With the threat of climate change adding to the Mena region’s water scarcity problem, there are mounting challenges and opportunities for artificial intelligence to play a crucial role in delivering effective solutions.
An estimated 3.5 billion people are expected to be living in water-scarce regions by 2025, and the role of AI in addressing this and other serious environmental problems in the coming years will be crucial.
The problems we face are highlighted in the Mena region, which has 7 per cent of the world’s population but only 1 per cent of its freshwater resources. Meanwhile, across 25 Mena countries, about 83 per cent of the population of 500 million people uses more than 80 per cent of the renewable water supply.
The imbalance between high water demand and limited supply poses a serious hurdle, but AI is already helping – and the big hope must be that future technological advancements can prevent a serious crisis.
For AI innovators and startups aiming to play their part, the size of the task ahead is as daunting as it could be ultimately rewarding. A World Bank report has said that, by the end of this decade, the amount of water available per capita annually in the Mena region will slide below the absolute water scarcity threshold of 500 cubic metres per person, per year.
The study estimates that by 2050, an additional 25 billion cubic metres of water per year will be needed to meet the region’s needs. That is equivalent to building 65 desalination plants the size of Ras Al Khair plant in Saudi Arabia, the largest in the world.
Ratings agency S&P Global recently issued a warning that water stress from rising temperatures and demand is already above globally recommended sustainability thresholds across the GCC nations. Meanwhile, research by PwC, commissioned by Microsoft, estimates that using AI for environmental applications could contribute up to $5.2 trillion to the global economy in 2030, a 4.4 per cent increase relative to business as usual.
It is in desalination, a critical water source, that the Mena benefits of AI could be felt most, as the technology is employed to make the desalination process more energy-efficient and cost-effective. This is a vital factor in a region that needs to dramatically reduce dependence on oil for desalination in order to reduce carbon emissions, while at the same time, meeting a rising demand for water.
The issue is clearest in Saudi Arabia, which aims to grow its current population of 32.2 million to 100 million by 2040. By 2010, Saudi desalination plants were already reportedly using 1.5 million barrels of oil a day, more than 15 per cent of today’s production. But Saudi Arabia is already making big strides in the right direction, investing heavily in AI to enhance the efficiency of desalination plants, reducing energy consumption and operational costs.
In 2019, the Kingdom launched the Saudi Data and Artificial Intelligence Authority that aims to drive the data and AI agenda, and it has set out to attract investments worth $20 billion and train up to 20,000 data and AI specialists by 2030. This can only be good news in the battle to clean up and simplify desalination, which makes freshwater from seawater through a complicated process involving filtering, removing salt and adding minerals.
Machine learning currently analyses data to predict and solve problems. Ongoing enhancements in AI algorithms will improve optimisation, decreasing the environmental impact of desalination processes and making them more accessible for wider use.
We can expect the continued advancement of AI technologies to deliver more innovative solutions for optimising water resource management, boosting efficiency in agriculture, and improving overall water sustainability.
Smart irrigation systems powered by AI will evolve to become more sophisticated, adapting in real-time to changing environmental conditions and ensuring precise water usage in agriculture. Additionally, AI-driven predictive models will enable proactive measures in addressing water quality issues and detecting potential infrastructure vulnerabilities.
In the UAE, AI is driving sustainable initiatives in water management, disaster response and agriculture. For instance, it is used in smart irrigation systems, such as the one in Abu Dhabi’s Masdar City, using real-time data to water plants at the best time to cut wastage. In disaster management, AI analyses various data sources for proactive measures, helping the National Emergency Crisis and Disaster Management Authority to monitor weather conditions and give timely warnings.
It is also transforming the UAE’s agricultural sector. The Emirates Institution for Advanced Science and Technology has developed an AI-based agricultural monitoring system that uses satellite imagery and AI algorithms to assess crop health, detect pest infestations, and make sure water is used wisely.
AI-equipped drones play a role in reforesting areas, as highlighted by Abu Dhabi’s initiative to plant 1 million mangrove seeds. In addition, the technology can play a crucial role in scenario modelling and policy simulation. By predicting the impact of different policies on water resources, decision-makers can formulate strategies to mitigate water scarcity effectively.
The Dubai Electricity and Water Authority uses AI to analyse data for water management, studying past information and current trends to make smart decisions about water policies and infrastructure development.
Meanwhile, the Qatar Environment and Energy Research Institute has been using AI for water quality monitoring. They study information from different sources, such as remote sensing and IoT devices, to give precise and timely details about water purity.
With its flourishing tech and business environment, the Mena region has experienced a significant rise in AI applications that are transforming our lifestyle and work dynamics.
According to PwC estimates, AI could contribute up to $320 billion to the Middle East economy by 2030. One of its primary goals, then, must be to eliminate water scarcity and effectively address other significant environmental challenges.
