Methodology
Wheat production in Australia accounts for 55% of the total cropland, averaging 12.6 million ha over the 14 seasons from 1998-9 to 2011-12 (ABARES 2012). Over that period Australian wheat averaged approximately 3.5% of world production, and 12.1% of global wheat exports (2005-2012).
Barley is Australia’s second most important grain crop. Barley production over the period from 2010-2015 averaged 8.4 million tonnes per year of which approximately 71% was exported (ABARES 2017).
The area of canola production in Australia fluctuates considerably from year to year. In the last decade the area of canola has averaged 2.6 to 3.2 million ha, approximately 20% of the wheat area (ABARES 2014). Canola was worth approximately $2.7 B in 2012-13 making it Australia’s third largest crop. Over the last 5 years 60 to 85% of the crop has been exported (ABARES 2015).
Sorghum is Australia’s most important summer grain crop. Production over the period from 2010-2015 averaged 1.9 million tonnes per year of which approximately 51% was exported (ABARES 2017).
The yield gap calculations displayed on this website are based on 15 years of data (2000 to 2014). This period is long enough to account for climate variability but short enough not to be substantially affected by technology change and climate change.
Actual yields (Ya)
The Australian Bureau of Statistics (ABS) collates national agricultural production data at the level of Statistical Area Level 2 (SA2; roughly equivalent to local shires or district councils) every five years when the national census is carried out, and at the coarser scale of Statistical Area Level 4 (SA4; which comprise of a number of SA2’s) annually. For non-census years where only the coarser data were available, SA2 crop yields (t/ha) were calculated using linear regressions fitted to census data from years between 1982 and 2010 (the Agricultural Census was conducted annually until 1996-97).
Water-limited potential yields (Yw)
Water-limited potential yields (potential yields) are best determined with a locally validated crop simulation model (van Ittersum et al. 2013). The Agricultural Production Systems sIMulator (APSIM) is a well validated cropping system model that is widely used in Australia as well as many other countries (Keating et al. 2003, Holzworth et al. 2014). It was therefore used here to generate water-limited potential yield estimates for the entire Australian wheat, barley, canola and sorghum growing areas. APSIM combines weather data, soil data, crop varieties and crop management rules to simulate crop production. Water-limited potential yields were estimated for 4040 weather stations for wheat, 3223 stations for barley, 1097 stations for sorghum and 3117 for canola. These yields were then interpolated across the Australian crop growing areas to generate estimates for each SA2. The APSIM simulations were carried out assuming current best practice and unlimited crop nutrition to ensure that water (made up of rainfall plus stored soil moisture at sowing) and climate were the only factors limiting crop growth.
Weather data was sourced from SILO Long Paddock (using the Patched Point dataset) in which recorded daily station data are augmented with interpolated data in order to generate complete daily datasets of solar radiation, temperature, rainfall, evaporation and vapour pressure for the several thousand stations in the cereal cropping zone. Simulations were run for each weather station and it was assumed that the results applied to a 20 km radius around each weather station. Give the relatively simple landscape of much of the crop growing areas of Australia this is a conservative estimate.
The nine major soil types used for growing wheat in Australia were identified from ASRIS maps. Their average water holding capacities were derived from the APSoil database. Separate simulations were run for up to three of the most common soil types which occur within the area bound by the 20 km radius of each weather station. Yield results were then aggregated, weighted by wheat land use area of each soil type, to calculate a single estimate of Yw for each weather station.
Photographic depictions of these soil types are available for viewing in the soil poster: http://www.clw.csiro.au/aclep/asc/Soil_Poster.pdf
Soil Name
Description
(based on: R.F Isbell. 1996. The Australian Soil Classification. CSIRO Publishing, Victoria pp 143 and the CSIRO/ACLEP/ASC Soil Poster)
Soils that are calcareous (presence of carbonate segregation or fine earth) to depth (directly below the A1 horizon or at a depth of 20 cm) and do not have clear or abrupt textural B horizons. These soils are widespread in southern Australia.
- Contain calcium carbonate as soft or hard white fragments or as a solid layer
- Occur in the low rainfall, arid and semi-arid regions of Australia
- Land use includes cereal growing and irrigated horticulture in the south and sparse grazing in the north
- Limitations include shallow depth, low water retention due to hard carbonate content and wind erosion on the sandier types.
High salinity, alkalinity and sodicity may also be a problem. Soil fertility deficiencies are widespread.
