
With this tool the user can generate a clear and distinctive display of complex and difficult-to-read flow volume time series, for example, for a particular District Metered Area (DMA) or a supply area. This display provides support in the interpretation of the changes present in the time series in terms of known processes and influences (weather, holidays, etc.) and indications of unknown processes (new leakages, wrong valve positions, customer behaviour).
Underground water distribution networks are occasionally subject to leakages. These are not always easy to determine, nor are the associated losses. Peter van Thienen has developed a method of quickly determining leakage losses: the Comparison of Flow Pattern Distributions (CFPD). Thanks to this innovative method, water companies can make use of the data they already collect to target their efforts in determining the causes of inconsistencies in water balance, as well as gaining more insight into their data and network.
Based on the supply patterns for different periods, the CFPD can characterise and quantify the demand changes and the changes in water losses due to leakage in a specific area.
When there are indications of new leakages and/or wrong valve positions, then further inspections – in the field for instance – can be carried out. The tool therefore constitutes an important source of information to effectively reduce leakage losses, gain insight into customer behaviour and control the distribution process.
Manual
The CFPD conducts a comparative analysis of the flow signals of different periods. These can be days, weeks, months, or other periods of arbitrary length. The comparison identifies the changes (including date) and divides them into types, which are quantified independently of each other.
Some processes that influence the flow are manifested in only one type of change, other processes only in the other type, while some others are, or may be, manifested in both. This differentiation makes it much easier for the user to interpret the observed changes. Based on the available knowledge of the network (operational management, leakage repairs, etc.) and the area (holidays, weather, agriculture, etc.), irrelevant changes can be crossed out, leaving only those changes that require attention (since they may signal leakages or open valves).
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The software
The software converts the raw flow volume data into readable CFPD charts. It also enables the generation of a report, which the user can then interpret in terms of the processes concerned.
Implementation
The software runs on the Watershare® server and can be accessed with a web browser. The software is also available for installation in the company’s own network or as a stand-alone tool. The user can upload the flow data (CSV or XLSX format), perform analyses and generate reports of these. . Any unexpected feature in the data can also be zoomed in on interactively. A report is generated containing the created charts. This can be done for a single DMA or supply area, but also for several areas in parallel, allowing for comparisons to be made between them.
Manual
Training
There are several forms of support available to ensure that you optimise your use of the tool, and that you are updated on all the latest developments. Specifically, you can make use of the following options to suit your particular situation:
- A short introductory – or more elaborate – course on the Network Flow Performance for you, your clients and other stakeholders.
- Expanded or modified functionalities to create tailored solutions.
- Consultancy services.
- Access to Network Flow Performance-related projects or research.
Exercises (with solutions) to familiarize the user with both the CFPD methodology and the NFP tool are available upon request.
Publications
Mentioned in: 4 Publications
Enrolled in: 3 Cases in 2 Countries
- Van Thienen, P. and I. Vertommen (2016)
Automated feature recognition in CFPD analyses of DMA or supply area flow data. Journal of Hydroinformatics 18 (3) 514-530; DOI: 10.2166/hydro.2015.056 - Irons, L., J. Boxall, V. Speight, B. Holden and B. Tam (2015)
Data driven analysis of customer flow meter data. Procedia Engineering, 119, 2015, Pages 834-843 - Zwolsman, G., P. van Thienen, K. Zuurbier, C. van Leeuwen and E. Görgün (2015)
WaterShare(R): an international network for efficient knowledge transfer within the water sector - potential applications in Turkey. Proceedings of the 3rd International Water Congress on Sustainable Water Management, Izmir, Turkey, October 2015. - Pieterse-Quirijns, I. et al. (2015)
Toepassing en uitwisseling van waterdistributiekennis in Zuid-Afrika. H2O Online. - Van Thienen, P. and F. Montiel (2014)
Flow Analysis and Leak Detection with the CFPD Method in the Paris Drinking Water Distribution System. 11th International Conference on Hydroinformatics - Van Thienen, P. (2013)
"A method for quantitative discrimination in flow pattern evolution of water distribution supply areas with interpretation in terms of demand and leakage."
Journal of Hydroinformatics Vol 15 No 1 pp 86–102 doi:10.2166/hydro.2012.171 - Peter van Thienen, Ilse Pieterse-Quirijns, Jan Vreeburg, Karel Vangeel and Zoran Kapelan (2013)
"Applications of discriminative flow pattern analysis using the CFPD method."
Water Science & Technology: Water Supply Vol 13 No 4 pp 906–913 doi:10.2166/ws.2013.080 - Peter van Thienen, Jan Vreeburg and Henk de Kater (2013)
"Water flow data key to pinpointing change."
Water21 June 2013 (15.3) pp36
Also in Chinese - 确定变化的 关键流量数据
Water21 Chinese language supplement, november 2013 - Peter Van Thienen, Ilse Pieterse-Quirijns, Henk de Kater, Johan Duifhuizen
"Nieuwe lekverliesbepalingsmethoden voor het drinkwaterdistributienet."
H2O April 13, 2012