Efficient strategies for preparing communities to protect against,respond to, recover from, and mitigateflood hazard are oftenhampered by the lack of information about the position and extentofflood-prone areas. Hydrologic and hydraulic analyses allow toobtain detailedflood hazard maps, but are a computationallyintensive exercise requiring a significant amount of input data,which are rarely available both in developing and developedcountries. As a consequence, even in data-rich environments,officialflood hazard graduations are often affected by extensivegaps. In the U.S., for instance, the detailedfloodplain delineationproduced by the Federal Emergency Management Agency (FEMA)is incomplete, with many counties having nofloodplain mappingat all. In this article we present a mapping dataset containing 100-yearflood susceptibility maps for the continental U.S. with a 90 mresolution. They have been obtained performing a linear binaryclassification based on the Geomorphic Flood Index (GFI). To thebest knowledge of the authors, there are no availableflood-proneareas maps for the entire continental U.S. with resolution lowerthat 30”30” (approximatively 1 km at the equator).
Knowing the location and the extent of the areas exposed to ﬂood hazards is essential to any strategy for minimizing the risk. Unfortunately, in ungauged basins the use of traditional ﬂoodplain mapping techniques is prevented by the lack of the extensive data required. The present work aims to overcome this limitation by deﬁning an alternative simpliﬁed procedure for a preliminary ﬂoodplain delineation based on the use of geomorphic classiﬁers. To validate the method in a data-rich environment, eleven ﬂood-related morphological descriptors derived from remotely sensed elevation data have been used as linear binary classiﬁers over the Ohio River basin and its sub-catchments. Their performances have been measured at the change of the topography and the size of the calibration area, allowing to explore the transferability of the calibrated parameters, and to deﬁne the minimum extent of the calibration area. The best performing classiﬁers among those analysed have been applied and validated across the continental U.S. The results suggest that the classiﬁer based on the Geomorphic Flood Index (GFI), is the most suitable to detect the ﬂood-prone areas in data-scarce regions and for large-scale applications, providing good accuracies with low requirements in terms of data and computational costs. This index is deﬁned as the logarithm of the ratio between the water depth in the element of the river network closest to the point under exam (estimated using a hydraulic scaling function based on contributing area) and the elevation difference between these two points.
How to cite: Caterina Samela, Tara J. Troy, Salvatore Manfreda, Geomorphic classiﬁers for ﬂood-prone areas delineation for data-scarce environments, Advances in Water Resources (doi: 10.1016/ j.advwatres.2017.01.007) 2017. [pdf]
In the present work, the flood hazard exposure in an ungauged basin in Africa is assessed exploiting the basin morphological characteristics. Flood-prone areas are identified using linear binary classifiers based on several geomorphic descriptors extracted from digital elevation models (DEMs). The classifiers are calibrated individually and evaluated by comparing their outputs with a flood inundation map obtained by two-dimensional (2D) hydraulic simulations and using receiver operating characteristics (ROC) curves as performance measures. The best-performing descriptors for the subcatchment of the Bulbula River, near the city of Addis Ababa (Ethiopia), are the elevation difference, H between the location under exam and the nearest drainage network, and the composite index ln [ hr / H ], that compares an estimate of the water level in the nearest point of the river network to the difference in elevation between the point under exam and the river. These simple procedures allow extending the flood delineation derived with the hydraulic model over the entire river basin. The study highlights the potential for the detection of flood-prone areas over ungauged basins and large areas.
How to cite: Caterina Samela, Salvatore Manfreda, Francesco De Paola, Maurizio Giugni, Aurelia Sole and Mauro Fiorentino, DEM-Based Approaches for the Delineation of Flood-Prone Areas in an Ungauged Basin in Africa, Journal of Hydraulic Engineering (doi: 10.1061/(ASCE)HE.1943-5584.0001272), 2015. [pdf]
The identiﬁcation of ﬂood-prone areas is a critical issue becoming everyday more pressing for our society. A preliminary delineation can be carried out by DEM-based procedures that rely on basin geomorphologic features. In the present paper, we investigated the dominant topographic controls for the ﬂood exposure using techniques of pattern classiﬁcation through linear binary classiﬁers based on DEM-derived morphologic features. Our ﬁndings may help the deﬁnition of new strategies for the delineation of ﬂood – prone areas with DEM-based procedures. With this aim, local features—which are generally used to describe the hydrological characteristics of a basin—and composite morphological indices are taken into account in order to identify the most signiﬁcant one.
Analyses are carried out on two different datasets: one based on ﬂood simulations obtained with a 1D hydraulic model, and the second one obtained with a 2D hydraulic model. The analyses highlight the potential of each morphological descriptor for the identiﬁcation of the extent of ﬂood-prone areas and, in particular, the ability of one geomorphologic index to represent ﬂood-inundated areas at different scales of application.
