AMG : a simple SOC balance model usedin France for in ...€¦ · AMG : a simple SOC balance model usedin France for in France for decisiondecisionsupport Annie DUPARQUE 1, Jean -Louis

AMG : AMG : a simple SOC balance model a simple SOC balance model

usedused in France for in France for decisiondecision supportsupport

Annie DUPARQUE1, Jean-Louis DINH1, Bruno MARY2a

SOMPATIC Workshop 20-22 - 11-2013AMG: a simple SOC balance model used in France for decision support A. Duparque, J.L Dinh, B. Mary and coll. , France

Annie DUPARQUE , Jean-Louis DINH , Bruno MARY

and Alain BOUTHIER3, Bénédicte BLIN4, Pascal DENOROY2b, Flora GANTEIL4,

Sabine HOUOT2c, Maxime LEVERT1, Stéphanie SAGOT4, Robert TROCHARD3

1: Agro-transfert Ressources et Territoires 2a : INRA, Agro-Impact, Laon ; 2b: INRA , UMR TCEM, Bordeaux ; 2c : INRA EGC, Grignon3 : Arvalis Institut du Végétal4 : LDAR (Laboratoire d’Analyses et de Recherche de l’Aisne)

Content

1 - AMG: description

2 - AMG-Research: a research tool

- Description


- Description

- Evaluation on several databases

3 - Simeos-AMG: a decision support tool

2

AMG model is derived of Hénin & Dupuis (HD) model used to simulate SOC evolution on the long term (1945),

Characteristics of HD model :

- 2 compartments of SOC- time step = 1 year


SOMPATIC Workshop 20-22 - 11-2013AMG: a simple SOC balance model used in France for decision support A. Duparque, J.L Dinh, B. Mary and coll. , France 3

- time step = 1 year- only 2 parameters - input information easily available at the field and the farm level

H&D model has been widely used in France as a support for decision making and formation until recently

Characteristics:

- 3 compartments of OCFresh OCCa = Active SOCCs = Stable SOC

- Time step = 1 year

Fresh OC

m

Active SOCCa

CO2

C input MineralizedSOC

K1.mK .Ca

(1-K1).m

Fluxes and compartments of OC in the AMG model

Stable SOC

1 - AMG : description

AMG structure


- Time step = 1 year

- 3 parameters:K1 humification coefficientK annual mineralization rateCs/Co initial fraction of stable C C = Ca + Cs

dC/dt = K1.m – K.Ca

Stable SOCCs

Ct = CS + Ca . exp(- k . t) . K1 . m / K . (1 – exp( - K . t))

Andriulo et al., 1999

FreshOC

mActive SOCCa

CO2

C input MineralizedSOC

K1.mK .Ca

(1-K1).m

Stable SOC

Roots

Main crops

Catch crops

Aerial residues

Determination of FOM inputs



C = Ca + CsdC/dt = K1.m – K.Ca

SOCCs

OrganicAmendments

FOM = crop residues and organic wastes

m =f(crop yield and amount of organic wastes; C concentration)

K1 = f(nature and composition of FOM)

Inputs from crop residues (grain crops)


MS récoltée = grains

ADMTotal = DMgrain / HI

DM harvested = grains

total

DMgrain = yield * DM content


MSA potentiellement restituable

= paille

MSA toujours restituée = chaumes (+ balles = glumes, glumelles ; + rachis)

MS racinaire (non récoltée)0 – 30 cm

MS totale

MSA totale

MS végétative

totale

MSA

ADM always incorporated

= (ADM Total – DMgrain) * a’

Root DM = ADM Total * CR / (1-CR)

ADM potentially harvestable = straw

totalADM total

vegetativeADM

Total DM---

Root dry matter

ADM always incorporated = stubble

Inputs from crop residues (root crops)


ADM potentially incorporated = leaves

ADM always

ADM unharvested


DM totalADM always incorporated = beet tops

DM harvested = tuber

Root DM incorporated = rootlets


Determination of K1

3 main methods:

• M1) Model fitting versus observed data in LTE


• M2) Calibration with laboratory incubations

• M3) Calibration with biochemical analyses


Method M2

Asymptotic remaining C ≈ K1

% Corg apporté

80

100

C minéralisémineralized C


temps (années)

0 10 20 30 400

20

40

60

C restant au solC stable

C remaining in the soil


Method M3

Biochemical index ISMO ≈ K1

Autres

Digestats

Matières animales

Engrais

Matières végétales

Other

Digestate

Animal material

Fertilizers

Plant material

Mulch

More than 650 organic wastes

of differenttypes


ISMO (% C organique)