Soils with strong contrast between A horizons and B horizons. B horizons are not strongly acid and not sodic. These are among the most widespread soils used for agriculture in Australia, particularly those with red subsoils.
- Abrupt increase in clay content down the soil profile.
- Common in the cereal belt of southern New South Wales and Victoria.
- Many have hard-setting surfaces with structural degradation caused by agriculture.
May have impeded internal drainage.
Soils with structured B2 horizons and lacking strong texture contrast between A and B horizons. Moderately deep and well-drained soils of wetter areas in eastern Australia.
- May be strongly acid in the high rainfall areas or highly alkaline if they contain calcium carbonate
- Occur in the mountainous high rainfall zones of south-eastern Australia
Cereal crops, especially wheat, are commonly grown on the more fertile Dermosols.
Soils with B2 horizons which are high in free iron oxide, and which lack strong texture contrast between A and B horizons.
- High free iron and clay contents
- Occur along the eastern coastline, in northern parts of Western Australia and the Top End
- In high rainfall zones they may be very deep and well drained
- May be degraded by erosion and compaction caused by cropping practices and may also suffer from acidification
Soils which lack strong texture contrast, have massive or only weakly structured B horizons and are not calcareous throughout.
- Mostly well-drained, permeable soils although some Yellow and most Grey Kandosols have impeded subsoil drainage
- Common in all States except Victoria and Tasmania. Most widespread in the arid and semi-arid interior
- Used for extensive agriculture in the wheat belt of southern New South Wales and southwest Western Australia.
- In the better watered areas they are used for a range of horticultural crops
Most have low fertility and land use is restricted to grazing of native pastures.
Soils with B horizons dominated by the accumulation of compounds or organic matter, aluminium and/or iron.
- Most are very permeable unless indurated pans are present
- Largely confined to parts of the coastal zone and some offshore islands
Agricultural use is limited because of extremely low fertility, poor water retention and the seasonal waterlogging in some forms.
Soils with strong texture contrast between A horizons and sodic B horizons which are not strongly acid.
- Abrupt clay increase down the profile and high sodium content, which may lead to soil dispersion and instability
- Seasonally perched water tables are common and subsoil horizons have a striking prismatic or columnar appearance
- Usually associated with a dry climate and widely distributed in the eastern half of Australia and western portion of Western Australia
- Many will hard-set when dry and are prone to crust formation
Dispersive subsoils makes them particularly prone to tunnel and gully erosion.
Soils with generally only weak pedologic organisation apart from the A horizons. It encompasses a rather diverse range of soils.
- Widespread in the eastern half of the continent where vast areas occur as red and yellow sand-plains
- Large areas in Western Australia have red loamy soils with red-brown hardpan at shallow depths
Due to their poor water retention, almost universal low fertility and occurrence in regions of low and erratic rainfall, Tenosols are mainly used for grazing of native pastures.
Clay soils with shrink-swell properties that exhibit strong cracking when dry. Have slickensides and/or lenticular structural aggregates at depth. Many have gilgi microrelief. May be deep (up to 6m or more).
- Used for grazing of native and improved pastures, extensive dryland agriculture where rainfall is adequate, and for irrigated agriculture
Problems of water entry are usually related to tillage practices and adverse soil physical conditions at least partly induced by high sodium in the upper part of many profiles.
Five wheat maturity types, three canola maturity types, six barley maturity types and one sorghum maturity type were simulated for each weather station and soil combination. The maturity type which gave the highest average yield over the nineteen year period was chosen for use in the calculation of Yw for that station. The maturity types for wheat were: early maturing (e.g. Wyalkatchem); mid-early maturing (e.g. Corell); mid maturing (e.g. Derrimut); mid-late maturing (e.g. Endure); and late maturing (e.g. Bolac). The maturity types for canola were: early maturing (e.g. Diamond); early-mid maturing (e.g. Gem); and mid maturing (e.g. AV-Garnet). All canola was simulated with a conventional growth type without penalties associated with herbicide resistance. The maturity types for barley were: very early maturing (e.g. Hindmarsh); early maturing (e.g. LaTrobe); mid-early maturing (e.g. Commander); mid maturing (e.g. Baudin); mid-late maturing (e.g. Gairdner); and late maturing (e.g. Oxford). The maturity type for sorghum was a mid maturing type (e.g. Buster). Buster was simulated at three sowing densities of 5, 7 and 9 plants/m² . The sowing density which gave the highest average yield over the nineteen year period was chosen for use in the calculation of Yw for that station.
