initial investigations into the potential and limitations of remote sensed data for irrigation...
TRANSCRIPT
Initial Investigations into the Potential and Limitations of Remote Sensed Data for Irrigation Scheduling in High Value Horticultural Crops
Outline
• Background – irrigation system requirements into the future
• Use of NDVI in irrigation scheduling
• Thermal – the ultimate irrigation scheduling tool?
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
Drip and Flood Water Use
0.0
1.0
2.0
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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
Yields
0
5
10
15
20
25
30
35
Drip Flood
Yie
ld (
t/h
a)
Yield District Average
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 ?
Large Scale Low Cost Irrigation Scheduling - NDVI for Irrigation Scheduling/Management/Benchmarking
NDVI
• NDVI = (RNIR – Rred) / (RNIR + Rred)
NDVI = (Band 4 - Band 3) / (Band 4 + Band 3)
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
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)
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
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
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.
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
Thermal
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
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
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
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
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
Wet Reference Surfaces
Results
Wet Reference Surfaces
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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