Simulation of tea yield with AquaCrop...Apr 30, 2013 · unit ground surface soil surface covered...
Transcript of Simulation of tea yield with AquaCrop...Apr 30, 2013 · unit ground surface soil surface covered...
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Simulation of tea yield
with AquaCrop Dirk RAES, KU Leuven University, Leuven Belgium Patricia MEJIAS, FAO, Land and Water Division, Rome, Italy Samson KAMUNYA, John BORE, Beatrice CHESEREK, Paul KIPRONO, David KAMAU, Tea Research Foundation of Kenya Aziz Elbehri, FAO, Land and Water Division, Rome, Italy
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Climate Change and the Tea Sector in Kenya: Impact Assessment and Policy Action
National Multi-stakeholder Workshop 29-30 April 2013, Naivasha
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1. Calculation scheme
Crop development
Crop transpiration
Biomass production
Yield formation
Structure of the presentation
2. Running simulations
Experimental fields
Farmer’s fields
Effect of climate change
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Instead of Leaf Area Index (LAI)
AquaCrop uses green canopy cover (CC)
CC = soil surface covered by the green canopy
unit ground surface area
ranges from 0 (bare soil) to 1 (full canopy cover)
0 % 100 %
unit ground surface
soil surface covered by green canopy
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CC = 25 %
CC = 95 %
Lung pruning
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Canopy development (non-limiting conditions)
1.5 years
4 years
CCini = 25%
CCx = 95%
pruning 5
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Relative tea yield (non-limiting conditions)
pruning
1st
year
2nd
year
3rd
year
4th
year
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irrigation (I)rainfall (P)
capillary
rise deep
percolation
sto
red
so
il w
ate
r (m
m)
field capacity
threshold
wilting point
evapo-
transpiration
(ET)
(CR)
(DP)0.0
Water stress (upper) thresholds
FC
PWP
leaf expansion
canopy senescence
0.10 – 0.40 TAW
0.60 – 1.00 TAW
TAW
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Effect of water stress on canopy development
1 Jan 1996
31 Dec 1997
slow expansion
senescence
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Transpiration = Kssto x KcTr x ETo
no water stress
reference evapotranspiration
crop coefficient
weather conditions
characteristics of the transpiring crop
evaporative power of the atmosphere
proportional factor (KcTr,x) = 0.85 (integrating the effects of characteristics that distinguish the crop from the reference grass)
proportional to green canopy cover (CC)
water stress coefficient for stomatal closure
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irrigation (I)rainfall (P)
capillary
rise deep
percolation
sto
red
so
il w
ate
r (m
m)
field capacity
threshold
wilting point
evapo-
transpiration
(ET)
(CR)
(DP)0.0
Water stress (upper) thresholds
FC
PWP
leaf expansion
stomatal closure
canopy senescence
0.10 – 0.40 TAW
0.60 – 1.00 TAW
0.25 – 1.00 TAW
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H O2
CO2
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1. Calculation scheme Crop development
Crop transpiration
Biomass production
CC
WP*
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WP* normalized biomass water productivity
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1. Calculation scheme Crop development
Crop transpiration
Biomass production
CC
WP* 14 g/m2
bi = Ksb WP* (Tri/EToi)
Tbase = 8°C cold stress
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Tmax
Tmin
Effect of cold stress on biomass production
°C
month
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1. Calculation scheme Crop development
Crop transpiration
Biomass production
Yield formation
CC
WP*
HI 14 %
14 g/m2
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30 % = 1.2 years
14 %
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1. Calculation scheme Crop development
Crop transpiration
Biomass production
Yield formation
CC
WP*
HI 14 %
14 g/m2
yi = Ksexp,w HI bi water stress
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Rain
water stress 18
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2005 2006
Effect of water stress on tea yield
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1. Calculation scheme
Crop development
Crop transpiration
Biomass production
Yield formation
Structure of the presentation
2. Running simulations
Experimental fields
Farmer’s fields
Effect of climate change
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Experimental fields
WP* = 14 g/m2
HI = 14 % CCx = 95 %
1 2 3 4 1 2 3 4 ….
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pruning pruning
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observed tea yield
simulated tea yield 22
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Experimental fields
WP* = 14 g/m2
HI = 14 % CCx = 95 %
Farmer’s fields
WP* = 14 g/m2
HIo = 10 % CCx = 70 %
1 2 3 4
1 2 3 4
1 2 3 4
1 2 3 4 …. ….
…. ….
….
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1 2 3 4 1 2 3 4 ….
pruning pruning
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average observed tea yield
average simulated tea yield 24
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average simulated tea yield
1st year
3rd year average observed tea yield
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Statistical
indicator
Value Observation
R2 0.76 values greater than 0.50 are considered acceptable
RMSE 261 kg/ha it summarizes the mean difference in simulated and
observed
NRMSE 10.0 % a simulation can be considered excellent if NRMSE
is smaller than 10%
EF 0.66 an EF of 1 indicates a perfect match between the
model and the observations, an EF of 0 means that
the model predictions are as accurate as the average
of the observed data
d 0.85 0 indicating no agreement and 1 indicating a perfect
agreement between the predicted and observed
data. This statistical indicator overcomes the
insensitivity of R² and EF to systematic over- or
underestimations by the model
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Effect of climate change Crop development
Crop transpiration
Biomass production
Yield formation
CC
WP*
HI
less water stress less temperature stress
+ + + +
CO2 fertilization
+++
heat stress ?
-