0 / On-Irrigator Moisture Sensors for Precision Irrigation Ian Woodhead, Adrian Tan, Ian Platt and...
If you can't read please download the document
0 / On-Irrigator Moisture Sensors for Precision Irrigation Ian Woodhead, Adrian Tan, Ian Platt and Sean Richards Lincoln Agritech Ltd., Lincoln University,
0 / On-Irrigator Moisture Sensors for Precision Irrigation Ian
Woodhead, Adrian Tan, Ian Platt and Sean Richards Lincoln Agritech
Ltd., Lincoln University, Christchurch, New Zealand
Slide 2
1 / 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
Slide 3
2 / 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
Slide 4
3 / 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
Slide 5
4 / 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.
Slide 6
5 / How does the sensor work? Microwave sensor mounted on the
boom Soil moisture in front is measured as the irrigator moves
Sprinklers application rate is modulated accordingly Soil moisture
Ground location
Slide 7
6 / Sensors Operating Principle Transmitted signal: Time
Received signal:
Slide 8
7 / Sensors Operating Principle Transmitted signal: Time
Received signal:
Slide 9
8 / Sensors Operating Principle Transmitted signal: Time
Received signal: Ground backscatter
Slide 10
9 / Sensors Operating Principle Transmitted signal: Time
Received signal: Ground backscatter
Slide 11
10 / Sensors Operating Principle Transmitted signal: Time
Received signal: Ground backscatter
Slide 12
11 / Sensors Operating Principle Transmitted signal: Time
Received signal: Ground backscatter
Slide 13
12 / Sensors Operating Principle Transmitted signal: Time
Received signal: Ground backscatter
Slide 14
13 / Sensors Operating Principle Transmitted signal: Time
Received signal:
Slide 15
14 / -0.5 m Sensors Theory and Modelling
Slide 16
15 / -0.4 m Sensors Theory and Modelling
Slide 17
16 / -0.3 m Sensors Theory and Modelling
Slide 18
17 / -0.2 m Sensors Theory and Modelling
Slide 19
18 / -0.1 m Sensors Theory and Modelling
Slide 20
19 / 0.0 m Sensors Theory and Modelling
Slide 21
20 / 0.1 m Sensors Theory and Modelling
Slide 22
21 / 0.2 m Sensors Theory and Modelling
Slide 23
22 / 0.3 m Sensors Theory and Modelling
Slide 24
23 / 0.4 m Sensors Theory and Modelling
Slide 25
24 / 0.5 m Sensors Theory and Modelling
Slide 26
25 / 0.6 m Sensors Theory and Modelling
Slide 27
26 / 0.7 m Sensors Theory and Modelling
Slide 28
27 / Estimating soil moisture Extensive research has been
conducted in empirical models of relating soils 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
Slide 29
28 / 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
Slide 30
29 / Sensors Antenna Design 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. Proposed method of small area illumination by
the sensors antenna Measured footprint of the antenna on ground.
Area = 0.62 m 2
Slide 31
30 / Measurement #1: Lawn grass 20 15 10 5 0 0 24 6 8 1214 16
18 Distance (m) Volumetric Moisture Content (%) Lawn grass, height
= 2 cm to 5 cm Volumetric moisture content between 5% to 15%
Validation with HS2 Hydrosense probe Lawn grass behind the RFH
building at Lincoln University
Slide 32
31 / 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) Pasture grass at Iverson Fields I9, Lincoln
University 20 10 0 56 7 8 Distance (m) Volumetric Moisture Content
(%) 40 30 50 60 9
Slide 33
32 / 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) Pasture grass at Iverson Fields I9, Lincoln
University 20 10 0 56 7 8 Distance (m) Volumetric Moisture Content
(%) 40 30 50 60 9
Slide 34
33 / CONCLUSION Existing Variable Rate Irrigation System
Modelling Software Modelling Software VRI Control System Terrain:
Digital elevation model Soil Type: Available water holding capacity
Obstacles: User excluded areas Crop intake: Crop type, growth stage
Soil Moisture: Measurements at few selected locations Soil
Moisture: Real time, meter scale measurement in front of irrigator
Soil Moisture: Real time, meter scale measurement in front of
irrigator Proposed
Slide 35
34 / 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 1 st 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.