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An International AI Strategy for Water

Do We Need a Multilateral Strategy to Consider the Use of AI in Water?

This article looks at three different angles from a video publisher on the water crisis; it then proceeds to the outline of the issue in the sustainable development goal 6: clean water and sanitation; then it proceeds to looking at a few applications of artificial intelligence within water management.

Three videos from VOX describes the issue from three different angles:

  1. The future of water with consideration for present treatment methods in places such as Namibia.
  2. Flint’s water crisis.
  3. As well as the international management of rivers in the Middle East.

Water is a local and international issue for humanity.

It can lead to local crisis due to mismanagement:

Rivers are managed through the building of dams and local initiatives.

Large issues mentioned as part of the sustainable development goal 6: clean water and sanitation.

  • 1 in 4 health care facilities lacks basic water services
  • 3 in 10 people lack access to safely managed drinking water services and 6 in 10 people lack access to safely managed sanitation facilities.
  • At least 892 million people continue to practice open defecation.
  • Women and girls are responsible for water collection in 80 per cent of households without access to water on premises.
  • Between 1990 and 2015, the proportion of the global population using an improved drinking water source has increased from 76 per cent to 90 per cent
  • Water scarcity affects more than 40 per cent of the global population and is projected to rise. Over 1.7 billion people are currently living in river basins where water use exceeds recharge.
  • 2.4 billion people lack access to basic sanitation services, such as toilets or latrines
  • More than 80 per cent of wastewater resulting from human activities is discharged into rivers or sea without any pollution removal
  • Each day, nearly 1,000 children die due to preventable water and sanitation-related diarrheal diseases
  • Approximately 70 per cent of all water abstracted from rivers, lakes and aquifers is used for irrigation
  • Floods and other water-related disasters account for 70 per cent of all deaths related to natural disasters

An article about Digital Water Transformation and the Promise of Artificial Intelligence mentions the following use cases:

  1. Use the aforementioned AI methods, like neural networks, for optimizing Waste Water Treatment: Research has shown that using neural networks for optimizing the traditional PID controllers in real time of wastewater can reduce energy cost up to 40%.
  2. Deploy sensor networks and remote actuators for optimizing leak detection and drinking water pressure, especially in cities with lack of water. (e.g, Stattus4) According to Mckinsey only leak detection could save the world’s utilities up to USD$69 billion a year.
  3. To share data between utilities and factories’ WWTPs, so ‘the learning’ would be better and decisions could be optimized. By sharing data among several water users, it could be much easier to improve and optimize each system.
  4. To deploy sensor networks for better real time insights of the drinking water and sewage system. Having an extended and comprehensive network of sensors could help identify and control non-revenue water and in cities with restricted water availability to manage the pressure and flows according to demand (e.g., EMAGIN).
  5. AI tools are already in place for optimizing AI desalination plants in Chile and Israel for both drinking water and industrial use for example.
  6. Coordinating Combined Sewer discharges for avoiding Combined Sewer Overflow during rainy periods. By sharing certain non-sensitive information between industries in a basin or city, it could be possible to coordinate discharges avoiding overflow and reducing pumping cost. It could even be possible to coordinate water withdrawals.

An interesting way to help gather data is the Ocean Data Foundation:

We have to manage our water resources better and AI can be part of the solution, so how will we collaborate across nations for us all to consider to live in harmony with our water resources?

It must be mentioned as well that data centres storing or helping to operate artificial intelligence algorithms are often quite water intensive (requires a lot of water).

This is #500daysofAI and you are reading article 259. I am writing one new article about or related to artificial intelligence every day for 500 days. My current focus for 100 days 200–300 is national and international strategies for artificial intelligence.

Written by

AI Policy and Ethics at www.nora.ai. Student at University of Copenhagen MSc in Social Data Science. All views are my own. twitter.com/AlexMoltzau

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