seasonal risk management

Commencement date

April 2004

Completion date

June 2008

Aim

This project was used to analyse constraints in reaching optimal water use efficiency (WUE) and how grower groups may implement sustainable strategies to overcome these poor conditions while establishing communication networks to drive peer-to-peer solutions.

Funding Provider

National Landcare Program (NLP) Sustainable Industries Initiative

Project lead organisation

Grower Group Alliance (GGA)

Collaborators

Liebe Group

Project background

In 2004, the GGA was successful in obtaining project funding through the NLP Sustainable Industries Initiative. This has allowed five grower groups to focus on implementing sustainable agricultural production practices that protect the soil and optimise water and nutrient use in Western Australia (WA).

 

The project has highlighted the key constraints to production in the Northern Agricultural Region (NAR) as:

  • herbicide resistance;

  • inefficient water use;

  • changes in land capability due to salinification;

  • subsoil constraints to plant growth (i.e. acidity), and;

  • seasonal variability associated with climate change.

This project is aimed at increasing the awareness of these production constraints within the region and establishing communication networks for growers, with both industry and/or other growers, in order to access information on possible solutions.

Liebe Group members rated seasonal risk as one of the major threats to production in the local area. We therefore designed a project aimed to assess the benefits of two yield prediction tools:

  1. PYCAL - gives an indication of water limited potential yield, based on the French Schultz equation (1984). This is calculated as potential Yield (kg/ha) = Crop Water Use (mm) - Evaporation (mm) x WUE. Crop water use is estimated as the sum of plant available water at the start of growing season (April 1) and the growing season rainfall (GSR). The model uses a standard WUE of 15 kg/mm/ha, although WUE in this case was calibrated for individual paddocks using five years of past yields and rainfall data.

  2. Yield Prophet - is the commercialisation of the Agricultural Production Systems Simulator (APSIM) model. This uses site-specific soil characterization data, and the soil water and nitrogen content at time of sowing. This information, in conjunction with historic rainfall data, is used to calculate the probabilities of achieving certain yields given the range of decile year outcomes. This program requires specific site constraints to determine the Plant Available Water Capacity (PAWC) of the soil, essentially considered the 'bucket size' of the soil. Soil site characterization should also detect other factors at play that may impede root growth (i.e. compaction, subsoil acidity, shallow soils, and salinity) and therefore a rooting depth can be set for the model.

 

It will be determined whether these programs can be beneficial to farmers in terms of realising yield potential. Furthermore, it is up for consideration as to whether they can be used as a future tool to assist with seeding and nutrition application decision-making processes.

Six sites with varying soil types and GSR will be chosen on a yearly basis to trial these projection tools.

Results and Reports

This project was funded by NLP Sustainable Industries Initiative.

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