Transcript Initial Investigations into the Potential and Limitations of Remote Sensed Data for Irrigation Scheduling in High Value Horticultural Crops Outline • Background – irrigation.

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
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Fl
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ML/ha
Drip and Flood Water Use
10.0
9.0
8.0
7.0
6.0
5.9 ML/ha
5.0
4.0
3.6
ML/ha
3.0
2.0
1.0
0.0
Irrigation System
Yields
35
30
Yield
District Average
Yield (t/ha)
25
20
15
10
5
0
Drip
Flood
Managing High Tech Irrigation Systems
6 Soil probes for 6 ha paddock
Assume each probe measured
1m2
So we know what is happening on:
Can we get something
6m
100  0.01%
60000m
better ?
2
2
• 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,
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
Readily available from
Weather stations/SILO
ETc = ETo x Kc
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
Satellite,
airborne or
On-ground
Spatial
Measurements
NDVI / EAS Images from
Satellite or quad bike
On Ground
ETo from
Weather Station
Incorporates
management/soil/water/salinity
constraints
Determination of Kc from
NDVI / EAS Data
Representing
Individual
Paddocks
ETc = ETo X Kc
Potential Evaporation based
on Atmospheric Demand
Actual crop evapotranspiration
across regions
NDVI +
ETo data
Harvesting
Daily delivery of
tailored irrigation
scheduling
information direct to
irrigator on SMS
ETc = ETo x kc
CRC IF
Irrigateway
server
Initialisation
data – system
parameters
Benchmarking
and data mining
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
irriGATEWAY
Dripper run times (min) for
Y’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
CWSI
(Tc-Ta)NTUBL
(Tc-Ta)NWSBL
Measured with IR temperature
sensor or thermal camera
(Tc  Ta )  (Tc  Ta ) NWSBL

(Tc  Ta ) NTUBL  (Tc  Ta ) NWSBL
(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 nontranspiring canopy with stomata closed
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
ECe
(dS/m)
CWSI
3
1
3
1
1
0.95
0.9
0.85
10
9.5
9
8.5
0.8
0.75
0.7
0.65
0.6
0.55
8
7.5
7
6.5
6
5.5
5
4.5
0.5
0.45
0.4
4
3.5
3
0.35
0.3
0.25
4
2
CWSI Before
Irrigation
4
2
CWSI After
Irrigation
0.2
0.15
2.5
2
1.5
0.1
0.05
0
1
0.5
0
Soil Salinity
1. 1
47.7
5
1
409500
0.15
0
409600
409700
0.2
409800
Volumetric Water Content (m3/m3)
0.25
0.3
0.2
0.4
0.6
0.8
1
1.2
1
2
3
4
0.35
0.4
200
300
409900
0
409400
100
409300
600
1. 1
51.5
5
4
400
1. 1.
23 3 3
3
500
1.
15
1. 1
7 .7
2
8
1. 1
13.2
3
10-1-2002 scan
Depth (m)
00
Canopy Temperature and Salinity Stress
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
Measured with IR temperature
sensor or thermal camera
CWSI
TLS  TWet

TDry  TWet
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
Thank you
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