0 20 40 60 80 100

Mulchs

Effluents d'élevage avec litière

Effluents d'élevage sans litière

Composts d'effluents d'élevage

Composts urbains

Boues

Mulch

Manure

Slurry

Manure compost

Urban compost

Sewage sludge

Lashermes et al., 2009

types characterized

FreshOC

mActive SOCCa

CO2

C inputMineralized

SOCK1.m

K .Ca

(1-K1).m

Stable

Calculation of mineralization rate K


SoilType

T°C, Rains, ET

Climate


SOC

C = Ca + CsdC/dt = K1.m – K.Ca

Stable SOCCs

Texture, CaCO3

Soil tilllage

K = K0 * f(clay) * f(lime) * f(T) * f(P-PET) * f(tillage)

11

Content



- Description


- Description



12

I1 – Description of AMG Research

AMG

DB

Postgre

Data

Tables of ref.

REQUESTS

Stats

Input

File

(CSV)

Output

File

(CSV)

Excel File Graph

Stocks

Input

Data

AMG Research

Postgre

Database


* Calculation of :- Simulated soil OC evolution- Statistic parameters relative to

the evaluation of the ajustment of the model to the data

* Optimisation of model parameters (MCMC process)

* Data selection / extraction

* Calculation of :- Means- Standard deviations- Observed soil OC evolution- Inputs of C from residues and

organic amendments* Génération of CSV input file

Example of SOC variations

I1 – Description of AMG Research


1) Evaluation on a 1) Evaluation on a databasedatabase of of soilsoil analyses in arable analyses in arable farmsfarms

I1 – Evaluation of AMG Research

Years 1970-1997

391 fields selected

Analyzed 3, 4 or 5 times


Analyzed 3, 4 or 5 times


Parcelle 23

y = -0.16x + 33.09R2 = 0.19

25

30

35

40

0 5 10 15 20 25

Parcelle 70

y = 0.22x + 32.29R2 = 0.83

30

35

40

45

0 5 10 15 20 25

Parcelle 95

y = 0.21x + 30.98R2 = 0.86

30

35

40

45

0 5 10 15 20 25

Parcelle 277 70 Parcelle 206 40Parcelle 228 45

Années

Stock C

Selection of the 391 fields


Linear regression versus timeConsistancy of the SOC variation kineticsSlope = mean rate of change of SOC

y = -0.42x + 64.89R2 = 0.46

55

60

65

0 5 10 15 20 25

y = 0.06x + 31.65R2 = 0.21

25

30

35

0 5 10 15 20 25

y = 0.01x + 37.80R2 = 0.01

30

35

40

0 5 10 15 20 25

Source : B. Mary


20%

25%

30%

35%Fréquence

observé

simulé

observed

simulated

Model evaluationSimulated vs observed rates of change


0%

5%

10%

15%

-2.0 -0.8 -0.4 -0.2 0.0 0.2 0.4 0.8 2.0

Variation du stock (t C/ha/an)Rate of SOC change

Source : B. Mary


•• Ultuna (Sweden) 35 years

• Askov (Denmark) 31 years

• Askov 2 (Denmark) 20 years

• Khon Kaen (Thaïland) 26 years

9 LTE with or without straw removal

2) Evaluation on 9 long2) Evaluation on 9 long--termterm experimentsexperiments


• Issoudun (France) 32 years

• Serreslous (France) 24 years

• Doazit (France) 13 years

• Grignon (France) 18 years

• Boigneville (France) 12 years

Saffih and Mary, 2008

Simulated vs observedSOC stocks


40

50

60

Sim

ulé

(t/h

a)

Paille exportée

Paille restituée

Straw Exported

Straw Incorporated

(t/h

a)

U

A

I G

B

D

A2

15%

20%

Sim

ulé

(%

app

ort)

ad

de

dC

)

Strawsburnt

Simulated vs observedchanges in SOC stocks due

to straw addition


0

10

20

30

0 10 20 30 40 50 60

Observé (t/ha)

Sim

ulé

(t/h

a)S

imu

late

d(t

/ha

Observed (t/ha)

A

S

K

A2

0%

5%

10%

0% 5% 10% 15% 20%Observé (% apport)

Sim

ulé

(%

app

ort)

Sim

ula

ted

(% a

dd

ed

Observed (% of added C)

High T°

Sandy soil

Low T°

Clay soil

Saffih and Mary, 2008

33) Evaluation on 23 long) Evaluation on 23 long--termterm experimentsexperiments in Francein France

Selection of adequate LTE based on:

- Consistent evolution of SOM versus time

- Available information on crops, yields,

Database of LTE available in France for testing SOM models


- Available information on crops, yields, residues and organic wastes management

- Number of measurement dates > 3

- Available information on sampling and/or tillage depths

50

60

70

80

Sim

ula

ted

(t

C/h

a)

