Flood vulnerability assessment using a GIS‐based multi‐criteria approach—The case of Attica region

Abstract

The identification of flood-prone areas is a fundamental component of rational urban planning and proper natural disaster management policy. The aim of the present study is to introduce a framework for the identification of flood-prone areas using geographical information systems techniques and decision-making, based on a comparative evaluation for various scenarios. As a case study, the Attica region in Greece is selected, which is occasionally affected by heavy rainfall, the main cause of flooding in the region, coupled with the fact that human activities and urbanization of recent years play a significant role in flood occurrence. In this context, the development and application of a GIS-based multi-criteria analysis method for the determination of areas susceptible to flood events is initially presented. The entire spatial analysis is performed using SAGA 6.3.0 and ArcMap 10.2 Desktop, by applying a number of alternative modifications and, finally, by evaluating different scenarios regarding methods for the criteria standardization, criteria hierarchy and factors' weighting estimation. The proposed framework has an advantage among other approaches, since it takes into account mainly static data that are linked to flooding, such as the topography and land cover distribution and it can be easily customized in ungauged catchments. K E Y W O R D Sflood vulnerability mapping, flood-prone areas, fuzzy, GIS, k-means, multi-criteria analysis, ungauged catchments

Hydrometeorological - Hydrometric Station Network Design Using Multicriteria Decision Analysis and GIS Techniques

“…Therefore, this criterion requires the implementation of a process in GIS that delivers standardized values along the mainstream and upstream to the ood-prone area in a way to give the maximum value at the outer margin of the vulnerable area and a gradually decreasing one as the Euclidean distance upstream of this margin across the mainstream grows. To create this layer, the determination of the ood-prone area is required, an information retrieved from a GIS-based MCDM for ood vulnerability assessment in Attica region, carried out by Feloni et al (2020). As in this analysis various scenarios are evaluated, for the formulation of the "distance from ood-prone areas" criterion, the zones of high and very high risk that were de ned according to their best performance scenario (named "FAHP.3K") are taken into consideration.…”

GIS-Based Flood Hazard Mapping in Itang District of the Gambella Region, Ethiopia

“…According to the authors, empirical models are observation-oriented based on data and mathematical formulas. Most of the recent models mainly focused on hydrological models, hydrodynamic models, multi-criteria decision analysis (MCDA), statistical models (SM), and machine learning (ML) techniques incorporated into geographical information system (GIS) (Lee et al 2012;Elsafi 2014;Tehrany et al 2014a;Yang et al 2014;Danumah et al 2016;de Brito and Evers 2016;Rahmati et al 2016c;Rao 2017;Shafapour Tehrany et al 2017;Luu et al 2018;Feloni et al 2020). Remote sensing and GIS tools are also important and have been used extensively for hazard assessment (Islam and Sado 2000a;Fernández and Lutz 2010;Kia et al 2012;Ashley et al 2014;Tehrany et al 2014b;Barua et al 2016).…”

Integration of catastrophe and entropy theories for flood risk mapping in peninsular Malaysia

“…Numerous studies on flood vulnerability and risk mapping have been conducted in recent years (Chen et al, 2014; Dano et al, 2019; Dewan & Yamaguchi, 2008; Elsheikh, Ouerghi, & Elhag, 2015; Feloni, Mousadis, & Baltas, 2019; Jato‐Espino, Lobo, & Ascorbe‐Salcedo, 2019; Matori, Lawal, Yusof, Hashim, & Balogun, 2014; Nigussie & Altunkaynak, 2019; Pradhan & Youssef, 2011). In general, different factors can be considered in a multi‐criteria decision analysis (MCDA) system.…”