A systematic approach for flood-impact data retrieval in urban floods modelling

Floods are one of the main natural disasters that affect environment and ecosystems, and an increasing number of evidences highlights how climate change and urbanization are contributing to exacerbate the risk related to their occurrences. A parallel and coupled investigation of meteo-hydrological causes and of impacts on societies is therefore of primary importance for allowing a reliable analysis of flood events and improving current emergency management techniques. Within this framework, flood modelling assumes a key role in developing an accurate knowledge of rain-related impacts, especially in the urban fabric. Recent advances in flood modelling have enabled hyper-resolution street-level studies, offering significant potential for flood reconstruction, nowcasting, and forecasting. However, the calibration of flood models faces challenges due, among others, to limited availability of flood-related measurement, particularly in ungauged basins or during extreme events. While low-complexity and low-resolution inundation models may suffice to be calibrated on estimated flow discharges, space-time variability of rainfall patterns and hydrodynamic information, namely flood depths and flow velocities, become crucial for accurate simulations in urban areas. To address this issue, there is a growing need for accurate information, prompting research into alternative documentary sources concerning the impact of past floods and solutions for dataset merging. Moving from a consolidated catalogue of historical damaging hydrogeological events (ASICal), this work explores the potential of a composite meteorological and impact-based data collection for pilot case studies in Calabria region (southern Italy). Information gathered from different data sources and characterized by different levels of detail, from pixel (radar/satellite) scale up to the street level, have been systematically retrieved and organized. In our study we review and highlight (i) the abilities of weather radar in characterizing rainfall dynamics in time and space, and (ii) how photos and video posted on social media represent valuable sources for quantitative information offering insights up to the house number level, despite the limitation of the need for a visual inspection and interpretation of their contents. Results are supportive of the opportunities arising from the proposed approach in the collection of impact data from multiple sources and different levels of detail, which represents a key task for the improvement of the emergent flood related studies based on high-resolution hydrodynamics and hydrological approaches to rainfall classification and modelling.