1 DYNAS Workshop, 6 th -8 th December 2004, INRIA M. Esteves, G. Nord PSEM_2D DYNAS Workshop...

1

DYNAS Workshop, 6th-8th December 2004, INRIA

M. Esteves, G. NordM. Esteves, G. Nord

PSEM_2D

DYNAS Workshop

Rocquencourt 6th-8th December 2004

A process-based soil erosion model at the plot scale

2


Introduction

PRIM_2D Plot Runoff and Infiltration Model (1999)PSEM_2D Plot Soil Erosion Model (2003)

These models were designed to dynamically couple hydrological and soil

erosion processes to predict the spatial pattern of overland flow

hydraulics to predict the spatial pattern of soil erosion to be used in natural slopes conditions to consider complex rainfall events

The models work on a rainfall event basisPRIM_2D has been validated (Esteves et al., 2000, J.

Hyd.,228)

PSEM_2D model is still under evaluation (Nord and esteves, WRR, submitted)

3


Objectives

The main goals are to improve our understanding of local overland

flow hydraulics

to develop a better understanding of soil erosion processes

to bring a better description of the spatial and temporal variability of soil erosion at the plot scale

4


Description of PRIM_2D and PSEM_2D

Applications of PRIM_2D Validation of the model by comparison with observed data

Effect of the micro-topography

Effect of soil surface features pattern (crusted soils)

Applications of PSEM_2D Evaluation of the model by comparison with experimental

data

Some numerical examples to show the capabilities of the

model

As a conclusion: Future research

Presentation outline

5


Model description Model description

6


The model has three major components Overland flow (OF) is generated as infiltration excess rainfall (hortonian)

OF is routed using the depth averaged two dimensional unsteady flow equations on a finite difference grid

Rainfall and OF hydraulics are used to compute soil erosion

A single representative particle size (D50)

Model description

7


The infiltration algorithm is based on the Green and Ampt equation (1911)

f

ff hh

Z

ZKIc

is

Zθθ

If

f

ff hh

Z

ZKI cc

cf ZZ

In the case of crusted soils the profile is divided in two layers

cf ZZ f

ff hh

Z

ZKI ec

c

c

s

ce

KZ

KZZZ

K

f

f

Zf

Model description : Infiltration

8


Model description : Overland flow

Fully dynamic two dimensional unsteady flow equations (Barré de Saint-Venant)

Continuity equation:

Momentum equations:

),()()(

yxIRt

h

y

vh

x

uh

0

oxfx SSx

hg

y

uv

x

uu

t

u

0

oyfy SSy

hg

y

vv

x

vu

t

v

x direction:

y direction:

g gravitational acceleration (m.s-2)h flow depth (m)R rainfall intensity (m s -1)I rate of infiltration (m s -1)

Sox ground slope (x direction)

Soy ground slope (y direction)

Sfx friction slope (x direction)

Sfy friction slope (y direction)

u flow velocity (x direction) (m s -1)v flow velocity (y direction) (m s -1)

9


Friction is approximated using the Darcy-Weisbach equation

The Darcy-Weisbach friction factor is constant

For small depth flows (< 0.1 mm) the velocities are calculated using a kinematic wave approximation

gh

vuufS fx 8

)( 22

gh

vuvfS fy 8

)( 22

Model description : Flow resistance

x direction:

y direction:

g gravitational acceleration (m.s-2)h flow depth (m)

Sfx friction slope (x

direction)

Sfy friction slope (y

direction)u flow velocity (x direction) (m s -1)v flow velocity (y direction) (m s -1)f Darcy-Weisbach friction factor

10


Model description : soil erosion

Transport by runoff

Detachment and re-detachment by raindrop

impactDeposition

Entrainment

Detachment by runoff

Dfd < 0

Dfd > 0

Drd > 0

Tc> qs

11


A covering Layer of loose sediment (Hairsine and Rose, 1991)

ε is conceptualized as the percentage of a grid cell covered by a deposited layer of depth the median

particle diameter D50.

