Monitoring and Modeling of the Background Oso Creek and Oso … · 2020. 8. 21. · Oso Creek and...

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Monitoring and Modeling of the Monitoring and Modeling of the Oso Creek and Oso Bay Oso Creek and Oso Bay

Watershed, Texas Watershed, Texas for a Bacteria TMDLfor a Bacteria TMDL

Joanna Mott, Richard Hay, Joanna Mott, Richard Hay, Zeke Campbell and Russell Zeke Campbell and Russell CardenCarden..

Texas A&M UniversityTexas A&M University--Corpus Christi, TexasCorpus Christi, Texas

BackgroundBackground

•• Oso Creek and Oso Bay were identified as Oso Creek and Oso Bay were identified as impaired segments in the 2004 Texas Water impaired segments in the 2004 Texas Water Quality Inventory and 303(d) list for the Quality Inventory and 303(d) list for the parameter ‘bacteria’. parameter ‘bacteria’.

•• A monitoring and modeling project was A monitoring and modeling project was developed with funding from the Texas developed with funding from the Texas Commission on Environmental Quality Commission on Environmental Quality (TCEQ) to:(TCEQ) to:–– identify potential sources of contamination and identify potential sources of contamination and –– calculate current loading, allowed load and load calculate current loading, allowed load and load

reductions of the fecal indicator ‘reductions of the fecal indicator ‘enterococcusenterococcus’.’.

Oso Watershed Land Oso Watershed Land UsesUses

0.20.2BarrenBarren2.02.0Forested UplandForested Upland2.82.8WetlandsWetlands3.83.8ShrublandShrubland4.54.5WaterWater5.25.2GrasslandsGrasslands13.813.8Urban DevelopmentUrban Development67.867.8Planted/CultivatedPlanted/Cultivated

PercentPercentLand Use TypesLand Use Types

2

Permitted DischargersPermitted Dischargers

•• Total of 10 permitted dischargersTotal of 10 permitted dischargers–– 6 major dischargers (> 1MGD) 6 major dischargers (> 1MGD)

•• 2 industrial2 industrial•• 4 municipal4 municipal

–– 4 minor dischargers (< 1MGD)4 minor dischargers (< 1MGD)•• 1 industrial1 industrial•• 3 municipal3 municipal

Permitted Discharger Permit No. Permitted Daily Avg. Flow (MGD)

American Electric and Power Barney Davis Power Station

01490-000 540

City of Corpus ChristiOso WWTP

10401-004 16.2

City of Corpus Christi Greenwood WWTP

10401-003 8.0

Texas A&M UniversityCBI La Coss Facility

03646-000 5.04

City of Robstown 10261-001 2.4

Equistar Chemical LPCorpus Christi Plant

02075-003 2.0

Tennessee Pipeline Construction Co.Cuddihy Airfield WWTP

14228-001 0.06

Corpus Christi Peoples Baptist Church Roloff WWTP

11134-001 0.02

Texas A&M UniversityAgriculture Research Ext.

11345-001 0.0015

City of Corpus ChristiStorm Water

04200-000 NA

Indicator: Indicator: EnterococcusEnterococcus

•• Oso Bay marine, Oso Oso Bay marine, Oso Creek part tidal, part Creek part tidal, part freshwaterfreshwater

•• Current EPA Current EPA recommended bacterial recommended bacterial indicator for marine (and indicator for marine (and fresh water)fresh water)

•• All water samples were All water samples were analyzed for enterococci analyzed for enterococci using EPA Method 1600.using EPA Method 1600.

Water Quality StandardWater Quality Standard•• Contact Recreation Contact Recreation

–– Geometric mean (GM): 35 cfu/100 mlGeometric mean (GM): 35 cfu/100 ml–– Single sample (SS): 89 cfu/100ml Single sample (SS): 89 cfu/100ml

(Incorrect)(Incorrect)•• Proposed WQS revisions for SS criteria: Proposed WQS revisions for SS criteria:

–– 158 cfu/100 ml for 158 cfu/100 ml for moderatemoderate recreation use recreation use (i. e. away from swimming beaches)(i. e. away from swimming beaches)

–– 104 cfu/100 ml for 104 cfu/100 ml for highhigh recreation use (i.e. recreation use (i.e. within 1,000 feet of shore in swimming within 1,000 feet of shore in swimming beach areas)beach areas)

Water Quality StandardWater Quality Standard

•• Assessment criteriaAssessment criteria

–– Fully supporting if geometric mean < Fully supporting if geometric mean < criterion criterion andand 25% of time or less, 25% of time or less, concentrations are < single sample concentrations are < single sample criterion.criterion.

-- Not supporting if geometric mean > Not supporting if geometric mean > standard, standard, oror if concentrations are > if concentrations are > single sample standard more than 25% of single sample standard more than 25% of time. time.

