Water and Environment

Alherifiere, Dominique

doi:10.1080/02508068008685878

Cited by 4 publications

(4 citation statements)

References 13 publications

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“…pipe networks. Hafskjold (2010) and Alegre & Coelho (2012) reinforced this with reports and conclusions from their work, which assesses AM of urban water systems. Hafskjold (2010) further emphasised that reliable data is the foundation of successful AM and indicated that it is vital to get the most out of existing data through proficient data recycling, quality control, analysis and interpretation.…”

Section: Graphical Abstract Introductionmentioning

confidence: 56%

“…Hafskjold (2010) and Alegre & Coelho (2012) reinforced this with reports and conclusions from their work, which assesses AM of urban water systems. Hafskjold (2010) further emphasised that reliable data is the foundation of successful AM and indicated that it is vital to get the most out of existing data through proficient data recycling, quality control, analysis and interpretation. Since IAM is data reliant (Alegre & Coelho 2012), a reasonable presumption would be that the alignment of strategic objectives and chain management between IAM levels also depends on data reliability and data management.…”

Section: Graphical Abstract Introductionmentioning

confidence: 56%

“…A review of AM methodologies, such as AWARE-P (Alegre et al 2013;Cardoso et al 2016), Rehabilitation of Urban Sewer Networks (RERAU) (Humbel et al 2014) and Computer-Aided Rehabilitation of Sewer/Water Networks, 2002-2005S & W Projects) (Saegrov 2015), as well as Hafskjold (2010) and Yang et al (2018), highlighted insufficient DQ and uncertainties in data collection and used as constraints limiting IAM implementation. Accessibility (unavailability of data), consistency (aggregation of data), interpretability, timeliness, accuracy, data quantity, integration and interoperability factors were reported which affected the fitness of data for set objectives (Koronios et al 2005;Halfawy 2008b;Woodall et al 2014;Parlikad & Jafari 2016;Rokstad et al 2016;Carriço et al 2020).…”

Section: Graphical Abstract Introductionmentioning

confidence: 99%

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Data-driven asset management in urban water pipe networks: a proposed conceptual framework

Okwori

Pericault

Ugarelli

et al. 2021

Journal of Hydroinformatics

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Analytical tools used in infrastructure asset management of urban water pipe networks are reliant on asset data. Traditionally, data required by analytical tools has not been collected by most water utilities because it has not been needed. The data that is collected might be characterised by low availability, integrity and consistency. A process is required to support water utilities in assessing the accuracy and completeness of their current data management approach and defining improvement pathways in relation to their objectives. This study proposes a framework to enable increased data-driven asset management in pipe networks. The theoretical basis of the framework was a literature review of data management for pipe network asset management and its link to the coherence of set objectives. A survey to identify the current state of data management practice and challenges of asset management implementation in five Swedish water utilities and three focus group workshops with the same utilities was carried out. The main findings of this research were that the quality of pipe network datasets and lack of interoperability between asset management tools was a driver for creating data silos between asset management levels, which may hinder the implementation of data-driven asset management. Furthermore, these findings formed the basis for the proposed conceptual framework. The suggested framework aims to support the selection, development and adoption of improvement pathways to enable increased data-driven asset management in municipal pipe networks. Results from a preliminary application of the proposed framework are also presented.

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Section: Graphical Abstract Introductionmentioning

confidence: 56%

Section: Graphical Abstract Introductionmentioning

confidence: 56%

Section: Graphical Abstract Introductionmentioning

confidence: 99%

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Data-driven asset management in urban water pipe networks: a proposed conceptual framework

Okwori

Pericault

Ugarelli

et al. 2021

Journal of Hydroinformatics

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“…Water pollution has become one of the most pressing environmental problems in the world today [ 1 , 2 , 3 , 4 ]. Water research, especially water pollution analysis, has drawn attention from the general public.…”

Section: Introductionmentioning

confidence: 99%

Optofluidic Technology for Water Quality Monitoring

Wang

Dai

Lei³

2018

Micromachines

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Water quality-related incidents are attracting attention globally as they cause serious diseases and even threaten human lives. The current detection and monitoring methods are inadequate because of their long operation time, high cost, and complex process. In this context, there is an increasing demand for low-cost, multiparameter, real-time, and continuous-monitoring methods at a higher temporal and spatial resolution. Optofluidic water quality sensors have great potential to satisfy this requirement due to their distinctive features including high throughput, small footprint, and low power consumption. This paper reviews the current development of these sensors for heavy metal, organic, and microbial pollution monitoring, which will breed new research ideas and broaden their applications.

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