STREAM alumnus wins gold at IWA World Congress

The International Water Association (IWA) World Water Congress is, arguably, the biggest event in the water sector’s calendar. Attracting water professionals from over 100 countries, the event connects people working in the water sector from all over the world to share knowledge about the latest trends, innovative technologies and leading practices. A highlight of the programme is the biennial IWA Project Innovation Awards, which recognise and promote excellence and innovation in water management, research and technology. The 2018 IWA Project Innovation Award winners, announced on 17^thSeptember, included Severn Trent Water, who received a gold award for their Smart Abstraction Management under the innovation category of Smart Systems and the Digital Water Economy. This award-winning work is based on the research of STREAM alumnus (and current Severn Trent employee) Alemayehu Shitaye Asfaw’s, whose EngD project developed a real-time surface water abstraction management tool. 

Severn Trent Water winning Gold Award for Smart Systems and the Digital Water Economy at  the IWA World Congress

The project

The focus of Alemayehu’s EngD project was to develop new approaches to inform and aid the management of surface water abstraction, with a specific focus on tackling the management challenges associated with increasing demand and diffuse pollution. The project combined the development of a real-time water resources management model with the development of a pollutant prediction model. The project was undertaken at the University of Sheffield, sponsored by Severn Trent Water. 

Abstraction management: water resources

Variability in the distribution of water spatially and over time poses challenges when supplying drinking water to meet rising demands while protecting the environment. These challenges are particularly potent in the face of a rapidly increasing population and climate change. Surface water is the primary source of drinking water in the UK, supplying two-thirds of the drinking water in England and Wales, which puts these water resources under pressure. UK environmental regulators are working with the water industry to implement environmental improvement schemes to ensure that UK water courses meet national and European targets. Therefore, the careful management of these water resources is necessary to enable their efficient and sustainable utilisation. Current abstraction management tools and decision-making processes are not supported by real-time data on river flow levels, which affect the daily availability of water, and so opportunities to abstract more water are missed. The use of real-time river flow data will also reduce the need to trigger drought management actions, improving the resilience of water resource production systems.

Abstraction management: diffuse pollution

Pesticide use in agriculture

Diffuse pollutants, such as pesticides from farming, are a significant threat to the quality of water resources, with ever increasing levels being found in raw water sources. The cost of water pollution is estimated at £700million to £1.3 billion per year. Water pollution increases the industry’s carbon footprint due to the need to further treat water to meet drinking water standards. Metaldehyde, a pesticide used globally in agriculture, is a pollutant of particular concern due to recently observed high levels. Therefore, a model capable of predicting short-term fluctuations in metaldehyde concentrations in surface waters will enable informed decision-making to improve water quality.

Outcomes

Alemayehu’s work integrated these two aspects through a combined modelling approach. The project was able to show that an integrated modelling framework can be used to develop a flow forecast model that is suitable for surface water abstraction management purposes. Such schemes can play a significant role in recharging reservoir levels during dry periods, which increases the resilience of drinking water supplies. The pollutant model was effective in predicting variability in pollutant concentrations for operational decision-making purposes. Importantly, the predictive model allows abstraction to be suspended up to 48 hours in advance of high metaldehyde concentrations occurring. 

Winning the IWA Smart Systems and Digital Water Economy Gold Award highlights the incredible potential of Alemayehu’s STREAM project for solving water industry issues through environmentally friendly methods. The implementation of his EngD work is ongoing, showing how a STREAM EngD can really make a difference in practice.