Sugarcane projects

Sugarcane harvest

Sugarcane project computation

November 2023 release

Underpinning the P2R Projector Sugarcane project fine sediment, dissolved inorganic nitrogen (DIN) and pesticide savings, are summarised constituent generation rates, taken from a large suite of P2R paddock modelling simulations (simulations applied using the ApSIM modelling framework).

The responses to the Sugarcane project survey questions provide numeric values, and based on expert weightings these are combined to provide survey scores for soil, nutrient, irrigation, and pesticide management. Using defined ranges, the weighted scores are used to align the farm’s before and after practices to the most closely matched simulation in the available ApSIM simulation suite. This allows an area-based estimate of constituent generation reduction to be calculated. These constituent generation rates have already considered proportion of fine sediment in total eroded soil mass, and the ratio of each constituent delivered to stream. Fine sediment and pesticides are assumed to only be carried to the stream in overland flow (runoff). DIN is conceptually provided via two pathways – runoff and through deep drainage seepage.

Recognising the spatial complexity built into the P2R paddock modelling simulation design, there are spatial layers used in P2R Projector to provide locational context for:

  • Soil type (distribution of P2R paddock modelling soil attribute collections), and
  • Climate series (Identifier of P2R paddock modelling collection), and
  • District (Identifier of P2R paddock modelling collection), and
  • River System Delivery Ratio (RSDR for each constituent, from P2R catchment modelling)

Each P2R Projector Sugarcane project polygon is intersected with the soil, climate, district and RSDR spatial layers, and constituent generation rates are calculated for each soil intersection (with dominant climate series and district based NUE used to select appropriate simulations). These intersections are proportionately combined to give the project (before and after practice change) constituent generation rates. Any calculations that require a specific fertiliser or yield value use weighted averages from the survey responses, with plant and ratoon components of the crop cycle considered.

Finally, a representative RSDR (dominant RSDR from project polygon intersection) is applied to each constituent generation rate, allowing calculation of a constituent load reduction as delivered to the Great Barrier Reef.

josh-withers-cane-train

New band calculation method based on Nitrogen Loss Risk Index (NiLRI)

November 2022 release

The November 2022 release applies the Nitrogen Loss Risk Index (NiLRI) across all bands. NiLRI is the ratio of Nitrogen (N) fertiliser applied to crops and the cane yield expected (i.e. kg N / t cane). The pre-November 2022 version (version 3) employed this approach to assign sites into bands one to six. This release also includes sub-steps [link] to provide greater sensitivity of load reduction to changes in N application rates.

This approach simply allows representation of any farm management improvements that increase expected yield, and/or reduce N fertiliser rate for a given yield. The tool can now represent relatively small, estimated dissolved inorganic nitrogen (DIN) load reductions.

BandNiLRI/NUE
1Less than 0.900
1.10.940
1.20.980
1.31.020
1.41.060
21.100
2.11.144
2.21.188
2.31.232
2.41.276
31.320
3.11.380
3.21.440
3.31.500
3.41.560
41.620
4.11.684
4.21.748
4.31.812
4.41.876
51.940
5.11.952
5.21.964
5.31.976
5.41.988
6Greater than 2.000

References

Peter J. Thorburn, Jody S. Biggs, Kevin McCosker, Adam Northey. 2022. Assessing water quality for cropping management practices: A new approach for dissolved inorganic nitrogen discharged to the Great Barrier Reef. Journal of Environmental Management. Volume 321.  https://doi.org/10.1016/j.jenvman.2022.115932

chaz-mcgregor-cane-farm-storm-portrait

Sugarcane industry mill mud management will not report nutrient saving for individual projects

November 2022 release

The dissolved inorganic nitrogen (DIN)savings from mill mud management are represented in catchment models rather than the P2R projector tool. Mill mud is a by-product of the sugar milling process and the majority of it is spread across cane paddocks. There are significant amounts on nitrogen (N) in mill mud and by reducing the application on one farm, it may reduce DIN generation and loss from that farm.

