How Artificial Intelligence Can Clean Up the World’s Groundwater

The Global Burden of Water Pollution

The United Nations’ Sustainable Development Goal 6 states, “Ensure availability and sustainable management of water and sanitation for all,” however, billions of people worldwide lack access to this. Recent estimates state that an approximate 2.2 billion individuals lack safely managed drinking water services, 4.2 billion people are deprived of safely managed sanitation services while 3 billion people do not have access to basic handwashing facilities.

To remedy the situation, the UN laid out four key principles to achieve SDG 6:

i. To filter drinking water from wastewater

ii. To access and purify drinking water to eliminate chemical and biological contaminants

iii. To guard and rehabilitate freshwater ecosystems

iv. To ensure access to water and water rights

Despite these clear and strategic principles, the world is still some way off from attaining the targets of SDG 6, designed in 2015. The World Bank has described this problem as an “invisible crisis of water quality”.

Consider the facts:

i. An estimated 80% of the world’s wastewater is released back into the environment untreated.

ii. Just about 26% of urban and around 34% of rural sanitation and wastewater services adequately prevent human contact with faeces and are considered well-treated. 

iii. Globally, microbiologically contaminated drinking water leads to around 485,000 deaths each year.

iv. The World Bank reports that water pollution can reduce economic growth by as much as a third in some regions of the world.

Groundwater: Global Importance and Pollution

Groundwater is the water found beneath the earth’s surface. It is the most extracted resource globally and the most used source of freshwater for human activities. By percentage, it makes up 50% of the world’s drinking water, 40% of all water used for irrigation is from groundwater while it accounts for 33% of industrial water use.

Its importance to humankind cannot be overstated.

Groundwater pollution results from the discharge of materials that reduce its quality for consumption or use. The source of the pollution may be point or non-point. Examples of point sources include oil spills, septic tanks, landfills while non-point sources include chemicals from agricultural activities.

Artificial Intelligence and Groundwater

Existing methods for monitoring the purity of groundwater require the periodic (quarterly or yearly) collection of samples for analysis. While contaminants may be detected at the time of collection of these samples, the limitation is that it does not allow for the real-time evaluation of changes that may lead to a spike in the level of pollutants. This restricts the extent to which proactive decisions can be made.

However, as several studies have demonstrated, the use of certain Artificial Intelligence techniques alone or in conjunction with hardware such as sensors can fill the gap for real-time monitoring of groundwater contamination. In addition, these same techniques can be used to predict contamination levels at different periods of the year based on historical data.

Furthermore, Artificial Intelligence can be used for more efficient management of groundwater resources through models designed to predict groundwater levels in a given area.

As climate change further reshapes the world’s landscape, its effect on groundwater quantity and quality will be inevitable. AI models may be developed to monitor these effects and establish correlational relationships from which intervention points may be identified to preserve the integrity of groundwater.


Comment  0

No comments.