DEM-Based Approaches for the Delineation of Flood-Prone Areas in an Ungauged Basin in Africa

Samela, Caterina; Manfreda, Salvatore; Paola, Francesco De; Giugni, Maurizio; Sole, Aurelia; Fiorentino, Mauro

doi:10.1061/(asce)he.1943-5584.0001272

Cited by 67 publications

(53 citation statements)

References 30 publications

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“…Their study confirmed that the classification using the elevation difference to the nearest stream (i.e., HAND) was reliable for delineating flood-prone areas, something also suggested in a remote sensing application of the HAND model by Westerhoff et al (2011) and later confirmed by Nobre et al (2016) and by Zheng et al (2018). Manfreda et al (2015) and Samela et al (2016Samela et al ( , 2017 further tested the ability of single and composite indices to classify flood-prone areas. The Geomorphic Flood Index (GFI, Samela et al, 2017), was found to be the best performing and the most consistent index (Manfreda et al, 2015;Samela et al, 2016Samela et al, , 2017.…”

Section: Hydrogeomorphic Flood Hazard Mapping: a Reviewsupporting

confidence: 65%

“…Manfreda et al (2015) and Samela et al (2016Samela et al ( , 2017 further tested the ability of single and composite indices to classify flood-prone areas. The Geomorphic Flood Index (GFI, Samela et al, 2017), was found to be the best performing and the most consistent index (Manfreda et al, 2015;Samela et al, 2016Samela et al, , 2017.…”

Section: Hydrogeomorphic Flood Hazard Mapping: a Reviewmentioning

confidence: 99%

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A web application for hydrogeomorphic flood hazard mapping

Costa

Manfreda

Luzzi

et al. 2019

Environmental Modelling & Software

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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 river floodplains. 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.

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Section: Hydrogeomorphic Flood Hazard Mapping: a Reviewsupporting

confidence: 65%

Section: Hydrogeomorphic Flood Hazard Mapping: a Reviewmentioning

confidence: 99%

A web application for hydrogeomorphic flood hazard mapping

Costa

Manfreda

Luzzi

et al. 2019

Environmental Modelling & Software

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“…The second step is in fact the flood hazard assessment stage, leading to results which can support decision makers regarding the selection of preventive measures. In the literature, no study exists dealing with the problem as in the way used here other than a case study performed very recently by Samela et al (2016) for delineation of flood-prone areas in ungauged basins.…”

Section: Methodsmentioning

confidence: 99%

Hydrological and hydraulic models for determination of flood-prone and flood inundation areas

et al. 2016

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Abstract. Geographic Information Systems (GIS) are widely used in most studies on water resources. Especially, when the topography and geomorphology of study area are considered, GIS can ease the work load. Detailed data should be used in this kind of studies. Because of, either the complication of the models or the requirement of highly detailed data, model outputs can be obtained fast only with a good optimization. The aim in this study, firstly, is to determine flood-prone areas in a watershed by using a hydrological model considering two wetness indexes; the topographical wetness index, and the SAGA (System for Automated Geoscientific Analyses) wetness index. The wetness indexes were obtained in the Quantum GIS (QGIS) software by using the Digital Elevation Model of the study area. Flood-prone areas are determined by considering the wetness index maps of the watershed. As the second stage of this study, a hydraulic model, HEC-RAS, was executed to determine flood inundation areas under different return period-flood events. River network cross-sections required for this study were derived from highly detailed digital elevation models by QGIS. Also river hydraulic parameters were used in the hydraulic model. Modelling technology used in this study is made of freely available open source softwares. Based on case studies performed on watersheds in Turkey, it is concluded that results of such studies can be used for taking precaution measures against life and monetary losses due to floods in urban areas particularly.

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“…Rainfall intensity, slope, flow accumulation, geology, land use, and elevation were considered. Degiorgis et al (2013) explored threshold binary classifier techniques for the Tanaro River, Italy for insurance purposes and Samela et al (2016) employed linear binary classifiers to identify flood-prone areas in Africa. Papaioannou et al (2015) studied a multicriteria perspective for delineation of potential floodprone areas for the Xerias River watershed, Greece.…”

Section: Literature Reviewmentioning

confidence: 99%

Delineation of flood-prone areas using modified topographic index for a river basin

2020

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The modified topographic index (TI m ) based on digital elevation models (DEMs) was employed to delineate floodprone areas in Mahanadi basin, India. TI m and flood inundation maps were compared to obtain the threshold (t) beyond which the area is assumed to be inundated by flood and the exponent of the TI m . Scale dependence was also investigated to evaluate the sensitiveness of spatial resolution of the DEMs. DEMs of five resolutions, namely, ASTER global, SRTM, GMTED2010 (30 arc-seconds), GMTED 2010 (15 arc-seconds), and GMTED 2010 (7.5 arc-seconds), were used and ASTER global was preferred due to its low error compared to the remainder. Flood frequency analysis was conducted to obtain the relationship between flood-prone areas and flood magnitude. It was observed that (i) the exponent in the TI m showed little variation, (ii) t is reduced with reducing spatial resolution of the DEM, and (iii) error is also reduced as the DEMs' resolution is reduced. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (CC BY 4.0), which permits copying, adaptation and redistribution, provided the original work is properly cited

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DEM-Based Approaches for the Delineation of Flood-Prone Areas in an Ungauged Basin in Africa

Cited by 67 publications

References 30 publications

A web application for hydrogeomorphic flood hazard mapping

A web application for hydrogeomorphic flood hazard mapping

Hydrological and hydraulic models for determination of flood-prone and flood inundation areas

Delineation of flood-prone areas using modified topographic index for a river basin

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