Keywords
flood early warning system, urban pluvial flooding, citizen science, smart sensing, cocreation in urban living labs
Start Date
16-9-2020 8:40 AM
End Date
16-9-2020 9:00 AM
Abstract
FloodCitiSense.eu aims at developing an early pluvial flood warning service for but also by citizens and city authorities. Despite rapid progress in forecasting, warning and management of urban pluvial floods, multiple drawbacks remain, including insufficient accuracy and resolution of rainfall estimates and forecast as well as a simulation time still too long in relation to the fast hydrological responses of urban settings. In this context, FloodCitiSense.eu takes on a high-resolution approach able to account for the complexity and heterogeneity of urban landscapes as well as for the characterization of rainfall intensity and distribution. To do so, we combine high-resolution elevation and land-cover data together with fine-resolution distributed rainfall data from both radar and station sources as well as crowdsourced and smart sensing data. Co-created, disseminated and tested together with stakeholders and citizens in an urban living lab context in each pilot city (Brussels, Rotterdam, Birmingham), web-based technologies and low-cost sensors for flood mapping and monitoring allow us to tackle the lack of a dense-monitoring network in our pilot cases. In this spirit, engagement strategies are used to keep citizen observatories up and living, while the use of more traditional radar and station data allows us to evaluate the quality and accuracy of data collected by social and smart sensing. In this contribution we focus on the problems and challenges encountered during the set-up of our low-cost rain monitoring networks, the quality of the data collected and its potential use in the real-time monitoring for an early warning service for urban pluvial floods. The FloodCitiSense.eu project is a close collaboration with TU Delft, Imperial College London, IIASA, Disdrometrics, VUB SMIT-imec, LGiU, EGEB and is funded within the ERA-NET Smart Urban Future programme of JPI Europe.
Monitoring Citizen Science Based Data, Between High-Resolution Modelling And Engagement Strategies On The Ground
FloodCitiSense.eu aims at developing an early pluvial flood warning service for but also by citizens and city authorities. Despite rapid progress in forecasting, warning and management of urban pluvial floods, multiple drawbacks remain, including insufficient accuracy and resolution of rainfall estimates and forecast as well as a simulation time still too long in relation to the fast hydrological responses of urban settings. In this context, FloodCitiSense.eu takes on a high-resolution approach able to account for the complexity and heterogeneity of urban landscapes as well as for the characterization of rainfall intensity and distribution. To do so, we combine high-resolution elevation and land-cover data together with fine-resolution distributed rainfall data from both radar and station sources as well as crowdsourced and smart sensing data. Co-created, disseminated and tested together with stakeholders and citizens in an urban living lab context in each pilot city (Brussels, Rotterdam, Birmingham), web-based technologies and low-cost sensors for flood mapping and monitoring allow us to tackle the lack of a dense-monitoring network in our pilot cases. In this spirit, engagement strategies are used to keep citizen observatories up and living, while the use of more traditional radar and station data allows us to evaluate the quality and accuracy of data collected by social and smart sensing. In this contribution we focus on the problems and challenges encountered during the set-up of our low-cost rain monitoring networks, the quality of the data collected and its potential use in the real-time monitoring for an early warning service for urban pluvial floods. The FloodCitiSense.eu project is a close collaboration with TU Delft, Imperial College London, IIASA, Disdrometrics, VUB SMIT-imec, LGiU, EGEB and is funded within the ERA-NET Smart Urban Future programme of JPI Europe.
Stream and Session
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