Therefore ε is calculated as:

Model description: Soil erosion

12


Sediment mass conservation equation (Bennet,1974)


)(1)()()(

fdrds

yx DDy

cq

x

cq

t

hc

h water depth (m)c sediment concentration (m3 m-3)s sediment particle density (kg m-3) qx unit runoff discharge (x direction) (m2 s-1 ) qy unit runoff discharge (y direction) (m2 s-1 ) Drd soil detachment rate by rainfall (kg m-2 s-1 )Dfd soil detachment/deposition rate by runoff (kg m-2 s-

1 )

13



Soil detachment by rainfall is a function of the rainfall intensity (Li, 1979)

mz

h1 Damping effect of the water film

at the soil surface

soil detachability coefficient by rainfall (kg m-2 mm-1)p an exponent set to 1.0 according to the results of Sharma et al. [1993]h water depth (m)ld loose sediment depth (m)zm the maximum penetration depth of raindrop splash (m)R rainfall intensity (m s-1)

where

182.069.6 Rzm

Before sediment movement

(kg m-2 s -1)

14



Soil detachment by rainfall

function of the area of the covering layer (0-1) soil detachability coefficient by rainfall (kg m-2 mm-1)d soil re-detachability coefficient by rainfall (kg m-2 mm-1)p an exponent (1.0) h water depth (m)zm the maximum penetration depth of raindrop splash (m)R rainfall intensity (mm h-1)

(kg m-2 s -1)

(kg m-2 s -1)Detachment

Re-detachment

After sediment movement

15


Soil detachment or deposition by runoff : a model proposed by Foster and Meyer [1972]

When • qs<Tc, additional sediment detachment • qs>Tc, excessive sediment deposition

)( scfd qTD (kg m-2 s-1)


Tc sediment transport capacity of the flow (kg m-1 s-1)qs sediment discharge per unit flow width in the flow direction (kg m-1 s-1)

16


When Tc>qs (Dfd>0) net erosion occurs and the detachment and entrainment rates are given by:

(kg m-2 s -1)

(kg m-2 s -1)Detachment

Entrainment

f is the flow shear stress in the flow direction (Pa)c is the critical shear stress of a spherical sediment particle [Yang, 1996] (Pa)soil the critical shear stress of the soil (Pa)Kr is the rill erodibility parameter (s m–1)Tc sediment transport capacity of the flow (kg m-1 s-1)qs sediment discharge per unit flow width in the flow direction (kg m-

1 s-1)


17


When Tc<qs (Dfd<0) net deposition occurs and the deposition rates is given by [Foster et al., 1995]:

(kg m-2 s -

1)

is a raindrop induced turbulence coefficient assigned to 0.5.Vf is the particle settling velocity (m s–1)q is the water dicharge per unit flow width in the flow direction (m 3 s-1 m-1)Tc sediment transport capacity of the flow (kg m-1 s-1)qs sediment discharge per unit flow width in the flow direction (kg m-

1 s-1)


18



Flow sediment transport capacity is based on the flow shear stress f (Foster, 1982)

coefficient of efficiency of sediment transport (m0.5 s2 kg –0.5 ) f flow shear stress acting on the soil particles (Pa)c critical shear stress of sediment (Pa) k an exponent taken as 1.5 (Finkner et al.,1989)

kcfcT )( (kg m-1 s-1)

19


Model description: Numerical methods

Hydrological model and erosion model are treated independently since it is assumed that the flow dynamics are not affected by the suspended sediment

The Saint Venant equations are solved using the MacCormack scheme

The mass balance equation for sediment is solved using a second-order centered explicit finite difference scheme

For numerical stability of the scheme and computational efficiency the time step is optimised

Topographic elevations are re-estimated at each time step if there is runoff

20


Model description

Flow chart of PSEM_2D

Model description: Numerical methods

To avoid directional bias of the Mac Cormack scheme the order is reversed

every time step (predictor-forward, corrector-backward then predictor-

backward, corrector-forward).

