dr. eric decarlo, professor marine geology and geochemistry division dr. grieg steward, associate...
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Dr. Eric DeCarlo, Professor
Marine Geology and Geochemistry Division
Dr. Grieg Steward, Associate Professor
Biological Oceanography Division
Dr. Margaret McManus, Associate Professor
Physical Oceanography Division
Department of Oceanography
School of Ocean and Earth Science and Technology (SOEST)
University of Hawaii at Manoa
7 July 2009
Water Quality Sensing
The economic well-being of the State of Hawaii depends upon healthy coastal ecosystems.
Public confidence in water quality and safety is crucial.
Many current monitoring approaches are labor intensive and slow.
Our integrated coastal sensor/ocean observing system will:
Boost public confidence by emphasizing the usually high quality of Hawaii’s coastal waters.
Contribute to public safety by providing early warning of water quality problems and forecasting areas likely to be affected.
Water Quality Sensing
Water Quality Sensor Locations
NS-03NS-03
NS-04NS-04
University of Hawaii at ManoaMoana SurfriderUniversity of Hawaii at ManoaMoana Surfrider
Outline
1. Near Shore Water Quality Sensors
1. Water Quality Buoys
2. Pathogen Sampling
3. The Future
Near ShoreWater Quality Sensors
Sensors
SITE INSTRUMENTS MEASUREMENTS
NS01SBE 16plus,
WETLabs FLNTUSC, T, Chlorophyll,
Turbidity
NS02SBE 16plus,
WETLabs FLNTUSC, T, Chlorophyll,
Turbidity
NS03 SBE 37 SMP C, T, P
NS04 SBE 37 SMP C, T, P
Data Flow DiagramData Flow Diagram
StatusSITE LAT / LON INSTRUMENTS MEASUREMENTS TELEMETRY STATUS POWER
NS01
21°17′16″ N 157°50′26″ W(Waikiki Yacht
Club)
SBE 16plus, WETLabs FLNTUS
C, T, Chlorophyll, Turbidity
Raven XT (Sprint)
Deployed 6/27/2008. Streaming data to KN database & HIOOS
webpage
Shore based AC
NS02
21°17′11″ N 157°50′34″ W(Hawaii Yacht
Club)
SBE 16plus, WETLabs FLNTUS
C, T, Chlorophyll, Turbidity
Raven XT (Sprint)
Deployed 7/28/2008. Streaming data to KN database & HIOOS
webpage
Shore based DC
NS03
21°16′49″ N 157°50′17″ W
(Atlantis Adventures /
Hilton Hotels)
SBE 37 SMP C, T, P Raven XT (Sprint)
Deployed 1/15/2009. Streaming data to KN database & HIOOS
webpage
Battery
NS04
21°15′57″ N 157°49′22″ W
(Waikiki Aquarium)
SBE 37 SMP C, T, P Raven XT (Sprint)
Site assessment complete and location selected. Deploy July
2009
Shore based AC
NS05 TBDSBE 16plus,
WETLabs FLNTUSC, T, P, Chlorophyll,
TurbidityRaven XT (Sprint)
Recon sites West of Ala Wai. Expected
deployment Fall 2009
TBD
Water Quality Buoys
Sensors
SITE INSTRUMENTS MEASUREMENTS
WQ-KN
SBE 16plus, WETLabs FLNTUS
CO2 sensorSBE 43
C, T, Chlorophyll, TurbidityCO2, O2
WQ-AW
SBE 16plus, WETLabs FLNTUS
CO2 sensorSBE 43
C, T, Chlorophyll, TurbidityCO2, O2
StatusSITE LAT / LON INSTRUMENTS MEASUREMENTS TELEMETRY STATUS POWER
WQ-KN 1
21° 17’ 19.35” N 157° 51’ 54.00”
W
SBE 16 V2plus WETLabs FLNTUS
SBE 43LICOR CO2 sensor
C, T, Chlorophyll, Turbidity, DO (water)
O2 (air/water) CO2, (air/water)
Cellular (SBE)
Iridium (CO2)
Deployed 6/2008. Streaming data.
Battery
WQ-AW
21° 16’ 47.50” N 157° 50’ 54.00”
W
SBE 16 V2plus, WETLabs FLNTUS
SBE 43LICOR CO2 sensor
C, T, Chlorophyll, Turbidity, DO (water)
O2 (air/water) CO2, (air/water)
Cellular (SBE)
Iridium (CO2)
Deployed 6/2008. Streaming data.
