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1 1 Overland flow and erosion in agricultural lands Process, model, assessment Paul van Dijk A.Véronique Auzet FORM-OSE Post-Graduate Training School “Living with hydro-geomorphological risks : From theory to practice” 2 Structure a. Introduction, processes and factors b. Impacts c. Models and applications 3 Structure a. Introduction, processes and factors b. Impacts c. Models and applications 4 Soil erosion is an ”old problem” on steep slopes in semi-arid regions Recognised more recently In loess regions in the European temperate climate zone with moderate relief Focus of today’s course 5 6 The french example, inventory based on reports Source : Auzet A.V., 1989. In Le grand atlas de la France rurale. (Eds INRA). J.P. de Monza, Paris.

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Page 1: Overland flow and erosion in agricultural lands - Unistraeost.u-strasbg.fr/omiv/Cerg_documents/VanDijk.pdf · 1 1 Overland flow and erosion in agricultural lands Process, model, assessment

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1

Overland flow and erosion in agricultural lands

Process, model, assessmentPaul van Dijk

A.Véronique Auzet

FORM-OSEPost-Graduate Training School“Living with hydro-geomorphological risks :From theory to practice”

2

Structure

a. Introduction, processes and factors

b. Impacts

c. Models and applications

3

Structure

a. Introduction, processes and factors

b. Impacts

c. Models and applications

4

Soil erosion is an ”old problem”on steep slopes

in semi-arid regions

Recognised more recently In loess regions in the European temperate climate zone with moderate relief

Focus of today’s course

5 6

The french example, inventory based on reports

Source :Auzet A.V., 1989.In Le grand atlas de la France rurale.(Eds INRA). J.P. de Monza, Paris.

Page 2: Overland flow and erosion in agricultural lands - Unistraeost.u-strasbg.fr/omiv/Cerg_documents/VanDijk.pdf · 1 1 Overland flow and erosion in agricultural lands Process, model, assessment

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7

Background of erosion problems in temperate climate

Change from forest/pasture towards arable land use

<< org.matter on the surface

>> Temp (exposure of the soil surface)

>> Aeration (tillage)

Exposure of the soil surface to raindrop

impact during part of the year>> activity of soil micro-biology

>> decomposition of mat. org. by mineralisation et oxidation

<< supply of org. matter in the soil

<< organic bounds in the soil

<< aggregate stability

>> crust formation

<< infiltration

>> overland flow >> splash erosion

>> erosion8

Why in areas with loess-derived soils (1) ?

Source : Kihlbom 1970

9

F0

F1

F2

Scodro (2001)

Low structural stability

Why in areas with loess-derived soils (2) ?

10

Soil surface conditions, crusting

11

Timing aspects : climat and agriculture(ex: Bretagne © C. Gascuel, 2001)

SowingWeeding harvesting

Rainfall characteristics

Soil conditions: roughness and infiltrability

Vegetation cover

Successive agricultural operationsSoil and hydrologic conditions

Winter:hydrologic conditions

Spring: a quick soil desagregation

Two key-periods 12

The processes

• Splash erosion

• Overland flow generation Hortonien (rainfall intensity > infiltration cap)

Rainfall intensity, soil surface state

Saturation (soil pore space is filled with water, additional rainfallcannot infiltrate)

Rainfall quantity, soil moisture storage capacity, impeding layer

Exfiltration

Snowmelt (on frozen soil)

• Soil detachment by overland flow

• Transport

• Deposition

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13

Erosion

Deposition

Transport

Sediment delivery

Spatial aspects, scales

14

Upstream overland flow formationand diffuse erosion

15

Overland flow concentration and rill erosion

Photos: A.V. Auzet 16

Transport phase

Photos: A.V. Auzet

17

Sediment deposition

Photos: P.M. van Dijk

18

Sediment delivery to streams

Page 4: Overland flow and erosion in agricultural lands - Unistraeost.u-strasbg.fr/omiv/Cerg_documents/VanDijk.pdf · 1 1 Overland flow and erosion in agricultural lands Process, model, assessment

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19

Structure

a. Introduction, processes and factors

b. Impacts

c. Models and applications

20

Impacts

• On siteSoil loss, reduced soil depth

Loss of nutrients

Modified physical and chemical properties, AWC

Destruction of crop

In case of gullies : problematique access with agr. machines

• Off siteSediment and pollutants transfers

Surface water quality and ecosystem degradation

Damage to infrastructure and built-up areas (muddy flows)

• Direct and indirect economical costs for communities and individuals

21

Damage depends on the land occupation

22

Damage in fields

Blotzheim, juin 2003© R. Armand

23Blotzheim, juin 2003 (©R. Armand) 24

Damage to infrastructure © P. van Dijk

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25

Damage in built-up areas Landser, 25 mai 2001

© Lemmel M., Scodro E.26Blotzheim, juin 2003 © R. Armand

27 28

Water quality impacts and effects on aquatic ecosystems

La Dijle (Belgique)Mai 1986

29

Structure

a. Introduction, processes and factors

b. Impacts

c. Models and applications

30

Models, in order to :

