Keywords

uncertainty policy scenario

Start Date

27-6-2018 3:40 PM

End Date

27-6-2018 5:00 PM

Abstract

Water quality issues due to nutrient contamination by intensive agriculture is a good example of a complex problem characterised by conflict and uncertainty. A collaborative approach to setting nutrient limits in catchments in Canterbury, New Zealand has been developed and implemented over the last 6 years. Policy and other non regulatory measures are developed by the regulatory body in collaboration with community stakeholders in a science-informed process. A technical group rely on modelling to provide estimates on the socio-economic, cultural and environmental outcomes under stakeholder specified scenarios. These modelled estimates inform the collaborative nutrient limit-setting process.

There is considerable uncertainty in this scientific knowledge that the decision-makers need to be aware of. However, the nutrient limit setting processes are time and resource constrained precluding a comprehensive uncertainty analysis. This paper presents some ideas for explicitly and transparently identifying and communicating the key uncertainties within a timeframe that fits with the collaborative process.

A five-stage framework for understanding, communicating and managing uncertainty is presented, and tested in a retrospective analysis of a recent collaborative process. Fuzzy indicator/outcome graphs, systems diagrams, outcome likelihood matrices and simple uncertainty estimates using the Sheffield Elicitation Framework (SHELF) tool are all used in the framework.

Stream and Session

F3: Modelling and Decision Making Under Uncertainty (paper)

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Jun 27th, 3:40 PM Jun 27th, 5:00 PM

Towards an improved understanding and management of uncertainty in science investigations of environment policy options

Water quality issues due to nutrient contamination by intensive agriculture is a good example of a complex problem characterised by conflict and uncertainty. A collaborative approach to setting nutrient limits in catchments in Canterbury, New Zealand has been developed and implemented over the last 6 years. Policy and other non regulatory measures are developed by the regulatory body in collaboration with community stakeholders in a science-informed process. A technical group rely on modelling to provide estimates on the socio-economic, cultural and environmental outcomes under stakeholder specified scenarios. These modelled estimates inform the collaborative nutrient limit-setting process.

There is considerable uncertainty in this scientific knowledge that the decision-makers need to be aware of. However, the nutrient limit setting processes are time and resource constrained precluding a comprehensive uncertainty analysis. This paper presents some ideas for explicitly and transparently identifying and communicating the key uncertainties within a timeframe that fits with the collaborative process.

A five-stage framework for understanding, communicating and managing uncertainty is presented, and tested in a retrospective analysis of a recent collaborative process. Fuzzy indicator/outcome graphs, systems diagrams, outcome likelihood matrices and simple uncertainty estimates using the Sheffield Elicitation Framework (SHELF) tool are all used in the framework.