Review of Review of EnterococcusEnterococcus DataData

•• TCEQ TRACS DataTCEQ TRACS Data•• Period of RecordPeriod of Record

–– 1999 1999 –– 20042004•• Frequency of Data CollectionFrequency of Data Collection

–– Quarterly (Stations 13028 and 13440)Quarterly (Stations 13028 and 13440)–– Monthly (Oct 1999Monthly (Oct 1999--Sep 2000)Sep 2000)

3

Enterococci Single Sample Exceedence of the Criterion (104 cfu/100 ml)

100

6756

42

25

36

83

33

0

20

40

60

80

100

120

13029 16712 13028 13027 13026 13440 13441 13442

TCEQ Station

Per

cen

t (%

)

Enterococci Geometric Mean (35 cfu/100 ml)

692

212 207

117

2856

316

56

0

100

200

300

400

500

600

700

800

13029 16712 13028 13027 13026 13440 13441 13442

TCEQ Station

cfu

/100

ml

Wet Weather Enterococci Sampling

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

13029 16712 13028 13027 13026 13440 13441 13442

cfu/

100

ml

14-Mar-0015-Mar-0017-Mar-0012-Apr-00

Study Strategy:Study Strategy:

•• Determine the Determine the potential sources of potential sources of enterococci in the enterococci in the watershed by watershed by analyzing data from analyzing data from both targeted and both targeted and ambient stationsambient stations

Sampling StationsSampling Stations

•• Ambient Ambient –– 11 stations in creek/bay11 stations in creek/bay–– Historical data for 8, 3 new upstream stationsHistorical data for 8, 3 new upstream stations–– Representative of watershedRepresentative of watershed

•• Targeted (after rainfall)Targeted (after rainfall)–– 11 stations throughout watershed 11 stations throughout watershed –– potential potential

sourcessources–– Source AssessmentSource Assessment

•• Sanitary Survey to assess possible sourcesSanitary Survey to assess possible sources–– Sample 3Sample 3--5 days 5 days

Potential sources Potential sources

•• Urban runoffUrban runoff•• Rural community (septic systems)Rural community (septic systems)•• Agricultural runoffAgricultural runoff•• LivestockLivestock•• Landfill runoffLandfill runoff

4

Source AssessmentsSource Assessments

• Downstream from WWTPs– Oso Bay (S1)– Robstown (WWTP ditch)

S7• Landfill runoff: S8• Rural communities (septic

system, animals): S9 S10

Source AssessmentsSource Assessments

• Livestock– Open storm ditch

(S5)

• Urban runoff ditches– S2, S6, S3

• Agriculture– S4

• Oso golf course– S11

Field ParametersField Parameters

•• HydrolabHydrolab H20 H20 MultiprobeMultiprobe Water Water Quality MonitorQuality Monitor–– Dissolved oxygen Dissolved oxygen

(DO)(DO)–– ConductivityConductivity–– Water temperatureWater temperature–– SalinitySalinity–– pHpH

•• Days since last Days since last significant rainfallsignificant rainfall

•• Rainfall: 24 hr, 7 dayRainfall: 24 hr, 7 day•• Water observations Water observations ––

color, odor, surfacecolor, odor, surface•• SecchiSecchi disk disk

transparencytransparency•• FlowFlow•• Tide stageTide stage•• Air temperatureAir temperature•• Weather (cloudy, etc.)Weather (cloudy, etc.)•• Wind intensity, Wind intensity,

directiondirection

Sampling PlanSampling Plan

•• May 19, 2005 May 19, 2005 -- June 8, 2006 June 8, 2006 •• Monthly: Monthly:

–– 11 ambient (in creek/bay) stations 11 ambient (in creek/bay) stations

•• Weekly: Weekly: –– Ambient stations for two monthsAmbient stations for two months

•• Daily for 5 days following rainfall :Daily for 5 days following rainfall :–– Ambient + targeted (22 stations) Ambient + targeted (22 stations)

Salinity Salinity –– dry weatherdry weather

0.0

4.0

8.0

12.0

16.0

20.0

24.0

28.0

32.0

36.0

40.0

44.0

48.0

52.0

5/19

/05

6/19

/05

7/19

/05

8/19

/05

9/19

/05

10/1

9/05

11/1

9/05

12/1

9/05

1/19

/06

2/19

/06

3/19

/06

4/19

/06

5/19

/06

Salin

ity (p

su)

1849918500

18501

1302916712

13028

1302713026

1344013441

13442

5

ExceedanceExceedance –– dry weather SSdry weather SS% Exceedance Dry Weather

0

10

20

30

40

50

60

70

80

90

100

1849

9

1850

0

1850

1

1302

9

1671

2

1302

8

1302

7

1302

6

1344

0

1344

1

1344

2

Station I.D.