21


Boundary conditions In the plot version the boundaries are

3 non porous walls and an open boundary (outlet)

Dummy cells are added to model wall boundary

At the outlet no condition is required because the flow is supercritical

Initial condition At the beginning of the simulation

h(x,y,0) = 0 u(x,y,0) = 0 v(x,y,0) = 0

c(x,y,0) = 0

Model description: Initial and boundary conditions

u = 0 u = 0

v = 0

inwardboundaries

upslope

downslope

y

dummy cellsu=0 v=0h=h_inwardc=c_inward

We consider that rainsplash transportation outside the plot is balanced by sediment coming from the area surrounding the

plot.

22


Model description : Calibrated parameters

Transport by runoff

Detachment and re-detachment by raindrop

impactDeposition

Entrainment

Detachment by runoff

Dfd < 0

Dfd > 0

Drd > 0

Tc> qs

soil

Kr

d

hf,f

23


The model needs information on

Slopes and elevations (Digital Elevation Model)

Map of soil surface features distribution

Infiltration parameters (hf, initial WC,Kc,Ks)

Map of DW friction factor

Soil erosion parameters (,Kr, soil, D50)

Map of and dd=10

Rainfall (time, intensities)

Model description: Data

24


The parameter identification is carried out in three stages

We started with parameters estimation based on physical characteristics and published data

Some of soil erosion parameters are defined using data available in the literature (s=0.047, soil is estimated using the WEPP soil database)

Calibration is undertaken for hf (crusted soils) and/or f on one rainfall event

Calibration is undertaken for ,Kr, soil using the ranges of values found in the literature

Model description: Parameter identfication

WEPP: Water Erosion Prediction Project (US Dept. Agr.)

25


Applications of PRIM_2DApplications of PRIM_2D

26


Two runoff plots located on the same hillslope Homogeneous soil surface feature (ERO)

one type of crust: erosion

Heterogeneous surface feature (JAC)

erosion crust and sandy aeolian micro mounds

• Grid resolution 0.25 by 0.25 m• Both plots have the same subsoil• Initial soil water content were obtained

from neutron probe measurements• Verification runs

Examples of application PRIM_2D

27


Examples of application PRIM_2D

Homogeneous soil surface feature (ERO)

Heterogeneous surface feature (JAC)

Runoff plots in Niger

(West Africa)

28

DYNAS Workshop, 6th-8th December 2004, INRIA0 2 40

2

4

6

8

10

12

14

ERO

0 2 40

2

4

6

8

10

12

14

16

18

20

0.95

Sandy mounds

Erosion crusts

J AC ERO

Soil properties

Soil texture Loamy sand Loamy sand s sat. W C (-) 0.296 0.296

hf (m) 1.3795 1.3795 Ks (m/ s) 2.15 E-05 2.15 E-05

Surf ace properties

ErosionZc (m) 0.005 0.005

hf (m) 1.3795 1.3795 Ks (m/ s) 1.70 E-08 1.70 E-08 f 0.25 0.25

Sandy moundsZc (m) 0.05

hf (m) 0.18 Ks (m/ s) 1.90 E-06 f 0.70

J AC ERO

Length (m) 20.0 14.25Width (m) 5.0 5.0Max slope (x) 0.19 0.12Max slope (y) 0.17 0.21

Examples of application PRIM_2DJAC

29


04 september 94

0

20

40

60

80

100

120

140

160

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000Time (s)

Dis

charg

e a

nd r

ainf

all

inte

nsit

y (m

m/h

)

Rainf all

Observed

Calculated

PRIM_2D Validation

An exemple of validation run

30


0

10

20

30

40

0 5 10 15 20 25 30 35 40

Observed (mm)

Calc

ulat

ed (

mm

)

calibration

validation

1:1

Runoff depth

PRIM_2D Validation

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30 35 40

Observed (mm)