• Identify problem areas (target areas for measures)

• Increase our knowledge

• Evaluate and predict (effects of measures, catchment management, climate/land use change)

At different spatial scales (field, catchment, region…)

At different time scales (minutes to years)

Page 6: Overland flow and erosion in agricultural lands - Unistraeost.u-strasbg.fr/omiv/Cerg_documents/VanDijk.pdf · 1 1 Overland flow and erosion in agricultural lands Process, model, assessment

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31

Model types

• empiricalUSLE, RUSLE, MUSLE

• deterministicCREAMS, AGNPS, SWAT, SWIM

• physically-basedWEPP, KINEROS, EUROSEM, LISEM, SHE

• stochasticRillGrow…

32

Models, objectifs, scales

Rillgrow, 3 m2LISEL, 4 km2

33

Two models, two spatio-temporal scales

• LISEM: the Limburg Soil Erosion ModelEvent (time step : seconds)

Physically-based

Distributed

Catchment-scale (raster cell size 5 to 50 m)

• RECODES: climate and land use change impacts on sediment delivery to streams in the Rhine basin

Time step : 1 month

Distributed, (raster cell size : 1 km2)

To reply to water management questions for the Netherlands in theperiod untill 2100

Model 1 : LISEM

35

Model 1LISEM : GIS embedded catchment model

DEM

Land use

Soil

Rainfall

Erosion

Overland flow

Hydrogramme

Deposition

Input Output

36

Flowchart of LISEM

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37

LDD (Local Drainage Direction)

The LDD defines flow direction in all cells and thus spatial structures

38

Basic data

Rain of ruturn period 5 years

0

1

2

3

4

5

6

7

8

618 30 42 54

duration (min)

pluv

iom

etry

(mm

)

rain of return

period 5

years

DEM Soil

Land use

Prec.

39

Model parameters derived from soil type

1 2 3 4 5 6D50 (mu) 22,30 23,65 22,42 26,30 23,12 22,30KSAT F(0) (mm/h) 21,10 22,50 20,70 28,60 21,50 22,00KSAT F(1) (mm/h) 10,00 10,00 10,00 10,00 10,00 10,00KSAT F(2) (mm/h) 2,00 2,00 2,00 2,00 2,00 2,00KSATCRST (mm/h) / / / / / /KSATWT (mm/h) 2,11 2,25 2,07 2,86 2,15 2,20PSI (cm) 100 100 100 100 100 100SOILDEP (mm) 200 250 350 300 300 300THETAI (-) 0,30 0,30 0,30 0,30 0,30 0,30THETAS (-) 0,48 0,50 0,51 0,47 0,49 0,50

LISE

M

SOIL TYPE

40

Model parameters derived from land use

AGGRSTAB (-) 19 18,5 14 -1 -1 -1 -1 -1

CH (m) 0 0 0,35 0 0,05 10 15 0

COH F(0) F(1) (kPa) 0,69 0,47 0,91 0,51 3,32 1,93 1,93 9999

COH F(2) (kPa) 0,75 0,52 0,95 0,57 3,32 1,93 1,93 9999

COHADD (kPa) 0 0 0,8 0 3,32 1,45 1,45 9999

LAI (m2/m2) 0 0 1,1 0 1,86 11 11 0

n (-) 80 115 123 120 227 300 300 0,001

PER (-) 0 0 0,4 0 0,95 0,95 0,95 0

STONEFRAC (-) 0,05 0,05 0,1 0,05 0,05 0,05 0,05 0 et 1

RR F(0) (cm) 0,89 1 0,48 0,97 0,7 0,73 1,36 0

RR F(1) (cm) 0,29 0,35 0,48 0,97 0,7 0,73 1,36 0

RR F(2) (cm) 0,12 0,25 0,48 0,97 0,7 0,73 1,36 0

Betterave

Les chiffres en italique sont ceux proposés par la table de LISEM pour la deuxième quinzaine du mois de mai. Leschiffres en gras correspondent à des valeurs que nous avons mesurées, observées ou bien choisies en fonction decritères prédéfinis.

