G. Thirel, L. Coron, V. Andréassian, C. Perrin

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Presentation transcript:

G. Thirel, L. Coron, V. Andréassian, C. Perrin Application of several hydrological models (and objective functions) to the complete dataset of the workshop G. Thirel, L. Coron, V. Andréassian, C. Perrin 22 July 2013

Introduction What is the main issue when we fail on non-stationarity? Models? Objective functions? Something else? Application of 3 models Application of 6 objective functions IAHS Hw15 22 July 2013

Outline of this presentation Impact of using different models The models The results Impact of using different objective functions The objective functions IAHS Hw15 22 July 2013

Outline of this presentation Impact of using different models The models The results Impact of using different objective functions The objective functions IAHS Hw15 22 July 2013

GR4J and GR5J Lumped conceptual models, resp. 4 and 5 parameters GR4J IAHS Hw15 22 July 2013

MORDOR6 Lumped conceptual model with 6 parameters (simplification of the MORDOR model). IAHS Hw15 22 July 2013

The snow module No snow module: Axe Creek, Gilbert, Flinders, Wimmera and Bani Rivers. CemaNeige: all the other basins. CemaNeige = degree-day model, 2 free parameters. IAHS Hw15 22 July 2013

The objective function The Nash on root square of discharge is used in this part. IAHS Hw15 22 July 2013

Outline of this presentation Impact of using different models The models The results Impact of using different objective functions The objective functions IAHS Hw15 22 July 2013

Rivers with T increase High flows IAHS Hw15 GR4J and GR5J are the best for the Kamp, except during P2 No big difference for the Garonne 22 July 2013

Rivers with T increase MORDOR6 misses the 2002 Kamp flood Observed peak value MORDOR6 peak values IAHS Hw15 22 July 2013

Rivers with T increase Low flows GR5J the best for the Kamp IAHS Hw15 GR5J the best for the Kamp MORDOR6 and GR5J the best for the Garonne 22 July 2013

Rivers with T increase Variability due to model and calibration choices GR4J GR5J Kamp MORDOR6 IAHS Hw15 22 July 2013 The model choice and calibration induce the same order of variability

Rivers with discharge change or high variability Best performance for GR5J Wimmera High flows IAHS Hw15 22 July 2013

Rivers with discharge change or high variability No model has the « solution » for handling the Millenium Drought Wimmera IAHS Hw15 22 July 2013

Rivers with T increase Variability due to model and calibration choices GR4J GR5J Wimmera MORDOR6 IAHS Hw15 22 July 2013 The model choice and calibration induce the same order of variability

Rivers with discharge change or high variability Severe crash from GR4J due to high reactivity Attempts to increase the reaction time or to better initialize the parameters all failed The structure of GR4J (&GR5J) is to revise for such a basin Bani GR4J IAHS Hw15 22 July 2013 MORDOR6

Outline of this presentation Impact of using different models The models The results Impact of using different objective functions The objective functions IAHS Hw15 22 July 2013

The objective functions For this part only the gr4j model is used Inverse of discharge Square root of discharge Discharge Nash NaIQ NaRQ NaQ KGE KGEIQ KGERQ KGEQ IAHS Hw15 22 July 2013

Outline of this presentation Impact of using different models The models The results Impact of using different objective functions The objective functions IAHS Hw15 22 July 2013

Rivers with T increase Calibrating on IQ gives the lowest Nash(Q) -> of course! IAHS Hw15 22 July 2013

Rivers with T increase Calibrating on Q gives the lowest Nash(IQ) -> of course! IAHS Hw15 22 July 2013

Rivers with P decrease Kamp Variability due to calibration and Objective function choices NaQ NaRQ NaIQ KGEQ KGERQ KGEIQ IAHS Hw15 The objective functions impact the model bias more than the model choice 22 July 2013

Rivers with discharge change or high variability Only NaRQ does not show disastrous results on P5 when calibrated on wet period. KGERQ performs the best on wet periods when calibrated on P5. Wimmera IAHS Hw15 22 July 2013 Prod. Store: NaRQ > KGERQ Loss for P5: KGERQ > NaRQ

Rivers with P decrease Wimmera Variability due to calibration and Objective function choices NaQ NaRQ NaIQ KGEQ KGERQ KGEIQ IAHS Hw15 The objective functions strongly impact the model bias 22 July 2013

Conclusions Attempts to quantify the (un-)stability induced by : The model choice –> low impact The calibration period -> low impact on variability, high impact on bias The objective function -> huge impact IAHS Hw15 22 July 2013

Thank you!