1. APSIM Agricultural Production Systems Simulator Mehrnoosh Eghtedari Decamber 2013

2. Introduction
APSIM:
is a modeling environment that uses various component modules to simulate cropping systems in the semi-arid tropics. Modules can be biological, environmental, managerial or economic and are linked via the APSIM "engine".
can simulate the growth and yield of a range of crops in response to a variety of management practices, crop mixtures and rotation sequences, including pastures and livestock.

3. Goals of APSIM
To simulate of biophysical processes in farming systems.
To assist the search for better farming strategies and the development of aids to better production decision making under risk.
To require a tool to accurate predictions of crop production in relation to climate, genotype, soil, and management factors regarding long term management of resources.

4. Commonwealth Scientific and Industrial Research Organisation
History of APSIM
In the early 1990s.
 Commonwealth Scientific and Industrial Research Organisation

5. Capabilities of APSIM
Growth and yeild simulation of more than 25 crops.
Growth and biomass simulation of pastures.
Growth and biomass simulation of trees.
Crop Competition with weeds simulation.
Weed population dynamics.

6. Capabilities of APSIM Intercropping systems simulation.
Systems simulation in irrigated and rainfed conditions.
The impact of management factors simulation. (Tillage, Irrigation, Fertilizing, Date of sowing)
Rotation and fallow simulation.

7. Capabilities of APSIM Agroforestry systems simulation.
Key processes simulation in the soil.
Carbon decomposition and surface residues simultion.
Systems simulation in various scales (gene to ecosystem).
The effect of climate change simulation.
Production socio-economic effects simulation.

8. Combining with Different Models
CABALA: A model for predicting forest growth

9. The APSIM Model Framework
A set of biophysical modules that simulate biological and physical processes in farming systems,
A set of management modules that allow the user to specify the intended management rules.
Various modules to facilitate data input and output to and from the simulation.
A simulation engine that drives the simulation process and controls all messages passing between the independent modules.

10. STRUCTURE of APSIM (Mathematical-Mechanistic- Dynamic-Code based)
System Control
Manager
Manager
Clock
Report
ENGINE
Climate
Met
Canopy
SoilWat
Wheat
SoilN
Maize
Crops
SoilPH
Sorghum
Soil
Legume
SoilP
Other Crops
Erosion
Irrigate
Manure
Fertilize
Residue
Economics
Management

11. APSIM Modules
Crop
Soil
Climate
Mangement
System Control

12. Crop Modules
APSIM contains an array of modules for simulating growth, development and yield of crops, pastures and forests and thier interactions.
The plant modules simulate key physiological processes and operate on a daily time step in response to input daily weather data, soil characteristics and crop management actions.
All plant species use the same physiological principles to capture resources and use these resources to grow. The main differences are the thresholds and shapes of their response functions.

13. Crop Modules
Crop ontogeny is simulated via relationships defining responses to temperature and photoperiod.
Leaf area production and senescence is simulated via relationships of leaf initiation rate, leaf appearance rate and plant leaf area with temperature.
Potential crop water uptake is simulated via relationships with root exploration and extraction potential, which depends on soil and crop factors.

14. Crop Modules
All coefficients for general crop responses and crop/cultivar specific coefficients are stored external to the code to allow ease of use and transition across crops/cultivars.
Constants and parameters from the code are stored in crop parameter files. Each file consists of two major parts: crop-specific constants and cultivar-specific parameters.

15. Physiology of Yield Formation
Climate
Soil
Mangement HI
Dry Matter
RUE
Light Interception k
Leaf Area °C
Phenology

16. Physiology of Yield Formation
Harvest Index × Dry Matter= Yield
HI = f(phenology, temperature, water,nutrients, management) HI
(Grain Number x Grain size )/Dry Matter
Linear function of biomass accumulation after anthesis

17. Crop Modules
AgPasture
Growth
Plant
Crops
Slurp
Canopy

18. Crop Submodules AgPasture : A pasture growth model,
Based on the physiological model of Thornley & Johnston (2000),
Designed for the simulation of mixed pastures of C3 and C4 grasses and legumes,
Requirement: Micromet, Soil (SoilN and SoilWat or SWIM), Surface Organic Matter (SurfaceOM) and Fertiliser, and optionally Irrigation and pasture Managers.

19. Crop Submodules Canopy (Intercropping):
Simulates light and water competition between crops,
On a daily basis, finds the number of crops in the simulation and their canopy heights,
Canopy layers are then defined, with the layer boundaries being defined by the top of each canopy. Thus there are as many layers as canopies.

20. Crop Submodules Canopy (Intercropping):
Then each layer in turn is taken from the top, in the combine canopy, to get the combined (extinct_coeff * LAI) value of the canopies present in that layer.
The fraction of light transmitted out of the bottom of that layer can be calculated.
The total radiation intercepted in a layer is divided amongst the canopies occupying the layer, being done on the basis of (extinct_coeff * LAI) of each canopy.

