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On-Irrigator Moisture Sensors for Precision Irrigation

On-Irrigator Moisture Sensors for Precision Irrigation. Ian Woodhead, Adrian Tan, Ian Platt and Sean Richards Lincoln Agritech Ltd., Lincoln University, Christchurch, New Zealand. PRESENTATION OVERVIEW:. 1. Introduction to the moisture sensor

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On-Irrigator Moisture Sensors for Precision Irrigation

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  1. On-Irrigator Moisture Sensors for Precision Irrigation Ian Woodhead, Adrian Tan, Ian Platt and Sean Richards Lincoln Agritech Ltd.,Lincoln University, Christchurch, New Zealand

  2. PRESENTATION OVERVIEW: 1. Introduction to the moisture sensor How does it enhance an existing variable rate irrigation system? 2. Operating principle How does the sensor measure the microwave reflection of pasture land? 3. Soil moisture content Relationship between sensor measurement and soil moisture 4. Sensor development Sensor prototype and antenna 5. Measurement examples Short lawn grass, medium and long pasture grass, at varying soil moisture 6. Conclusion

  3. Variable Rate Irrigation Pulsing sprinkler and varying system speed to achieve different application depth. Beneficial for different crops / non-crop areas; soil types; terrain; and obstacles. Need a computer database, knowledge of their effect on water intake, and algorithm. Irrigator needs to know the soil moisture content that are measured at a few locations. Images sourced from ars.usda.gov

  4. Variable Rate Irrigation Existing variable rate irrigation systems Systems of varying complexities, accounting for water budget, soil type, vegetation, growth stage, dynamics etc. Substantial modeling often required Systems with the ability to communicate and control sprinkler volume or irrigator speed Rely on indicative measurements of soil moisture at small sample size area How does an on-irrigator sensor improve the system? Measures the soil moisture content of the ground area in front of the wetted pattern of an irrigator Measured soil moisture content at meter scale used to modulate the application rate Not entirely based on models/ prior measurements, but real time measurements

  5. Benefits to the environment and farmer Benefits to the environment Improves soil water dynamics reduces nitrate leaching Benefits to the farmer Correct application of irrigation improves nutrient availability and crop yield, and thus farm productivity. • Improved feed quality and uniformity of dairy pasture enhances amount and consistency of milk production • Lowers risk of water logging due to excessive water supply in areas of poor drainage • More efficient utilization of water and energy lowers the cost of farming Ref: K.C. Cameron et. al., Ann. Appl. Biol., vol. 163, pp. 145-173, 2013.

  6. How does the sensor work? Microwave sensor mounted on the boom Soil moisture in front is measured as the irrigator moves Sprinkler’s application rate is modulated accordingly Soil moisture Ground location

