1. Mass Balance Assessment of 2014 Synoptic Survey Results: Dave Dilks Spokane River Regional Toxics Task Force 2014 Workshop January 13, 2015 1

2. Outline Synoptic survey Mass balance assessment – Approach and findings Uncertainty analysis – Approach and findings Conclusions 2

3. Synoptic Survey August 12-24, 2014 Seven Spokane River stations, plus Hangman Creek – Each sampled seven times Seven point source discharges – Sampled three times 3

4. 4 (Barker Rd.)

5. Intent of Synoptic Survey Support dry weather mass balance assessment – Measure river concentration at flow gaging locations – Measure all known dry weather sources Identify unknown sources between each station Unknown source = Downstream load – Upstream load – Known Load 5

6. Mass Balance Approach Measure flow (Q) and total PCB concentration (C) at paired upstream and downstream stations Q d, C d River Reach Q u, C u 6

7. Mass Balance Approach Calculate unmonitored load between stations – Unmonitored load = Downstream load – upstream load Q d, C d River Reach Q u, C u Unmonitored Load 7

8. Mass Balance Approach But what about instream reaction processes? – Adsorption/settling, resuspension, volatilization Results from CE-QUAL-W2 model combined with typical PCB kinetic coefficients – Each loss component determined to be small Q d, C d River Reach Q u, C u Unmonitored Load 8

9. Mass Balance Equations Load (W) = Concentration times flow – Downstream load = Q d * C d – Upstream load = Q u * C u – Unmonitored load (W ? ) = Q d * C d - Q u * C u W ? Q d, C d River Reach Q u, C u 9

10. Unmonitored Load Components Calculate unmonitored flow and concentration Q ? = Q d – Q u Q u * C u + Q ? * C ? = Q d * C d C ? = [Q d C – Q u * C u ]/Q ? Q ?, C ? Q d, C d River Reach Q u, C u 10

11. Expand to Consider Point Sources Equation can be expanded to consider point sources (and tributaries) – Unmonitored load = Downstream load – upstream load – point source load Q p,C p Q ?,C ? Q d, C d River Reach Q u, C u 11

12. Equations with Point Sources Calculate unmonitored flow and concentration Q ? = Q d – Q u – Q p Q u * C u + Q ? * C ? + Q p * C p = Q d * C d C ? = [Q d C d – Q u * C u – Q p * C p ]/Q ? Q p,C p Q ?,C ? Q d, C d River Reach Q u, C u 12

13. Groundwater Interactions Spokane River flows into and out of its adjacent groundwater aquifer This requires some adjustments to the mass balance calculations 13

14. Losing Reaches Can estimate incremental loads in losing reaches Q u * C u + W ? - Q l * C l = Q d * C d W ? = [Q d * C d – Q u * C u + Q l * C l ] Q l,C l W ? Q d, C d River Reach Q u, C u 14

15. Re-Gaining Reaches Can separate out unknown load from return of load from upstream losing reaches Q u * C u + W ? + Q l * C l = Q d * C d W ? = [Q d C d – Q u * C u - Q l * C l ] W ? Q l,C l Q d, C d River Reach Q u, C u 15

16. Mass Balance Application Compile data Define concentrations expected from known loads Assess presence unknown loads 16

17. Mass Balance Data Sources River flows – USGS gages – Gravity Discharge flows – Provided by dischargers PCB concentrations – Synoptic survey 17

18. River Flows Flow (cfs) 8/128/148/168/188/208/228/24 Post Falls637648632809916815733 Barker Rd.-271347484572-323 Trent Ave.92792391998910601050948 Spokane103010501080114012501140 Hangman Ck.101115171918 Nine Mile1040 10601190125010801120 18

19. Discharge Flows Discharge (cfs) 8/138/198/24 Coeur d’Alene5.35.4 HARSB000 Post Falls3.83.94.0 Liberty Lake1.1 1.2 Kaiser Aluminum13.314.413. 8 Inland Empire Paper11.310.911.0 Spokane County11.811.6 City of Spokane43.645.743.0 19

20. Discharge PCB Concentrations Total PCB (pg/L) 8/138/198/21Composite City of Spokane771/955234041177878 Spokane County490330/290333274 Inland Empire Paper362729572636/26292766 Kaiser Aluminum3276401246252514 Liberty Lake200193260211 Post Falls221219 200176 Coeur d’Alene1227534531668 20

