fisheries management and red tide early warning system for
Post on 25-Jan-2017
216 Views
Preview:
TRANSCRIPT
-
Project WATERMAN Public Lecture Series
Fisheries Management and Red Tide Early Warning System for Hong Kong
Project WATERMAN Public Lecture Series
Fisheries Management and Red Tide Early Warning System for Hong Kong
-
Project WATERMAN Public Lecture SeriesFisheries Management and Red Tide Early Warning System for Hong Kong
Project WATERMAN Public Lecture SeriesFisheries Management and Red Tide Early Warning System for Hong Kong
Lecture Title: Fisheries Management and Red Tide Early Warning System for Hong Kong
:
Speakers: Professor Joseph Hun-wei Lee
Principal Investigator of Project WATERMAN
Project WATERMAN
-
Project WATERMAN Public Lecture SeriesFisheries Management and Red Tide Early Warning System for Hong Kong
Project WATERMAN Public Lecture SeriesFisheries Management and Red Tide Early Warning System for Hong Kong
WATERMAN system
www.waterman.hku.hk
-
Project WATERMAN Public Lecture SeriesFisheries Management and Red Tide Early Warning System for Hong Kong
Project WATERMAN Public Lecture SeriesFisheries Management and Red Tide Early Warning System for Hong Kong
A New Environmental Knowledge BaseA New Environmental Knowledge Base
A New Environmental Knowledge Base
-
Outline
MarineFishFarminginHongKongandChallenges
WATERMANFisheriesModule
HowtoQuantifyCarryingCapacity
Whatisalgalbloom/redTide?HowcanWATERMANpredictalgalblooms?/
-
Mariculture inHongKong
Highdemandonlive/freshfish(forhighqualityfood)
300and100tonnesofmarinefishandfreshfishconsumedeveryday(top5fishconsumptioninAsia;4xworldaverage)4
Commonculturedspecies(grouper,snapper,seabream):,
BanningoffishtrawlinginHKby2012
7m
-
FishCultureZone(FCZ)
Familyoperated
Fishraftsarelocatedatshelteredcoastalwaters(weaklyflushed)
Stockingdensityvariesfromafewfishperm2 tohundredfishperm2~/
26FCZs
-
IncreaseinTotalInorganicNitrogen(TIN)inPearlRiverflow
HongKongSAR1,072km2oflandarea
1,800km2ofcoastalwatersPopulation6.7M
HongKongSAR1,072km2oflandarea
1,800km2ofcoastalwatersPopulation6.7M
1000
1500
2000
2500
3000
3500
4000
4500
1990 1992 1994 1996 1998 2000 2002 2004
Population of PRD (ten thousand )
0
0.1
0.2
0.3
0.4
0.5
0.6
1986 1988 1990 1992 1994 1996 1998 2000
TIN (mg/L) at SM7
1000
1500
2000
2500
3000
3500
4000
4500
1992 1994 1996 1998 2000 2002 2004
waste water discharge(106 t)
PearlRiverDeltaPearlRiverDelta
Pearl River - 2200 km; Annual precipitation 1470 mm; wet season flow 20,000 m3/s
-
2 1 4 1 19
411
232928
3340
88
3936
2519
10
202325
19
3731
4540
2120
3441
1413151617
0
10
20
30
40
50
60
70
80
90
100
75 7677 7879 8081 828384 8586 8788 8990 9192 9394 9596 9798 9900 010203 0405 0607 0809 10
Year
No.
