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Simulation of C and N dynamicsin soil and plants

R.A. Poluektov & V.V.Terleev

Agrophysical Research Institute,St.-Petersburg, Russia


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Model structure


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Input data

Soil Texture, bulk density, hygroscopy, wilting point, fieldcapacity, saturation point, saturation hydraulic conductivity

Climate (daily weather

values)

Minimum and maximum air temperature, minimum air humidity, precipitation, average wind speed, sunshineduration

Management Irrigation and fertilization regimes

Initial conditions Sowing date; water and nitrogen content in one meter soillayer; soil organic matter and mass of microbial populationin 0-30 cm layer


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State variables and output

State variables Soil water moisture, soil temperature, and nitrogencontent according to layers: 0-10, 10- 20,,90 -100 cm;Physiological time (0 at emergency, 1 at anthesys, 2

at full ripening)

Output (daily variables)

Primary assimilates; development stages; leaf area index;

dry mass of the leaves, stems, roots and ears;evapotranspiration; water storage and nitrogen content inone meter soil layer; infiltration of soil water; nitrogenleaching; grain yield


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Submodels

Processes

Radiation regime of crop, turbulent exchange betweenair and plant, photosynthesis and respiration, plantdevelopment stages, crop transpiration and soilevaporation, soil water dynamics, nitrogen

transformation in soil and plant

Parameters

Parameters of: photosynthesis unit (3 items); plantdevelopment (6 10 items according to phases);distribution keys (6 4 items according to plant organs);hydrological constants (4); N-transformation in soil (5);

N-uptake by root (2)


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Shell structure of AGROTOOL

Place selection

Place selection

Field

selection

Field

selection

Culture selection

Choice of the yearmanagement and

the date of forecast

Choice of the yearmanagement and

the date of forecast

D

T

B

SE

D

T

B

SE

Estimationand

forecast


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Model features

Initialization is done by means of management program (Model shell), which constitutes simulation systemAGROTOOL (together with model itself) and includes selection of: simulation place (geographic coordinates and concretefield); culture (spring and winter wheat, spring burley, winter ray, potatoes, oats, perennial grasses); management(irrigation and fertilization regimes); task type (analysis, forecast, weather generation); calculation year; and initial state(sowing date, water and nitrogen content in one meter soil layer).

Resolution in time and space (profile ) is following: basic time step is 24 h (units of photosynthesis, water and nitrogen dynamics use hourly internal time step) basic spatial step on vertical direction is 10 cm(up to 100 cm).

Peculiarities of the model are: New method of calculation of plant transpiration and soil water evaporation based on modification Penman-Monteith

method;Adaptive distribution key for calculation of root/shoot ratio using C:N interaction in plant canopy;Automotive system for calculation of the parameters of pedotransfer functions.


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Model identification consists of 5 steps:

1) Calibration of water dynamics unit,

2) Determination of parameters of development unit,

3) Determination of water stress function,

4) Calibration of nitrogen dynamics unit,

5) Determination of parameters of forecast function.


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Parameters controlling temp of plantdevelopment:

T 0 biological zero, 0C;

c1 , coefficient of extra plant heating, 0C;

opt boundary of comfort zone for soil water potential, cm;

S 0 water stress coefficient;

T Ph boundary of development change, degree-days.


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Water stress function

)( _ )1( SS BWstr W W

j

l s p

j

l

l E l E

l PR jSS

0

0

)()(

)()(

Wstr B a a SS a SS a SS _ 0 1 22

33

Correction of dry matter accumulation

Argument of water stress function

Stress function


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Calculation of root:shoot ratio

Shoot

Root

CO 2

NO 2 , NH 4

NH 4 PrimAss

(Two flows model)


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C and N transformation in soil

