data analysis for source id: examples of statistical methods and results julie kinzelman, city of...
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Data Analysis for Source ID:Examples of Statistical Methods and Results
Julie Kinzelman, City of Racine
Beach Management Workshop
April 14 – 15, 2005, Egg Harbor, WI
Association of Bacterial Indicator Levels to Coastal
Conditions
Can we tell when E. coli will be elevated?
Potential Associations
• Wind Direction
• Wave Height Estimation
• Precipitation
• Surface Water Temperature
• Presence of Algae
Wind Direction
Wind Vector Containing Direction East
YEAR NUMBER OF DAYS INCLUDING WIND VECTOR EAST (90°)
May June July August
2002 0* 10 9 16
2003 1** 9 12 17
2004 1*** 9 10 10
Number of Sampling Events
Wind Vector East vs. Bathing Water Quality Failures
y = 0.7475x + 0.1884
R2 = 0.4988
0
2
4
6
8
10
12
14
16
18
0 2 4 6 8 10 12 14 16 18
Number of Days Per Month With Wind Vector East
Nu
mb
er
of
Fa
ilu
res
Winds East = High Waves
Influence of East Wind
• In 2 out of the 3 years the increased number of days including wind vector E also reflected an increase in the number of days per month with poor water quality failures
• This translates to a correlation of ~ 50%
• Onshore winds frequently increased wave height as noted in field observations
Wave Height
Estimated Visually (low, medium, or high)
YEAR DAILY FREQUENCY OF WAVE HEIGHT BY MONTH
May/June July August/September
Low Med. High Low Med. High Low Med. High
2002 6 5 10 12 6 9 4 13 10
2003 15 13 0 6 14 5 8 11 4
2004 14 6 4 13 4 5 5 16 9
Frequency of Wave Height
0
5
10
15
20
25
30
35
40
NUMBER OF DAYS
MAY/JUNE JULY AUGUST
MONTH
WAVE HEIGHT DISTRIBUTION (DAYS/MONTH)
LOW
MEDIUM
HIGH
The number of days with moderate or high waves increased
as the summer progressed.
The total number of days designated as having high waves increased in August
Local Mathematical Model
Best Predictor:
E. coli today = 10.801 + 0.248 (yesterday's E. coli count) + 65.859 (wave height) [p = 0.009]
Second Best Predictor:
Wave Height + Easterly Wind Vector [p = 0.02]
Precipitation
Wet Weather Advisories
Average Daily Precipitation
AVERAGE DAILY PRECIPITATION BY MONTH (CM)
YEAR MONTH
JUNE JULY AUGUST
2002 0.61 0.38 0.48
2003 0.15 0.58 0.18
2004 0.58 0.08 0.33
Monthly Precipitation
MONTHLY PRECIPITATION TOTALS (CM)
YEAR TOTAL MONTHLYPRECIPITATION
SEASONTOTAL
JUNE JULY AUGUST
200212.82 9.48 12.65 34.95
20033.62 14.08 4.05 21.75
200412.50 1.78 8.80 23.08
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
PRECIPITATION (CM)
june july august
MONTH
AVERAGE DAILY PRECIPITATION BY MONTH
2002
2003
2004
0
2
4
6
8
10
12
14
16
PRECIPITATION (CM)
june july august
MONTH
MONTHLY PRECIPITATION TOTALS (CM)
2002
2003
2004
Although June had high amounts of ppt. it always had the least number of BWQF.
0
2
4
6
8
10
12
14
16
Monthly Rainfall (cm)
JUNE JULY AUGUST
Month
Monthly Precipitation Totals (cm) vs. Number of Bathing Water Quality Failures - 2002
PPT (CM)
NO. OF BWQF
2004
0
2
4
6
8
10
12
14
16
18
Monthly Rainfall (cm)
JUNE JULY AUGUST
Month
Monthly Precipitation Totals vs. Number of Bathing Water Quality Failures - 2004
PPT (CM)
BWQF
Rainfall can have an immediate impact on surface water quality
1 9 1
8 7 2
01 0 02 0 03 0 04 0 05 0 06 0 07 0 08 0 09 0 0
E . c o l i M P N /1 0 0 m l
9 0 0 1 2 0 0
T im e o f S a m p le C o l le c t io n ( 0 9 0 0 o r 1 2 0 0 )
0 8 / 1 7 / 2 0 0 4
Storm Water Discharge to Lake Michigan after Rain Event
Rainfall vs. BWQF
• Rainfall preceded about 50% of all BWQF in Racine in 2004
• The impacts of rainfall can be sudden and immediate
• Pre-emptive advisories may be appropriate• Rainfall can impact surface in a variety of
ways:– CSO, SSO, Runoff, Storm water discharge
Surface Water Temperature
Did Warmer Water = More Bacteria?
Upwelling can change surface water temperatureLake Michigan Surface Temperature (F) at North Beach, Racine, WI- Summer 2002
40
45
50
55
60
65
70
75
80
03-J
UN-02
05-J
UN-02
07-J
UN-02
09-J
UN-02
12-J
UN-02
17-J
UN-02
19-J
UN-02
21-J
UN-02
26-J
UN-02
28-J
UN-02
02-J
UL-02
08-J
UL-02
11-J
UL-02
15-J
UL-02
18-J
UL-02
20-J
UL-02
23-J
UL-02
25-J
UL-02
27-J
UL-02
29-J
UL-02
01-A
UG-02
03-A
UG-02
05-A
UG-02
07-A
UG-02
10-A
UG-02
12-A
UG-02
15-A
UG-02
19-A
UG-02
21-A
UG-02
23-A
UG-02
27-A
UG-02
Date
Te
mp
era
ture
(F
)
Wind Direction = S
Wind Direction = S
RELATIONSHIP OF E. COLI TO SURFACE WATER TEMPERATURE - 2004
y = 0.0629x - 2.6058
R2 = 0.0379
-2
-1
0
1
2
3
4
5
50 55 60 65 70 75 80
TEMPERATURE (F)
E.
CO
LI
MP
N/1
00
ML
(L
OG
10
)
Scatter plots of the data demonstrate that a strong
correlation did not exist between E. coli and surface water
temperature [R2=0.04(2004)]
Algae (Cladophora)
Was there more E. coli when there was more algae?
High Amounts of Algae - 2002
Low Amounts of Algae - 2004
ALGAL PRESENCE VS. E. COLI CONCENTRATION
0
0.5
1
1.5
2
2.5
3
3.5
0 0.5 1 1.5 2 2.5 3 3.5
ALGAL PRESENCE
Association of Algae to BWQF
• The concentration of E. coli isolated from North Beach did not correlate with the amount of algae noted in the field at the time of collection
• Neither was there a higher incidence of water quality advisories on days when moderate or high levels of algae were noted
Association of Algae to BWQF
• E. coli concentration, ranked by code relating to Cladophora presence and subjected to ANOVA showed no significant difference (p = 0.64)
• Limited by the small number of degrees of freedom (n = 27)
• Correlation may have been noted if the degrees of freedom were higher, i.e. more samples collected
Best Predictors of Water Quality in Racine, WI
• Wave Height (> 1.0 ft.)
• Wind Direction (East)
Acknowledgements
• S. C. Johnson, A Family Company
• WI DNR
• Richard Whitman, USGS
• City of Racine Health Department
• University of Surrey, RCPEH
Too Many Statistics!!!