Solving multi-objective water management problems using evolutionary computation

A. Lewis, M. Randall

Research output: Contribution to journalArticleResearchpeer-review

10 Citations (Scopus)

Abstract

Water as a resource is becoming increasingly more valuable given the changes in global climate. In an agricultural sense, the role of water is vital to ensuring food security. Therefore the management of it has become a subject of increasing attention and the development of effective tools to support participative decision-making in water management will be a valuable contribution. In this paper, evolutionary computation techniques and Pareto optimisation are incorporated in a model-based system for water management. An illustrative test case modelling optimal crop selection across dry, average and wet years based on data from the Murrumbidgee Irrigation Area in Australia is presented. It is shown that sets of trade-off solutions that provide large net revenues, or minimise environmental flow deficits can be produced rapidly, easily and automatically. The system is capable of providing detailed information on optimal solutions to achieve desired outcomes, responding to a variety of factors including climate conditions and economics.

Original languageEnglish
Pages (from-to)179-188
Number of pages10
JournalJournal of Environmental Management
Volume204
DOIs
Publication statusPublished - 15 Dec 2017

Fingerprint

Water management
Evolutionary algorithms
water management
climate conditions
food security
Irrigation
trade-off
Crops
global climate
Water
Decision making
irrigation
water
crop
Economics
resource
economics
modeling
decision making support
test

Cite this

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Solving multi-objective water management problems using evolutionary computation. / Lewis, A.; Randall, M.

In: Journal of Environmental Management, Vol. 204, 15.12.2017, p. 179-188.

Research output: Contribution to journalArticleResearchpeer-review

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