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1
I will be examining how chlorophyll relates to exceedences in the following water qualityparameters (criteria/thresholds in parentheses):
2
I will be examining how chlorophyll relates to exceedences in the following water qualityparameters (criteria/thresholds in parentheses):
1) Dissolved oxygen (5.5 mg/l or 5.0 mg/l)
Designated Use Criteria Concentration/Duration Protection Provided Temporal Application
Migratory fish spawning
and nursery use
7-day mean > 6 mg liter-1 (tidal habitats with 0-0.5 ppt salinity)
Survival/growth of larval/juvenile tidal-fresh resident fish; protective of threatened/endangered species.
February 1 - May 31
Instantaneous minimum > 5 mg liter-1 Survival and growth of larval/juvenile migratory fish;
protective of threatened/endangered species.
Open-water fish and shellfish designated use criteria apply June 1 - January 31
Shallow-Water bay grass use
Open-water fish and shellfish designated use criteria apply Year-round
Open-water fish and shellfish use1
30-day mean > 5.5 mg liter-1 (tidal habitats with 0-0.5 ppt salinity)
Growth of tidal-fresh juvenile and adult fish; protective of threatened/endangered species.
Year-round 30-day mean > 5 mg liter-1 (tidal habitats with >0.5 ppt salinity)
Growth of larval, juvenile and adult fish and shellfish; protective of threatened/endangered species.
7-day mean > 4 mg liter-1 Survival of open-water fish larvae.
Instantaneous minimum > 3.2 mg liter-1 Survival of threatened/endangered sturgeon species.2
Deep-water seasonal fish and
shellfish use
30-day mean > 3 mg liter-1 Survival and recruitment of bay anchovy eggs and larvae.
June 1 - September 30
1-day mean > 2.3 mg liter-1 Survival of open-water juvenile and adult fish.
Instantaneous minimum > 1.7 mg liter-1 Survival of bay anchovy eggs and larvae.
Open-water fish and shellfish designated-use criteria apply October 1 - May 31
Deep-channel seasonal refuge
use
Instantaneous minimum > 1 mg liter-1 Survival of bottom-dwelling worms and clams. June 1 - September 30
Open-water fish and shellfish designated use criteria apply October 1 - May 31
3
I will be examining how chlorophyll relates to exceedences in the following water qualityparameters (criteria/thresholds in parentheses):
1) Dissolved oxygen (5.5 mg/l or 5.0 mg/l)2) pH (6-9)
4
I will be examining how chlorophyll relates to exceedences in the following water qualityparameters:
1) Dissolved oxygen (5.5 mg/l or 5.0 mg/l)2) pH (6-9)3) Percent-Light-Through-Water (22% or 13%)
From EPA-CPB’s “Chesapeake Bay Submerged Aquatic Vegetation Water Quality and Habitat-Based Requirements andRestoration Targets: A Second Technical Synthesis” (2000)
5
I will be examining how chlorophyll relates to exceedences in the following water qualityparameters:
1) Dissolved oxygen (5.5 mg/l or 5.0 mg/l)2) pH (6-9)3) Percent-Light-Through-Water (22% or 13%)4) DO Saturation (125%)
6
Excessive dissolved gas super-saturation is associated with:
· Bubble formation in the cardiovascular system, causing blockage of blood flow and death (Jensen 1980, Weitkamp and Katz 1980, Fidler 1988).
· Overinflation and possible rupture of the swim bladder in young (or small) fish, leading to death or problems of overbuoyancy (Shirahata 1966, Jensen 1980, Fidler 1988, Shrimpton et al. 1990a and b).
· Extracorporeal bubble formation in gill lamella of large fish or in the buccal cavity of small fish, leading to blockage of respiratory water flow and death by asphyxiation (Fidler 1988, Jensen 1988).
· Sub-dermal emphysema on body surfaces, including the lining of the mouth. Blistering of the skin of the mouth may also contribute to the blockage of respiratory water flow and death by asphyxiation (Fidler 1988, White et al. 1991).
