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Timescale: Oct.2015 – Sept.2018
Prof. Dr. Annegret Thieken, University of Potsdam
PD Dr. Gert Zöller, University of Potsdam
Floods are responsible for the largest economic losses worldwide. In the future, climate change may contribute to an increase in flood losses in several regions due to increasing flood frequencies and magnitudes. However, ongoing settlement and economic development have already led to continuously rising assets in flood-prone areas. Human-induced changes in land use have been identified to play a key role in flood risk development.
While an increasing number of studies combines climate and land use change to assess future flood risks on the regional scale, changes in the susceptibility of exposed buildings are currently neglected in loss estimations. In most of the studies, simple loss models, such as stage-damage curves for standard buildings, were used. This is contrasted by recent reports of insurers that floods or hail storms cause tremendous losses particularly at modern buildings with a good thermal insulation and innovative building materials. While these buildings perfectly fulfil the requirements of energy saving standards that are important to mitigate climate change in the long run, it seems that such constructions tend to drive average building losses due to their high susceptibility to flooding and other impacts of natural events. On the contrary, private precautionary measures are able to reduce flood damage to great extent and are frequently implemented after having experienced a flood (e.g., Thieken et al., 2007). Therefore, this project focuses on the development of average building losses in the view of a combined mitigation of climate change and natural hazard risks.
Objectives and Methods
The PhD-project aims at explaining and quantifying changes in the susceptibility of residents and their homes to flooding due to their precautionary and preparatory behaviour. The ultimate goal is to develop more reliable flood loss estimation models that account for private mitigation measures and can hence be used to assess future flood risks and risk reduction through non-structural adaptation.
In a first step, we will analyse whether there is empirical evidence for recent changes in building susceptibility to floods, and identify and characterise highly susceptible buildings; statistical analyses will be complemented by using data mining techniques. This will be based on large data sets from computer-aided telephone interviews with private households in Germany that were affected by flooding between 2002 and 2013. Besides describing building and content losses, these data contain a wealth of information on e.g. hydraulic impacts, construction types, precautionary measures, socio-demographic data. In a second step, we identify key factors that govern homeowners’ decisions on climate and/or flood-proof building constructions and precautionary behaviour. To test their influence on mitigation behaviour, households that were affected by the flood in 2013 and have already been interviewed in spring 2014 will be interviewed again in autumn 2014 and ideally every two years thereafter to monitor risk perception and behaviour. The questionnaire will include questions on homeowners’ perceptions of climate change, natural hazards and living standard. Data analysis will greatly benefit from Bayesian analyses (Zöller et al., 2013).
Jonas Laudan is based at the research teams “Geography and Natural Risks Research” and “Applied Mathematics” of the University of Potsdam.