How to cite: Manfreda, S., C. Samela, A. Gioia, G. Consoli, V. Iacobellis, L. Giuzio, A. Cantisani, A. Sole, Flood-Prone Areas Assessment Using Linear Binary Classifiers based on flood maps obtained from 1D and 2D hydraulic models, Natural Hazards, 79 (2), 735-754, (doi: 10.1007/s11069-015-1869-5), 2015. [pdf]
L’individuazione delle aree inondabili è un problema cruciale che, col passare del tempo, sta diventando sempre più impattante sulla nostra società. Una delimitazione preliminare può essere effettuata mediante procedure basate sull’analisi della geomorfologia del bacino, la quale può essere ricavata da un DEM di sufficiente risoluzione. Nel presente lavoro, la mappatura delle aree inondabili viene condotta utilizzando tecniche di classificazione binaria lineare basate sui descrittori geomorfologici che hanno un ruolo di controllo sul processo di inondazione. I risultati ottenuti possono contribuire alla definizione di nuove strategie per la delimitazione di aree a rischio di inondazione con procedure basate sui DEM. A tal fine sono prese in considerazione alcune caratteristiche locali, generalmente utilizzate per descrivere le caratteristiche idrologiche del bacino, e alcuni indici morfologici compositi, allo scopo di individuare quello più significativo. Le analisi sono effettuate su due diverse serie di dati: una basata su simulazioni idrauliche realizzate con un modello 1-D, e la seconda ottenuta attraverso un modello idraulico 2-D. I risultati evidenziano il potenziale di ogni descrittore morfologico per individuare l’estensione delle aree a rischio d’inondazione e, in particolare, la capacità di un indice geomorfologico di rappresentare le aree inondabili a diverse scale di applicazione.
How to cite: Sole, A., C. Samela, A. Cantisani, L. Giuzio, S. Manfreda, Stima delle aree inondabili mediante metodi geomorfologici e modellazione idraulica mono e bi-dimensionale: applicazione al Fiume Bradano, Tecniche per la Difesa dall’Inquinamento, Editoriale Bios, 2015.
Three different geomorphic approaches to the identiﬁcation of ﬂood prone areas are investigated by means of a comparative analysis of the input parameters, the performances and the range of applicability. The selected algorithms are: the method proposed by Manfreda et al. (2011) based on a modiﬁed version of the Topographic Index (TIm); the linear binary classiﬁer proposed by Degiorgis et al. (2012), which uses different geomorphic features related to the location of the site under exam with respect to the nearest hazard source; the hydro-geomorphic method by Nardi et al. (2006) simulating inundation ﬂow depths along the river valley with the associated extent of surrounding inundated areas. Comparison has been carried out on two sub-catchments of the Tiber River in Central Italy. The simulated ﬂooded areas, obtained using the selected three methods, are evaluated using as a reference the Tiber River Basin Authority standard ﬂood maps. The aim of the research is to deepen our understanding on the potential of geomorphic algorithms and to deﬁne new strategies for prompt hydraulic risk mapping and preliminary ﬂood hazard graduation. This is of foremost importance when detailed hydrologic and hydraulic studies are not available, e.g., over large regions and for ungauged basins.
How to cite: Salvatore Manfreda, Fernando Nardi, Caterina Samela, Salvatore Grimaldi, Angela Celeste Taramasso, Giorgio Roth, Aurelia Sole, Investigation on the use of geomorphic approaches for the delineation of ﬂood prone areas, Journal of Hydrology, Pages 863 – 876 (doi: 10.1016/j.jhydrol.2014.06.009), 2014. [pdf]
The discussers address a number of interesting questions on the original paper. The writers strongly believe that this kind of discussion represents an extraordinary opportunity to exchange ideas and comments on current research, helping both writers and discussers to better address their research tasks and to explain their thoughts. For these reasons, the writers would like to thank the discussers for their critical reading of the paper, which has raised interesting points that deserve to be explained in detail. Focusing on the comments, there are four questions that have been posed by the discussers. These will be addressed in the same order presented in the discussion.
How to cite: Manfreda, S. and Sole, A. Closure to “Detection of Flood-Prone Areas Using Digital Elevation Models” by Salvatore Manfreda, Margherita Di Leo, and Aurelia Sole. Journal of Hydrologic Engineering, 18(3), 362-365, (doi: 10.1061/(ASCE)HE.1943-5584.0000693), 2013. [pdf]
r.hazard.flood is an implementation of a fast procedure to detect flood prone areas. It is based on a simple procedure that exploits the correlation between flood exposure and a Modified Topographic Index (MTI), calculated on the basis of the DTM and strongly influenced by the resolution of this latter.
