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The Project

HOWS is a three-year EPSRC-funded project run by the University of Exeter's Centre for Water Systems, which will investigate interactive methods for designing and managing water systems, incoprorating visual analytics, heuristic optimisation and machine learning methods.

The overall aim of the HOWS project is to develop a new approach for designing and managing improved, near-optimal and engineering-intuitive water systems by incorporating visual analytics, heuristic optimisation and feedback-informed learning.

It is widely acknowledged that the water and wastewater infrastructure assets, which communities rely upon for health, economy and environmental sustainability, are severely underfunded on a global scale. For example, a funding gap of nearly $55 billion has been identified by the US EPA (ASCE, 2011). In England and Wales, the total estimated capital value of water utility assets is £254.8 billion (Ofwat, 2015), but between 2010 and 2015 only £12.9 billion was allocated for maintaining and replacing assets. Combined with the drive to reduce customers' bills, there will be even more pressure on water companies to find ways to bridge the gap between the available and required finances. As a result of this it is not surprising that optimisation methods have been extensively researched and applied in this area (Maier et al., 2014).

The inability of those methods to include into optimisation 'unquantifiable' or difficult to quantify, yet important considerations, such as user subjective domain knowledge, has contributed to the limited adoption of optimisation in the water industry. Many cognitive and computational challenges accompany the design, planning and management involving complex engineered systems. Water industry infrastructure assets (i.e., water distribution and wastewater networks) are examples of systems that pose severe difficulties to completely automated optimisation methods due to their size, conceptual and computational complexity, non-linear behaviour and often discrete/combinatorial nature. These difficulties have first been articulated by Goulter (1992), who primarily attributed the lack of application of optimisation in water distribution network (WDN) design to the absence of suitable professional software. Although such software is now widely available (e.g., InfoWorks, WaterGems, EPANET, etc.), the lack of user under-standing of capabilities, assumptions and limitations still restricts the use of optimisation by practicing engineers (Walski, 2001).

Automatic methods that require a purely quantitative mathematical representation do not leverage human expertise and can only find solutions that are optimal with regard to an invariably over-simplified problem formulation. The focus of the past research in this area has almost exclusively been on algorithmic issues. However, this approach neglects many important human-computer interaction issues that must be addressed to provide practitioners with engineering-intuitive, practical solutions to optimisation problems. This project will develop new understanding of how engineering design, planning and management of complex water systems can be improved by creating a visual analytics optimisation approach that will integrate human expertise (through 'human in the loop' interactive optimisation), IT infrastructure (cloud/parallel computing) and state-of-the-art optimisation techniques to develop highly optimal, engineering intuitive solutions for the water industry.

The new approach will be extensively tested on problems provided by the UK water industry and will involve practicing engineers and experts in this important problem domain.


Water Distribution Networks

To develop a flexible application for the intuitive visualisation, simulation and optimisation of WDNs.

Continual Learning

To develop the application to enable continual learning wherein practicing engineers come to under-stand the optimisation process through interaction with the software system.

Industry Collobaration

To work in collaboration with key industry representatives from the technology sector (Virtalis, XP Solutions), water (Bristol Water, South West Water) and consulting (SEAMS Ltd).

Visual Analytics

To create new visual analytics capability for water distribution network design.

Optmisation Heuristics

Learn optimisation heuristics from human interaction and embed them within the approach.

Performance Metrics

Develop real-world performance metrics that characterise 'engineering intuitive' solutions.

Method Evaluation

To evaluate these methods on benchmark problems (e.g. Anytown, Exenet - Wang et al., 2015); to establish a relationship between 'mathematical optimality' and 'engineering intuitive' solutions with the aim to create more 'engineering intuitive' objective functions.

Engage Experts

To use the system to engage water industry experts and to investigate the stages of the learning process, test user intervention strategies and the performance improvements thereof.


To experiment with the parameters of the intervention strategies to reduce fatigue and maximise useful human input to the optimisation process.


To use the developed system to optimise the design, rehabilitation and operation of real-world water systems derived from the industrial users, e.g., the Exeter network with over 21,000 pipes (see the letter of support from South West Water).


We are working with the following industrial and academic partners

The Team


Dragan Savic

Professor of Hydroinformatics

Professor Savic (FREng, FICE, FCIWEM, FIWA, MASCE, CEng) is the UK's first Professor of Hydroinformatics having held this post at the University of Exeter since 2001. His research interests cover the interdisciplinary field of Hydroinformatics.


Ed Keedwell

Associate Professor in Computer Science

Prof. Ed Keedwell is an Associate Professor in Computer Science. He joined the Computer Science discipline in 2006 having previously been a Research Fellow in the Centre for Water Systems and was appointed as a lecturer in Computer Science in 2009.


David Walker

Research Fellow

David Walker is a Research Fellow at the University of Exeter. The focus of his PhD was the understanding of many-objective populations. A principal component of his thesis involved visualising such populations and he is particularly interested in how evolutionary algorithms can be used to enhance visualisation methods.


Matt Johns

Research Fellow

Matthew Johns is a Research Fellow in the College of Engineering, Mathematics and Physical Sciences at the University of Exeter. After obtaining degrees in Mechanical Engineering (BEng) and Engineering and Management (MSc) he embarked on a PhD in Computer Science at the University of Exeter.


Alan Denbigh

Impact Manager

Alan Denbigh works in the environment team of Exeter University’s Impact, Innovation and Business division. His role in the HOWS project is to develop the impact with our partners and looking for ways to ensure that the research gets good traction in the water industry and beyond.


Nick Ross

PhD Student

Nick Ross is a PhD Student in the College of Engineering, Mathematics and Physical Sciences at the University of Exeter, undertaking research in the Gamification of Optimisation of Water Distribution Systems.



HOWS Team Present at CwMAG Autumn Conference

October 2017 by David

Members of the HOWS team attended the Clean Water Modelling Advisory Group (CwMAG)’s annual autumn conference in Nottingham last week. Bringing together members of the modelling community from across the UK water industry, the conference was an ideal opportunity to present progress on the project to date and engage with industry experts.


First TAG Meeting Held

May 2017 by David

The first HOWS project Technical Advisory Group (TAG) meeting was held at Exeter this week. The TAG, comprising representatives from the water industry, visualisation and optimisation experts from technology companies as well as academic partners, is vital to the project's success as they will be active in steering the design of interactive optimisation tools, as well as evaluating their potential.


HOWS Project Begins

February 2017 by David

The HOWS project - "Human-Computer Optimisation for Water Systems Planning and Management" - began this month. The project, which is funded by the EPSRC is a collaboration between academics within Engineering and Computer Science, and will look at ways in which state-of-the-art optimisation tools can be used within the water industry. Often, such methods are not intuitively understood by engineers, which can limit their use to more basic approaches.




As a first step in the HOWS project, the team are gathering industry opinions about the use of optimisation within the water industry. If you are a water industry professional engaged in optimisation work, we would be delighted to hear your thoughts. Please take a few minutes to fill out the survey, which can be found here.