessment, based on sample and acoustic coverage, is helpful in identifying data gaps. The harmonised seabed substrate maps are particularly useful in supraregional, transnational and pan-European marine spatial planning

Do tidal sand waves always regenerate after dredging?

Tidal sand waves are rhythmic bedforms found on sandy continental shelves that pose a threat to offshore activities. While emphasis is placed on studying their natural morphodynamic evolution, little is known about if and how fast sand waves recover after dredging. This work presents an analysis of multibeam echosounder data collected at three former sand extraction sites on the Belgian continental shelf. At one of the sites, sand waves seemed to reappear approximately 5 years after dredging had stopped, which did not happen at the other two sites during the measurement period (5 and 9 years). The lack of recovery in those sites is likely the result of larger depths and smaller local sediment availability compared with the site where recovery occurred. Furthermore, these data reveal that in the latter site sand wave recovery was established mainly through local sediment redistribution. • Tidal sand waves are isolated from bathymetric data of the Belgian continental shelf. • At only one of the three sites, sand waves seemed to regenerate after dredging. • Possible explanations are differences in water depth and local sediment availability. • The regenerating tidal sand waves do so as a result of local redistribution of sand