1. Matthew Espie Khalilha Haynes
Where the River Meets the Sea: Turbidity Maxima in the Columbia River Estuary
Matthew Espie
Khalilha Haynes

2. Introduction: An Estuary is…
Washington
Oregon
Partially enclosed, brackish waters
Formed when freshwater bodies meet and mingle with saltwater from the ocean
Among the most productive environments on earth
An assortment of habitats, in and around the water: salt marshes, swamps, oyster reefs, mangrove forest, and tidal pools…
Home to thousands of species of mammals, birds, and fish
Coastal regions today are the home for 110 million people and is expected to increase to 127 million by the year 2010 (

3. Estuarine Turbidity Maxima (ETM)
What Makes an ETM:
ETM are areas of elevated levels of suspended sediments.
ETM vary in strength and move with the tides.
ETM are thought to be an important factor in the productivity of estuaries
ETM are the points in the estuary that are most turbid (opaque)
High biological activity
Provides nutrients for bacteria and smaller animals at lower trophic levels
Columbia River ETM seems to follow the leading edge of the salt wedge as it makes its way upstream as the tide is flooding, and then as it retreats during an ebb tide. (

4. Introduction: CMOP
CMOP’s Vision: To understand and predict the response of coastal margins to human and climate influences
Focus on the Columbia River and the adjacent Pacific Northwest estuaries

5. Objectives
Find and predict the location of the elusive estuarine turbidity maximum (ETM) for the Columbia River estuary
Analyze sensor data from the Saturn 01 and 03 systems. Analyze relationships between variables:
Turbidity
Salinity
Chlorophyll
Tide

6. Process Explore CMOP database (http://www.stccmop.org/datamart)
Examine data from multiple stations in the estuary (
Read background information
Import data into Excel
Make plots
Perform correlation analyses
Analyze the different types of tides.
Research ETM.

7. Process
Analyze data time series to provide context for previous research cruises. (
Analyze data time series.
Download data from station SATURN01 and graph them in Excel. Analyze the spikes in turbidity.
Create a diagram of the ETM
Download data from Aug cruise where samples were taken during an ETM.

8. Create a program that imports the ETM data into Matlab.
Process
Find peaks in graphs of turbidity, salinity, tides, and change in salinity (include time of peak).
Find time differences between peaks in each parameter and peaks in tidal peaks.
Import the data into Matlab. Make graphs that show relationship between turbidity and another variable. Make graphs of the max turbidity at each station sampled and the corresponding salinity values.
Create a program that imports the ETM data into Matlab.

9. Process Sort time differences according to tidal type.
Perform statistical analyses on sets of data.
Redesign sediment distribution maps.
Analyze sediment distribution trends in regard to the ETM

10. Conclusion and Future Work
Using the results of the statistical analyses of SATURN01 sensor data, we were able to better predict the timing of the ETM at the sensor location.
Future statistical analyses should be done over multiple seasons, with a more diverse data and representative data supply, including data from SATURN03.

11. ...and everyone else at CMOP who also assisted us!
THANK YOU!!
We would like to thank our mentors Nirzwan Bandolin, António Baptista, Grant Law, and Karen Wegner and all of our parents for their help and support!
...and everyone else at CMOP who also assisted us!

12. The Goods: How the ETM works…
Material in the water column is re-suspended and advected up the salt wedge and dispersed on it’s way to the ocean. /
At the foot of the salt wedge there is lots of turbulence and mixing of the salt water and the sediment found on the river bed; the ETM should be close.

13. August 2007 RV Barnes Research Cruise
Turbidity (NTU) and Oxygen (mg/L) at Station 22
Turbidity (NTU) and Salinity (PSU) at Station 22
Depth (m)
Casts
Casts

14. August 2007 RV Barnes Research Cruise
Max Turbidity at each Station
Turbidity (NTU)
stations
Corresponding Salinity Values
Salinity (PSU)
stations

15. Time series
Time

16. Predicting Turbidity Type 1 Type 2 Type 3 Type 4 Mean 19.89 16.28
Type 1
Type 2
Type 3
Type 4
Mean
19.89
16.28
13.27
17.21
Standard Error
1.35
0.97
1.37
1.62
Median
20.69
16.06
13.26
18.11
Standard Deviation
4.06
3.07
3.87
4.85
Range
13.14
9.35
12.87
12.84
Minimum
12.05
12.426
8.17
9.97
Maximum
25.19
21.76
21.04
22.81
Sample Size 9 10 8

17. Predicting Change in Salinity
Type 1
Type 2
Type 3
Type 4
Mean
5.14
0.86
4.26
0.77
Standard Error
0.11
0.42
0.41
0.09
Median
5.28
0.65
4.17
0.74
Standard Deviation
0.32
1.25
1.1
0.26
Range
0.92
4.53
3.17
0.78
Minimum
4.68
-0.5
3.23
0.3
Maximum
5.6
4.03
6.4
1.08
Sample Size 8 9 7

18. Predicting Salinity small large Mean 0.06 0.07 Standard Error 0.15
0.21
Median
0.23
-0.01
Standard Deviation
0.46
0.67
Range
1.15
2.37
Minimum
-0.62
-0.6
Maximum
0.53
1.77
Sample Size 10

19. What the Numbers Mean…
Tide 3 4 2 1
Height (m)
Time

20. Sediment Distribution Maps*
*blue: positively skewed magenta: negatively skewed
North Channel
South Channel
Sedimentary Processes & Environments in the Columbia River Estuary
C. Sherwood J. Creager E. Roy G. Gelfenbaum T. Dempsey

21. Sediment Distribution Maps*
*blue: positively skewed magenta: negatively skewed
Sedimentary Processes & Environments in the Columbia River Estuary
C. Sherwood J. Creager E. Roy G. Gelfenbaum T. Dempsey

22. Time series
Time

23. Tides
Height (m)
Time
Slack tide
Ebb tide
Flood tide

24. Graphs and Analyses June 1-11, 2008 TIME
Turbidity has a pattern: low spike, high spike… high spike, low spike,… etc
June 1
Salinity is high when tubidity is low.
Matthew: These are graphs of turbidity. The top graph shows a long timeseries, while the bottom one shows a shorter period of time. One interesting turbidity pattern is the spikes. They seem to go low spike, high spike… high spike, low spike… low spike, high spike… etc. One would assume that these spikes happen during tidal transitions, when there is more energy. Also, near the end of the time series, the turbidity is generally lower has less distinctive spikes (click). This new graph has added salinity. Salinity can be an indicator for turbidity because when salinity is changing rapidly, it indicates the ocean water moving past the sensor. When this ocean water is moving past, is seems to be accompanied by high turbidity. This would suggest that there is a large amount of mixing between the river water and the salt water (click). Now, with the tides added in, the patterns continue to make sense. When there are larger energy tidal transition, we see higher spikes in turbidity. Also, when the tides progress to neap tides towards the end of the time series, the turbidity values become lower.
Turbidity pattern coincides with flood and ebb tides.
TIME

25. The Estuary