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Last update: May 2021

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AGADAPT - Adapting the water use by the agriculture sector

Regional STICS

The model represents the water balance of agricultural covers over regional areas. The model estimate irrigation, evapotranspiration, soil water balance and drainage flow, which are computed on every simulation unit by the STICS model. The regionalization is addressed using a multi-simulation approach thanks to the the Multisimlib framework that facilitate the link between spatial information and the STICS model. It can be combined with a ground water model to provide the soil contribution of agricultural areas to the net balance of the aquifer. The strength of STICS approach is to offer a comprehensive crop model adapted to a wide range of crops. It can then simulate agriculture areas by taking into account both climate change (precipitation, climatic demand, CO2 increase) and adaptation in cropping system.

You can download the PDF Version here

Model architecture

The model contains two main modules:

  • a simulation case generator to establish the different simulation cases that are necessary to represent the variability in climate, soil, and agricultural practices
  • a crop model to represent the soil water balance and the water flow at its boundaries

 The outputs are computed over simulation spatial units, which are defined as the intersection of soil, land use and climate units. For a given simulation several simulations with the crop model may be done to represent the variability within the spatial unit (soil, agricultural practices). In such a case, the results are then aggregated over the spatial unit.

 The link between the two modules are done by files that allow the multiple STICS run.

Diagramme1

Module description : Simulator case generator

Main processes being represented

The simulator case generator will select the soil types, the appropriate climates. The main processes being modeled at this level are the cropping operations: variety selection, residue management, tillage, sowing, fertilization, irrigation and harvest. Basically three strategies can be foreseen for every cropping operation :

                - a single representative operation (type, date, intensity ie irrigation dose);

                - interactions of cropping operation with climatic condition (useful to address climate changes);

                - interactions between crop operations (ie irrigation and fertilization)

For every strategy, stochastic approaches can be easily implemented to represent the variability induced by soil, climate and farm management.

Description of the inputs
Input Type

Variable identification and metric

Temporal and spatial scale

Default source of data in space

Source of data for future scenarios

Climate

Climate grid

Areas

ERA-Interim(past) - SAFRAN (Past-France) - Ensemble regionalized scenarios

Ensemble regionalized scenarios

Land use

Percentage of each suface managment type:

  • Field crop irrigated
  • Field crop non irrigated
  • Orchard
  • Garden market
  • Grass irrigated
  • Grass non irrigated
  • Vineyards
  • Olives
  • Forest
  • Urban

Land use unit

Corinne Land Cover

Soil

Soil map (texture, organic matter content, root obstacle, dry bulk density, stone content)

Soil unit

European data base

Agricultural practices

Rotation Practices (sowing, harvest, irrigation, residue management, nitrogen fertilization)

Crop cycle, representative fields

Eurostat, MARS Regional expertise

Description of the outputs

The output is a table gathering all information required to implement the STICS Crop model for every simulation case.

Module description : STICS Crop Model

Main function

STICS represent the crop growth and yield according to soil properties, climate conditions and cropping operation. The main simulated processes are the crop growth, the crop development, yield components, root growth, water and nitrogen balance and thermal environment of the plant. The generic structure of the model allows addressing a wide range of crops (bread wheat, durum wheat, barley, rapeseed, sunflower, potato, tomato, vineyard, peas, salad, and sugar cane). The model works at the daily time scale and represents one crop cycle. Several crop cycles can be chained.

Diagramme
Description of the inputs
Input Type

Variable identification and metric

Temporal and spatial scale

Default source of data in past

Source of data for future scenarios

Climate

Precipitation (mm), air temperature min and max (°C), wind speed (m/s), vapor pressures (mbar), Solar radiation (MJ/m2), PET (mm) Not mandatory CO2 (ppm)

Daily - spatial unit

ERA-Interim (past) - SAFRAN (Past - France) - Ensemble regionalized scenarios

Ensemble regionalized scenarios

Soil
  • Number of layer (max 5)
  • Layer thickness
  • Wilting point (g/g)
  • Field capacity (g/g)
  • Stone content (g/g)
  • Dry Bulk density
  • Organic Nitrogen (g/g)
  • Texture
  • Initial water content (g/g)
  • Initial NO3 content (KgN/ha)
  • Initial NH4 content (KgN/ha)

Spatial unit

European texture map combined with pedotransfer functions

Agricultural pratices
  • Crop type and variety
  • Crop residue management (amount and composition)
  • Sowing (date, depth, density)
  • Irrigation (rules or calendar)
  • Fertilization (amount, calendar, type)

Crop cycle, representative fields

Eurostat, MARS Regional expertise

Description of the outputs

Various variables can be computed. The main categories are :

                                         

Soil profile (water content, nitrogen)

Soil Flux (drainage, Nitrogen leaching, evapotranspiration, N2O flux, PET)

Organic matter dynamic

Vegetation (biomass, leaf area index, yield, root depth, plant development stages)

Condition of access to the model codes

Three components should be considered

 

  1.    STICS crop model
  2.    Multisimlib (software managing the multisimulation : developed under matlab)
  3.    Simulation case generation (developed in AGADAPT under Matlab)

  Condition of acces to the component 1 and 2

  • Licensing condition or subcontracting according to the dissemination mode
  • Based on revenue
  • Contact : André Chanzy

-        Condition of access to the component 3

  • Free (exemple developed in AGADAPT, that need adaptation to other context)

 

References

http://www7.avignon.inra.fr/agroclim_stics/modele_stics

Brisson, N., Mary, B., Ripoche, D., Jeuffroy, M. H., Ruget, F., Nicoullaud, B., Gate, P., Devienne-Barret, F., Antonioletti, R., Durr, C., Richard, G., Beaudoin, N., Recous, S., Tayot, X., Plenet, D., Cellier, P., Machet, J. M., Meynard, J. M., and Delecolle, R. (1998c). STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn. Agronomie 18, 311-346.

Brisson, N., Launay M., Mary, B and Baudoin N., 2008 Conceptual basis, formalizations and parameterization of the STICS crop Model, Editions Quae, Paris, France ISBN 978-2-7592-0169-3

Version PDF

PDF Version of STICS Model
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