Dr Steve Mounce

Dr Steve Mounce

Visiting Research Fellow

Department of Civil and Structural Engineering
Sir Frederick Mappin Building
Mappin Street, Sheffield, S1 3JD

Email: s.r.mounce@sheffield.ac.uk
Twitter: @HydroSmartLtd

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ORCiD: 0000-0003-0742-0908


PhD Computer Science / Engineering, University of Bradford; MSc Computing, University of Bradford; BSc Special Honours Mathematics, University of Hull.


After promotion to Research Fellow in 2011, Dr. Mounce was an investigator on research projects with a total value of £7.5 M, including £1.9 M to the University of Sheffield (£470 k PI and £1.43 M CoI). Since 2015 he worked part-time whilst developing his own micro- company (Mounce HydroSmart) and now holds a Visiting Research Fellow position.

Steve has a Degree in Mathematics with Specials Honours from Hull University in Mathematics, a Masters Degree in Computer Science at the University of Bradford in 1994 and was awarded a doctorate in Computer Science at the University of Bradford in 2005 (A Hybrid Neural Network Rule-Based System applied to Leak Detection in Water Pipeline Distribution Networks). He joined the Pennine Water Group in 2005. During this period he worked on and led a number of research projects including:

  • YWS funded ADA project - Researching an automated computing system for the detection and location of leakage in water distribution systems using Artificial Neural Networks (ANNs) and Fuzzy Logic
  • EPSRC NEPTUNE project - Delivering sustainable water systems by optimising existing infrastructure via improved knowledge, understanding and technology
  • EPSRC Pipe Dreams project - New knowledge, tools and techniques to maximise the performance of existing ageing buried pipe infrastructure
  • EU FP7 SmartWater4Europe project - Developing and demonstrating for four European test sites an integrated solution for smart management of water distribution including leakage control, water quality management and energy optimisation (PI)
  • EU H2020 CENTAUR project to provide an innovative, cost effective, local autonomous sewer flow control system to reduce urban flood risk (investigator)

His main research areas are:

  • Application of Artificial Intelligence and machine learning techniques such as Artificial Neural Networks (Design, implementation and training using various architectures including MLP, Kohonen SOM, Time Delay, recurrent, associative and Mixture Density Network), Fuzzy Logic and Knowledge Based Systems for classification, prediction and pattern recognition applications. Experience with other data driven methodologies such as Support Vector Machines, ensemble decision trees and Genetic Algorithms. Latest research interests involve Deep learning, ontologies and knowledge extraction for intelligent agents/ chatbots and blockchain as a service.
  • Active in applying computer science skills to water engineering and hydroinformatics research in the areas of leakage (including smart meters), CSO analytics, water quality and burst event detection systems, fuzzy RTC, data mining, case based reasoning, sustainability assessment and knowledge management.

Activities and Distinctions

  • Invited peer reviewer for high quality international journals, including Water Research, HydroInformatics, American Society of Civil Engineers Water Resources Planning and Management, ICE Water Management, IME Engineering for the Maritime Environment, Water Resources Management, Environmental Software and Modelling, Advances in Water Resources and Environmental Research. Reviewer for the Royal Society, National Science Centers and international PhD external examiner.
  • Winner of the 2010 IWEX University Challenge (Presented at Sustainabilitylive! 2010).
  • Commercialisation of Artificial Intelligence based automated analysis research software (FlowSure) by Servelec, £100,000 IP assignment deal. (Datective Flowsure). Nominated for ‘Innovative Technology’ Water Industry Achievement Award 2017 with Welsh Water for application to wastewater network.

Selected Publications

Authored more than 100 journal and conference papers and book chapters and H-Index 13/ 19 (Scopus/ Google Scholar). Examples of outputs:

