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Assessing Fecal Coliform Contribution During Storms at Kensico Reservoir: A Case Study

This presentation outlines a case study conducted at Kensico Reservoir to assess the potential fecal coliform contribution during storms. It examines the effect of storms on coliform concentration using historical data and compares low flow and storm loads to other estimates. The study highlights the importance of using historical data to estimate fecal coliform loading during storm events.

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Assessing Fecal Coliform Contribution During Storms at Kensico Reservoir: A Case Study

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  1. Using Historical Data to Assess Potential Fecal Coliform Contribution During Storms at Kensico Reservoir: A Case Study Christian Pace, NYCDEP and Kerri Alderisio, NYCDEP NYC Watershed/Tifft Science and Technical Symposium Thayer Hotel West Point, NY September 19, 2013

  2. Presentation Outline Kensico Reservoir Effect of storms on concentration Case Study: TS Irene / Lee Historical FC data Loading estimate from flow and concentration Compare low flow + storm loads to other estimates Summary

  3. Kensico Reservoir New York City’s terminal source water reservoir - 30.6 BG storage Aqueduct Monitoring Sites Influents – CATALUM – DEL17 Effluent – CATLEFF – DEL18 Kensico also has its own small watershed = 34.3 km2 Mixed land use approx. <1% of annual flow • During storms… direct runoff pushes stream flow contribution from 0.1% at base flow up to 4% (or more in extreme cases)

  4. Kensico Reservoir Watershed • Aqueducts provide most of the inflow >1 BGD • Eight perennial streams • Monitoring began: MB-1 1987 Others 1991 • WQ samples taken monthly • Each equipped for flow monitoring • Ungauged area = approx. 54%

  5. Kensico Reservoir Watershed • Aqueducts provide most of the inflow >1 BGD • Eight perennial streams • Monitoring began: MB-1 1987 Others 1991 • WQ samples taken monthly • Each equipped for flow monitoring • Ungauged area = approx. 54%

  6. Base Flow Storm Flow

  7. Storm Event Effects Flow and G/C composite sample results for stream N5-1MAIN Storm on 10/17/2006, Rainfall total = 0.82” • Small stream flow increases 10X+ during moderate events and 100X+ during extreme events • Pathogens more concentrated in storm runoff - Generally consistent for bacteria and protozoans

  8. Extreme Events : Case Study TS Irene/Lee • Tropical Storm Irene Aug 27–28, 2011 • Preceded by wet August (>7” rain) - 2.85” rain 3 weeks before - 3.14” rain 2 weeks before - almost 1” in 7 days prior • Intense rain (up to 0.92” in 10min) • Rainfall total = 6.60” – 7.06” • Sharp rise in fecal coliform at effluents (less than 24 hours) • TS Lee (+ Katia) Sept 6–8, 2011 • 8 days after TS Irene • Less intense (<1” per hour) • Rainfall total = 6.27” – 6.80” • Sharp rise in fecal coliform at effluents • Elevated FC counts at Kensico into October

  9. Prior DEP Work with Loading Estimates • Methods created for Kensico protozoan budget (2009) • Vital to separate storm and base flow for loading estimates • Importance to factor in whole watershed (gauged and ungauged sub-basins) • Apply method to estimate fecal coliform loading

  10. Fecal Coliform Data Data Handling Utilize only data for existing stream conditions (ex. post-BMP) (BMP data from ~2000 and unmodified stream data from 1991) Coliform data issues Confluent growth – samples removed Too Numerous To Count (TNTC) – samples removed Greater than or equal, estimated – Used value given Non-detects or “Less thans” (ex. <1, <10, etc.) - ??? <14% of samples for any stream were non-detects

  11. Handling of FC Non-Detects Medians

  12. Separation of Storm Influence Rainfall Bin Classification System Divide long-term routine and storm event dataset into bins according to: - Amount of precipitation - Time interval since precipitation Allows for use of data prior to flow measurement Westchester County Airport and DEL18 met station data used

  13. Separation of Storm Influence Sample N using historical data Between 132 and 549 samples from each site

  14. Separation of Storm Influence MB-1 FC Concentrations Significant difference between low flow and storm flow Mean and median increase with rainfall bin

