An iterative method for discovering feasible management interventions and targets conjointly using uncertainty visualizations

This paper presents a generic method, referred to as Iterative Discovery, to guide deliberation with analysis where the aim is to plan refinements to management interventions with difficult-to-define objectives, often due to system uncertainties and diverse stakeholder positions. The method can be initiated by evaluating a scenario describing the current-best intervention. This provides the starting point for three evaluation cycles, focusing on model assumptions, alternative interventions and management targets. The outcome of this method is a list of management targets that can and cannot be achieved, the potential interventions that correspond to these targets, and the assumptions and uncertainties associated with these interventions. It was applied to a case study for environmental flow management in the Macquarie Marshes, Australia. We identified feasible management targets based on ecological outcomes in flood suitability across different locations, climate conditions and species, and the suitable environmental flow volumes that correspond to these targets.