Cal

cula

ted (

mm

)

calibration

validation

1:1

I nfi ltration depth

0

1000

2000

3000

4000

0 1000 2000 3000 4000

Observed (s)

Cal

cula

ted (

s)

calibration

validation

1:1

Time to peak

Cal

cula

ted (

mm

/h)

0

25

50

75

100

125

150

175

200

0 25 50 75 100 125 150 175 200

Observed (mm/ h)

calibration

validation

1:1

Maximum discharge

31


PRIM_2D Validation

0

100

200

300

400

500

600

700

0 100 200 300 400 500 600 700

Observed (s)

Cal

cula

ted (

s)

calibration

validation

1:1

Time to begin runoff

32


ERO 25 august 94 20:31:00

0

20

40

60

80

100

120

140

160

0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400

Time (s)

Run

off a

nd R

ainf

all

inte

nsity

(mm

/h) Rainfall

Observed

Computed

JAC 25 august 94 20:31:00

0

20

40

60

80

100

120

140

160

0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400

Time (s)

Run

off a

nd R

ainf

all

inte

nsity

(mm

/h)

Rainfall

Observed

Computed

Plot scale results

33


Plot Rain(mm)

Ov. flow(mm)

Peak disch.(mm/ h)

I nfi ltration(mm)

ERO obs. 23.9 14.3 91.6 9.6

ERO cal. 23.9 14.5 95.2 9.4

Rel. error - -1.9 % + 3.9 % + 1.3 %

J AC Obs. 23.9 11.9 68.7 12.0

J AC cal. 23.9 11.3 69.2 12.6

Rel. error - - 5.0 % + 0.7 % + 5.0 %

Efficiency ERO : 0.879 Efficiency JAC : 0.913

Plot scale results

34

DYNAS Workshop, 6th-8th December 2004, INRIA0 1 2 3 4 50

2

4

6

8

10

12

14

0 1 2 3 4 50

2

4

6

8

10

12

14

0 1 2 3 4 50

2

4

6

8

10

12

14

16

18

20

0

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.01

Velocities (m /s)

0.5

0 1 2 3 4 50

2

4

6

8

10

12

14

16

18

20

JACJAC

ERO

ERO

Water depth (m)

Time 789 s(max discharge)

Distributed results

35


2

4

6

8

10

12

14

16

18

20

0.043

0.048

0.053

0.058

0.063

0.068

0.073

0.078

0.083

0.088

0.093

0.098

0 1 2 3 4 50

2

4

6

8

10

12

14

0.043

0.0435

0.044

0.0445

0.045

0 1 2 3 4 50

2

4

6

8

10

12

14

16

18

20

0

0.01

0.02

0.03

0.04

0.05

0.06

0 1 2 3 4 50

2

4

6

8

10

12

14

JACJAC

ERO

ERO

Infiltration depth (m)

Shear velocities(m/s)

Time 789 s

Distributed results

36

DYNAS Workshop, 6th-8th December 2004, INRIA0 2 4

0

2

4

6

8

10

12

14

16

18

20

0

50

100

150

0 500 1000 1500 2000 2500

mm

/h

A small pond

B rill

D top

C rill

0

0.1

0.2

0.3

0 500 1000 1500 2000 2500

(m/s

)

0

0.0025

0.005

0.0075

0.01

0 500 1000 1500 2000 2500

(m)

0

0.02

0.04

0.06

0 500 1000 1500 2000 2500

(m/s

)

0

500

1000

1500

0 500 1000 1500 2000 2500Time (s)

Velocities

Water depth

Shear velocities

ReynoldsRainfall

Point results

37


The microtopography is represented by

the topographic map of the plot (JAC)

a plane surface with the same mean

slope

All other parameters are the same

Effect of the microtopography

38


25 august 94 20:31:00

010

20304050

607080

90100

0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400Time (s)

Run

off

and

Rai

nfal

l in

tens

ity (

mm

/h) Observed

Computed Plan.