% (

per

cen

t) 104 CFU/100ml

158 CFU/100ml

89 CFU/100ml

ExceedanceExceedance –– wet weatherwet weather

% Exceedance Wet Weather

0

10

20

30

40

50

60

70

80

90

100

1849

9

1850

0

1850

1

1302

9

1671

2

1302

8

1302

7

1302

6

1344

0

1344

1

1344

2

Statio n I.D.

% (

per

cen

t)

104 CFU/100ml 158 CFU/100ml

89 CFU/100ml

ExceedanceExceedance: targeted : targeted stationsstations

% Exceedance Wet Weather

0

10

20

30

40

50

60

70

80

90

100

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11

Station I.D.

% (p

erce

nt)

104 CFU/100ml

158 CFU/100ml

89 CFU/100ml

110

100

1000

1000

010

0000

08-May-05 07-Jul-05 05-Sep-05 04-Nov-05 03-Jan-06 04-Mar-06

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13027 -All Dates Rule GM 13027-dry Station GM Dry Station GM

Bacteria concentrations Bacteria concentrations --1302713027

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•• Geometric mean for all collected data at 13027Geometric mean for all collected data at 13027

•• Geometric mean rule 35 cfu/100mlGeometric mean rule 35 cfu/100ml

•• Dry day sample concentrations onlyDry day sample concentrations only

•• Does not meet geometric mean rule for wet or Does not meet geometric mean rule for wet or dry conditions. Must meet dry conditions first!dry conditions. Must meet dry conditions first!

•• Geometric mean for dry day concentrations onlyGeometric mean for dry day concentrations only

Results Results –– Oso CreekOso Creek

•• Oso Creek bacteria levels exceeded Oso Creek bacteria levels exceeded standards for many dry weather standards for many dry weather events as well as following rainfall events as well as following rainfall events. events.

•• Targeted stations sampled following Targeted stations sampled following rainfall provided insight into loading rainfall provided insight into loading from a variety of sourcesfrom a variety of sources

Bacteria Concentrations Bacteria Concentrations --1344213442


13442 Rule GM Station GM 13442-dry Dry Station GM

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•• Geometric mean rule 35 cfu/100mlGeometric mean rule 35 cfu/100ml

•• Dry day sample concentrations onlyDry day sample concentrations only

•• Geometric mean for dry day Geometric mean for dry day concentrations onlyconcentrations only

•• Geometric mean of all daysGeometric mean of all days

•• Both wet and dry conditions meet Both wet and dry conditions meet geometric mean!geometric mean!

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Results Results –– Oso BayOso Bay

•• With the exception of 1 station in Oso With the exception of 1 station in Oso Bay (which has been identified as not Bay (which has been identified as not representative of the bay) there were representative of the bay) there were no load reductions needed to meet no load reductions needed to meet water quality goalswater quality goals

ModelingModeling

•• A numerical bacteria loading model A numerical bacteria loading model was developed and the required load was developed and the required load reduction was calculated as the reduction was calculated as the difference between the current loading difference between the current loading and the allowed loadingand the allowed loading

Daily Model SetDaily Model Set--upup

•• Calibration period.Calibration period.–– 10/01/1999 10/01/1999 –– 09/31/2000.09/31/2000.

•• Inputs.Inputs.–– Precipitation (NEXRAD).Precipitation (NEXRAD).

•• Hourly grids combined into Hourly grids combined into 1 daily grid.1 daily grid.

–– Runoff.Runoff.

–– Bacteria loadings for each Bacteria loadings for each subsub--basin.basin.

•• Initial bacteria input for Initial bacteria input for each station.each station.

–– Land use (Event Land use (Event Concentrations)Concentrations)

•• 12 time step intervals.12 time step intervals.–– Look at decay process every Look at decay process every

2 hours.2 hours.

•• Time of flow.Time of flow.–– Nontidal stations.Nontidal stations.

•• Calculate velocity.Calculate velocity.

–– Tidal stations.Tidal stations.•• Calculate residence times.Calculate residence times.

•• Bacteria from upstream Bacteria from upstream station depends on:station depends on:

–– Flow of water from station.Flow of water from station.–– Volume of water in stream.Volume of water in stream.–– Decay RatesDecay Rates

EC

Rain

Runoff

Runoff Load

*

Runoff Coefficient

Sum Loads

Along each subwatershed

Calculate Decayed Loads

From station

upstream

Dry Day Loading

Modeling ProcessModeling Process

Repeat for next subbasin

Point Source Load

SubbasinSubbasin LocationsLocations

Model ResultsModel Results

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Model PerformanceModel PerformanceRMSE of log(concentration) RMSE of log(concentration) –– Current dataCurrent data

•• Overall RMSE 0.68 log of ConcentrationOverall RMSE 0.68 log of Concentration•• Bay stations exhibit higher error but concentrations are Bay stations exhibit higher error but concentrations are

lowlow

Overall RMSE(log) by StationDaily Model for Current Data

0

0.5

1

1.5

2

18499 18500 13029 16712 13028 13027 13026 13440 13442

Stations

RM

SE

(lo

g)

RMSE

Data VariabilityOverall RMSE

Bias in Measured and Bias in Measured and Modeled DataModeled Data•• Measured data over current study period Measured data over current study period

has 1/3 of the data collected in association has 1/3 of the data collected in association with rain events.with rain events.

