Hydrology Calibration

Phase 5

Calibrators

• USGS-MD– Jeff Raffensperger– Sarah Martucci– Joe Vrabel– Angelica Gutierrez– Gary Fisher

Calibrators

• USGS-VA– Doug Moyer– Alan Simpson– Jen Krstolic

• ICPRB– Ross Mandel– Julie Kiang

Calibrators

• CBP– Sara Brandt– Jing Wu– Kate Hopkins– Lewis Linker– Gary Shenk

Status

• Consistent with other HSPF calibrations in the literature

• Better and more consistent overall than phase4

• Reaching point of diminishing returns

Strategy

• Water Balance

• Stormflow / Baseflow separation

• Base Flow

• Storm Flow

• Seasonal ChangesAdapted From:

Users Manual for an Expert System (HSPEXP) forCalibration of the Hydrological SimulationProgram—Fortran

By Lumb, McCammon, and Kittle USGS-WRI Report

Statistics to judge overall calibration

• Bias

• Base / Storm separation

• Recession rates

• Model efficiency

Starting Bias

0

10

20

30

40

50

60

70

80

90

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Ending Bias

0

10

20

30

40

50

60

70

80

90

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Jan 1

March 1 Bias

0

10

20

30

40

50

60

70

80

90

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

April 1 Bias

0

10

20

30

40

50

60

70

80

90

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Baseflow / Stormflow Stat

Fraction of flow that is baseflow (simulated)

Fraction of flow that is baseflow (observed)Bstat = 1 -

baseflow / total flow (observed)Bstat = 1 - baseflow / total flow (simulated)

stormflow / total flow (observed)Qstat = 1 - stormflow / total flow (simulated)

Starting Bstat

0

10

20

30

40

50

60

70

80

90

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Ending Bstat

0

10

20

30

40

50

60

70

80

90

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Jan 1

March1 Bstat

0

10

20

30

40

50

60

70

80

90

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

April 1 Bstat

0

10

20

30

40

50

60

70

80

90

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Starting Qstat

0

10

20

30

40

50

60

70

80

90

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Ending Qstat

0

10

20

30

40

50

60

70

80

90

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Jan 1

March1 Qstat

0

10

20

30

40

50

60

70

80

90

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

April 1 Qstat

0

10

20

30

40

50

60

70

80

90

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Baseflow / Stormflow Recession Statistic

average Simulated recession index

average Observed recession indexQ rec Index = 1 -

quick flow todayAverage Recession index = Average (

quick flow tomorrow)

April 1 Average Baseflow Recession

0

20

40

60

80

100

120

140

160

180

200

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

March1 Quickflow Recession Index

0

10

20

30

40

50

60

70

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

April 1 Quickflow Recession Index

0

10

20

30

40

50

60

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Nash – Sutcliffe Model efficiency

(variance of errors)

(variance of observed)

Computed for daily, log of daily,

and monthly values.

1 -

Reported values of N-S efficiency

• Often reported, but little information on ‘standards’ of efficiency

• Reported daily efficiencies 0.5 - 0.75

• Reported daily log efficiencies 0.5 - 0.75

• Reported monthly efficiencies 0.7 – 0.8

Starting Efficiency

0

5

10

15

20

25

30

35

40

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Efficiency after bias adjustment

0

5

10

15

20

25

30

35

40

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Efficiency after Storm/Base Adjustment

0

5

10

15

20

25

30

35

40

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Efficiency after New Diversions

0

5

10

15

20

25

30

35

40

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Efficiency as of March 1

0

5

10

15

20

25

30

35

40

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Efficiency as of April 1

0

5

10

15

20

25

30

35

40

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Reported values of N-S efficiency

• Often reported, but little information on ‘standards’ of efficiency

• Reported daily efficiencies 0.5 - 0.75

• Reported daily log efficiencies 0.5 - 0.75

• Reported Monthly efficiencies 0.7 – 0.8

Starting Efficiency of Logs

0

5

10

15

20

25

30

35

40

45

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Efficiency of Logs after bias adjustment

0

5

10

15

20

25

30

35

40

45

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Efficiency of Logs after Storm/Base Adjustment

0

5

10

15

20

25

30

35

40

45

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Efficiency of Logs with New Diversions

0

5

10

15

20

25

30

35

40

45

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Efficiency of Logs as of March 1

0

5

10

15

20

25

30

35

40

45

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Efficiency of Logs as of April 1

0

5

10

15

20

25

30

35

40

45

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Reported values of N-S efficiency

• Often reported, but little information on ‘standards’ of efficiency

• Reported daily efficiencies 0.5 - 0.75

• Reported daily log efficiencies 0.5 - 0.75

• Reported Monthly efficiencies 0.7 – 0.8

Efficiency of Monthly Flow with new diversions

0

10

20

30

40

50

60

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Efficiency of Monthly Flow as of March 1

0

10

20

30

40

50

60

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Efficiency of Monthly Flow as of Apr 1

0

10

20

30

40

50

60

-103% -83% -63% -43% -23% -3% 18% 38% 58% 78% 98%

Parameter Values

INFILT AGWR INTFW IRC AGWETPmin 0.009 0.867 0.5 0.12 0.0010th 0.041 0.954 1.0 0.25 0.0025th 0.045 0.965 1.0 0.30 0.01median 0.072 0.974 1.0 0.38 0.0575th 0.117 0.979 2.5 0.46 0.0590th 0.176 0.983 3.5 0.60 0.05max 0.337 0.995 5.0 0.85 0.12

Where are we in relation to p4

• Better overall

• More consistent parameterization

• Calibrated at many more sites

Phase 5 vs Phase 4 Efficiencies

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

-0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Phase 4

Pha

se 5

Phase 5 vs Phase 4 Log Efficiencies

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.4 0.5 0.6 0.7 0.8 0.9

Phase 4

Pha

se 5

Status

• Consistent with other HSPF calibrations in the literature

• Better and more consistent overall than phase4

• Reaching point of diminishing returns

• Still a few small areas and issues that need attention in hydrology

Ready for Sediment?

• River calibration cannot change significantly

• Land calibration must have significant surface runoff

percent of days with surface runoffmin 26%10th 28%25th 30%median 32%75th 35%90th 38%max 48%

Work Plan

• Hydrology Group ( 2/3 of group )– Consistent parameterization– Better reservoirs– Data Issues– Local hydrology issues

• Sediment Group ( 1/3 of group )– Begin land and river sediment calibration

Sediment Calibration

• Land– Long-term average washoff calibrated to NRI

by county

• River– Calibrated to in-stream data– About 80 stations

Land Sediment Simulation

Detached Sediment

Att

achm

ent

= k3 * (Detached sediment)

= X lb/day

Input

storage

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0 50 100 150 200

j1= k1*RO (RO + Storage)

Land Sediment Simulation

Detached Sediment

Soil Matrix(unlimited)

Wash off

Det

achm

ent

= (1-cover) * k2 (Rain)j2

Land Sediment Simulation

Detached Sediment

Soil Matrix(unlimited)

Wash off

Det

achm

ent

= (1-cover) * k2 (Rain)j2

j1= k1*RO (RO + Storage)

critz

w

eMass

1

1

River Cohesive Sediment Simulation

SuspendedSediment

Bed Storage(unlimited)

Outflow

Sco

ur

Dep

osit

ion

Inflow

1*

crit

AreaM