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Discussion papers
https://doi.org/10.5194/nhess-2019-272
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-272
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 30 Aug 2019

Submitted as: research article | 30 Aug 2019

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Urban pluvial flood risk assessment – data resolution and spatial scale when developing screening approaches on the micro scale

Roland Löwe and Karsten Arnbjerg-Nielsen Roland Löwe and Karsten Arnbjerg-Nielsen
  • Section of Urban Water Systems, Department of Environmental Engineering, Technical University of Denmark (DTU), Kgs. Lyngby, Denmark

Abstract. Urban development models typically provide simulated building areas in an aggregated form. When using such outputs to parametrize pluvial flood risk simulations in an urban setting, we need to identify ways to characterize imperviousness and flood exposure. We develop data-driven approaches for establishing this link, and we focus on the data resolutions and spatial scales that should be considered. We use regression models linking aggregated building areas to total imperviousness, and models that link aggregated building areas and simulated flood areas to flood damages. The data-resolutions used for training regression models are demonstrated to have a strong impact on identifiability, with too fine data resolutions preventing the identification of the link between building areas and hydrology, and too coarse resolutions leading to uncertain parameter estimates. The optimal data resolution for modelling imperviousness was identified to be 400 m in our case study, while an aggregation of the data to at least 1000 m resolution is required when modelling flood damages. In addition, regression models for flood damages are more robust when considering building data with coarser resolutions of 200 m than for finer resolutions. The results suggest that aggregated building data can be used to derive realistic estimations of flood risk in screening simulations. Future work needs to focus on training regression approaches where different degrees of flood-awareness in landuse management can be considered.

Roland Löwe and Karsten Arnbjerg-Nielsen
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Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Roland Löwe and Karsten Arnbjerg-Nielsen
Model code and software

Urban pluvial flood risk assessment - data resolution and spatial scale when developing screening approaches on the micro scale - Computer code R. Löwe https://doi.org/10.11583/DTU.8863766

Roland Löwe and Karsten Arnbjerg-Nielsen
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Latest update: 16 Nov 2019
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Short summary
To consider potential future urban developments in pluvial flood risk assessment, we develop empirical relationships for imperviousness and flood damages based on an analysis of existing urban characteristics. Results suggest that (1) data resolutions must be carefully selected; (2) there are lower limits for the spatial scale at which predictions can be generated; and (3) depth-dependent damage estimates are challenging to reproduce empirically and can be vulnerable to simulation artifacts.
To consider potential future urban developments in pluvial flood risk assessment, we develop...
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