1. Ken T.M. Wong Department of Civil Engineering, The University of Hong Kong Red Tide Field Monitoring and Forecasting at Kat O and Lamma Island, HK

2. Algal Bloom / Red Tide - rapid increase in number of microalgae - discoloration of water Harmful Algal Blooms (HABs) - beach closure - mariculture loss due to fish intoxication, oxygen depletion or fish gill irritation. - human intoxication through shellfish-vectored poisoning or direct contact with the toxic species Massive Red Tide in 1998 - estimated mariculture loss over HK$315 Million

3. Continuous Field Monitoring Kat O Luk Chau Wan Estuarine Oceanic (diatom dominate) (dinoflagellates become more active)

4. Monitoring Parameters Meteorological Information Wind, Air Temperature, Solar Radiation, Photosynthetical Active Radiation (PAR) Hydrographic Information Tidal Level, Tidal Current Water Quality Water Temperature, Dissolved Oxygen (DO), pH, Salinity, Chlorophyll, Secchi Depth, Suspend Solid (SS), Cell Count, Nutrient (DIN, ON, PO 4 +, Si)

5. Anemometer Pyranometer Acoustic Doppler Current Meter Water Profiler Relay box Magnetic valves Thermistor box Micrologger Peristaltic pump Fluorometer DO meter & probe Telemetry System

6. 06:00 12:00 18:00 24:00 CTD Profile Telemetry Data of a Typical Day ( 11Dec00 )

7. Biweekly Water Sampling Cell sample - live and fixed Nutrient - DIN, PO4, Si, ON Chlorophyll-a, SS, Secchi Depth

8. Alarming Level Red Tide Early Detection 24hrs Field Survey

9. Red Tides observed from 2000 to 2004 Kat O StationLamma Station

10. Dinoflagellate Bloom at Kat O (Mar2001)

11. Diatom Bloom at Lamma Island (Aug2000)

12. Transportation of red tide patch Tidal Flushing (NEST Lagrangian particle method) (from Lee and Qu, 2004)

13. Red Tide Organisms Non-motile algae (diatoms) Rapid growing (1-2 doubles per day) Move passively by water turbulence Motile algae (dinoflagellates) Slow growing (less than 1 double per day) Swimming actively and aggregation Algae – plants require light (energy source) and nutrient (material source) for photosynthesis

14. Depth (m) Chlorophyll Fluorescence (  g/L) Depth (m) Dissolved Oxygen (mg/L) 06:0012:0024:0018:0006:0012:0024:0018:00 Observed Vertical Structure Diatom Bloom (August 2000)Dinoflagellate Bloom (March 2001)

15. Condition of red tide formation by non-motile species irradiance surface photiczone (thickness = l) non-productive lower segment simplified growth function depth z net growth rate =  loss rate =d sinking velocityv turbulent diffusivityE irradiance surface (thickness = l) non-productive lower segment simplified growth function depth z net growth rate =  loss rate =d sinking velocityv turbulent diffusivityE Consider the effect of turbulent diffusion, sinking and growth/mortality on the algal concentration...... For a typical diatom growth rate  =2day -1, depth of photic zone l=5m, the criteria for bloom formation is E<2.3×10 -4 ms -2

16. Condition of red tide formation by motile species Consider aggregation of motile species with vertical migration For a typical dinoflagellate swimming speed v = 1mhr -1, migration distance =5m, the criteria for bloom formation is E < 1.4×10 -4 ms -2......

17. Competition Threshold (for bottom nutrient source) non-motile species motile species swim down nutrient source For motile species, they swim down to acquire bottom nutrient For non-motile specie, nutrient has to be supplied through turbulent diffusion...... For a typical dinoflagellate growth rate  ’=0.5day -1, algal nitrogen concentration for bloom C N =100  gL -1, depth of photic zone l=5m, bottom nitrogen concentration at bloom N 0 =200  gL -1, the competition threshold E < 3.6×10 -5 ms -2

18. Triggering Nutrient Level nutrient utilisationstability criteria giving a typical triggering nitrogen concentration around 100  gL -1 to 200  gL -1 (a typical value of 120  gL -1 ) Similar triggering level has been observed based historical records of red tides in Hong Kong

19. Red Tide Prediction Model triggering level stability criteria competition threshold

20. Validation with Red Tides Monitored

21. Comparison of predicted bloom occurrences with field observation

22. Comparison of predicted blooms of motile and non-motile species with field observations

23. Red Tide Triggering Factors at Lamma Island

24. Red Tide Triggering Factors at Kat O

25. Conclusions An online early warning system has been set up The system is capable to detect and give extensive data on red tide A simple vertical stability theory has been devised to determine the condition necessary for red tide occurrence A practical mathematical model has been constructed to predict the likelihood of red tide occurrence with readily available field measurements The mathematical can help understand the characteristics and reasons for red tide occurrences at the red tide blackspots