Peak irrigation requirement key to peak profitability
Jim Phillips, JP Water Pty Ltd and Jeremy Cape, CapeAbility Pty Ltd
John Mc Donnell of Rivulis (left) and grower David Sjroh with the Q208 cane that yielded 238 t/ha.
There is a disturbing pattern developing in crops such as sugar cane, almonds and macadamias that is raising questions about how much water a crop requires to meet its best potential. The pattern being observed is that some growers who are generally considered to be “over irrigating” are achieving dramatic increases in yields.
Recently, cane grower David Sjroh at Mareeba Queensland achieved a very high yield of 238 t/ha, similar to that recorded for Terry Cunningham at Bundaberg in the early 1990s. It was also achieved in Mexico in the mid-1990s. Are these tonnages anomalies or is there something different these growers did to achieve them?
Peak irrigation requirement – underestimated?
Many of our farms are under irrigated possibly because peak irrigation requirement (PIR) is underestimated. Often water supply is a cause of under irrigation or, perhaps, irrigation has been looked upon by the grower more as a necessary expense to be minimised than an important part of farm management. Irrigation does not stand alone, rather it is an integral part of the overall farm management package; it works in harmony with agronomy and overall farm management practices to offer the best opportunity of making a farm a viable enterprise.
The starting point for planning any irrigation enterprise is specifying PIR for the crop or plants to be grown. Specifying PIR is critical in determining how available water can be used, over what area, at what times of the year and in what type of irrigation system it can best be applied. While there are good sources of the information available to estimate PIR, such as the Bureau of Meteorology, FAO’s LocClim and CropWat and the Queensland Department of Agriculture’s KMSI program, recent work at Mareeba on the Atherton Tablelands has underlined the importance of developing accurate PIR for each site (see tables 1 and 2).
Table 1 details calculations of PIR for Mareeba using LocClim and KMSI done by JP Water for their client David Sjroh.
The calculated PIR are based on weather data and a crop coefficient that ranges from 0.52 to a maximum of 1.56. Evapotranspiration (the column headed PET/day mm max. in Table 1) is multiplied by the crop coefficient to estimate the PIR(max) in mm per day. This gives an estimate of water requirements for each stage of crop growth, as the coefficient varies throughout the growing season.
| Month | Precipitation | Evapotranspiration | Peak irrigation water requirement | |||
|---|---|---|---|---|---|---|
| mm/month (min) | mm/day (min) | PET/mth mm (max) | PET/day mm (max) | PIR/day mm (max) | PIR/week | |
| January | 268.41 | 8.66 | 180.85 | 5.83 | 8.50 | 59.53 |
| February | 324.49 | 11.59 | 155.26 | 5.55 | 7.52 | 52.63 |
| March | 335.31 | 10.82 | 169.88 | 5.48 | 5.76 | 40.31 |
| April | 131.67 | 4.39 | 160.35 | 5.35 | 3.80 | 26.63 |
| May | 0 | 0 | 148.86 | 4.80 | 2.82 | 19.75 |
| June | 0 | 0 | 144.80 | 4.83 | 2.84 | 19.85 |
| July | 0 | 0 | 149.38 | 4.82 | 2.83 | 19.82 |
| August | 0 | 0 | 165.08 | 5.33 | 3.91 | 27.38 |
| September | 13.39 | 0.45 | 184.82 | 6.16 | 5.99 | 41.91 |
| October | 30.15 | 0.97 | 200.62 | 6.47 | 8.26 | 57.84 |
| November | 82.29 | 2.74 | 194.85 | 6.50 | 9.91 | 69.35 |
| December | 147.29 | 4.77 | 195.98 | 6.32 | 11.14 | 78.01 |
| Average | 111.14 | 3.70 | 170.89 | 5.62 | 5.90 | 41.33 |
Table 2 details modified PIR for each month using a crop coefficient that was amended to account for additional stress on the crop resulting from pests, weeds and temperature. The stress factor was estimated based on the farmer’s experience.
