| publications-1661 |
|
2016 |
E.J. Blokker , William Furnass , John Machell , Stephen Mounce , Peter Schaap , Joby Boxall |
Relating Water Quality and Age in Drinking Water Distribution Systems Using Self-Organising Maps |
|
10.3390/environments3020010 |
Simulation & Modeling |
Uncategorized |
|
Understanding and managing water quality in drinking water distribution system is essential for public health and wellbeing, but is challenging due to the number and complexity of interacting physical, chemical and biological processes occurring within vast, deteriorating pipe networks. In this paper we explore the application of Self Organising Map techniques to derive such understanding from international data sets, demonstrating how multivariate, non-linear techniques can be used to identify relationships that are not discernible using univariate and/or linear analysis methods for drinking water quality. The paper reports on how various microbial parameters correlated with modelled water ages and were influenced by water temperatures in three drinking water distribution systems. |
619024 |
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| publications-1662 |
PEER REVIEWED ARTICLE |
2015 |
S. R. Mounce , E. J. M. Blokker , S. P. Husband , W. R. Furnass , P. G. Schaap , J. B. Boxall |
Multivariate data mining for estimating the rate of discolouration material accumulation in drinking water distribution systems |
|
10.2166/hydro.2015.140 |
Simulation & Modeling |
Uncategorized |
|
Particulate material accumulates over time as cohesive layers on internal pipeline surfaces in water distribution systems (WDS). When mobilised, this material can cause discolouration. This paper explores factors expected to be involved in this accumulation process. Two complementary machine learning methodologies are applied to significant amounts of real world field data from both a qualitative and a quantitative perspective. First, Kohonen self-organising maps were used for integrative and interpretative multivariate data mining of potential factors affecting accumulation. Second, evolutionary polynomial regression (EPR), a hybrid data-driven technique, was applied that combines genetic algorithms with numerical regression for developing easily interpretable mathematical model expressions. EPR was used to explore producing novel simple expressions to highlight important accumulation factors. Three case studies are presented: UK national and two Dutch local studies. The results highlight bulk water iron concentration, pipe material and looped network areas as key descriptive parameters for the UK study. At the local level, a significantly increased third data set allowed K-fold cross validation. The mean cross validation coefficient of determination was 0.945 for training data and 0.930 for testing data for an equation utilising amount of material mobilised and soil temperature for estimating daily regeneration rate. The approach shows promise for developing transferable expressions usable for pro-active WDS management. |
619024 |
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| publications-1663 |
PEER REVIEWED ARTICLE |
2015 |
S. R. Mounce , J. W. Gaffney , S. Boult , J. B. Boxall |
Automated Data-Driven Approaches to Evaluating and Interpreting Water Quality Time Series Data from Water Distribution Systems |
|
10.1061/(asce)wr.1943-5452.0000533 |
Simulation & Modeling |
Uncategorized |
|
No abstract available |
619024 |
|
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| publications-1664 |
PEER REVIEWED ARTICLE |
2014 |
F. Williamson , J. van den Broeke , T. Koster , M. Klein Koerkamp , J. W. Verhoef , J. Hoogterp , E. Trietsch , B. R. de Graaf |
Online water quality monitoring in the distribution network |
|
10.2166/wpt.2014.064 |
Simulation & Modeling |
Uncategorized |
|
To ensure the safe supply of drinking water, the quality needs to be monitored online in real time. The consequence of inadequate monitoring can result in substantial health risks and economic and reputational damages. Therefore, Vitens, the largest drinking water company of the Netherlands, set a goal to explore and invest in the development of intelligent water supply by implementing a smart water grid. To enable this, Vitens has allocated a designated part of their distribution network to be a demonstration network for online water quality monitoring, the Vitens Innovation Playground (VIP). In the VIP, a network of 44 Optiqua EventLab sensors has been installed. EventLab utilizes refractive index as a generic parameter for continuous real-time monitoring of changes in water quality. The EventLab units in the network transmit their data by GPRS to Optiqua servers where the data are processed using event detection algorithms. Deployed as an online sensor network, it allows early detection and rapid response, as well as accurate location of the spread of a contamination within the distribution network. The use of the EventLab sensor network under operational conditions in the VIP is described and its effectiveness is demonstrated by the detection of two water quality events. |
