OR/16/001 Background

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Dove, D, Bradwell, T*, Carter, G, Cotterill, C, Gafeira, J, Green, S, Krabbendam, M, Mellet, C, Stevenson, A, Stewart, H, Westhead, K.; INFOMAR: Scott, G, Guinan, J, Judge, M, Monteys, X.; MAREANO: Elvenes, S, Baeten, N, Dolan, M, Thorsnes, T, Bjarnadóttir, L, and Ottesen, D . 2016. Seabed geomorphology: a two-part classification system. British Geological Survey Internal Report, OR/16/001.
(* now at Stirling University)

Detailed and accurate mapping of the seabed is important for a number of user-groups (research, commercial, conservation and policy). For example: i) the ever increasing activity in the offshore renewables industry has demonstrated a critical need for improved characterisation of shallow geology for appropriate site selection and foundation design; ii) the designation of marine protected areas (MPAs) requires the identification and mapping of benthic habitats that are underpinned by the geological substrate; iii) to understand the environmental processes that formed and actively govern the marine environment, scientists and marine spatial planners require more accurate and up-to-date geological interpretations at multiple scales; and iv) marine policies and environmental legislation, e.g. Marine Strategy Framework Directive, can only be enforced where the most accurate information is available. New, extensive high-resolution bathymetry datasets are enabling significant insights into the geology of the seabed and shallow sub-seabed. In contrast to terrestrial settings, the increasing availability of high-resolution data in the marine environment is leading to many features being revealed and described for the first time. This calls for an observational mapping approach, which is analogous to that which may have been applied on land over a century ago. For example, swath-bathymetry datasets (~1–10 m resolution) not only permit scientists to better distinguish the genetic origin of seabed features, but also cover sufficiently extensive areas to allow feature assemblages to be understood in the broader context of environmental systems (Figures 1, 2) (e.g. Dove et al., 2015[1]).

Figure 1    Regional interpretation of ice sheet flow and retreat based on geomorphic interpretation. Extensive bathymetry data enable feature-scale landform assemblages to be placed in context of broader environmental systems.
Figure 2    Bathymetry data from the Sound of Jura reveal an assemblage of glacially streamlined landforms and moraines overlying commonly exposed bedrock strata. Panel C) shows the local glacial landform interpretation, and how morphological character may infer sub-surface characteristics (i.e. degree of presence/absence of bedrock in landforms.

Mapping the geomorphology of the seabed provides a fundamental and effective means to characterise this important element of the marine environment. The science of geomorphology addresses the general configuration of the earth’s surface, in this case in a submarine setting, with the purpose of describing the nature of landforms/bedforms, and their relationship to the underlying geology. Geomorphological analysis enables a better understanding of the environmental processes recorded at the earth’s surface as the physical characterisation (form and other attributes e.g. symmetry) of landforms may be used to distinguish feature origin, as well as describe their development and evolution through time. Geomorphological maps combined with other marine datasets, e.g. ground-truthing and shallow seismic data, allow for considerably improved geological characterisations and predictions of associated geotechnical properties.

The concept of mapping seabed geomorphology is not inherently innovative or ground-breaking. Terrestrial geomorphology is a well-established field of science (e.g. Hubbard and Glasser, 2005[2]; Summerfield, 2014[3]), and within the marine environment for example, mapping submarine glacial landforms has become the most useful and common method to reconstruct the extent and dynamics of former marine-based ice-sheets (e.g. Dowdeswell et al., in press[4]). Geomorphology has also been demonstrated to exert significant control on the character and distribution of benthic habitats (e.g. Harris et al., 2011[5]). What is novel here, and useful/necessary for survey organisations, is to have the means to describe the geomorphology of the seabed in a consistent, and where appropriate, standardised way. This requires the development of a new classification system that is: i) applicable to multiple and diverse environments, and ii) sufficiently detailed and interpretive to be informative, but not so detailed that features are over-interpreted, and/or become mired in disputed designations or definitions.

New high-resolution and extensive datasets also result in large, and exponentially increasing data volumes. This requires that BGS, together with other survey, research, and industry-based scientists supplement classical mapping with improved methodologies. Adapting to this challenge requires innovative data acquisition, processing, and interpretation techniques, including: image analysis, statistical approaches, and automated-feature-detection protocols (e.g. Gafeira et al., 2012[6]; Cazanave et al., 2013[7]; Ismail et al., 2015[8]). Incorporating these tools will form an important component in the effort to produce better geomorphological map products.

References

  1. DOVE, D, AROSIO, R, FINLAYSON, A, BRADWELL, T, and HOWE, J A. 2015. Submarine glacial landforms record Late Pleistocene ice-sheet dynamics, Inner Hebrides, Scotland. Quaternary Science Reviews, 123, pp.76–90.
  2. HUBBARD B, and GLASSER N F. Field techniques in glaciology and glacial geomorphology. John Wiley & Sons; 2005 Jul 8.
  3. SUMMERFIELD, M A. 2014. Global geomorphology. Routledge.
  4. DOWDESWELL, J A, CANALS, M, JAKOBSSON, M, TODD, E K, DOWDESWELL, E K, HOGAN, K A. In press. Atlas of submarine glacial landforms. Geological Society of London.
  5. HARRIS, P T, and BAKER, E K. eds. 2011. Seafloor Geomorphology as Benthic Habitat: GeoHab Atlas of seafloor geomorphic features and benthic habitats. Elsevier.
  6. GAFEIRA, J, LONG, D, and DIAZ-DOCE, D. 2012. Semi-automated characterisation of seabed pockmarks in the central North Sea. Near Surface Geophysics, 10(4), pp.303–314.
  7. CAZENAVE, P W, DIX, J K, LAMBKIN, D O, and MCNEILL, L C. 2013. A method for semi‐automated objective quantification of linear bedforms from multi‐scale digital elevation models. Earth Surface Processes and Landforms, 38(3), pp.221–236.
  8. ISMAIL, K, HUVENNE, V A, MASSON, D G. 2015. Objective automated classification technique for marine landscape mapping in submarine canyons. Marine Geology, 362, pp.17–32.