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 and profit sought to retain yield prediction in relation to
management options and environment (c/f - CERES, CROPGRO models)
Fate of the soil resource sought valid long-term simulation of key soil
processes (c/f - CENTURY, EPIC)
Impacts 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/treewheatsorghumsugarcane chickpeamungbean soybeanbarley groundnutmaizesunflowerhemp lucernefababean canolalupin mucunacowpea Pinus radiata Eucalyptus sp.
cotton - CSIRO PIpearl millet - ICRISATpigeonpea - ICRISAT
Soil SoilWatSWIMSoilNSoilP
SoilpHSolute
ResidueManure - ICRISAT
ManagementSowingTillageIrrigateFertilize
Intercrop/mixture competition
Multiple user interfaces –e.g. APSFront interface
APSIM has been used to simulate …
Some examples
Pigeonpea qualitative photoperiod response
ICPL87
0
20
40
60
80
100
120
140
160
180
0 50 100 150 200 250 300 350 400
Day of year
Flo
we
rin
g t
ime
(D
AS
)
10
11
12
13
14
15
Dayle
ng
th (
h)
ICRISAT 1990/91Hissar - 1st floweringICRISAT 1992
critical photoperiod
…physiological processes
…plant organs
Main stem
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
160 210 260 310
Day
La
i
Tillers
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
160 210 260 310
Day
La
i
Total
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
160 210 260 310Day
La
iTiller leaf area in millet
…crop growth & development
GRAIN DW
0
2000
4000
6000
8000
10000
12000
14000
0 20 40 60 80 100 120 140 160 180 200
yield
grain_wt
BIOMASS
0
2000
4000
6000
8000
10000
12000
14000
0 20 40 60 80 100 120 140 160 180 200
Total DW
tot_biom
biomass
LEAF NO
0
50
100
150
200
250
300
350
400
450
0 50 100 150 200
Leaf No.
Node No.
green_leaves
node_no
leaf_no
LAI
0
1
2
3
4
5
6
7
8
0 20 40 60 80 100 120 140 160 180 200
tlai
lai
lai
slai
Growth & development of pigeonpea
Cowpea
0
300
600
900
1200
0 300 600 900 1200
Observed
Pre
dic
ted
1:1 line
Grain (g/m2)
Biomass (g/m2)
Chickpea
y = 0.87x + 221.44R2 = 0.77
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
0 1000 2000 3000 4000 5000
Observed
Pre
dic
ted
Mungbean
y = 1.0631x - 70.964
R2 = 0.7924
0
500
1000
1500
2000
2500
3000
0.0 500.0 1000.0 1500.0 2000.0 2500.0 3000.0
yields
1:1 line
regression
Pre
dic
ted
Observed
Prediction n regression line R2
slope interceptwheat grain 43 1.07 -13.0 0.79maize grain 111 0.98 ( 0.04) -5.5 ( 240) 0.85chickpea grain 60 0.90 ( 0.07) 163 ( 172) 0.76mungbean grain 47 1.07 ( 0.10) -27.2 ( 128) 0.72cowpea grain 15 0.93 ( 0.08) -31.6 ( 34.6) 0.91stylo biomass 63 0.84 ( 0.06) -131.7 ( 171) 0.78
…yield of experimental crops
…yield of commercial crops
APSIM tested against data from commercial farms
Crops include cotton, sorghum, mungbean, wheat, chickpea
Simulated v's farm yields
0
1
2
3
4
5
6
7
8
9
10
0 1 2 3 4 5 6 7 8 9 10
Farm yield (/ha)
Sim
ula
ted
yie
ld (
/ha)
SORGHUM
COTTON
MUNGBEAN
1:1 line
… yield of smallholder crops
Grain yield (kg/ha)
0
1000
2000
3000
4000
5000
6000
7000
0 1000 2000 3000 4000 5000 6000 7000
O bserved
Sim
ula
ted
Biomass at maturity (kg/ha)
0
2000