of R
ed T
ides
Eutrophication,algalbloomsandredtides
Increased frequencies of harmful algal blooms, red tides, and fish kills around
the world recent decades
-
ChallengestoHKFisheries
EstimatedmariculturelossoverHK$315Million
(NewspapercuttingsfromSCMPandMingpaoDaily,1998)
Pollutionandpoorwaterquality Redtides Oxygendepletion Fishdiseaseandparasites Coldspell
MassiveRedTidein1998
-
ProjectWATERMANOnlineFisheriesManagementandRedTideEarlyWarningForecasting
ScienceBasedDecisionSupportPlatform1) Carryingcapacityforfishmanagement
sustainableandprofitablefishfarming Healthyfishproduct Healthyecosystem
2)Redtideearlywarningsystem
Dailyforecastofredtideriskforcurrentweek Predictionofredtidemovementsandmitigations
-
Marine fish farming causes local nutrient enrichment but can also be a victim of existing pollution. A robust quantitative methodology is needed for mariculture management (site selection; impact assessment; determine carrying capacity)
Organic loading Flushing rate Hydro-meteorological condition
Environmental Management of Mariculture
-
WaterQualityObjectivesforMarineWater
DissolvedOxygen 4mg/L
NH3 Annualmean 0.021mg/L
Chla
runningarithmeticmeanof5dailymeasurementsforanylocationanddepth
20mg/m3
Totalinorganicnitrogen(TIN)
Annualmeandepthaveragedtotalinorganicnitrogen
0.3mg/L
-
Cannot find
CarryingcapacityofFishFarm
-
CarryingcapacityofFishFarm
What is the capacity (stocking density) of the farm
With sustainable fish farming Meet water quality objectives Healthy fish product
High stocking Density Increase waste excretions, hence pollution Reduces growth rates (for a number of species)
-
Potential/existing fish culture zone(FCZ)
Carrying capacity of FCZ
Hydrodynamics model
Mass transport model
Water quality model (sediment water exchange)
Numerical tracer experiments
Flushing time
Pollution loading, ambient water quality
Bathymetry, tidal conditions, salinity
-
TidalFlushing FlushingTime=thetimerequiredtoexchangetheentirevolumeofthegivenwaterbodybynewoceanwateror theaveragelifetimeofaparticleinthatsystem
Insemienclosedcoastalwaters,theflushingtimecanbequitelong,intheorderof1040days.Anyalgaespeciesintroducedintotheareahasachancetogrowandbloom.
Pollutantsreleasedintothecoastalenvironmentaremixedandflushedbythehighlyvariablehydrodynamiccirculation.
pollutants
clean water
contaminated water
mixing
Semi-enclosed tidal inlet
Ocean/estuary
tidal flushing by ocean current
-
openboundary
Numerical determination of Flushing time: Release tracer in fishfarm and track changes
Computation via3D hydrodynamic and mass transport (particle tracking)model
Flushing time =average lifetime of a particle in the given water system
System = fish farm
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0 0.5 1 1.5 2 2.5 3
Time (day)
Elev
atio
n ab
ove
MSL
(m)
0
1f
oT tdM
M
-
0
0.2
0.4
0.6
0.8
1
Mas
s re
mai
ned
NESTRandom WalkDouble exponential curve f it
Tf 10 days
TracermassintheFishCultureZone
Numericaltracerexperimentfordeterminingthetidalflushingtimeinasemienclosedbay(YungShuAu)
-
1 2
1fT k k
tktko
eeMM
21 1
3D models and laboratory experiments show that the tracer mass removal process due to tidal flushing can be approximated by a double-exponential decay curve that is described by 3 flushing parameters only, from which the flushing time (or flushing rate) can be uniquely determined.
