A spatial Bayesian network model to assess the benefits of early warning for urban flood risk to people

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

Multi-risk assessment in mountain regions: A review of modelling approaches for climate change adaptation

“…In summary, results showed the wide range of problems these approaches are used for, but also highlighted the limited number of models applications dealing with climate impacts in mountain environments (Balbi et al, 2016(Balbi et al, , 2013Girard et al, 2015;Grêt-Regamey and Straub, 2006;Lacasse et al, 2008;Marzocchi et al, 2012). This gap is particularly clear for system dynamic models and hybrid models, highlighting potential room for further applications and methodological improvements.…”

“…However, BN cannot autonomously manage spatial evaluations, but it can be combined with GIS software to deal with the assessment of hydrogeological hazard extension and exposed mountain territorial elements. Within this context, Balbi et al (2016) described the probability of direct injury for people exposed to flooding events working with a GIS polygons approach. In the same way, Grêt-Regamey and Straub (2006) assessed mountain avalanche risk in Switzerland using a GIS cell-by-cell method.…”

“…BN can also integrate nodes representing indicators on potential elements exposed and their vulnerability from a socio-economic point of view as implemented by Balbi et al (2016) and Liu et al (2016). These cross-sectoral information contributed to a better description of vulnerability dynamics and a more accurate quantification of the impacts of natural hazard (Liu et al, 2016).…”

“…Finally, BN can be used to communicate results to experts and assist the decision-making process considering the uncertainty associated to the results (Balbi et al, 2016).…”

“…,Balbi et al (2016) andGrêt-Regamey and Straub (2006) are reported and analysed for their specific focus on mountain risk assessments Song et al (2012). considered a potential interaction of two hazards (i.e.…”