Agricultural Production Systems
Simulator (APSIM)
Simulates:
 yield of crops, pastures, trees, weeds
...
 key soil processes (water, N, P,
carbon, pH)
 surface residue dynamics & erosion
 range of management options
 crop rotations + fallowing +
mixtures
 short or long term effects
 one or two dimensions
 high software engineering standards
 BUT, not yet pests nor diseases
APSIM - developmental goals
 Production

 Fate

sought to retain yield prediction in relation to
management options and environment (c/f - CERES,
CROPGRO models)
of the soil resource
sought valid long-term simulation of key soil processes
(c/f - CENTURY, EPIC)
 Impacts

and profit
off-farm
predict loss of soil, water, nutrients off-site (c/f - EPIC)
APSIM - some statistics

Development team
7 programmers / model support staff
 12 scientist / modellers


User base
180 licensed users
 9 countries, 4 continents


Product Suite
ca. 450,000 lines of code
 4 languages
 38 modules
 12 interfaces or major tools

Developing our knowledge &
capability - APSIM modules
Crop/pasture/tree
wheat
sorghum
sugarcane
chickpea
mungbean
soybean
barley
groundnut
maize
sunflower
hemp
lucerne
fababean
canola
lupin
mucuna
cowpea
Pinus radiata
Eucalyptus sp.
cotton - CSIRO PI
pearl millet - ICRISAT
pigeonpea - ICRISAT
Soil
SoilWat
SWIM
SoilN
SoilP
SoilpH
Solute
Residue
Manure - ICRISAT
Management
Sowing
Tillage
Irrigate
Fertilize
Intercrop/mixture competition
Multiple user interfaces –
e.g. APSFront interface
APSIM has been used to
simulate …
Some examples
…physiological processes
IC P L 87
180
15
160
14
140
120
13
100
80
12
60
40
11
IC R IS A T 1 9 9 0 / 9 1
20
IC R IS A T 1 9 9 2
H is s a r - 1 s t flo w e rin g
0
10
0
50
100
150
200
250
300
350
Da y o f y e a r
Pigeonpea qualitative photoperiod response
400
Dayle ngth (h)
Flow e ring tim e (DAS)
c rit ic a l p h o t o p e rio d
…plant organs
T ille rs
T o ta l
5
4 .5
4 .5
4 .5
4
4
4
3 .5
3 .5
3 .5
3
3
3
2 .5
L ai
5
L ai
L ai
M a in s te m
5
2 .5
2 .5
2
2
2
1 .5
1 .5
1 .5
1
1
1
0 .5
0 .5
0 .5
0
0
160
210
260
D ay
310
0
160
210
260
D ay
Tiller leaf area in millet
310
160
210
260
D ay
…crop growth & development
8
14000
tla i
7
L AI
B IO M AS S
To ta l D W
la i
12000
to t_ b io m
la i
6
b io m a s s
10000
s la i
5
8000
4
6000
3
4000
2
2000
1
0
0
0
20
40
60
80
100
120
140
160
180
200
450
0
20
40
60
80
100
120
140
160
180
200
120
140
160
180
200
14000
Leaf No.
400
L E AF NO
G RAIN D W
yie ld
12000
Node No.
g ra in_ w t
350
g re e n_ le a ve s
10000
300
no d e _ no
8000
250
le a f_ no
200
6000
150
4000
100
2000
50
0
0
0
50
100
150
200
0
20
40
60
80
100
Growth & development of pigeonpea
…yield of experimental crops
Chickpea
Cowpea
1200
yields
4500
2500
1:1 line
300
Grain (g/m2)
0
300
600
900
1200
Observed
Prediction
wheat grain
maize grain
chickpea grain
mungbean grain
cowpea grain
stylo biomass
3500
3000
2500
2000
1500
y = 0.87x + 221.44
R2 = 0.77
1000
Biomass (g/m2)
0
Predicted
Predicted
Predicted
600
500
0
0
1000
2000
3000
4000
5000
y = 1.0631x - 70.964
2000
R2 = 0.7924
1500
1000
500
0
0.0
43
111
60
47
15
63
regression line
slope
1.07
0.98 ( 0.04)
0.90 ( 0.07)
1.07 ( 0.10)
0.93 ( 0.08)
0.84 ( 0.06)
500.0
1000.0
1500.0
2000.0 2500.0
Observed
Observed
n
1:1 line
regression
4000
900
Mungbean
3000
5000
R2
intercept
-13.0
-5.5 ( 240)
163 ( 172)
-27.2 ( 128)
-31.6 ( 34.6)
-131.7 ( 171)
0.79
0.85
0.76
0.72
0.91
0.78
3000.0
…yield of commercial crops
Simulated v's farm yields
10