•• Measured data over the calibration period Measured data over the calibration period also had 1/3 of the data associated with rain also had 1/3 of the data associated with rain eventsevents

•• Only about 1/5 of the year is rainy.Only about 1/5 of the year is rainy.

Modeled Load Modeled Load –– 2485a2485a•• Modeled Load for nonModeled Load for non--tidal creek stationstidal creek stations

–– All exceed geometric mean criteria and single All exceed geometric mean criteria and single sample criteriasample criteria

•• Modeled Load for tidal creek stationsModeled Load for tidal creek stations–– All exceed geometric mean criteria and single All exceed geometric mean criteria and single

sample criteriasample criteria

18499 18500 13029Model Load w/ Dry Load in creek 1.71E+16 1.26E+16 1.35E+16GM Concentration from Model 1366.50 1320.46 908.6825 % Exceedence from Model 1220.59 1508.19 1135.79


Modeled Load Modeled Load –– 24852485

•• Modeled Load for bay stations.Modeled Load for bay stations.–– All meet geometric mean and single All meet geometric mean and single

sample criteria.sample criteria.


What is responsible for the What is responsible for the exceedancesexceedances??•• Dry day loading occurs every day.Dry day loading occurs every day.•• This keeps daily bacteria This keeps daily bacteria

concentrations high.concentrations high.•• High daily concentrations cause the High daily concentrations cause the

segment to violate the geometric mean segment to violate the geometric mean criteria.criteria.

Dry Day LoadingDry Day Loading

•• Loading not associated with runoff events.Loading not associated with runoff events.–– Supports high bacteria concentrations without Supports high bacteria concentrations without

runoff input.runoff input.•• Major factor in nonMajor factor in non--attainment for the creek attainment for the creek

section.section.•• Potential source for dry day loading:Potential source for dry day loading:

–– Ground water influx (septic systems).Ground water influx (septic systems).–– Bacteria flux from soils.Bacteria flux from soils.–– Birds nesting under bridges.Birds nesting under bridges.–– Wildlife or other animals in creek.Wildlife or other animals in creek.–– Illegal discharge to stream.Illegal discharge to stream.–– Leaking utilities.Leaking utilities.–– Natural bacterial growth.Natural bacterial growth.

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Modeled load with no Dry Day Load Modeled load with no Dry Day Load -- CreekCreek

•• Loading and concentrations for nonLoading and concentrations for non--tidal creek tidal creek section after removing dry day load contributionsection after removing dry day load contribution

•• Loading and concentrations for tidal creek Loading and concentrations for tidal creek section after removing dry day load contributionsection after removing dry day load contribution

•• Some creek segments meet Geometric Mean Some creek segments meet Geometric Mean goals if dry day loading is eliminated!goals if dry day loading is eliminated!

•• None meet Single Sample rule.None meet Single Sample rule.

18499 18500 13029Model Load w/o Dry Load in creek 1.70E+16 1.25E+16 1.34E+16GM Concentration from Model 36.03 39.41 38.6025 % Exceedence from Model 419.30 929.63 793.62


Load ReductionsLoad Reductions

Load reductions (modeled data)Load reductions (modeled data)•• No Dry Day Load and reduction in runoff load of No Dry Day Load and reduction in runoff load of

93% (18499), 90% (18500) 93% (18499), 90% (18500) –– Segment 2485a nonSegment 2485a non--tidaltidal..

•• No Dry Day Load and reduction in runoff load of No Dry Day Load and reduction in runoff load of 90% (16712), 50% (13027) 90% (16712), 50% (13027) -- Segment 2485a tidalSegment 2485a tidal

18499 18500 13029Model Load w/noDry Load in creek 1.19E+15 9.45E+14 4.22E+15GM Concentration from Model 13.45 10.81 13.2025 % Exceedence from Model 31.78 68.61 96.59Total Reduction 1.59E+16 1.17E+16 9.30E+15Allowed Load 1.19E+15 9.45E+14 4.22E+15

Model Load w/noDry Load in creek 6.64E+15 6.30E+15 7.79E+15GM Concentration from Model 15.67 10.83 11.6425 % Exceedence from Model 66.97 60.18 78.78Total Reduction 1.44E+16 1.59E+16 1.06E+16Allowed Load 6.64E+15 6.30E+15 7.79E+15

