Identification of Optimal Water Supply Portfolios for a Major City-Reference-Cited by-同舟云学术

Identification of Optimal Water Supply Portfolios for a Major City

Published:2017-09 Issue:9 Volume:143 Page:05017007
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Wu Wenyan¹,Dandy Graeme C.²,Maier Holger R.³,Maheepala Shiroma⁴,Marchi Angela⁵,Mirza Fareed⁶

Affiliation:

1. Research Associate, School of Civil, Environmental and Mining Engineering, Univ. of Adelaide, Adelaide, SA 5005, Australia (corresponding author).

2. Emeritus Professor, School of Civil, Environmental and Mining Engineering, Univ. of Adelaide, Adelaide, SA 5005, Australia.

3. Professor, School of Civil, Environmental and Mining Engineering, Univ. of Adelaide, Adelaide, SA 5005, Australia.

4. Senior Project Manager, Dept. of Environment, Land and Water Planning, VIC 3000, Australia.

5. Research Associate, School of Civil, Environmental and Mining Engineering, Univ. of Adelaide, Adelaide, SA 5005, Australia.

6. Experimental Scientist, CSIRO Land and Water Division, Highett, VIC 3190, Australia.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29WR.1943-5452.0000811

Reference48 articles.

1. Australian Bureau of Statistics. (2011). “2011.0.55.001—Information paper: Census of population and housing—Products and services.” ⟨http://www.abs.gov.au/ausstats/abs@.nsf/mf/2011.0.55.001⟩ (May 29 2014).

2. Compromise programming: A utility-based linear-quadratic composite metric from the trade-off between achievement and balanced (non-corner) solutions

3. Optimal sequencing of water supply options at the regional scale incorporating alternative water supply sources and multiple objectives

4. Adaptive, multiobjective optimal sequencing approach for urban water supply augmentation under deep uncertainty

5. Scenario driven optimal sequencing under deep uncertainty

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