P.Steduto.pdf
Transcript of P.Steduto.pdf
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AquaCrop
A new model for crop prediction
under water deficit conditionsPasquale STEDUTO1, Theodore C. HSIAO2, Elias FERERES3,
Dirk RAES4, Lee HENG5, G. Izzi1 and J. Hoogeven1
Drought Management: Scientific and technological innovationsZaragoza, SPAIN, 12-14 June, 2008
1 Land and Water Division, FAO, United Nations, Rome, Italy2 Dept. of Land, Air and Water Resources, Univ. of California, Davis, USA3 IAS-CSIC and Univ. of Cordoba, Spain4 Dept. of Land Management and Economics, K. Univ. Leuven, Belgium5 Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture,
IAEA, Vienna, Austria
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Background
Revision of the 1979 FAO I & D Paper no.33,
Yield Response to Water
Consultative process with experts
Separation between herbaceous-crops andtrees: AquaCrop & Guidelines
AquaCrop as one model with crop-specific
parameters
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Evolution from Paper 33
(b)(a)
=
x
axy
x
ax
ET
ETET
Y
YYk
CanopyCanopy
TranspirationTranspiration
(c)
(a) (b)
BIOMASSBIOMASS
CropCropEvapotEvapotranspirationranspiration
YIELDYIELD(c)
EHI
Paper 33Paper 33
{AquaCropAquaCrop
long-term sums
daily time-steps
Ky
WP
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Atmosphere
Soil
Crop
AquaCrop Conceptual Framework
Manag
ement
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CLIMATE
Rain
AquaCrop Conceptual Framework | Atmosphere
RS, T, RH, u
ETo
T (oC) CO2
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T (oC) Es TaETo
Phenology Canopy CoverLeaf expansion gs
Senescence
Biomass
WP
YieldHI
Rooting depth
AquaCrop Conceptual Framework | Crop
CO2
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Canopy Cover (CC)
CGC
CCx
start of canopy senescence
time to harvest
canopy
cover
timetime to full canopy
CDC
CCo
CC follows the exponential
growth during the first halfof the full development (Eq. 1)
and an exponential decay
during the second half of thefull development (Eq. 2)
tCGCoeCCCC
= (1) tCGCoxx
e)CCCC(CCCC = (2)
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WPWater Productivity
(g m-2 mm-1)
=
CT
BiomassWP
(g m-2)
)2000(COO
C
*
2
ETT
BiomassWP
=
ETc (mm x 1000)0.0 0.3 0.6 0.9
Biomass
(kgm
-2)
0
1
2
3Sorghum
Sunflower
Chickpea
Wheat
CT (ETc/ETo)0 40 80 120 160
Biomas
s
(kgm-2)
0
1
2
3SorghumSunflowerChickpeaWheat
)ET/T( OC
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Soil water (& salt) balance
Infiltration
UptakeRedistribution
Runoff
Rain
KsEs Ta
AquaCrop Conceptual Framework | Soil
deeppercolationcapillaryrise
Leaf expansiongs
Senescence
WP
HI
Texture 1
Texture 2Texture
Ksat
FCPWP
Irrig.
Runoff
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Stresses
Ks for leaf expansion, maize
Ksfor stomata, maize
Ks for senescence, maize
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Field Management
Water Management
Fertility level (non-limiting; moderate; poor)
Field-surface practices (mulching; soil bunds)
Rainfed
User defined schedule (timing and depth) Model-generated schedule (fixed interval; fixed depth;
% of RAW) Irrigation method (drip; sprinkler;
surface basin; border; furrow)
Irrigation
AquaCrop Conceptual Framework | Management
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AquaCrop Flow-Chart
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AquaCrop Tests
Wheat
TexasTexas
KansasKansas
SardiniaSardinia
QuzhouQuzhou
LuanchengLuancheng
FengquiFengqui
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China Quzhou Wheat 98-99
0
5
10
15
20
25
30
35
40
0 50 100 150 200 250DAP
Bio
mass(t/ha)
China Quzhou Wheat 98-99
-20
-10
0
10
20
30
40
0 50 100 150 200
DAP
MinandMaxTemper
ature(oC)
China Quzhou Wheat 98-990
25
50
75
100
0 50 100 150 200 250
DAP
CanopyCover(%
)
YieldYield
(ton ha(ton ha--11
))
MeasuredMeasured SimulatedSimulated
6.726.72 6.506.50 3%3%
China
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0
5
10
15
20
25
30
35
40
0 50 100 150 200 250
DAP
Bio
mass(t/ha)
China Quzhou Wheat 99-00
China Quzhou Wheat 99-00
-20
-10
0
10
20
30
40
1 31 61 91 121 151 181 211
DAP
MinandMaxTemperature(oC)
0
25
50
75
100
0 50 100 150 200 250
DAP
CanopyCover(%
)
China Quzhou Wheat 99-00
YieldYield
(ton ha(ton ha--11
))
MeasuredMeasured SimulatedSimulated
6.226.22 7.097.09 14%14%
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Maize
TexasTexas
CaliforniaCalifornia
FloridaFlorida
SpainSpainQuzhouQuzhou
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I55 treatment biom ass
0
500
1000
1500
2000
2500
3000
0 20 40 60 80 100 120 140
DAP
cumD
M
(g/m2)
DM
Biomass
Treatments:
Irrigated (I)Rainfed (NI)
Irrig. day 55 onward (I55)
I
NII55
Biomass
24.3
16.821.2
Yield
11.4
5.210.3
NI treatm ent biom as s
0
500
1000
1500
2000
2500
3000
0 20 40 60 80 100 120 140
DAP
cumD
M
(g/m2)
DM
Biomass
I55 (IRR on Day55) tr eatm ent Ground Cove r
0
20
40
60
80
100
0 20 40 60 80 100 120 140
DAP
GC(%)
Calc GC
CC
22.7
16.822.4
10.8
6.210.6
measured
simulated
California
NI (No IRR) tr eatm ent Ground Cover
0
1020
30
40
50
60
70
80
90
100
0 20 40 60 80 100 120 140
DAP
GC(%)
Calc GC
CC
I treatm ent biom ass
0
500
1000
1500
2000
2500
3000
0 20 40 60 80 100 120 140
DAP
cumD
M
(g/m2)
DM
Biomass
I (Full IRR) treatm ent Ground Cover
0
20
40
60
80
100
0 20 40 60 80 100 120 140
DAP
GC(%)
Calc GC
CC
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Cotton
SpainSpainTexasTexas
GreeceGreece
TurkeyTurkey
SyriaSyria
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0
20
40
60
80
100
0 20 40 60 80 100 120 140 160
DAS
GC
(%)
Measur
Model
0
2
4
6
8
10
12
14
0 2 4 6 8 10 12 14
Obser ved (t ha-1)
Simulated(tha-1)
Yield
Biomass
1:1
Cordoba (SPAIN)Cordoba (SPAIN)
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Conclusions
AquaCrop is explicit and mostly intuitive, and maintains anoptimum balance between simplicity, accuracy and robustness
AquaCrop differs from other models for being water-driven,and for its relatively small number of parameters
AquaCrop is aimed at practical end-users, as those in farmers
and irrigation associations, extension services, governmentalagencies and NGOs, for devising water management and savingstrategies
AquaCrop is also particularly suited for perspective studies(e.g., under different climate change scenarios)
AquaCrop is also aimed at planners and economists who needestimates of production for given amounts of water
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Thank You
www.fao.org/nr/water