1. Page 1 CONSULTANCY AND RESEARCH IN AQUACULTURE AND THE AQUATIC ENVIRONMENT A Company in the NIVA-group Modelling of environmental impact of aquaculture – hydrographical models

2. Page 2 Modelling objectives Reach a better understanding of aquacultures impact. Find causes of perceived problems. Give recommendations on remedial actions to be taken. Identify areas with less risk. Give indications of total carrying capacity of the areas.

3. Page 3 What is a model ?...we mean a mathematical model. One or more expressions or equations. Example 1: A familiar expression Fish length = A (1 – e -kt ) is a model. Importance of data: To determine coefficients A and k for a particular species of fish, you must have data. Without data you have a theoretical model but you can not apply it to any fish species. Similarly:

4. Page 4 Example 2: Effect of freshwater source on the coastal sea Equations for conservation of momentum, mass, propagation of turbulence, transport of heat and salinity make a hydro dynamical model.

5. Page 5 Bathymetric map

6. Page 6 Another view to the bay

7. Page 7 Numerical mesh

8. Page 8 Residual current in the future - current now = change in the future. Colour coded is the change in the absolute values. Vectors denote directional change.

9. Page 9 Temperature Salinity

10. Page 10 Vertical slices in temperature and salinity <= Vertical slice: Temperature Vertical slice: => Salinity

11. Page 11 Effect of an aquaculture on P conc. in the water column

12. Page 12 Effect of an aquaculture to the bottom: deposition of Carbon

13. Page 13 How to compute carrying capacity ? There have been various approaches. All focus to the description of the most limiting factor likely to affect fish health and mortality first. For most areas, this factor is oxygen availability. Clearly, when dissolved oxygen drops below 2 mg/l fish mortality will occur. But dissolved oxygen content in water is the result of several processes. There are organisms that produce oxygen and those that consume it. Fish and shellfish are those that consume it. Algae produces it, They all play a direct and an indirect role.

14. Page 14 How to compute carrying capacity ? Available nutrients are taken by phytoplankton which grows in number very quickly, thereby depleting nutrient content in water. A huge number of phytoplankton cells in water are now hungry and can not find enough nutrients any more. This is the start of the phytoplankton crash. When it crushes, it does so in phase. Suddenly a huge mass of phytoplankton leftover is found in water. Decomposition of this mass will cause deadly hypoxia.

15. Page 15 Effect of nutrient inflow on PHYTOPLANKTON concentration Let: N-nutrient concentration, P- phytoplankton density, I- total nutrient inflow. Concentration of N and P will change according to: dN/dt = (I - N) D – e N P dP/dt = e N P - D P where D is the flushing rate of the lake, e is the efficiency of phytoplankton uptake. Flushing rate: D = Q/V. In steady state: N* = D/e, P* = I - D/e. Look: N* + P* = I If we measure eutrophication as an increase in phytoplankton concentration, the concentration will increase linearly with the nutrient inflow. So we see that carrying capacity is linearly related to the nutrient inflow because when P* reaches a critical concentration, DO will drop to the value where fishkill is imminent.

16. Page 16 Assumptions of Model HYDRODYNAMIC TRANSPORT 2D Model Grid size: 75m x 75 m (160 x 301 grid points) A number of open boundaries: Tidal forcing obtained from pressure gauges PARTICLE DISPERSION (RESIDENCE TIME) Each grid has a particle Bottom friction varied depending on type of structure: cf=0.001 (no structure) cf=0.25 ( fish cage, fish aggregating device (FAD),fyke net) cf=0.5 (fish pen and bivalve culture)

17. Page 17 Residence Time of Control Assuming no mariculture structure High residence time,low flushing Low residence time, high flushing

18. Page 18 Residence Time With Varying Mariculture Structures I.Vulnerability of Channel (Caquiputan) II.Residence Time Based on actual distribution of structures (2003)

19. Page 19 I. CAQUIPUTAN CONTROL Blocked CaquiputanResidence Time Residual (Blocked & control)

20. Page 20 II. YEAR 2003 CONTROL Distribution of Structure (2003) Residence Time Residual (2003&control)

21. Page 21 CRITICAL SITE 2003 DistributionResidence Time (B) Residual (D-B) W/o CaquiputanResidence Time (D) Removing the structures in Caquiputan will significantly improve the residence time