Wildfires are an escalating global threat, particularly during summer periods, jeopardizing ecosystems and human activities, with evident consequences across multiple regions worldwide. Forest wildfires, in particular, demand urgent attention due to their profound impact on environmental and socioeconomic systems. The study of forest wildfires is crucial for understanding and mitigating their adverse effects, but such combined fire-impacts phenomena are complex and challenging to study.

The consequences of forest wildfires include altered hydrological processes, which increase the risk of flash floods in downstream areas during extreme storm events. In this study, we address this often-overlooked issue by simulating a real flash-flood event that occurred after a forest wildfire in a Greek case study. We assess the flood inundation of an extreme storm that took place after the wildfire, and estimate the associated direct economic damages.

We employ a combination of multiple methods and tools, including: a) the atmospheric model WRF-ARW to represent the real storm; b) remote sensing techniques to assess the burn extent and severity, in order to mode the different catchment properties in pre-fire and post-fire conditions, as well as the flood extent; c) the 2D HEC-RAS hydraulic-hydrodynamic model to simulate the flood extent and water depth; and d) a coupled semi-automated AI-based approach alongside an economic routine to estimate the flood’s damages in terms of affected properties and road closures.

The results indicate that the impact of forest wildfires can significantly influence flood response and risk in downstream areas. The direct economic damages are substantial, affecting multiple sectors and infrastructure systems.

It is crucial to better understand the influence of forest wildfires on flooding dynamics and develop portfolios of proactive measures to address these increasing risks.