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Overview

Overview. Overview of Dataflow data processing method Chlorophyll- a correction method Dataflow processing output Thoughts on supplementary data analysis methods. Processing the 2005 – 2013 DATAFLOW Data. Chlorophyll- a Correction Method.

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Overview

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  1. Overview • Overview of Dataflow data processing method • Chlorophyll-a correction method • Dataflow processing output • Thoughts on supplementary data analysis methods

  2. Processing the 2005 – 2013 DATAFLOW Data

  3. Chlorophyll-a Correction Method • Purpose: To correct/calibrate YSI chl-a based on extracted chl-a • Different methods used in past by DEQ, VIMS, HRSD • Variants: • How to lump data (by season, segment, year, etc.) • Whether or not to ln-transform • Whether to include additional explanatory variables (turbidity, temperature) • Magnitude of correction is small compared to normal variation (over space and time)

  4. Recent developments • Recently recommended method was a compromise between monthly and multi-year lumping • Lump by season-segment-year • Use ln transform • Exclude turbidity and temperature • However, it results in some unreasonable corrections; e.g.: • 192 ug/L  808 ug/L • 333 ug/L  954 ug/L • Cause: Outliers and fewer number of high chl-a values (limited dynamic range) in some combinations

  5. Appears that seasons can be lumped

  6. TF different, but little evidence that other segments are fundamentally different

  7. Some years are different

  8. Log transform improves some regression properties but can contribute to unreasonable corrections

  9. Recommendation: Annual Correction Method • Use consistent correction method • Remove outliers • Lump non-TF segments by year • Simple linear regression • These regressions have already been developed by HRSD.

  10. Dataflow Processing Output:Maps Mesohaline …can be made “prettier” using GIS Polyhaline

  11. Dataflow Processing Output:Tables of Threshold Exceedance Rates • By segment, individual cruise • Spatial exceedance, no temporal averaging • By segment-season • Averaged spatially and temporally • Can perform CFD calculations

  12. Dataflow Processing Output:Charts of %Area by Chl-a Bin Seasonal mean 14.5 7.1 8.2 19.9 9.17 17.3 6.1 10.3 9.3

  13. Dataflow Processing Output:Graphics of Mean vs. Threshold Exceedance Rates

  14. Other Potential Graphical/Statistical Analysis Methods • Conditional probability • Chl-a bin charts are a version of this • Some bins are data limited • Inter-bin thresholds? • Potential supplementary analyses • Simple graphical (e.g., scatterplots) • Locally-weighted averaging (LOWESS) • Continuous conditional probability methods • Changepoint analysis

  15. Scatterplot/LOWESS Example: Cocholodinium density vs. chlorophyll-a

  16. Scatterplot/LOWESS Example: C. polykrikoidesdensity (transformed) vs. chlorophyll-a 10,000 cells/mL

  17. Locally-weighted conditional probability example: Probability that C. polykrikoidesexceeds 10kcells/mLvs. chlorophyll-a

  18. Changepoint analysis example: Probability of C. polykrikoides> 10k cells/mL split by chlorophyll-a Significantly higher probability when chla > 100 ug/L

  19. Extra Slides Brown and Caldwell

  20. Brown and Caldwell

  21. Brown and Caldwell

  22. Brown and Caldwell

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