Human-Computer Optimisation for Water Systems Planning and Management (HOWS)

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.

The cost of repairing and expanding UK drinking water infrastructure will increase substantially in the next 25 years, an expense that likely will be met primarily through higher water bills if better planning tools are not developed and adopted by the water industry. However, currently, the industry and their supply chain (contractors, consultants) do not consider optimisation as a viable vehicle for achieving efficiency in water infrastructure planning and management. The project directly addresses not only this issue, but also a major societal challenge: how should the UK achieve its provisioning of high-quality water supply services in the future while facing severe economic and population pressures, a strategic question of great importance to any society. The research will focus on how water supply infrastructure planning and management can be improved by creating a visual analytics optimisation approach that will integrate human/industrial expertise, advanced IT infrastructure and state-of-the-art optimisation techniques to develop highly optimal and engineering intuitive solutions for the water industry.

Two broad communities of stakeholders will be targeted: the end-user and research communities.

End-user communities:
The work will be of interest to: (i) the water industry and their contractors, (ii) the public, including various water users (domestic, industrial, commercial), (iii) software and IT technology providers, (iv) infrastructure stakeholder beyond the water industry, e.g., gas, electricity, transport, and (v) the policy community and regulators (e.g., Ofwat, Water Industry Commission for Scotland, the Environment Agency, etc).

Research/academic communities:
Impact within the academic and research communities will be achieved through (i) publications in prestigious international journals and (ii) presentations at key conferences and workshops. Importantly the research community will additionally benefit from the same pathways specified for the user community.

Methods of Engagement:
During the application period the PI and Co-Is have already engaged with a range of stakeholders regarding this particular project. They will further develop these dialogues during the project in keeping with the following Impact Strategy:

1. Build awareness of the project among stakeholders (the direct and indirect water infrastructure managers and policy makers). This will be done by the following means:
a. Technical Advisory Group meetings - TAG is composed of members representing the major stakeholders in the planning and management of water infrastructure in the UK.
b. Case Studies and HOWS system demonstrations - The two water utility partners (South West Water and Bristol Water) are will provide data on real water distribution systems for case studies
c. The Clean Water Modelling Advisory Group meetings - A member of TAG will enable two-way communication between research team and CwMAG practitioners.
d. Visits to stakeholder organisations - Visits to project partners, stakeholder organisations and a number of water and software companies will be arranged.
e. Publications and International Conferences - Publish in industry specific journals and magazines and attend industry conferences, e.g., Water Distribution Systems Analysis Symposium 2018.
f. Development of a website - This will target academic and non-academic audiences; provide information on the project, academic and user publications; allow user feedback.

2. Influence policymakers on key aspects of the research, e.g., OFWAT and the Environment Agency.

3. Engage third sector bodies, e.g., UK Water Partnership,The Rivers Trust, Smart Water Network-SWAN, Ctrl+Swan Action Group of EIP Water, KWR in the Netherlands, gas, electricity and transport infrastructure managers.

4. Engage the public and other interested parties via, e.g., press releases, media interviews and social media (Twitter, Research Gate, LinkedIn groups).