RiverWatch: a citizen-science approach to river pollution monitoring

Under unprecedented pressure from urbanization and climate change, an ever increasing number of streams worldwide fails to meet good ecological status, thus threatening water quality and ecology, and severely impacting our territories. In this vein, RiverWatch aims to develop a new disruptive monitoring infrastructure for river systems focused on the transport of buoyant plastics, woody material, and floating pollution. The infrastructure will build on current knowledge in image-based hydrological monitoring to explore novel advancements in unsupervised computer vision techniques for environmental analyses. RiverWatch will exploit camera systems on fixed stations as well as volunteer smartphones to build a dense network of monitoring stations potentially along any river system in the world. This may help to overcome the current limitations in the management and maintenance of high cost installations and at the same time allow us to expand our monitoring capabilities. 

Towards establishing a robust infrastructure, RiverWatch will focus on the Sarno River to develop a dense monitoring system. Notably, the Sarno River is the most polluted river in Europe and a challenging and socially disadvantaged environment to establish monitoring networks. A custom-built mobile app as well as advanced image-based algorithms will be developed to process footage captured by citizens and fixed cameras and collected at a remote server. Image-based algorithms will enable analysis of the river flow along with the estimation of surface pollutants discharge and their characterization. Such data will be published in close to real-time on a web-Gis online platform featuring a storymap and a public database. High-frequency data at several locations in the drainage network will facilitate implementation of simple modeling tools to describe and forecast pollutant transport in the Sarno watershed.


The Partnership

 Associated InvestigatorUniversity/ Research Institution
1TAURO FlaviaUniversità degli Studi della TUSCIA
2POGGI MatteoUniversità degli Studi di BOLOGNA
3MANFREDA SalvatoreUniversità degli Studi di Napoli Federico II
4BISCARINI ChiaraUniversità per Stranieri di PERUGIA


Manfreda, S., D. Miglino, K. C. Saddi, S. Jomaa, A. Etner, M. Perks, D. Strelnikova, S. Peña-Haro, I. Maddock, F. Tauro, S. Grimaldi, Y. Zeng, G. Gonçalves, T. Bogaard, T. van Emmerik, M. Bussettini, S. Mariani, G. Marchetti, B. Lastoria, B. Su, M. Rode, Advancing river monitoring using image-based techniques: challenges and opportunitiesHydrological Sciences Journal, (https://doi.org/10.1080/02626667.2024.2333846), 2024.