Use of social media crowdsourcing data for pluvial flood modelling validation to assess future climate-related impacts. The Crisi-Adapt Project
2022
Russo, Beniamino | Paindelli, Andrea | Locatelli, Luca | Yubero, Daniel | Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental | Universitat Politècnica de Catalunya. Geo2Aqua - Monitoring, modelling and geomatics for hydro-geomorphological processes
Flood models always requires calibration and validation using real data as reference. To get the access to these data is not always an easy task, both because they are not shareable information or simply not available at all. The Crowdsourced Social Data (CSD) represent all the data generated by the internet community, intended as group of single privates, in which anybody can bring its own contribution by taking/posting a photo, video or sharing a text-based information. During extreme events it is typical that people record these types of data, just as memories or to be shared across various social platforms. By looking at this material, flood modelers can obtain a huge quantity of basic and extra information which can be adopted in model design, calibration/validation and damage estimation. The state of the Art of the Crowdsourced Social Data (CSD) has been described (Zheng, et al., 2018) and its implementation investigated by different Authors, such as for model validation (Kutija, et al., 2014), post-event flood mapping (Li, et al., 2017) and for tracing past events (Macchione, et al., 2019). Considering that none of the papers listed above describe and classify open data sources available useful for urban flood modeling set up and calibration/validation, this document pretends to address this knowledge gap and to offer an example of CSD application in a real case study, presenting the approach followed during the pluvial flood assessment of the central hydrological basin of Malta in the context of the CRISI ADAPT II project.
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