Load reductions (modeled Load reductions (modeled data)data)

•• No load reduction required in bay No load reduction required in bay section (Segment 2485)section (Segment 2485)

•• Loading on bay after upstream load Loading on bay after upstream load reductions appliedreductions applied


13026 13440 13442Model Load w/noDry Load in creek 6.52E+15 4.38E+15 2.39E+15GM Concentration from Model 2.36 2.41 2.1525 % Exceedence from Model 1.56 1.88 1.29

Load Distribution by Load Distribution by SubbasinSubbasin

Station

Annual Dry

Loading

WWTP Annual Loading Residential Urban Crop Range

Total Non-Point

Source Load

Upstream Load

Load Reductions

18499 20 0.07 3411 2186 8863 669 15129 NA 1409018500 24 0.00 54 25 2625 124 2828 1206 256913029 3 0.00 24 22 2195 80 2320 965 316712 50 0.40 2985 5749 7525 1168 17427 954 1573413028 166 0.00 139 233 4526 334 5232 2156 16613027 616 0.00 11536 6310 2936 762 21545 1553 1138813026 108 0.00 1436 1254 7374 4216 14279 1470 013440 134 0.00 6683 3001 845 1559 12088 1207 013441 7 0.79 5159 1780 1 138 7079 NA 513442 285 0.00 4482 4028 381 593 9483 3009 0

All numbers are in 1012

colony forming units

SummarySummary

•• Segment 2485a (Oso Creek Tidal and nonSegment 2485a (Oso Creek Tidal and non--Tidal) Tidal) cannot meet water quality goals without controlling cannot meet water quality goals without controlling Dry Day Loading and Runoff Loading.Dry Day Loading and Runoff Loading.

–– Dry day loading must be eliminated to meet geometric Dry day loading must be eliminated to meet geometric mean rule.mean rule.

–– Runoff loading in Runoff loading in subbasinsubbasin 18499 must be reduced by 93%.18499 must be reduced by 93%.–– Runoff loading in Runoff loading in subbasinsubbasin 18500 must be reduced by 90%.18500 must be reduced by 90%.–– Runoff loading in Runoff loading in subbasinsubbasin 16712 must be reduced by 90%.16712 must be reduced by 90%.–– Runoff loading in Runoff loading in subbasinsubbasin 13027 must be reduced by 50%.13027 must be reduced by 50%.

•• Most of segment 2485 (Oso Bay) meets water Most of segment 2485 (Oso Bay) meets water quality goals especially if sample collection is more quality goals especially if sample collection is more representative of annual dry/wet day distributionrepresentative of annual dry/wet day distribution

•• OsoOso Bay TMDL report prepared by TCEQBay TMDL report prepared by TCEQ

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SummarySummary

•• Water quality objectives for Oso Creek could be met Water quality objectives for Oso Creek could be met by removing dry day loadings from all creek subby removing dry day loadings from all creek sub--basins and runoff loadings from 4 of the subbasins and runoff loadings from 4 of the sub--basins.basins.

•• Dry day loading in Oso Creek is a critical element in Dry day loading in Oso Creek is a critical element in the bacteria loading of Oso Creek; however, its the bacteria loading of Oso Creek; however, its source(s) are unknown and will need to be identified source(s) are unknown and will need to be identified in order to develop and implement a load reduction in order to develop and implement a load reduction strategy for Oso Creek. strategy for Oso Creek.

•• Modeled loadings more representative of wet and Modeled loadings more representative of wet and dry periods than measured loadingsdry periods than measured loadings

What Next?What Next?

•• Potential sources of dry day loading Potential sources of dry day loading –– Ground water interaction with Oso Creek/Oso Bay Ground water interaction with Oso Creek/Oso Bay –– Wildlife or other animal input Wildlife or other animal input –– Natural growth of bacteria in the creek Natural growth of bacteria in the creek

•• Upper subUpper sub--basin source(s) of loadingsbasin source(s) of loadings–– Bacterial Source Tracking (Animal)Bacterial Source Tracking (Animal)–– Physical Source TrackingPhysical Source Tracking

•• Sediment /soil studiesSediment /soil studies

•• Continued collaboration for agricultural runoff Continued collaboration for agricultural runoff (TAES, USGS)(TAES, USGS)

Questions ?Questions ? Event Mean ConcentrationsEvent Mean Concentrations

•• Daily model with bihourly calculations Daily model with bihourly calculations required data representing actual runoff required data representing actual runoff concentrations not mean concentrations concentrations not mean concentrations over a runoff eventover a runoff event

•• Back calculated runoff concentrations from Back calculated runoff concentrations from measured values at 18501 based on an measured values at 18501 based on an average observed decay rate (average observed decay rate (––2.0)2.0)

•• This estimates a runoff concentration 7 This estimates a runoff concentration 7 times higher that the previously applied times higher that the previously applied event mean concentrations.event mean concentrations.