Blé JachèrePlan d'eau et habitat

LISE

M

Bande enherbée/Prairie

Verger ForêtMais

OCCUPATION DU SOL

41

Application of LISEM, no. 1

Effects of soil surface conditions

(Mickaël Lemmel, 2001)

42

F0

F2

Runoff

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43

Erosion

G1AF0

G1AF1

G1AF2

G1AF0

G1AF1

G1AF2

-Initial soil surface state

- Moderate degradation

-Strong degradation

44

Application of LISEM, no. 2

LISEM + TCRP (tillage controlled runoff pattern)

Accounting for tillage structures effects on runoff patterns and erosion

45

Dead furrow

Headlands 46

47 48

Effects of tillage direction

LDD topographique TCRP

Structures de drainage de la partie amont du BV GUTZ

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Runoff distribution over the catchment

LDD modifié avec TCRPLDD topographique

Lame d’eau ruisselée (mm)

0 500

N

mètres

•Different spatial structure

•Overland flow concentration often occurs at field boundaries 50

topography tillage

Takken et al., 1999

51

Application of LISEM, no. 3

Scenarion studies at the catchment scale

(Marc Pichaud, 2001)

52

Secteur de l’Outre Forêt

53 54

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reduction of eroded surface (<0.5tonne/ha)

05

101520253035

band

e enhe

rbée

tcs à

20 %

15 di

gues

be+tcs

20%

be+di1

5

tcs1+

di15

tcs2+

di15

be+tcs

2+di1

5

scenarii

redu

ctin

g fa

ctor

(%)

2 years5 years10 years

Scenarios with different combinations of : - grass strips- reduced tillage- retention structures (dikes)

56

reduction of peak discharge

05

1015202530354045

grass

strips

(gr)

mulch (2

0%)

15 da

ms

gr + m

ul.

gr + da

ms

mul.(10%)+d

ams

mul.(20%)+d

ams

gr+mul.+

dams

scenarii

redu

ctio

n fa

ctor

(%)

2 years5 years10 years

57

Model 2: RECODES (GAMES + USLE)

Climate and land use change : impacts on sediment delivery in the Rhine basin

(Van Dijk, 2001)

58

0 100 km

THENETHERLANDS

Andernach

Kaub

SWITZERLAND

FRANCE

Rheinfelden

GERMANY

LUXEMBURG

AUSTRIA

Cochem

Worms RockenauKleinheubach

Viereth

SchweinfurtKalkofen

Diepoldsau

Approach

• fully distributed model with a time step of one month

• a sediment production module to quantify mobilisation of sediment by soil erosion at the hillslopescale

• a module accounting for sediment storage through a delivery ratio expression

• sediment supply: between or within cells

• written in PCRaster dynamic modelling language

60

The basic modules

• Sediment production: USLE, RUSLE, ABAG

• Delivery ratio: GAMES, the fraction of mobilised sediment that actually reaches the stream depends on:

proximity of source to stream

the probability of overland flow occurrence

the character of the terrain along the route towards the channel(roughness, slope angle)

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R-factor

62

K-factor

63

Snowmelt effects are taken into account

64

Hydrological coefficient described the availability

of overland land to transport sediment towards streams

65

Sediment source to stream distances are estimated

using a detailed drainage network map

66

Local annual erosion

Sediment delivery to streams

Source: Van Dijk (2001)

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67

0

5

10

15

20

25

30

35

N D J F M A M J J A S O

mois

éros

ion

(t/km

2)

Neckar

Aare (UL)

Mosel

Temporal variations

Source: Van Dijk (2001) 68

-30

-20

-10

0

10

20

30

40

CPC+UKHI(high)

CPC+UKHI(central)

CPC+UKHI(low)

UKHI (high) UKHI (central) UKHI (low) CP

scenario

Effe

t sur

l'ap

port

de

sédi

men

t (%

)

climate and land use change only climate change only land use change

best estimate

Results of scenario calculations

Source: Van Dijk (2001)

69

Attention! Errors and uncertainty!

• Errors in input data

• Model errors

Never consider model output as the truth

Uncertainty analyses ! (such as Monte Carlo analyses)

70

0

500

1000

1500

2000

2500

sim

ulat

ed

0 500 1000 1500 2000 2500

measured

cal

val

Total Discharge (m3)

Example of Govers and Jetten

71

0

100

200

300

400

500

600

700

0 100 200 300 400 500 600 700

sim

ulat

ed

measured

cal

val

Peak Discharge (l/s)

Example of Govers et Jetten72

0

10

20

30

40

0 10 20 30 40

sim

ulat

ed

measured

cal

val

Total Soil loss (ton)

Example of Govers et Jetten

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Why do erosion models perform poorly ?

Source: Govers et Jetten74

Deterministic, spatio-temporal models require many input parameters which all contain some

degree of errors. Model output can be very sensitive to some of them (non-linearity)

Source: Govers et Jetten

75

In case rainfall or infiltration has an error of 5,10,15 et 20%...

Error propagation

Source: Govers et Jetten76

error propagation h->V->Q

0.0

100.0

200.0

300.0

400.0

0 5 10 15 20 25

relative error input (%)

rela

tive

erro

r out

put (

%)

Q V h

…the error in modelled catchment discharge can be > 300% !

Source: Govers et Jetten

77

Example: sensitivity to Ksat

Source: De Roo et al (1995)78

Incertainty / model complexity

Source: Grünwald (1997)

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Thanks !