Calibration of thePhase 5 Watershed Model

Progress Report

Modeling Subcommittee

4/3/2007

Today’s Presentations

• This Presentation– Phase 5 calibration strategy overview– Progress since January– Hydrology model validation– First run of 10-year hydrologic periods

• Jing and Rob– Upgrades to the ground cover database– Nursery targets– Re-calibration of land sediment

• Me– River Calibration

Automated Calibration

• Makes Calibration Feasible

• Ensures even treatment across jurisdictions

• Enables uncertainty analysis

• Fully documented calibration strategy

• Repeatable

View from 30,000 feet

CalibrationProcedures

Input Data

“vortex”

CalibrationData

Calibration ProcessHydrology

Land parametersRiver data

TemperatureLand parametersRiver parameters

River data

Land SedimentLand parameters

Land targets

Land NutrientsLand parameters

Land targets

River Water QualityRiver parameters

River targets

1 week

1 week

1 week

1 week

Single-processor time

Progress in January

• Stabilized forest calculation and recalibrated

• Work on EOF to EOS Transport Factors

• Full calibration HydrologyLand parameters

River data

TemperatureLand parametersRiver parameters

River data

Land SedimentLand parameters

Land targets

Land NutrientsLand parameters

Land targets

River Water QualityRiver parameters

River targets

Progress Since January - Code

• Modified hydrology and temperature calibration procedures to allow for calibration of smaller basins

• Consolidation of various phase 5 code versions

• Wrote code to generate outputs requested by VA

Progress Since JanuaryExtended data through 2005

• Rainfall, Temperature, PET

• Observed River Flow data

• Atmospheric deposition data

• Point Source data

• Ran hydrology and temperature calibration

Progress Since January – Land Sediment

• Integrated land cover and tillage data into the Vortex (COAST)

• Updated targets as requested by MDE

• Ran the calibration

Progress Since January – Land Nutrients

• Modified nutrient species targets– Labile organics < Refractory organics– Refractory (P:N) < Labile (P:N)

• Ran the calibration

TN TP

DIN OrgN Labile OrgN

Refractory OrgN

Labile OrgP

Refractory OrgP

DIPOrgP

Organic Simulation

Labile ORGN

Labile ORGP

BOD

P:N = 0.1384

Refract ORGN

Refract ORGP

RefractoryORGN

RefractoryORGP

Algae

P:N = 0.1384

DIN

DIP

0.1384

BenthicAlgae

P:N = 0.1384

DIN

DIP

0.13

84

0.13

84

Median Observed ORGN:ORGP ratio is 0.056

Progress Since JanuaryRiver Water Quality

• Derived and used subgrid transport factors– (convert EOF to EOS)

• Extended calibration to 2005

• Ran calibration

Hydrology Recalibration with Validation

• Differences from previous hydrology– Through 2005 rather than 1999– New land use, rainfall, . . .

• Two Scenarios– Calibrate using all data– Calibrate using first and last 40% of Data– Check Validation for Both

1985-2005 Hydro Efficiency - Calibrated with all data

0

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1985-2005 Hydro efficiency - calibrated with first and last 40% data

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-0.0

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Slight decrease in efficiency

Efficiency of Validation Data (middle 20%) - Calibrated using first and last 40% of data (1985-2005)

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Validation better than Calibration

1985-2005 Hydro Efficiency - Calibrated with all data

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s t

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.25

-0.0

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Efficiency of Validation Data (middle 20%) - Calibrated using all data (1985-2005)

0

5

10

15

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les

s t

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-0.8

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.75

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.25

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Validation period better than total period

Efficiency of Validation Data (middle 20%) - Calibrated using first and last 40% of data (1985-2005)

0

10

20

30

40

50

les

s t

ha

n -

1

-0.8

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.75

-0.5

5 t

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-0.3

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.25

-0.0

5 t

o 0

0.2

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0.4

5 t

o 0

.5

0.7

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0.9

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o 1

Validation about the same either for either calibration

Observations

• The calibration and the validation are slightly better using all data rather than the first and last 40%

• In both cases the agreement with the validation data set (middle 20%) is better than the calibration

Model Validation

• It has been shown that the hydrology model and calibration procedure can be adequately validated

• Questions:– Should we use the best calibration or the

validated calibration?– Should we do the same thing for water

quality?

The Effect of Different Averaging Periods

The Way to Test

• Well Calibrated Model– Used January Version

• Use 1985 conditions throughout– Used Time-Varying conditions

• Use results to get bounds on effects of hydrology on allocation decisions

Average Change Between 10-year Periods (TN)

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

PA VA MD NY DC WV DE Total

Average Change Between 10-year Periods (TP)

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

PA VA MD NY DC WV DE Total

Average Change Between 10-year Periods (TSS)

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

PA VA MD NY DC WV DE Total

Averaging Period

• Relatively small changes due to averaging period

• Real results (well calibrated model, constant scenario) will be presented to the Water Quality Steering Committee