Decay RateDecay Rate

•• Two distinct salinity zonesTwo distinct salinity zones•• Low salinity zone above 13027 (Staples)Low salinity zone above 13027 (Staples)•• High salinity below Barney Davis outfall High salinity below Barney Davis outfall

(Yorktown)(Yorktown)•• Constrained by literature values for Constrained by literature values for

enterococci enterococci •• Values (calculated from observed data but Values (calculated from observed data but

constrained by literature values for constrained by literature values for enterococcienterococci ))–– Low salinity zone Low salinity zone ––2.0 (1.1 days for 90% die off)2.0 (1.1 days for 90% die off)–– High salinity zone High salinity zone ––4.0 (0.57 days for 90% die off)4.0 (0.57 days for 90% die off)

“Event Concentrations”“Event Concentrations”

•• Event concentrations correspond to the Event concentrations correspond to the actual bacteria concentration of the runoff actual bacteria concentration of the runoff water (first flush)water (first flush)

•• EMC values were as high as 47,880 EMC values were as high as 47,880 cfu/100mlcfu/100ml

•• EC values are now as high as 353,000 EC values are now as high as 353,000 cfu/100mlcfu/100ml–– EC values are in the range of those reported by EC values are in the range of those reported by

the City of Corpus Christi in a storm water the City of Corpus Christi in a storm water assessment program for some urban runoff assessment program for some urban runoff (330,000 cfu/100ml to 445,000 cfu/100ml for (330,000 cfu/100ml to 445,000 cfu/100ml for Fecal Coliform bacteria)Fecal Coliform bacteria)

10

Dry Day LoadingDry Day Loading•• Bacteria loadings were noted to occur Bacteria loadings were noted to occur

without the driving force of precipitationwithout the driving force of precipitation•• Although the source is unknown, an Although the source is unknown, an

estimate can be made of the magnitude of estimate can be made of the magnitude of the loadingthe loading

•• This estimate was “fitted” into the model for This estimate was “fitted” into the model for each each subbasinsubbasin..

•• Dry Day Loading was applied to the model Dry Day Loading was applied to the model as a constant for each as a constant for each subbasin subbasin with no with no temporal variationtemporal variation

•• Dry day load ranges from 10Dry day load ranges from 1088 bacteria (in a bacteria (in a segment) to 10segment) to 101111 bacteria.bacteria.

Summary (continued)Summary (continued)•• Station 13441 (in segment 2485 Station 13441 (in segment 2485 –– Oso Oso

Bay) does not meet water quality goals.Bay) does not meet water quality goals.•• Load reduction.Load reduction.

–– Dry day loading must be reduced by 75% Dry day loading must be reduced by 75% (4.7x10(4.7x101212).).

–– Removal of runoff loading Removal of runoff loading does notdoes not reduce reduce load enough to meet geometric mean rule.load enough to meet geometric mean rule.

–– Removal of load from Oso WWTP Removal of load from Oso WWTP does notdoes notreduce load enough to meet geometric mean reduce load enough to meet geometric mean rule or the single sample rule. rule or the single sample rule.

•• Station 13441 may not be representative Station 13441 may not be representative of ambient conditions in Oso Bay.of ambient conditions in Oso Bay.–– Does not respond in a similar fashion to other Does not respond in a similar fashion to other

stations.stations.–– Is not in the direct flow pattern of the Oso Is not in the direct flow pattern of the Oso

Creek/Oso Bay drainage system.Creek/Oso Bay drainage system.

Bacteria Concentrations Bacteria Concentrations --1344113441


13441 Rule GM Station GM 13442-dry Dry Station GM

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00m

l)

•• Geometric mean of all data for station Geometric mean of all data for station (134)(134)

11

01

00

10

00

10

00

01

00

00

0


Bac

teri

a (c

fu/1

00m

l) •• Dry day concentrationsDry day concentrations

11

01

00

10

00

10

00

01

00

00

0


Bac

teri

a (c

fu/1

00m

l)

•• Geometric mean of dry day Geometric mean of dry day concentrations (95)concentrations (95)

•• Does not meet GM rule on dry days.Does not meet GM rule on dry days.

•• Geometric mean rule (35 cfu/100ml)Geometric mean rule (35 cfu/100ml)

Model loadings for 13441Model loadings for 13441

•• Modeled load with dry day loadings.Modeled load with dry day loadings.

•• Modeled load with no dry day loading.Modeled load with no dry day loading.

