Citizens as hazard forecasters: how citizen science can strengthen anticipatory action

In Ecuador, the Ecuadorian Red Cross and the Geophysical Institute trained citizens to take meter readings to monitor volcanic ash levels – data that informs them about possible eruptions of the Sangay volcano. In Zimbabwe, Welthungerhilfe worked with communities to calibrate the data used for its forecast models, for example by including crop assessments and feedback from farmers and communities. And in Peru, communities helped to set up and check monitoring stations that measure temperature, soil moisture and rainfall conditions, all of which are used to forecast mudslides and flash floods caused by heavy rain. 

These are just some examples of how citizen science – the term used to describe citizens taking an active role in scientific research – is being used in anticipatory action and early warnings around the world. To date, there is no comprehensive documentation of the extent to which citizen-generated data is used to forecast hazards. Yet, given the many potential benefits, there is an argument for increasing citizens’ role in collecting hazard data. 

How citizen science can enhance anticipatory action 

The benefits of citizen science have been well documented. One of these is more data being available than there would be without citizens’ involvement – and an increase in data often results in more precise data or greater coverage. Both are useful for anticipatory action, which depends on highly localized data to establish and activate the triggers used to release the pre-agreed financing and initiate the actions. In Ecuador, for example, the citizen scientists enhanced ashfall forecasts by observing and reporting back on ash type, quantity and accumulation – activities that the Geophysical Institute did not have the capacity to undertake itself.  

Other benefits of participation in citizen science include a better understanding of the science itself, as well as increased feelings of responsibility or empowerment. These can also be an advantage for anticipatory action: it is likely that communities that fully understand the science behind the hazards they face are in a better position to act ahead of them, and to recover afterwards.  

Involving citizens from at-risk communities in collecting hazard data could, potentially, also help to speed up early warnings. If communities are helping to collect data that informs the warnings, then they could theoretically issue or forward those warnings to others, enabling everyone to act more quickly ahead of a coming hazard.  

Can – and should – citizen science be an integral part of anticipatory action? 

Communities are often heavily involved in the anticipatory action process – in many places, they are the best placed to carry out or support the actions within their communities – and providing hazard data through citizen science offers another way they can be active participants. Citizen science has been identified as an excellent way for citizens to contribute to forecasting hazards that impact them, and could be particularly helpful in low- and middle-income countries where such data is incomplete or irregularly updated.  

This is not a new idea, of course: communities have been forecasting hazards for centuries, often relying on indigenous knowledge to do so. In Namibia, for example, community elders have used indigenous knowledge of insect numbers to determine if a drought is coming. Describing this as ‘citizen science’ is, essentially, adding a label to something that is already happening. 

Despite the benefits, it may not be possible for citizen-generated data to inform all the forecasts that are used to trigger anticipatory action. One widely reported barrier for citizen science is a lack of trust in citizen-generated data, often due to its perceived (lack of) quality or reliability. Given the need for accuracy in hazard forecasts and triggers, these perceptions may be an issue. Speed could also be a constraint, if it takes time to collate and process citizen-generated data. Nor is everyone willing or interested in being a citizen scientist; it can be an additional time pressure for people facing many other daily tasks. These can be a particular problem when working with marginalized or indigenous communities. 

One way forward is to continue documenting examples of where citizens have actively provided data for hazard forecasts, and to highlight the benefits of them doing so. These can act as case studies for other initiatives to review when considering if this should be part of their own processes. And, in keeping with the principles of locally led anticipatory action, communities can best decide for themselves if this is something they can do – and want to do – as part of their own activities to prepare for and anticipate hazards.