21. River PCB Concentrations Total PCB (pg/L) 8/128/148/168/188/208/228/24Composite Nine Mile 156/1971931791722289784136 Hangman Ck. 646667/735324442653595 Spokane Gage 163163/14430320315839986137 Greene St. 164*207110124/1061817459124 Trent Ave. 168117152399158/17295120111 Barker Rd. 2817947111/281029 Post Falls 5392219171917/9227 Coeur d’Alene 1931119775**11 * Collected 8/13 ** Collected 8/23 21

22. River Concentrations  Flow 22

23. Assessment Using only Known Loads Compute segment by segment concentrations – Use average point source flows and concentrations measured during the synoptic survey 23

24. Predicted Concentrations Using only Known Loads  Flow 24

25. Best Estimate of Unknown Loads River ReachGroundwater Interaction Unknown Load (mg/day) All DataOutliers Excluded Coeur d’Alene to Post FallsLosing10- Post Falls to Barker RoadLosing-1.3 Barker Road to Trent AvenueMixed (losing, then gaining) 241166 Trent Avenue to Spokane GageMixed (gaining, then (losing) 52- Spokane Gage to Nine MileMixed (losing, then gaining) -- 25

26. Best Estimate of Unknown Loads 26

27. Consideration of Uncertainty Need to recognize uncertainty/variability in flows and concentrations – Uncertainty: Concentrations close to blanks – Variability: Concentrations and flows vary from day-to-day Re-state model inputs as probability distributions rather than single values – W i = Q d * C d - Q u * C u 27

28. Probability Distributions Describe expected probability of occurrence of entire range of values Probability 0 0.1 0.2 0.3 0.4 0 2 4 6 8 10 Concentration 28

29. Probability Distributions Higher uncertainty corresponds to broader curves Low Moderate High 29 Probability 0 0.1 0.2 0.3 0.4 0.6 0 2 4 6 8 10 Concentration 0 2 4 6 8 10 12 14 16 18 20 22 Concentration 0 2 4 6 8 10 Concentration Probability 0 0.1 0.2 0.3 0.4 Probability 0 0.1 0.2 0.3

30. Defining Probability Distributions Need three pieces of information – Central tendency (mean) – Variance (spread) – Shape of distribution Normal Log-Normal Shape determined by goodness-of-fit testing 30

31. Goodness-of-Fit Testing Compare observed distribution of data to idealized distribution – Rank values – Plot on probability paper – Examine fit Process now applied via statistical packages 31

32. Defining Uncertainty in Model Inputs Flows – Day to day variability PCB Concentrations – Day to day variability – Uncertainty in measurement due to blank contamination 32

33. Defining Flow Uncertainty Characterize day to day variability at each station – Conduct goodness of fit testing to define type of distribution – Calculate mean and standard deviation 33

34. Uncertainty in Concentration Inputs Uncertainty in concentration inputs has two components – Day to day variability at each station – Uncertainty due to blank contamination Laboratory and field Each component is evaluated separately, then combined 34

35. Daily Variability in Concentration Characterize day to day variability at each station using the blank-correction method defined in the QAPP QAPP Concentration (pg/l) 40 50 60 70 80 90 35

36. Uncertainty Due to Contamination Characterize uncertainty by using an alternate blank correction method (no exclusion, subtract maximum of field and lab blank) – Expressed as difference from the QAPP method  Concentration (pg/L) -30 -20 -10 0 10 20 30 36

37. Combining Sources of Uncertainty 1.Select value representing daily variability 2. Select value representing incremental uncertainty due to contamination 3.Combine to generate total uncertainty Daily Variability Contamination Uncertainty Total Uncertainty + = 60 70 80 90 -30 -20 -10 0 10 20 30 40 50 60 80 90 100 110 37

38. Defining Uncertainty in Results Characterize uncertainty in each model input – Using best-fit statistical distribution Use Monte Carlo analysis to characterize uncertainty in mass balance assessment 38

39. Defining Uncertainty in Results Q u C u Q d C d Incremental Load 1.Characterize uncertainty in each model input as a statistical frequency distribution 39

40. Defining Uncertainty in Results Q u C u Q d C d 0 Incremental Load (mg/day) 0.5 2.Randomly select inputs and run model 40

