Optimisation methods are routinely used in exploring decision options in conservation planning for nature reserve design, hydrology applications for storage operations, emission scenarios for climate change, and cropping decisions in agriculture. Optimisation methods are embedded in decision theory approaches to explore management alternatives for optimal solutions, which are constrained to available information. Optimisation tools differ from more scenario-based modelling methods where the focus is on predicting outcomes. Solutions seek to avoid worst-case outcomes by seeking robust alternatives that are less sensitive to uncertainties. Recent advances have been made in using optimisation methods to explore management of environmental flows in regulated river systems. In this presentation we will overview optimisation in environmental flow contexts and introduce the ecological components of the optimisation model, using the Murrumbidgee River system as a case study. Existing ecological data and response relationships were complemented with new knowledge from the CSIRO Cluster-funded project to explore scenarios of flow and optimal flow release decisions to achieve ecological objectives. A challenge in the project was in accessing ecological data at the scale and in the context for establishing objectives and in deriving response relationships. Whilst some data is available to establish overbank flow objectives, little was available for in-channel objectives. We will discuss the types of ecological data sets that are applicable to optimisation applications and the challenges of scales.