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Multibox Model of PCB Fate in San Francisco Bay

Multibox Model of PCB Fate in San Francisco Bay. Presented to the CFWG January 15, 2008. Brief Model Overview Model Confidence Hindcast Model Validation Uncertainty Analysis Model Sensitivity Uncertainty of Important Input Parameters Response to Extreme Scenarios Forecast Results

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Multibox Model of PCB Fate in San Francisco Bay

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  1. Multibox Model of PCB Fate in San Francisco Bay Presented to the CFWG January 15, 2008

  2. Brief Model Overview Model Confidence Hindcast Model Validation Uncertainty Analysis Model Sensitivity Uncertainty of Important Input Parameters Response to Extreme Scenarios Forecast Results Source and Loss Pathways Information Gaps Next Steps Outline

  3. Model Overview

  4. Model Overview

  5. Central Bay Carquinez Validation : Salinity

  6. Central Bay Mallard Island Lower South Bay Validation : SSC Dashed = Model Solid = Observations

  7. Preliminary (Uncalibrated) Hindcast Results * Magnitude and spatial distribution of results can be improved.

  8. Considering Tetra Tech’s testing and Workgroup comments, do certain model parameters need revising?  Magnitude of WY 2000 tributary loads.  Temporal trend of historic PCB loads. Spatial distribution of tributary loads Removed this ‘tweak’ per CFWG recommendation Targeted Calibration

  9. Historic PCB Loads Breivik et al, 2002

  10. Hindcast Results After Targeted Calibration *Still room for improvement. Workgroup recommended spatially explicit Koc.

  11. RMP data insufficient for regional Koc Filter size overestimates dissolved fraction Need objective means of determining Koc Should consider more than just sediment PCBs.  Model Bias Estimator Iteratively run model with small perturbations of regional Koc and search for model bias closest to 1 Objective Calibration of Partitioning (Koc)

  12. Hindcast Results After Calibration Error Bars: EMAP & RMP = Standard Deviation of Samples Model = Aggregate Uncertainty

  13. Hindcast Results After Calibration Net Erosional Net Depositional

  14. 10,000 runs made as part of Tetra Tech testing re-analyzed to determine ‘aggregate uncertainty of model results given uncertainty in input parameters.’ 3 sediment results (SSC, net sedimentation, sediment export) 10 PCB results (wct, sed, mass in water, mass in sed, burial, deposition, degradation, erosion, outflow, volatilization) Uncertainty Analysis

  15. Uncertainty, expressed as std. dev., is function of mean. Use this relation to project uncertainty onto forecast Uncertainty Analysis : Results

  16. *Regional differences due to local watersheds vs. Delta Uncertainty Analysis : Results

  17. Initialized with water and sediment concentrations from RMP 2006 data and profiles from end of hindcast Future loads attenuate from current levels with ~50yr half-life Relationships of PCBs to SSC @ Mallard Island remain Delta outflow includes potential climate change Sedimentation rates/patterns continue Uncertainty determined by hindcast Base Forecast Setup

  18. Forecast Setup : Sedimentation *

  19. Model Sensitivity O = Model Output P = Model Input Parameter

  20. Model Sensitivity High Relative Sensitivity Low

  21. Uncertainty of Important Input Parameters : Vertical Profile Profiles that increase subsurface mass change forecast predictions considerably.

  22. Model Sensitivity High Relative Sensitivity Low

  23. Extreme Scenarios : Delta Outflow

  24. Extreme Scenarios : Instantaneous Inputs Double Check of South Bay: 200 kg PCBs mixed into 2.3x1013kg sediment = 8.8 ng/g increase

  25. Model Confidence Summary * 2005 survey suggests South Bay depositional. Survey to which model calibrated (1984?) suggested erosional. - D. Schoellhamer, personal communication

  26. Base Forecast : Recovery Due to Natural Attenuation Net Erosional Controlled by Subsurface Mass Net Depositional Controlled by Attenuation & Degradation

  27. Loading Scenarios : Local Tributary Loads

  28. Loading Scenarios : Delta Loads

  29. Loading Scenarios : Wastewater

  30. Loading Scenarios : No External Loads

  31. PCB Source and Loss Pathways * ‘Active Sediments’ refers to top 5 cm Erosion Inputs ~ Total External Inputs

  32. Sediment cores Hindcast : depositional cores more important Forecast : erosional cores more important Better info on attenuation, degradation, Koc Possible to get better info? Estimate outflow of sediment & PCBs USGS et al. have study planned for 2008 Information Gaps

  33. Is South Bay depositional? Congener specific model Smaller spatial scales – hot spots or sub- embayments (e.g., LSB) 3D hydrodynamics & sediment transport Apply multibox to multiple contaminants (screening tool) Possible next steps or PCB modeling

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