1. Status & Trends Component The Design Process
Sarah Lowe, Bruce Thompson,
Rainer Hoenicke, Jon Leatherbarrow,
Robert Smith, Don Stevens,
Cristina Grosso, and the DIWG
Every three years the RWQCB is required to list contaminants on the federal 303(d) list based on water quality evaluations of the regions receiving waters.
The RMP’s new Status and Trends component provides the Regional Board with scientific information to address this objective. It’s new, spatially balanced sampling design allows us to make general inferences about the water quality of the major hydrographic regions of the Estuary.
I’m going to talk about The Design Process of the Status & Trends Component of the RMP

2. Design Process Review and evaluate the hydrographic regions
Determine the number of samples per hydrographic region
Develop an optimum sampling design to address the new RMP objectives
Select the sampling locations
The Redesign process had four parts to it:
To review and evaluate the existing hydrographic regions of the Estuary for use in the RMP.
To determine the number of samples per hydrographic region that would provide statistical confidence for comparing mean concentrations to regulatory guidelines.
To develop an optimum sampling design to address the new RMP objectives
To select the sampling locations.
Don Stevens will talk about the sampling locations in his talk following mine.
I’m going to talk about the other 3 parts.

3. Review and Evaluate the Hydrographic Regions
Evaluating the existing segmentation scheme
Soliciting the professional opinions
Performing our own analyses
We reviewed and evaluated the Hydrographic Regions and developed a new segmentation scheme using a weight-of-evidence approach. This weight of evidence was based on:
Evaluating the existing segmentation scheme used by the RWQCB
Surveying the professional opinions of Bay Area scientists
Performing our own analyses, using nearly ten years of water and sediment monitoring data

4. Existing Segments
The existing segmentation scheme used for regulatory purposes by the Regional Board were originally derived from USGS drainage basin maps. These maps were adapted for use in the Estuary. However, these boundaries may not reflect the hydrographic regions of the receiving waters. Because of this, and the RMP’s need to provide scientific data that will be used to make general inferences about the condition of the sub-regions in the Bay, we needed to arrive at the best definition of the hydrographic regions in the Estuary.

5. Professional Opinions
We solicited the professional opinions of several Bay Area biologists, hydrologists and ecologists by sending out a survey. We mapped their recommendations on this map.
These results are Largely based on studies of:
Zooplankton
Water density and circulation
Geomorphological constrictions
Water quality
and Benthic community studies

6. Water Quality data source: RMP and BPTCP (1989-1998)
Cluster Analysis
Results
Graphical Analysis
Results
Temperature
salinity DO
DOC
TSS pH
Temperature
salinity
WATER RESULTS
We Performed Statistical Cluster, and Graphical Analyses based on both Water quality and Sediment quality Data
A cluster analysis is a statistical tool that allows one to group samples according to similarities between two or more attributes.
The graphical analyses we performed were not statistical. First we grouped samples with similar temperature and salinity regimes and then ploted them on a map.
These are the cluster analysis results using 6 WQ variables for the wet and dry seasons.
These are the graphical analysis results for the dry seasons.
Water Quality data source: RMP and BPTCP ( )

7. Sediment Quality data source: RMP, BPTCP & DWR (1991-1998)
Cluster Analysis
Results
Graphical Analysis
Results
% Fine sediment
TOC
% Fine sediment
TOC
These are the sediment analyses results using two sediment quality variables: % fine sediments and Total organic carbon.
The cluster analyses results showed that the sediment characteristics of the estuary are relatively homogenous.
However the graphical analyses did show some partitioning.
Sediment Quality data source: RMP, BPTCP & DWR ( )

8. Expert Opinion Water Cluster Water Graphical Sediment Graphical1 5 1
We combined and compared the maps from the expert opinions and our own analyses and built this table that lists the boundaries of the hydrographic regions from each of these methods. By couting up the number of times each boundary was defined, we developed a “weight-of-evidence” SCALE.
(POINT TO THE TOTAL COLUMN)
This is how the table works. [N] The arrows point to Benicia Bridge….
All five experts defined BB as a region boundary,
1 of the 2 Water cluster, and the Water graphical analyses also defined BB as a boundary.
The Sed-graphical analysis did not.
This gave a total score of 7 out of 9 possible hits for BB.
In this way, the DIWG defined the major hydrographic regions for use in the new RMP.

9. The New Segmentation Scheme has Six Main Hydrographic Regions
Rivers
READ SLIDE CAPTION and PAUSE
Rivers, Suisun Bay, SP Bay, Central Bay (which extends to San Bruno Shoals), South Bay and Lower South Bay.
Having defined the hydrographic regions, the DIWG moved on to other design considerations
For Example:
For regulatory purposes, it is important, to have enough samples in each region, in order to have sufficient statistical confidence that a measured mean contaminant concentration is clearly above or below a given guideline.
To address this, we determined the number of samples per hydrographic region.
We also considered questions like:
Should we have a Random or Random- Stratified design?
Should we continue to sample seasonally?
How shallow should we sample?
Should the S&T component include the sloughs, estuary margins, and tributaries?

