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Contents Interpolated Rainfall :« simple to complexe » methods

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Presentation on theme: "Contents Interpolated Rainfall :« simple to complexe » methods"— Presentation transcript:

1 Analysis of the relative contributions -(hydrographs) of the sub-catchments during the flood

2 Contents Interpolated Rainfall :« simple to complexe » methods
Hydrographs calculation SCS Method Calibration of MIKE SHE for the VAR catchments Parameters, values, graphs Contribution analysis during the flood Calibration??? Conclusions

3 Rainfall Interpolation Methods :« simple to complexe »
Homogeneous Rainfall on the sub-catchment Thiessen Method Kriging Method Homogeneous Rainfall on the sub-catchment Hypothesis : Spatial distribution of the rainfall are the same on the all catchment => mean of the six rain gauges station

4 Rainfall Interpolation Methods :« simple to complexe »
Thiessen Method Estimating rainfall weighted taking into account each station. Thiessen Polygon (ARCGIS) Tinée Upper Var Vésubie Down Var Esteron Carros 64 8 Levens 6 2 22 36 7 Roquesteron 46 Puget Théniers 38 39 Guillaumes 48 53 St Martin de Vésubie 47 78 Assigning to each station an influence area (%) that represents weighting factor. To calculate the interpolated rain : ∑ rainfall for each station x weighting factor Total area conerning

5 Rainfall Interpolation Methods :« simple to complex »
Kriging Method Interpolation by kriging for each sub-catchment and for each hour

6 Hydrographs calculation
SCS Method (Soil Conservation Service) Hypothesis 1: Infiltration capacity tends to zero as time increases. Hypothesis 2: Runoff appear after it dropped some rainfall. Hypothesis 3: R (t) = [ si Pu (t) > 0 ] Cumulated Water Finish Time Time SCS Parameters: S: Maximum infiltration capacity, depend on Soil characteristics, cover, condition of initial wetting. Tinée Upper Var Vésubie Down Var Esteron SCS Value 85 30 80 Tm: Time of the peak discharge, base on Concentration Time ( Tm = 3/8 Tc). Tc: Concentration Time, calculate with PASSINI Method (take in account: Surface, Slope and Longest Flow Path). Area (km²) : Surface of each sub-catchment.

7 Hydrographs calculation
Almost no big differences appear between the rainfall distribution results from the Thiessen and the homogeneous method The discharge value are globally in accord with calculate value in the Napoleon Bridge Except for Surfer method. Doesn’t take in account the different landuse, the slope or the topography. With more than we could obtain better result including topography in Surfer. Homogeneous discharge is more important than the Thiessen value. Due to Thiessen method take in account spatial reference of the station. SCS Result:

8 Hydrographs calculation
SCS Result: Discharge (m3/s) Contributions of the sub-catchments during the flood (%) Tm (hours) Tinee 1177,8 28 8 Vésubie 869,1 20 5 UpperVar 1204 12 DownVAr 336 4 Estéron 689 16 Tinee hydrograph

9 Calibration of MIKE SHE
First calibration-using only MIKE SHE Using: 300 m grid size Experiences : very little peak of runoff the width of the imagined river bed is 1500 m Reasons: big grid size too big width of river bed, big hydraulic radius and little water depth little velocity and discharge Conclusion: we have to use river network for modelling coupling with MIKE11

10 Calibration of MIKE SHE and coupling with MIKE 11
Parameters: IWD - Initial Water depth 0,00-0,005 DS – Detention storage 0,00-0,05 Manning number (overland)10,0-40,0 Net Rainfall Fraction 0,90-0,95

11 Calibration of MIKE SHE and coupling with MIKE 11
Parameters of the best calibration: M=24 m1/3/s NRF=0.93 IWD = m DS= 0.00 mm Results of calibration: Peak of discharge Qc= 3701 m3/s Qm= 3680m3/s Wrong time of the peak hours differences sensitivity analysis not sensitive M,IWD,NRF little sensitive DS Conclusions: We can’t calibrate more accurately under these conditions (300 grid size) and It’s not necessery because there are not observed data!

12 Contributions analysis
The runoff’s peak and timing depends on the following parameters: Shape of the catchment Landuse surface roughness Topography Rainfall, Area Var sub-catchments: same Landuse more than 90% forest and natural area except Down Var sub-catchment similar topography Differences: rainfall, area, shape of the sub-catchments

13 Contributions analysis
Similar runoff characteristic on every sub-catchment Relative contributions of runoff: Q%=∑Q/Qi A%=∑A/Ai Esteron:20% c= Q%/A%=128% Vesubie:8% c=57% Tineé: % c=120% Upper Var: 36% c=93% Down Var: 4% c=74%

14 Calibration ??? Similar runoff characteristic on every sub-catchment
Relative contributions of runoff: Esteron:21% Vesubie:5% Tineé: % Upper Var: 36,5% Down Var: 1,5%

15 Calibration ???

16 Conclusions CONCLUSIONS OF MIKE PART:
The relative contribution of sub-catchments only depends on the distribution of rainfall. The Tinee, Upper Var, Esteron gave more than 90% of the whole runoff. CONCLUSIONS OF MIKE PART: If we calculate the relative contributions of the sub-catchments (during the flood), we don’t need to use calibrated modell, because the relative contribution is not sensitive for the calibrated parameters.

17 Thank for your attention
Team Six...


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