Temperature loggers are a common tool grain growers use as part of their frost risk management.
So with the data loggers you probably need 20 or 30 or 40 of them through your paddocks
and that creates a lot of work every month or so to go and download them.
It's a workload that increases with the frequency of frost events.
In this environment they could be getting 20 or 30 frosts a year and to get rapid identification
of temperature across the landscape is really critical for them.
So what if there was a tool that could rapidly identify where a crop has been exposed to
damaging frost.
Well that tool has been developed and this is what the information it generates looks
like when animated.
So this is now 9pm and we can see the reds indicating temperatures above zero and the
blues are indicating temperatures that are below zero.
The tool uses modeling to analyse temperature data from field sensors together with spatial
and terrain data.
So what we're talking about when we refer to spatial data is data that's got a geographic
component or has a latitude and a longitude or a place on a map and then we use the terrain
data the elevation of the height of the land, the variability in elevation in an area or
the range of elevation in an area.
We use those extensively in this work to relate the temperatures to the terrain itself.
David Gobbett is a spatial data analyst and a member of the CSIRO team working on Frost
Mapping.
It's one of a number of projects related to GRDC's key investment target strategy for
Frost.
The little crosses here show where loggers were actually deployed in the paddocks.
Up to one hundred temperature loggers were deployed at each of two trial sites.
This one in South Australia's northeastern cropping zone, the second at Hopetoun in Victoria.
And this animation is taken from the data of each of these loggers, which was recorded
every 30 minutes.
By animating the data it helped illustrate temperature behavior across variable terrain
on a frosty night.
Part of what we found particularly interesting with these is the sort of ebbs and flows of
temperature.
So in this case by 3 o'clock almost the entire area is covered in below zero temperatures.
Strangely then at about 4:30 at night there's some sort of warming and then by 6 o'clock
its cooled down again.
So there's very little wind on this night but perhaps there was enough to cause this
air mixing and then by 7:30 the sun's coming up and you get a few residual pockets that
last awhile with sub zero then the whole area warms up.
This also highlighted the difference between on-farm weather observations compared to a
district observation, which grain growers normally rely on.
So for example here in Mintaro in the mid north of South Australia if you're farming
there your nearest Bureau of Meteorology weather station is about 15 kilometres away and its
over a range of hills, so it really doesn't tell a farmer in Mintaro what has happened
on their properties that night.
The overnight minimum at the Mintaro trial site when the animation's data was recorded
was minus 1.2 degrees.
Over the hills at Clare 15 kilometres away, the Bureau's weather station recorded an overnight
low of 2 degrees, just over 3 degrees warmer.
While CSIRO used up to a hundred loggers to record temperatures, that was only necessary
to build the data set for the model.
In practice gathering data would be a much less labour intensive system for a grain grower
as the model together with a low cost automated weather station would replace the loggers.
Access to a high quality Bureau of Meteorology compliant weather station such as this one,
could be combined with ground-truthing to further refine the temperature mapping algorithms,
resulting in even greater benefits for grain growers.
OK so an example of how this model might be used in practice, which would be down the
track a bit, would be for a farmer to have a single weather station with telemetry that
enabled the temperatures to be transmitted to a central point.
When that minimum temperature is received the model can be used to generate a map and
then sent back to the farmer by whatever method they'd prefer and so by sometime the next
morning they would have a map of temperatures across their farm.
Agricultural adviser Mick Faulkner is collaborating with growers, Agriculture Victoria and the
University of Western Australia on the mapping project's second component, using the Electromagnetic
spectrum to recognise and assess frost damaged plant tissue.
We're really looking for the wavelength in the EM spectrum that might indicate that a
plant has had some freezing damage.
The hope is to be able to use it with some remote sensing but we just don't know if that's
possible as yet.
Certainly with the PhD students at UWA and what we've been able to achieve here we have
found some signal differences and I think that's positive.
What both components of the frost-mapping project could also provide is data to help
make immediate crop management decisions such as to cut a damaged cereal crop for hay, and
to plan longer term farming system strategies.
Hopefully in the future we can use this modelling to help us base some decisions like taking
canola and certain crops out of the zone where we know we have a chance of getting frosted
and even as far as maybe variable rate seeding some paddocks and with changing varieties
in paddocks to try to minimise the frost risk and try to maximise potential for production.
Whenever the modelling tool becomes available it will have national application but it will
be just one tool in the frost management tool-kit, albeit a powerful one.
We have data layers of yield maps, we now have data layers hopefully of temperature
modelling from CSIRO and maybe another data layer is some sort of damage assessment due
to sensors.
You start putting all those data layers together and then the tool is so much more powerful
in terms of forward planning and some sort of response to frost when they occur.