Flood risk and vulnerability mapping of essential services using GIS and SMCDA : A case study of schools and healthcare services in Gävle urban area

In line with global warming, heavier and more frequent rainfall has increased, which is expected to lead to increased precipitation and more frequent rainfall in Sweden, where urban areas become particularly vulnerable. In August 2021, Gävle municipality was hit by an extreme cloudburst that led to extensive damage to, among other things, schools and infrastructure. In this study, flood-prone buildings in Gävle urban area have been analyzed, with a special focus on essential services in the form of schools and healthcare services. The analysis has been carried out through spatial multi-criteria analysis using geographic information systems and the analytic hierarchy process. The analysis in GIS was performed using twelve indicators supported by previous research and carried out in two versions with different weightings. One is based on previous research, the other on assessments from two respondents. By combining flood vulnerability, exposure, and constraint maps, two definitive pluvial flood risk maps were generated. Geographically, the area with the highest flood risk was identified in central Gävle, near Norrtull and Sätra, where hospital and healthcare centers were particularly vulnerable. The areas were characterized by flat terrain with low elevation, where the soil had low infiltration capacity. The flood-prone buildings were characterized by their proximity to waterbodies and industries and their relatively low building height. A comparison of the results from the different weightings showed variations in both the number of buildings and the area classified as flood prone. The results from the different weightings also showed differences in precision in relation to the validation data, where the literature-based weighting showed higher accuracy. The analysis also included how the result was affected by the choice of classification method, which showed variations in both the number of objects and the total area classified as flood prone. The choice of classification method also affected the visual result. Finally, the impact of different visualization methods on the communication of flood risk was investigated, where respondents’ opinions showed that different visualization methods were best suited for different purposes.