APSIM simulations include management rules for sowing dates and fertiliser application. Sowing dates for wheat, canola and barley were based on latitude on the east coast of Australia (i.e. north or south of Dubbo at latitude -32.24), rainfall and soil plant available water (PAW).
For northern locations (Qld and NSW stations north of Dubbo):
- Sow wheat if rain >= 15mm over 3 days and PAW >= 30mm from 26 April-15 July
- Sow canola if rain >= 15mm over 3 days and PAW >= 30mm from 20 April-15 June
- Sow barley if rain >= 15mm over 3 days and PAW >=30mm from 26 April-15 July
For southern and western sites:
- Sow if rain >=15mm over 3 days regardless of soil moisture from 26 April-15 July
- Sow if rain >= 15mm over 3 days regardless of soil moisture from 20 April-15 June
- Sow barley if rain >= 15mm over 3 days regardless of soil moisture from 26 April-15 July
If the above criteria were not met the simulated wheat crop was dry-sown on 15th July, canola on 15th June and barley on 15th July. Wheat sowing density was 150 plants m–², row spacing was 0.25 m and sowing depth was 3 cm. Canola sowing density was 40 plants m–², row spacing was 0.18 m and sowing depth was 2 cm. Barley sowing density was 150 plants m–², row spacing was 0.25 m and sowing depth was 3 cm.
Sowing dates for sorghum were based on latitude (ie Central Qld at latitude > -25o; Southern Qld at latitude -25o to -29o; and Northern NSW at latitude < -29o) and rainfall.
For Central Qld locations:
- Sow sorghum if rain >= 20mm over 5 days from 15 September-15 January
For Southern Qld locations:
- Sow sorghum if rain >= 20mm over 5 days from 15 September-15 January
For Northern NSW locations:
- Sow sorghum if rain >= 20mm over 5 days from 15 October-15 January
If the above criteria were not met a sorghum crop was not simulated. Sorghum sowing density was 5, 7 and 9 plants m–², row spacing was 1.0 m, sowing depth was 3 cm and solid planting was simulated.
Fertiliser was applied during simulations to ensure that rainfall was the only factor limiting crop growth. For wheat, soil nitrate in the top 60 cm of soil at sowing was topped up by 100 kg/ha nitrate minus nitrate in top 60 cm of soil on 25 April. A further 70 kg/ha nitrate was added if nitrate in the top 60 cm of soil fell below 80 kg/ha and soil plant available water was greater than 30 mm. This was done until Zadoks growth stage 49 (first awns visible). For canola, nutrients (i.e. soil nitrate) were topped up by 50 kg N/ha whenever soil nitrate in the top 60 cm was less than 50 kg N/ha up to anthesis. At time of canola sowing, add 250 kg NO3/ha minus the amount of soil nitrate in top 60 cm of soil on April 25. At bud visible (APSIM stage 5.5) add 100 kg N/ha. For barley, the same fertiliser rules were used as for wheat. For sorghum, soil nitrate in the top 60 cm of soil at sowing was topped up by 175 kg/ha nitrate minus nitrate in top 60 cm of soil on 1 September. A further 70 kg/ha nitrate was added if nitrate in the top 60 cm of soil fell below 80 kg/ha and soil plant available water was greater than 30 mm. This was done until appearance of the flag leaf.
The APSIM canola model does not reduce grain yield in response to heat and frost shock around flowering and adjustments to simulated yield were made based on daily temperatures around the sensitive period around flowering and early grain filling (see Lilley et al 2015). This frost/heat adjusted yield is the variable used on this website for canola.
Potential yields were aggregated for each met station by weighting the soil type simulations by their crop land use areas. Local kriging was used to smooth out the individual met station estimates to determine annual Yw values for each SA2 and each year.
Yield gap and yield potential
The yield gap (Yg) and relative yield (Y%) were calculated from the actual yield (Ya) and water-limited yield (Yw) for each SLA and year.
Yg = Yw – Ya
Y% = (Ya / Yw) x 100
Soil specific potential yields (used in Compare My Farm tool)
An estimate of potential yield for each soil type within each SA2 was produced for the Compare My Farm tool. The water-limited potential yields calculated for the different soil types at each weather stations were averaged within each SA2. This produced Yw estimates for between one and seven soil types in each SA2.