Know your environment to get the most out of N
Author: Rebecca Barr | Date: 27 Mar 2015
Growers who want to get the most out of their nitrogen applications need to focus on knowing their soils and the climate, according to Queensland University of Technology's Peter Grace.
Professor Grace says the first step in defining a nitrogen program is for growers to observe how their soils respond to rainfall to better understand how they are likely to lose nitrogen (see breakout box on types of N loss).
“With nitrogen application there are no set rules. Everything is dependent on the grower’s soil type and both the seasonal and short-term forecasts for the farm, so there is no hard and fast rule for when or how much to apply,” Prof Grace said.
“Sandy soils are far more likely to experience leaching, as the coarse-grained particles facilitate good drainage, and because nitrate is highly soluble, it will drain out of the soil profile with the water. Clay soils on the other hand, are more susceptible to denitrification because they’re more likely to reach saturation for prolonged periods of time.”
He suggests monitoring soil moisture to increase understanding of plant available water capacity and a soil’s response to rainfall. Soils with a large plant available water capacity – also called the soil moisture ‘bucket’ – will require very heavy rainfall to reach saturation and for N to leach. Soils with a small plant available water capacity will be more likely to experience N losses after rain.
“By observing this response, growers can learn what level of rainfall will cause denitrification or leaching, and avoid top-dressing before such a rainfall event,” Prof Grace said. “There are complications for alkaline soils where the third type of loss, volatilisation, can occur if there isn’t enough rain. That’s why it’s so important that growers know how their soils respond and also learn how to use weather forecasts.”
“If the longer range forecast isfor a wet season, then the yield potential is likely to be high, and also there’s likely to be big rainfall events that may make it difficult to top-dress nitrogen later in the cropping cycle. In this case, it’s probably a good plan for the grower to put out a bit more nitrogen up-front. However in an average or dry year, there’s more risk in paying for that extra nitrogen up-front, so a grower may want to apply less up-front and wait for a suitable forecast rain event during the season when the crop is ready to take it up,” Prof Grace said.
For short-term forecasts, growers can use their soil and plant available water knowledge to wait for a rain event that will wash the fertiliser in, reducing the risk of volatilisation, but not so much rain that denitrification or leaching is a risk.
Prof Grace recommends growers use the POAMA tools provided by the Bureau of Meteorology to identify the most likely seasonal conditions. While forecasts are never certain, they give the most probable outcome so growers can use them to decide, based on their soils and crop type, how to allocate their nitrogen budget.
Climate Forecasting: POAMA
Seasonal climate forecasting has long been a controversial topic for grain growers, and in the past forecasts have been considered with low levels of confidence. However since the transition to the Bureau of Meteorology POAMA model in 2013, seasonal forecast accuracy has improved substantially.
POAMA, which has been supported by the GRDC through the Managing Climate Variability (MCV) program, models the climatic conditions based on the laws of physics, and on ocean, atmosphere and land observations. This is distinct from previous forecasting methods using statistical techniques, which had a lower accuracy due to their simplicity, and decreasing accuracy due to climate change altering the usefulness of historical statistical relationships.
CSIRO Oceans and Atmosphere Flagship researcher Peter McIntosh says that while climate forecasting will never be perfect, it is already very useful. POAMA forecasts of above or below median rainfall during the growing season are correct 60-80 per cent of the time over most of the grain growing regions, and this level of skill can be very valuable over a number of years.
“Think of it as flipping a coin. Without additional knowledge, you can only assume the coin is not biased, and is equally likely to turn up heads or tails. POAMA gives information about how the climate coin is biased each year, and in the long run this can be very useful to a farmer” he said.
The accuracy of the model varies both with location and the time of year. Tasmania has lower accuracy as the weather is influenced by more complex factors compared to the south-east mainland, which has higher accuracy. Forecasts improve further into the calendar year due to influences of ENSO (El Nino Southern Oscillation).
While POAMA was originally devised as a nine month seasonal forecast, researchers later identified that it had good accuracy for forecasting on multi-week timescales beyond traditional weather forecasts.
“Weather systems can be predicted out to about 10 days. Within this period, weather models can forecast where the fronts and pressure systems will move. Beyond 10 days, however, we can only forecast how climate drivers such as ENSO change the average behaviour of weather, and this is where POAMA comes in” Dr McIntosh said.
The latest version of POAMA, currently available from the BOM website with a login, provides forecasts from one week up to nine months.
The model is still improving, with MCV researchers including Dr McIntosh working on improving value from the model for grain growers. In parallel Dr McIntosh is working on a GRDC funded project to incorporate POAMA into Yield Prophet.
“Currently growers can forecast yield based on previous years’ weather, or can choose only, say, El Nino years. Our project will incorporate the actual POAMA predictions for the current season and therefore produce 33 possible scenarios which will give probability curves for grain yield. We’re currently developing this system and hope to have it available for growers in a few years,” he said.
MCV have measured the benefit of understanding forecasts, modelling the yield growers would obtain with nitrogen applications based on POAMA compared to no forecasting.
“Studies we’ve performed in Western Australia showed that in the long run, using POAMA provided growers with a $50/ha benefit per year on average compared to using no forecast. This is because improved knowledge of the seasonal forecast allowed for more informed nitrogen applications, providing the opportunity to maximise yield potential in wet years, or save fertiliser costs in dry years” Dr McIntosh said.
Organic MatterProf Grace says that the key to reducing the risk of nitrogen loss is having adequate organic matter in the soil.
“Organic matter supplies native nitrogen to the plant in a form that is slow-release. Because of the slow release, there’s less plant available nitrogen at any time to be lost, so overall nitrogen loss is lower. In sandy-loams, loams and clays, organic matter also improves aggregation of the soil, which improves soil structure, increases the plant available water capacity and improves infiltration. If the water can get in and move into the profile and drain relatively freely, the risk of denitrification is reduced,” he said.
Options to improve organic matter include pasture rotations, reduced tillage, stubble retention, and where soils are very sandy, clay spreading or delving can be considered.
“In essence, conservation farming practices will put any grower well on the way to maximising N conversion into the crop. By reducing the external nitrogen input, growers are saving fertiliser costs and making it easier to balance the requirement to add sufficient N to maximise crop yield with the limited top-dressing opportunities in a season,” Prof Grace said.
07 3138 9283
Dr Peter McIntosh
03 6232 5390
- Read the GRDC Factsheet
- Learn about nitrogen mineralisation
- Get started with soil moisture monitoring
- Visit the Managing Climate Variability website
GRDC Project Code DAF00004-15, UNE000012, DAN00144, CMA00003
Region South, North