Estimation of CH 4 and N 2 O emissions from rice fields under AWD irrigation management through a DNDC model approach

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Estimation of CH₄and N₂O emissions from rice fields under AWD irrigation management through a DNDC model approachEstimation of CH4 and N2 O emissions from rice fields under AWD irrigation management through a DNDC model approach

Estimation of CH₄and N₂O emissions from rice fields under

AWD irrigation management through a DNDC model approach

Managing Climate Change (MC2)

“Process, Measurements, Modelling and Mitigation of Greenhouse Gasses” 18-20 November 2009

Massey University, Palmerston North, New Zealand Managing Climate Change (MC2)

“Process, Measurements, Modelling and Mitigation of Greenhouse Gasses” 18-20 November 2009

Massey University, Palmerston North, New Zealand

N. Katayanagi1,2_{, Y. Furukawa}2,3_{, T. Fumoto}4_{, and Y. Hosen}1,2

1 Japan International Research Center for Agricultural Sciences,Tsukuba, Japan 2 International Rice Research Institute, Los Baños, Philippines

3 Niigata Agricultural Research Institute, Nagaoka, Japan (present address)

N. Katayanagi1,2_{, Y. Furukawa}2,3_{, T. Fumoto}4_{, and Y. Hosen}1,2

1 Japan International Research Center for Agricultural Sciences, Tsukuba, Japan 2 International Rice Research Institute, Los Baños, Philippines

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2009/11/20

2009/11/20 Managing Climate Change Managing Climate Change - -MC2MC2

2 1. Background

2. Modification of DNDC-Rice model

3. Model Validation

4. Summary

1. Background

2. Modification of DNDC-Rice model

3. Model Validation

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1. Background

2. Modification of DNDC-Rice model

3. Model Validation

4. Summary

1. Background

2. Modification of DNDC-Rice model

3. Model Validation

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2009/11/20

4

4 Alternate Wetting and Drying

A

lternate

W

etting and

D

rying

A Water-saving irrigation technique for rice cropping AWD has been investigated by International Rice

Research Institute (IRRI) in Philippines since the early 1970’s.

With the technique:

• 15-30% unproductive water outflow can be cut down • Water productivity can be increased without

sacrificing yield.

The main objectives of research for AWD technique are: • The spread of the technique

• The evaluation of the technique from the viewpoint of its environmental impact

A Water-saving irrigation technique for rice cropping

AWD has been investigated by International Rice

Research Institute (IRRI) in Philippines since the early 1970’s.

With the technique:

• 15-30% unproductive water outflow can be cut down

• Water productivity can be increased without

sacrificing yield.

The main objectives of research for AWD technique are:

• The spread of the technique

• The evaluation of the technique from the viewpoint of

its environmental impact

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Criteria of driest conditions,

e.g. Certain soil water tension at 150 mm depth or

Criteria of driest conditions,

e.g. Certain soil water tension at 150 mm depth or Maximum height of standing water, e.g. + 50mm Continuously flooding Continuously flooding

AWD

Soil Soil Time Standing water

Irrigation Timing of AWD technique

AWD

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2009/11/20

6 Field water tube

Instruments for monitoring hydrological conditions

Tensiometer

AWD

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2009/11/20

8 GHGs measurement conducted in IRRI since 2007

GHGs measurement conducted in IRRI since 2007

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AWD

Irrigation Water Plenty

Global warming potential

High 0

CH

₄

CH

₄

N

₂

O

N

₂

O

Total

GWP

Total

GWP

AWD can decrease GWP of paddy fields

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2009/11/20

10 1. Background

2. Modification of DNDC-Rice model

3. Model Varidation

4. Summary

1. Background

2. Modification of DNDC-Rice model

3. Model Varidation

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DNDC model for rice paddy fields

 1992: A DNDC model was developed by Li et al. (1992) • Process-based model for agroecosystems

simulates carbon and nitrogen dynamics based on biogeochemical processes

Non-flooded agricultural conditions • Carbon sequestration

• GHGs (N₂O, CH₄, CO₂, NO and NH₃)

 2004: Anaerobic biogeochemistry was incorporated for rice paddy fields (Li et al. 2004)

 2008: DNDC 8.2 was modified for paddy ecosystems by Fumoto et al. (2008) →DNDC-Rice model

 2009: A regional scale evaluation of CH₄ emission using the

1992: A DNDC model was developed by Li et al. (1992)

• Process-based model for agroecosystems

simulates carbon and nitrogen dynamics based on biogeochemical processes

Non-flooded agricultural conditions

• Carbon sequestration

• GHGs (N₂O, CH₄, CO₂, NO and NH₃)

2004: Anaerobic biogeochemistry was incorporated for rice

paddy fields (Li et al. 2004)

2008: DNDC 8.2 was modified for paddy ecosystems by

Fumoto et al. (2008) →DNDC-Rice model

2009: A regional scale evaluation of CH₄ emission using the

Outline

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Schematic description of the soil biogeochemistry sub-model of DNDC-Rice (Fumoto et al. 2008 and 2009)