  15. Separation of Storm Influence N5-1 FC Concentrations Significant difference between low & storm flow, but doesn’t increase for every rainfall bin

  16. Separation of Storm Influence Mean FC concentration using historical data

  17. Separation of Storm Influence Median FC concentration using historical data

  18. Concentrations Used to Create Load Estimates Following the same rainfall criteria used to create means/medians … • Apply the appropriate concentration to flow measurements (10-min) • Must consider cumulative amount of rainfall and time interval since accumulation • Historical mean represents high estimate (worst-case scenario) • Historical median represents lower estimate • Utilize samples taken on site during the time period • DEP assigned these measured values to a 6-hr timespan

  19. Concentrations Used to Create Load Estimates WHIP Flow (10-min) Sampled on site Median Concentration

  20. Concentrations Used to Create Load Estimates WHIP Flow (10-min) Sampled on site Median Concentration Mean Concentration

  21. FC Loading Estimate – Whippoorwill Brook Historical means when missing values Flow Loading estimate Closely follows flow because mean is applied consistently (except when samples were collected)

  22. Kensico Perennial Stream Loading Estimate Volume (L / 10 min) and fecal coliform load (accumulating) for 8 streams Aug 23 – Sept 12, 2011 Aug 28 8 Streams = 10.6% Kensico Input Volume* * Estimated flow – above rating curves

  23. Kensico Perennial Stream Loading Estimate Cumulative loading estimate for 8 streams (Aug 23 – Sep 29, 2011) (~46% by area) Arithmetic Mean Estimate 97.7 trillion N12 E10 MB-1 E11 WHIP E9 Median Estimate 57.7 trillion BG9 N5-1

  24. Kensico Input Loading Estimates Arithmetic Mean Estimate 249.0 trillion FC N12 E10 MB-1 E11 WHIP CATALUM E9 BG9 DEL17 Median Estimate 162.0 trillion FC N5-1 Ungauged Watershed (54% by area)

  25. Breakdown of Loading Estimates Median Loading Estimate Total load = 162.0 trillion FC Mean Loading Estimate Total load = 249.0 trillion FC Estimated Watershed Load - 77.5% Estimated Watershed Load - 85.4%

  26. Tropical Storms Irene and Lee HDR/Gannett Fleming (JV) contracted to : - Review events and DEP operational response - Create fecal coliform loading estimate for these storms - Assess function of BMPs during the storm - Make recommendations on future response measures and program enhancements to protect WQ Final Summary Report – May 2012

  27. Tropical Storms Irene and Lee

  28. Tropical Storms Irene and Lee 80,000 MB-1 Hydrograph from Aug 26 – Sept 13, 2011 60,000 40,000 FC Concentrations (FC / 100mL) 20,000 JV used 2 approaches to “fill in” daily concentration data for FC load estimates: • Interpolated concentrations between samples & geometric means for ungauged areas • Missing values set to the median concentration from historical data (Jul ‘99 – Nov ‘11)

  29. Kensico Input Loading Estimates Arithmetic Mean Estimate 249.0 trillion FC JV Interpolated Estimate 170 trillion FC Median Estimate 162.0 trillion FC JV Median Estimate 61 trillion FC

  30. Summary Many ways to do loading calculations for a complex system such as Kensico Goal to estimate worst case scenario during timeframe Separating historical samples by storm size allowed us to differentiate loading calculations by storm size Use of “0” for non-detect samples did not significantly affect mean or median concentrations Worst case load estimate = 249.0 trillion FC Sample sizes: DEP 132 - 549 samples from each site JV 58 - 184 samples from each site DEP estimates: High estimates are almost 1.5X JV high Low estimate is more than 2.6X JV low

  31. Acknowledgements WWQO East of Hudson Field Staff Kensico Laboratory Staff Kurt Gabel and James Alair Kelly Seelbach Glenn Horton and Jim Machung *2012. HDR Gannett Fleming. Kensico Reservoir Watershed Assessment, Fecal Coliform Occurrence, and Operation Response During and After Tropical Storms Irene and Lee – Final Summary Report. May 2012.

  32. THANK YOU! Questions?

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