Scotland is currently the largest producer of Atlantic salmon in the EU, and the third largest globally. Exports have doubled in the past decade to nearly £1 billion per annum, and the Scottish Government has specified targets for further expansion. SEPA is working with fish-farmers to help them comply with environmental legislation and to ensure that this growth is sustainable. Modelling is used to predict the environmental impact of organic material and medicines, and to determine appropriate locations and biomass limits for fish-farms. Traditionally, these farms have been assessed and licensed in isolation, but numerical modelling is increasingly being used to investigate larger scale impacts, cumulative effects, and hydrodynamic connectivity between farms. MIKE21 models of several water bodies have been developed, with the Particle Tracking module used to predict the spatial and temporal variation of SLICE, a sea-lice medicine. A sub-model of the Scottish Shelf Model developed by Marine Scotland has been converted from FVCOM and is being used to develop a screening tool for assessing the interaction between farms in the Highlands and Islands. By adopting risk-based modelling over a range of scales, SEPA can obtain a better understanding of the environmental impact of fish-farms, influence strategic policy decisions and support sustainable growth of the aquaculture industry. Presented at the DHI UK Symposium 2018.

1. Using numerical modelling to regulate a
growing aquaculture industry
Dr Ted Schlicke
Air & Marine Modelling Unit,
Scottish Environment Protection Agency

2. Salmon Fish Farm Locations

6. Hydrodynamic Connectivity

7. Chemical Impact Scenario Testing

8. Scottish Shelf Model

9. Mike21 / FVCOM Comparison

11. Summary
• SEPA is using Mike21 to investigate larger
scale impacts of fish-farming
• Specific applications include:
• cumulative effect of multiple farms
• suitable areas for expansion
• hydrodynamic connectivity
• identification of management zones
• Also working to develop screening tools from
FVCOM model to help identify riskier sites