This year’s High-level Political Forum on Sustainable Development (HLPF) discusses SDG 6 on ensuring availability and sustainable management of water and sanitation for all. One major goal of the HLPF is to review the qualitative status of the targets so as to improve water quality by 2030.
One important indicator for reviewing targets is indicator 6.3.2: ‘Proportion of bodies of waters with good ambient water quality’.
Governments face one major challenge here: the water quality data gap. Whereas there are common indicators to measure water quality such as pH, temperature, or the total amount of nitrogen, such indicators are not measured thoroughly for a comprehensive understanding of water quality. As the 6.3.2 indicator report highlights, many custodian agencies lack institutional structures and coordination to collate data and mobilise necessary personnel.
In hopes of tackling the problem, there are signs for a shift from traditional data gathering — government authorities monitoring water quality through extensive networks — to additionally gathering data through citizen-led water quality monitoring activities. The thematic review paper for HLPF focusing on volunteer groups specifically refers to SDG 6, pinpointing the importance of citizens testing water samples in ensuring safe water and sanitation for all.
‘Citizen Science’: Is it really useful to address the water quality data gap?
A relatively new concept, citizen-led monitoring is also referred to as ‘Citizen Science’ — “the collection and analysis of data relating to the natural world by members of the general public, typically as part of a collaborative project with professional scientists.”
It is one of the avenues suggested by the custodian agencies of SDG indicator 6.3.2. But is the involvement of citizens really useful to address the water quality data gap?
Such involvement can have important advantages, particularly in data collection. Because any citizen can go out to collect data, data samples are potentially large. Such data can also be collected in a cost-effective manner, and it can speed up and improve environmental detection. In other words, the more people that are collecting good quality data, the higher the chances of detecting environmental changes early on.
Citizen science thus makes projects possible to operate at larger geographic scales and over longer periods of time, depending on available human and capital resources. For instance, the National Water Quality Monitoring Council points out that there are more than 1,720 citizen science groups just across the US, carrying out volunteer water quality monitoring. Earthwatch supported approximately 1,400 field research projects in more than 120 countries, as well as over 100,000 people joining Earthwatch projects to contribute 10 million hours of data collection.
However, literature points out that citizen science also has shortcomings. Data collected by volunteers may be skewed or biased because the volunteers may not have appropriate scientific knowledge and training to gather accurate data. Also, motivating volunteers to participate in water quality monitoring scientific projects can be quite difficult since volunteers may also lack necessary laboratory equipment and funding for proper data collection. Lastly, people tend to be selective about which citizen science project they participate in because interests vary. Particular public attention and funding, for example, are given to biodiversity monitoring of attractive species such as wolves, bears, and certain birds.
The way forward for citizen science in water quality monitoring
Vigorous discussion is ongoing on how to overcome these obstacles in citizen science. The motivation of non-scientists to participate in citizen science can be increased by providing recognition and attribution for the work they have done, and when they gain feedback from the scientists on how their data were put to use. Analyses also point to increased motivation when the volunteers felt involved within the community. Furthermore, citizen science data can also have high statistical power if data samples are large, which has potential for correcting flawed and biased data.
So, is citizen science an effective method for tackling the water quality data gap? Literature reviews and a quick review of citizen science projects suggest that involving citizens in water quality monitoring has strong potential — that’s for sure. But to fully benefit from the involvement of citizens, possible bottlenecks have to be overcome.
We argue for well-designed citizen science projects in the field of water quality monitoring, considering lessons learned from existing projects and other fields of practice. The custodian agencies could consider providing guidelines for good citizen science and encourage Member States to implement well-designed projects for resolving the water quality data gap.