Derepasko, DianaGuillaume, JosephHorne, Avril C.Volk, Martin2022-11-042022-11-041364-8152http://hdl.handle.net/1885/278012A key issue in optimization model development is the selection of spatial and temporal scale representing the system. This study proposes a framework for reasoning about scale in this context, drawing on a review of studies applying multi-objective optimization for water management involving environmental flows. We suggest that scale is determined by the management problem, constrained by data availability, computational, and model capabilities. There is therefore an inherent trade-off between problem perception and available modelling capability, which can either be resolved by obtaining data needed or tailoring analysis to the data available. In the interest of fostering transparency in this trade-off process, this paper outlines phases of model development, associated decisions, and available options, and scale implications of each decision. The problem perception phase collects system information about objectives, limiting conditions, and management options. The problem formulation phase collects and uses data, information, and methods about system structure and behaviour.Joseph Guillaume received funding from an Australian Research Council Discovery Early Career Researcher Award (project no. DE190100317). Avril Horne received funding from Australian Research Council Discovery Early Career Researcher Award (project no. DE180100550)application/pdfen-AU© 2021 The Author(s). Published by Elsevier Ltd.https://creativecommons.org/licenses/by-nc-nd/4.0/Multi-scale analysisEnvironmental flowsMulti-objective optimizationWater managementTrade-off analysis202110.1016/j.envsoft.2021.1049912021-11-28Creative Commons Attribution-NonCommercial-NoDerivs License