Team 10 Presentation Vol. II 18th February 2011 Sophia Antipolis, France
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Team 10 Presentation Vol. II 18th February 2011 Sophia Antipolis, France Improvement by calibration or with geometry?
description
Team 10 Presentation Vol. II 18th February 2011 Sophia Antipolis, France. Improvement by calibration or with geometry?. Introduction. Hydrological Analysis Spatial rainfall distribution Relation between rain gauges HEC-HMS Model Setup - Methods and Parameters Output HEC-RAS Setup - PowerPoint PPT Presentation
Transcript of Team 10 Presentation Vol. II 18th February 2011 Sophia Antipolis, France
Team 10 Presentation Vol. II
18th February 2011Sophia Antipolis, France
Improvement by calibration or with geometry?
IntroductionHydrological AnalysisSpatial rainfall distribution
Relation between rain gaugesHEC-HMS
Model Setup - Methods and ParametersOutput
HEC-RAS Setup
MIKE 11 Setup
MIKE SHESetup and Parameters
CalibrationGeometry
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Hydrological AnalysisThiessen PolygonWhy no interpolation?
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Carros
Roquesteron Levens
Guillaumes
Puget Théniers
St MartinVésubie
Hydrological AnalysisThiessen Polygon
Table: partial contribution of gages on the subcatchments Strongest influence St. Martin Vesubie Smallest influence Roquesteron
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Hydrological Analysis
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Hydrological Analysis
Correlation between the stations A strong correlation between the ones that are close to each other
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Carros
Roquesteron Levens
Guillaumes
Puget Théniers
St MartinVésubie
Carros Levens RoquesteronPuget
ThéniersGuillaumes
St Martin Vésubie
Carros 1.00
Levens 0.60 1.00
Roquesteron 0.73 0.63 1.00
Puget Théniers 0.65 0.67 0.88 1.00
Guillaumes 0.70 0.62 0.76 0.84 1.00
St Martin Vésubie 0.51 0.80 0.58 0.84 0.64 1.00
Hydrological AnalysisCorrelation of Rainfall and Elevation
Weak correlation distance between rain gauges, rainfall caused by frontal depression
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Hydrological Analysis – HEC HMS Model
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HEC HMS SETUP
Transformation Method: Clark UHSimple, Fast, Risky!
Loss Method: SCS Curve NumberGood Approximations, Simple, Risky too!
Routing: MuskingumEvent, Lumped, Empirical
Baseflowmodel: Constant MonthlyAveraged time series data
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Lumped Model Setup – FinishedDistributed Model setup – Not Ready Jet (Difficult Grid Generation)
Lumped (Semi-distributed)
Parameter Setup
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Catchment Upper Var Tinee Vesubie Esteron Lower VarArea [m²] 1090215000.00 747483750.00 393536250.00 450860625.00 151509375.00Area [km²] 1090.22 747.48 393.54 450.86 151.51LongestFlowpath 87893.04 71481.75 48448.22 62249.59 37357.69Slope 0.03 0.04 0.06 0.03 0.03CN [land use] 66.00 66.00 66.00 67.00 68.00CN [wet soil] 82.00 82.00 82.00 83.00 83.00S max retention coeff 57.00 55.00 56.00 54.00 51.00Tc [h] KIRPICH 8.02 6.13 3.88 6.15 4.15Tc Ventura 24.21 17.36 10.29 15.57 9.03Tc Ventur 50% 12.11 8.68 5.14 7.78 4.51Storage Coeffi cent 15.00 10.00 3.00 3.00 4.00Impervious 0.30 0.60 0.20 0.50 9.00
Sensitivity
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Sensitivity
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HEC RAS Goal : comparison with Mike11 data obtained. Realized :
Install network Create cross-sections Integrate Hydrological results
Problems met: To run the unsteady simulation To install the weirs
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Total Length : Approx. 24 Km
Branches: 10
Weirs : 9
X-sec: 120
River Network of Lower Var:Q
:WL
Model Inputs Network X-section Weir formula: Weir formula 2 (Honma) Hydrodynamic Parameter
Resistance : roughness coefficient Initial Condition :
Water Depth (1m) and Discharge (10 cumec)
Boundary Condition: Upstream Bnd: Q from hydrological analysis Downstream: WL
Simulation Mode: Unsteady Simulation Period: 05/11/1994 to 6/11/1994
Model Output: Maximum Longitudinal Water Profile
MIKE SHESetup and parameters
Strickler coefficient Extreme values
Net effective rainfall
What is the effect of changing these valueson the hydrograph?
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MIKE SHE – Strickler coeffieient
Strickler coeffieient – numerical representation of the catchment and river bed roughness
Extreme values of Strickler coeffieient used
10 – flood plain covered
in trees 60 – tarmac
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Strickler coefficient
0
1000
2000
3000
4000
5000
0:00 6:00 12:00 18:00 0:00Time
Disc
harg
e m
3/s
30/20 (default) 10 60
MIKE SHE – Net Effective Rainfall
Proportion of rainfall that forms runoff Losses due to infiltration
Reduction in hydrograph peaks
with decreasing net effective rainfall
Less runoff volume represented
by the area under the hydrograph
0.9 is a suitable value due to
antecedent catchment conditions
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MIKE SHE – Parameter Calibration
Parameters make little difference to the simulation.
In this case calibration is not required and can be detrimental to the model results
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...and the geometry
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Grid resolution
1000m grid – 2 820 data points
600m grid – 7833 data points
300m grid – 31 333 data points
75m grid – 50 133 321 data points
Event of 5 November 1994 modelled using a DEM with a resolution of 300 mfor a river geometry based on 300 m (Model 300a) and 75 m (Model 300d)DEM resolutions. The time is counted from 0000 hours on 5 November 1994.(Guinot, V. And Gourbesville P. 2003)
Resolution is important!!!
Thank You For Your Attention
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ReferencesGuinot, V. and Gourbesville, P. (2003). Calibration of physically
based models: back to basics? Journal of Hydroinformatics, 5(4): 233-244
