Barr-Milton Watershed Barr-Milton Watershed Modeling Project - Workshop #4Modeling Project - Workshop #4

David Pillard, Ph.D. – Project Manager, Ft. David Pillard, Ph.D. – Project Manager, Ft. Collins, COCollins, CO

Ken Heim, Ph.D. – Lead Modeler, Westford, MAKen Heim, Ph.D. – Lead Modeler, Westford, MA

Ken Wagner, Ph.D. – Solutions Support – Ken Wagner, Ph.D. – Solutions Support – Willington, CTWillington, CT

Key Project PremisesKey Project Premises

• Barr Reservoir and Milton Lake experience periodic high pH (>9.0) that violate state standard (<9 for 85% of time)

• High pH is believed to be a consequence of algal productivity (removal of CO2 during photosynthesis)

• Algal productivity is controlled mainly by nutrients, light and temperature

• Nitrogen affects the types of algae present, but phosphorus tends to control the quantity of algae and is the most practical nutrient to control

• Available phosphorus levels are very high in both waterbodies

Derivation of Potentially Protective P LoadsDerivation of Potentially Protective P LoadsFeature or Scenario Units Barr Milton Notes

Chlorophyll (ug/L) target based on regressions using Chl and Temp - Summer (constructed from 2002-2007 data) ug/L 14 1.5

Accounts for only about half the variation in pH

Chlorophyll (ug/L) target based on regressions using Chl and Temp - Winter (constructed from 2002-2007 data) ug/L 127 5.0

Accounts for only about half the variation in pH; lower temp allows greater Chl

Chlorophyll (ug/L) target based on calculated mean that yields a Chl corresponding to pH=9.0 SU for 15% of the time from all 2002-2007 data ug/L 77 77

Depends on Chl-pH relationship that is very weak in Barr and Milton; Barr data applied to both

Chlorophyll (ug/L) target based on calculated mean that yields a Chl corresponding to pH=9.0 SU for 15% of the time from summer 2002-2007 data ug/L 47 47

Depends on Chl-pH relationship that is very weak in Barr and Milton; Barr data applied to both

Chlorophyll (ug/L) target based 15th percentile of pH data >9.0 SU from 2002-2007 data ug/L 21 6.8

Reflects actual occurrence of high pH over 6 years

Chlorophyll (ug/L) target based 15th percentile of pH data >9.0 SU from summer 2002-2007 data ug/L 18 8.2

Lower Chl from subset of data, most likely results from influence of higher temperature

Chlorophyll (ug/L) target based 15th percentile of pH data >9.0 SU from 2002-2007 data for other Denver area reservoirs ug/L 25 25

Mostly summer data from 15 area reservoirs with some wastewater influence but no major benthic algae or rooted plants

mg/L

mg/L

mg/L

mg/L

mg/L

kg/yr 20500 19600

kg/yr 12400 11900

kg/yr 6230 5950

Applies to Barr

Derivation of Potentially Protective P LoadsDerivation of Potentially Protective P Loads

ug/L 14 1.5

ug/L 127 5.0

ug/L 77 77

ug/L 47 47

ug/L 21 6.8

ug/L 18 8.2

Chlorophyll (ug/L) target based 15th percentile of pH data >9.0 SU from 2002-2007 data for other Denver area reservoirs ug/L 25 25

Mostly summer data from 15 area reservoirs with some wastewater influence but no major benthic algae or rooted plants

Total Phosphorus (mg/L) target to achieve Chl=25 ug/L based on projections from 2002-2007 data mg/L Relies on weak relationshipTotal Phosphorus (mg/L) target to achieve Chl=25 ug/L based on projections from 2002-2007 data from other Denver area reservoirs mg/L

Relies on weak relationship, but consistent with findings for Barr-Milton

Total Phosphorus (mg/L) target to achieve Chl=25 ug/L based on projections from empirical models for temperate North America mg/L

