Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Nat. Hazards Earth Syst. Sci., 16, 1323-1337, 2016
https://doi.org/10.5194/nhess-16-1323-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
08 Jun 2016
A spatial Bayesian network model to assess the benefits of early warning for urban flood risk to people
Stefano Balbi1, Ferdinando Villa1,4, Vahid Mojtahed2,5, Karin Tessa Hegetschweiler3, and Carlo Giupponi2 1BC3, Basque Centre for Climate Change, 48940 Leioa, Spain
2Ca' Foscari University of Venice, Department of Economics and Venice Centre for Climate Studies, 30123 Venice, Italy
3Swiss Federal Institute for Forest, Snow and Landscape Research – WSL, 8903 Birmensdorf, Switzerland
4IKERBASQUE, Basque Foundation for Science, 48013 Bilbao, Spain
5Fera Science Ltd., York YO41 1LZ, UK
Abstract. This article presents a novel methodology to assess flood risk to people by integrating people's vulnerability and ability to cushion hazards through coping and adapting. The proposed approach extends traditional risk assessments beyond material damages; complements quantitative and semi-quantitative data with subjective and local knowledge, improving the use of commonly available information; and produces estimates of model uncertainty by providing probability distributions for all of its outputs. Flood risk to people is modeled using a spatially explicit Bayesian network model calibrated on expert opinion. Risk is assessed in terms of (1) likelihood of non-fatal physical injury, (2) likelihood of post-traumatic stress disorder and (3) likelihood of death. The study area covers the lower part of the Sihl valley (Switzerland) including the city of Zurich. The model is used to estimate the effect of improving an existing early warning system, taking into account the reliability, lead time and scope (i.e., coverage of people reached by the warning). Model results indicate that the potential benefits of an improved early warning in terms of avoided human impacts are particularly relevant in case of a major flood event.

Citation: Balbi, S., Villa, F., Mojtahed, V., Hegetschweiler, K. T., and Giupponi, C.: A spatial Bayesian network model to assess the benefits of early warning for urban flood risk to people, Nat. Hazards Earth Syst. Sci., 16, 1323-1337, https://doi.org/10.5194/nhess-16-1323-2016, 2016.
Publications Copernicus
Download
Short summary
This study develops a novel methodology to assess flood risk to people by integrating people’s vulnerability and ability to cushion hazards through coping and adapting. The model is used to estimate the effect of improving an existing early warning system. The proposed approach extends traditional risk assessments beyond material damages, complements quantitative and semi-quantitative data with subjective and local knowledge, and improves the use of commonly available information.
This study develops a novel methodology to assess flood risk to people by integrating people’s...
Share