APSIM tested
against data from
commercial farms

Crops include
cotton, sorghum,
mungbean, wheat,
chickpea
9
8
Simulated yield (/ha)
7
6
5
4
3
SORGHUM
2
COTTON
MUNGBEAN
1
1:1 line
0
0
1
2
3
4
5
6
Farm yield (/ha)
7
8
9
10
… yield of smallholder crops
Maize response to N in Malawi
Maize response to N & manure in Kenya
Maize Grain Yield (Kenya, on-farm expts)
G ra in y ie ld (k g /h a )
4000
7000
3500
Predicted (k g/ha)
5000
4000
3000
2000
3000
2500
Clay SR97
Sand LR97
2000
1:1 line
Clay SR96
1500
1000
Sand SR96
500
1000
0
0
0
0
1000
2000
3000
4000
5000
6000
7000
1000
2000
3000
4000
Measured (k g/ha)
O bse rv e d
Maize response to N at Makoholi
B io m a s s a t m a tu rity (k g /h a )
Biomass at maturity (kg/ha)
14000
8000
12000
7000
10000
6000
8000
5000
Predicted
S im u lated
S imulate d
6000
6000
4000
4000
3000
2000
2000
0
1000
0
2000
4000
6000
8000
O b s e rv e d
10000
12000
14000
1:1 line
0
0
1000 2000 3000 4000 5000 6000 7000 8000
O bserved
1992-9
1991-92
5000
G rain yield (t/ha)
G rain yield (t/ha)
5000
4000
4000
… N response in smallholder crops
3000
2000
1000
3000
2000
1000
0
0
-10
10
30
50
-10
70
Nitrogen a
Nitrogen applied (kg/ha)
1992-93
1991-92
2000
1000
4000
3000
2000
1000
0
-1 0
10
30
50
-1 0
70
Nitro g e n ap p lie d (kg /ha)
1993-94
10
4000
3000
2000
1000
0
50
30
5000
G rain yield (t/ha)
3000
-10
Nitro g e n ap p lie d (kg /ha)
1000
3000
2000
1000
0
0
-1 0
10
30
50
-1 0
70
30
50
2000
1000
-10
70
10
30
3000
2000
1000
0
50
1996-9
5000
4000
-10
Nitro g e n ap p lie d (kg /ha)
Nitro g e n ap p lie d (kg /ha)
70
10
30
50
4000
3000
2000
1000
0
-10
70
1995-96
1996-97
3000
2000
1000
0
-1 0
10
30
50
Nitro g e n ap p lie d (kg /ha)
70
5000
4000
G rain yield (t/ha)
Grain yield (t/ha)
Grain yield (t/ha)
1997-98
5000
4000
10
Nitrogen a
Nitrogen applied (kg/ha)
5000
10
Nitrogen a
G rain yield (t/ha)
2000
3000
1995-96
5000
4000
G rain yield (t/ha)
Grain yield (t/ha)
3000
Testing
simulation of
maize response to
N at Makoholi
over 7 seasons
1991-1997
Nitrogen applied (kg/ha)
5000
4000
4000
0
70
10
1994-95
5000
1994-9
5000
G rain yield (t/ha)
4000
0
Grain yield (t/ha)
1993-94
5000
Grain yield (t/ha)
Grain yield (t/ha)
5000
10
3000
2000
1000
0
-1 0
10
30
50
Nitro g e n ap p lie d (kg /ha)
70
4000
3000
2000
1000
0
-10
10
30
50
Nitrogen applied (kg/ha)
70
… seasonal perspectives
Cumulative probability
1.00
0.80
0.60
0.40
0.20
-20
0.00
0
-10
10
20
30
40
50
60
70
Grain yield response to 30 kgN (kg grain/kg N)
How representative were the seasons 91-98 at Makoholi?
Average of Yield
… yield of crops in rotation
7000
6000
Lines = predicted
5000
4000
Symbols = observed
Sorghum
Wheat
w _yield
3000
2000
1000
0
15-Jun-94
s_yield
15-Jun-95
14-Jun-96
14-Jun-97
Average of LAI
6
Wheat
4
3
2
w _lai
1
s_lai
0
15-Jun-94
2000
Average of Biomass
Sorghum
5
15-Jun-95
14-Jun-96
14-Jun-97
Sorghum
Wheat
1500
1000
w_biomass
500
0
15-Jun-94
s_biomass
15-Jun-95
14-Jun-96
14-Jun-97
Wheat-Sorghum Long Fallow rotation
… soil water of crops in rotation
240
220
Total Soil Water (0.1-0.5 m)
mm
200
180
160
140
120
100
240
80
220
Total Soil Water (0.5-0.9 m)
200
mm
180
160
140
120
240
100
220
Total Soil Water (0.9-1.3 m)
mm
80
200
180
160
140
mm
120
240
100
220
80
200
180
160
Total Soil Water (1.3-1.7 m)
Wheat
Sorgham
140
120
100
80
Wheat-Sorghum Long Fallow rotation
7/08/94
8/08/94
9/08/94
10/08/94
11/08/94
12/08/94
13/08/94
14/08/94
15/08/94
16/08/94
17/08/94
18/08/94
19/08/94
20/08/94
21/08/94
22/08/94
… ET of crops in rotation
450
Rain
Measured ET
Predicted ET
Rain / Evaporation (mm)
400
350
300
250
200
150
100
50
0
01-Apr- 30-Sep- 01-Apr- 30-Sep- 01-Apr- 30-Sep- 31-Mar- 29-Sep- 31-Mar- 29-Sep- 31-Mar- 29-Sep93
93
94
94
95
95
96
96
97
97
98
98
Date
