This study estimates flood direct damage to businesses in Italy using 812 damage records from five riverine flood case studies. A multiple regression model predicts economic damage based on business size, water depth, and economic sectors. The results show that damage increases non-proportionally with firm size, while water depth mainly affects stock damage. Healthcare, commercial, and manufacturing sectors are most vulnerable to building, stock, and equipment damage, respectively.

INSYDE 2.0 is a tool for modelling flood damage to residential buildings. By incorporating ultra-detailed survey and desk-based data, it improves the reliability and informativeness of damage assessments while addressing input data uncertainties.

The study illustrates the methodology developed for flood risk assessment for road and railway infrastructures. Through the creation of a detailed database, using different data sources, and the definition of a risk matrix, a risk level (High, Medium, Low and Null) is assigned to each section, considering the physical and functional characteristics of the infrastructure, as well as its relevance and the magnitude of the expected event.

This paper presents a conceptual model for the estimation of flood damage to power grids and reviews the available methodologies, to better understand current modelling approaches, challenges, and limitations. The model adopts an interdisciplinary and multi-scale evaluation approach to handle the complex damage mechanisms and capture the cascading effects. In doing so, it adapts to different geographical and economic contexts, allowing stakeholders to implement comprehensive damage assessments.