In recent years, the acquisition of data from multiple sources, together with improvements in computational capabilities, has allowed to improve our understanding on natural hazard through new approaches based on machine learning and Big Data analytics. This has given new potential to flood risk mapping, allowing the automatic extraction of flood prone areas using digital elevation model (DEM) based geomorphic approaches. Most of the proposed geomorphic approaches are conceived mainly for the identification of flood extent. In this article, the DEM‐based method based on a geomorphic descriptor—the geomorphic flood index (GFI)—has been further exploited to predict inundation depth, which is useful for quantifying flood induced damages. The new procedure is applied on a case study located in southern Italy, obtaining satisfactory performances. In particular, the inundation depths are very similar to the ones obtained by hydraulic simulations, with a root‐mean‐square error (RMSE) = 0.335 m, in the domain where 2D dynamics prevail. The reduced computational effort and the general availability of the required data make the method suitable for applications over large and data‐sparse areas, opening new horizons for flood risk assessment at national/continental/global scale.
How to cite: Manfreda, S., C. Samela, A DEM-based method for a rapid estimation of flood inundation depth, Journal of Flood Risk Management, 12 (Suppl. 1):e12541, (doi: 10.1111/jfr3.12541) 2019. [pdf]
The scour at bridge foundations caused by supercritical flows is reviewed and knowledge gaps are analyzed focusing on the flow and scour patterns, on available measuring techniques for laboratory and field, and on physical and advanced numerical modeling techniques. Evidence suggest that scour depth caused by supercritical flows is much smaller than expected, in the order of magnitude of that found in subcritical flows, although the reasons explaining this behavior remain still unclear. Important questions on the interaction of the horseshoe vortex with the detached hydraulic-jump and the wall-jet flow observed in supercritical flows arise, e.g. does the interaction between the flow structures enhance or debilitate the bed shear stresses caused by the horseshoe vortex? What is the effect of the Froude number of the incoming flow on the flow structures around the foundation and on the scour process? Recommendations are provided to develop and adapt research methods used in the subcritical flow regime for the study of the more challenging supercritical flow case.
How to cite: Link, O., E. Mignot; S. Roux; B. Camenen; C. Escauriaza; J. Chauchat; W. Brevis; S. Manfreda, Scour at Bridge Foundations in Supercritical Flows: An Analysis of Knowledge Gaps, Water (MDPI), 11(8), 1656; https://doi.org/10.3390/w11081656, 2019. [pdf]
A detailed delineation of flood-prone areas over large regions represents a challenge that cannot be easily solved with today’s resources. The main limitations lie in algorithms and hardware, but also costs, scarcity and sparsity of data and our incomplete knowledge of how inundation events occur in different riverfloodplains. We showcase the implementation of a data-driven web application for regional analyses and detailed (i.e., tens of meters) mapping of floodplains, based on (a) the synthesis of hydrogeomorphic features into a morphological descriptor and (b) its classification to delineate flood-prone areas. We analysed the skill of the descriptor and the performance of the mapping method for European rivers. The web application can be effectively used for delineating flood-prone areas, reproducing the reference flood maps with a classification skill of 88.59% for the 270 major river basins analysed across Europe and 84.23% for the 64 sub-catchments of the Po River.
How to cite: Tavares da Costa, R., S. Manfreda, V. Luzzi, C. Samela, P. Mazzoli, A. Castellarin, S. Bagli, A web application for hydrogeomorphic flood hazard mapping, Environmental Modelling and Software, Volume 118, August 2019, Pages 172-186 (doi: 10.1016/j.envsoft.2019.04.010) 2019. [pdf]
Small unmanned aerial systems (UASs) equipped with an optical camera are a cost-effective strategy for topographic surveys. These low-cost UASs can provide useful information for three-dimensional (3D) reconstruction even if they are equipped with a low-quality navigation system. To ensure the production of high-quality topographic models, careful consideration of the flight mode and proper distribution of ground control points are required. To this end, a commercial UAS was adopted to monitor a small earthen dam using different combinations of flight configurations and by adopting a variable number of ground control points (GCPs). The results highlight that optimization of both the choice and combination of flight plans can reduce the relative error of the 3D model to within two meters without the need to include GCPs. However, the use of GCPs greatly improved the quality of the topographic survey, reducing error to the order of a few centimeters. The combined use of images extracted from two flights, one with a camera mounted at nadir and the second with a 20° angle, was found to be beneficial for increasing the overall accuracy of the 3D model and especially the vertical precision.