Tracer mass
Flushingtime
The three flushing parameters , k1 and k2 can be interpreted in terms of the size of the fish farm, the exchange flows between the fish farm and its surrounding and that between the water system and the external clean ocean using a two-segment model
-
dryseasonwetseason
dryseason
time(days)
M/M
o
YimTinTsaifishculturezone
Yim TinTsaiFCZ
NumericalTracerexperimentfordeterminingtheflushingtime
ChoiandLee,J.ofMarineSystems,2004;Leeetal,MarinePollutionBulletin,2002
Tolo Harbour
-
Flushing time of some representative eutrophic water bodies -
LocationTolo Harbour
Sok Kwu Wan Ma WanYim Tin Tsai Yung Shu Au Lo Fu Wat
flushing time (d) 38.0 23.6 15.8 25.8 3.1
Tolo Harbour
Dry season (Nov Feb)
Wet season (May Aug)
flushing time (d) 14.4 14.2 7.1 3.5 1.5
-
Salinity and Velocity distribution in a partially mixed estuary
Density-induced circulation due to salinity gradients
-
Numerical simulation of salinity intrusion in a rectangular estuary (with fresh runoff Qf and 2.8Qf)
S/So
-
Tolo HarbourResidence time = mass weighted average of the time taken by individual particles to leave the system through the open boundary = system-wide flushing time
Movement track for individual particles
-
Wet season Dry season
Flushing time (days) 3.5 25.8
Flushing rate (day-1) 0.2857 0.0388
Sok Kwu Wan
the wet season flushing time is about an order of magnitude smaller than that for dry season;
For other coastal bays in Hong Kong, the wet season flushing rate is only about 2~3 times that for dry season
Sok Kwu Wan
-
Wet Season
Dry Season
Tidal Flushing in Sok Kwu Wan
-
Vertical profiles of tidally averaged longitudinal velocity
three-layer structure (diffusion-induced circulation)
two-layer structure (commonly observed in stratified and partially mixed estuaries)
-
Flushing Time (dry / wet season) of FCZs (days)
-
Schematic diagram of the water quality model and sediment-water interactions
-
Dissolved Oxygen
Biochemical Oxygen Demand
Phytoplankton
Inorganic Nutrient
Organic Nutrient
Algal Nutrient
Inorganic Nutrient
Organic Nutrient
Sediment Oxygen Demand
Re-aeration
deoxygenationphotosynthesis
respiration
nitrification
decay
uptake
hydrolysis
Diffusion & settling
settlingsettlingsettling uptake
settling
Water Column
Sediment Layer
Water Quality Model
decay
decay mineralization
/
-
Introduced feed (100%)
Ingested nutrients
Nutrients in waste feed
Non & slow-settleableparticulates
Soluble nutrients
(15%-30%)
Settles out
Fecal nutrients
Near-field advection
(42%-51%)
Dissolves in water column
(10%-13%)
Indigestible nutrients
Digested nutrients
Retained(18%-21%)
FishFarmPollution
(70%-85%)
-
Main Physical Processes
Diagenesis (Decay)
Deposition
Diffusive fluxes
Exchange due to tides
Pollution Load
-
PavaSODh
CCk
CCkPTrgNgaNkaLkdtdC
WVPrafVNhfv
kkdt
dNV
WVNkVNkVPrfNgadtdNV
VPdkhvTrgNg
dtdPV
cpsocffsf
saopnond
NnpONpNs
fn
NnfONnp
pfs
1
1
11
1
11
1
growth respiration settling flushing nonpredatorymortality
Phytoplankton
Dissolved Inorganic Nitrogen
Organic Nitrogen
Dissolved Oxygen
uptake regeneration hydrolysis loading
deoxygenation nitrification re-aeration
maricultureactivities
decay ofsettled algae
algal production
Algal Growth Modelling
-
g(I) g(N) g(T)
sI
hesIoIsIoI
eeh
Ig
ZeoII
sIIesI
IIg
1
0
01718.2)(
1)(
Saturating intensity
ISI (ly/day) Nutrient Concentration (ug/l)
KN
Temperature (OC)
NK
NNK
NNg )(
Half-saturation constant
Limiting nutrient =NITROGEN
20)( TTg
0 20 400
1
2
3
4
0 100 200 300 400 5000
0.5
1
0 500 1000 1500 2000 25000
1 Rate of Photosynthesis
g(N)
Phytoplankton growthLimiting Factors
Light Nutrient Temperature
Or Multiple-nutrient limitation using LiebigsLaw of Minimum
-
Best Fit Curve
Riley Eq.
