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Changes in the eustatic sea level have enhanced the impact of inundation events in the coastal zone, ranging in significance from tropical storm surges to pervasive nuisance flooding events.The increased frequency of these inundation events has stimulated the production of interactive web-map tracking tools to cope with changes in our changing coastal environment.

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As a result of decreased technological costs, low-cost low-energy networks of water level sensors leveraging the Internet of Things (Io T) are beginning to dramatically densify the flood data available in urban environments in coastal areas throughout the world [5,6].Thus, quality assurance of flood validation data near these fine-scale features can become valuable model improvement assets through the proper training of a citizen scientist network [16].Through technological progression, many effective methods for mapping inundation and flood depths have been developed using GPS, photo tagging, Augmented Reality (AR) image landmark recognition, and Quick Response (QR) codes [7,11,13].This includes occluded areas in heavily canopied flood-prone areas and built infrastructure, such as box culverts, highway overpasses, and bridges that impact proper hydrologic drainage in flooding conditions [27].A proactive and safe way to leverage these technological advances in citizen science flood monitoring methods without waiting for a major storm to elucidate inaccurate model assumptions is to map the incidence of “nuisance flooding.” This approach takes advantage of mapping inundation in places where it frequently occurs with minimal danger to the reporter, and can identify issues with modeled flood forecasts without waiting for a major tropical or extratropical storm event to identify them first [12].

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