1. NYWEA WSTC at West Point, NY September 15, 2009 The Impacts of Reservoir Drawdown on Water Quality in NYC’s Catskill and Delaware Reservoirs by L. Janus, R. VanDreason, G. Marzec, J. Mayfield, D. Pierson, R. Gelda

2. Impacts of Drawdown on Water Quality Outline: 1.0 Introduction Why is drawdown important? Why is drawdown important? How was the analysis conducted? How was the analysis conducted? 2.0 Hydrology and water quality 2.0 Hydrology and water quality Elevation histories Elevation histories Water residence times – headwaters vs terminal Water residence times – headwaters vs terminal Relation of hydrodynamics to WQ Relation of hydrodynamics to WQ 3.0 Reservoir WQ observations: Time series plots: 20-years of water quality Time series plots: 20-years of water quality WQ vs elevation relationships WQ vs elevation relationships ‘Breakpoints’ and correlations ‘Breakpoints’ and correlations 4.0 Diagnostic Modeling Ashokan – 2008 drawdown Ashokan – 2008 drawdown West Branch during 2008 drawdown West Branch during 2008 drawdown 5.0 Conclusions

3. Approach:  literature review - nation-wide  Review hydrodynamics  Relate elevations to reservoir WQ Time series behavior Time series behavior Correlations of WQ with elevations Correlations of WQ with elevations  Analyze case studies of specific events diagnostic modeling diagnostic modeling 1. Introduction Objectives: Objectives:  Define how and when DEP reservoirs respond to drawdown.  Determine elevation ‘targets’ that are protective of WQ.  Understand how drawdown or prolonged drought might affect WQ.  Gain insight into impacts of climate change.

4. Literature Review  Nationwide review; studies have demonstrated: Increased sediment resuspension occurs at a threshold level. Increased sediment resuspension occurs at a threshold level. Impacts on algal dynamics with increases in chlorophyll Impacts on algal dynamics with increases in chlorophyll Impacts on the thermal structure, with decreases in the duration of stratification. Impacts on the thermal structure, with decreases in the duration of stratification. changes to benthic invertebrate communities changes to benthic invertebrate communities impacts on fish populations impacts on fish populations  3 NYC Watershed Studies: Effler & Matthews, 2004; Effler & Bader, 1998; Effler, et al., 1998 Effler & Matthews, 2004; Effler & Bader, 1998; Effler, et al., 1998 Major drawdown at Cannonsville in 1995 demonstrated: Major drawdown at Cannonsville in 1995 demonstrated: Increased tripton (suspended particles other than algae) Increased tripton (suspended particles other than algae) Increased turbidity Increased turbidity Increased phosphorus Increased phosphorus Enhanced phytoplankton growth Enhanced phytoplankton growth Decreased Secchi depth Decreased Secchi depth

5. 2.0 Hydrology and water quality Configuration of NYC’s Catskill and Delaware Reservoirs: 2.0 Hydrology and water quality Configuration of NYC’s Catskill and Delaware Reservoirs: Map by D. Lounsbury - terminal reservoirs receive flow from upstream headwater reservoirs - terminal reservoirs receive flow from upstream headwater reservoirs

6. Schoharie West Basin Ashokan East Basin Ashokan Proportion of Available Storage Water Surface Elevation (meters above sea level) Catskill Reservoirs - elevation and storage histories:

7. Cannonsville Pepacton Neversink Rondout Water Surface Elevation (meters above sea level) Proportion of Available Storage

8. Water Residence Times - 30 years (Volume/Hydraulic load = replacement rate)

9. How does hydrology affect water quality? History:  equations developed in 1960s by Vollenweider basis of OECD solution to eutrophication problems in Europe basis of OECD solution to eutrophication problems in Europe basis of TMDLs in the US basis of TMDLs in the US  Late 1960s National Eutrophication Survey by USEPA  1981 EPA issued Restoration of Lakes and Inland Waters resulting from conference in Portland, Maine  1983 Chapra & Reckhow explored refinements – sedimentation Hydrology is a determinant of Water Quality:  Hydraulic loads determine water residence times, nutrient loads, and reservoir nutrient concentrations  Water residence times are a primary determinant of nutrient concentrations and influence primary production, turbidity, and Secchi depths