4000
6000
8000
10000
12000
14000
0 2 0 0 0 4 0 0 0 6 0 0 0 8 0 0 0 1 0 0 0 0 1 2 0 0 0 1 4 0 0 0
Observed
Sim
ula
ted
Maize Grain Yield (Kenya, on-farm expts)
0
500
1000
1500
2000
2500
3000
3500
4000
0 1000 2000 3000 4000
Measured (kg/ha)
Pred
icte
d (k
g/h
a)
Clay SR97
Sand LR97
1:1 line
Clay SR96
Sand SR96
Maize response to N in Malawi Maize response to N & manure in Kenya
Biomass at maturity (kg/ha)
0
1000
2000
3000
4000
5000
6000
7000
8000
0 1000 2000 3000 4000 5000 6000 7000 8000
Observed
Pre
dic
ted
1:1 line
Maize response to N at Makoholi
… N response in smallholder crops
1991-92
0
1000
2000
3000
4000
5000
-10 10 30 50 70
Nitrogen applied (kg/ha)
Gra
in y
ield
(t/ha) 1992-93
0
1000
2000
3000
4000
5000
-10 10 30 50 70
Nitrogen applied (kg/ha)
Gra
in y
ield
(t/ha)
1993-94
0
1000
2000
3000
4000
5000
-10 10 30 50 70
Nitrogen applied (kg/ha)
Gra
in y
ield
(t/ha) 1994-95
0
1000
2000
3000
4000
5000
-10 10 30 50 70
Nitrogen applied (kg/ha)
Gra
in y
ield
(t/ha)
1995-96
0
1000
2000
3000
4000
5000
-10 10 30 50 70
Nitrogen applied (kg/ha)
Gra
in y
ield
(t/ha) 1996-97
0
1000
2000
3000
4000
5000
-10 10 30 50 70
Nitrogen applied (kg/ha)
Gra
in y
ield
(t/ha)
1997-98
0
1000
2000
3000
4000
5000
-10 10 30 50 70G
rain
yie
ld (
t/ha)
Testing simulation of maize response to N at Makoholi over 7 seasons 1991-1997
… seasonal perspectives
0.00
0.20
0.40
0.60
0.80
1.00
-20 -10 0 10 20 30 40 50 60 70
Grain yield response to 30 kgN (kg grain/kg N)
Cum
ulat
ive
prob
abili
ty
How representative were the seasons 91-98 at Makoholi?
… yield of crops in rotation
Lines = predicted
Symbols = observed
0
1000
2000
3000
4000
5000
6000
7000
15-Jun-94 15-Jun-95 14-Jun-96 14-Jun-97
Ave
rag
e o
f Y
ield
Sorghum
Wheat
w _yield
s_yield
0
1
2
3
4
5
6
15-Jun-94 15-Jun-95 14-Jun-96 14-Jun-97
Ave
rag
e o
f L
AI
Sorghum
Wheat
w _lai
s_lai
0
500
1000
1500
2000
15-Jun-94 15-Jun-95 14-Jun-96 14-Jun-97
Ave
rag
e o
f B
iom
ass Sorghum
Wheat
w_biomass
s_biomass
Wheat-Sorghum Long Fallow rotation
7/08/948/08/949/08/94
10/08/9411/08/9412/08/9413/08/9414/08/9415/08/9416/08/9417/08/9418/08/9419/08/9420/08/9421/08/9422/08/9423/08/94
Total Soil Water (0.1-0.5 m)
80
100
120
140
160
180
200
220
240
mm
Total Soil Water (0.5-0.9 m)
80
100
120
140
160
180
200
220
240
mm
Total Soil Water (0.9-1.3 m)
80
100
120
140
160
180
200
220
240
mm
Total Soil Water (1.3-1.7 m)
80
100
120
140
160
180
200
220
240
mm Wheat Sorgham
… soil water of crops in rotation
Wheat-Sorghum Long Fallow rotation
0
50
100
150
200
250
300
350
400
450
01-Apr-93
30-Sep-93
01-Apr-94
30-Sep-94
01-Apr-95
30-Sep-95
31-Mar-96
29-Sep-96
31-Mar-97
29-Sep-97
31-Mar-98
29-Sep-98
Date
Rai
n /
Eva
po
rati
on
(m
m)
RainMeasured ETPredicted ET
93 Wheat, 94-97 Lucerne measured in lysimeter
… ET of crops in rotation
… legume rotation effects
Vertisol
0
2000
4000
6000
8000
10000
12000
14000
16000
P20_N0 P20_N40 P20_N80
Measured
Predicted
Alfisol
0
2000
4000
6000
8000
10000
12000
14000
16000
P20_N0 P20_N40 P20_N80
Measured
Predicted
Maize response (TBM) to fertiliser N following pigeonpea, India
