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Initial Investigations into the Potential and Limitations of Remote Sensed Data for Irrigation Scheduling 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 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 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 Drip and Flood Water Use

Yields Yields

Managing High Tech Irrigation Systems 6 Soil probes for 6 ha paddock Assume each Managing High Tech Irrigation Systems 6 Soil probes for 6 ha paddock Assume each probe measured 1 m 2 So we know what is happening on: Can we get something better ? • 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 Large Scale Low Cost Irrigation Scheduling - NDVI for Irrigation Scheduling/Management/Benchmarking

NDVI • NDVI = (RNIR – Rred) / (RNIR + Rred) NDVI = (Band 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 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) Mc. Clymont et Canopy Cover and Light Interception Vs WU Williams and Ayars (2005) Mc. Clymont 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 / 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 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 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 irri. GATEWAY 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 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 Thermal

Crop Water Stress Index (CWSI) What is CWSI? • Relates canopy temperature to an 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 (Tc-Ta)NTUBL (Tc-Ta)NWSBL 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 nontranspiring canopy with stomata closed

Agrosense - Irriscan • • • Trials undertaken in MIA in 2002 Collaboration with Agrosense - Irriscan • • • Trials undertaken in MIA in 2002 Collaboration with MIGAL Galilee Technology Centre, Israel 0. 1 m 2 Resolution 1250 ha per day On-site calibration

Results Results

Canopy Temperature and Salinity Stress 1 3 2 4 Canopy Temperature and Salinity Stress 1 3 2 4

Crop Water Stress Index (CWSI) – Jones et al. What is CWSI? • Relates 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 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 Wet Reference Surfaces

Results Wet Reference Surfaces Results Wet Reference Surfaces

NAFE • Assessment of alternative methods of determining baselines for CWSI • Comparison of 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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