Evaluation of the performance of automated bay irrigation

Smith, Rod and Uddin, Jasim and Gillies, Malcolm (2014) Evaluation of the performance of automated bay irrigation. Project Report. University of Southern Queensland, National Centre for Engineering in Agriculture , Toowoomba, Australia. [Report]


High flow bay irrigation together with automation and accurate and precise timing gives what we are calling High Flow Precision Bay Irrigation. This project seeks to demonstrate to farmers the extent of the efficiency gains that are possible with this system and the management strategies necessary to achieve those gains.

In recent evaluation studies conducted by the CRC for Irrigation Futures (Smith et al., 2009 and Gillies et al., 2010) higher irrigation flows have been shown to offer very much improved (volumetric) application efficiencies, well above those currently achieved across the GMID. On all but the lightest soils efficiencies in excess of 85% should be achievable, reaching as high as 95% on some soils.

Irrigation duration (or time to cut-off) is critical in reaching those efficiencies. As flow rates are increased, the optimum duration decreases dramatically. Consistent with this, the accuracy and precision required in estimating and controlling the irrigation duration increases. The difficulty is compounded by the fact that conditions can change with each irrigation, for example, changes in irrigation flow rate, crop density, soil moisture, hence the optimum time to cut-off (Tco) also changes. Management needs to adapt to these changes.

Automation of bay irrigation, such as the Rubicon FarmConnect® system (http://rubicon.com), provides the needed certainty in managing irrigation durations (along with very substantial labour efficiencies). Measurement of flow rate (SmartMeter Gateway) and the irrigation advance (FloodTech depth sensor) early in each irrigation should provide the data needed to calculate in real-time the precise time to cut-off required for that irrigation. Various methods are appear feasible and include empirical guidelines (Smith et al., 2013), volume balance calculations, and full hydrodynamic simulation (Smith et al., 2012)

The principal objective of the study was to demonstrate the gains in application efficiencies possible through the use of optimally-managed, automated, high-flow bay irrigation. A secondary objective (that will be the subject of a later paper) was to evaluate the techniques for calculating the irrigation duration (or time to cut-off) for each irrigation in real time, using data captured during that irrigation, in sufficient time to provide optimum control of that irrigation.

Nine existing automated farms were selected for the trial that together represent the range of soils, bay geometries, and crops typical of the GMID. A SmartMeter Gateway was installed at each site giving a measure of the flow rate onto the farm from which the flow rate down each trial bay could be inferred. Three Rubicon FloodTech depth sensors were installed in each bay, located at approximately one third of the distance down of the field, at two thirds distance, and near the downstream end. These sensors record the rate of advance of the irrigation flow down the bay and a measure of the flow depth at each point throughout the entire irrigation. The first sensor location was that thought to be useful in the real-time control of irrigations.

The key performance measure used in the evaluations was the application efficiency, which is a measure of the water lost (as tail-water run-off or deep percolation below the root zone) in irrigating a given bay. A total of 46 irrigations across the various sites were evaluated. Analysis of each event included calibration of the surface irrigation hydraulic simulation model SISCO from the measured flow rate, advance and depth data, and simulation of each event using SISCO to give the required performance parameters. These provide the main reportable outcome from the project. The evaluation data is also able to be used to explore the techniques that can be used to calculate Tco.

The results from the evaluations, summarised in the table below, demonstrate that application efficiencies in excess of 90% are indeed achievable and being achieved through correct and precise management of automated surface irrigation. Four of the farms evaluated in this study are already operating at that level. For four of the other five farms strategies have been identified that will raise their efficiency close to or above 90%. On the remaining farm (farm R) soil limitations preclude any improvements in efficiency on the trial bay. Fortunately this bay is not representative of the remainder of the farm where higher efficiencies would be expected.

Summary of results
Farm No of Irrigations Application Efficiency (%) Recommended Action
Ll 6 95 Nil required
Q 1 87 Monitor more events
P 5 92 Nil required
I 9 74 Reduce time to cut-off to 90 min
Th 5 63 Cut off when advance reaches 50% of length
M 6 68 Cut-off at 90 min and irrigate less frequently and at consistent soil moisture
R 7 63 None possible – conduct further trials on a more representative bay
G 2 90 Cut off when advance reaches 50% of length
D 5 56 Grade bay, flow rate 20 ML/d, cut off at 100 min & re-evaluate

Farm Ll is the prime example of a high performing farm. For the irrigations evaluated on that farm application efficiencies between 90 and 100% were consistently obtained. This means that on average 95% of the water supplied to the farm was added to the crop root zone and made available to the crop. Losses to either tail-water runoff or deep percolation were a low 5%. These results were achieved through consistent, correct and precise management of the irrigations. Soil moisture measurements were used to determine when to irrigate, with each irrigation commencing at about the same moisture content. The same flow rate was applied at each irrigation and for the same duration (with minor adjustments to compensate for slight differences in the starting soil moisture content). The duration was selected to minimise tail-water runoff. Over time this farmer reduced his irrigation durations to the point where the advance just reached the end of his field. The management on this farm provides a model for all irrigators.

There are two main reasons for the relatively low efficiencies on some farms. First and most common is the use of irrigation durations of excessive length. This typically results in excessive tail-water runoff. It also means that water is present on the surface of the bay for long periods of time which leads to waterlogging of the soils and reduced pasture growth. Indication of this was evident in the soil moisture data from at least four farms. The second reason for low efficiencies on two farms was the use of flow rates that were too low for the particular soils. This led to excessive deep percolation loss. Both causes of low efficiencies are easily remedied by correct selection of flow rate and duration.

One further factor, important in its own right, which also contributed to the low efficiencies, was the selection of when to irrigate. All trial bays had soil moisture probes installed and the data from the probes was available to the farmers to aid in their irrigation management. It allows farmers to select an appropriate refill point, that is, the soil moisture level at which they should irrigate. Typically this is the point at which the water consumption by the crop or pasture just starts to decline. By irrigating sooner, the soil is maintained in a wetter state, and the crop develops a shallower root system. The result is more frequent waterlogging and reduced production. From an irrigation efficiency perspective, it is easier to obtain high application efficiencies when the soil moisture deficit is greater. In a number of cases the soil moisture data gathered in this study indicated that farmers were irrigating well before the true refill point was reached and that the period between irrigations could have been extended by at least two days. These same farmers were also inconsistent in the moisture content at which they irrigated. This meant that the optimum irrigation duration varied from one irrigation to the next making the task of estimating the duration more difficult.

Finally, it is worth noting that the automation per se does not confer high efficiencies. The management skill of the grower is a critical factor. He/she is still required to determine when to irrigate, the flow rate to be used and the duration appropriate to that flow rate. Once selected the automation provides precision in the application of those decisions.

Statistics for USQ ePrint 27349
Statistics for this ePrint Item
Item Type: Report (Project Report)
Item Status: Live Archive
Additional Information: Report to Rubicon Water and Goulburn Murray Water. NCEA Publication 1005612/1. USQ publication.
Faculty/School / Institute/Centre: No Faculty
Faculty/School / Institute/Centre: No Faculty
Date Deposited: 23 Jun 2015 05:42
Last Modified: 06 Nov 2017 23:42
Uncontrolled Keywords: high flow precision bay irrigation; performance
Fields of Research (2008): 07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070101 Agricultural Land Management
Fields of Research (2020): 30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300202 Agricultural land management
URI: http://eprints.usq.edu.au/id/eprint/27349

Actions (login required)

View Item Archive Repository Staff Only