Riley Eq. r(p)=0.24+0.0088*p+0.054*p2/3
Best Fit Eq. r(p)=0.24-0.0057*p+0.145*p1/2
EXTINCTION COEFF. AS A FUNCTION OF CHL-A
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
0 10 20 30 40 50 60
CHL-A(UG/L)
EXTINCTION COEFF.(M-1 )
Field Data
Effect of Self-shading by algae
-
Changes in nutrient concentration and cell countsduring the growth of Porocentrum minimum in alaboratory experiment
1.0E+03
1.0E+04
1.0E+05
0 50 100 150
Time (HR)
CellCountsPerml
0
100
200
300
0 20 40 60 80 100Time(HR)
Ammoniaor
NitrateNitrogen(ug/l)
NH3
NO3
Preference of ammonia nitrogenin nutrient uptake (lab)
Field observationDec 1987 diatom bloomTIN change = 65 ug/LNH3 change = 60 ug/L
-
0
10
20
30
40
31-Dec-99 20-Jan-00 09-Feb-00 29-Feb-00 20-Mar-00 09-Apr-00 29-Apr-00 19-May-00
Chl
orop
hyll-
a (
g/L)
Surface MountedSurfaceMiddleBottom
Alarming Level
0
2
4
6
8
10
12
14
31-Dec-99 20-Jan-00 09-Feb-00 29-Feb-00 20-Mar-00 09-Apr-00 29-Apr-00 19-May-00
Dis
solv
ed O
xyge
n (m
g/L)
SurfaceMiddleBottom
Chlorophylla
DissolvedOxygen
Algal bloom dynamics:
-
fishkill
Fishkill due to Oxygen Depletion, Three Fathoms Cove, July87
Dissolved Oxygen
High water temperature and prolonged sunny clear skies led to high algal production; significant DO consumption during period of overcast skies and neap tide
Three Fathoms Cove, Tolo Harbour, Hong Kong
-
Comparison of model prediction of Chl-a (solid line) with field data (symbols) for 1987 and 1998
Less algal blooms after introduction of Tolo Harbour Effluent Export Scheme
Two-layer Diagenetic Water Quality Model for Tolo Harbour
-
Comparison of model prediction of DO (solid line) with field data (symbols) for 1987 and 1998
Low DO (below 2 mg/L) even after introduction of the Tolo HarbourEffluent Export Scheme!El Nino Effect? (1998 warmestyear on record)
Two-layer Diagenetic Water Quality Model for Tolo Harbour
-
Oxygen Consumption at Night
FISHSODh
CCkPTrgaNkaLkdtdC
saopnond 1
TBOD algal respiration re-aeration sediment oxygen demand + fish consumption
-
PDODCPLDO
PavaSODh
CCk
CCkPTrgaNkaLkPDOD
cpsocffsf
saopnond
1
)(
Potential Dissolved Oxygen Drop (PDOP)
Potential Lowest Dissolved Oxygen (PLDO)
Carrying Capacity Indicator
-
Organic loads, flushing times and key water quality indicators at six representative fish culture zones
-
Time variation of the water quality parameters in the fish farm in response to a constant loading
simulated by a box model
-
Predicted potential lowest DO level (PLDO) under different loading conditions
Potential LowestDissolved oxygenLevel (PLDO) as a measure of carrying capacity Potential DO dropOn a day of
Negligible Photosynthetic Production
YTTE - Poor flushingHigh loading
Sok Kwu Wan- Good flushing
in wet seasonModerate loading
Ma Wan- strong flushing
High loading
-
T = 30 C and kf = 0.1 day-1
Carrying capacity for: DO > 4 mg/L Chl-a < 20 ug/L
-
Carrying capacity (tonne fish) of the 26 FCZs
-
Recommended stocking density(e.g. Lo Tik Wan)
0
1000
2000
3000
4000
5000
6000
0.5 1 1.5 2
Size of Fish (kg)M
ax. N
umbe
r of F
ish
Lo Tik Wan FCZ
Raft Size
6mx6m
3mx3m4mx4m5mx5m
FCZ Carrying Capacity = 1,900 tonne
Recommended stocking densityCarrying Capacity
Licensed Area
Max Number of fishRecommended density raft area
fish size
= = 78kg/m2
=
-
surface
bottom
Why not 3D WQ Model?Uncertainties in the model parameters and the forcing conditions including loadings from other sources, the spatial and temporal variations
-
Computed and observed long-term (1990-2001) water quality for six fish culture zones
-
Observed and computed long term water quality via Box Model and Delft3d-WAQ Model in 4 FCZs of Tolo Harbour: DO, Chlorophyll-a, and organic nitrogen for dry season
-
Red tide - red discoloration of the sea by micro-organisms (mainly micro-algae)
Algal Bloom - rapid growth/ germination of micro-algae (phytoplankton) to concentration as high as 100,000 cells per ml
Red Tide and Harmful Algal Bloom (HAB)