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O₂ Diffusion Diffusion H₂ CO₂ CO₂ CH₄ Fe2+_{, Mn}2+ Fe3+_{, Mn}4+ DOC

Modification

Schematic description of the soil biogeochemistry sub-model of DNDC-Rice

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2009/11/20

14 O

₂

diffusion to soil

O

₂

diffusion to soil

Modification

Cs Cs Max Crack Depth (m)

O₂diffusion from four rateral faces Crack_factor = 4/Cs * h

O₂diffusion from surface

Cs: crack space (m)

h: thickness of a layer (m)

(Fumoto et al. 2008)

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Gas diffusivity model – Osozawa 1987

Osozawa (1987)

D_i= D₀ε_i2.7

D_i: O₂-air diffusion coefficient in soil (cm2 _sec-1₎

D₀: O₂-air diffusion coefficient in air at 20℃, 1 atm (=0.201 cm2 _sec-1₎

ε_i: gas phase (m3 _m-3₎

Osozawa (1987)

D_i= D₀ε_i2.7

D₀: O₂-air diffusion coefficient in air at 20℃, 1 atm (=0.201 cm2 _sec-1₎

(Fumoto et al. 2008 and 2009)

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2009/11/20

16 Gas diffusivity model – BBC model

Gas diffusivity model – BBC model

Backingham-Burdine-Campbell (BBC) model (Moldrup et al. 1999, Rolston and Moldrup 2002)

D_i= D_0,T φ_i2 _(φ

i /εi ) 2+3/b

D_0,T = D_0,20((273+T)/(273+20))1.72 b = 13.6 clay + 3.5

D_{0, T}: O₂-air diffusion coefficient in air at T ℃, 1 atm (cm2 _sec-1₎

D_{0, 20}: O₂-air diffusion coefficient in air at 20 ℃, 1 atm (=0.201 cm2 _sec-1₎

φ_i: porosity (m3 _m-3₎

b: campbell pore-size distribution parameter

Backingham-Burdine-Campbell (BBC) model

(Moldrup et al. 1999, Rolston and Moldrup 2002)

D_i= D_0,T φ_i2 _(φ

i /εi ) 2+3/b

D_0,T = D_0,20((273+T)/(273+20))1.72 b = 13.6 clay + 3.5

D_{0, T}: O₂-air diffusion coefficient in air at T ℃, 1 atm (cm2 _sec-1₎

D_{0, 20}: O₂-air diffusion coefficient in air at 20 ℃, 1 atm (=0.201 cm2 _sec-1₎

φ_i: porosity (m3 _m-3₎ ε_i: gas phase (m3 _m-3₎

b: campbell pore-size distribution parameter

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Other changes

Decomposition factor (DRF) was changed from 0.82 to 0.2. Water table estimation

• Water table was estimated using simulated WFPS values of each 2cm depth soil.

 Assumption1:

water content ≧ 0.94 Æ saturated water content < 0.94 Æ unsaturated  Assumption2:

There is the water table at the top layer of the saturated layers.

Decomposition factor (DRF) was changed from 0.82 to 0.2.

Water table estimation

• Water table was estimated using simulated WFPS

values of each 2cm depth soil. Assumption1:

water content ≧ 0.94 Æ saturated water content < 0.94 Æ unsaturated

Assumption2:

There is the water table at the top layer of the saturated layers.

Modification

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2009/11/20

18 1. Background

2. Modification of DNDC-Rice model

3. Model Validation

4. Summary

1. Background

2. Modification of DNDC-Rice model

3. Model Validation

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2009/11/20

20 A pot experiment conducted in a screenhouse, IRRI

A pot experiment conducted in a screenhouse, IRRI

Size of the pot

700 mm height and 530 mm i.d. Bulk density (0-15 cm)

0.82±0.53(Mg m-3₎

Percolation rate 1 (mm day-1₎

_{Clay content} _59%

Soil organic C cont. 2.4%

Soil pH 6.2

_{Soil texture} _Clay

Field water capacity 0.8 （WFPS） Wilting point 0.4（WFPS） Size of the pot

700 mm height and 530 mm i.d.

Bulk density (0-15 cm)

0.82±0.53(Mg m-3₎

Percolation rate 1 (mm day-1₎

Clay content 59%

Soil organic C cont. 2.4%

_{Soil pH} _6.2 Soil texture Clay

Field water capacity 0.8 （WFPS）

_{Wilting point} _{0.4（WFPS）}

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Scheme of the pot management

Criteria: -30 kPa at 15 cm depth or water table become below 40 cm Criteria: -30 kPa at 15 cm depth or water table become below 40 cm ↑ Soil surface Standing Water Surface Water retention Layer depth Flooding Transplanting PSB Rc80 Harvest Continuously flooding Continuously flooding N fert. 40 kgN ha-1 Straw 4 t ha-1 N fert. 40 kgN ha-1 Straw 4 t ha-1

Puddling _Drainage_Drainage

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22 Measurement of CH

₄

and N

₂

O fluxes

Measurement of CH

₄

and N

₂

O fluxes

Gas sampling

• Closed-chamber method

Collected gas samples at 0, 15, and 30

minutes after closing a rid.