Soil organicmatter

Microbal biomass

NH4+

Mineralization

Immobilization

Nitrification

NO3-Immobilization

N uptake byroots

Losses

Ficsation

Clayminerals

Mineralfertilizers

Denitrification

Losses

N2+H2O NH3


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)()1()(

)()(

k ck W

k ck W

rs s

rsr

,)()(

,)()(

root cr rd

shoot c s sd

N Rk W k N

N S k W k N

RT

T k N av dt t k V k N

)1(

,)()1()(

)()1( k k V N N av )()( k W S k r root

)()()( k N k N k N avrd sd

Distribution of PrimAss:

N demand by shoot

and root

N uptake by roots:

N balance:

Calculation of crs


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Determination of root:shoot ratio

1- N-dependenceof crop,

2 N-uptake by

roots

0

1

2

3

0 0,2 0,4 0,6 0,8 1

Part of assimilates allocated to roots

N i t r o g e n a

b s o r b e

d b y c r o p

1

2


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Dependence of root:shoot ratio on N-doze

1- flowering phase,

2 fullripening

phase

0

0,05

0,1

0,15

0,2

0,25

0,3

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0 20 40 60 80 100

Nitrogen fertilization dose, kg ha -1

R o o

t : s h o o

t r a

t i o

1

2


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Dynamics of root:shoot ratio byvarious N-fertilization

1- variant without N,

2 N=45 kg ha-1

,3 N=90 kg ha-1

0,0

0,1

0,2

0,3

0,4

0,5 0,6

0,7

0,8

0,9

0 10 20 30 40 50 60 70 80 90

Days of vegetation starting from sowing

R o o

t : s h o o r r a

t i o

1 2

3


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,

1 ab MH SP

MH

wherevolumetric soil moisture,matrix potential,

MH maximum hygroscopy, SP saturation point, a, b empirical parameters.

Model of water retention curve


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Variants of calculation of hydrological constants

, , , ,Variants Input data Results of calculation

1 r , MH, WP, SP LC, FC, UC

2 r , WP, SP , soil texture MH, LC, FC, UC

3 r , MH, SP soil texture LC, WP, FC, UC

4 r , SP MH, LC, WP, FC, UC

1 r, r S , MH, WP LC, FC, UC, SP

2 r, r S , WP, soil texture MH, LC, FC, UC, SP

3 r, r S , MH, soil texture LC, WP, FC, UC, SP

4 r, r S MH, LC, WP, FC, UC, SP

r - soil bulk density, r S - solid phase density , M H maximum hygroscopy,SP - saturation point, WP wilting point , F C field capacity,L C lower capillary moisture, UC upper capillary moisture.


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0

1

2

3

4

5

6

0,0 0,1 0,2 0,3 0,4 0,5 0,6

4

3

2 1

Volumetric soil moisture -d /d( pF ), cm 3 cm-3

LC

UC

p F =

l o g 1 0 ( -

) , w

h e r e - m a t r i x p o t e n

t i a l c m

H 2

O

1 water retention curve,

2 specific water capacity,

3 dependence of UC on UC ,

4 - dependence of LC on LC

Calculation of water retention curve for the soil of Men'kovo experimentation station using the followingexperimental data:

r , r S , M H.


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0

1

2

3

4

5

6

0,0 0,1 0,2 0,3 0,4 0,5 0,6

Volumetric soil moisture -d /d( pF ), cm 3 cm-3

p F =

l o g 1 0

( -

) , w

h e r e - m a t r i x p o

t e n t

i a l c m

H 2

O

Comparison of calculated and experimental data

o experimental points,

-.- - interpolated curve,

curve calculatedusing experimental data


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Computer system for estimation soil hydraulic parameters


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Estimation of Badlauchstadt pedotransfer functions

This program was used for estimation of the parametersincluded in pedotransfer functions. The experimental data for soil texture and saturated hydraulic conductivity were used for

this purpose. Two additional data, apart from available MH and SP , were necessary for estimation of the pF -curve

parameters. Such hydraulic soil parameters as field capacity( FC ) and wilting point ( WP ) were chosen for this purpose.The comparison of simulated pF -curves with experimentaldata is presented in the following Figs.


