A powerful tool for predicting risks
A new study led by BlueAdapt researcher Hao Wang (Deltares, Netherlands) shows that accounting for sunlight exposure and sediment interactions significantly improves predictions of harmful contamination in bathing waters. The team’s approach offers a powerful model that can be used to protect water users.
Read the publication here: https://www.sciencedirect.com/science/article/pii/S0043135425021025?via%3Dihub
Sunlight and sediments
In this new research published by Water Research, Hao Wang and colleagues developed a generic, next-generation model that more realistically simulates what happens to microbes like E. coli once they enter rivers, lakes, and coastal waters. Unlike conventional approaches, the model tracks two key processes that strongly influence how long contamination persists: how quickly bacteria die off when exposed to sunlight, and how they attach to or detach from sediments on the waterbed.
Bathing water quality is commonly assessed using faecal indicator bacteria (FIB) such as E. coli, which signal pollution from sources including wastewater treatment plants, sewer overflows, and agricultural runoff. Under the EU Bathing Water Directive, monitoring is typically done every two weeks. While essential, this sampling can miss short-lived pollution peaks, and laboratory analysis introduces delays that limit early public warnings.
Computer models help to fill this gap, and existing models have provided valuable insights using simplified representations of bacterial behaviour. The new model extends these efforts by accounting for exposure to sunlight and the attachment and detachment of particles in the water.
Key findings:
- Sunlight matters: UV light reduces E. coli in clear waters, but is far less effective in darker, organic-rich waters.
- Sediment type matters: Whether bacteria attach to or detach from sediments depends on their composition (for example, clay versus sand), which affects how long contamination persists in the water.
- Science informs accuracy: Including these processes leads to predictions that are far more accurate than those produced by existing models.
Hao Wang said, “Water quality can change very quickly after heavy rain, sewer overflows, or strong sunlight, and the risks can be hard to assess using just water sampling. Our new model significantly improves accuracy by simulating how microbes like E. coli behave once they enter the water, especially how sunlight and sediments influence how long the contamination lasts. This makes predictions more reliable to help answer questions like ‘is it safe to swim today or tomorrow?” or ‘how will pollution spread after a storm?’.”
A powerful tool for predicting risks
Although developed using E. coli, the model can be adapted for other faecal bacteria and even viruses, and combined with hydrological and climate models. This makes it a powerful tool for building coastal resilience by anticipating pollution risks, providing timely warnings, and assessing long-term climate impacts. For more information about how to use and access the model, please contact Hao Wang via Hao.wang@deltares.nl.
