Mott MacDonald’s global sector leader for water Mark Sterndale-Bennett discusses the importance of data-based infrastructure solutions in meeting the challenges of urbanisation, climate change and population growth.
We have an abundance of data in the water and wastewater industry. Asset owners routinely collect data on the performance of their assets, such as flow rates, water quality, and overflow volumes. This can be supplemented by other data streams that influence the performance of a system, such as weather data, geological data, customer patterns, and peak usage.
So, gathering data isn’t the problem. It’s at the next stage of the data journey – where data is stored, combined and analysed – that is often the problem. Too often, data is isolated in siloes. It might even be recorded on paper then filed away. If it’s digitised, it might be accessible to one person or team, but unknown and inaccessible to the wider business.
We’re working on a number of projects to help our clients get ‘data fit’ – connecting their data sources to make better sense of it, leading to new insights that lead to better service.
Added benefits for the ultimate customer
For example, we developed SafeSwim in Auckland to inform local people of which beaches are best to visit in order to avoid pollution from sewer overflows. Doing this the traditional way involves testing water quality at discharge points, with a time lag while samples are analysed in a laboratory. By the time the results are in, water quality may have changed, making the exercise inaccurate at best and possibly dangerous, as swimmers would choose where to swim based on this advice.
However, Safeswim uses data from sensors across the wastewater network combined with other data sources such as weather and tidal information to model asset performance and provide a real-time appraisal of where surfers, swimmers and divers should go.
Auckland Council has a far-sighted approach to the use of cloud-based analytics, enabling it to provide an excellent service to its customers. The potential benefits are clear for any organisation that supplies water, or collects, treats and discharges wastewater. It should appeal to anyone with an interest in the quality of receiving waters. SafeSwim is for beaches, but the same approach could help determine water quality in rivers, recreational lakes or around the performance of treatment plants.
And there's a range of potential applications for a data-led approach. Say you want to build storage capacity to cope with heavy rainfall and minimise the amount of discharge into the river or sea. Traditionally, asset owners tend to be quite conservative in the way they size overflows and will usually end up over-sizing tanks, which equates to a waste of space and capital. If you put your faith in data-based modelling, rather than ‘belt and braces’, then you’ll gain a better real-time understanding of asset performance and have the evidence to reduce the amount of storage.
Let’s develop a data-first approach to infrastructure
Ultimately, the result is better decisions based on better information. This is critical for meeting the challenges of growing populations and rapidly expanding urban areas, and the need to gain resilience against climate change. It’s central to achieving the sixth UN Sustainable Development Goal (SDG6); clean water and sanitation for all.
The water industry has made great strides in data collection, but it’s making sense of that data that really adds value. To do that you need to understand the people and systems that operate these assets. You also need to get excited about the outcomes, not just the technology itself. Water is an easy example, but this opportunity reaches across all sectors where we can bring a real, tangible benefit to the communities we serve.
As societies continue to grow, with climate change impacts on the rise, and with changing supply and demand pressures, smart infrastructure solutions will be key to unlocking hidden capacity and boosting service in a world of constrained resources. If we don’t want to waste water, then we mustn’t waste data.