13441Model Load w/ Dry Day Load 2.64E+13GM Concentration from Model 71.1025 % Exceedence from Model 57.55

13441Model Load w/o Dry Day Load 2.01E+13GM Concentration from Model 11.3625 % Exceedence from Model 17.47

Station 13441Station 13441

•• Has been modeled as a tributary and not Has been modeled as a tributary and not part of the ordered stream flow from part of the ordered stream flow from Robstown to Corpus Christi Bay.Robstown to Corpus Christi Bay.–– Station responds differently than the other bay Station responds differently than the other bay

stations.stations.–– Salinity similar to creek stations.Salinity similar to creek stations.–– Poorest model fit (compared to other stations) Poorest model fit (compared to other stations)

•• perhaps due to seasonality in dry day loading.perhaps due to seasonality in dry day loading.

–– Dry day loading might be attributed to shore bird Dry day loading might be attributed to shore bird population.population.

Annual Load Reduction for Annual Load Reduction for 1344113441•• 75% Load reduction of dry day loadings.75% Load reduction of dry day loadings.

•• Without runoff loading(1.96x10Without runoff loading(1.96x1013 13

bacteria).bacteria).

•• Remove Oso WWTP Load (7x10Remove Oso WWTP Load (7x101111

bacteria).bacteria).

75%Reduction in Dry Day Load 2.17E+13GM Concentration from Model 28.8525 % Exceedence from Model 27.50Load Reduction 4.74E+12

Without Runoff Load 7.00E+12GM Concentration from Model 44.8725 % Exceedence from Model 47.31Load Reduction 1.94E+13

Annual Load with no Oso WWTP 2.57E+13GM Concentration from Model 65.5625 % Exceedence from Model 53.22Load Reduction 6.77E+11

11

Log Normal Distribution of Bacteria Log Normal Distribution of Bacteria Concentrations (loading)Concentrations (loading)at Station 13442 with no dry day loading.at Station 13442 with no dry day loading.

•• Meets both criteriaMeets both criteria

Loadings at 13442

0

1

2

3

4

5

6

7

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Probability

Lo

g(C

on

cen

trat

ion

)

Data

Log Normal fit to data

LogNormal fit to GMLog normal fit to SSC

25% exceedance

Geometric MeanSingle Sample Criteria

50% exceedance

Model with Dry Load

ResultsResults

•• Enterococci numbers increase Enterococci numbers increase dramatically 1dramatically 1--2 days after rainfall2 days after rainfall

•• Stay elevated 3Stay elevated 3--5+ days depending on 5+ days depending on rainfallrainfall

•• Ambient stations exceeded both Ambient stations exceeded both standards 27standards 27--100% after rainfall 100% after rainfall depending on stationdepending on station

•• Targeted stations exceeded standards Targeted stations exceeded standards 3939--100% after rainfall depending on 100% after rainfall depending on stationstation

June Rain Event (2006)June Rain Event (2006)

00.5

11.5

22.5

33.5

44.5

5

CFU

s/10

0ml

(log

scal

e)

1849

9

1850

1

1850

0

1302

9

1671

2

1302

8

1302

7

1302

6

1344

0

1344

1

1344

2

Station I.D.

Ambient Stations

Day 1

Day 2

Day 3

Day 4

Day 5

June Rain Event (2006)June Rain Event (2006)

00.5

11.5

22.5

33.5

44.5

5

CFU

s/10

0ml

(log

scal

e)

S3

S7

S9

S8

S4

S10 S2

S6

S5

S11 S1

Station I.D.

Targeted Stations

Day 1

Day 2Day 3Day 4Day 5

ResultsResults

•• Ambient freshwater Ambient freshwater stations exceeded stations exceeded 3939--100% of the time 100% of the time for dry sampling for dry sampling datesdates

•• Targeted stations Targeted stations sampled during dry sampled during dry weather exceeded weather exceeded standardsstandards

VolumesVolumes

•• Main channel volumes.Main channel volumes.–– Inputs.Inputs.

•• Upstream flow.Upstream flow.•• Runoff.Runoff.•• Additional sources (Robstown, Greenwood, Additional sources (Robstown, Greenwood,

Oso WWTPs, and Barney Davis power plant).Oso WWTPs, and Barney Davis power plant).

12

Average Monthly Flow at Barney Davis Power Plant 1998 - 2004

0

100

200

300

400

500

600

Jan-

98

Jul-

98

Jan-

99

Jul-

99

Jan-

00

Jul-

00

Jan-

01

Jul-

01

Jan-

02

Jul-

02

Jan-

03

Jul-

03

Jan-

04

Jul-

04

Flo

w (

MG

D)

Model PerformanceModel PerformanceRMSE of log(concentration) RMSE of log(concentration) –– Historic dataHistoric data

•• Overall RMSE 1.04 log of ConcentrationOverall RMSE 1.04 log of Concentration•• Bay station exhibit higher error but Bay station exhibit higher error but

concentrations are lowconcentrations are low

Historic Dataon Daily model with Dry loads upcreek

0.00

0.50

1.00

1.50

2.00

13029 16712 13028 13027 13026 13440 13442

Stations

RM

SE

(lo

g)