93 Wheat, 94-97 Lucerne measured in lysimeter
… legume rotation effects
Maize response (TBM) to fertiliser N following pigeonpea, India
Vertisol
Predicted
16000
Alfisol
Measured
14000
12000
12000
10000
10000
8000
8000
6000
6000
4000
4000
2000
2000
0
0
P20_N0
P20_N40
P20_N80
Predicted
16000
14000
Measured
P20_N0
P20_N40
P20_N80
… consequence of crop
rotations
Summary of crop contribution
Cumulative drainage
$400
1,200.00
W_W__S
$350
$300
drainage
W_WM_SC
WS__C
$250
Drainage (mm)
Gross margin ($/ha/yr )
$GM
W_W__SC
1,000.00
$200
$150
$100
800.00
W__S_S
W_W
W_W__S_S
600.00
W_WS_S
400.00
$50
200.00
_S
19
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
19
83
19
81
19
79
Rotation
19
77
0.00
19
75
S_
S
W
_W
S
W
_W
W
_W
__
S_
S
W
__
__
C
W
S
_S
C
SC
W
_W
M
W
_W
__
W
_W
__
S
$0
Year
Wheat1
Wheat2
Mungbean
Sorghum
Chickpea
Sorghum2
wheat_wheat/mungbean_sorghum/chickpea
7000
5000
Sorgh
Chickp
Mungb
4000
3000
2000
1000
0
19
72
19
73
19
74
19
75
19
75
19
76
19
77
19
78
19
79
19
79
19
80
19
81
19
82
19
83
19
83
19
84
19
85
19
86
19
87
19
87
19
88
19
89
19
90
19
91
19
91
19
92
19
93
19
94
19
95
19
95
19
96
19
97
19
98
19
9
Grain yield (kg/ha)
6000
wheat-wheat-mungbeansorghum-chickpea rotation
Whea
Year
… soil organic matter changes
Total Soil N (0-20 cm)
2200
1800
1400
Cropping 0 kg N/ha
Cropping 40 kg N/ha
Cropping 80 kg N/ha
1000
Lucerne Rotation
600
0
10
20
30
40
50
60
70
80
90
Years of cropping
Farming systems on a vertisol at Dalby, Qld.
100 110
…crop-weed competition
24000
4
B io m a s s
LA I
3
LAI
Dr y w e ight
18000
12000
2
6000
1
0
0
352
12
37
62
87
112
352
12
Maize – volunteer stylo
37
62
87
112
…response to manure application
S h o r t r a in s
3000
3000
2500
g rain yie ld (kg /h a)
g rain yie ld (kg /h a)
2500
Lo n g r a in s
2000
1500
1000
F e rtilis e r
H Q m a n u re
500
2000
1500
1000
500
L Q m a n u re
0
0
0
50
100
N r a te (k g /h a )
150
0
50
100
150
N r a te (k g /h a )
High & low quality manure applied to maize
… response to N, P fertilizer
& manure
Maize response to P rates in Kenya
Biomass (g/m2)
1200
P0
P40
Response to N, P and manure, India
P10
Pnon-lim
Vertisol
12000
1000
Biom ass (kg/ha)
10000
800
600
400
Measured
Predicted
8000
6000
4000
2000
200
1990.4
1990.6
Nx
P
N8
0
P2
0
an
_B
1990.2
M
1990
Co
nt
ro
l
M
an
_A
0
1989.8
0
… “on-farm” constraints
Agronomic efficiency
(kg grain / kg N)
70
Response to 36 kg N/ha
60
50
40
30
20
10
0
Optimal
agronomy /
deep soil
Good
agronomy /
shallow soil
+ weed
pressure
+ late
sowing
+ low Plant
population
… agroforestry systems
Enabling landholder assessment of the productivity and risk of commercial
agroforestry investment on grain farms in Australia’s medium to low rainfall
regions
Zones of influence in an agroforestry system
II
III
90
30
60
25
Stem
Branch
20
Foliage
50
15
40
30
10
20
5
10
0
1982
1984
1986
Year
0
1988
0
Wheat Yield (kg/ha)
70
Foliage weight (t/ha)
Stem/branch wt (t/ha)
80
IV
Simulated wheat yields in zone III
Mean, biggest & smallest responses
Simulated wheat yields in zone II
5m high windbreak, 150mm in-crop rain
5000
5000
4000
4000
Grain yield (kg/ha)
I
Simulated tree growth in zone I
3000
2000
1000
3000
2000
mean
1980
1978
1000
0
0
5
Grain
yield
0
1
2
3
4
10
15
Distance from trees (H)
5
20
Distance from windbreak (tree heights)
0
25
10
20
Distance from trees (H)
… change in wheat production
under climate change
Yield response (%)
50
40
Rainfall
change
30
20%
0%
20
-20%
10
0
0
1
2
3
-10
Temperature increase (o C)
4
… but can you use such technical
information with farmers?
YES…but the information needs to
be made relevant to farmers’ realities
Source: Peter Carberry
CSIRO, Australia
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