ADAPTATION OF A HYDROLOGICAL
MODEL TO ROMANIAN PLAIN
Elena SAVIN, Gheorghe STANCALIE, Corina ALECU
National Institute of Meteorology and Hydrology Bucharest
MARS (Monitoring Agriculture with Remote Sensing) project
cooperation with CIRAD France
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ROMANIA
- geographical position
East Europe
- climate: temperate:
annual mean temperature 10 C
precipitation (400 - 700 mm/year)
- cultivated surface : 20 000 ha
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Demand from: minister and trade
- product estimation for cultivated
areas for wheat and maize
Solution: adaptation of
a simple water balance
model - BIPODE
Possibilities - many models
Limitations - available data
steps: adaptation for station
surface yield estimation
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INPUT DATA
OUTPUT DATA
meteo : mean daily temperature (C)
relative humidity (%)
sun shine duration (hours)
wind speed (m/s)
maximum evapotraspiration (mm)
real evapotraspiration (mm)
ETR/ETM ratio (%)
water amount for irrigation
plant: type (white, maize)
phenological phases duration
sowing date
crop coefficient
root growing rate (cm/day)
soil:
type
field capacity at 1 m
water content at sowing date at 1 m
ADAPTATION:
- crop coefficient
- root growing rate
- ETP daily values
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Algorithm used by BIPODE
1. Ru = 0 if P<Pth
Ru = Kr *Pth ifP>Pth
2. Peff = P-Ru
ETP, Kc
P
3. Dr = 0 if Peff+Wa z-1<AWC
Dr = AWC - (Peff+AWC z-1)
ETM, 7
Kr, Pth
RU, 1
4. WAz = Peff - Dr + WAz-1
on entire profile
ETR, 8
SOIL reservoir
1m 4,5,9
5. Knowing the day (z) and the root
growth rate (RGR) AWCr and War
were determined
HR, 6
6. HR = Awrz/AWCr
DR 3
5 AWCr
Z, RGR
7. ETM = Kc*ETP
8. ETR = f(ETM,HR)
Peff, 2
AWC
input data
output data
9. Awz = Peff - Dr - ETR + Awz-1
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CROP COEFICIENTS
Crop coeficient - maize
Crop coeficient - wheat
1,4
1,4
1,2
1,2
1
1
0,8
0,8
Vegetativ
phase
0,6
Maturity
Flowering
Germination
0,6
0,4
0,4
0,2
0,2
0
0
0
0
20
40
60
80
100
120
140
160
180
50
Tallage Flowering
Montaison
100
150
Maturity
200
Days
Days
Phenological phases - mean from 170 data sets for wheat and 101 for maize
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The best correlation yield - IR (obtained from 60 data sets - wheat
30 data sets - maize)
IR=(ETR/ETM)flowering*(ETR)vegetative period
Yild=23.3 * IR + 2960
Maize
Yild=8.7 * IR + 2410.8
Wheat
r2=0.53
14000
7000
12000
6000
10000
5000
Yild( Kg/ha)
Yield ( Kg/ha)
r2=0.61
8000
6000
4000
3000
4000
2000
2000
1000
0
0
0
50
100
150
200
250
300
350
400
0
IR=(ETR/ETM)flowering*(ETR)vegetative period
100
200
300
400
500
IR
Estimation of yield after flowering
(ETR/ETM) from model
(ETR) vegetative period - mean from 10 years
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Models Vs. observation for wheat (29 data sets)
Résidus (wheat,data used for validation)
6000
5000
3000,00
4000
Yield (Kg/ha)
estimated yield (Kg/ha)
7000
3000
2000
1000
0
0
2000
4000
6000
2000,00
1000,00
0,00
-1000,00
0
100
200
300
400
500
-2000,00
IR
obseved yield (Kg/ha)
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- Romanian plain was classified in 6 homogenous zones (soil, climate,
agro)
- for 4 zones the correlation coefficient increases
- for 2 zones the correlation coefficient decreases (hills zones) temperature influence
- yield was estimated for station and integrated for cultivated surface
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Data Spatialisation
grid 20 km x 20km - data set associated (interpolation of
missing input data)
40
30
20
10
0
-10
-20
Tréelle
358
337
316
295
274
253
232
211
190
169
148
127
106
85
64
43
22
Tinterpol.
1
T ( °C)
real T real and interpolated T - kriging method
days
- use of data estimated from NOAA-AVHRR satellite images
- spatial data
- repetivity (4 images / day)
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NOAA - AVHRR images
channel 1(visible)
channel 2(NIR) channel 3(MIR) channel 4
channel 5
(IR thermal)
=0.58-0.98m
=0.72-1m =3.55-3.9 m =10.3-11.3 m =11.5-12.5m
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Image reception
hrp format
Image import ERDAS Imagine:

