Abstract. Citizen contributions to science have been successfully implemented in many
fields, and water resources is one of them. Through citizens, it is possible
to collect data and obtain a more integrated decision-making process.
Specifically, data scarcity has always been an issue in flood modelling,
which has been addressed in the last decades by remote sensing and is already
being discussed in the citizen science context. With this in mind, this
article aims to review the literature on the topic and analyse the
opportunities and challenges that lie ahead. The literature on monitoring,
mapping and modelling, was evaluated according to the flood-related variable
citizens contributed to. Pros and cons of the collection/analysis methods
were summarised. Then, pertinent publications were mapped into the flood
modelling cycle, considering how citizen data properties (spatial and
temporal coverage, uncertainty and volume) are related to its integration
into modelling. It was clear that the number of studies in the area is
rising. There are positive experiences reported in collection and analysis
methods, for instance with velocity and land cover, and also when modelling
is concerned, for example by using social media mining. However, matching the
data properties necessary for each part of the modelling cycle with
citizen-generated data is still challenging. Nevertheless, the concept that
citizen contributions can be used for simulation and forecasting is proved
and further work lies in continuing to develop and improve not only methods
for collection and analysis, but certainly for integration into models as
well. Finally, in view of recent automated sensors and satellite
technologies, it is through studies as the ones analysed in this article that
the value of citizen contributions, complementing such technologies, is
demonstrated.