  7. Sensor’s Operating Principle Transmitted signal: Time Received signal: Time

  8. Sensor’s Operating Principle Transmitted signal: Time Received signal: Time

  9. Sensor’s Operating Principle Transmitted signal: Time Received signal: Time Ground backscatter

  10. Sensor’s Operating Principle Transmitted signal: Time Received signal: Time Ground backscatter

  11. Sensor’s Operating Principle Transmitted signal: Time Received signal: Time Ground backscatter

  12. Sensor’s Operating Principle Transmitted signal: Time Received signal: Time Ground backscatter

  13. Sensor’s Operating Principle Transmitted signal: Time Received signal: Time Ground backscatter

  14. Sensor’s Operating Principle Transmitted signal: Time Received signal: Time

  15. Sensor’s Theory and Modelling -0.5 m

  16. Sensor’s Theory and Modelling -0.4 m

  17. Sensor’s Theory and Modelling -0.3 m

  18. Sensor’s Theory and Modelling -0.2 m

  19. Sensor’s Theory and Modelling -0.1 m

  20. Sensor’s Theory and Modelling 0.0 m

  21. Sensor’s Theory and Modelling 0.1 m

  22. Sensor’s Theory and Modelling 0.2 m

  23. Sensor’s Theory and Modelling 0.3 m

  24. Sensor’s Theory and Modelling 0.4 m

  25. Sensor’s Theory and Modelling 0.5 m

  26. Sensor’s Theory and Modelling 0.6 m

  27. Sensor’s Theory and Modelling 0.7 m

  28. Estimating soil moisture Extensive research has been conducted in empirical models of relating soil’s electrical properties with its moisture content. First order estimate of soil moisture content can be obtained directly due to dominating effects of water on electrical properties Ref: G.C. Topp, J.L. Davis and A.P. Annan, Water Resources Research, vol. 16, no. 3, pages 574-582, June 1980 Accounting for pasture grass effect • Method of calibrating the radar scattered signal to account for various crop types has been developed. • Crops include corn, soybeans, milo and wheat at various stages of growth. • Pasture grass is much shorter than crops, long grass might require minimal compensation. Ref: F.T. Ulaby, A. Aslam, M.C. Dobson, IEEE Trans. AP, 22(2) March 1974, and IEEE Trans. GRS, 20(4), Oct 1982

  29. Sensor Prototype Sensor on mobile cart with supporting structure for operation in windy conditions Antenna height = 2.7m, pointing at 45° at ground in front Antenna is an array of log periodic dipoles: Bandwidth = 400 – 1300 MHz Gain = 11 dBi 3-dB beamwidths = 45° ± 7° Agilent Fieldfox vector network analyzer PC for data collection, signal processing and display

  30. Sensor’s Antenna Design Proposed method of small area illumination by the sensor’s antenna Measured footprint of the antenna on ground. Area = 0.62 m2 • Array of 4 log-periodic dipole arrays and a wideband 1-to-4 power combiner. • ~50 individual antennas in 0.4m x 0.4m x 0.5m volume • Still a prototype, to be optimized in size.

  31. Measurement #1: Lawn grass Lawn grass, height = 2 cm to 5 cm Volumetric moisture content between 5% to 15% Validation with HS2 Hydrosense probe 20 15 Volumetric Moisture Content (%) 10 5 0 16 8 10 6 2 4 0 12 14 18 Distance (m) Lawn grass behind the RFH building at Lincoln University

  32. Measurement #2: Dry pasture grass Pasture grass, height = 8 cm to 15 cm Volumetric moisture content of soil between 15% to 25% Validation with HS2 Hydrosense probe at 12 cm (blue line) and 20 cm (black line) 60 50 Pasture grass at Iverson Fields I9, Lincoln University 40 Volumetric Moisture Content (%) 30 20 10 0 7 9 5 6 8 10 Distance (m)

  33. Measurement #3: Wet pasture grass Pasture grass, height = 5 cm to 10 cm Volumetric moisture content of soil between 30% to 40% Validation with HS2 Hydrosense probe at 12 cm (blue line) and 20 cm (black line) 60 50 Pasture grass at Iverson Fields I9, Lincoln University 40 Volumetric Moisture Content (%) 30 20 10 0 7 9 5 6 8 10 Distance (m)

  34. CONCLUSION • Existing Variable Rate Irrigation System Proposed Obstacles: User excluded areas Crop intake: Crop type, growth stage Terrain: Digital elevation model Soil Type: Available water holding capacity Modelling Software Soil Moisture: Measurements at few selected locations • Soil Moisture: • Real time, meter scale measurement in front of irrigator VRI Control System

  35. CONCLUSION On-irrigator moisture sensor can enhance precision irrigation by providing meter scale soil moisture mapping Development effort shows the feasibility, and limitations of such systems Measured soil moisture from a single sensor controlling the sprinkler water volume provides 1st level benefit There can be multiple sensors controlling the individual sprinklers to achieve the best water savings Cost savings can be achieved by multiplexing many (low cost) antennas with one single active element.

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