Matric Potential (cm)

Modelling Water, Nitrogen and Carbon Fluxes

during Decomposition of Crop Residues,

Incorporated or left at the Soil Surface

Filip Coppens 1,3_{, Patricia Garnier} 1_{, Antoine Findeling}2_{, Sylvie Recous} 1_{, Roel Merckx}3

1_{INRA, Unité d’Agronomie LRM, Laon (France)}

2_{CIRAD-AMIS – Programme Agronomie, Montpellier (France)}

3_{K.U.Leuven, Department of Land Management, Heverlee (Belgium)}

Introduction

• Global change:

– carbon sequestration in agricultural land

• Reduced / no-tillage

– change in crop residue localisation

• Soil column experiment

• Modelling

Residue decomposition

Fate of C, N in soil

soil water dynamics

nutrient distribution

microbial activity

Experimental setup

• Soil columns:

– Silt loam soil

• sieved at 2 mm

• compacted in columns (1.3 g/cm3 _{; 25 cm,} ∅ _{15 cm)}

– Oilseed rape residue

• labelled 13_{C and} 15_N

• particle size of 1 cm

• incorporated (0-10 cm) or mulch

• 14 g DM/column (equivalent 7.4 t/ha)

• Incubation during 9 weeks at 20°C

– 3 dry-wet cycles

Experimental setup

CO₂

Soil solution samplers Tensiometers

TDR Rain simulator

Modelling

• Why modelling?

– Interaction water dynamics ~ residue decomposition

– Gross fluxes N-mineralization/immobilization

– Scenario analysis

• different rain applications • other crop residue quality

• Which model?

– Link soil physical - biological processes

– surface residue decomposition

Modelling: PASTIS model

• PASTIS :

1-dimentional, mechanistic model

– module biotransformations C + N

• residue-C decomposition

– module transport

• water transfer θ(t,z) => f_θ(t,z)

• heat transfer T(t,z) => f_T(t,z)

• solute transport [NO₃](t,z) => f_[NO3](t,z)

B N W T i i

C

f

f

f

f

K

dt

dC

−

=

Modelling: C + N

Soluble Organic Matter (SOL)

Biomass Zymogenous

(ZYB)

Humified Organic Matter (HOM)

Biomass Autochtonous

(AUB) Fresh Organic Matter (FOM)

Rapidly decomposable Hemicellulose Cellulose Lignin

material (RDM) _(HCE) (CEL) (LIG)

CO2 NO3 -CO2 NH4 + NH4 + CO2 NH4 + NH4 + CO2 NO₃ -NH4 + Vmax K₁ K₂ K₃ K_{4 H} l H_a K_h K_z K_s K_a H_z Y_h Y_s Y_z Y_a N/C

Modelling: mulch decomposition

- max. mass in contact with soil - min./max. water content

- max. rain interception …..

Biological parameters - quality = incorporation - specific functions for

- Temperature - Water content - N availability Soil

Modelling: concept

Input

Model

Output

Water potential CO₂-flux NO₃-_-N residual 13_C Initial conditions Boundary conditions Constant temperature Hydrodynamic parameters - column control soil

Biological parameters - incubation experiment

Observation vs. Simulation

Soil water potential

Observation (-6 cm)

Simulation (-6 cm)

Observation (-14 cm)

Simulation (-14 cm)

Calibration: control columns

Incorporation 0 20 40 60 80 0 20 _Days 40 60 kg C-CO 2 / h a / d ay Incorporation > Mulch Rain application!

Water content mulch

Control 0 20 40 60 80 0 20 _Days 40 60 k g C-CO 2 / ha / day Mulch 0 20 40 60 80 0 20 _Days 40 60 k g C-CO 2 / h a / d a y

CO

- flux

Observation vs. Simulation

Water content mulch

0.0 0.5 1.0 1.5 2.0 2.5 0 20 40 60 Days g w a te r / g r e s idue

Incorporation 0 20 40 60 80 100 0 20 Days 40 60 % of a dde d 13 C

Residual oilseed rape-C

Observation vs. Simulation

Control 0 5 10 15 20 25 0 20 Days 40 60 kg N O3 - -N / h a Incorporation 0 5 10 15 20 25 0 20 Days 40 60 kg N O3 - -N / h a Mulch 0 5 10 15 20 25 0 20 _Days 40 60 kg N O 3 - -N / h a

NO

_-N

Observation vs. Simulation

Incorp.: net N immobilization Mulch: net N mineralization Measured NO₃-_-N:

mineralization-immobilization, leaching + upward transport

Conclusion / Perspectives

• Model

– interaction water / N-dynamics

• Improvements for

– initial rate of C-mineralization

– mulch decomposition

• transport of nitrate, soluble C from mulch

• Perspectives

– effect of residue quality

– scenario analysis