4.3 Article

Parameterising resuspension in aquaculture waste deposition modelling

Journal

AQUACULTURE ENVIRONMENT INTERACTIONS
Volume 12, Issue -, Pages 401-415

Publisher

INTER-RESEARCH
DOI: 10.3354/aei00372

Keywords

Aquaculture; Deposition; Benthic impacts; Resuspension; DEPOMOD

Funding

  1. Scottish Government [SAM/004/12]
  2. Scottish Aquaculture Innovation Centre
  3. Scottish Salmon Producers Organisation (ExPAND project)

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Sustainable expansion of global aquaculture depends on a thorough understanding of environmental impacts. Open-water culture operations produce waste food and faeces, the benthic impacts of which are a focus of regulation. Seabed interactions of wastes are complex, depending on current velocity, seabed substrate and waste material characteristics. The accuracy achieved in modelling intensity and spatial extent of impacts is contingent upon the representation of this interaction and its implications for resuspension. We used benthic flumes to study resuspension processes at 11 salmon aquaculture sites, covering a range of sediment types. Erosion rates and critical entrainment stress were computed at the cage edge and between 100 and 500 m away, characterising seabed erodibility in highly impacted and less impacted sediments. Heavily impacted cage-edge sediments had an erosion threshold (mean 0.02 N m(-2)) that was an order of magnitude lower, and markedly less heterogeneous, than that of nearby less impacted sediments (mean across sites 0.19 N m(-2)). This likely reflects a seabed which was smothered by waste material close to the depositional centre. Further out, the covering of waste material is less continuous, thinner, and more admixed with underlying sediments. Bed erosion rates were found to be a linear function of excess stress. The results provide important information on how benthic flumes can be deployed to collect spatial and temporal data for parameterisation of erosion and entrainment processes in numerical waste transport simulation models such as DEPOMOD, and the comparatively large field-based dataset should contribute to the goal of allowing a more realistic representation of particulate waste in these models.

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