EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

RESCUE a new physically-based large scale flood model

Luciano Pavesi, Elena Volpi, and Aldo Fiori
Luciano Pavesi et al.
  • Roma Tre University, Engineering, Department of Civil Engineering, Rome, Italy (

Flood mapping is an essential step in flood risk assessment to reduce losses. Through flood mapping, we can detect vulnerable areas, assess flood impacts and create mitigation plans.
From the literature, we have two consolidated approaches to delineating flood maps. The first one is the hydrologic-hydraulic approach. Its strength relies on the possibility of simulating scenarios for different probabilities of occurrence (return period scenarios), considering the physics of the phenomenon. At the same time, the weaknesses of this approach regard the required amount of input data and high computational costs. The second approach is the geomorphological one, which allows to delineate flood-prone areas directly from some topographic features derived from a Digital Terrain Model (DTM), i.e. elevation, distance to the channel, etc.. Thanks to the limited request of input data and its rapidity in terms of computational efficiency, this approach is particularly appealing for large scale analyses. However, the geomorphological approach does not allow for the delineation of flood maps for different return period scenarios; further, the output is strongly linked to the quality of the input DTM.
Here we propose a model that combines the two approaches to enable preliminary mapping of flood areas for different scenarios at the regional scale; the model is named RESCUE, laRgE SCale inUndation model. RESCUE takes advantage from coupling geomorphological analysis and simplified hydrologic-hydraulic modeling, providing simple and reliable large scales inundation estimates. Like geomorphological models, it requires few data in input and has a high computational efficiency; while like hydrological-hydraulic models, it is physically-based and linked to a return period scenario.
Noteworthy, RESCUE allows for parameter uncertainty estimation through Monte-Carlo analysis, leading to a probabilistic assessment of flooded areas. Here, we show the potentialities and limitations through two examples: The Paglia-Chiani River system, and Central Apennines District (Central Italy).

How to cite: Pavesi, L., Volpi, E., and Fiori, A.: RESCUE a new physically-based large scale flood model, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1316,, 2023.