Source: British Columbia Water Quality Guidelines of Dissolved Gas Supersaturation (1994)
Gas bubble trauma in a juvenile rainbow trout
7
In addition to being linked to harmful impacts on aquatic life, DO super-saturation is alsoan excellent indicator of algal blooms.
USA EPA (1986) recommends a dissolved gas criterion of 110% to protect aquatic life. Other sources suggest 125% for DO saturation. This is the number I’ve chosen to use as athreshold.
8
I will be examining how chlorophyll relates to exceedences in the following water qualityparameters:
1) Dissolved oxygen (5.5 mg/l or 5.0 mg/l)2) pH (6-9)3) Percent-Light-Through-Water (22% or 13%)4) DO Saturation (125%)
8
9
I’m analyzing three types of monitoring data:
1) DATAFLOW (HRSDS and VIMS)2) Long-term, mid-channel fixed stations (DEQ)3) Continuous (VIMS)
10
DATAFLOW provides a precise estimation of chlorophyll in space.When run frequently (as it is in the lower James), it also capturestemporal variability. These two qualities make DATAFLOW the idealdataset for assessing chlorophyll.
So if there are relationships between chlorophyll and water qualityexceedences, I would expect to find evidence in theDATAFLOW data.
11
Step 1. Plot DATAFLOW cruisetrackpoints…
Case study: JMSMH
12
…over Bay Interpolator cells
JMSMH
13
Step 2. Generate descriptive statistics for each cell that intersectsa cruise point
• mean chlorophyll• mean DO concentration• mean Kd
• mean pH• mean DO Saturation %
JMSMH
14
From EPA’s 2008 Technical Support for Criteria Assessment Protocols Addendum
percent-light-through-water
15
Step 3. Repeat for each cruise.
For the results I’m going to show,I used 71 summertime cruises from2007-2012. This resulted in 8748samples (cell averages).
16
Probability of Exceeding Selected Water Quality Parameter Thresholds
0
10
20
30
40
50
60
70
80
90
100
rela
tive
freq
uenc
y
Based on cell-averaged DATAFLOW measurementsJMSMH, July-September 2007-2012 (n=8748)
0102030405060708090
100
0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100
prob
abili
ty o
f exc
eede
nce
DO < 5.0 mg/l
0102030405060708090
100
0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100
prob
abili
ty o
f exc
eede
nce
pH>9.0
0102030405060708090
100
0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100
prob
abili
ty o
f exc
eede
nce
DO Saturation >125%
0
10
20
30
40
50
60
70
80
90
100
0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100
prob
abili
ty o
f exc
eede
nce
PLW <22%
criterion=10 ug/l
17
0
10
20
30
40
50
60
70
80
90
100
rela
tive
freq
uenc
y
Based on cell-averaged DATAFLOW measurementsJMSMH, summer months 2007-2012 (n=8748)
• DO and pH exceedences are very rare in the daytime surface waters monitored by DATAFLOW.
• Exceedence rates in DO Sat and PLW appear to increase with chlorophyll.
• This analysis would seem to suggest that the current criterion (10 ug/l) is protective of water quality.
0
10
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80
90
100
0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100
prob
abili
ty o
f exc
eede
nce
PLW <22% ProbabilityBy binCumulativeProbability
0
10
20
30
40
50
60
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80
90
100
0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100
prob
abili
ty o
f exc
eede
nce
DO Saturation >125%
ProbabilityBy binCumulativeProbability
18
JMSMH Summer
Based on semi-monthly/monthly fixed station monitoring conducted by DEQ and VIMS, 1985-2013 (n=29).
BUT…
There doesn’t seem to be arelationship between seasonal chlorophyll averages and water quality exceedence rates.