21. Crop Submodules Canopy (Intercropping):
LAI is distributed with height in the canopy using normalized height and integration of a specific function.
This results in 47% of the leaf area in the top 10% of height, 27% in the next 10%, 15% in the next 10%, and so on.

22. Crop Submodules Growth:
A simplified plant growth module developed for simulating pasture and forestry systems module.
Major classes of biomass pools:
Growth pool responsible for most growth processes
Structural pool provides sinks for assimilate and nutrients and are used to describe plant properties such as plant height.

23. Crop Submodules Growth: Growth Calculation: : Daily Growth
: Daily intercepted solar radiation (MJ/m2)
: The light use efficiency (g/MJ)
: Growth modifiers for temperature
: Growth modifiers for nitrogen
: Growth modifiers for vapour pressure deficit
: Soil water supply

24. Crop Submodules Growth: Partitioning variation in root:shoot ratio
structural fraction of above-ground growth

25. Crop Submodules Plant :
Simulates the growth of a number of different species on a daily time-step (on an area basis not single plant).
Plant growth in this model responds to climate (temperature, rainfall and radiation from the Met module), soil water supply (from the Soilwat module) and soil nitrogen (from the SoilN module).

26. Crop Submodules Slurp:
a model for calculating soil water uptake by plants.
Inputs :
plant root (root length profile and extraction potential)
 canopy (live LAI, dead LAI, extinction coefficients and canopy height)

27. Crop Modules
Crops

28. dlt_dm = min(dlt_dm_water, dlt_dm_rue)
Crop Modules
Crops
Biomass accumulation
Water-nonlimiting
dlt_dm_rue = RUE *radiation_interception (1)
Water-limiting
dlt_dm_water = soil_ water_ supply * transpiration_efficiency (2)
dlt_dm = min(dlt_dm_water, dlt_dm_rue)

29. Soil Submodules
Eroison Daily soil erosion, and its effect on the soil profile
Map It maps simulation soil layers onto output layers
SoilN  The dynamics of both carbon and nitrogen in soil
SoilP The availability of phosphorus in soil
SoilTemp Soil temperature

30. Soil Submodules SoilWat The soil water balance model
Solute Solute balance model
Surfac Surface water conductivity changes with time
SurfaceOM The effect of surface organic matter
SWIM Infiltration and water movement in soil
WaterSupply The role of water-source for the Irrigate module

31. Soil Erosion Module Sub model 1: Freebarin E: Event soil loss (t/ha)
COV: Cover (%)
Q: Event runoff (mm)
K: Soil erodibility factor
LS: Slope length and steepness factor
P: Supporting practice factor
 Sine of slope angle
Length of catchment (m)

32. Soil Erosion Module Sub model 1: Rose E: Event soil loss (t/ha)
S: Sine of slope angle
cov: Fractional surface cover (0-1)
Q: Event runoff (mm)
λ: Factor approximating efficiency of entrainment
  λbare : Efficiency of entrainment (bare surface)
COV: Surface cover (%)

33. SoilN Module FOM - fresh organic matter (crop residues, dead roots)
BIOM – the more labile, soil microbial biomass
HUM – the bulk of soil organic matter

34. SoilN Module
Decomposition of Soil Organic Matter Pools

35. SoilTemp Module Method: 1- Heat storage in nodes
Air temperature
thermal conductance
heat storage
 boundary layer
depth
temperature
Method:
1- Heat storage in nodes
2- Resistance to heat transfer in layers
number of nodes
annual average soil temperature

36. SoilWat Module
The Water Balance INPUT = OUTPUT

37. Methods of water movement
SoilWat Module
Methods of water movement
Cascading Layer Richard ΄s equation
Daily time step

38. SoilWat Module The thickness of each layer by the user
100 or 150 mm the uppermost layer
300 or 500 mm the base of the profile
The whole profile by up to 10 or more layers

39. SoilWat Module
Processes represented in SOILWAT, adapted from water balances such as WATBAL and CERES, include:
Runoff: USDA curve number (CN) runoff model, include effect of :
soil water content
soil cover both from crop and crop residue
roughness due to tillage
Evaporation: based on potential evaporation
(Priestly/Taylor or Penman/Monteith)

40. SoilWat Module Saturated flow :
Swi+1 = Swi+1 + SWCONi x (SWi - DULi) for layer i, SWi > DULi
Unsaturated flow : Between LL and DUL, water can move between layers in proportion to the water content gradient.
Movement of solutes associated with saturated and unsaturated flow of water are calculated using a ‘mixing’ algoritm.

41. Met Module
The APSIM Met module provided daily meteorological information to all modules within an APSIM simulation.

42. Management Module
Fertilizer Effect of fertilizer application on a system
Irrigation Irrigation scheduling
Economics Maintains a cash balance through the simulation, which monitors all financial activity (e.g. income, expenses, loan repayments).

43. System Control
Manager Capability to specify a set of rules using conditional logic during simulations to control the actions of modules.
Clock Simulation time
Report Creates a columnar output file to record data from an APSIM simulation.