Uses mean of 5 models constructed from different groups of temperate zone lakes

Total Phosphorus (mg/L) target to achieve Chl=25 ug/L based on empirical models as interpreted for Denver area reservoirs mg/L

Doubles empirical model result based on research on plains lakes

Total Phosphorus (mg/L) target to achieve Chl=25 ug/L based on hypothetical trajectory and actual variation in TP-pH relationship from 2002-2007 data mg/L

Hypothetical but theoretically sound constructed curve applied; available data do not cover lower range

Average Total Phosphorus - all 2002-2007 data mg/L 0.68 0.57Average Total Phosphorus - summer data only mg/L 0.56 0.59

Current TP Load kg/yr 85000 67800Converts concentration to load via empirical models

TP load that leads to meeting 0.165 mg/L TP target intended to lead to a 25 ug/L Chl level kg/yr 20500 19600

Converts concentration to load via empirical models

TP load that leads to meeting 0.10 mg/L TP target intended to lead to a 25 ug/L Chl level kg/yr 12400 11900

Converts concentration to load via empirical models

TP load that leads to meeting 0.05 mg/L TP target intended to lead to a 25 ug/L Chl level kg/yr 6230 5950

Converts concentration to load via empirical models

0.09

Applies to Barr

0.17

0.16

0.05

0.10

Limitations of Empirical ModelingLimitations of Empirical ModelingMilton Reservoir Summer Avg pH (WC) vs. TP mg/L

7.00

7.50

8.00

8.50

9.00

9.50

10.00

0.00 0.20 0.40 0.60 0.80 1.00

TP (mg/L)

pH

(S

U)

Barr Lake Summer Avg pH (WC) vs. TP mg/L

7.00

7.50

8.00

8.50

9.00

9.50

10.00

0 0.2 0.4 0.6 0.8 1

TP (mg/L)

pH

(S

U)

• We don’t have site specific data for the low end of the scale• We have a reasonable idea of “background” pH• We can project how background would be approached with

declining TP and the level of associated variability • A TP value somewhere near 0.1 mg/L appears most appropriate,

but is not a hard threshold

Important Things to Remember When Important Things to Remember When Considering ModelingConsidering Modeling

• Biological factors are less amenable to modeling and induce variability/uncertainty in predictions

• Types of algae may matter almost as much as quantity of algae, especially diatom vs. bluegreen dominance

• Historical and current loads are high; predicting responses at lower loads requires reliance on other systems (prediction outside range of site data)

• Internal load is likely to compensate for reduced external load

• Water in Milton appears to be “pre-conditioned” – arrives with higher pH and less margin for compliance

• Actual data is “spotty” – exercise caution when comparing predictions and observations

Watershed InfluencesWatershed Influences

• Major tributary InletsMajor tributary Inlets

• Sub-watershed inletsSub-watershed inlets

• Point SourcesPoint Sources

• ReservoirsReservoirs

• Withdrawals/TransfersWithdrawals/Transfers

(not shown, very (not shown, very complicated pattern)complicated pattern)

Gather all Relevant Watershed and Water Withdrawal/Discharge/Transfer Information

and Comparative Data

Import into Enhanced SWAT Model, Run, and Calibrate

Prepare Required Files using Visual Basic Macros

Prepare SWAT Output for WASP Model

Link WASP to Prepared Files, Run, and Calibrate.

Prepare and Execute Alternative Simulations

Develop TMDL

SchematicSchematic Showing Steps Showing Steps

Taken to Taken to Complete Complete

Watershed-Lake Watershed-Lake ModelingModeling

SWAT = Soil and Water Assessment Tool

WASP = Water Analysis Simulation Program

O'Brian Canal Inlet to Barr - Total Phosphorus

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Jan-03 Apr-03 Jul-03 Oct-03 Jan-04 Apr-04 Jul-04 Oct-04

Co

nce

ntr

atio

n (

mg

/L)

