knowledge management, sensing and control tools for ... · knowledge management, sensing and...
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Knowledge management, sensing and control tools for irrigated broadacrecropping
Dr Alison McCarthy, Michael Scobie, Dr Malcolm Gillies, Lidya Agustina and Dr Joseph Foley
National Centre for Engineering in Agriculture Institute for Agriculture and the Environment University of Southern Queensland
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NCEA’s irrigation research Knowledge Management System for Irrigation (KMSI) SISCO – surface irrigation modelling Automation through commercial control systems (Rubicon,
WiSA, Valmont, Lindsay-Zimmatic) VARIwise, site-specific irrigation decision making
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KMSI
Suite of tools funded by the Queensland Government as part of the South East Queensland Irrigation Futures project
Centralised online decision support tools for irrigation, nutrient and energy calculators with benchmarking function to compare across catchments, systems and industries
Also has simple calculator tools with simple input/output interface
For growers and industry consultants
kmsi.usq.edu.au
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KMSI - IPARTIrrigation Performance Audit and Reporting Tool (IPART) Assist in the evaluation and collation of infield irrigation application system
performance data
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KMSI - IPERTIrrigation Pump Evaluation and Reporting Tool (IPERT) Assist in the evaluation and collation of on-farm irrigation pumping system
performance data
Grower 1 Egg place
Grower 2 Tree place
Grower 3 Other place
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KMSI - MIMMetering & Irrigation Management Tool (MIM) Assists farmers in managing their metered water
usage through provision of meter readings, farm and field information.
Mobile friendly
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KMSI – SIDScheduling Irrigation Diary (SID) Irrigation recording and scheduling features based
on evapotranspiration (ET) Web based tool, also available in iOS and Android
with the Augmented Reality feature There will be demo during the field day
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SISCO - surface irrigation Tool for modelling furrow & border check irrigationNeeds good field measurements
Can predict distribution of water across field Enables users to optimise performance
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Automation systems First step = Remote control Second step = Automated control Third Step = Smart automated control
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Using WiSA control systemsa) Linear actuators on valvesb) Pressure sensor in cylinder/pipec) Buried end of row sensorsd) Flowmeters
(c)
Furrow in Sugarcane
(b)
(a)
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Using Rubicon control systems
Furrow in Cotton
Depth sensor for flow meas. and control of
channel system
Control Gate
Secondary head channel
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Furrow in CottonCurrent Questions? Channel and pump control How to estimate spatial soil moisture? Spatial variability of rain? Sensing advance?
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Irrigation advance monitoring Thermal and visible camera on 10 m towerUpload image on motion detectionCamera tower Thermal images from head ditch
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Model-basedSensor-based
VARIwise: site-specific irrigation control system
2. Control strategy- convert data to irrigation application- sensor or model-based- model-based control needs calibration with infield data
Surface irrigation system Overhead irrigation system
1. Sensors
- fixed sensors- historical maps- on-the-go sensors
3. Real-time irrigation adjustment
- actuators to apply irrigation
Model calibration
Control strategies
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Original image Analysis
Original image Analysis
Smartphone camera
Height from quad bike sensor
0 Height (mm) 250
Canopy cover from cameras
Camera-based sensors
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Control system implementation on centre pivotReal-time camera-based plant sensing to update irrigation:
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Control system implementation for surface irrigation
Crop growth and fruiting
Soil-water, weather Control strategy determinesirrigation volumes
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Conclusions Tools developed for growers, consultants and
automated irrigation data management and processing
Used for manual or automated managementNext steps: Evaluation of SISCO and VARIwise control
strategies at cotton, sugarcane and dairy pasture over next two years
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Acknowledgements
Cotton Research and Development Corporation, Federal Government Rural R&D for Profit Program, Queensland Government, TIA, Dairy Australia, Sugar Research Australia and Queensland Department of Natural Resources for funding support
Cotton growers Lindsay Evans and Neil and Lachlan Nass for providing field trial sites