Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 24, issue 10
Articles | Volume 24, issue 10
https://doi.org/10.5194/hess-24-4777-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-4777-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 24, issue 10
Research article
 | 
05 Oct 2020
Research article |  | 05 Oct 2020

Socio-hydrological data assimilation: analyzing human–flood interactions by model–data integration

Yohei Sawada and Risa Hanazaki

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Cited articles

Barendrecht, M. H., Viglione, A., Kreibich, H., Merz, B., Vorogushyn, S., and Blöschl, G.: The Value of Empirical Data for Estimating the Parameters of a Sociohydrological Flood Risk Model, Water Resour. Res., 55, 1312–1336, https://doi.org/10.1029/2018WR024128, 2019. 
Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical weather prediction, Nature, 525, 47–55, https://doi.org/10.1038/nature14956, 2015. 
Ciullo, A., Viglione, A., Castellarin, A., Crisci, M., and Di Baldassarre, G.: Socio-hydrological modelling of flood-risk dynamics: comparing the resilience of green and technological systems, Hydrol. Sci. J., 62, 880–891, https://doi.org/10.1080/02626667.2016.1273527, 2017. 
Dang, Q. and Konar, M.: Trade Openness and Domestic Water Use, Water Resour. Res., 54, 4–18, https://doi.org/10.1002/2017WR021102, 2018. 
Di Baldassarre, G., Viglione, A., Carr, G., Kuil, L., Salinas, J. L., and Blöschl, G.: Socio-hydrology: conceptualising human-flood interactions, Hydrol. Earth Syst. Sci., 17, 3295–3303, https://doi.org/10.5194/hess-17-3295-2013, 2013. 
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Short summary
In socio-hydrology, human–water interactions are investigated. Researchers have two major methodologies in socio-hydrology, namely mathematical modeling and empirical data analysis. Here we propose a new method for bringing the synergic effect of models and data to socio-hydrology. We apply sequential data assimilation, which has been widely used in geoscience, to a flood risk model to analyze the human–flood interactions by model–data integration.
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