Reference: Manfreda S., Di Leo M., Sole A., Detection of Flood Prone Areas using Digital Elevation Models, Journal of Hydrologic Engineering, (10.1061/(ASCE)HE.1943-5584.0000367), 2011. [pdf]
The availability of new technologies for the measurement of surface elevation has addressed the lack of high-resolution elevation data, which has led to an increase in the attraction of automated procedures based on digital elevation models (DEMs) for hydrological applications, including the delineation of floodplains. In particular, the exposure to flooding may be delineated quite well by adopting a modified topographic index (TIm) computed from a DEM. The comparison of TIm and flood inundation maps (obtained from hydraulic simulations) shows that the portion of a basin exposed to flood inundation is generally characterized by a TIm higher than a given threshold, τ (e.g., equal to 2.89 for DEMs with cell size of 20 m). This allows the development of a simple procedure for the identification of flood-prone areas that requires only two parameters for the calibration: the threshold τ and the exponent of TIm. Because the modified topographic index is sensitive to the spatial resolution of the DEM, the optimal scale of representation for the performance of the method is investigated. The procedure is tested on the Arno River Basin by using the existing documentation of flood inundations produced by the Arno River Basin Authority for calibration and validation. This approach is applied on 11 subcatchments with areas ranging from 489–6;929 km2 utilizing DEMs of different resolutions with cell sizes ranging from 20–720 m. Results show that the proposed procedure may help in the delineation of flood-prone areas, especially in basins with marked topography. The method is sensitive to the DEM resolution, but a cell size of ∼ 100 m is sufficient for good performance for the catchments investigated here. The procedure is also tested by adopting DEMs from different sources, such as the shuttle radar topography mission (SRTM) DEM, ASTER global DEM (GDEM), and national elevation data. This experiment highlights the reliability of the SRTM DEM for the delineation of flood-prone areas. A useful relationship between model parameters and the reference scale of the DEM was also obtained, providing a strategy for the application of this method in different contexts. The use of the modified topographic index should not be considered as an alternative to standard hydrological-hydraulic simulations for flood mapping, but it may represent a useful and rapid tool for a preliminary delineation of flooding areas in ungauged basins and in areas where expensive and time-consuming hydrological-hydraulic simulations are not affordable or economically convenient.
How to cite: Manfreda, S., M. Di Leo, A. Sole, Detection of Flood Prone Areas using Digital Elevation Models, Journal of Hydrologic Engineering, 16(10), 781-790 (doi: 10.1061/(ASCE)HE.1943-5584.0000367), 2011. [pdf]
L’espressione “rischio idraulico” indica il pericolo di inondazione da parte di corsi d’acqua naturali o artificiali e definisce il manifestarsi di eventi di inondazione che producono danni misurabili a persone o cose (Frescura, 2007). Il progressivo aumento di vittime e danni, causato tanto dal manifestarsi di eventi di inondazione quanto da un’antropizzazione spesso incompatibile con le dinamiche naturali del territorio, ha fatto sì che negli ultimi anni si registrasse un aumento dell’interesse, in ambito scientifico, tecnico e legislativo, attorno al problema della previsione e gestione del rischio idraulico (Plate, 2002). Le cause naturali che possono generare un’inondazione sono molteplici: un evento di pioggia con intensità tale da determinare portate in eccesso rispetto alle normali capacità di convogliamento di un fiume o di un canale di drenaggio; un accumulo di acqua su zone che hanno scarsa capacità di drenaggio e che normalmente non sono sommerse; un deflusso proveniente da aree urbane e suburbane poste a monte; le maree ed il moto ondoso. A queste cause naturali c’è da aggiungere l’effetto legato all’interferenza umana. La costruzione di strutture di controllo quali argini, traverse, dighe e sbarramenti ha cambiato le dinamiche proprie dei corsi d’acqua provocando modifiche sostanziali all’esposizione al rischio di inondazione del territorio. Eventuali collassi delle citate strutture antropiche possono provocare fenomeni di inondazione da un lato ed un ritorno dei corsi d’acqua nei propri percorsi naturali dall’altro.
How to cite: Manfreda, S., L. Giuzio, L. Giosa, B. Onorati, A. Sole, V.A. Copertino, Utilizzo di tecniche GIS per la delineazione di aree di inondazione nei tronchi incisi, alluvionati e incassati di un corso d’acqua: sviluppo di un metodo geomorfologico applicato al bacino del fiume Basento, in Catalogo di morfologie fluviali ed instabilità idrodinamiche nei corsi d’acqua di V.A. Copertino, G. Scavone, V. Telesca, Editoriale Bios, pp. 679-694, (ISBN: 978-88-6093-061-3), 2009.