Can data science help solve the water crisis?

Claudia Bakeev is an expert in Data Science

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This #TechnicalTuesday, Claudia Bakeev wonders: how can data science help solve the water crisis?

The ever-increasing demand for clean water combined with reducing resources aggravated by climate change continuously imposes new challenges to the water industry. Ofwat’s Price Review 2024 (PR24) has highlighted the need to manage water demand and the environment, while improving services for an increasing customer base.

Current technologies allow for the collection of vast amounts of data every day, ranging from water quality to consumption, from leakage to customer satisfaction, and everything in between. However, the data collected are often of poor quality or not well understood.

Data science is a discipline that can be used to extract meaningful information from large, difficult to interpret data. It uses mathematics, statistics, programming and machine learning to generate solutions ranging from simple analytics to artificial intelligence. It is an expanding field that has been adopted across different industry and business types.

The adoption of data-driven solutions in the water industry is still lagging behind other sectors, and water companies need to invest in data-based innovation to help them comply with the requirements set for AMP8. Possible uses of data science include (but are not limited to):

  • Investigate how climate change will affect the quality of the water supplied to water treatment plants in order to identify and correct potential treatment issues.
  • Identify where and when pipe failures might occur and determine the most cost-effective option to keep the networks in working order, for example, by comparing the cost of replacing the pipe before it fails against fixing it after a failure.
  • Forecast weather conditions and use them in the prediction of future asset health.
  • Detect leakage in water supply networks to help prevent further pipe damage and reduce waste of water while improving supply reliability.
  • Predict the likelihood of a cyber attack on critical infrastructure control systems to improve cyber security.
  • Identify carbon emission patterns to help improve, for example, water and wastewater treatment processes and energy efficiency.
  • And much more.

Although the work to resolve the many issues around clean water supply involves a number of disciplines and organisations, data science has an essential role by providing invaluable insights that can inform the decision-making process that will hopefully lead to a more sustainable future.

Created by potrace 1.16, written by Peter Selinger 2001-2019

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Created by potrace 1.16, written by Peter Selinger 2001-2019

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Claudia Bakeev

Consultant Data Scientist

Claudia is a Chartered engineer with 18 years’ experience in data-driven computer modelling for different industries, including water, wastewater and biopharmaceuticals. She has experience in delivering specialist knowledge to multidisciplinary teams and the ability to use model analysis to achieve solutions. Her project experience ranges from a Mains Repair Analysis with Afinnity water to investigating the effects of climate change on the quality of available water for various water companies.

2023-05-30 11:00:00