Battery
Data Flow Diagram Data Flow Diagram
Early Warning System Alert
Matlab code on SOEST server
Automatic, hourly threshold checks•NS01, NS02 – salinity and temperature•USGS – rainfall, stream height, stream flow
If threshold is exceeded, the program sends text message to
Members of the Ala Wai Research Group•cell phone or emails (depending on choice)
Triggers sampling alert Other hourly checks (sends alerts if web sites are down)
Early Warning System Alert
Title: EVENT ALERT Body: Manoa rainfall is currently 0.6ft.” or “NSO1 Salinity is 15 PSU.”
If multiple thresholds are exceeded, the message adjusts to include all of the values, i.e. “Manoa rainfall is currently 0.6ft, NS01 Salinity is 15 PSU and NS02 Salinity is 18 PSU.”
What about Pathogens?
Current sensors great for monitoring chemical and physical properties of the water
A major issue for coastal recreational water users is the presence of pathogenic bacteria and viruses
The Dream
Tem
p.
(°C
)Salin
ity
Chlo
rophyll
Tu
rbid
ity
Pathogens
The Reality
No off-the-shelf sensors yet available for pathogen detection in seawater
Conventional methods are labor-intensive, slow
The Reality
Cultivation-Based Assays
Labor-intensiveHours to days
Molecular & Direct Detection Methods
Molecular - extract DNA, use tools to detect specific genes of interest
Direct Detection - Capture pathogenic viruses or bacteria on a sensor surface
Molecular MethodsLab in a can & Lab on a chip
Environmental Sample Processor (MBARI)
Expensive, complicatedHigh maintenance
Direct Capture
Pathogens
Specific Antibodies
Sensing the CaptureQuartz CrystalMicrobalance
Surface PlasmonResonance
http://www.biosensors.pan.olsztyn.pl/images/stories/reserearchprofile/qcm-2.jpghttp://spie.org/Images/Graphics/Newsroom/Imported/0882/0882_fig1.jpg
The Challenges for Automation
Biofouling
What are we looking for? Too many potential pathogens to screen for all of them
The needle in a haystack
What are we looking for? Sewage Pathogens
There are many possible pathogens, usually present at low levels
Indicator organisms, not pathogenic, but more abundant and come from the same source (e.g., enterococci as indicators of sewage)
Non-sewage pathogens: some pathogens are not pollutants
Sewage IndicatorWater quality vs. Rainfall
Exceedance data calculated from Dept of Health, Clean Water Branch web site
Water QualityWhen it rains, it’s Poor
EnterococciNot a Reliable Indicator
Data from Dept of Health, Clean Water Branch
The Needle in the Haystack Pathogens are a tiny
fraction of the microbes in seawater
Outnumbered by “good” microbes by a millions or billions to one
The Future (for Pathogens)
Pathogen sensors are under development, but there are hurdles to routine deployment
In the meantime, the abundance of non-sewage pathogens, like vibrios, may be predictable using data from existing sensors and predictive models.
You could also go into our plans for water quality deployments in the Pacific region and illustrate the potential linkage to the instruments Rusty has out with CRED
CRED is backbone of ecological Part of IOOS future
The Future(Automated Water Quality Sensors)
Installation of water quality monitoring systems in each of the PacIOOS jurisdictions.
You could also go into our plans for water quality deployments in the Pacific region and illustrate the potential linkage to the instruments Rusty has out with CRED
CRED is backbone of ecological Part of IOOS future
CRED study areas: Ecosystem Observations~50 islands & atolls
The FuturePartnership: Coral Reef Ecosystem Division
March of 2006 375,000 gallons of raw sewage were diverted
into the Ala Wai canal when a sewer main in Honolulu cracked after several days of heavy rain.
Several people who came into contact with the contaminated water became ill, and there have been suggestions that one death resulted from the incident.
For several weeks after the incident, it was unclear (1) if there were harmful bacteria in our nearshore waters as a result of the diversion, (2) if the nearshore circulation patterns were retaining Ala Wai waters nearshore.
Without an idea of the baseline biological and physical conditions in the Ala Wai and adjacent coastal waters, it was impossible to determine when and if the system had returned to baseline
An Example of the Problem
Ala Wai Research Group Members include:
Drs. Geno Pawlak and Sergio Jaramillo, Ms Jennifer Patterson (Ocean Resource Engineering UH Manoa)
Drs. Margaret McManus, Eric DeCarlo, and Grieg Steward, Mr. Ross Timmerman, Mr. Mike Tomlinson, and Ms. Olivia Nigro (Oceanography UH Manoa)
Dr. Marc Ericksen and Mr. Andrew Rocheleau (Sea Engineering)
Army Corps of Engineers (CH2M Hill Lisa Kettley) USGS - invited
Regular Conference calls/workshops 3 times/year Linked by ALERT system Coordinated physical and biological sampling