initial investigations into the potential and limitations of remote sensed data for 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

Drip and Flood Water Use

0.0

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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

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Drip/S

prink

ler

Drip/S

prink

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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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