Why using data and AI is key to effective river conservation

Stig Martin Fiskå
1 January, 24

Despite the importance of water to survival, water pollution, from chemicals to sewage, has become a pressing issue in the UK. The compounding effects of climate change and a rising population has led to our water supplies struggling to meet demand. At the same time, a significant 75% of UK rivers pose a serious risk to human health. As climate change intensifies, nations globally will have to grapple with hotter and drier summers, resulting in severe water shortages. In the UK, the situation is reaching a critical point, with the UK Environment Agency cautioning that within 25 years London and the South-East could run out of drinking water.

Meanwhile, the UK population will only grow. While currently at 67 million, by 2050 the UK is expected to be home to 75 million people. Serious change must be implemented to mitigate the effect of existing water pollution, as well as reduce contamination going forward, to ensure sufficient and safe water supplies for the expanding population.

Unfortunately, multiple issues hold us back from achieving our goal of water source preservation. Much of the monitoring of our water sources that takes place currently is not detailed enough or as frequent as necessary. To truly understand our water sources, we must embrace the use of modern technologies to amplify the amount of data we collect and create a holistic system that is able to help us understand changes in real time.

Ensuring the health of our rivers with data and AI

Digitisation will be a driving force to help us keep rivers clean from pollution and protect against accidents. Currently, data is collected from our rivers using a method known as geo-reporting. This consists of data snapshots of rivers being taken – at most monthly. However, rivers ebb and flow, with properties, such as pollution levels, changing not only monthly but on a minute-to-minute basis. As such, it is impossible to tell the overall health of the river from this method.

Enter prediction and real-time monitoring, powered by Artificial Intelligence (AI) and Machine Learning (ML). Autonomous sensors can help us measure biodiversity and pollution levels in rivers with accuracy. Sensors can be placed throughout rivers, and the subsequent data collected is combined with flyover images and satellite data to create a holistic profile of a river’s health.

While water companies might feel the pressure to measure the levels of toxins and bacteria in their water sources, the huge cost of upgrading the relevant infrastructure to be able to achieve this is preventing comprehensive measurement from coming to fruition. There is a solution right in front of us that uses existing sensors, and a smarter approach to utilising the data that comes from them. Machine learning tools and algorithms can be applied to these existing data points to accurately predict activity between the sensors. These innovative models can also detect leakages in our water systems if, for example, pressure drops between pipes.

What’s more, human-produced wastewater also poses a threat to the cleanliness and hence health of our rivers. Currently, wastewater is only required to be treated to 85% cleanliness. The key challenge facing wastewater treatment plants are the significant energy requirements necessary for operations. Implementing real-time monitoring of equipment asset management systems (EAM) can drive significant energy savings, opening up the possibility of cleaning water more thoroughly. At the same time, by incorporating AI capabilities into the treatment process, detrimental ingredients can be identified in sludge disposal, allowing us to identify and remove polluters before they are released back into our rivers.

Fostering systemic change

The key to mitigating further water pollution will be the ability to get the right information to the right people in time to support faster decision making. For example, real-timing monitoring of overflows allows water utility companies and authorities to prepare for any potential flooding and alert local areas so they can protect themselves from harm. As a result, water companies can be more efficient with their resources, helping them identify leaks and underperforming machinery.

Single point solutions that are currently deployed will not be enough to effectively improve the health of our rivers. Systemic change relies on creating a holistic overview of a river. Through the implementation of data-powered tools, the end goal is to create a holistic water supply management system that can not only identify but predict incidents of pollution, allowing human intervention before accidents happen. Water companies will thus be able to move away from purely reporting on their water sources but move towards mitigating and restoring damage.

Giving a voice to our rivers

Water companies and other stakeholders face a complex responsibility in the journey to keeping our rivers healthy while communicating their work. By leveraging the capabilities of data and AI, we can give a voice to the river to speak up for what it needs. Our rivers and water sources are crucial to the survival of mankind. We must ensure that our water supplies are healthy and compliant to standards, that we have a reliable supply and that we are able to increase our abilities to source and deliver water to our growing population.

At the same time, we collectively have a collective responsibility to look after the ecosystems that exist within our water sources, and to minimise sewer floodings and pollution events that can cause havoc on our environment, affecting all sources of life. Our responsibility does not end with only looking after our water sources, but to be able to engage actively with our communities and provide transparency in services and support in water saving programmes.

With our rivers’ health already seriously compromised, using cutting edge technology will no longer be a nice add-on for the water industry, but a critical move to save our rivers from further degradation and mitigate existing damage.

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