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

• Published in: Journal of flood risk management 2020-01, Vol.13 (S1), p.n/a
• Main Authors: Feloni, Elissavet, Mousadis, Ioannis, Baltas, Evangelos
• Format: Article
• Language: English
• Subjects: Catchment area; Catchments; Criteria; Decision making; Disaster management; Emergency preparedness; Evaluation; flood vulnerability mapping; Flooding; Floods; flood‐prone areas; fuzzy; Geographic information systems; Geographical information systems; GIS; Heavy rainfall; Identification; Information systems; k‐means; Land cover; multi‐criteria analysis; Natural disasters; Rain; Rainfall; Spatial analysis; Standardization; Topography (geology); ungauged catchments; Urban planning; Urbanization; Vulnerability
• ISSN: 1753-318X; 1753-318X
• DOI: 10.1111/jfr3.12563

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.