Securing bathing water quality after extreme storms in Barcelona, Spain

Key Learnings

About the Region

Figure 1: Location of Barcelona. Image Credit: Britannica

Climate Threats

Like many other coasts in the Mediterranean and in Europe, the Catalan coast is highly vulnerable to climate change due to the complex interplay between climate, rich biodiversity and high human activity. Sea level rise is threatening low-lying coasts (especially deltas and estuaries) with increasing flooding risks and salt intrusion, among other impacts. More frequent and intense marine storms affect coastal assets and threaten local species and biodiversity. Water scarcity is a chronic problem, aggravated by climate change and increased tourism, with water supply relying heavily on river transfers, desalination plants, and reclaimed water. Increasing variability in rainfall is exacerbating flash floods – floods associated with heavy rains and occurring in less than six hours – and is causing damage, which is particularly problematic in densely populated areas where marine floods pose an additional threat.

Assessing the impact of overflowing sewage systems on water quality and public health  

Figure 2: Bogatell channel discharge in Barcelona. Sampling point location. Image Credit: Google Maps

Rising global temperatures and more frequent extreme rain events will likely lead to more frequent and more intense occurrences of Combined Sewer Overflow, necessitating improved monitoring and management strategies.

Predicting health risks from sewage overflows with real-time data

To estimate the health risk for bathers exposed to contaminated seawater, the IMPETUS project team developed a Quantitative Microbiological Risk Assessment model and tested it at an urban beach in Barcelona. By combining real-time environmental data, such as weather, sea conditions and sewage overflow events, the model predicts when and where water quality poses a health risk.

It simulates how pathogens spread from the discharge point and estimates concentrations in nearby bathing zones. The model also considers how environmental factors like currents, sunlight and temperature affect pathogen survival.

This tool supports more informed, timely decisions to protect public health after sewage overflows and is transferable to other urban coastal areas facing similar challenges.

The Quantitative Microbiological Risk Assessment model represents a valuable approach for proactive water quality management and establishing early warning systems. It predicts the microbiological risk for bathers in different situations of Combined Sewer Overflow and identifies the areas which present the greatest risk.

Mireia Mesas Suárez, Eurecat (IMPETUS project partner)

Figure 3 shows how the Quantitative Microbiological Risk Assessment model works to estimate the infection risk from microorganism exposure in wastewater.

First, it collects data on weather, seawater and sewage overflow. Then, it calculates how pathogens spread and how likely they are to cause infections. The figure differentiates the steps included in the Calculation module (in green), the input data needed (in blue) and the different improvements incorporated into the model regarding a preliminary Quantitative Microbiological Risk Assessment model developed in previous projects (highlighted in red).

This explains how contamination travels from the discharge point to the surrounding bathing waters.

The model also incorporates degradation processes, which are influenced by environmental factors, such as temperature, solar radiation and salinity. Those parameters can significantly impact pathogen survival and decay rates.

Figure 3: Outline of the QMRA model workflow, upgraded items highlighted in red. Image Credit: Eurecat.

After the sewer discharge stops, the pathogen amount in the water flowing through the discharge channel quickly decreases.

This shows that the contamination in the channel does not last for long, once the overflow event has ended, which is important for estimating how long the bathing area may remain unsafe.

Figure 4: The model output shows the predicted concentration risk, considering the favourable scenario for sea conditions and average CSO intensity (considering 2023-2024 data). Image Credit: Eurecat.

To better prepare for future extreme weather events affecting bathing water quality, simulations with a transport and risk model explored scenarios based on marine currents, wind conditions, and combined sewer discharges. For each scenario, the model predicted pathogen movement and dispersion, estimating swimmer risk and indicating how long a beach might remain unsafe after heavy rainfall. This approach supports decision-making and planning as climate change increases the frequency of such events.

Once in the sea, some pathogens start to lose strength or die due to natural processes; for example, sunlight helps destroy many of them. Warm temperatures and the salt in seawater also affect the survival time of these germs. Therefore, pathogen persistence varies seasonally, showing that degradation rates are higher in summer due to increased sunlight exposure, which supports pathogen degradation. The way the sea moves, especially the speed and direction of currents, has a big impact on how pathogens spread. During spring and autumn, the water currents are generally stronger and more dynamic, which helps to carry away and dilute contaminants faster. As a result, the infection risk usually disappears more quickly in these seasons.

Using bacterial indicators to improve risk assessment

To better estimate health risks from contaminated water, the project team refined the link between commonly monitored bacteria (used as indicators of pollution) and actual disease-causing pathogens. By improving this understanding, the risk assessment model can more accurately reflect real-world conditions for bathers' health.

The sampling campaigns in the case study area supported real-time monitoring of commonly monitored bacteria as indicators, particularly during sewage overflows. This data helped to create more realistic maps, showing where health risks are highest, which in turn supports quicker, more effective decisions on water quality and public safety, including early warnings and targeted actions.

Economic contributions, challenges and outlook

The developed Early Warning System, based on a Quantitative Microbiological Risk Assessment model, helps reduce health risks and prevent unnecessary beach closures by identifying when and where pollution poses a threat. This avoids overly cautious decisions and supports the reputation and economy of coastal areas that depend on tourism. In doing so, the solution benefits both public health and local businesses.

Despite remaining challenges, such as limited access to detailed data and variations in local regulations, this type of tool can play a key role in developing early warning systems for bathing water safety. It enables authorities to act before a situation becomes critical, protecting both public health and the environment.

Looking ahead, integrating artificial intelligence (such as machine learning) could enhance the system by learning from past events to better predict infection risks in future situations, particularly useful for coastal cities aiming to prepare for extreme weather events.

Summary

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