RMSE(log)Data Variability

Overall Model RMSE

Loadings at 13027

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Probability

Lo

g(C

on

cen

trat

ion

)

LogNormal fit to GM

Log normal fit to SSC

25% exceedanceGeometric Mean

Single Sample Criteria

50% exceedance

Loadings at 13027

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Probability

Lo

g(C

on

cen

trat

ion

)

Data


25% exceedance


50% exceedance

Loadings at 13027

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Probability

Lo

g(C

on

cen

trat

ion

)

DataLog Normal fit to data

LogNormal fit to GM

Log normal fit to SSC25% exceedance

Geometric Mean


50% exceedance

Loadings at 13027

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Probability

Lo

g(C

on

cen

trat

ion

)

Data



25% exceedance


50% exceedance

Model with Dry Load

Log Normal Distribution of Bacteria Log Normal Distribution of Bacteria Concentrations (loading) at Station 13027Concentrations (loading) at Station 13027

•• Critical rule Critical rule –– Geometric MeanGeometric Mean

•• Red lines show a logRed lines show a log--normal distribution of normal distribution of bacteria concentrations that meet (just) Single bacteria concentrations that meet (just) Single Sample rule Sample rule –– no more that 25% of values can no more that 25% of values can exceed 104 cfu/100mlexceed 104 cfu/100ml•• Green lines show a logGreen lines show a log--normal distribution of normal distribution of

bacteria concentrations that meet (just) the bacteria concentrations that meet (just) the Geometric Mean rule Geometric Mean rule –– GM of ten samples must GM of ten samples must be less than 35 cfu/100mlbe less than 35 cfu/100ml

•• Bacteria concentrations measured in this projectBacteria concentrations measured in this project

•• LogLog--normal fit to data measured in this projectnormal fit to data measured in this project

•• Model loads for 365 daysModel loads for 365 days

Log Normal Distribution of Bacteria Log Normal Distribution of Bacteria Concentrations (loading) at Station 13442Concentrations (loading) at Station 13442

•• Meets both criteriaMeets both criteria

Loadings at 13442

0

1

2

3

4

5

6

7

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Probability

Lo

g(C

on

cen

trat

ion

)

Data



25% exceedance


50% exceedance

Model with Dry Load

Log Normal Distribution of Bacteria Log Normal Distribution of Bacteria Concentrations (loading) at Station 13027 with no Concentrations (loading) at Station 13027 with no dry day loadingdry day loading

•• Meets only Geometric Mean rule.Meets only Geometric Mean rule.

Loadings at 13027

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00

Probability

Lo

g(C

on

cen

trat

ion

)

Data

Log Normal fit to dataLogNormal fit to GM

Log normal fit to SSC

25% exceedanceGeometric Mean


50% exceedanceModel with Dry Load

ConclusionConclusion

•• Suggest large Suggest large amount of dry daily amount of dry daily loadingloading

•• Enterococci in Enterococci in water column or water column or sedimentssediments

13

OutlineOutline

•• BackgroundBackground•• SamplingSampling•• Bacteria concentration measurementsBacteria concentration measurements•• Dry day loadingDry day loading•• Ground waterGround water•• Fitting model to dataFitting model to data•• Model performanceModel performance•• Model resultsModel results•• Load reductionsLoad reductions•• Station 13441Station 13441•• ConclusionsConclusions

Pathogen sources and Pathogen sources and transporttransport•• Point sourcesPoint sources

–– Direct transport from Direct transport from sourcesource

•• Wastewater Treatment Wastewater Treatment Plant (WWTP) effluentPlant (WWTP) effluent

•• Combined sewer Combined sewer overflowsoverflows

•• Sewer overflowsSewer overflows•• Animal feeding Animal feeding

operationsoperations•• SlaughterhousesSlaughterhouses•• Fish and Shellfish Fish and Shellfish

processing facilitiesprocessing facilities

•• NonNon--point sourcespoint sources–– Diffuse, hard to define Diffuse, hard to define

and wide geographic and wide geographic areaarea

–– UrbanUrban•• Domestic petsDomestic pets•• Wildlife excrementWildlife excrement•• Failing sewer linesFailing sewer lines

–– Rural areasRural areas•• Leaking septic systemLeaking septic system•• Land application of Land application of

manuremanure•• Wildlife excrementWildlife excrement•• LivestockLivestock

Modeled load with No Dry Day Load Modeled load with No Dry Day Load --BayBay

•• Loading and concentrations for bay Loading and concentrations for bay section without dry day loadingsection without dry day loading

•• Stations continue to meet water quality Stations continue to meet water quality goalsgoals


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