Using this approach the PIR for December increased from 11.14 to 13.93 mm/day. The data in Table 2 was used for setting the operating parameters and design of the irrigation system.
| Month | Precipitation | Evapotranspiration | Peak irrigation water requirement | |||
|---|---|---|---|---|---|---|
| mm/month (min) | mm/day (min) | PET/mth mm (max) | PET/day mm (max) | PIR/day mm (max) | PIR/week | |
| January | 268.1 | 8.66 | 180.85 | 5.83 | 10.63 | 74.41 |
| February | 324.49 | 11.59 | 155.26 | 5.55 | 9.40 | 65.79 |
| March | 335.31 | 10.82 | 169.88 | 5.48 | 7.20 | 50.39 |
| April | 131.67 | 4.39 | 160.35 | 5.35 | 4.76 | 33.29 |
| May | 0 | 0 | 148.86 | 4.80 | 3.53 | 24.69 |
| June | 0 | 0 | 144.80 | 4.83 | 3.55 | 24.82 |
| July | 0 | 0 | 149.38 | 4.82 | 3.54 | 24.77 |
| August | 0 | 0 | 165.08 | 5.33 | 4.89 | 34.22 |
| September | 13.39 | 0.45 | 184.82 | 6.16 | 7.48 | 52.38 |
| October | 30.15 | 0.97 | 200.62 | 6.47 | 10.33 | 72.30 |
| November | 82.29 | 2.74 | 194.85 | 6.50 | 12.38 | 86.69 |
| December | 147.92 | 4.77 | 195.98 | 6.32 | 13.93 | 97.51 |
| Average | 111.14 | 3.70 | 170.89 | 5.62 | 7.38 | 51.66 |
Local conditions determine irrigation requirement
In Mareeba, spring cane planting starts in late August so the highest PIR is in the following November to January period. Ideally, the irrigation design would be able to apply the required PIR from 120 to 140 hours of operation each week. This is about 20 hours per day with a “reserve” of 24 to 48 hours per week.
David Sjroh is gradually increasing the irrigated area of his farm using subsurface drip irrigation (SDI). His rows of cane are 1.8 m apart with each row of cane having its own lateral of drip tape. The application rate is 2.25 mm/hr. As he expands the area of drip, the calculation of PIR was critical to the design. David’s experience was that it was necessary to apply 14 mm/day in December or he would suffer lower returns so an SDI system was designed which met these requirements.
The impact of different PIR is shown in Table 3.
The daily PIR in Table 3 was selected as:
- 11.2 mm is the standard calculated PIR using KMSI figures
- 5.25 mm is the average PIR
- 7.5 mm is the PIR that could be supplied within the constraints of Queensland electricity Tariff 62
- 13.4 mm is the maximum PIR applying a stress factor of 0.8 to the standard PIR
No allowance was made in the calculations for rain or storm events.
| Application calculation | ||
|---|---|---|
| Daily PIR mm/hr | Hours available | Hours/week |
| 11.2 | 5 | 140 |
| 5.25 | 2.35 | 65.8 |
| 7.50 | 3.5 | 98 |
| 13.40 | 6 | 168 |
Considering these time constraints highlights the need for growers to make their own decisions about the area of irrigation. The grower has to answer the question as to whether it is better to grow a larger area with just enough water or a smaller area with the optimum amount of water. The answer is likely to vary from enterprise to enterprise.
Application is an important consideration as this has to be taken into account when estimating operating times. JP Water designed a system that comprised a single row of drip for each row of cane. The capital costs of this system were higher but its operating costs lower because the alternative of a drip line between two rows of cane was less efficient and required longer run times on the relatively light soils on the farm. Non-pressure- compensating drip was chosen so that variable application rates were possible. A higher inlet pressure would give an increased application rate, which might be necessary to meet higher PIR.
All these issues were considered by the designer and grower who worked closely to achieve the system David wanted.
The bottom line – higher yields
Sloping country in which non-pressure compensating drip was installed.
The results on the Sjroh farm, which are impressive, are causing some controversy in the industry as they fly in the face of conventional practice, however, the results speak for themselves.
In a recent harvest the farm cane productivity report from the Mareeba mill showed that he had achieved an average yield across his whole farm of 137 t/ha against the mill average of 95 t/ha. His peak yield was 238 t/ha. Most importantly, his net return was $4,450/ha compared with the mill average of $2,600/ha. In addition, actual water use over the season dropped from about 8 to 11 ML/ha to 6.5 to 7.2 ML/ha even though applications were higher than industry average at particular times of the season based on crop factor and plant physiology.
This case study highlights the importance of a good working relationship between the irrigation designer and the grower and of considering all of the key plant-soil- water relationships in achieving a first class return. Accurately estimating peak irrigation requirement leads to peak profitability.
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