Step wise modelling approach

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Step wise modelling approach
Climate data long and short term
Soil schematisation
Soil physics
Soil temperatures
Water fluxes and moisture contents long and
short term
Carbon long term static experiment
Nitrogen short term
CO2 short term
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Climate

• Long term and short term experiment
• Data applied
• Rainfall (not corrected)
• Long term ET using Dutch equation using Tair,
  Rglobal/HrsSun
• Short term PenmanMonteith
• Result long term evaporation excess of 57
  mm/year

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Soil schematization

• 3 m soil profile
• 25 soil layers / horizons
• 45 model compartments water flow
• 26 model compartments solute flow
• physical dispersion of 2.5-10 cm

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Hydrology soil temperature

• numerical model to solve soil heat equation
• example for plot12a/b

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soil physics

• Short term experiment
• Different relations theta-h
• Calibration
• Default MVG-set
• Hysteresis
• Reduced theta_sat

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Hydrologysoil moistureplot12a/bcrop rotation
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Hydrologysoil moistureplot12a/bcrop rotation
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Model exercise on static experiment

• Management
• Soil tillage
• Mineral N fertilizer
• 2 types of organic manure

• Initial partitioning
• 90 native SOM (stable)
• 10 humus/biomass

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Short term nitrogen plot12a/b with crop

• OM from long term
• Mineral N fertilizer

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Short term conc. NH4-N and NO3-N black fallow
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Short term conc. NH4-N and NO3-N plot12a/b
cropped
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peculiarities

• Meteo precipitation of short and long term
  experiment differ (88 mm in 1998)
• Soil physical data same theta gives different
  heads (what about quality / uncertainty in
  measurements ?
• Nitrate concentration extremely high in soil
  solution (625 mg/l NO3-N)

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Conclusions (1)

• Long term predictions demand for an appropriate
  description of slow processes
• Partitioning requires long term data sets
• For long term simulations, generalized data on
  land management are sufficient
• Data of the static experiment are of great value
• Little influence of soil physical characteristics
  on long term carbon dynamics (large on short term
  N?)

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Conclusions (2)

• Partitioning of organic matter pools in the Animo
  model is important for short term leaching
  studies
• determines mineralization rates
• Biologigal activity -gt denitrification
• Animo model could easily be calibrated to data of
  static experiment
• Animo was able to simulate the soil-N contents
  quite well, but not the soil moisture
  concentrations
• But, it seems there is a discrepancy between
  soil- nitrogen and soil moisture nitrogen
  measurements

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discussion

• On the use of SWAP/ANIMO
• Elaborate more on trace house gas emissions
• Short term carbon and nitrogen dynamics requires
  further analysis, influence of soil physical
  properties, soil temperature?
• Standardize calibration techniques (e.g. GLUE?)
• Standardize storage of valuable data sets
  include uncertainties

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• Thank you for your attention