Maximising the Value of Irrigation

The H2Grow Team are excited to introduce Carolyn Hedley as our guest contributor, it is with great pleasure that we can share with you her valuable expertise. Carolyn is a Soil Scientist with Manaaki Whenua, based in Palmerston North, and lives on a small Kairanga farm with husband, Mike. Carolyn has combined her interests in soil science, proximal soil sensing and precision agriculture with on-farm studies of precision irrigation and soil carbon mapping. She has led several nationally funded projects in irrigation and soil carbon, including current leadership of the MBIE funded programme “Maximising the Value of Irrigation”.

Maximising the Value of Irrigation  -  Carolyn Hedley

Early in the new millennium I found out about EM mapping and in 2004 published a method in the Australian Journal of Soil Research to rapidly EM map soil variability on a basis of soil texture. I realised that EM mapping was a really useful new technology to rapidly survey soil variability. The EM map had picked the difference between a Kairanga silt loam and a Kairanga clay loam, and this had management implications for the farmer because the heavier textured soil would compact sooner when grazed in wet conditions.

I could see great potential in this new technology and so embarked on a PhD in proximal soil sensing and this is when I started to relate the EM map to soil available water holding capacity and realised how useful this could be for irrigation scheduling. But critics commented that irrigation systems cannot irrigate to such a complex pattern (example shown in Figure 1 below). Enter Stu Bradbury and George Ricketts, who had worked with me on some EM mapping projects when they were students at Massey University. There was an engineering solution to this problem – control the sprinkler system on a pivot to irrigate to any pattern – which led to the development of the Precision VRI system. Precision VRI, the world’s first true variable rate irrigation system, turned the heads of the global irrigation giants and as a result Lindsay Corporation acquired the technology development company founded by Stu and George.

Figure 1: Available Water-holding Capacity map derived from an EM map for a 100-ha area irrigated by a VRI linear move irrigation system

There was still work to be done though and a proposal put to the Ministry for Business Innovation and Employment received six years funding in 2013 to further research methods to improve management of irrigated land. Now in its final year, the “Maximising the Value of Irrigation” programme has been able to refine methods to use proximal sensor data to create prescription maps for precision irrigation. It has developed soil and crop sensing methods that can inform in near real time the prescription map, and a prototype scheduling tool has been tested with participating farmers as a smart phone app. The in-field sensor monitoring methods have been used to support Lindsay further refine the software control features for the Precision VRI system, which is remotely managed through the FieldNET platform.

Ekanayake, J. and Hedley, C. (2018) Advances in Information Provision from Wireless Sensor Networks for Irrigated Crops. Wireless Sensor Network, 10, 71-92. 

Research into different soil management methods has identified correct tillage and soil surface management methods to store more water in the soil and reduce irrigation requirement and water losses. A spatial framework to run the APSIM model has been created to test the effect of different irrigation scenarios on yield, drainage and water use efficiency. Spatial-APSIM simultaneously runs the model for up to 1,400 grid cells for one irrigation system to compare results of different irrigation scenarios at spatial resolution < 50 m, over several decades.

The MBIE Programme “Maximising the Value of Irrigation” is now working closely with its industry advisory group to ensure that its findings are communicated effectively and to find ways to integrate new tools and support improved management of irrigated land in New Zealand.

Harvest 2019 is Upon Us!

Do you have yield mapping capabilities?

Are you storing your data in a secure location?

If your combine harvester is capable of yield mapping, do you use it? Yield map data is a powerful tool for making decisions on your farm. It is a record of how your crops reacted and performed under that season’s constraints. Constraints and variation may be apparent in your crops nutrient levels or application methods, or available water in the profile at critical times in the plant’s life cycle,and in most cases a combination of all the above!

I’ve been to many agronomy seminars where they always reiterate that when you sow your crop it starts at its maximum yield potential and everything from that point on reduces that potential. So, your yield data is a map of how well the crop has performed under that season’s conditions and how much variability there is in the soil profile within a paddock. Many arable farmers have paid for the technology but aren’t able to harness the power of the information that it provides. Agri Optics NZ are here to help with this.

Yield monitoring in any combine

One thing that isn’t stressed enough to growers with yield monitors is that they should capture the data regardless of whether they are able to use it at present or not. As having multiple years’ worth of data is far more useful than one year of data. The more years’ worth of data you have lessens the influence of a single seasons weather pattern or any out of the ordinary extremes. For example, in a wet year the lighter freer draining soils may be preferable for a higher yield and visa versa in a dry season. This process of compiling several years of data is called normalisation. Data is put into a relative scale and is compared across the years. Once data is normalised then we can identify common zones or production areas. These zones can be marked for future management decisions.

The difference between raw and processed data

Processing or “cleaning” the data is the key to successfully utilising the captured data. Raw yield points have a large amount of errors and “noise” that can significantly impact on the results. With these noisy bits removed and tidied up the data becomes more representative of the paddock. Some of the factors that impact on the data accuracy are cut width, flow delay and travel distance errors.

A processed yield map

Yield data can also be useful for identifying problems during the actual harvest of the crop. In one example a grower saw the results of him harvesting grass seed in the hottest part of the day. He was able to spot the mistake as recorded yield dropped in the swaths that he completed in the hottest temperatures. Ultimately the yield information informed him that the decision had cost him.

Making useful yield maps – the essential information

1. ‘Rubbish in equals rubbish out’ – you only get one opportunity to collect this data so ‘do it once and do it right’
2. Start the season with an empty data card - save a copy of all previous data to your computer and then ‘clean’ the card
3. Naming –use the same naming for the same paddock each year as this makes finding your data easier at the end of the season
4. Check the flow and moisture sensors – if these are not working properly then everything that follows may be a waste of time
5. Calibration – at the start of harvesting each grain type calibrate the flow sensor
6. Operation setup – make sure the cutter bar width is correct, as well as the flow delay is as accurate as possible
7. Card check and back-up – confirm data is being logged by importing it into your mapping software or sending it to your Precision Ag specialist once you start for the season...not at the end of this season! Backup the data as a raw format throughout the harvest season also.
8. If you collect the data as accurately as possible in the first place, then post-processing of the data to make it a useful resource is much simpler!

Yield data is the final measure of a seasons work. Yield data allows for insights into different management practices and the old adage “what gets measured gets managed” comes to mind. 

Have a good harvest!
Chris