619024 |
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| publications-1665 |
PEER REVIEWED ARTICLE |
2015 |
Peter van Thienen , Ina Vertommen |
Automated feature recognition in CFPD analyses of DMA or supply area flow data |
|
10.2166/hydro.2015.056 |
Hydrological modeling |
Precipitation & Ecological Systems |
|
The recently introduced comparison of flow pattern distributions (CFPD) method for the identification, quantification and interpretation of anomalies in district metered areas (DMAs) or supply area flow time series relies, for practical applications, on visual identification and interpretation of features in CFPD block diagrams. This paper presents an algorithm for automated feature recognition in CFPD analyses of DMA or supply area flow data, called CuBOid, which is useful for objective selection and analysis of features and automated (pre-)screening of data. As such, it can contribute to rapid identification of new leakages, unregistered changes in valve status or network configuration, etc., in DMAs and supply areas. The method is tested on synthetic and real flow data. The obtained results show that the method performs well in synthetic tests and allows an objective identification of most anomalies in flow patterns in a real life dataset. |
619024 |
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| publications-1666 |
PEER REVIEWED ARTICLE |
2017 |
Joost van Summeren , Sidney Meijering , Hendrik Beverloo , Peter van Thienen |
Design of a Distribution Network Scale Model for Monitoring Drinking Water Quality |
|
10.1061/(asce)wr.1943-5452.0000799 |
Uncategorized |
Uncategorized |
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No abstract available |
619024 |
|
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| publications-1667 |
CONFERENCE PROCEEDING |
2014 |
P. van Thienen , D. Vries , B. de Graaf , M. van de Roer , P. Schaap , E. Zaadstra |
Probabilistic Backtracing of Drinking Water Contamination Events in a Stochastic World |
|
10.1016/j.proeng.2014.02.186 |
Simulation & Modeling |
Uncategorized |
|
No abstract available |
619024 |
|
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| publications-1668 |
|
2016 |
E.J. Blokker , William Furnass , John Machell , Stephen Mounce , Peter Schaap , Joby Boxall |
Relating Water Quality and Age in Drinking Water Distribution Systems Using Self-Organising Maps |
|
10.3390/environments3020010 |
Simulation & Modeling |
Uncategorized |
|
Understanding and managing water quality in drinking water distribution system is essential for public health and wellbeing, but is challenging due to the number and complexity of interacting physical, chemical and biological processes occurring within vast, deteriorating pipe networks. In this paper we explore the application of Self Organising Map techniques to derive such understanding from international data sets, demonstrating how multivariate, non-linear techniques can be used to identify relationships that are not discernible using univariate and/or linear analysis methods for drinking water quality. The paper reports on how various microbial parameters correlated with modelled water ages and were influenced by water temperatures in three drinking water distribution systems. |
619024 |
|
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| publications-1669 |
PEER REVIEWED ARTICLE |
2016 |
M. A. Mart?nez-Gimeno , M. Castiella , S. R?ger , D. S. Intrigliolo , C. Ballester |
Evaluating the usefulness of continuous leaf turgor pressure measurements for the assessment of Persimmon tree water status |
|
10.1007/s00271-016-0527-3 |
Uncategorized |
Uncategorized |
|
No abstract available |
619061 |
|
|
|
| publications-1670 |
CONFERENCE PROCEEDING |
2017 |
GALINDO, J., TOROK, S., SALGUERO, F., DE CAMPOS, S., ROMERA, J., PUIG, V. |
Optimal Management of Water and Energy in Irrigation Systems: Application to the Bardenas Canal |
|
10.1016/j.ifacol.2017.08.694 |
Simulation & Modeling |
Uncategorized |
|
No abstract available |
619061 |
|
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