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Comparison between simulated water retention curves andexperimental data sets presented by Franko et al.

(site Badlauchstadt)

Fig. 1. 20-24 cm Fig. 2. 45-49 cm Fig. 3. 115-119 cm


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Comparison of simulated and real winter ray grain yield(Menkovo experimentation station)


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Dependence of spring barley grain yieldon N- dose (Menkovo experimentation station)

10

20

30

40

0 20 40 60 80 100 120

N-fertilization dose kg ha-1

G r a

i n y i e l d

d t h a - 1

1

2

3


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Nitrates leaching (Menkovo experimentation station)

0

30

60

90

120

150

0 20 40 60 80 100 120

N-fertilization dose, kg ha -1

N - N

O 3 l e a c h

i n g ,

k g

h a

- 1 y

e a r -

1

1

3

2


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Yield and dry mass

0

20

40

60

80

100

120

0 20 40 60 80 100 120 140

Days since planting

D

r y m a s s o

f p l a n t o r g a n s , d t h a - 1

1

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4

Dynamics of dry mass of potatoes plant organs.Badlauchstadt, 2001 yr.

1 - leaves,2 - stems,3 - leaves + stems,4 - tubers, experimental data for leaves.


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Yield and dry mass

0

10

20

30

40

50

60

70 90 110 130 150 170

Days on Julian calender

D r y m a s s o

f p l a n t o r g a n s ,

d t h a - 1

1

2

3

4

Dynamics of dry mass of spring barley plant organs.Badlauchstadt, 2000 yr.

1 - leaves,2 - stems,3 - aboveground,4 - ears,

- experimental data for aboveground mass.


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Yield and dry mass

0

20

40

60

80

100

120

140

160

100 150 200 250 300

Days since sowing

D r y m

a s s o f p l a n t o r g a n s d t h a - 1

1

2

3

4

Dynamics of dry mass of winter wheat plant organs.Badlauchstadt, 2001 yr.

1 - leaves,2 - stems,3 - aboveground,4 - ears,

- experimental data for aboveground,o - experimental data for ears.


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Water status

10

15

20

25

30

0 20 40 60 80 100 120 140

Days since planting

W a t e r s t o r a g e

i n o n e m e t e r l a y e r

, c m

Soil water dynamics under potato crop,Badlauchstadt, 2001 yr.

measurement data


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Water status

10

15

20

25

30

40 60 80 100 120 140 160 180

Days on Julian calender

W a t e r s t o r a g e

i n o n e m e t e r l a y e r , c

m

Soil water dynamics under spring barley crop,Badlauchstadt, 2000 yr.

- measurement data


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Results of statistical treatment for water content

Culture/year Mean value, cm Error, cm MSE, cm

Spring barley/2000 19.0

-0.208 1.04

Potatoes/2001 22.4 -1.16 0.95

The error was calculated according to formula:

iiiw WS WSsimn

Ewn

E exp11

where WSsimi is simulated soil water storage corresponding to i-th measurement, n istotal number of measurements. Mean square error (MSE) is the square root from thevariance of the errors Ew i.


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Results of statistical treatment for dry mass

Relative error was calculated on formula:

i

ii

Bsim B Bsim

n RE

exp1,

here Bsim i is simulated value of dry mass, Bexp i corresponding experimental value,n total number of measurements. Mean square error (MSE) was calculated as squareroot from variance of RE i.

Culture/year Relative error

MSE

Spring barley/2000 0.065 0.24

Potatoes/2001 0.061 0.30

Winter wheat/2001/02 -0.21 0.44


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Conclusion

Generally, there are externally few things inthe World, which we really anything knowabout. In the most cases it only seems to us

that we know.

Kharuki Murakami

Hunting on sheep


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Thank you

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