SALVATORE MANFREDA

Associate Professor

All our science, measured against reality, is primitive and childlike — and yet it is the most precious thing we have


(Albert Einstein)

Most Recent Publications

Manfreda et al. Assessing the Accuracy of Digital Surface Models Derived from Optical Imagery Acquired with Unmanned Aerial Systems, Drones, 2019. [pdf]

Manfreda et al. A Theoretically Derived Probability Distribution of Scour, Water, 2018. [pdf]

Manfreda, On the derivation of flow rating-curves in data-scarce environments, Journal of Hydrology, 2018. [pdf]

Dal Sasso et al. Exploring the optimal experimental setup for surface flow velocity measurements using PTV, Environmental Monitoring and Assessment, 2018. [pdf]

Manfreda et al. On the Use of Unmanned Aerial Systems for Environmental Monitoring, Remote Sensing, 2018. [pdf]

Manfreda et al. Exploiting the Use of Physical Information for the Calibration of a Lumped Hydrological Model, Hydrological Processes, 2018. [pdf]

Samela et al. An open source GIS software tool for cost effective delineation of flood prone areas, Computers, Environment and Urban Systems,  2018. [pdf]

Tauro et al. Measurements and Observations in the XXI century (MOXXI): innovation and multidisciplinarity to disclose the hydrological cycle, Hydrological Sciences Journal, 2018.  [pdf]

Pizarro et al. An entropy-based model for bridge-pier scour estimation under complex hydraulic scenarios, Water, 2017. [pdf]

Samela et al. Geomorphic classifiers for flood-prone areas delineation for data-scarce environments, Advances in Water Resources, 2017. [pdf]

Baldwin et al. Predicting root zone soil moisture with soil properties and satellite near-surface moisture data at locations across the United States, Journal of Hydrology, 2017. [pdf]

Manfreda et al. An Ecohydrological framework to explain shifts in vegetation organization across climatological gradients, Ecohydrology, 2017. [pdf]

Pizarro et al. Effective Flow Work for Estimation of Pier Scour under Flood Waves, Journal of Hydraulic Engineering, 2017. [pdf]

D’Addabbo et al. A Bayesian Network for Flood Detection Combining SAR Imagery and Ancillary Data, IEEE Transactions on Geoscience and Remote Sensing, 2016. [pdf]

Samela et al. DEM-based approaches for the delineation of flood prone areas in an ungauged basin in AfricaJournal of Hydrologic Engineering, 2016. [pdf]

Manfreda et al. Flood-Prone Areas Assessment Using Linear Binary Classifiers based on flood maps obtained from 1D and 2D hydraulic modelsNatural Hazards, 2015. [pdf]

Manfredaet al. Investigation on the Use of Geomorphic Approaches for the Delineation of Flood Prone Areas, Journal of Hydrology, 2014. [pdf]

Manfreda et al. A physically based approach for the estimation of root-zone soil moisture from surface measurementsHydrology and Earth System Sciences, 2014. [pdf]