HarmfulAlgalBloom(HAB) Oxygen depletion Cause shellfish to contain toxins Cause mass mortality of fish,
invertebrates etc. Cause fish to contain toxins Cause skin or respiratory irritations
-
Dynamicsofalgalbloomsandredtidesinsubtropicalcoastalwaters(RGCGroupResearchProject19992004)
Kat O
Lo Tik Wan
Estuarine
Oceanic
Objective: To develop real time forecasting model of algal bloom dynamics
Red Tide Research and Mariculture Management
-
Anemometer Pyranometer
Field Monitoring
Alarming Level
Red Tide Early Detection
0
10
20
30
40
31-Dec-99 30-Jan-00 29-Feb-00 30-Mar-00 29-Apr-00 29-May-00 28-Jun-00 28-Jul-00 27-Aug-00 26-Sep-00 26-Oct-00
Chl
orop
hyll-
a (
g/L)
Surface MountedBottomMiddleSurface
Alarming Level
Red Tide Early Detection
0
10
20
30
40
31-Dec-99 30-Jan-00 29-Feb-00 30-Mar-00 29-Apr-00 29-May-00 28-Jun-00 28-Jul-00 27-Aug-00 26-Sep-00 26-Oct-00
Chl
orop
hyll-
a (
g/L)
Surface MountedBottomMiddleSurface
TelemetrySystem
M a g n e tic v a lv e s
R e la y b o x
P u m p
P e rso n a lC o m p u te r
M o d e m
T e le p h o n e L in e
M o d e m
M ic ro lo g g e r
C o n tro l M e a s u re m e n t
F L U O R I M E T E R T H E R M IS T O R SD O M E T E R
P Y R A N O -M E T E R
A N E M O -M E T E R
A C O U S T I C D O P P L E R C U R R E N T
M E T E R
L A B O R A T O R Y
F IE L D
D a ta R e tr ie v a l, A n a ly s is & S to r a g e
D a ta C o lle c tio n
D a ta T r a n sm is s io n
C H L O R O P H Y L L D IS S O L V E D O X Y G E N
T ID A L L E V E L &
C U R R E N T
S O L A R R A D IA T IO N
W A T E R T E M P E R A T U R E
W IN D
-
When do algal blooms occur?
Based on field observations and theoretical modeling, we propose the first quantitative model for forecast algal blooms
-
FactorsAffectingAlgalGrowth
Irradiance
Water Temperature
Nutrient
Growth Rate = 0G(I)G(T)G(N)
T
G(T)summer species
winter speciesN
G(N)
I
G(I) algae acclimatized to high and low irradiance levels
photo-inhibition
0 optimal growth rate at reference temperature
-
Aug2000 - Chlorophyll-a
0102030405060
17-Aug 19-Aug 21-Aug 23-Aug 25-Aug
Read
ing
(inst
rum
ent v
alue
)
BottomMiddleSurfaceS.Mounted
Aug2000 - temp
23
25
27
29
31
17-Aug 19-Aug 21-Aug 23-Aug 25-Aug
Tem
pera
ture
(OC)
SurfaceMiddleBottomAir
Aug2000 - Predicted Tidal Level
0
1
2
3
17-Aug 19-Aug 21-Aug 23-Aug 25-AugTi
dal L
evel
(m C
.D.)Aug2000 - Wind speed at 3m height
0123456
17-Aug 19-Aug 21-Aug 23-Aug 25-Aug
Win
d Sp
eed
(m/s
)
Field observations show that algal blooms are highly correlated with the stability of the water column (tide, wind, stratification)
Chla
Wind
Temperature
Tide
Field observations before and during an Algal Bloom
-
RedTideForecast
Model-DataIntegration
Model-DataIntegration
Red TideForecast and Investigation
Hydro-meteorologicalData
-
Dissolved OxygenLevel
Water Quality Data
NO2NO3NH3
NutrientConcentration
Predicted Red Tide Risk and
Impacted Areas
Biological Knowledge
Past Experience
Hydrodynamic Knowledge Tidal Mixing
Solar Radiation
-
Two-layer model for vertical biomass (Wong et al., 2007)
Ct = 0 Ct < 0,
Ct > 0 )
irradiance
surface photic zone (thickness = l)
non-productive lower segment
simplified growth function
depth z
net growth rate =
lossrate = d
sinking velocity v
turbulent diffusivity E
irradiance
surface
(thickness = l)
non-productive lower segment
simplified growth function
depth z
net growth rate =
lossrate = d
sinking velocity v
turbulent diffusivity E
Considertheeffectofturbulentdiffusion,sinkingandgrowth/mortalityonthealgalconcentration
Ct = E
2Cz2 - v
Cz + kC
underwhatconditionscould:
(andalso
:
()
-
0.00001
0.0001
0.001
0.01
0.00001 0.0001 0.001 0.014l2/2
Diff
usiv
ity E
(m 2 s
-1)
Motile species
Non-motile species
Dinof lagellate(YSA)Diatom (YSA)
P. mican (Kat O2004)Dinof lagellate(YTT)Diatom (YTT)
Blooms unlikely
Blooms likely
Critical Turbulence (m2s-1) Critical turbulence
E < Ec = 4l2
(1)
Ec (m2s-1)
E(m2s-1)
-
start
Diffusivity < Critical Turbulence?