41. Defining Uncertainty in Results Q u C u Q d C d 0 Unmonitored Load (mg/day) 0.5 3.Tabulate results 41

42. Defining Uncertainty in Results Q u C u Q d C d 0 Unmonitored Load (mg/day) 0.5 4.Repeat process 42

43. Defining Uncertainty in Results Q u C u Q d C d 0 Unmonitored Load (mg/day) 0.5 4.Repeat process Q u C u Q d C d 43

44. Defining Uncertainty in Results Q u C u Q d C d 0 Incremental Load (mg/day) 0.5 5.Output distribution completely characterizes uncertainty – As long as inputs are characterized properly 44

45. Uncertainty Analysis Inputs: River Flows Flow (cfs) MeanStd. Dev.DistributionSerial Correlation Lake Coeur d’Alene*735.6109.8Normal0.92 Post Falls741.3109.8Normal1.0 Barker Rd.399124.4Normal0.92 Trent Ave.973.760.4Normal0.94 Spokane1118.673.8Normal0.84 Hangman Ck.14.43.8Normal0.92 Nine Mile1101.380.3Normal0.91 *Temporarily set at Post Falls flow minus average Coeur d’Alene WWTP flow 45

46. Uncertainty Analysis Inputs: River Concentrations Total PCB (pg/L) VariabilityMeasurement Uncertainty MeanStd. Dev.DistributionMeanStd. Dev.Distribution Lake Coeur d’Alene12.599.14Normal015.4Normal Post Falls16.045.04Normal015.4Normal Barker Rd.18.7314.7Normal015.4Normal Trent Ave.14029.4Normal015.4Normal Spokane152.838.1Normal015.4Normal Hangman Ck.59.7613.7Normal015.4Normal Nine Mile163.249.6Normal015.4Normal 46

47. Uncertainty Analysis Inputs: Discharge Flows Flow (cfs) MeanStd. Dev.Distribution Coeur d’Alene5.350.03Normal HARSB00Normal Post Falls3.890.12Normal Liberty Lake1.120.04Normal Kaiser Aluminum13.80.56Normal Inland Empire Paper11.10.22Normal Spokane County11.70.10Normal City of Spokane44.11.44Normal 47

48. Uncertainty Analysis Inputs: Discharge Concentrations Total PCB (pg/L) VariabilityMeasurement Uncertainty MeanStd. Dev.DistributionMeanStd. Dev.Distribution Coeur d’Alene 533 3Lognormal015.4Normal Post Falls 214 12Lognormal015.4Normal Liberty Lake 218 36Lognormal015.4Normal Kaiser Aluminum 3949 673Lognormal015.4Normal Inland Empire Paper 2978 456Lognormal015.4Normal Spokane County 361 82Lognormal015.4Normal City of Spokane972209Lognormal015.4Normal 48

49. Results: Incremental Load by Reach Lake Coeur d‘Alene to Post Falls Post Falls to Barker Rd. 49

50. Incremental Load by Reach Barker Rd. to Trent Ave. Trent Ave. to Spokane Gage 50

51. Incremental Load by Reach Spokane Gage to Nine Mile 51

52. Estimated Range of Unknown Loads River ReachGroundwater Interaction Magnitude of Unknown Load (mg/day) Coeur d’Alene to Post Falls Losing0 to 14 Post Falls to Barker Road Losing0 to 21 Barker Road to Trent Avenue Mixed (losing, then gaining) 94 to 157 Trent Avenue to Spokane Gage Mixed (gaining, then (losing) 0 to 80 Spokane Gage to Nine Mile Mixed (losing, then gaining) 0 to 81 52

53. Estimated Range of Unknown Loads 53

54. Loading Sources in Context *Stormwater loading estimate from Ecology (2011) Source Assessment |------ Unknown/Groundwater ------|------ Other* ------| 54

55. Conclusions Synoptic survey identified a potential unknown source (between Barker Rd. and Trent Avenue) – Magnitude of the unknown source not large enough to conclude that it is the primary cause of PCB issues – But large enough to be a contributor Unknown loads (if any) in other sections are likely smaller 55

56. 56

57. Uncertainty Due to Blank Correction Difference in results between alternative blank correction methods 57

58. Uncertainty Due to Blank Correction Comparison between QAPP blank corrected and uncorrected concentrations 58

59. Uncertainty Due to Blank Correction Comparison between subtraction blank corrected and uncorrected concentrations 59