towards an hydrological qualification of the simulated rainfall in mountainous areas
DESCRIPTION
Towards an Hydrological Qualification of the Simulated Rainfall in Mountainous Areas. Eddy Yates, Sandrine Anquetin, Jean-Dominique Creutin Laboratoire d’étude des Transferts en Hydrologie et Environnement, Grenoble, France. Introduction MethodResultsConclusions. 300 mm 9 h. - PowerPoint PPT PresentationTRANSCRIPT
Towards an Hydrological Qualification of the Simulated Rainfall
in Mountainous Areas
Eddy Yates, Sandrine Anquetin, Jean-Dominique Creutin
Laboratoire d’étude des Transferts en Hydrologie et Environnement, Grenoble, France
Cévennes-Vivarais : a region prone to flash floods
• Objective : forecast of these flash floods.
• We focus here on the precipitation forecast.
Introduction Method Results Conclusions
• Watersheds– 100 to 1000 km2
– specific outflows of up to 5 m3s-1km-2
• Storms– 300-400 mm in 6-12 h. over some
100s km2
HYDRAM Water depth seen by the Nîmes radar (Météo-France)October 6, 2001 Vidourle, October 6 – 7, 2001
Q~ 100 Q mean
300 mm9 h
Hilly region between the Mediterranean sea and the Massif Central. Rainy autumns.
Precipitation forecast model
We use Meso-NH (Météo-France, CNRS) : a meso-scale non-hydrostatic model a nested configuration. The finest grid has a
2.5 km resolution which allows an explicit resolution of the convection
Introduction Method Results Conclusions
Reference observed rain fields
We use kriging : an exact interpolator it takes into account the statistical structure
of the rain-gauge data it gives an estimation of the reliability of the
interpolation (estimation variance)
Simulation and observation are observed for 1h and 11h cumulated rainfall.
Introduction Method Results Conclusions
Cases studied
Two simulations with very different qualities.
The point is : “how much better” is the better simulation ? is it better for hydrological purposes too ?
Introduction Method Results Conclusions
1995 : Gardon d’Anduze 2001 : Vidourle
Bad localisation Not enough precipitation simulated (maximum cumulated rainfall
of 160 mm vs. 260 mm)
Observations Simulation
2001
Observations SimulationQuite a good localisation
Not enough precipitation simulated (maximum cumulated rainfall of 100 mm vs. 170 mm)
1995
MethodIntroduction Method Results Conclusions
MethodIntroduction Method Results Conclusions
R²(area)
R²(area)
Observation
Forecast
MethodIntroduction Method Results Conclusions
0
0,1
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10 100 1000 10000
Area (km²)
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Area (km²)
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estimation error limit
point to point correlation limit
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Area (km²)
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Evolution of the correlation with the area
Introduction Method Results Conclusions
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1995 2001
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Area (km²)
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1995 11 h cumulated rainfall
Lower short-range accuracy for short time accumulation
1995 1 h cumulated rainfall
Limits of the methodIntroduction Method Results Conclusions
1
10
100
1000
10000
100000
10 100 1000 10000
Area (km²)
# pe
r cla
ss
1
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Area (km²)
# p
er c
lass
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# p
er c
lass
2001 1995
Conclusions, perspectives
• The method can discriminate good forecasts from very bad forecasts
• We need other cases to test the method• The method must be tested with distributed data
too (radars)• Next step : use of TOPODYN (LTHE), a
hydrologic model from the TOPMODEL family. It considers several scales of the watersheds.
Introduction Method Results Conclusions
Thank you