Research
My research integrates hydrology, geomorphology, remote sensing, and data-driven modeling to advance flood hazard assessment and environmental monitoring. The objective is to develop scalable, physically-based, and computationally efficient tools for understanding hydrological processes and supporting risk management.
Research Areas
Scientific Vision
The research bridges process-based hydrology and data-driven approaches, enabling reliable flood mapping even in data-scarce and ungauged basins.
Reference
In this section
Part of the HydroLAB research programme.
Publications on this topic
- Manfreda, S., J. Saavedra Navarro, C. Albertini, R. Zhuang, F. D. Pacia, S. Chaturvedi and C. Samela, Geomorphic flood index 2.0: Enhanced tools for delineating flood-prone areas in data-scarce regions., Catena, 2026. [pdf] [doi]
- Albertini, C., A. Gioia, V. Iacobellis, G. P. Petropoulos and S. Manfreda, Assessing multi-source Random Forest classification and robustness of predictor variables in flooded areas mapping., Remote Sensing Applications: Society and Environment, 2024. [pdf] [doi]
- Albertini, C., A. Gioia, V. Iacobellis and S. Manfreda, Detection of surface water and floods with multispectral satellites., Remote Sensing, 2022. [pdf] [doi]
- Samela, C., R. Coluzzi, V. Imbrenda, S. Manfreda and M. Lanfredi, Satellite flood detection integrating hydrogeomorphic and spectral indices., GIScience & Remote Sensing, 2022. [pdf] [doi]
- Albertini, C., D. Miglino, V. Iacobellis, F. De Paola and S. Manfreda, Flood-prone areas delineation in coastal regions using the Geomorphic Flood Index., Journal of Flood Risk Management, 2022. [doi]
- Tavares da Costa, R., S. Zanardo, S. Bagli, A. G. J. Hilberts, S. Manfreda, C. Samela and A. Castellarin, Predictive modelling of envelope flood extents using geomorphic and climatic-hydrologic catchment characteristics., Water Resources Research, 2020. [doi]
- Manfreda, S. and C. Samela, A DEM-based method for a rapid estimation of flood inundation depth., Journal of Flood Risk Management, 2019. [doi]
- Manfreda, S., C. Samela, A. Refice, V. Tramutoli and F. Nardi, Advances in large scale flood monitoring and detection., Hydrology, 2018. [doi]
- Samela, C., R. Albano, A. Sole and S. Manfreda, A GIS tool for cost-effective delineation of flood-prone areas., Computers, Environment and Urban Systems, 2018. [doi]
- Samela, C., T. J. Troy and S. Manfreda, Geomorphic classifiers for flood-prone areas delineation for data-scarce environments., Advances in Water Resources, 2017. [doi]
- Samela, C., S. Manfreda and T. J. Troy, 100-year geomorphic flood-prone areas for the continental U.S.., Data in Brief, 2017. [doi]
- D’Addabbo, A., A. Refice, G. Pasquariello, F. Lovergine, D. Capolongo and S. Manfreda, A Bayesian Network for Flood Detection Combining SAR Imagery and Ancillary Data., IEEE Transactions on Geoscience and Remote Sensing, 2016. [doi]
- Samela, C., S. Manfreda, F. De Paola, M. Giugni, A. Sole and M. Fiorentino, DEM-based approaches for the delineation of flood prone areas in an ungauged basin in Africa., Journal of Hydrologic Engineering, 2016. [pdf] [doi]
- Manfreda, S., C. Samela, A. Gioia, G. Consoli, V. Iacobellis, L. Giuzio, A. Cantisani and A. Sole, Flood-Prone Areas Assessment Using Linear Binary Classifiers based on flood maps obtained from 1D and 2D hydraulic models., Natural Hazards, 2015. [pdf] [doi]
- Manfreda, S., F. Nardi, C. Samela, S. Grimaldi, A. C. Taramasso, G. Roth and A. Sole, Investigation on the Use of Geomorphic Approaches for the Delineation of Flood Prone Areas., Journal of Hydrology, 2014. [doi]
- Manfreda, S. and A. Sole, Closure to Detection of Flood-Prone Areas Using Digital Elevation Models by Salvatore Manfreda, Margherita Di Leo, and Aurelia Sole., Journal of Hydrologic Engineering, 2013.
- Manfreda, S., M. Di Leo and A. Sole, Detection of Flood Prone Areas using Digital Elevation Models., Journal of Hydrologic Engineering, 2011. [doi]