10. We determined the final number of samples per region based on:
Statistical power analyses for key contaminants when compared to specific guidelines
Regional Board priorities
Funding
The work group determined the final number of samples per hydrographic region based on:
Statistical power analyses results comparing key contaminants to specific guidelines
Regional Board priorities
Funding

11. Key contaminants were compared to specific guidelines
Water: compared dissolved copper to the CA Toxics Rule – WQC
Sediment: compared copper, mercury and total PAHs to the Effects Range Low guidelines - ERL (Long et al. 1995)
Key contaminants that are important to the Regional Board were compared to the following guidelines
Water: compared dissolved copper to the Ca. Toxics Rule – WQ Criteria
Dissolved copper is important to the Regional Board because of the TMDL process in the South Bay.
Sediment: compared copper, mercury and total PAHs to the Effects Range Low guidelines

12. Dissolved Copper WQC : saltwater = 3.1, freshwater = 9 (µg/L)
Here are the results of the statistical power analyses.
This table shows the % power achieved with between 2 and 10 samples per region for dissolved copper.
The dry season mean and StDev.per region are based on ten years of monitoring data. (PAUSE)
[N] You can see that with 4 or fewer samples per region we achieve over 80% confidence that the dissolved copper concentration is different from the WQC.
However, let’s look at the South Bay region. [N]
Even with tem samples we get very little power. This is because the mean concentration, and the standard deviation, over lap the WQC. It would take an inordinate number of samples bring the standard deviation down to where you could distinguish between the mean concentration and the WQC. (PAUSE)
WQC : saltwater = 3.1, freshwater = 9 (µg/L)
Type I error rate (a) = Dry Season: May-Oct.

13. Sediment samples compared to the ERL guidelines.
Type I error rate (a) = 0.05.
These are the results for sediment compared to the ERL guidelines for Cu, Hg, and Total PAHs. The point of this slide is to show you that even with 10 samples per region we have very little power to distinguish the mean contaminant concentration from the guideline. (PAUSE)
So, based on the power analyses,-- Regional Board priorities,-- and funding, --the WG determined [N] the final # of the samples per hydrographic region and the new sampling design.

14. Number of S A M P L E Suisun San Pablo Bay Rivers Central South W=4
Lower South
Number of S A M P L E l
W=4
S=8
W=4
S=8
Water: 33 total
Sediment: 49 total
W=4
S=8
We will be sampling annually during the dry season.
There will be a total of 28 randomly allocated water samples and 40 randomly allocated sediment samples
Additionally, we will [N] maintain 5 fixed historical RMP water sampling locations and 9 fixed historical RMP sediment sampling locations.
This is mainly to provide transition and continuity with our long-term baseline dataset.
W=10
S=8
W=6
S=8

15. Sampling Plan Annual sampling (during the dry season) Measure
priority pollutants & ancillary measures
effects (toxicity)
bivalve bioaccumulation
We plan to sample annually,
And to measure
Trace elements, trace organics, and ancillary measurements, at all randomly selected stations
Aquatic and sediment Toxicity effects, at a subset of randomly selected stations
and continue Bivalve bioaccumulation studies, at a subset of fixed stations

16. W A T E R
Wat1
I’m going to show you what the water and sediment sampling will look like over time.
I want to do this to emphasize the extensive spatial coverage within each hydrographic region that the new design will bring to the RMP.
This visual summary , will also set the stage for Don Stevens’s talk where he will describe how the samples were spatially allocated.
These are the sampling locations in each hydrographic region, for the first year of water sampling.
[N] SHOWS Fixed stations
Keep in mind that we will also be sampling these five fixed historical RMP stations.

17. 5 Fixed historical stationsW A T E R 5
Fixed
historical
stations
WatYr1
Keep in mind that we will also be sampling these five fixed historical RMP stations.

18. This is year 1 and 2

19. Year 1-3

20. Year 1-4

21. Yr1-5
As you can see we get good spatial coverage, which will allow us to make probabilistic inferences about the water quality within each hydrographic region.
(PAUSE)
This random sampling design continues within each region for up to 72 samples and then the pattern can be repeated.

22. S E D I M N T
Sed1
SedYr1
Sediment sampling will be different than the water.
With sediment we assume that some sediment charateristics are retained over time so we will want to repeat sampling at some locations to help us understand trends.
There will be eight sampler per hydrographic region and there will repeated sampling.
Two stations from each region will be sampled on an annual, five year, ten year, and twenty year cycle.
This is how it will look.

23. S E D I M N T
Sed1new 9
Fixed
historical
stations
SedYr1

24. S E D I M N T
Sed1w/arrows
SedYr1

25. SedYr1-2

26. sYr1-3

27. sYr1-4

28. sedYr1-5

29. S E D I M N T
1 to 6
SedYr1-6

30. sed7

31. sed8

32. SedYr1-9

33. Sed1-10
sedYr1-10

34. S E D I M N T
1 to 11
S1-11

35. S E D I M N T
S1-11
To summarize, The DIWG has developed an optimum sampling design that will capture long-term status & trends of contaminants in the Estuary.
This design will allow us to make scientifically significant inferences about the condition of contamination within each major hydrographic region in the Estuary.

36. Developed a random sampling design with good spatial coverage
Defined the major hydrographic regions using a weight-of-evidence approach
Used statistical analyses and management needs to determine best sample size per region
Developed a random sampling design with good spatial coverage
We Defined the major hydrographic regions using a weight of evidence approach
Used statistical analyses and management considerations, to determine the best sample size per hydrographic region
We developed a Random sampling design that gives us good spatial coverage