Computed Topo.

Simulation Rain(mm)

Ov. flow(mm)

Peak disch.(mm/ h)

I nfi ltration(mm)

Topography 23.9 11.3 69.2 12.6

Plane 23.9 11.1 73.0 12.8

Diff . - - 1.8 % + 5.5 % + 1.6 %


39


2

4

6

8

10

12

14

16

18

20

0

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.01

Vel. (m /s)

0.5

0 1 2 3 4 50

2

4

6

8

10

12

14

16

18

20

0 2 40

2

4

6

8

10

12

14

16

18

20

0 2 40

2

4

6

8

10

12

14

16

18

20

JAC PLANPLANJAC

Water depth (m)

Distributed results Time 789 s


40


The soil surface features are represented by

the soil surface feature map (JAC)

the dominant surface feature (erosion crust)

All the other parameters are the same

Effect of the surface features distribution

41


Simulation Rain(mm)

Ov. flow(mm)

Peak disch.(mm/ h)

I nfi ltration(mm)

2 Surf . f eat. 23.9 11.3 69.2 12.6

1 Surf . Feat. 23.9 14.4 84.6 9.5

Diff . - + 27.4 % + 22.3 % - 24.6 %

25 august 94 20:31:00

010

2030

4050

6070

8090

100

0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400Time (s)

Run

off

and

Rai

nfal

l in

tens

ity (

mm

/h)

Observed

Computed 1 SF

Computed 2 SF


42


JAC 2 SF JAC 1 SF

0 2 40

2

4

6

8

10

12

14

16

18

20

0 2 40

2

4

6

8

10

12

14

16

18

20

0

0.001

0.002

0.003

0.004

0.005

0.006

0.007

Water depth (m)

Time 589 s

For this storm the time to ponding is

390 s for erosion crust 625 s for sandy

mounds


43


Even in low relief plots, OF is not a sheet of flowing water, uniform in depth and velocity across the slope. OF concentrates downslope into deeper flow pathways

Small surface feature may play a major role in the OF production from a plot

A good reproduction of discharges at the outlet of a plot does not imply that OF hydraulics is correctly simulated

Infiltration is not homogeneous all over the plot which is partly due to the effect of micro-topography

Large variations in the OF hydraulics are due to the variable rainfall rates and to the characteristics of the uphill areas

Key results

44


PSEM_2D EvaluationPSEM_2D Evaluation

45


Kilinc and Richardson (1973) experimental data

A 1.52 m wide × 4.58 m long flume with an adjustable slope and a rainfall simulator. Each run was one hour long

The flume was filled with compacted sandy soil composed of 90 % sand and 10 % silt and clay.

The soil had a non-uniform size distribution with a median diameter D50 of 3.5 × 10-4 m.

The soil surface was levelled and smoothed before each run.

Psem_2D Evaluation : Experimental data

46


Kilinc and Richardson (1973) experimental data

The major controlled variables were rainfall intensity and soil surface slope.

Infiltration and erodibility of surface were supposed constant.

Six slopes (5.7, 10, 15, 20, 30, and 40 %) were tested

Four rainfall intensities (32, 57, 93, and 117 mm h-1).

Calibration was carried out using a run with 20 % slope and 93 mm h-1 rainfall intensity.


