systematic testing of parameterizations to account for land cover changes in the gr4j model

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Systematic testing of parameterizations to account for land cover changes in the GR4J model. Vazken Andréassian Hydrosystems and Bioprocesses Research Unit, Irstea, Antony, France. Introduction. This presentation: - PowerPoint PPT Presentation

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1

Systematic testing of parameterizations

to account for land cover changes in the GR4J model

Vazken Andréassian

Hydrosystems and Bioprocesses Research Unit, Irstea, Antony, France

Introduction

This presentation:

• is based on data made available for the workshop (3 forested/deforested catchments + 2 urbanizing catchments)

• uses as example a single rainfall-runoff model (GR4J)

2

Forest hydrology experiments

Dealing with changes within a conceptual model

• Models are simplification of the physical reality

Cou

rtes

y of

Ste

n B

ergs

tröm

, SM

HI

Dealing with changes within a conceptual model

• Dealing with changing catchments is difficult with any model, but:

– within a physically-faithful model representation, the solution to account for the change is imposed

– within a conceptual model, the solution is not imposed, several possibilities exist

Dealing with changes within GR4J

Calibration strategy

• First calibrate a ‘central parameter set’ on the entire time series ( )

• Allow only one parameter to vary on each successive sub-periods (recalibration)

centralcentralcentralcentral4321 ,,,

Questions asked

• Is there a solution better than the others?

• Can the variations of the recalibrated parameter be correlated to land use?

Results (Fernow deforested catchment)

-100

-80

-60

-40

-20

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Calibration Period

Mod

el e

ffici

en

cy (

KG

E)

average of the sub-periods calibration efficiency

calibration efficiency for each sub-period

Results (Fernow deforested catchment)

-100

-80

-60

-40

-20

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Calibration Period

Mod

el e

ffici

en

cy (

KG

E)

conversion to conifers

deforestation

Results

-100

-80

-60

-40

-20

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Calibration Period

Mod

el e

ffici

en

cy (

KG

E)

ReferenceX1 recalibrated

Results

-100

-80

-60

-40

-20

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Calibration Period

Mod

el e

ffici

en

cy (

KG

E)

ReferenceX2 recalibrated

Results

-100

-80

-60

-40

-20

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Calibration Period

Mod

el e

ffici

en

cy (

KG

E)

ReferenceX3 calibrated

Results

-100

-80

-60

-40

-20

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Calibration Period

Mod

el e

ffici

en

cy (

KG

E)

ReferenceX4 recalibrated

Parameter values evolution for the Fernow WS6 catchment

Recalibrated parameter

Ref X1 X2 X3 X4

Deforested / reforested catchments

Fernow WS6 (cut & replanted with pines)

38.1 56.2 72.2 76.4 39.4

Rimbaud(forest fire)

74.1 85.3 86.2 82.2 80.3

Mörrumsån River at Lissbro(tree destruction by a storm)

80.2 85.8 87.7 90.0 81.6

Urbanized catchments

Ferson creek 65.5 79.4 83.6 80.0 70.6

Blackberry creek 70.4 79.3 80.5 76.5 72.0

Parameter correlation on urbanizing catchments (Blackberry)

Parameter correlation on urbanizing catchments (Ferson)

Conclusion

• A diagnostic which– opens the way towards a parameterization of land-

use changes

– remains (necessarily) model-specific

Limits

• More case studies are needed for more general results

• Be careful with parameter interactions within the model

Thank you

Forest hydrology

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