An overview of all projects in DCAP 1
This report examines those factors that limit decision making for improved drought preparedness and management in Queensland grazing enterprises. The report gains information through interviews with grazing specialists and a small group of leading graziers.
This project developed a prototype seasonal forecasting framework that incorporates the influence of the Quasi-Biennial Oscillation and the Southern Oscillation Index to address limitations in current seasonal forecasting.
High skill appears to exist many months and years into the future when utilising the UK Met Office Decadal Prediction System, known as DePreSys. Rainfall accuracy rates of 62% to 75% have been calculated, often with many years advanced lead time, suggesting an opportunity for use in strategic risk management decisions for Queensland (and potentially Australian) rural industry.
The aim of this project was to provide high-resolution climate change projection daily data for Queensland in an ‘application-ready’ format to be used by common biophysical models for simulation modelling.
Climate Change Adaptation workshops were conducted in three Central Queensland locations in 2017 with a total of 44 stakeholders. These workshops assisted producers, government, industry groups and communities to understand the risks and prepare for the impacts of climate change.
This project conducted focussed reviews on climate risk in agriculture and how insurance products could be used to address these risks.
This project developed products such as indices for use in drought monitoring as a support tool to assist producers and other stakeholders to improve their climate risk management and capacity to prepare for and manage drought.
The aim of the project was to develop an operational integrated seasonal climate-crop modelling system for yield and production forecasting of major crops in Queensland (wheat, sorghum, sugarcane and cotton).
This project aimed to provide graziers with the critical information they need to be prepared for and manage the impacts of drought. The ‘Pasture Growth Alert’ is a property-scale report providing historical and future outlooks for rainfall and pasture growth to be delivered through the DSITI’s decision support system FORAGE.
A series of Best Management Practice workshops were held in Western Queensland. Two consultants were engaged to carry out the workshops.
This project delivered 4 industry Climate Risk Matrix workshops targeted at primary producers to communicate the risks of climate change and drought in particular, to develop adaptation pathways.
Nine Managing Climate Risk Workshops were conducted successfully under this project. The MFC workshops formed the basis of a process where producers were given the knowledge and understanding to integrate climate information into key management decisions by interpreting the current forecasts and integrating this into management decisions.
The aim of this project was to provide a detailed biophysical and economic assessment of identified adaptation strategies, potential implications and adaptation potential under different climate change (CC) scenarios for the Queensland cropping industry.
In this study, a bio-economic model of forecast use was developed which explicitly incorporates forecast uncertainty to test the value of seasonal climate forecasts in farm management decision making.
The objective of this project was to (a) demonstrate palaeoclimate proxy approach in producing robust catchment statistics; (b) gain improved insights into the risk of hydroclimate extremes in South East Queensland (SEQ) for water security planning and (c) deliver recommendations to SEQ water managers to optimise hydroclimatic risk adaptation strategies and solutions.
The aim of this project was to redevelop the LongPaddock website to a climate and decision support tool data service portal hosted on Amazon Web Services (AWS) which also included the development of spatial functionality for the FORAGE decision support tool.
This project quantified and mapped change in pasture productivity on grazing lands during drought using remote sensing technology, specifically the enhanced vegetation index (EVI), which measures change in green biomass.