36 research outputs found

    Investigating Transitions of Centralized Water Infrastructure to Decentralized Solutions – An Integrated Approach

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    AbstractThe lifespan and therefore planning horizon of central organized water infrastructure can be up to 100years. The impact of climate change, water scarcity, land use change, population growth but also population shrinking can only be predicted for such a time horizon with uncertainties. One solution is to make centralized organized water infrastructure more flexible (i.e. implement decentralized measures). But these can cause severe impacts on existing centralized infrastructure. Low flow conditions in urban drainage systems can cause sediment deposition and for water supply systems water age problems may occur. This work focuses on city scale analysis for assessing the impact of such measures (i.e. transitions from centralized to decentralized solutions)

    Resilience of Interdependent Urban Water Systems

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    This is the final version. Available on open access from MDPI via the DOI in this recordFederal Ministry of Agriculture, Regions and Tourism (BMLRT), Austri

    Stationary vs non-stationary modelling of flood frequency distribution across northwest England

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    Extraordinary flood events occurred recently in northwest England, with several severe floods in Cumbria, Lancashire and the Manchester area in 2004, 2009 and 2015. These clustered extraordinary events have raised the question of whether any changes in the magnitude and frequency of river flows in the region can be detected. For this purpose, the annual maximum series of 39 river gauging stations in the study area are analysed. In particular, non-stationary models that include time, annual rainfall and annual temperature as predictors are investigated. Most records demonstrate a marked non-stationary behaviour and an increase of up to 75% in flood quantile estimates during the study period. Annual rainfall explains the largest proportion of variability in the peak flow series relative to other predictors considered in our study, providing practitioners with a useful framework for updating flood quantile estimates based on the dynamics of this highly accessible and informative climate indicator

    Pareto-optimal design of water distribution networks: an improved graph theory-based approach

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    This is the final version. Available on open access from IWA Publishing via the DOI in this recordData availability statement: All relevant data are included in the paper or its Supplementary Information.One of the main drawbacks of using evolutionary algorithms for the multi-objective design of water distribution networks (WDNs) is their computational inefficiency, particularly for large-scale problems. Recently, graph theory-based approaches (GTAs) have gained attention as they can help with the optimal WDN design (i.e., determining optimal diameters). This study aims to extend a GTA to further improve the quality of design solutions. The GTA design is based on a customized metric called ‘demand edge betweenness centrality’, which spatially distributes nodal demands through the weighted edges of a WDN graph and provides an estimation of water flows. Assigned edge weights can be constant (i.e., static) or modified iteratively (i.e., dynamic) during the design process, leading to different flow estimations and alternative design options. Three hydraulic-inspired dynamic weights are developed in this study to better reproduce hydraulic behavior and, consequently, find better solutions. Additionally, this work proposes a framework for the optimal design of multi-source WDNs and provides guidelines for obtaining near-optimal solutions in such networks. A comparative study between GTAs and evolutionary optimizations confirms the efficiency of the improved GTA in providing optimal/near-optimal solutions, especially for large WDNs, with a runtime reduction of up to seven orders of magnitude.Austrian Science Fund (FWF

    Optimal rehabilitation planning for aged water distribution mains considering cascading failures of interdependent infrastructure systems

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    This is the final version. Available on open access from IWA Publishing via the DOI in this recordData availability statement: All relevant data are included in the paper or its Supplementary Information.Water distribution networks (WDNs) with other infrastructures constitute a complex and interdependent multi-utility system. Considering interdependencies between WDNs and other urban infrastructures, this work proposes WDN intervention planning using a dynamic multi-utility approach to tackle the challenges of pressure deficits and cascading failures by the decoupling of different infrastructure systems. For this purpose, the study develops reliability indices representing the hydraulic and decoupled statuses of WDNs with neighbor infrastructures; the hydraulic reliability represents the robustness of the network against the water pressure deficit, and decoupling reliability represents the extent to which WDN elements are decoupled from other assets elements. A multi-objective optimization algorithm is employed to develop rehabilitation strategies by introducing three approaches for WDN upgrade following a phased design and construction method. Evaluating intervention plans based on construction cost, reliability and cascade effects shows that, under budget limitation conditions, decoupling a WDN could significantly save the cascade cost such that 1% improvement in the decoupling reliability brings about 157.42 billion Rials cascade cost saving to asset managers. On the other hand, the decoupled network is weak against hydraulic reliability, which could make it by far less resilient network than the coupled network with around 75% hydraulic reliability difference.University of InnsbruckAustrian Academy of Sciences (ÖAW)Austrian Organization Funding for Basic ResearchDOC FellowshipAustrian Science Fund (FWF)European Union Horizon 202

    Smart urban water networks: Solutions, trends and challenges

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    This Editorial presents the paper collection of the Special Issue (SI) on Smart Urban Water Networks [...]</jats:p
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