Water Quality

Ru Morrison, NERACOOS

Pixie Hamilton, USGS

Water Quality

John Haines, USGS, Pixie Hamilton, USGS, Ru Morrison, NERACOOS, Mario Tamburri, ACT, Jawed Hameedi, NOAA NCOOS

Types of RA activities related to Water Quality Types of RA activities related to Water Quality

Plume Tracking

Observations, including support for partners

Data Services - simplifying access to data for users

Customized Products

Beach Water Quality Assessment and Modeling Activities

Issue: Exposure to beach swimming waters with elevated bacterial levels is a public health concern.

Goal: Develop and implement scientifically-justified decision-support tools to for accurate and defensible preemptive advisory issuance decisions.

Process:Level 1

0%

10%

20%

30%

40%

50%

60%

NMB2 NMB3 MB1 MB2 MB3 MB4 SS GCPerc

ent M

iscl

assi

ficat

ion

1.) Data integration

2.) Model development

3.) Model validation

4.) Operational decision-support tool

Who is doing it: Related work is taking place within 6 of the RAs.

Drinking Water Quality:Drinking Water Quality:Huron Erie Corridor Waterways Forecast System (HECWFS)Huron Erie Corridor Waterways Forecast System (HECWFS)

Goal: • Reduce health risks and

costs associated with pollutant spills in the Lake Huron to Lake Erie Corridor

Major Elements:• Link 2d model for corridor

to NOAA Great Lakes Forecasting System

• Generate 3d public domain model

• Use 3d model to support water intake risk assessment work

Water Quality and Ecosystemslight

Chl & TSM

DO

nutrients

NJDEP, EPA, Rutgers, MARACOOS

Gliders: Capture spatial features• DO Part of NJ water quality monitoring

• Unraveled causes and help predict predict low DO low DO in the Long Island Sound

Buoys: Capture high resolution temporal features• Unraveled controls of light penetration in Great Bay Estuary, NH helping protect critical eelgrass habitat through developing Nutrient CriteriaNutrient Criteria

Harmful Algal BloomsRapid Detection/Timely Forecasts

Range of ObservationsLifeguards w/smart phones, Shore stations, Moorings, Gliders, fluid imaging, Satellites

TechnologyDevelopmentACT workshopsNew sensors

Analysis and ModelilngNOAA Forecasts

Data source: N.N. Rabalais, Louisiana Universities Marine Consortium, R.E. Turner, Louisiana State University Funded by: NOAA, Center for Sponsored Coastal Research

Bottom Water Dissolved Oxygen in the Gulf of Mexico

Yield delivered to estuary from watershed, kg/yr/ha

Eutrophic, influenced by nitrogen input

Technology to Meet User Needs

Technology Trends:• Affordable and accurate physical and chemical sensors• Sensors deployed on multiple fixed and moving platforms • Real-time data and communications

Technology Needs:• Improved spatial and temporal coverage• Reliable/robust sensors (e.g., antifouling) that are easy to use• Bio- and geno-sensors (from marine mammals to microbes)

ACT supports IOOS by:• Independent third-party testing for technology

developers/manufacturers and users• Forum for communication and consensus on state of

technology and user needs• Coastal and ocean technology information clearinghouse

Water-Quality Data Exchange and Portal

Northeast Data Management and Portal

Research/ discovery

TrendsStatus Modeling ecol. impacts

Source attribution

Weather & Climate Assessments Forecasting Volunteer monitoring

0

100

200

300

400

500

600

1988 1991 1997 2003

Year sampled

Cu (ppm) in oysters (IRL)

NOS/National Centers for Coastal Ocean ScienceWater Quality-Related Portfolio

Invasive species

National Water Quality Monitoring Network for U.S. Coastal Waters and Their Tributaries (“Network”)

Continuum of observations in:

Estuaries Near-shore waters Off-shore waters Great Lakes Coastal beaches Wetlands Flow and flux from streams, groundwater, atmosphere

Discussion Questions1. There are successes (in new technology and observation

capabilities, data integration and interoperability, scientific analysis and modeling and decision support tools) around the country – at the regional and national levels. How do we transform these successes into a sustained national effort? What’s working that can be expanded right now? What are the gaps/challenges that is preventing a national effort.

2. Data management provides a vehicle for the multitude of WQ providers to share data. How do we continue the progress made to date? How do we fund data management efforts? How to engage the broader interagency community and the larger community?