47


Data available

• Flow discharge at the outlet of the flume

• Mean sediment concentration in the flow at the outlet

• Mean infiltration rate

• No data were collected on microtopography and Overland flow hydraulics (water depth, velocity)


48


0

0.01

0.02

0.03

0.04

0.05

0 10 20 30 40 50 60

Time (min)

Sed

imen

t di

scha

rge

(kg/

m/s

)

Observed, 30 % slope

PSEM_2D, 30 % slope

Govindaraju and Kavvas[1991], 30 % slope


PSEM_2D, 20 % slope(CALIBRATED)



PSEM_2D, 15 % slope


Rain intensity, 93 mm h-1. Slopes, 15, 20, and 30 %

Psem_2D Evaluation : Results

49


0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0 10 20 30 40 50 60

Time (min)

Se

dim

en

t d

isch

arg

e (

kg/m

/s)


PSEM_2D, 30 % slope



PSEM_2D, 20 % slope



PSEM_2D, 15 % slope


Rain intensity, 117 mm h-1. Slopes, 15, 20, and 30 %


50


0

5

10

15

20

25

30

35

40

45

50

0 5 10 15 20 25 30 35

Time (min)

Se

dim

en

t co

nce

ntr

atio

n (

g/l)

Observed, 50 mm/h Observed, 100 mm/h

PSEM_2D, 50 mm/h (calibrated) PSEM_2D, 100 mm/h

Govindaraju and Kavvas [1991], 50 mm/h Govindaraju and Kavvas [1991], 100 mm/h

Singer and Walker [1983] experiment Slope 9%

D50 of the soil: 2. 10-5 m


51


Psem_2D Evaluation : Sensitivity analysis

The range of variation of the parameters calibrated with the data of Singer and Walker [1983]

9 % slope and 50 mm h-1 rainfall intensity.

52


-200

-100

0

100

200

300

400

500

-500 0 500 1000 1500 2000 2500

parameter variation (in %)

C v

ari

atio

n (

in %

)

s

Kr

f

D50

soil

ld_initia l = 0.01 m

Variations in percentage of the mass sediment concentration versus variations in percentage of each

tested parameter, all the other parameters keeping the calibrated value

Psem_2D Evaluation : Sensitivity analysis

53


PSEM_2D ApplicationsPSEM_2D Applications

54


Psem_2D application

Plot 5 by 15 m a grid of 0.2 by 0.2 m

Parameter values of Singer and Walker experiment

Average slopes are 0.02 and 0.06 in the x and y directions.

55


0

20

40

60

80

100

120

140

160

180

2000 20 40 60 80 100 120 140

time (min)

rain

fall in

ten

sit

y (

mm

/h)

0

20

40

60

80

100

120

140

160

180

200

wate

r d

isch

arg

e (

mm

/h)

an

d s

ed

imen

t con

cen

trati

on

(g

/L)

rainfallwater dischargesediment concentration

sediment concentration (without the first rainfall event)D50 = 20 µm

Psem_2D application: Effect of initial condition

Effect of the formation of a deposited layer before the rainfall

56


-0.007 m

-0.006 m

-0.005 m

-0.004 m

-0.003 m

-0.002 m

-0.001 m

0 m

0.001 m

0.002 m

0.003 m

0.004 m

0.005 m

Erosion and deposition pattern on the plot at the end of the two consecutive rainfall events (time = 135 min

after the beginning of the simulation)

Deposition

Erosion

Psem_2D application

D50 = 20 µm

57


0 m

0 . 0 0 0 4 m

0 . 0 0 0 8 m

0 . 0 0 1 2 m

0 . 0 0 1 6 m

0 . 0 0 2 m

0 . 0 0 2 4 m

0 . 0 0 2 8 m

0 . 0 0 3 2 m

0 . 0 0 3 6 m

0 . 0 0 4 m

Computed flow depths

0 m

0 . 0 0 0 4 m

0 . 0 0 0 8 m

0 . 0 0 1 2 m

0 . 0 0 1 6 m

0 . 0 0 2 m

0 . 0 0 2 4 m

0 . 0 0 2 8 m

0 . 0 0 3 2 m

0 . 0 0 3 6 m

0 . 0 0 4 m

Psem_2D application

time = 124 mintime = 27 min

58


Hydrograph and related sedimentographs for different particle

size diameter0

20

40

60

80

100

120

140

160

180

2000 20 40

time (min)

rain

fall

in

ten

sity

(m

m/h

)