1, 2, 3 in radiance or albedo values
4, 5 in temperature

NDVI

Data calibration for AVHRR channels
surface
emissivity
Image Process ERDAS
Imagine:
Reprojection
geometric corrections
albedo
Surface temperature
actual
evapotranspiration
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NORMALISED DIFFERENCE VEGETATION INDEX
CHANEL 2 - CHANEL 1
NDVI = --------------------------------CHANEL 2 + CHANEL 1
CANAL 2 - near infrared radiation
CANAL 1 - visible radiation
visible near infrared
0.4 0.6 0.8 1.2 1.4 1.6 1.8 2
2.2 2.4 2.6 2.8
wavelength (um)
Reflectance for green leafs
blue
green red
near infrared
dry grass
soil
green grass
LEGEND
<1
0.1
0.2
0.3
0.4
NDVI 12 June 2000
0.5
0.53
0.4
0.5
0.6
0.7
0.8
0.9
wavelength (um)
Reflectance for vegetation and soil
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NORMALISED DIFFERENCE VEGETATION INDEX - daily values
22 June - 26 June 2000 and 5 days value
obtained by MAXIMUM VALUE COMPOSITE
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Broad band ALBEDO obtained from the combination of
albedo values for channels 1 and 2
6 June 2000
Legend
0.05-0.1
0.1-0.2
0.2-0.3
0.3-0.4
clouds
d = bo+b1*a1 + b2*a2
where:
a1,a2 albedo values for channels 1,2
bo, b1 si b2 coefficients
b1 = 0.494*NDVI2 - 0.329*NDVI + 0.372
b2 = -1.437*NDVI2 + 1.209*NDVI + 0.587
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SURFACE EMISSIVITY 12 June 2000
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SURFACE TEMPERATURE 6 June 2000 split window method
<18 20 22 24 26 28 30 32 34 36
38 >40
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ACTUAL EVAPOTRASPIRATION
Image data NOAAAVHRR 12, 13, 14, 16
Surface temperature
(Ts) split-window
method
Meteorological
stations
Maximum air
temperature (Ta)
(Ts-Ta) daily, 5 days,
10 days values
ETR = Rn + A+B(Ts-Ta)
daily values
ETR (mm)
1
ETR = Rn + A + B (Ts-Ta)
daily, 5 days, 10 days values
2
3
4
5
5.2
FOREST
ACTUAL EVAPOTRANSPIRATION ESTIMATED FROM
NOAA-AVHRR image 12 June 2000
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SURFACE TEMPERATURE (covered with vegetation)
split-windows method
20 June 1999
22 June 2000
TEMPERATURA SUPRAFETEI (o C)
15 - 20
20 - 25
25 - 30
TEMPERATURA SUPRAFETEI (o C)
30 - 32
< 25
20 - 30
30 - 35
35 - 40
40 - 45.3
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NDVI - 4 April 2001
Surface emissivity 4 April 2001
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Surface temperature (covered with vegetation)
4 April 2001
Actual evapotranspiration 4 April 2001
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CONCLUSION
1. For 3 years estimated yield was  200 kg/ha to the real yield
2. Adaptation of the improved water balance model for yield forecast
3. Validation of data obtained from NOAA-AVHRR images using
measured data
4. Estimation of : LAI (leaf area index)
FPAR (photosinteticaly active radiation)
5. Use of data obtained from NOAA-AVHRR images in the model
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