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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
3
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
CC = 25 %
CC = 95 %
Lung pruning
4
Canopy development (non-limiting conditions)
1.5 years
4 years
CCini = 25%
CCx = 95%
pruning 5
Relative tea yield (non-limiting conditions)
pruning
1st
year
2nd
year
3rd
year
4th
year
6
7
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
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
10
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
H O2
CO2
11
1. Calculation scheme Crop development
Crop transpiration
Biomass production
CC
WP*
WP* normalized biomass water productivity
12
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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
Tmax
Tmin
Effect of cold stress on biomass production
°C
month
14
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1. Calculation scheme Crop development
Crop transpiration
Biomass production
Yield formation
CC
WP*
HI 14 %
14 g/m2
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
Rain
water stress 18
2005 2006
Effect of water stress on tea yield
19
20
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
Experimental fields
WP* = 14 g/m2
HI = 14 % CCx = 95 %
1 2 3 4 1 2 3 4 ….
21
pruning pruning
observed tea yield
simulated tea yield 22
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 …. ….
…. ….
….
23
1 2 3 4 1 2 3 4 ….
pruning pruning
average observed tea yield
average simulated tea yield 24
average simulated tea yield
1st year
3rd year average observed tea yield
25
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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
27
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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 ?
-
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