In recent years, significant advancements in geomorphic methods have provided a valuable and cost-effective alternative for large-scale flood mapping. The Geomorphic Flood Index (GFI) is one such method that has gained widespread adoption for flood delineation applications. The development of the GFI plug-in for QGIS has helped to disseminate this approach, boosting its popularity. The GFI is derived from digital elevation models (DEMs), and its current formulation performs well in several hydrological contexts. However, certain limitations can affect its usability and reliability. For example, near confluences, floodwater does not always follow river connectivity patterns strictly, and secondary tributary floodplains may be partially submerged due to the backflow from the mainstream. To address these issues, a new procedure built on the GFI method (GFI 2.0) has been developed, which explicitly accounts for confluences and backwater effects. The GFI 2.0 has been tested in the Bradano River basin in southern Italy and evaluated using two-dimensional hydrodynamic simulations. In addition, a recently developed method for accounting for floodwater transfers from the main river to adjacent flat coastal areas can be implemented. This enhanced approach improves the robustness of the index and enables more reliable flood mapping, even in complex environments such as large alluvial valleys. It also increases the reliability of flood depth estimations produced using this method. 

Keywords: flood mapping, DEM-based methods, Geomorphic Flood Index (GFI), morphology, river confluences

How to cite: Manfreda, S., Saavedra Navarro, J., Albertini, C., Zhuang, R., Pacia, F. D., Chaturvedi, S., Samela, C., Geomorphic Flood Index 2.0: Enhanced Tools for Delineating Flood-Prone Areas in Data-Scarce Regions. Available at SSRN: https://ssrn.com/abstract=5461780 or http://dx.doi.org/10.2139/ssrn.5461780

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He is Full Professor of Hydrology and Hydraulic Constructions at the University of Naples Federico II. He is currently chair of the IAHS MOXXI working group. His research primarily centers on hydrological modeling and monitoring. Recognizing the challenges posed by the complexity and limitations of traditional hydrological observations, he actively explores advanced and alternative monitoring techniques, such as the utilization of Unmanned Aerial Systems (UAS) coupled with image processing.