Smarter Irrigation Project Dairy Innovation Day 2017 May 4th – Sam Taylor

Smarter Irrigation Project Components Practical, reliable irrigation scheduling technologies Precise, low cost automated control systems for a range of irrigation systems A network of farmer managed learning sites located in major regions referred to as “optimised irrigation” farms These details are from the initial project application, and grants a wide scope to work within (as far as demonstration activities are concerned) Increased adoption of scheduling on area to focus on (authors thoughts – seen as low hanging fruit) Automation favoured for low labour, reliability, adaptability, and to be investigated in both surface and pivot irrigation systems Other dairy sites in SA, VIC, TAS, NSW & QLD as this is part of a greater national project

Project Outcomes 10-20 percent improvement in water productivity, efficiency and farmer profitability Adoption of new irrigation technologies and science application by farmers and irrigation professionals to improve farm profits. Improved cross sector industry research collaboration with public and private sectors in four major irrigation industries providing a legacy platform for other sectors to also benefit These are the high level outcomes across the project Ultimately looking to improve Water Use Efficiency, reduce home grown fodder costs and improve profitability We will look at new components, soil type assessments and management applications. This is a cross industry project with partners comprising the major water users of Cotton RDC, Rice, Sugar & Dairy. We are looking to benefit from the learnings of these other industries and apply in Dairy where applicable.

WA Demonstration Site Introduction to WA Site – Host Farmer Michael Giumelli pictured. Michael has 1 40ha pivot and 30 ha of surface irrigated land. He grows summer crop under the pivot, and early germinates pasture on remaining land (when water allocation allows) Water allocation has been restricted to ~40% of entitlement the last 2 summers.

Electromagnetic survey (0-50cm) EM 4 Measures soil electro conductivity Primarily influenced by salinity Clay and moisture also influence EM EM 5 EM 3 EM 2 EM 1 The site was surveyed for variability via EM38 and Radiometrics in October 2016 Soil Moisture Sensors installed at EM 1, 2 & 3. EM 1 = Sandy Clay Loam EM 5 = Clay Loam From this image, an estimation of PAWC can be made. Soil moistures told us that the soil at EM1 was continually drier than the soil at EM2 & EM3, despite the pivot only being capable of single rate application.

Plant Available Water Content Another (larger) pivot site surveyed by EM38 and Radiometrics shows far greater soil type variation. This pivot has since had Variable Rate Irrigation installed, and production has increased in both the blue/dark blue and red/orange areas, as the appropriate amount of water is now being applied to these soils.

Current Activities EM 38 & Radiometrics Survey completed Pivot DU Survey (1 done pre pivot repairs, another planned) Installation of Soil Moisture Monitors & Electronic Rain Gauge Activities undertook at Giumellis

Soil Moisture Sensors - Wildeyes The Wildeye soil moisture sensors use to monitor soil moisture levels. 2 sensor units used to monitor moisture at selected depths (we used 10cm and 30cm) Very simple installation – Dig hole and push pins into undisturbed soil onside of hole at selected depths. Data reader located on post adjacent to sensors to enable mobile phone signal.

EM1 – Sandy Clay Loam Soil Water Levels over Jan – Mar 2017 on the drier site at the south of the pivot. Soil moisture often dropped below the arbitrary “stress point” entered into the software. Web based software updates data 1 x per day. Blue Line is 10cm depth and clearly shows fluctuations in soil moisture levels associated with irrigation events. Green Line is drainage at 30cm and does not vary as much. The large spike in mid February is a summer rainfall event (~100mm) and allowed Michael to reduce irrigation for some time and conserve available water allocation for Autumn pasture germination. Michael was confident in extending the irrigation the period as he could “see” what the soil moisture levels were.

EM 2 Clay Loam The wetter soil to the north of the pivot showing higher available soil moisture levels under a similar watering regime to the previous slide.

Modified Irrigation scheduling based on crop demand (maize) Discussion around crop water demand (red line) vs flat rate irrigation (Green line). Both lines represent the same amount of water applied over the life of the crop. Watering to maintain soil moisture equilibrium (green line) may not always meet crop demand (depending on crop type) as this graphic shows. Maize water requirement is represented by the red line, and you can see maize requires an increasing amount of water up to the mid point of its growth cycle, from which point the demand decreases. It is important to understand not only the crop demand, but also the environmental demand.

Irrigation Schedule Week Applications per week Pivot Setting (% Speed) mm delivered per application Emergence 1 100 7.55 2 85 8.88 3 4 70 10.62 5 6 75 10.06 Improved / validated decision making based on objective data (soil moisture sensors) This chart demonstrates what an irrigation schedule may look like. It details the number of applications required per week, along with pivot settings (in this case) to ensure the correct amount of water is applied per week. This information must be correlated with soil moisture sensors, and also climate data (Eto – Evapotranspiration) and adjusted as the season goes where necessary to ensure crops have sufficient available water in the soil profile (but do not become waterlogged)

Acknowledgments Thankyou to our research partners and funding organisations for making this project possible.