… consequence of crop rotations
Summary of crop contribution
$0
$50
$100
$150
$200
$250
$300
$350
$400
W_W
__S
W_W
__SC
W_W
M_S
C
WS__
C
W__
S_SW
_W
W_W
__S_S
W_W
S_S
Rotation
Gro
ss
ma
rgin
($
/ha
/yr)
Wheat1 Wheat2 Mungbean Sorghum Chickpea Sorghum2
wheat_wheat/mungbean_sorghum/chickpea
0
1000
2000
3000
4000
5000
6000
7000
1972
1973
1974
1975
1975
1976
1977
1978
1979
1979
1980
1981
1982
1983
1983
1984
1985
1986
1987
1987
1988
1989
1990
1991
1991
1992
1993
1994
1995
1995
1996
Year
Gra
in y
ield
(kg
/ha)
Cumulative drainage
0.00
200.00
400.00
600.00
800.00
1,000.00
1,200.00
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
Year
Dra
inag
e (m
m)
W_W__S
W_W__SC
W_WM_SC
WS__C
W__S_S
W_W
W_W__S_S
W_WS_S
$GM drainage
wheat-wheat-mungbean-sorghum-chickpea rotation
… soil organic matter changes
Total Soil N (0-20 cm)
600
1000
1400
1800
2200
0 10 20 30 40 50 60 70 80 90 100 110Years of cropping
Cropping 0 kg N/ha
Cropping 40 kg N/ha
Cropping 80 kg N/ha
Lucerne Rotation
Farming systems on a vertisol at Dalby, Qld.
…crop-weed competition
0
1
2
3
4
352 12 37 62 87 112
LA
I
LAI
0
6000
12000
18000
24000
352 12 37 62 87 112
Dry
we
igh
t
Biomass
Maize – volunteer stylo
0
500
1000
1500
2000
2500
3000
0 50 100 150
N rate (kg /ha)
grai
n yi
eld
(kg/
ha)
Fertiliser
HQ manure
LQ manure
Short rains
0
500
1000
1500
2000
2500
3000
0 50 100 150
N rate (kg /ha)
grai
n yi
eld
(kg/
ha)
Long rains
…response to manure application
High & low quality manure applied to maize
… response to N, P fertilizer & manure
Biomass (g/m2)
0
200
400
600
800
1000
1200
1989.8 1990 1990.2 1990.4 1990.6
P0 P10
P40 Pnon-lim
Maize response to P rates in Kenya Response to N, P and manure, India
Vertisol
0
2000
4000
6000
8000
10000
12000
Bio
mas
s (
kg
/ha)
Measured
Predicted
0
10
20
30
40
50
60
70
Optimalagronomy /deep soil
Goodagronomy /shallow soil
+ weedpressure
+ latesowing
+ low Plantpopulation
Ag
rono
mic
effi
cie
ncy
(kg
gra
in /
kg N
)
… “on-farm” constraints
Response to 36 kg N/ha
Enabling landholder assessment of the productivity and risk of commercial agroforestry investment on grain farms in Australia’s medium to low rainfall
regions
Simulated wheat yields in zone IIIMean, biggest & smallest responses
0
1000
2000
3000
4000
5000
0 10 20
Distance from trees (H)G
rain
yie
ld (k
g/ha
)
mean
1980
1978
Simulated wheat yields in zone II5m high windbreak, 150mm in-crop rain
0
1000
2000
3000
4000
5000
0 1 2 3 4 5Distance from trees (H)
Whe
at Y
ield
(kg/
ha)
Simulated tree growth in zone I
0
10
20
30
40
50
60
70
80
90
1982 1984 1986 1988
Year
Ste
m/b
ranc
h w
t (t/h
a)
0
5
10
15
20
25
30
Folia
ge w
eigh
t (t/h
a)
Stem
Branch
Foliage
Zones of influence in an agroforestry system
0 5 10 15 20 25
Distance from windbreak (tree heights)
I II III IV
Grain yield
… agroforestry systems
-10
0
10
20
30
40
50
0 1 2 3 4
Temperature increase (oC)
Yie
ld r
esp
on
se (
%)
20%
0%
-20%
Rainfall change
… change in wheat production under climate
change
… 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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