Tracking the Health of our Rivers: a first overview and potential patterns found by our community

Blogpost and infographics by Sandra de Vries | Data analysis by Grace Saville | Survey design by Camille Janssen

Since the opening of the Drinkable Rivers Citizen Science Programme in 2022, we have been able to grow into 65 hubs in over 22 countries. These hubs have explored their rivers together with locals and visitors, and taken measurements using the Drinkable Rivers measurement kit. The measurements, that have been uploaded to the Drinkable Rivers data platform are now reaching sufficient levels for analyses, so we can find patterns and have a better understanding of our rivers. Although on a local scale there is not always sufficient data, on a global scale we are starting to see patterns and interesting relationships that we might use to improve the water quality of our streams, canals and rivers. To increase this global and community potential, we have initiated Measurement Weeks twice a year. In these weeks, as many hubs as possible measure in the same week, making their data more comparable. As can be seen in the infographic, this spring 7 hubs measured around the same time. In the years to come, as the number of hubs joining these Measurement Weeks grows, our combined ability to compare river sites improves.

Give your input about data analysis

A river from upstream to downstream: the Thames

Another manner of investigating the data is by tracking the measurements taken from upstream to downstream. One example is the Thames, where Li An took measurements from source to sea when she walked it in September 2023.

In these plots, we highlight the measured Electrical Conductivity (EC), Nitrate and E.coli bacteria. The plots show for each measurement point (1 to 9) the different results, as well as how they compare to an accepted parameter range. Overall, the nitrate and bacteria (e.coli) levels of the Thames are worrying, easily above the preferred parameter range.

Of course since there are only 9 measurements, we can only make some guesses about the meaning of the changes in EC, pH and E.coli levels from up- to downstream. However, we can definitely perceive some plausible hypotheses. For example, we see here that just after measurement point 5, most of the parameters have an increase. Just after Reading and Henley, some tributaries join with the Thames main river. It could be that this tributary brings in more polluted water that mixes with the main stem, and around point 6 we start seeing its influence in the measurements. Of course, this would need to be investigated more closely by, for example, also taking measurements in those tributaries in the future.

source: River Thames Basin (primaryhomeworkhelp.co.uk)

Experiencing the health of your river

In the Surroundings Measurement, one of our 14 different measurements, participants are also asked to observe and share their experience of the river. Mapping these experiences shows that more than half of the time, we experience our observed rivers as pleasant, which is already encouraging.

The relationship between the experience of a river and its actual water quality is multifaceted. The experience of a river can be influenced by its aesthetic qualities, such as the clarity of the water, the presence of wildlife, and the overall natural beauty. These aspects contribute to the recreational and cultural value of a river.

On the other hand, actual water quality refers to the physical, chemical and biological characteristics of the water, which are measured through scientific analysis. This includes parameters like pH levels, dissolved oxygen, presence of pollutants, and microbial content ^{1 2}. We measure some of those parameters, too, and we therefore plotted the perceived experiences and compared them to the average level of electrical conductivity (EC) and pH, measured by you at these locations.0

While a river may appear clean and inviting, it could still have underlying water quality issues due to factors such as pollution from urban runoff, industrial discharges, or agricultural activities. Conversely, a river with poor aesthetic appeal might still have good water quality if it’s well-managed and protected from contaminants.

Understanding the complex interplay between these two aspects is important for effective river management and conservation efforts. It involves considering both the subjective experiences of individuals and communities, as well as objective scientific data to ensure that rivers are preserved for their ecological integrity and for future generations to enjoy.

Interestingly, a more pleasant experience correlates clearly with lower levels of EC and pH. Higher levels correspond here to more unpleasant experiences. High pH levels in surface water can indicate alkalinity, which may be due to natural processes or pollution. Elevated electrical conductivity (EC) levels often suggest the presence of dissolved salts and minerals. Both high pH and EC can affect water quality and ecosystem health.

Influence of surroundings on the health of your river

The health of a river is significantly influenced by its surroundings. The type of landscape around the measurement site therefore tells us much about how these landscapes are used and what type of activities occur there. Factors such as environmental occurrences and human activities like pollution, deforestation, and overfishing can threaten rivers and the communities that depend on them ¹

Urban areas are expected to have a high influence on the water quality, and this can also be recognized in the high levels of EC measured in urban areas compared to other landscape types. Comparably, in farmland areas we expect high levels of nutrients like nitrate and nitrite, and again this pattern is visible here. Farmlands have the highest measured levels of nitrate and nitrite.

Future analyses and overviews of the Drinkable Rivers community data

From now on, we aim to show such overviews of the global community data every half year. But we want to go further than that. We would like to have your own exploration page on the data platform, to display on a local scale the results of your measurements and the relationship between the different parameters, to enable lessons to be learned and action to be taken in the future. We can imagine what type of analyses you would like to see, but we would rather ask you for your input and your needs, to see whether we can fulfill them. We therefore ask you to fill in this survey, and help us understand what you need to learn from your measurements.