Aroon Melwani, Michelle Lent, Ben Greenfield, and Lester McKee

1. San Francisco Estuary Institute Item #1b Optimizing sampling methods for pollutant loads and trends in San Francisco Bay urban stormwater monitoring Aroon Melwani, Michelle Lent, Ben Greenfield, and Lester McKee Sources Pathways and Loadings Workgroup May 6th 2010

2. San Francisco Estuary Institute Background • Small Tributary Loading Strategy – • Quantify annual loads or concentrations of pollutants of concern • Quantify the decadal-scale loading or concentration trends • Support small tributary loading monitoring plan that meets the objectives of MRP Provision C.8.e

3. San Francisco Estuary Institute Study Design • Two components: • Compare strategies for determining annual pollutant loads • Determine the power and sample size needed to detect declining trends in concentrations • Statistically sub-sampled existing empirical data sets • Examined scenarios to optimize sampling designs and strategies

4. Data Used • Guadalupe River • Water years 2003 – 2005 • 236 km2 (downstream from reservoirs) • 80% urbanized • Zone 4 Line A • Water years 2007 – 2009 • 4.5 km2 • 38% industrial

5. San Francisco Estuary Institute Approach • Following Leecaster et al. (2002) • Within-storm Designs • Among-storm Designs • Turbidity-surrogate Regression • Trend Analysis

6. San Francisco Estuary Institute Best Estimate of Loads • Turbidity-surrogate methods (McKee et al.) • Continuous turbidity measurements (5 - 15 mins) • ~ 10 - 40 grab samples per year • Regressions used to determine continuous concentrations • Combined with flow measurements to calculate loads = Baseline for all design comparisons

7. San Francisco Estuary Institute Within-storm Designs

8. Storm Sampling • Simulated ISCO protocols • Flow Sampling Criteria (1:1) Flow (cfs)

9. San Francisco Estuary Institute Within-storm Designs

10. San Francisco Estuary Institute Among-storm Designs * Largest storm selected randomly from three highest discharges per water year ** MRP design

11. San Francisco Estuary Institute Turbidity Surrogate Simulations • Simulated TSR using sub-sampled turbidity-pollutant data • Determine mean slope and intercept to calculate loads • TSR loads compared against loads from all samples

12. San Francisco Estuary Institute Trend Analysis • Trends evaluated in Hg and PCBs • Targets • 0.2 mg Hg / kg SS • 0.002 mg PCBs / kg SS • Used Coefficient of Variation to examine trend • Power examined for trends in 10, 20, 25 or 40 years

13. San Francisco Estuary Institute Within-storm Results

14. Results Accuracy Precision Units are fractional percent bias, e.g. 0.05 = 5%

15. San Francisco Estuary Institute Within-storm Design Strategies

16. San Francisco Estuary Institute Among-storm Results

17. San Francisco Estuary Institute Guadalupe River (WY 2004)Hg First Flush + Random n First Flush + Random n First Flush + Random n First Flush, Largest storm + Random n First Flush, Largest storm + Random n First Flush, Largest storm + Random n Random n Random n

18. San Francisco Estuary Institute Zone 4 Line A (WY 2007)PCBs First Flush + Random n First Flush, Largest storm + Random n Random n

19. Sampling Design Results • The optimal within-storm design was an equal-spacing design (1:1), n = 12 or 18, with the linear interpolation estimator • The optimal among-storm design was first flush or first flush and largest storm with 10 storms total (the maximum number evaluated) • Design with first flush and largest storm generally biased high when few storms sampled • Random design showed less bias when few storms sampled, but very poor precision

20. San Francisco Estuary Institute Turbidity-Surrogate Simulations

21. Guadalupe RiverHg

22. San Francisco Estuary Institute Zone 4 Line APCBs

23. San Francisco Estuary Institute TSR Simulations • Turbidity-surrogate results indicate that accurate loads could be obtained with significantly less samples • Precision in annual loads was optimal with 7 – 10 samples per year, depending on year and pollutant

24. San Francisco Estuary Institute Trend Results

25. San Francisco Estuary Institute Guadalupe River * Hg: n = 25; n = 37; n = 52 ** PCBs: n = 21; n = 19; n = 12

26. San Francisco Estuary Institute Zone 4 Line A Target set to 0.05 * Hg: n = 30; n = 15; n = 21 ** PCBs: n = 18; n = 15; n =14

27. San Francisco Estuary Institute Power Results • Power for current sample sizes generally high • Inter-annual differences apparent • Could reduce sampling effort to 10 grab samples per year without loss of power for trend detection

28. San Francisco Estuary Institute Next Steps • Choice of sampling method is a compromise between • Accuracy (true loads) • Precision (width of confidence) • Cost (field logistics, QA/QC, Reporting) • Next step - cost out the recommended designs

29. San Francisco Estuary Institute Discussion • Straw-man • Linear interpolation estimator with 12 samples/storm and 10 wet season storms • Turbidity surrogate method with 7 – 10 grab samples • Trend detection need 10 grab samples • Are loads estimates every year needed or are loads calculated every few years sufficient, with less intense annual monitoring for concentrations and trends

30. San Francisco Estuary Institute Appendix Slides

31. San Francisco Estuary Institute Guadalupe RiverHgFlow

32. San Francisco Estuary Institute Guadalupe RiverHgTurbidity

33. San Francisco Estuary Institute Z4LAHgFlow

34. San Francisco Estuary Institute Z4LAHgTurbidity

35. San Francisco Estuary Institute Guadalupe River (WY 2004)PCBs

36. San Francisco Estuary Institute Guadalupe River (WY 2005)Suspended Sediment

37. San Francisco Estuary Institute Zone 4 Line A (WY 2007)Hg

38. San Francisco Estuary Institute Zone 4 Line A (WY 2009)Suspended Sediment

39. San Francisco Estuary Institute Guadalupe RiverPCBs

40. San Francisco Estuary Institute Guadalupe RiverSuspended Sediment

41. San Francisco Estuary Institute Zone 4 Line AHg

42. San Francisco Estuary Institute Zone 4 Line ASuspended Sediment