0
10
20
30
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50
60
70
80
90
100
0 5 10 15 20 25 30
exce
eden
ce ra
te
seasonal average chlorophyll (ug/l)
30-Day Mean DO (5.0 mg/l)Instantaneous Min DO (3.2 mg/l)
Dissolved Oxygen
0
10
20
30
40
50
60
70
80
90
100
0 5 10 15 20 25 30
exce
eden
ce ra
te
seasonal average chlorophyll (ug/l)
PLW 22% (secchi)
Water Clarity
19
Summer chlorophyll averages and 90th percentiles based on DATAFLOW, plotted against the exceedence rate of the 30-Day Mean DO criterion (5.0 mg/l) observed at DEQ/VIMS fixed stations
JMSMH
0
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6
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0 5 10 15 20 25
30-D
ay M
ean
DO
exc
eede
nce
rate
%
summer mean chl (ug/l)<---DATAFLOW--->
<--F
IXED
STAT
ION
-->
2007
2011
20082009
2012
2010
0
2
4
6
8
10
12
14
0 5 10 15 20 25
30-D
ay M
ean
DO
exc
eede
nce
rate
(%)
summer 90th Percentile chl (ug/l)<---DATAFLOW--->
<--F
IXED
STAT
ION
-->
2007
2011
2012
2010
20082009
20
CONMON data allow us to answer these important questions:
1) Over what time period(s) do we see relationships between chlorophyll and water quality exceedences?
2) How do these relationships change with increasing duration?
21
Four durations examined:
1) Instantaneous chlorophyll (15-minute observations)
2) 24-hour average chlorophyll3) 7-day average chlorophyll rolling averages4) 30-day average chlorophyll
Following results are for JMSOH Summer
22
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
15-min chlorophyll (ug/l)
bin probability
cumulative probability
pH >9.0
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
15-min chlorophyll (ug/l)
bin probability
cumulative probability
DO <5.0 mg/l
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
15-min chlorophyll (ug/l)
bin probability
cumulative probability
DO SAT >125%
88
90
92
94
96
98
100
pro
bab
ility
of e
xcee
den
ce %
15-min chlorophyll (ug/l)
bin probability
cumulative probability
PLW <13%
0
5
10
15
20
25
30
35
rela
tive
freq
uenc
y %
15-minute chlorophyll (ug/l)
JMSOH CONMON Summer 2006-2008 Instantaneous Chlorophyll
n=23,115
23
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
24-hour chlorophyll average (ug/l)
bin probability
cumulative probability
90th percentile pH >9.0
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
24-hour average chlorophyll (ug/l)
bin probability
cumulative probability
10th Percentile DO < 5.0 mg/l
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
24-hour average chlorophyll (ug/l)
bin probability
cumulative probability
90th Percentile DO SAT >125%
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
24-hour average chlorophyll (ug/l)
bin probability
cumulative probability
Mean PLW <13%
0
5
10
15
20
25
30
35
40
45
50
9-10 10-11 11-12 12-13 13-14 14-15 15-16 16-17
rela
tive
freq
uenc
y%
24-hour average chlorophyll (ug/l)
n=23,353
JMSOH CONMON Summer 2006-2008 24-hour Average Chlorophyll
24
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
7-day average chl (ug/l)
bin probability
cumulative probability
90th Percentile pH >9.0
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
7-day average chl (ug/l)
bin probability
cumulative probability
10th Percentile DO <5.0 mg/l
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
7-day average chl (ug/l)
bin probabilitycumulative probability
90th Percentile DO SAT>125%
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
7-day average chlorophyll (ug/l)
bin probabilitycumulative probability
Mean PLW <13%
0
20
40
60
80
100
9-10 10-11 11-12 12-13 13-14 14-15 15-16 16-17
rela
tive
freq
uenc
y %
7-day average chl (ug/l)
n=22,624
JMSOH CONMON Summer 2006-2008 7-Day Average Chlorophyll
25
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
30-day average chl (ug/l)
bin probability
cumulative probability
90th Percentile pH >9.0
0
10
20
30
40
50
60
70
80
90
100
pro
bab
ility
of e
xcee
den
ce %
30-day average chl (ug/l)
bin probability
cumulative probability
10th Percentile DO <5.0 mg/l
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
30-day average chl (ug/l)
bin probability
cumulative probability
90th Percentile DO SAT >125%
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
30-day average chl (ug/l)
bin probability
cumulative probability
Mean PLW<13%
0
10
20
30
40
50
60
70
80
90
100
9-10 10-11 11-12 12-13 13-14 14-15 15-16 16-17
rela
tive
freq
uenc
y %
30-day average chl (ug/l)
