Workshop on Advanced Technologies in Realtime Monitoring and Modeling for Drinking Water Safety and

1
Workshop on Advanced Technologies in Real-time
Monitoring and Modeling for Drinking Water Safety
and Security

• Dr. David Lipsky
• Acting Director
• Drinking Water Quality Control
• New York City Dept. Env. Protection

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What Are Water Safety Concerns

• Inadequate and too broad statement of issue.
• Lots of constituents and threat scenarios to
  consider.
• Cannot quantify safety.
• Laundry list of technologies.
• No guidance for decision makers.

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Example of Problem

• Recent article in EST on water quality
  security.Several reports have detailed the need
  for developing monitoring technologies and
  research to address future water quality
  concerns, which can then be incorporated into a
  risk assessment framework.

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Risk Management Framework

• Reverse the above.
• Apply risk management framework first.
• What constituents present a credible risk to
  water and then evaluate the availability,
  effectiveness, cost, and level of risk reduction
  provided by the monitoring technologies.
• Separate into risk bins.
• High-probability high consequence events vs.
  Low-probability-low consequence events.

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Contd

• Evaluate both screening and broad brush approach
  (e.g. Bioassays) versus chemical or microbial
  specific technologies.
• Risk to water should arguably be greater than
  other routes of exposure (air, food).

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Technology Goals

• A system to reliably identify medium to high
  consequence contamination events in source water
  or distribution systems in time to allow an
  effective local response (that will prevent,
  mitigate, or reduce risk to the greatest extent
  practicable).

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Goals Contd

• Decision support tools to turn monitoring/modeling
  data into information for risk managers.
• Affordability.
• Meets DQO and QA objectives for accuracy,
  reliability, reproducibility, and timeliness.
• Remotely operated.

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Goals Contd

• Maintainable.
• Functions year around.
• Not overly sensitive to flow changes, treatment
  changes or differences in background water
  quality.

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Decision Support Tools

• Decision support tools, response actions,
  contingency plans, and data interpretation
  guidelines need to be coordinated with local
  health, state and federal oversight agencies, in
  advance.
• If measure surrogate parameters or gross
  indicators (e.g. Bioassays)-need to establish a
  network of local/regional centers of analytical
  (chemical and microbiological) excellence to
  quickly quantify and assess actual risk.

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Other Helpful Non-water Quality Technologies

• Syndromic surveillance-may be important in
  identifying waterborne versus airborne exposures.
• Robust complaint center.
• Tying in water complaints to robust GIS grid and
  Syndromic surveillance may be most cost-effective
  approach towards early detection of many acute
  chemical threats.

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Other Safety Issues

• Risk managers have to make difficult and complex
  decisions, quickly, often with inadequate
  information.
• Complex monitoring and modeling technologies need
  to provide appropriate and targeted answers for
  risk managers.
• Need to understand and fill data gaps and improve
  risk assessments.
• Technology good but no substitute for sound,
  experienced judgment.

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Water Quality Monitoring

• Sampling Stations
• Located throughout NYC
• Locations for the stations were chosen based on
  the need to gather representative samples of the
  water quality in all distribution areas

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Water Quality Monitoring

• Water samples are analyzed for
• Bacteria
• Chlorine levels
• pH
• Inorganic and organic pollutants
• Turbidity
• Odor
• Other water quality indicators
• Substantive No. Samples each week

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Water Quality Monitoring

• PC/RM
• A variety of parameters monitored continuously at
  various locations.

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Data Usage

• PC/RM data available on-line and includes alarm
  indicators and dial-out.
• Enhancing real-time monitoring within reservoirs.

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Use of Models

• DEP has actively supported the development,
  calibration, and verification of linked
  terrestrial and reservoir models.
• These models help provide information for
  operational, regulatory, and management
  purposes.
• Have been used for predictive purposes.