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2010-2011 TEAM. Interest of distributed hydrological models ( Mike SHE & H EC-HMS ). 1 st Topic Presentation , Friday 18 th February 2011 Polytech’Nice - Sophia . Different types of models. Definition. 1) lumped = complete basin as single homogeneous - PowerPoint PPT Presentation
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2010-2011TEAM
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
INTEREST OF DISTRIBUTED
HYDROLOGICAL MODELS(Mike SHE & HEC-HMS)
22
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-Shecomparison
Conclusion
HEC-HMScomparison
1) lumped = complete basin as single homogeneouselement with average rainfall input
2) quasi-distributed = discretization of watershed into homogeneous sub-basins with single rainfall parameters based on topography 3) distributed = physically based, division into elementary unit areas as grid cells, solving equations in each cell
Different types of models
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• much simpler than deterministic models
• obtained by aggregating or averaging the spatially variable processes
• usually not done in a formal mathematical manner
• rather, some simple assumptions are made which invariably start with continuity equation
• can’t be used for longer simulation periods considering groundwater infiltration and flow
Model type - lumped
3
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-Shecomparison
Conclusion
HEC-HMScomparison
4
•hydrological phenomena vary spatially and temporally
• in accordance with the conservation laws of mass, energy and momentum
• models based on conservation laws are physically-based
• laws expressed as partial differential equations (PDEs)
• solutions of PDEs on finite differences or finite element grid computationally demanding
Model type - distributed
4
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-Shecomparison
Conclusion
HEC-HMScomparison
5
Loss Methods Categorization
Initial and constant rate
Event, lumped, empirical, fitted parameter
SCS Curve Number (CN)
Event, lumped, empirical, fitted parameter
Gridded SCS CN Event, distributed, empirical, fitted parameter
Green and Ampt Event, distributed, empirical, fitted parameter
Deficit and Constant Event, lumped, empirical, fitted parameter
Transform Methods Categorization
User-specified unit Event, lumped, empirical, fitted parameter
Hydrograph (UH) Event, lumped, empirical, fitted parameter
Clark’s UH Event, lumped, empirical, fitted parameter
ModClark Event, distributed, empirical, fitted parameter
Kinematic Wave Event, lumped, empirical, fitted parameter
Methods Categorization
Baseflow Lumped
Channel Flow Routing
Lumped
HEC-HMSmainly lumped
modelsExample of method’s
categorization:
5
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-Shecomparison
Conclusion
HEC-HMScomparison
66
Fully Lumped Model based on mean value
Quasi Distributed ExampleUsing new Rainfall distribution based on Kriging
method for each sub-catchments
Distributed Model Inconvenient: Take time to build a model based
on gridded file (.dss)Advantage: Good for long time computation
window
HEC-HMS
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-Shecomparison
Conclusion
HEC-HMScomparison
7
HEC-HMSFully Lumped Model Vs Lumped Model
Required parameters:
SCS Unit Hydrograph
SCS CNPercent
Impervious (%)
Initial Abstraction
(mm)Tc (hr)
Storage Coeff. (hr)
Lag Time (min)
77 5,3 15,17 28,934 0,500 578,678 - -75 5,22 16,93 21,459 0,400 429,174 - -70 5,46 21,77 13,323 0,400 266,465 - -75 5,31 16,93 19,364 0,400 387,276 - -80 14,6 12,70 19,885 0,800 397,704 - -
75,40 7,18 16,70 20,59 0,50 411,86- - - - - 0,9 0,4- - - - - 0,7 0,2- - - - - 1,2 0,1- - - - - 0,9 0,3
Hydrologic Elements
Runoff volume Parameters Direct Runoff Parameters Channel Flow SCS Curve Number Clark Unit Hydrograph
Muskingum K (hr)
Muskingum X
Upper Var
Esteron
Fully Lumped Model
Vesubie
Lower Var
Fully Lumped Model
Reach1Reach2Reach3
Tinee
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1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-Shecomparison
Conclusion
HEC-HMScomparison
8
0
500
1000
1500
2000
2500
3000
3500
4000
Observed hydrograph (cm/s)
SCS Unit Hydrograph (cm/s)
SCS fully Lumped (cm/s)
SCS Unit Hydrograph
(cm/s)
SCS fully Lumped (cm/s)
Observed hydrograph (cm/s)
Total Residual SCS U H
Total Residual SCS fully Lumped
Peak Outflow (cm/s) 3585,8 3411,4 3680 94,20 268,60Time of peak flow (h) 5/11/94 21:00 5/11/94 21:00 5/11/94 18:00 3h 3hVolume (mm) 94,43 67,61 91,56 -2,87 23,95
Fully Lumped Vs Lumped Model
8
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-Shecomparison
Conclusion
HEC-HMScomparison
Rainfall Distribution: Thiessen Polygons
Lumped : assign 1 rainfall value for 1 polygon.
