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

Beh, Eva H. Y.; Dandy, Graeme C.; Maier, Holger R.; Paton, F. L.

doi:10.1016/j.envsoft.2013.11.004

Cited by 50 publications

(55 citation statements)

References 30 publications

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“…So the overall challenge is to ensure that the optimisation can "see" all significant uncertainties that affect performance, to specify objectives that not only seek efficiency (in its widest sense), but also robustness (or the ability to cope if future trajectories of the system are unfavourable), and to ensure decisions are framed to allow flexibility (or the ability to adapt to changing circumstances). Multistage decision methods (Beh et al, 2014;Beh et al, 2011;Watkins and McKinney, 1997) can provide some flexibility, but more flexible and adaptive approaches are needed.…”

Section: Current Statusmentioning

confidence: 99%

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Maier

Kapelan

Kasprzyk

et al. 2014

Environmental Modelling & Software

523

317

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In all cases accepted manuscripts should:  link to the formal publication via its DOI  bear a CC-BY-NC-ND license -this is easy to do, click here to find out how  if aggregated with other manuscripts, for example in a repository or other site, be shared in alignment with our hosting policy  not be added to or enhanced in any way to appear more like, or to substitute for, the published journal article AbstractThe development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e.g., model calibration, water distribution systems, groundwater management, river-basin planning and management, etc.). However, there has been limited synthesis between shared problem traits, common EA challenges, and needed advances across major applications. This paper clarifies the current status and future research directions for better solving key water resources problems using EAs. Advances in understanding fitness landscape properties and their effects on algorithm performance are critical. Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts.

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Section: Current Statusmentioning

confidence: 99%

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Maier

Kapelan

Kasprzyk

et al. 2014

Environmental Modelling & Software

523

317

View full text Add to dashboard Cite

show abstract

“…Paton et al (2014) developed a framework for water supply system planning with alternative sources and climate change considerations, while Beh et al (2014Beh et al ( , 2015 developed two methods for optimal sequencing of urban water supply augmentation options under deep uncertainty regarding demands and climate. The research by both Paton et al (2014) and Beh et al (2014Beh et al ( , 2015 considered only the planning of water supply projects, and did not optimize the specific design or operation of the systems. Sequencing is also considered in Cai et al (2015), however, in this case it is applied to planning of drought mitigation strategies in agricultural systems.…”

Section: Literature Reviewmentioning

confidence: 99%

Framework for the optimization of operation and design of systems with different alternative water sources

et al. 2017

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Water security has become an increasing concern for many water system managers due to climate change and increased population. In order to improve the security of supply, alternative sources such as harvested stormwater, recycled wastewater and desalination are becoming more commonly used. This brings about the need for tools to analyze and optimize systems that use such sources, which are generally more complex than traditional water systems. Previous methodologies have been limited in their scope and cannot be applied to all types of water sources and systems. The framework presented in this paper has been developed for holistic analysis and optimization of water supply and distribution systems that use alternative water sources. It includes both design and operational decision variables, water and energy infrastructure, simulation of systems, analysis of constraints and objectives, as well as policies and regulations which may affect any of these factors. This framework will allow users to develop a comprehensive analysis and/or optimization of their water supply system, taking into account multiple types of water sources and consumers, the effect of their own design and operational decisions, and the impact of government policies and different energy supply options. Two case study systems illustrate the application of the framework; the first case study is a harvested stormwater system that is used to demonstrate the importance of simulation and analysis prior to optimization, the second utilizes four different water sources to increase security of supply and was optimized to reduce pump energy use.

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“…Consequently, the optimisation problem to be solved involves the sequencing of the potential supply augmentation options over a given planning horizon (see Beh et al, 2014). This problem is used here for illustration purposes of the proposed approach, as it has been studied previously in relation to the identification of optimal water supply augmentation options (Paton et al, , 2014a(Paton et al, , 2014b, as well as the optimal sequencing of these options without the consideration of uncertainty (Beh at al., 2014).…”

Section: Introductionmentioning

confidence: 99%

“…The recorded annual rainfall ranges from 257mm to 882mm . Average annual mains water consumption was estimated In order to cater to projected demand increases and the impacts of climate change, there are plans to augment Adelaide's future water supply (Beh et al, 2014;Paton et al, 2013Paton et al, , 2014b. Potential water supply augmentation sources include a desalination plant at Port Stanvac, various stormwater harvesting schemes, and household rainwater tanks, as detailed in Beh et al (2014) and Paton et al (2014b).…”

Section: Introductionmentioning

confidence: 99%

“…Examples include the sequencing of urban water supply augmentation sources and infrastructure (Beh et al, 2014;Kang and Lansey, 2014;Mortazavi-Naeini et al, 2014;Ray et al, 2013), the scheduling of pumps and rehabilitation activities in water distribution systems (Kleiner et al, 1998;Dandy and Engelhardt, 2001;Dandy and Engelhardt, 2006;Savić et al, 2011;Zheng and Zecchin, 2014), the scheduling of wastewater discharges (Murillo et al, 2011), the scheduling of mining production activities (Badiozamani and Askari-Nasab, 2014), the scheduling of forest management activities (Sharples et al, 2009;Simon and Etienne, 2010;Zhang and Barten, 2009), the scheduling of irrigation water (Ge et al, 2013;Merot and Bergez, 2010), the scheduling of crop management activities (Lautenbach et al, 2013;Ripoche et al, 2011), the scheduling of environmental flows in rivers (Szemis et al, 2013;Szemis et al, 2012) and determining the optimal schedule of investments of conservation funding (Bode et al, 2008;Wilson et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Scenario driven optimal sequencing under deep uncertainty

Beh

Maier

Dandy

2015

Environmental Modelling & Software

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After the embargo period  via non-commercial hosting platforms such as their institutional repository  via commercial sites with which Elsevier has an agreement In all cases accepted manuscripts should: link to the formal publication via its DOI  bear a CC-BY-NC-ND license -this is easy to do, click here to find out how  if aggregated with other manuscripts, for example in a repository or other site, be shared in alignment with our hosting policy  not be added to or enhanced in any way to appear more like, or to substitute for, the published journal article AbstractThe optimal sequencing / scheduling of activities is vital in many areas of environmental and water resources planning and management. In order to account for deep uncertainty surrounding future conditions, a new optimal scheduling approach is introduced in this paper, which consists of three stages. Firstly, a portfolio of diverse sequences that are optimal under a range of plausible future conditions is generated. Next, global sensitivity analysis is used to assess the robustness of these sequences and to determine the relative contribution of future uncertain variables to this robustness. Finally, an optimal sequence is selected for implementation. The approach is applied to the optimal sequencing of additional potential water supply sources, such as desalinated-, stormand rain-water, for the southern Adelaide water supply system, over a 40 year planning horizon at 10-year intervals. The results indicate that the proposed approach is useful in identifying optimal sequences under deep uncertainty.

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

Cited by 50 publications

References 30 publications

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions

Framework for the optimization of operation and design of systems with different alternative water sources

Scenario driven optimal sequencing under deep uncertainty

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