THE CLIMATE KELPIE BLOG: Can advances in mid-term weather forecasts reduce emissions from nitrogen fertiliser?
It is commonly accepted that soil moisture is a critical factor in N emissions but there has been little emphasis on the management of fertiliser application and soil moisture. This study focused on the interaction between N fertiliser decisions and soil moisture content, specifically high rainfall events.
Climate forecasts for the coming season are a major determinant of the optimum rate of fertiliser application. And weather following fertiliser applications has an influence on the ideal timing. Choices on the placement and the form of nitrogen are also influenced by climate. This project was based on the premise that information from weather and climate forecasts could lead to better economic and environmental outcomes from nitrogen fertiliser decisions in the grains, dairy and sugar industries. These three industries were studied across five case study sites which provided a range of climatic conditions and soil characteristics relevant to nitrogen emissions, including soil water holding capacity, labile carbon, pH and nitrogen content.
This was a proof of concept project with three objectives:
- Develop a framework for using scientific advances in climate forecasts to guide nitrogen fertiliser decisions in farming systems, to increase productivity and minimise nitrous oxide emissions.
- Apply the framework to case studies in the grains, dairy and sugar industries using simulation modelling to evaluate any effects of informed nitrogen fertiliser decisions.
- Document the opportunities and barriers to developing and adopting Carbon Farming Initiative (CFI) offset methods for nitrous oxide emissions abatement.
1 May 2016
To address the question of the use of forecasts for nitrogen fertiliser decisions, we relied on four disciplines:
- Soil nitrogen dynamics
- Climate science
- Agricultural economics and
- Farming systems
Resources from the project enabled climate forecasts from the Bureau of Meteorology’s dynamic climate model, POAMA, to be linked into three commonly-used simulation models (APSIM, DAIRYMOD and DAYCENT). The outcomes we considered of value were based on information that was economic (yield and pasture production) and environmental (nitrous oxide). The CSIRO ADOPT tool was also useful in providing insights on the potential for adoption, based on the characteristics of the target audience and the nature of weather and climate forecasts.
Towards the end of the project, a workshop was held with the project team and representatives of the grains, dairy and sugar industries, followed by an online survey distributed to NANORP researchers and the MCVP Climate Champions. Based on workshop feedback and survey responses, we recommend against the use of forecasts for managing nitrogen fertiliser as an Emissions Reduction Fund (ERF) offset method. Instead, we suggest a potential for forecasts as a component of other fertiliser decision-making methods.
Although there were substantial challenges to developing the methodology, a valuable framework was provided with the potential for adoption by users and benefits for improved nitrogen use efficiency as well as reductions in nitrous oxide emissions.
South Australian Research and Development Institute (SARDI)
Charles Sturt University, Orange (CSU)
Australian Bureau of Meteorology (BOM)
Managing Climate Variability (MCV)
Dairy Australia (DA)
Sugar Research Australia (SRA)
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