Quasi distributed :Assign 2 rainfall values in 1 sub-basin.
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1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-Shecomparison
Conclusion
HEC-HMScomparison
Interpolation method :Best Linear Estimator Unbiased
Could be interesting to apply with :
•More point of measurements,•Taking into account the altitude,•Taking into account the distance to the sea.
Lack of data to built a variogram.
10
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-Shecomparison
Conclusion
HEC-HMScomparison
Comparison
3/11/94 0:00
4/11/94 0:00
5/11/94 0:00
6/11/94 0:00
7/11/94 0:00
8/11/94 0:00
0
500
1000
1500
2000
2500
3000
3500
4000
Comparison of the Hydrograph produced by Thiessen and Krigging distribution method
Observed Hydrograph
SCS Unit Hydrograph with Thiessen Poly-gons
SCS Unit Hydrograph with Kriging Method
date / hours
Discharge (m3/s)
In our case of study, the rainfall distribution method= Thiessen polygons
11
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-Shecomparison
Conclusion
HEC-HMScomparison
Fully distributed.
The spatial and temporal variation of meteorological, hydrological, geological and hydrogeological data across the model area is described in gridded form for the input as well as the output from the model.
Mike SHE model
12
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-SHEcomparison
Conclusion
HEC-HMScomparison
Modelling Process
Network :
Manning MTopographyDomain
Thiessen Polygons and precipitation rates
very complex and time
consuming
13
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-SHEcomparison
Conclusion
HEC-HMScomparison
Results
0
400
800
1200
1600
2000
2400
2800
3200
3600
Disc
harg
e Q
[m³/
s]
Time
Hydrographs at Napoleon III
Mike SHE
estimated
Mike SHE Tutorial
14
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-SHEcomparison
Conclusion
HEC-HMScomparison
Results• Mike SHE hydrograph doesn’t match observed/estimated discharge rates and peak time at Napoleon III - bridge
• although model is set up more precisely is doesn’t give more accurate results than lumped models
• Manning coefficients M can be adjusted, however no big influence is expected
• most likely destroyed sills/structures during the flood event responsible for “time-shifting”
15
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-SHEcomparison
Conclusion
HEC-HMScomparison
CONCLUSION
0
400
800
1200
1600
2000
2400
2800
3200
3600
Disc
harg
e Q
[m³/
s]
Time
Hydrographs at Napoleon III
Mike SHE
estimated
Mike SHE Tutorial
HEC-HMS
16
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-SHEcomparison
Conclusion
HEC-HMScomparison
CONCLUSION
17
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Are 5 rain gauges sufficient enough to distribute the rainfall well across the catchment?
The observed/estimated discharge provided at Napoleon III Bridge is not accurate due to extrapolation of the rating curve.
There is no justification in employing a complex, spatially distributed model when a simple one will suffice. Simpler models invariably have fewer parameters and are easy to calibrate.
Definition
Rainfall distribution
methods
Mike-SHEcomparison
Conclusion
HEC-HMScomparison
Which model should we use?• purpose (resolution of prediction)
• available data (spatially and temporal varying data – soil, landuse, precipitation, temp. and other forcing variables)
• time window (the more complex the more time needed)
• scale of the project (small – homogeneous / large– inhomogeneous catchment)
• budget (computational and engineering time are expensive
18
1st Topic Presentation, Friday 18th February 2011Polytech’Nice - Sophia
Definition
Rainfall distribution
methods
Mike-SHEcomparison
Conclusion
HEC-HMScomparison
Thank you for your attention
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