10. Critical phosphorus load - is a function of depth and hydraulic load. - shallower lakes tolerate lower nutrient loads (from Vollenweider, 1976)

11. Observations on hydrology of NYC reservoirs:  Reservoirs typically have shorter water residence times than lakes (average of 1.3 years for North American lakes).  Terminal reservoirs show very stable elevations and water residence times (with the exception of drought periods).  Terminal reservoirs have greater hydraulic loads than upstream reservoirs, and therefore shorter water residence times. More rapid flushing benefits WQ.  Headwater (upstream) reservoirs are more frequently drawn down than terminal (downstream) reservoirs, therefore provide insight into WQ changes due to drought.

12. 3.0 Water Quality: potential impacts of drawdown cited in the literature were explored with reservoir data:  Turbidity  Conductivity  Eutrophication indicators: (Secchi depth, nutrients, algae) (Secchi depth, nutrients, algae)  Bacteria – fecal coliforms

13. Scatter Plot Analysis Methodology: Scatter Plot Analysis Methodology: Monthly (April-December) reservoir medians using all sample depths and sites from1988-2007 Monthly (April-December) reservoir medians using all sample depths and sites from1988-2007 Only elevations 0.5 ft below spill considered Only elevations 0.5 ft below spill considered LOWESS curves shown LOWESS curves shown Spearman correlations Spearman correlations Non-parametric rankingNon-parametric ranking P<0.05P<0.05 R= -0.71

14. Cannonsville Scatter Plots R= -0.71 R= -0.55R= -0.30 R= -0.66 R= -0.11 (ns)R= 0.50

15. Pepacton Scatter Plots R= -0.46R= 0.33R= -0.10 (ns) R= -0.33R= -0.32 R= -0.20 R= -0.51 R= -0.47R= 0.59

16. Neversink Scatter Plots R= -0.28 R= -0.12R= -0.44 R= -0.37R= 0.51 R= -0.36 R= -0.68 R= -0.47 R= 0.63 R= -0.37

17. Water quality variables vs. elevation correlations with r > 0.50 (r values shown were highest at the designated elevation range) Note: There were no examples where chlorophyll a had an r of > 0.5

18. Ashokan Reservoir Bathymetry

19. Waterfowl in the East Basin of Ashokan – coincident with high fecal coliform bacteria

20. 4.0 Two Examples of diagnostic modeling: Example 1. Ashokan Example 2. West Branch Both occurred during a Rondout–West Branch Tunnel valve repair in 2008. Both occurred during a Rondout–West Branch Tunnel valve repair in 2008. Both analyses depended on high frequency monitoring. Both analyses depended on high frequency monitoring.

21. Example 1. Ashokan : Simulated Turbidity Compared to Turbidity Measured in the Reservoir by Robotic Monitoring Model simulations that include resuspension more closely match measured data. Wind driven shoreline resuspension is important.

22. What does wind resuspension look like? This photo shows resuspended clays in Schoharie Reservoir. Note photos on right: very sensitive even when nearly flat calm

23. Example 2. West Branch - High Frequency Monitoring of Turbidity (black) and elevation (red) during 2008 Delaware Aqueduct Shutdown Mean Daily Turbidity vs. Water Surface Elevation Conclusion: These data clearly link drawdown to increased turbidity Turbidity nearly doubles, but levels only reach 4 NTU

24. 5. Conclusions  Water quality is affected negatively by reservoir drawdown.  Draw-down affects flushing rates, which in turn affect water quality.  Headwater reservoirs are more frequently drawn down than terminal reservoirs due to operations; this benefits WQ as it approaches intakes.  Time series and correlations of WQ data showed correspondence to elevation, but with high variability.  Secchi depth and turbidity showed the highest correlations to elevation.  Diagnostic modeling provided insight into the role of wind-driven resuspension.  Models are essential in deciphering functional relationships between dynamically changing parameters.

25. Thank You www.nyc.dep.gov Acknowledgements: Acknowledgements: D. Kent, and Y. Tokuz for literature search, D. Lounsbury for map, C. Nadareski and M. Reid for waterfowl info, WQD field and lab staff for historic data, and UFI for modeling work