blooms likely
Nutrient > threshold?
blooms unlikely
Y
N
N
Y
Decision model for predicting algal bloom occurrences -
?
?
Environmental and hydro-meteorological conditions
-
Bloom Triggering Factor for Lamma Island Period Species10Aug00-11Aug00 Mixed diatoms
18Aug00-24Aug00 Mixed diatoms16Jun01-20Jun01 Thalassiosira subtilis20Jun02-26Jun02 Thalassiosira subtilis01Jul02-06Jul02 Skeletonema Costatum24Jul02 Chaetoceros spp.12Aug03 Pseudonitszchia pseudodelicatissima
-
1)StabilityRiskFactor (R)=CriticalTurbulence(EC)/EstimatedDiffusivity(E)
R 1:stablewatercolumnfavouringalgalblooms
2)Nutrientthreshold sufficientnutrientconcentration
100mgm3 forinorganicnitrogen 15mgm3 forphosphate
In any given coastal water, there is a risk of algal blooms if both criteria are fulfilled.
Algal Bloom Risk Map
-
Algal bloom risk map (October1995)
Bloom Risk Observed Chl-a
Sufficient nutrient
Mirs Bay
Tolo Harbour
Port Shelter
Victoria Harbour
Lamma Island
Mirs Bay
Tolo Harbour
Port Shelter
Victoria Harbour
Lamma Island
(mg/m3)
Bloom : Chl-a > 10 mg/m3
(mg/m3)
: > 10 mg/m3
-
Predictability of the Risk Map
Bloom Not Bloom Total
Bloom 86 24 110
Not Bloom 39 321 360
Total 125 345 470
VerificationofAlgalBloomRiskForecastPerformanceagainstwaterqualitydatainHongKongforyears88,93,95,9804
The algal bloom forecast is accurate for (86+321)/470 = 87% of the time: 87%
Model Predictions
Field Observations
-
0%
20%
40%
60%
80%
100%
Per
cent
age
Blo
omed
Field ObservationApproximated Sigmoid Function
0.1 10.05.02.01.00.50.2
Nutrient Criterion Fulfilled
Stability Factor R
0%
20%
40%
60%
80%
100%
Per
cent
age
Blo
omed
Field ObservationApproximated Sigmoid Function
50 30020015010070Nutrient Concentration (mg/L)
Stability Criterion Fulfilled
Index Probability Red Tide Risk1 < 30% Low2 30% ~ 70% Medium3 >70% High
Red Tide Prognostic Forecast/
P(Bloom) = P(Stability) P(Nutrient)
P(Nutrient |High Stability) P(Stability |High Nutrient)
Historical data in past 20 years
-
2005
Feb 2009
Oct 2009
Sep 2011
First generation of red tide risk map forecast using historical water quality data in HK
Daily trial of probabilistic red tide forecast for six water zones
Field surveys based on predicted red tide risk and red tide reports
Pilot red tide early warning system with daily red tide risk forecast
Milestones
Dynamics of algal blooms and red tides in sub-tropical coastal waters (RGC Group Research Project )
1999-2004
-
Harmonic Analysis
HKO Daily Meteorological Data
AFCD Biweekly Monitoring Data
MeteorologyDatabase
Water QualityDatabase
Email + manual input
FTP transfer +manual checking
DailyRedTideForecastSystem/
Nutrient Data
Tidal Range
Temperature
Salinity
Wind Speed
Secchi DepthNutrient vs threshold
Stability RiskFactor
/
-
Probability ofred tide occurrencein coming week
High
Medium
Low
Red Tide Risk Map -
Red tide occurrencein past week
EasternWaters
SoutheasternWaters
SouthernWaters
Western Waters
Tolo Harbour
NortheasternWaters
Clear Water Bay Gonyaulax Polygramma2009-03-25 2009-03-26