n=16,000
JMSOH CONMON Summer 2006-2008 30-Day Average Chlorophyll
26
Three things jump out at me…
27
Three things jump out at me…
1. The chlorophyll bin where we see a jump in exceedences shifts to lower values with increasing duration.
28
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
15-min chlorophyll (ug/l)
bin probability
cumulative probability
DO SAT >125%
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
24-hour average chlorophyll (ug/l)
bin probability
cumulative probability
90th Percentile DO SAT >125%
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
7-day average chl (ug/l)
bin probabilitycumulative probability
90th Percentile DO SAT>125%
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
30-day average chl (ug/l)
bin probability
cumulative probability
90th Percentile DO SAT >125%
The chlorophyll bin where we see a jump in exceedences shifts to lowervalues with increasing duration.
29
Three things jump out at me…
1. The chlorophyll bin where we see a jump in exceedence rate shifts to lower values with increasing duration.
2. The strength of a relationship is dependent on the duration.
30
88
90
92
94
96
98
100
pro
bab
ility
of e
xcee
den
ce %
15-min chlorophyll (ug/l)
bin probability
cumulative probability
PLW <13%
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
30-day average chl (ug/l)
bin probability
cumulative probability
Mean PLW<13%
“If we can keep the chlorophyll at less than 10 ug/l,water clarity will still be poor. But at least we won’t make it worse!”
“There isn’t a relationship between chlorophyll and water clarity.”
31
Three things jump out at me…
1. The chlorophyll bin where we see a jump in exceedence rate shifts to lower values with increasing duration.
2. Exceedences can be obscured by increasing duration.
3. The duration affects how we talk about exceedences.
32
“DO saturation was excessive in JMSOH 6% ofthe time during the summer months.”
“JMSOH experienced excessive DO saturation levels during26% of the 24-hour periods monitored during this study.”
“22% of the 7-day periods sampled in JMSOH werecharacterized by at least 16 hours of excessive DOsaturation levels.”
“12% of the 30-day periods sampled in JMSOH werefound to have at least 72 hours of excessive DOsaturation levels.”
All the statements below describe the same dataset, just parsed in different ways. But which statement is more meaningful to aquatic life?
0
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prob
abili
ty o
f exc
eede
nce
%
15-min chlorophyll (ug/l)
bin probability
exceedence rate
DO SAT >125%
0
10
20
30
40
50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
24-hour average chlorophyll (ug/l)
bin probability
exceedence rate
90th Percentile DO SAT >125%
0
10
20
30
40
50
60
70
80
90
100
prob
abilit
y of e
xcee
denc
e %
7-day average chl (ug/l)
bin probabilityexceedence rate
90th Percentile DO SAT>125%
0
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50
60
70
80
90
100
prob
abili
ty o
f exc
eede
nce
%
30-day average chl (ug/l)
bin probability
exceedence
90th Percentile DO SAT >125%
33
ns
ns ns
ns
ns= no significant difference, Wilcoxon-Rank Sum test
34
ns
a a b
a b c
ns= no significant differenceKruskal-Wallis ANOVAPairwise Wilcoxon Rank Sum
35
Based on summertime DEQ/VIMS fixed station monitoring in JMSOH, 1985-2013. Redline indicates the chlorophyll criterion for this segment-season. (n = 29)
0
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6
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10
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14
0 5 10 15 20 25
DO
exc
eede
nce
rate
%
season average chlorophyll (ug/l)
30-Day Mean DO (5.0 mg/l)
Instantaneous Minimum DO (3.2 mg/l)
36
0
1
2
3
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5
6
7
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9
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18
60
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120
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160
180
200
June 27, 2006 July 17, 2006 August 6, 2006 August 26, 2006 September 15, 2006
CHO
ROPH
YLL
(UG
/L)
DO
% S
ATU
RATI
ON
DO % Saturation
chlorophyll
Spearman r=.56