Gas analysis

• CH

₄

Gaschromatography with FID

• N

₂

O Gaschromatography with ECD

Calculation of gas fluxes

• Linear regression method

Gas sampling

• Closed-chamber method

Collected gas samples at 0, 15, and 30

minutes after closing a rid.

Gas analysis

• CH

₄

Gaschromatography with FID

• N

₂

O Gaschromatography with ECD

Calculation of gas fluxes

• Linear regression method

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Meteorological data

Site: IRRI wetland

• Daily maximum temperature

• Daily minimum temperature

• Solar radiation

※Precipitation was assumed zero because the

measurement was conducted in a

screenhouse.

Site: IRRI wetland

• Daily maximum temperature

• Daily minimum temperature

• Solar radiation

※Precipitation was assumed zero because the

measurement was conducted in a

screenhouse.

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2009/11/20

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A_m: mean value of observed values

F_i: Simulated value

A_i: Observed value

N: Number of sample

Statictics

Root Mean Square Error (RMSE)

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0 10 20 30 40 0 20 40 60 80 100 0 10 20 30 40

Observed daily maximum and minimum temperature and solar radiation during the cropping period

DAT Temperature( ℃ ) Solar radiation (MJ m -2 )

Daily mean air temp.

Solar Radiation

PuddlingTransplant Harvest

Fertilizer

Validation

May 19

2007 Aug. 242007

Results

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2009/11/20

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0 20 40 60 80 100 -0.6 -0.4 -0.2 0 0.2 0 20 40 60 80 100 -0.6 -0.4 -0.2 0 0.2

Observed and simulated water table for continuously flooding and AWD

Water Table (m) DAT Simuated value Simuated value Observed value Observed value Continuously flooding AWD

PuddlingTransplant Harvest

Fertilizer

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Simulated daily O₂content at 10 cm depth soil under continuously flooding and

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0 20 40 60 80 100 0 2 4 6 8 10 12 0 20 40 60 80 100 -0.20 0.2 0.4 0.6 0.81

Observed and simulated daily CH₄and N₂O fluxes under continuously flooding (DRF=0.2)

Observed and simulated daily CH₄and N₂O fluxes under continuously flooding (DRF=0.2) CH 4 flux (kg C ha -1 d -1 )

TransplantFertilizer Harvest

Puddling N 2 O flux (kg N ha -1 d -1 ) DAT

Validation

Results

Simulated (before modification)

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0 20 40 60 80 100 0 2 4 6 8 10 12 0 20 40 60 80 100 -0.20 0.2 0.4 0.6 0.81

Observed and simulated daily CH and N O fluxes under AWD irrigation

DAT

TransplantFertilizer Harvest

Puddling CH 4 flux (kg C ha -1 d -1 ) N 2 O flux (kg N ha -1 d -1 )

Validation

Results

Simulated (before modification)

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2009/11/20

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Observed and simulated CH₄and N₂O emission rates of paddy fields under continuously flooding and AWD during the cropping period

Validation

Results

Observed value Modification

(mean , SE) Before After

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Modification of calculation method for O₂diffusion improved accuracy of simulation results of CH₄and N₂O fluxes, even though more improvement must be added.

Modification of calculation method for O₂diffusion

improved accuracy of simulation results of CH₄and N₂O

fluxes, even though more improvement must be added.

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2009/11/20

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We are going to make more modification to the model using monitoring data collected in field.

We are going to make more modification to the

model using monitoring data collected in field.

₃₂

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Estimation of CH 4 and N 2 O emissions from rice fields under AWD irrigation management through a DNDC model approach

2

Table of Contents

Table of Contents

1. Background

2. Modification of DNDC-Rice model

3. Model Validation

4. Summary

1.

Background

2.

Modification of DNDC-Rice model

3.

Model Validation

Table of Contents

Table of Contents

1. Background

2. Modification of DNDC-Rice model

3. Model Validation

4. Summary

1.

Background

2.

Modification of DNDC-Rice model

3.

Model Validation

4

4

Alternate Wetting and Drying

A

lternate

W

etting and

D

rying

AWD

AWD

Irrigation Timing of AWD technique

Irrigation Timing of AWD technique

6

Field water tube

Instruments for monitoring hydrological conditions

Instruments for monitoring hydrological conditions

Tensiometer

8

GHGs measurement conducted in IRRI since 2007

GHGs measurement conducted in IRRI since 2007

AWD

AWD

CH

CH

N

O

N

O

Total

GWP

Total

GWP

AWD can decrease GWP of paddy fields

AWD can decrease GWP of paddy fields

10

Table of Contents

Table of Contents

1. Background

2. Modification of DNDC-Rice model

3. Model Varidation

4. Summary

1.

Background

2.

Modification of DNDC-Rice model

3.

Model Varidation

DNDC model for rice paddy fields

DNDC model for rice paddy fields

12

Modification

14

O

Gas sampling

Collected gas samples at 0, 15, and 30

Gas analysis

Calculation of gas fluxes

Site: IRRI wetland