A spatial causal network approach for multi-stressor risk analysis and mapping for environmental impact assessments

Area of Science:

• Environmental Science
• Risk Assessment
• Network Analysis

Background:

• Environmental Impact Assessments (EIAs) are crucial for development decisions but often lack comprehensive analysis of causal pathways, spatial scope, and risk transparency.
• Existing EIA methodologies can be limited in their ability to fully assess potential environmental impacts and communicate risk evaluation processes.

Purpose of the Study:

• To present a novel EIA methodology using network analysis to systematically map and evaluate potential causal pathways of environmental impacts.
• To improve the transparency, spatial explicitness, and rigor of risk assessments in EIAs.

Main Methods:

• Developed a network analysis approach to model causal pathways from human activities to valued environmental assets.
• Integrated systematic evaluation of likelihood, consequence, mitigation options, and confidence levels for each pathway.
• Incorporated spatially explicit analysis to map residual risks and identify 'risk hotspots'.

Main Results:

• The causal network approach identified key activities and pathways of concern for various valued assets, including aquifers, ecosystems, and protected species.
• Spatially explicit mapping revealed areas with the greatest residual risks, highlighting priorities for monitoring and detailed assessment.
• The methodology was demonstrated for unconventional gas development in Australia's Cooper Basin.

Conclusions:

• The spatial causal network approach offers a systematic, consistent, and transparent method for assessing environmental impacts and risks.
• This improved assessment quality supports better-informed decision-making regarding planned developments and their environmental consequences.