Water scarcity is a global crisis; according to the World Wide Fund for Nature (WWF), at its current consumption rate, two thirds of the world’s population may face water shortages by 2025. Whilst 70% of the world’s surface is covered by water, only 3% is fresh water, and two thirds of that is tucked away in frozen glaciers, or otherwise unavailable for our use.
Industry is a major user of water; copious amounts are consumed across mining operations, petroleum refineries, smelting facilities, and food processing facilities, to name a few. According to research groups, the fashion industry alone uses 93 billion cubic metres of water per year, which is 4% of all freshwater extraction globally. This number is set to double by 2030. Some of the challenges facing the global water sector are high water demand and its declining supply, poor quality, pollution, climate change, urbanisation, aging infrastructure, spiralling energy costs, and evolving regulations.
South Africa’s water supply and scarcity challenges mirror our global peers; Cape Town and Gqeberha’s recent day zero challenges have fundamentally changed the way we look at the consumption of water in our country. Water sustainability strategy relies on infrastructure that enables data transparency. There are some important, mitigating steps that can be taken to set the world on course to preserving this precious resource. Digital transformation in water processing and delivery operations can begin to help provide lower energy consumption, higher sustainability, and less waste.
Sustainability starts with the ability to extract performance data from the physical infrastructure that supports core operations. In the water and wastewater (WWW) sector, digitisation leads to water processing and distribution network transparency, and traceability of assets as they move through municipal systems. To achieve transparency, core equipment such as motors drives, and pumps need to incorporate sensors to collect the necessary data. Then, cloud-based software tools can connect to the various data silos from different sources and consolidate and combine that data with legacy data.
Once data access is achieved, machine learning (ML) solutions can extract trends which can lead to faster and more sustainable decisions. For example, accurate decisions can be made on how water assets flow through the processes of recycling purification, transportation, and ultimately consumption.
The highest potential for achieving sustainability objectives lies with training intelligent algorithms, or artificial intelligence (AI) to make sustainability decisions in real time, incorporating the many data points that no human could process in a timely enough fashion, to yield autonomous decision making.
Looking at a practical application, UK-based Anglian Water partnered with Schneider Electric to prevent water loss, with a cloud-based holistic solution for water loss management that monitors incoming system performance data on a near real-time basis from multiple data sources.
The municipality now benefits from real-time detection of leaks and anomalies; work orders are dispatched, and repair works are effectively and efficiently executed, saving millions of litres of water per year.
When proposing solutions to water and wastewater firms worldwide, Schneider Electric often partners with major technology firms like Microsoft that share our passion for sustainable operations and support our cloud-based digitisation solutions. In fact, Microsoft has pledged to become water positive by 2030. In water-stressed regions, they have established a goal to replenish more water than is consumed by their operations.
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