Articles | Volume 379
Proc. IAHS, 379, 193–198, 2018
https://doi.org/10.5194/piahs-379-193-2018
Proc. IAHS, 379, 193–198, 2018
https://doi.org/10.5194/piahs-379-193-2018
Pre-conference publication
05 Jun 2018
Pre-conference publication | 05 Jun 2018

Estimating parameter values of a socio-hydrological flood model

Marlies Holkje Barendrecht et al.

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Cited articles

BMBF-Projekt: “Integration von historischen und hydrologisch/hydraulischen Analysen zur Verbesserung der regionalen Gefährdungsabschätzung und zur Erhöhung des Hochwasserbewusstseins”, BTU Cottbus, Cottbus, available at: http://www-docs.tu-cottbus.de/hydrologie/public/files/Schlussbericht_BMBF0330686.pdf, 2007.
Bradford, R. A., O'Sullivan, J. J., van der Craats, I. M., Krywkow, J., Rotko, P., Aaltonen, J., Bonaiuto, M., De Dominicis, S., Waylen, K., and Schelfaut, K.: Risk perception – issues for flood management in Europe, Nat. Hazards Earth Syst. Sci., 12, 2299–2309, https://doi.org/10.5194/nhess-12-2299-2012, 2012.
Bubeck, P., Botzen, W. J. W., and Aerts, J. C. J. H.: A review of risk perceptions and other factors that influence flood mitigation behavior, Risk Anal., 32, 1481–1495, 2012.
Bubeck, P., Botzen, W. J. W., Kreibich, H., and Aerts, J.: Detailed insights into the influence of flood-coping appraisals on mitigation behaviour, Global Environ. Chang., 23, 1327–1338, 2013.
Carpenter, B., Gelman, A., Hoffman, M., Lee, D., Goodrich, B., Betancourt, M., and Riddell, A.: Stan: A Probabilistic Programming Language, J. Stat. Softw., 76, 1–32, https://doi.org/10.18637/jss.v076.i01, 2017.
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The aim of this paper is to assess whether a Socio-Hydrological model can be calibrated to data artificially generated from it. This is not trivial because the model is highly nonlinear and it is not clear what amount of data would be needed for calibration. We demonstrate that, using Bayesian inference, the parameters of the model can be estimated quite accurately from relatively few data, which could be available in real case studies.