Simulation of C and N dynamics in soil and plants

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Simulation of C and N dynamics in 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, field capacity, saturation point, saturation hydraulic conductivity
Climate (daily weather values) Minimum and maximum air temperature, minimum air humidity, precipitation, average wind speed, sunshine duration
Management Irrigation and fertilization regimes
Initial conditions Sowing date water and nitrogen content in one meter soil layer soil organic matter and mass of microbial population in 0-30 cm layer
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State variables and output
State variables Soil water moisture, soil temperature, and nitrogen content 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 in one meter soil layer infiltration of soil water nitrogen leaching grain yield
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Submodels
Processes Radiation regime of crop, turbulent exchange between air and plant, photosynthesis and respiration, plant development stages, crop transpiration and soil evaporation, soil water dynamics, nitrogen transformation in soil and plant
Parameters Parameters of photosynthesis unit (3 items) plant development (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
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Model features
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Model identification consists of 5 steps
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Parameters controlling temp of plant development
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Water stress function
Correction of dry matter accumulation
Argument of water stress function
Stress function
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Calculation of rootshoot ratio
(Two flows model)
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C and N transformation in soil
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Calculation of crs
Distribution of PrimAss
N demand by shoot and root

N uptake by roots

N balance
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Determination of rootshoot ratio
1- N-dependence of crop, 2 N-uptake by roots
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Dependence of rootshoot ratio on N-doze
1- flowering phase, 2 full ripening phase
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Dynamics of rootshoot ratio by various
N-fertilization
1- variant without N, 2 N45 kg ha-1, 3 N90
kg ha-1
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Model of water retention curve
where volumetric soil moisture, matrix
potential, MH maximum hygroscopy, SP saturation
point, a, b empirical parameters.
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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, rS , MH, WP LC, FC, UC, SP
2? r, rS, WP, soil texture MH, LC, FC, UC, SP
3? r, rS , MH, soil texture LC, WP, FC, UC, SP
4? r, rS MH, LC, WP, FC, UC, SP
,
,
,
,
r- soil bulk density, rS - solid phase density,
MH maximum hygroscopy, SP - saturation point,
WP wilting point, FC field capacity, LC
lower capillary moisture, UC upper capillary
moisture.
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Calculation of water retention curve for the
soil of Men'kovo experimentation station using
the following experimental data r, rS , MH.
1 water retention curve, 2 specific water
capacity, 3 dependence of UC on yUC, 4 -
dependence of LC on yLC
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Comparison of calculated and experimental data
o experimental points, -.- - interpolated
curve, curve calculated using 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
  parameters included 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 experimental data is presented in the
  following Figs.

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Comparison between simulated water retention
curves and experimental data sets presented by
Franko et al. (site Badlauchstadt)
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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 yield on
N-dose (Menkovo experimentation station)
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Nitrates leaching (Menkovo experimentation
station)
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Yield and dry mass
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Yield and dry mass
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Yield and dry mass
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Water status
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Water status
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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
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Results of statistical treatment for dry mass
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 in the
  World, which we really anything know about. In
  the most cases it only seems to us that we know.
• 
  Kharuki Murakami
• 
  Hunting on sheep

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• Thank you