•
Jul 1
Sand Technologies
Mounting challenges are confronting the UK water sector, particularly those related to polluted rivers. Industrial wastewater runoff is a significant source of concern for water quality, alongside other pollution sources, including agricultural runoff and sewage discharges. Agricultural runoff carries nutrients, such as nitrogen and phosphorus from fertilizers and manure, which can cause algal blooms, deplete oxygen levels in water (hypoxia) and harm aquatic life. Runoff can also transport eroded soil into rivers, leading to sedimentation, which can smother habitats and disrupt aquatic ecosystems. Pesticides used in agriculture can also contaminate water sources, posing risks to marine life and even potentially impacting drinking water supplies.
For water companies in England and Wales, the inability to determine the source and impact of pollutants leaves them with the sole responsibility for environmental water quality.
The water sector must address several persistent issues affecting river health to ensure long-term improvements and safeguard public health. First, the current Bathing Water regulations are insufficient and misaligned with the diverse ways people interact with coastal and inland waters. Designed with a narrow focus on swimmer safety, these outdated and inconsistent regulations fail to account for the needs of other recreational water users, such as kayakers, surfers and paddleboarders.
Next, bathing waters are only officially tested during the designated bathing season, leaving water quality unchecked for 32 to 37 weeks annually. During these unmonitored periods, citizen science data reveals a concerning trend: unsafe water samples can double in some areas, posing heightened risks to water users outside of the bathing season.
Further, current water regulations focus on monitoring for Escherichia coli (E. coli) and intestinal enterococci. Water sources have been found to contain PFAS (known as “forever chemicals”), antimicrobial-resistant bacteria, and pharmaceuticals, according to recent research. Unlike traditional contaminants, these pollutants are not routinely tracked, despite their significant risks to human health. Addressing these unmonitored threats requires immediate regulatory innovation and advanced monitoring solutions to protect public health effectively.
Finally, rivers and open water bodies that are not officially designated as bathing waters primarily support fish and wildlife, rather than human recreational use. This designation means they may present higher health risks as they are not monitored or maintained with public safety in mind.
AI can play a transformative role in environmental monitoring solutions, particularly in areas such as water quality. It is essential to ensure the highest water quality standards are met by shifting from reactive to proactive management. Traditional water quality testing often involves sampling and analysis, which provides a snapshot of water conditions at the time the samples are collected. However, the analysis is slow, and the manual nature of sampling is expensive, resulting in a partial and delayed picture of water quality health at a given time.
In a water treatment facility, AI, integrated with networks of smart sensors (IoT devices), enables continuous, real-time data collection of various parameters, including pH, turbidity, dissolved oxygen, temperature and even the presence of specific contaminants. The constant flow of data enables the instant detection of anomalies.
However, in environmental bodies of water, such as rivers and streams, citizen scientists are willingly collecting water samples to increase visibility, trust and coverage. Their data feeds into an AI model for analysis and detection of contaminants. The citizen scientist collaboration and data collection are a game-changer in river health. AI algorithms are capable of analyzing extensive historical data, encompassing weather patterns, land use, industrial activities, and past contamination incidents. By identifying complex patterns and correlations, AI can predict potential water quality issues before they occur. For example, it can forecast algal blooms, predict pathogen outbreaks after heavy rainfall and anticipate increased pollutant concentrations during droughts. This foresight allows water authorities to take proactive interventions, such as deploying resources to mitigate predicted problems and issuing early warnings to the public.
AI excels at synthesizing data from multiple sources. It can combine river sample data with satellite imagery (for large-scale phenomena such as algal blooms or sediment plumes), weather forecasts, hydrological models and climate projections to provide a more comprehensive understanding of water quality dynamics. This multi-modal data integration enables richer insights and more accurate predictions and mitigation strategies.
AI models learn from the training data. High-quality, timely and accurate data forms the bedrock for trustworthy and accurate predictions and decisions, especially in critical applications such as water quality.
Timely data, in particular, ensures that AI models reflect current conditions and trends, preventing “data drift” where the model’s performance degrades over time due to changes in the underlying data distribution.
In essence, timely and accurate data are the fuel that powers effective AI. Without it, even the most sophisticated algorithms will struggle to deliver meaningful and trustworthy results. This predicament underscores the vital role of citizen scientists in preserving the quality of the UK’s rivers.
Citizen scientists play a crucial role in monitoring and improving river health by actively participating in data collection, analysis and reporting, particularly in the non-bathing season. They contribute to scientific research, often filling data gaps and providing valuable insights into local river conditions.
Data collection among citizen scientists is common in the UK. Citizen scientists use a water quality test kit to collect water samples, test for water quality indicators, such as pH, temperature and dissolved oxygen, and monitor for pollutants. They can identify pollution incidents or other problems early, allowing for timely intervention. Data collected by citizen scientists can also help advocate for policies and actions that improve river health. Groups like the Coquet River Action Group monitor the quality of rivers in Northumberland to address water pollution issues.
The Northumbrian Water Innovation Festival is a unique showcase of innovative thinking paired with new technology. This event brings together individuals from various organizations to develop creative solutions for addressing pressing environmental challenges.
The festival will take place from July 7 to 10, 2025, at Newcastle Racecourse. Since 2017, it has been a hub for collaborative solutions to water sector challenges.
One focus area this year is river health, a pressing issue in the UK. Sand Technologies is partnering with RPS and EMR to host two headline events focused on leveraging citizen science data for a better understanding of environmental water quality:
Sand Technology will also participate in the two hackathons to help the UK improve river health through the use of AI and data. Join us at the festival. Click here to register.
Other articles that may interest you
