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 MIKE 11 Setup MIKE SHE Setup and Parameters Calibration Geometry 02/18/20112

Hydrological Analysis Thiessen Polygon Why no interpolation? 02/18/20113

Hydrological Analysis Thiessen Polygon Table: partial contribution of gages on the subcatchments Strongest influence  St. Martin Vesubie Smallest influence  Roquesteron 02/18/20114

Hydrological Analysis 02/18/20115

Hydrological Analysis Correlation between the stations A strong correlation between the ones that are close to each other 02/18/20116 CarrosLevensRoquesteron Puget Th é niers Guillaumes St Martin V é subie Carros 1.00 Levens Roquesteron Puget Th é niers Guillaumes St Martin V é subie

Hydrological Analysis Correlation of Rainfall and Elevation Weak correlation  distance between rain gauges, rainfall caused by frontal depression 02/18/20117

Hydrological Analysis – HEC HMS Model 02/18/20118

HEC HMS SETUP Transformation Method: Clark UH Simple, Fast, Risky! Loss Method: SCS Curve Number Good Approximations, Simple, Risky too! Routing: Muskingum Event, Lumped, Empirical Baseflowmodel: Constant Monthly Averaged time series data 02/18/20119 Lumped Model Setup – Finished Distributed Model setup – Not Ready Jet (Difficult Grid Generation) Lumped (Semi-distributed) 

Parameter Setup 02/18/201110

Sensitivity 02/18/201111

Sensitivity 02/18/201112

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 02/18/201113

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 SHE Setup and parameters Strickler coefficient Extreme values Net effective rainfall What is the effect of changing these values on the hydrograph? 02/18/201117

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 02/18/201118

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 02/18/201119

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 02/18/201120

...and the geometry 02/18/201121

Grid resolution 1000m grid – data points 600m grid – 7833 data points 300m grid – data points 75m grid – data points

Event of 5 November 1994 modelled using a DEM with a resolution of 300 m for 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 (Guinot, V. And Gourbesville P. 2003)

Resolution is important!!!

Thank You For Your Attention 02/18/201125

References Guinot, V. and Gourbesville, P. (2003). Calibration of physically based models: back to basics? Journal of Hydroinformatics, 5(4):