Citation

Loli M, Kefalas G, Dafis S, Mitoulis SA, Schmidt F. Data Brief 2023; 48: e109062.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.dib.2023.109062

PMID

37006387

PMCID

PMC10051021

Abstract

This dataset is related to the research paper entitled "Bridge-specific flood risk assessment of transport networks using GIS and remotely sensed data" published in the Science of the Total Environment. It provides the information necessary for the reproduction of the case study that was used for the demonstration and validation of the proposed risk assessment framework. The latter integrates indicators for the assessment of hydraulic hazards and bridge vulnerability with a simple and operationally flexible protocol for the interpretation of bridge damage consequences on the serviceability of the transport network and on the affected socio-economic environment. The dataset encompasses (i) inventory data for the 117 bridges of the Karditsa Prefecture, in Central Greece, which were affected by a historic flood that followed the Mediterranean Hurricane (Medicane) Ianos, in September 2020; (ii) results of the risk assessment analysis, including the geospatial distribution of hazard, vulnerability, bridge damage, and associated consequences for the area's transport network; (iii) an extensive damage inspection record, compiled shortly after the Medicane, involving a sample of 16 (out of the 117) bridges of varying characteristics and damage levels, ranging from minimal damage to complete failure, which was used as a reference for validation of the proposed framework. The dataset is complemented by photos of the inspected bridges which facilitate the understanding of the observed bridge damage patterns. This information is intended to provide insights into the response of riverine bridges to severe floods and a thorough base for comparison and validation of flood hazard and risk mapping tools, potentially useful for engineers, asset managers, network operators and stakeholders involved in decision-making for climate adaptation of the road sector.

Language: en

Keywords

Case study; Risk analysis; Floods; Field data; Network; Extreme weather; Flood adaptation