Global evaluation


Simulated vs observed SOC stocks(t

C /

ha)


0

10

20

30

40

0 10 20 30 40 50 60 70 80

Sim

ula

ted

(t

C/h

a)

Observed (t C/ha)

C

C3

C4

21

Observed (t C / ha)

Sim

ula

ted

Content



- Description


- Description



22

Current system :• Plowing : 4 yrs/5• Plowing depth : 28 cm• Catch crops : 2 yrs/5

Cropping system with vegetables and potatoes in a sandy loam

Potatoes / Wheat / Peas / Sugar Beet / Carots

Evolution de la teneur en Corganique de la couche travaillée

6,8

7,0

7,3

7,5

7,8

8,0

0 4 8 12 16 20 24 28 32 36 40

Années

Ten

eur e

n C

org

(g

/kg)

1,35

1,40

1,45

1,50

1,55

1,60

Ten

eur e

n M

O (%

)

3nd modif. of system :

• + 10 T/ha of compost /5yrs• 1 plowing1st modif. of the

SOC Content evolution in tillage layer

SIMEOS-AMG


Evolution du Stock de C org sur 0-30cm

28,5

29,0

29,5

30,0

30,5

31,0

31,5

32,0

32,5

0 5 10 15 20 25 30 35 40

Années

Sto

ck C

org

0-30

cm

T

/ha

2nd modif. of system : • + 10 T/ha of compost /5yrs• Catch crops : 3 yrs/5

• 1 plowingsuppressed and plowing depthreduced to 22 cm

1st modif. of the system :• 1 plowingsuppressed : 3 yrs/5• Plowing depthreduced to 22 cm

SOC Stock evolution (T/ha)

System '‘cereals + sugarbeet'‘Loamy soil

betterave – blé – orge - colza – blé.Engrais verts : 1 année/5Labour à 25 cm

1234

Hypothesis on soil OM content

1,8 % of OM

2,2 % of OM

Hypothesis on soil tillage

80%Plough

40% Plough

Wich proportion of straw might be exported without a risk at the field scale ?

A decision support tool for advisory services

80%Plough

40% Plough

I1 – Simeos-AMG: a decision support tool


Allowedstraw

exportation

1paille/3

1paille/2

0%

0%

Evolution du Stock de Corg sur 0-30cm

37,0

39,0

41,0

43,0

45,0

47,0

0 5 10 15 20 25 30Années

Sto

ck C

org

0-3

0 cm

T

/ha

1

2

34

Simulations by

Simeos-AMG?

24

Evolution of SOC Stocks 0-30 cm

The C org reference concentration

Corg reference concentration = Median value of the distribution of observedCorg concentrations for a type-situation in the region

Principle :

Avoiding the deterioration of soil organic status and related soil properties on the long term for each main agronomical situation

(type- situation = combination of a soil type and a cropping system type)



Corg concentrations for a type-situation in the region

25

0

5

10

15

20

25

30

35

Eff

ect

if

Classes de teneurs en C organique

Cas-type 5 Limon moyenSystem '‘cereals + sugarbeet'‘

Loamy soil

betterave – blé – orge - colza – blé.Engrais verts : 1 année/5Labour à 25 cm

A decision support tool for advisory servicesProportion of straw that might be exported without major risks at the field scale



Application of Simeos-AMG to the diagnosis of SOC evolution at the territory scale

ABC’Terre Project (2013-2015)

Spatialized diagnosis of LT variations of SOC stocks

of agricultural area

Spatialized soil and croppingsystems data

RPG

RRP

BDAT


Combinaisons SdC X Sol x Stocks Corg

localised at the territory scale(currrent state)

État organique à t + 20 ans

AMGAMG

Tool to rebuild crop rotationsAgronomical ExpertiseMethod to combine Corg x SoilTypeMethod to combine SdC x Soil type

Regional DB on cultural

pratices+ Farmstypology

BDAT

Simulations of SOC evolution

SIMEOS-AMG

AMG Model: limitations and improvement prospects

Conclusions

- The model does not apply to grasslands and other perenn ial crops (miscanthus, … )

- The effect of soil moisture (through a water balance indicator) must be improved

- The values of humification coefficients of organic wastes (manures, sludges, composts, slurry, …) must be updated using


Future prospectsAn interest for evaluating AMG on other datasets in Europeand comparing with other models, in this Sompatic group !

(manures, sludges, composts, slurry, …) must be updated using a database of laboratory experiments

These issues are addressed in on going studies in F rance.

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AMG : a simple SOC balance model usedin France for in ...€¦ · AMG : a simple SOC balance model usedin France for in France for decisiondecisionsupport Annie DUPARQUE 1, Jean -Louis