Clear Water Bay Gonyaulax Polygramma2009-03-25 2009-03-26
Silver Mine Bay Beach Karenia Digitata
2009-03-23 2009-03-28
Silver Mine Bay Beach Karenia Digitata
2009-03-23 2009-03-28
Fish culture zone
Red tide risk forecast map
-
TrackingfortheAugust2011RedTide
-
PilotTestingSince20092009
NE E TOL SE S W Total
2009 0/0 0/1 0/2 5/5 3/4 0/2 8/14
2010 5/5 0/0 1/2 4/5 0/4 0/1 10/17
2011 6/8 1/2 4/7 6/6 3/9 0/2 20/34
Successfully Predicted Red Tides
-
Collaboration withtheAgriculturalFisheriesandConservationDepartment(AFCD) Red tide risk prediction is available in the intranet. Alert (phone call /
email) is sent to AFCD in case of predicted high red tide risk to increase the vigilance on the field condition.
When a red tide is spotted, AFCD will send us an alert on the location and the extent of the bloom, and information on the red tide causative species.
Red tide tracking will then be run to predict the possibly affect area and the information will be send back to AFCD. Announcement on the red tide news will be made on the WATERMAN intranet as well.
AFCD will keep updates through local network. If necessary, field investigation will be carried out jointly with AFCD.
Recommendations will be given to fishermen on actions to be taken (pumping DO, pulling fish raft to safer location).
-
Prediction on 2011-8-16
-
TemporaryFishRaftRelocation
No go zones
Fish Raft Move Away from Culture Zone
-
EquipmentsuppliedtofishfarmertomonitorDO
EfficiencyAeration(Airblower+microporetubing)
DOMonitoringandAerationatFishCultureZone
Micropore air tubingElectric Air blower
-
Conclusions Redtidesandharmfulalgalbloomsarehighlydynamicandnon
linearphenomonagovernedbycomplexphysicalbiologicalinteractions
Redtidesoccurinweaklyflushedandeutrophicwaterbodiesunderfavorabletemperature,sunlightandhydrodynamicconditions
Itispossibletodevelopshorttermforecastsofredtiderisksbydatamodelintegration
Redtideandfishkillsdisasterscanbepreventedormitigatedthroughnutrientreduction,flowaugmentation,monitoringandeducation,andsimpleearlywarningsystems
-
Conclusions
-
ThankYou
-
HydrodynamicEffect Inweaklyflushedsemienclosedcoastal
waters,theoptimalalgalgrowthrate(~1perday)ismuchgreaterthantheloss/flushingrate
Henceunderfavorablelightandnutrientconditions,analgalbloomwillbeabletotakeoff
However,thisisnegatedbytheverticalmixingoutoftheeuphoticzone,sinking,andotherlosses(e.g.flushing,respiration)
Irradiance
Nutrient
Turbulence
Algae
-
Relation between Eutrophication & Red Tides in Tolo Harbour -
Rising population, increase of nutrient (annual mean inorganic N), and corresponding increase of red tides (1982-87)
1982 1983 1984 1985 1986 19870.00
0.03
0.06
0.09
0.12
0.15
0.18 Inorganic N
Ann
ual M
ean
inor
gani
c N
(mg/
L)
0.0
0.2
0.4
0.6
0.8
1.0
Population
Pop
ulat
ion
(milli
on)
Red tide number
3 11 15 16 19 19
-
1998
Temperature: Effect of Global Warming ()Mean annual air temperature in Hong Kong (1997-2008)
1998
Temperature anomalyin April 2008 = 2.3 deg C
top related