Considering scale within optimization procedures for water management decisions: Balancing environmental flows and human needs

A 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 environ...

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Veröffentlicht in:Environmental modelling & software : with environment data news 2021-05, Vol.139, p.104991, Article 104991
Hauptverfasser: Derepasko, Diana, Guillaume, Joseph H.A., Horne, Avril C., Volk, Martin
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Sprache:eng
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Zusammenfassung:A 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. [Display omitted] •Reviews water management multi-objective optimization studies with environmental flow.•Outlines optimization model development decisions affecting temporal and spatial scale.•Proposes a framework for reasoning about scale, fostering transparency.
ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2021.104991