However, the remaining mill mud can be applied elsewhere in the catchment, meaning landholders cannot guarantee that there is a net reduction in DIN to the Reef by farm scale mill mud management programs.

Previous versions of P2R Projector (up to Nov 2022) accounted for the use of mill mud as part of the farm scale N balance for determining potential N surplus. P2R Projector would account for reported changes in ‘before’ and ‘after’ mill mud application rates to determine the overall N budget and potential DIN savings. Changing the mill mud application rate between the ‘before’ and ‘after’ surveys results in no estimated DIN load reductions in the P2R projector tool. The ‘before’ mill mud application rate is the default value used for both the before and after case (as of Nov 2022 release).

The mill mud use questions have been retained in the sugarcane practice survey because they are used in the collective Paddock to Reef Integrated Monitoring, Modelling and Reporting program (Paddock to Reef program). The Paddock to Reef program level modelling considers the collective impact of all previously reported practice change, and as such the modelling approach has the capacity to include the impact of spatial patterns of changes in in mill mud use.

Sugarcane industry finer resolution of results

November 2022 release

Additional steps in DIN reductions are calculated using a linear interpolation equation. For example, if a site moves halfway to the next existing band, the estimated DIN load reduction will be half of the impact of that change.

Previous versions of P2R Projector (up to Nov 2022) estimated DIN savings by calculating the difference in DIN loss between the before band and the after band. As an example, the before band of five (original bands) might have a DIN loss of 10kg N/ha and the practice change moves the project to band four which might have a DIN loss of 6kg N/ha. Hence, a DIN saving of 4kg N/ha (10kg/ha – 6kg/ha).

Worked example of DIN reduction using the combination of NiLRI approach and sub-steps

November 2022 release

As no additional modelling is available to represent the additional steps the DIN savings are calculated using a linear interpolation equation. For example, if a site moves halfway to the next existing band, the estimated DIN load reduction will be half of the impact of that change.

In the pre-November 2022 version of P2R Projector, DIN savings are estimated by calculating the difference in DIN loss between the before band and the after band. As an example, the before band of 5 (original bands) might have a DIN loss of 10kg N/ha and the practice change moves the project to band 4 which might have a DIN loss of 6kg N/ha. Hence, a DIN saving of 4kg N/ha (10kg/ha – 6kg/ha).

In the October 2022 version, the DIN loss values for five intermediate steps between the bands must be estimated. This is done using the liner interpolation equation below.

linear interpolation equation

y = interpolated DIN losses
x = given Nitrogen Loss Risk Index (NiLRI)
x1 = lower Nitrogen Loss Risk Index (NiLRI) old band x falls into
x2 = upper Nitrogen Loss Risk Index (NiLRI) old band x falls into
y1 = losses aligned to the Nitrogen Loss Risk Index (NiLRI) old band x falls into
y2= losses aligned to the next Nitrogen Loss Risk Index (NiLRI) old band x falls into

For example:

Before Nitrogen Loss Risk Index (NiLRI) of 1.94
After Nitrogen Loss Risk Index (NiLRI) of 1.81

The before Nitrogen Loss Risk Index (NiLRI) for this example is band 5.0 and the after Nitrogen Loss Risk Index (NiLRI) relates to band 4.3, see the new band calculation table.

Band 5.0 aligns to one of the existing bands and there is an existing DIN loss figure (e.g. 10kg N/ha). Therefore, the before DIN loss is 10kg N/ha. Band 4.3 does not align directly to one of the old modelling bands so the DIN loss must be estimated by interpolating between the major bands.

y = interpolated DIN loss
x = 1.81
x1 = 1.94 (band 5.0)
x2 = 1.62 (band 4.0)
y1 = 10kg/ha (band 5.0)
y2 = 6kg/ha (band 4.0)

example equation

After DIN loss for band 4.3 is 8.37kg N/ha

Therefore, the estimated DIN load reduction for this project using the November 2022 method is 10 – 8.37 = 1.63kg N/ha