0

20

40

60

80

100

120

140

160

180

200

wat

er d

isch

arg

e (m

m/h

) an

d

sed

imen

t c

on

cen

tra

tio

n (

g/L

)

rainfall water dischargesediment concentration D50=12µm sediment concentration D50=20µmsediment concentration D50=100µmsediment concentration D50=200µmsediment concentration D50=500µmsediment concentration D50=1000µm

Psem_2D application

59


Contribution of the different processes to the sediment yield

-40

-20

0

20

40

60

80

12µm 15µm 20µm 100µm 200µm 500µm 1000µm

Median diameter D50

mass (

kg

)

Entrainment

F Detachment

R Re-detachment

R Detachment

Deposition

Psem_2D application

60


Interrill versus Rill erosion: what does it change in terms of processes ?

Hyetograph

0

20

40

60

80

100

120

140

160

180

200

0 20 40time (min)

rain

fall

inte

nsi

ty (

mm

/h)

Psem_2D application

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Comparaison interrills rills contributing processes to the total sediment yield

plot size

Deposition represents 0.7 % of the total mass

eroded

Deposition represents 11.4 % of the total mass eroded

Psem_2D application

0%

20%

40%

60%

80%

100%

1m*1m plot 15m*5m plot

Tota

l sed

imen

t m

ass

Entrainment

F Detachment

R Re-detachment

R Detachment29 %

95 %64 %

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Some key issues Runoff production limited to excess rainfall Sources and sinks of sediment vary with the

magnitude of the events The soil erodibility coefficients have not yet been

quantitatively related to a measurable soil property and must therefore be determined empirically or calibrated

Model calibration, a lot of parameter to determine More complex models increase data requirement

and … Increase data and model uncertainty, which

affects model results Propagation of errors in input data

Model structural errors Uncertainty associated with evaluation of model parameters

Problem of the model evaluation (spatial field data) “the right answer for the wrong reason”

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Overland flow hydraulics To improve the prediction of the flow resistance

from surface roughness To analyse the respective effects of roughness

and micro topography Modelling erosion

To validate the model for complex microrelief and natural rainfall events : new experiments

To improve the representation of the flow detachment at the subgrid level

To implement a multiclass sediment representation

To test alternative parametrisation of the transport capacity

Unit stream power Govers equation (1990)

As a conclusion Future research

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Thank you for your

attention

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Expériences utilisées pour le calibrage et l’évaluation du modèle

Singer and Walker (1983) experimental data The experiment set up was a laboratory flume (3.0 by 0.55 m)

and a rainfall simulator. The flume was filled with 200 kg of compacted moist fresh soil

to produce a 0.08 m thick bed. The soil was a fine sandy loam with a clay content of 13.9 %

and a high amount of silt plus very fine sand (59.2 % in the range 2.10-6 –1. 10-4 m).

The D50 of the soil was 2. 10-5 m. The final soil surface was smooth and hard to the touch.

The slope was constant and equal to 9 %. The major control variable was rainfall intensity. Bare soil surfaces were tested with two rainfall intensities (50

and 100 mm h-1) constant during 30 minutes. Calibration of soil erosion parameters 50 mm h-1

Données disponiblesDébit d’écoulement à l’exutoire Concentration moyenne de sédiments dans l’écoulement à l’exutoire


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The sediment discharge per unit flow width in the flow direction qs is defined by:

The flow shear stress in the flow direction is expressed as:

The critical shear stress c is that of a spherical sediment particle expressed as [Yang, 1996]:

s is the the critical dimensionless shear stress of the particle


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Psem_2D Evaluation : Model parametrisation

Values of the parameters

1 DYNAS Workshop, 6 th -8 th December 2004, INRIA M. Esteves, G. Nord PSEM_2D DYNAS Workshop...

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Transcript of 1 DYNAS Workshop, 6 th -8 th December 2004, INRIA M. Esteves, G. Nord PSEM_2D DYNAS Workshop...