Measured Predicted

Results of Watershed Model

Barr LakePredicted Volume

Barr LakePredicted P Concentration

Barr Lake: 2003-04Measured and Predicted Volumes

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

Jan-03 Apr-03 Jul-03 Oct-03 Jan-04 Apr-04 Jul-04 Oct-04

Vo

lum

e (a

cre-

ft)

Measured Predicted

Barr Lake Total Phosphorus Barr Lake Total Phosphorus Calibration ResultsCalibration Results

0.0

0.5

1.0

1.5

2.0

Jan

2003

Apr

200

3

Jul 2

003

Oct

200

3

Jan

2004

Apr

200

4

Jul 2

004

Oct

200

4

To

tal P

(p

pm

)

WASP PredictedMeasured

Barr Lake Total Chlorophyll Barr Lake Total Chlorophyll Calibration ResultsCalibration Results

0

50

100

150

200

250

Jan

2003

Apr

200

3

Jul 2

003

Oct

200

3

Jan

2004

Apr

200

4

Jul 2

004

Oct

200

4

To

tal C

hlo

rop

hyl

l (p

pb

)

WASP PredictedMeasured

Barr Lake Total Chlorophyll Barr Lake Total Chlorophyll Calibration ResultsCalibration Results

Quantify the effects of several management options on Barr Lake/Milton Reservoir water quality.

1. Wastewater – Reduced phosphorus loads from three major dischargers.

2. Refill – Alter the timing and sources of water for Barr Lake infill.

3. Land Use – Alter the effects of agriculture and urbanization.

4. Reservoir Treatment – Reduced internal phosphorus loading.

Model Scenarios

Total Total Phosphorus Phosphorus PredictionsPredictions

for Barr Lakefor Barr Lake

Total Total Chlorophyll Chlorophyll PredictionsPredictions

for Barr Lakefor Barr Lake

Total Total Phosphorus Phosphorus PredictionsPredictionsfor Milton for Milton ReservoirReservoir

Total Total Chlorophyll Chlorophyll PredictionsPredictionsfor Milton for Milton ReservoirReservoir

Total Total Phosphorus Phosphorus PredictionsPredictions

for Barr Lakefor Barr Lake

Total Total Chlorophyll Chlorophyll PredictionsPredictions

for Barr Lakefor Barr Lake

Total Total Phosphorus Phosphorus PredictionsPredictionsfor Milton for Milton ReservoirReservoir

Total Total Chlorophyll Chlorophyll PredictionsPredictionsfor Milton for Milton ReservoirReservoir

Modeling Implications for Modeling Implications for Compliance StrategiesCompliance Strategies

• The lower the WWTP output P level, the better for the reservoirs, but not necessarily proportionally

• Addressing P from Metro and Littleton/Englewood WWTP is essential

• Internal loading must be addressed• Unless WWTP and internally loaded P are both

addressed, compliance is unlikely to be achieved through P control

• There is enough loading from other sources to prevent achievement of “pristine” conditions

• Have to think in terms of distribution of values; not just mean/median, but shape of upper “tail”

In-Lake Strategies for Lowering pHIn-Lake Strategies for Lowering pH

• P inactivation – reducing available P with aluminum sulfate additions to lakes (also directly lowers pH)

• Mixing/aeration – would avoid localized high pH with algal blooms, may disrupt blooms (esp. blue-greens), encourages CO2 transfer

• Biomanipulation – fosters zooplankton that minimize algal biomass; usually involves altering the fish community

• Algaecides – directly kills algae when too abundant, could limit maximum pH

Towards a TMDL and Towards a TMDL and Management PlanManagement Plan

• A few more combination scenarios might be worthwhile (e.g., WWTP @ 1.0 ppm and 70+% internal load reduction, or other water management options)

• Pilot testing of mixing or reduced P in limnocorrals in the reservoirs might be useful to define direct pH response

• Defining goals in terms of use attainability would be appropriate, with comparison to WQ standards (e.g., when and why should the pH standard be met, based on water uses?)

Questions and CommentsQuestions and Comments