How to cite: Manfreda, S., P. Dvorak, J. Mullerova, S. Herban, P. Vuono, J.J. Arranz Justel, M. Perks, Assessing the Accuracy of Digital Surface Models Derived from Optical Imagery Acquired with Unmanned Aerial Systems, Drones, 3(1), 15; (doi: 10.3390/drones3010015), 2019. [pdf]
The last decades have seen a massive advance in technologies for Earth Observation (EO) and environmental monitoring, which provided scientists and engineers with valuable spatial information for studying hydrologic processes. At the same time, the power of computers and newly developed algorithms have grown sharply. Such advances have extended the range of possibilities for hydrologists, who are trying to exploit these potentials the most, updating and re-inventing the way hydrologic and hydraulic analyses are carried out. A variety of research fields have progressed significantly, ranging from the evaluation of water features, to the classification of land-cover, the identification of river morphology, and the monitoring of extreme flood events. The description of flood processes may particularly benefit from the integrated use of recent algorithms and monitoring techniques. In fact, flood exposure and risk over large areas and in scarce data environments have always been challenging topics due to the limited information available on river basin hydrology, basin morphology, land cover, and the resulting model uncertainty. The ability of new tools to carry out intensive analyses over huge datasets allows us to produce flood studies over large extents and with a growing level of detail. The present Special Issue aims to describe the state-of-the-art on flood assessment, monitoring, and management using new algorithms, new measurement systems and EO data. More specifically, we collected a number of contributions dealing with: (1) the impact of climate change on floods; (2) real time flood forecasting systems; (3) applications of EO data for hazard, vulnerability, risk mapping, and post-disaster recovery phase; and (4) development of tools and platforms for assessment and validation of hazard/risk models.
How to cite: Manfreda S., C. Samela, A. Refice, V. Tramutoli, F. Nardi, Advances in Large Scale Flood Monitoring and Detection, Hydrology, 5, 49, (doi: 10.3390/hydrology5030049) 2018. [pdf]
[2018-19] Coordinatore scientifico della convenzione di ricerca intitolata “Studi idraulici sulle aste fluviali a valle delle dighe lucane”, Ufficio Difesa del Suolo Dipartimento Infrastrutture e Mobilità Regione Basilicata (Budget 39.500,00 € + IVA).  Coordinatore scientifico della convenzione di ricerca intitolata “Mappature ad alta risoluzione mediante SAPR”, Geoatlas srl (Budget 5.000,00 €+ IVA). [2015-19] Coordinatore scientifico dell’accordo di ricerca intitolato “Sistemi di allertamento per l’avvio del Centro Funzionale Decentrato della Basilicata”, Protezione Civile della Regione Basilicata (Budget totale 680.000,00 €). [2012-16] Coordinatore scientifico dell’accordo di ricerca intitolato “Implementazione e sperimentazione di sistemi di allertamento e controllo del rischio idrologico”, Protezione Civile della Regione Basilicata (Budget totale 370.000,00 €). [2011-12] Coordinatore scientifico della convenzione di ricerca intitolata “Ottimizzazione di modello idrologico per la previsione dei deflussi in arrivo ad un impianto idroelettrico”, RSE spa (Budget 20.000,00 €).
[2020-23]Coordinatore locale del progetto intitolato “La mitigazione del rischio idraulico in bacini costieri con casse di espansione in linea: approccio di dimensionamento integrato” finanziato dal Ministero dell’Ambiente e della Tutela del Territorio e del Mare sul tema progetti di ricerca finalizzati alla previsione e alla prevenzione dei rischi geologici. Coordinatore Nazionale Prof. Francesco De Paola (Budget totale 260.000,00 €).
[2019-22] Coordinatore italiano del progetto WATER JPI 2018 intitolato “An integrative information aqueduct to close the gaps between global satellite observation of water cycle and local sustainable management of water resources – iAqueduct”. Coordinatore Europeo Prof. Bob Su (Budget totale 1.247.018,00 €).
[2014-19] Componente del progetto “Technologies to stabilize soil organic carbon and farm productivity, promote waste value and climate change mitigation – CarbOnFarm” LIFE12 ENV/IT/00719 (Budget totale 3.051.265,00 €).
Collaborazioni Nazionali: CNR IMAA di Tito, CNR IRPI di Perugia, CNR ISSIA di Bari, Politecnico di Bari, Politecnico di Milano, Politecnico di Torino, Università degli Studi della Tuscia, Università degli Studi di Bologna, Università degli Studi di Palermo, Università di Genova, Università di Napoli Federico II.
Collaborazioni Internazionali: Princeton University (USA), University of California (USA), KAUST (SA), Universidad Politecnica Valencia (Spagna), University of Twente (Olanda), Universidad de Concepción (Cile), Czech Academy of Sciences (Rep. Ceca), e Ferdowsi University of Mashhad (Iran).