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DISTRIBUTED RAINFALL RUNOFF MODELS APPLIED TO THE DARGLE

DISTRIBUTED RAINFALL RUNOFF MODELS APPLIED TO THE DARGLE. Prof. Eng. Ezio TODINI e-mail : todini@geomin.unibo.it. Rainfall Runoff Models. Black Box M. Semi Distributed M. Distributed M. DISTRIBUTED RAINFALL-RUNOFF MODELLING. Advantages of Distributed Models

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DISTRIBUTED RAINFALL RUNOFF MODELS APPLIED TO THE DARGLE

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  1. DISTRIBUTED RAINFALL RUNOFF MODELS APPLIED TO THE DARGLE Prof. Eng. Ezio TODINI e-mail : todini@geomin.unibo.it

  2. Rainfall Runoff Models Black Box M. Semi Distributed M. Distributed M. DISTRIBUTED RAINFALL-RUNOFF MODELLING • Advantages of Distributed Models • Physical meaning of model parameters • Distributed representation of phenomena Limited calibration requirements Possibility of internal analysis

  3. Model 1: AFFDEF Mass Balance in each cell • Main model characteristics: • Modified CN for estimating infiltration • Radiation method for evapotranspiration • Muskingum-Cunge for ovrland and channel flow

  4. Model 2: TOPKAPI • Main model characteristics • Vertical lumping of hydraulic conductivity • Dunne infiltration • Soil horizontal flow, overland and channel flows represented using a kinematic equation • Horizontal lumping of kinematic equations Model for the single cell

  5. ODE TOPKAPI Distributed approachThe model for the single cell SOIL COMPONENT mass conservation moment conservation

  6. ODE TOPKAPI Distributed approachThe model for the single cell SURFACE COMPONENT mass conservation moment conservation …

  7. ODE TOPKAPI Distributed approachThe model for the single cell CHANNEL COMPONENT mass conservation moment conservation …

  8. TOPKAPI Distributed approachParameters

  9. Model 3: MIKE SHE • Main model characteristics: • 1D Richards equations for unsaturated zone • 3D Boussinesq equation for greoundwater • Parabolic approximation for overland flow

  10. Case study The Dargle Republic of Eireland County of Wicklow

  11. Case study • - Surface Area circa 122 km2 • Elevation from 20 m to 713 m a.s.l. • Sandy and sandy loam for about • 1.5 m

  12. Dunne Saturation mechanism Horton The “unrealistic” profile used in MIKE SHE to meet the observations

  13. Efficiency Coefficients Variance of obs. = 17.85 Variance of errors= 6.97 Nash Sutcliffe= 0.59 Explained Variance= 0.61 Coefficient of correlation =0.91 Volume Control = 0.74 Willmott= 0.93 Results: AFFDEF

  14. Efficiency Coefficients Variance of obs. = 17.85 Variance of errors= 6.97 Nash Sutcliffe= 0.59 Explained Variance= 0.61 Coefficient of correlation =0.91 Volume Control = 0.74 Willmott= 0.93 5 [Km2 ] Areal threshold Risults: AFFDEF Average computer time = 5 min 0.01 [ms-1] Saturated Hydraulic Conductivity Infiltration Res. Const 4320000[s] Infiltration constant 0.7 Infiltration Capacity 0.1 Uniform value for curve number: 20

  15. Efficiency Coefficients Variance of obs. = 17.85 Variance of errors= 4.01 Nash Sutcliffe= 0.77 Explained Variance= 0.77 Coefficient of correlation =0.91 Volume Control = 0.90 Willmott= 0.95 Results: TOPKAPI

  16. Efficiency Coefficients Variance of obs. = 17.85 Variance of errors= 4.01 Nash Sutcliffe= 0.77 Explained Variance= 0.77 Coefficient of correlation =0.91 Volume Control = 0.90 Willmott= 0.95 Results: TOPKAPI Average comp. time = 5 min

  17. Efficiency Coefficients Variance of obs. = 17.85 Variance of errors= 8.32 Nash Sutcliffe= 0.52 Explained Variance= 0.54 Coefficient of correlation =0.85 Volume Control = 0.80 Willmott= 0.90 Results: MIKE SHE

  18. Efficiency Coefficients Variance of obs. = 17.85 Variance of errors= 8.32 Nash Sutcliffe= 0.52 Explained Variance= 0.54 Coefficient of correlation =0.85 Volume Control = 0.80 Willmott= 0.90 Results: MIKE SHE Average computer time = 2.5 h

  19. Distributed soil moisture Saturation percentage

  20. TOPKAPI CALIBRATION TOOL

  21. Ponte Spessa Example of link ECMWF -TOPKAPI on the Po Basin The basin closed at Ponte Spessa (Surface area 36,900 km2 )

  22. The Soil Types The Land Uses The DEM

  23. Reproduction of the 1994 event in the Po river

  24. ECMWF: deterministic run

  25. ECMWF: deterministic run

  26. ECMWF: deterministic run

  27. ECMWF: deterministic run

  28. ECMWF: deterministic run

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