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.
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.
Stream and Session
F3: Modelling and Decision Making Under Uncertainty (paper)