Abstract. The increasing frequency and intensity of extreme rainfall events present a critical global challenge for urban areas. While flood risk management has historically prioritised fluvial hazards, pluvial flooding and urban overland runoff pathways require local and global attention and scalable, community-inclusive solutions. This proof-of-concept paper presents the local-scale development and implementation of a prototype Citizen and Community Science mobile application, designed within a municipal extreme rainfall context, where both the app's testing environment and current operational scale are spatially limited to neighbourhood and city level in the Ahr valley. The prototype enables residents to document, classify, and report pluvial flood risks, while supporting community-based risk minimisation through enhanced awareness and embedded educational guidance on hazard categorisation and preventive actions. Crowdsourced observations are transferred to a Geo Data Warehouse, providing local authorities with customisable dashboards for analysis, visualisation, and decision support. Although technical constraints remain – particularly restricted offline functionality and variability in Global Navigation Satellite System accuracy – the system architecture was intentionally designed to support iterative refinement. Despite its present local application, the prototype is based on a fully open-source, modular, and scalable design, allowing international transferability and future expansion to regional, national, or global datasets and governance frameworks. This proof-of-concept thus demonstrates the global scaling potential of combining citizen-generated flood risk data with centralised geospatial infrastructure as a pathway toward more climate-resilient and participatory urban pluvial flood risk management worldwide.
Hoffmann et al. (Mon,) studied this question.