  • Mounce, S. R., Shepherd, W., Ostojin, S., Abdel-Aal, M., Schellart, A., Shucksmith, J., and Tait, S. (2020) Optimisation of a fuzzy logic based local real-time control system for mitigation of sewer flooding using genetic algorithms. IWA Journal of Hydroinformatics.  In Press.
  • Furnass, W. R., Mounce, S. R., Husband, P. S., Collins, R. P. and Boxall, J. B. (2019) Calibrating and validating a combined accumulation and mobilisation model for water distribution system discolouration using particle swarm optimisation. Journal of Smart Water  Springer (Open Access), Vol 4 (3), pp 1-24.
  • Mounce, S. R., Ellis, K., Edwards, J., Speight, V., Jakomis, N. and Boxall, J. B. (2017) Ensemble decision tree models using RUSBoost for estimating risk of iron failure in drinking water distribution systems. Water Resources Management. Vol. 31 (5), pp. 727-738. DOI: DOI: 10.1007/s11269-017-1595-8  (Open Access Springer)
  • Mounce, S. R., Blokker, E. J. M, Husband, S. P., Schaap, P. G. and Boxall, J. (2016) Multivariate data mining for estimating the rate of discoloration material accumulation in drinking water distribution systems Journal of HydroInformatics. Vol. 18, No. 1, pp. 96-€“114. DOI 10.2166/hydro.2015.140 .
  • Mounce, S. R., Gaffney, J. W., Boult, S. and Boxall J. B. (2015) Automated data driven approaches to evaluating and interpreting water quality time series data from water distribution systems. ASCE Journal of Water Resources Planning and Management. Vol. 141 (11), pp. 1-11. http://dx.doi.org/10.1061/(ASCE)WR.1943-5452.0000533
  • Mounce, S. R., Mounce, R. B., Jackson T., Austin J. and Boxall J. B. (2014) Pattern matching and associative artificial neural networks for water distribution system time series data analysis. Journal of HydroInformatics. Vol. 16 (3), pp. 617-632. DOI: http://www.iwaponline.com/jh/016/jh0160617.htm (IWAP OPEN)
  • Farley B., Mounce S. R. and Boxall J.B. (2013) Development and field validation of a burst localisation methodology. ASCE Journal of Water Resources Planning and Management, Vol. 139, No. 6, pp. 604-613. DOI: 10.1061/(ASCE)WR.1943-5452.0000290
  • Furnass, W. R., Mounce, S. R. and Boxall, J.B. (2013). Linking distribution system water quality issues to possible causes via hydraulic pathways, Environmental Modelling and Software, 40, pp. 78-87. DOI: 10.1016/j.envsoft.2012.07.012.
  • Mounce, S. R. and Boxall, J.B (2011) Online Monitoring and Detection in Water Loss, Bentley Systems, Ed. Zheng Wu. ISBN: 978-1-934493-08-3.
  • Mounce, S. R., Boxall, J.B. and Machell, J. (2010) Development and Verification of an Online Artificial Intelligence System for Burst Detection in Water Distribution Systems. ASCE Journal of Water Resources Planning and Management, Vol. 136, No. 3, pp. 309-318. DOI 10.1061/(ASCE)WR.1943-5452.0000030. Citations 104 (Scopus)

Selected Grants

  • 2018-2021: Utility Analytics for Water - part of the Siemens strategic partnership with the University of Sheffield on IoT and Industry 4.0. Investigators: SR Mounce and others. Value: Confidential.
  • 2015-2019: STREAM IDC Industrial project 'Analytics for locating bursts in water distribution systems' funded by United Utilities and EPSRC. Investigators: SR Mounce and JB Boxall. Value: £50k.
  • 2015-2018: CENTAUR (Cost Effective Neural Technique for Alleviation of Urban Flood Risk) Horizon 20-20 European Project. Investigators: ST Tait, SR Mounce, ANA Schellart and JD Shucksmith). Value: £477k Sheffield (consortium total award: €2.5M).
  • 2014-2017: SmartWater4Europe Demonstration Project funded by EC FP7. Investigators: SR Mounce and JB Boxall. Value: £405k Sheffield (Consortium total award: €6M).
  • 2015-2017: PODDS VI Project funded by seven UK Water Companies. Investigators: JB Boxall, PS Husband and SR Mounce. Value: £378k.
  • 2015-2016: Intellitect water quality event detection project. Investigators: JB Boxall, SR Mounce Value: £25k.
  • 2014-2015: Stagnation data mining Phase III project funded by Anglian Water. Investigators: JB Boxall, SR Mounce and V Speight. Value: £50k.
  • 2014-2015: Statistical Services and Operational Research funded by DCC Welsh Water. Investigators: JB Boxall, SR Mounce and V Speight. Value: £72k.
  • 2013-2014: Stagnation data mining Phase II project funded by Anglian Water. Investigators: JB Boxall, SR Mounce and V Speight. Value: £44k.
  • 2013-2014: CSO Analytics Phase II and IIb funded by Yorkshire Water. Investigators: (AJ Saul), JB Boxall, SR Mounce and G Sailor. Value: £79k.
  • 2012-2013: Data mining project funded by Anglian Water. Investigators: JB Boxall and SR Mounce. Value: £27k.
  • 2012: eWater e-Science collaboration with ACA University of York. Funded by Pennine Water Group Platform Grant. Investigators: SR Mounce and JB Boxall. Value: £15k.
  • 2011-2013:  KTP in GA optimised Fuzzy Logic Pumping Station Controller funded by Anglian Water.  Investigators:  JB Boxall, AJ Saul and SR Mounce.  Value: £130k.
  • 2007-2011: Fuzzy logic and ANNs in the Water Industry funded by Anglian Water. Investigators: JB Boxall and SR Mounce. Value: £90k.


  • Supervised three PhD students to completion, currently supervising one external international PhD and primary supervisor for a STREAM EngD student (funded by United Utilities). Previously involved with many MSc / BSc projects.