Resilience enhancing expansion strategies for water distribution systems: A network theory approach

Yazdani, Alireza; Otoo, Richard Appiah; Jeffrey, Paul

doi:10.1016/j.envsoft.2011.07.016

Cited by 190 publications

(142 citation statements)

References 34 publications

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“…Further work should be considered to assess the impact of re-defining risk and target system performance in terms such as reliability, resilience and vulnerability (Hashimoto et al 1982;Yazdani et al 2011 …”

Section: Discussionmentioning

confidence: 99%

Comparison of Robust Optimization and Info-Gap Methods for Water Resource Management under Deep Uncertainty

Roach

Kapelan

Ledbetter

et al. 2016

J. Water Resour. Plann. Manage.

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This paper evaluates two established decision making methods and analyses their performance and suitability within a Water Resources Management (WRM) problem. The methods under assessment are Info-Gap decision theory (IG) and Robust Optimisation (RO). The methods have been selected primarily to investigate a contrasting local vs global method of assessing water system robustness to deep uncertainty but also to compare a robustness model approach (IG) with a robustness algorithm approach (RO), whereby the former selects and analyses a set of prespecified strategies and the latter uses optimisation algorithms to automatically generate and evaluate solutions. The study presents a novel area-based method for IG robustness modelling and assesses the applicability of utilising the Future Flows climate change projections in scenario generation for water resource adaptation planning. The methods were applied to a case study 2 resembling the Sussex North Water Resource Zone in England, assessing their applicability at improving a risk-based WRM problem and highlighting the strengths and weaknesses of each method at selecting suitable adaptation strategies under climate change and future demand uncertainties. Pareto sets of robustness to cost are produced for both methods and highlight RO as producing the lower costing strategies for the full range of varying target robustness levels. IG produced the more expensive Pareto strategies due to its more selective and stringent robustness analysis, resulting from the more complex scenario ordering process.

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Section: Discussionmentioning

confidence: 99%

Comparison of Robust Optimization and Info-Gap Methods for Water Resource Management under Deep Uncertainty

Roach

Kapelan

Ledbetter

et al. 2016

J. Water Resour. Plann. Manage.

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“…This factor has been quantified through metrics such as grouping and meshing coefficients [31], along with an index that combines the magnitude and duration of system failures where redundancy is evaluated by comparing how an existing system functions with and without redundant elements until failure occurs [33]. Of the four identified factors, this is the least considered because of its recent incorporation, which is primarily related to the evaluation of resilience in urban water systems [16,41].…”

Section: Redundancymentioning

confidence: 99%

“…This factor evaluates the capacity to recover and is associated with the time of failure, reliability and recovery speed of a system from the perspective of risk management. Flexibility has been quantified through semi-quantitative indices that measure the capacity to provide a service [20], mathematical functions that quantify the probability of system failure [23][24][25][26][27]29,32], system reliability [30,31] and indicators based on performance curves of a system that provide information on its behaviour before and after a disturbance [17,18,28,33,34].…”

Section: Redundancymentioning

confidence: 99%

Identification of resilience factors, variables and indicators for sustainable management of urban drainage systems

Londoño¹,

Torres–Lozada²,

Galvis-Castaño³

2017

DYNA

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Water management systems in general and urban drainage systems (UDS) in particular should be designed to ensure not only the provision of public service but also their sustainability and resilience. This paper performed an analysis and assessment to identify the factors, variables and indicators of resilience for sustainable UDS management by using an information management tool for scientific subjects. As a result of this analysis, four water resource resilience factors were identified: i. Flexibility; ii. Resourcefulness; iii. Redundancy; and iv. Robustness. In addition, six UDS resilience variables were identified: i. Recovery capacity; ii. Response capacity; iii. Amplitude; iv. Absorption capacity; v. Resistance capacity; and vi. Response curve. Corresponding indicators were proposed to quantify these variables. The identified elements contribute to the development of integrated frameworks to assess UDS resilience.Keywords: urban drainage; management; resilience; sustainability.Identificación de factores, variables e indicadores de resiliencia para la gestión sostenible de sistemas de drenaje urbano ResumenLa gestión del agua en general y de los sistemas de drenaje urbano (SDU) en particular, debe ser concebida no solo para asegurar la prestación de un servicio público, sino también para garantizar su sostenibilidad y resiliencia. En el presente artículo se presenta un análisis y reflexión que permitió identificar los factores, variables e indicadores de resiliencia para la gestión sostenible de SDU, usando herramientas de gestión de información de temas científicos. Como resultado de este análisis, se identificaron cuatro factores de resiliencia de recursos hídricos: i. Flexibilidad; ii. Recursividad; iii. Redundancia; y iv. Robustez y seis variables de resiliencia de SDU: i. Capacidad de recuperación; ii. Capacidad de respuesta; iii. Amplitud; iv. Capacidad de absorción; v. Capacidad de resistencia; y vi. Curva de respuesta. Para cuantificar estas variables, se proponen sus correspondientes indicadores. Los elementos identificados contribuyen al desarrollo de modelos integrales de evaluación de la resiliencia en SDU.

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“…The index is based on the power balance of the network and gives information about how much pressure surplus is available at each network node, compared to a minimum required head [30]. The pressure surplus can be seen as a "buffer capacity" that can be used under critical operation conditions (e.g., pipe breaks), when the internal energy dissipation increases.…”

Section: Modelling Frameworkmentioning

confidence: 99%

Enabling Efficient and Sustainable Transitions of Water Distribution Systems under Network Structure Uncertainty

Zischg

Mair

Rauch

et al. 2017

Water

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This paper focuses on the performance of water distribution systems (WDSs) during long-term city transitions. A transition describes the pathway from an initial to a final planning stage including the structural and functional changes on the infrastructure over time. A methodology is presented where consecutive WDSs under changing conditions are automatically created, simulated and then analyzed at specific points in time during a transition process of several decades. Consequential WDS analyses include (a) uncertain network structure, (b) temporal and spatial demand variation and (c) network displacement. With the proposed approach, it is possible to identify robust WDS structures and critical points in time for which sufficient hydraulic and water quality requirements cannot be ensured to the customers. The approach is applied to a case study, where a WDS transition of epic dimensions is currently taking place due to a city relocation. The resulting necessity of its WDS transition is modelled with automatically created planning options for consecutive years of the transition process. For the investigated case study, we tested a traditional "doing-all-at-the-end" approach, where necessary pipe upgrades are performed at the last stages of the transition process. Results show that the sole design of the desired final-stage WDS is insufficient. Owing to the drastic network deconstruction and the stepwise "loss of capacity", critical pipes must be redesigned at earlier stages to maintain acceptable service levels for most of the investigated future scenarios.

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Resilience enhancing expansion strategies for water distribution systems: A network theory approach

Cited by 190 publications

References 34 publications

Comparison of Robust Optimization and Info-Gap Methods for Water Resource Management under Deep Uncertainty

Comparison of Robust Optimization and Info-Gap Methods for Water Resource Management under Deep Uncertainty

Identification of resilience factors, variables and indicators for sustainable management of urban drainage systems

Enabling Efficient and Sustainable Transitions of Water Distribution Systems under Network Structure Uncertainty

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