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Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/73654

Type: Journal article
Title: A framework for using ant colony optimization to schedule environmental flow management alternatives for rivers, wetlands, and floodplains
Author: Szemis, Joanna Margaret
Maier, Holger R.
Dandy, Graeme Clyde
Citation: Water Resources Research, 2012; 48(8):W08502
Publisher: American Geophysical Union
Issue Date: 2012
ISSN: 0043-1397
School/Discipline: School of Civil, Environmental and Mining Engineering
Statement of
Responsibility: 
J.M. Szemis, H.R. Maier and G.C. Dandy
Abstract: [1] Rivers, wetlands, and floodplains are in need of management as they have been altered from natural conditions and are at risk of vanishing because of river development. One method to mitigate these impacts involves the scheduling of environmental flow management alternatives (EFMA); however, this is a complex task as there are generally a large number of ecological assets (e.g., wetlands) that need to be considered, each with species with competing flow requirements. Hence, this problem evolves into an optimization problem to maximize an ecological benefit within constraints imposed by human needs and the physical layout of the system. This paper presents a novel optimization framework which uses ant colony optimization to enable optimal scheduling of EFMAs, given constraints on the environmental water that is available. This optimization algorithm is selected because, unlike other currently popular algorithms, it is able to account for all aspects of the problem. The approach is validated by comparing it to a heuristic approach, and its utility is demonstrated using a case study based on the Murray River in South Australia to investigate (1) the trade-off between plant recruitment (i.e., promoting germination) and maintenance (i.e., maintaining habitat) flow requirements, (2) the trade-off between flora and fauna flow requirements, and (3) a hydrograph inversion case. The results demonstrate the usefulness and flexibility of the proposed framework as it is able to determine EFMA schedules that provide optimal or near-optimal trade-offs between the competing needs of species under a range of operating conditions and valuable insight for managers.
Keywords: Ant colony optimization; environmental flow; management schedules
Rights: © 2012. American Geophysical Union. All Rights Reserved.
RMID: 0020121269
DOI: 10.1029/2011WR011276
Appears in Collections:Environment Institute Publications
Civil and Environmental Engineering Publications
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