APSIM Agricultural Production Systems Simulator Mehrnoosh Eghtedari Decamber 2013 Introduction APSIM: is a modeling environment that uses various component modules to simulate cropping systems in the.
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Transcript APSIM Agricultural Production Systems Simulator Mehrnoosh Eghtedari Decamber 2013 Introduction APSIM: is a modeling environment that uses various component modules to simulate cropping systems in the.
APSIM
Agricultural Production Systems Simulator
Mehrnoosh Eghtedari
Decamber 2013
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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.
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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
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resources.
History of APSIM
In the early 1990s.
Commonwealth
Scientific and
Industrial Research
Organisation
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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.
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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.
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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.
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Combining with Different Models
CABALA: A model for predicting forest growth
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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.
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STRUCTURE of APSIM
(Mathematical-Mechanistic- Dynamic-Code based)
System Control
Manag
Manager
er
Clock
Report
Met
Canopy
Wheat
Maize
Crops
Sorghum
Legume
Other Crops
SoilN
SoilPH
Soil
SoilP
Erosion
Manure
Fertilize
Management
SoilWat
E
N
G
I
N
E
Irrigate
Climate
Residue
Economics
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APSIM Modules
Crop
Soil
Climate
Mangement
System Control
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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.
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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.
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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.
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Physiology of Yield Formation
Yield
HI
Dry Matter
Climate
RUE
Light
Interception
Soil
k
Leaf Area
Mangement
°C
Phenology
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Physiology of Yield Formation
Harvest Index × Dry Matter= Yield
HI = f(phenology, temperature, water,nutrients,
management)
(Grain Number x Grain size )/Dry Matter
HI
Linear function of biomass accumulation after anthesis
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AgPasture
Canopy
Growth
Crop
Modules
Slurp
Plant
Crops
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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.
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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.
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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.
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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.
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Crop Submodules
Growth:
A simplified plant growth module developed for
simulating pasture and forestry systems module.
Major classes of biomass pools:
1. Growth pool
responsible for most growth processes
2. Structural pool
provides sinks for assimilate and
nutrients and are used to describe plant properties such
as plant height.
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Crop Submodules
Growth:
Growth Calculation:
G Rint min(FT , FN , FVPD ) Fw
G : Daily Growth
Rint : Daily intercepted solar radiation (MJ/m2)
: The light use efficiency (g/MJ)
FT : Growth modifiers for temperature
FN : Growth modifiers for nitrogen
FVPD : Growth modifiers for vapour pressure deficit
Fw : Soil water supply
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Crop Submodules
Growth:
variation in root:shoot ratio
Partitioning
structural fraction of above-ground growth
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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).
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Crop Submodules
Slurp:
a model for calculating soil water uptake by plants.
Inputs :
a) plant root (root length profile and extraction potential)
b) canopy (live LAI, dead LAI, extinction coefficients and canopy
height)
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Crop Modules
Crops
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Crop Modules
Crops
Biomass accumulation
1. Water-nonlimiting
dlt_dm_rue = RUE *radiation_interception
2.
(1)
Water-limiting
dlt_dm_water = soil_ water_ supply * transpiration_efficiency (2)
dlt_dm = min(dlt_dm_water, dlt_dm_rue)
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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
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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
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Soil Erosion Module
Sub model 1: Freebarin
LS .K .P.Q
E (16.52 0.46COV 0.0031COV )
COV 50%
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LS .K .P.Q
E (0.0254COV 2.54)
COV 50%
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E: Event soil loss (t/ha)
COV: Cover (%)
Q: Event runoff (mm)
Sine of slope angle
K: Soil erodibility factor
Length of catchment (m)
LS: Slope length and steepness factor
P: Supporting practice factor
2
LS (65.41S 2 4.56 S 0.065 )(
L 0.6 (1exp( 35 S ))
)
22.1
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Soil Erosion Module
Sub model 1: Rose
E 2700 S (1 cov)
Q
100
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
bare e
0.15 cov
λbare : Efficiency of entrainment (bare surface)
COV: Surface cover (%)
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SoilN Module
FOM - fresh organic matter (crop residues, dead roots)
BIOM – the more labile, soil microbial biomass
HUM – the bulk of soil organic matter
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SoilN Module
Decomposition of Soil Organic Matter Pools
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SoilTemp Module
Air temperature
heat storage
thermal conductance
boundary layer
depth
temperature
Method:
1- Heat storage in
nodes
2- Resistance to heat
transfer in layers
number of nodes
annual average soil temperature
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SoilWat Module
The Water Balance
INPUT = OUTPUT
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SoilWat Module
Methods of water movement
Cascading Layer
Richard ΄s equation
Daily time step
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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
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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 :
a. soil water content
b. soil cover both from crop and crop residue
c. roughness due to tillage
Evaporation: based on potential evaporation
(Priestly/Taylor or Penman/Monteith)
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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.
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Met Module
The APSIM Met
module
provided
daily meteorological
information to all
modules within an
APSIM simulation.
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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).
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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.
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