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Initial Investigations into the Potential and Limitations of Remote Sensed Data for Irrigation Scheduling in High Value Horticultural Crops
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Outline
• Background – irrigation system requirements into the future
• Use of NDVI in irrigation scheduling
• Thermal – the ultimate irrigation scheduling tool?
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Background
• Ongoing switch from flood/furrow irrigation to drip in perennial horticulture
• Supported through the Integrated Horticulture Systems Project in the Murrumbidgee Irrigation Area
• Aims to see majority of horticulture converted to pressurized irrigation systems by 2010
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Drip and Flood Water Use
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
10.0
Flood/
Furro
w
Flood/
Furro
w
Flood/
Furro
w
Flood/
Furro
w
Avera
ge
Drip/S
prink
ler
Drip/S
prink
ler
Drip/S
prink
ler
Drip/S
prink
ler
Drip/S
prink
ler
Drip/S
prink
ler
Drip/S
prink
ler
Drip/S
prink
ler
Drip/S
prink
ler
Drip/S
prink
ler
Drip/S
prink
ler
Drip/S
prink
ler
Drip/S
prink
ler
Irrigation System
ML
/ha
5.9 ML/ha
3.6 ML/ha
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Yields
0
5
10
15
20
25
30
35
Drip Flood
Yie
ld (
t/h
a)
Yield District Average
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Managing High Tech Irrigation Systems
6 Soil probes for 6 ha paddock
Assume each probe measured 1m2
So we know what is happening on:
• Method lacks ability to ‘see’ what is happening over the whole vineyard
• Only infer the plant stress based on the soil moisture, plants can also be stressed due to a number of other factors such as soil salinity,
%01.010060000
62
2
m
mCan we get something better ?
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Large Scale Low Cost Irrigation Scheduling - NDVI for Irrigation Scheduling/Management/Benchmarking
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NDVI
• NDVI = (RNIR – Rred) / (RNIR + Rred)
NDVI = (Band 4 - Band 3) / (Band 4 + Band 3)
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Irrigation Scheduling – FAO 56
ETc = ETo x Kc
Readily available from
Weather stations/SILO
Relates actual water use of the crop to reference water use
-Large variation and crop/management specific
NDVI to Kc functional relationship
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Canopy Cover and Light Interception Vs WU
Williams and Ayars (2005) McClymont et al.
ECC = 1.2 NDVI – 0.2
(extrapolated from Johnson and Scholasch, 2005)
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Irrigation Scheduling from Remote Sensing indices
Determination of Kc from NDVI / EAS Data
ETo from Weather Station
Incorporates management/soil/water/salinity
constraints
On Ground
NDVI / EAS Images from Satellite or quad bike
Representing Individual Paddocks
Satellite, airborne or On-groundSpatial Measurements
Potential Evaporation based on Atmospheric Demand
ETc = ETo X Kc
Actual crop evapotranspiration across regions
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CRC IF Irrigateway server
NDVI + ETo data Harvesting
Daily delivery of tailored irrigation scheduling information direct to irrigator on SMS
Initialisation data – system parameters
Benchmarking and data mining
ETc = ETo x kc
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SMS Drip Scheduler
• Uses simple SMS text messages for delivering irrigation scheduling information
• Will be tested with 20 horticultural growers this coming season in MIA
irriGATEWAYDripper run times (min) forY’day: A-250, B-330, C-270.2 days: A-510, B-620, C-545.3 days: A-790, B-920, C-770.
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NAFE
• NAFE 06 NDVI data will be used for fine tuning of EAS/ECC relationships to NDVI
• Investigation into scaling effects from high resolution NDVI (NAFE 06) data to Landsat NDVI in relation to providing irrigation scheduling information – sensitivity analysis
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Thermal
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Crop Water Stress Index (CWSI)
What is CWSI?• Relates canopy temperature to an
index between 0 and 1 indicating how stressed the plant is:
• 0 = No stress• 1 = High stress
NWSBLacNTUBLac
NWSBLacacCWSI
TTTT
TTTT
)()(
)()(
Measured with IR temperature sensor or thermal camera
(Tc-Ta)NWSBL = Non water stressed base line – equated fully open stomata and fully transpiring canopy
(Tc-Ta)NTUBL = non-transpiring upper baseline –equated to temp. of non-transpiring canopy with stomata closed(Tc-Ta)NWSBL
(Tc-Ta)NTUBL
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Agrosense - Irriscan
• Trials undertaken in MIA in 2002 • Collaboration with MIGAL Galilee Technology Centre, Israel • 0.1 m2 Resolution• 1250 ha per day• On-site calibration
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Results
1
2
3
4 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1
1
2
3
4 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 10
CWSI ECe
(dS/m)
CWSI Before Irrigation
CWSI After Irrigation
Soil Salinity
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Canopy Temperature and Salinity Stress
40 92 00 40 93 00 40 94 00 40 95 00 40 96 00 40 97 00 40 98 00 40 99 00
1 0-1-200 2 scan
6 19 83 00
6 19 84 00
6 19 85 00
0
0.2
0.4
0.6
0.8
1
1.2
0.15 0.2 0.25 0.3 0.35 0.4
Volumetric Water Content (m3/m3)
Dep
th (
m) 1
234
1
43
2
050
100
150
200
010020
030040
050060
0
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Crop Water Stress Index (CWSI) – Jones et al.
What is CWSI?• Relates canopy temperature to an
index between 0 and 1 indicating how stressed the plant is:
• 0 = No stress• 1 = High stress
WetDry
WetLSCWSI
TT
TT
Measured with IR temperature sensor or thermal camera
Tdry = upper bound for canopy temp. – equated to temp. of non-transpiring canopy with stomata closed
Twet = non-stressed baseline – equated fully open stomata and fully transpiring canopy
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Wet Reference Surfaces
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Results
Wet Reference Surfaces
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NAFE
• Assessment of alternative methods of determining baselines for CWSI
• Comparison of PLMR data with high intensity on-ground gravimetric soil moisture content sensing
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Email: [email protected] Web: www.csiro.au
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