Urban surface water flood modelling – a comprehensive review of
current models and future challenges

Ke, Guo; Guan, Mingfu; Yu, Dapeng

doi:10.5194/hess-2020-655

Cited by 4 publications

(3 citation statements)

References 72 publications

(116 reference statements)

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“…It has received further developments to sustain its utility and speed for such applications: for instance, the ACC solver has been enabled with a subgrid channel model to integrate the flow from river channels with any width below that of the grid resolution (Neal et al, 50 2012a), and its efficiency maximised on the Central Processing Unit (CPU) with shared-memory parallelisation with an optimised treatment of wet-dry zones (Neal et al, 2018). Still, the ACC solver can be further sustained with alternative speed-up measures to enable faster and more efficient simulations across a wide range of spatial scales and grid resolutions (Guo et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

LISFLOOD-FP 8.1: New GPU accelerated solvers for faster fluvial/pluvial flood simulations

Sharifian

Kesserwani²,

Chowdhury³

et al. 2022

Preprint

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Abstract. The local inertial two-dimensional (2D) flow model on LISFLOOD-FP, so-called ACC uniform grid solver, has been widely used to support fast, computationally efficient fluvial/pluvial flood simulations. This paper describes new releases, on LISFLOOD-FP 8.1, for parallelised flood simulations on the graphical processing units (GPU) to boost efficiency of the existing parallelised ACC solver on the central processing units (CPU) and enhance it further by enabling a new non-uniform grid version. The non-uniform solver generates its grid using the multiresolution analysis (MRA) of the multiwavelets (MWs) to a Galerkin projection of the digital elevation model (DEM). This sensibly coarsens the resolutions where the local topographic details are below an error threshold ε and allows to properly adapt classes of land use. Both the grid generator and the adapted ACC solver on the non-uniform grid are implemented in a GPU new codebase, using the indexing of Z-order curves alongside a parallel tree traversal approach. The efficiency performance of the GPU parallelised uniform and non-uniform grid solvers are assessed for five case studies, where the accuracy of the latter is explored for ε = 10-4 and 10-3 in terms of how close it can reproduce the prediction of the former.

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Section: Introductionmentioning

confidence: 99%

LISFLOOD-FP 8.1: New GPU accelerated solvers for faster fluvial/pluvial flood simulations

Sharifian

Kesserwani²,

Chowdhury³

et al. 2022

Preprint

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show abstract

“…On 1 September, record rainfall caused floods in New York that largely paralyzed the city. Flooding has become a major constraint on urban public security and social and economic development (Alexander et al., 2019; Guo et al., 2021; Lee et al., 2020). Quantifying and evaluating the damage of flooded urban areas not only allows for timely mitigation measures, but also provides a basis for post‐disaster recovery and reconstruction (Kreibich et al., 2014; Merz et al., 2010; Schröter et al., 2014).…”

Section: Introductionmentioning

confidence: 99%

Optimal Domain Scale for Stochastic Urban Flood Damage Assessment Considering Triple Spatial Uncertainties

Wang

et al. 2022

Water Resources Research

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On 15 July 2021, the massive floods that occurred in many German states were seen as a national tragedy by Chancellor Angela Merkel. On 20 July, in Zhengzhou, China, a time-interval rainfall of 201.9 mm between 16:00 and 17:00 broke the global land record. Millions of people were affected and the economic loss amounted to 53.2 billion Chinese yuan. On 1 September, record rainfall caused floods in New York that largely paralyzed the city. Flooding has become a major constraint on urban public security and social and economic development (Alexander et al., 2019;Guo et al., 2021;Lee et al., 2020). Quantifying and evaluating the damage of flooded urban areas not only allows for timely mitigation measures, but also provides a basis for post-disaster recovery and reconstruction (Kreibich et al., 2014;Merz et al., 2010;Schröter et al., 2014). Accurate flood damage assessment results are also essential for the natural disaster insurance industry in post-disaster claims settlement (Diakakis et al., 2020;Wagenaar et al., 2017). Hence, scientific and reasonable flood damage quantification plays an important role in urban flood risk control and rescue decision making.The flood damage assessment process is characterized by multidimensionality, dynamic changes and uncertainties due to multiple factors such as regional rainfall characteristics, geographical conditions and socio-economic levels (Gall, 2017;Schoppa et al., 2020). It is a widely used flood damage assessment method to achieve damage results by combining flood damage ratios with inundation depth, land use and economic factors (Chen et al., 2019;Jongman et al., 2012;Scorzini & Frank, 2017). The damage ratio serves as the link between flood inundation

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“…Numerical models have been developed (Mignot et al 2019) to model the predicted amount of floodwater accumulated during flood events that considers the specific features of the urban environment. These models depend on the quality and accuracy of topographic data to provide a comprehensive representation of ground topography (Guo et al 2020;Xing et al 2021). Discrepancies in the resulting flood depth and extent can be observed when the digital elevation model (DEM) resolutions are increased in the grid size (Muthusamy et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Urban Flood Simulations with Modified Digital Elevation Model

Dasallas

Lee

2022

Preprint

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The acquisition of high-resolution digital elevation model (DEM) data is an on-going challenge in urban flood modeling, especially for larger domains. The accuracy of flood simulations is significantly dependent on the precision of DEM data. To address this issue, we propose a method of modifying mid-resolution DEM data to provide a realistic ground elevation for urban flood modeling using geographic information system (GIS) tools. The modified DEM contains the properties of the existing digital terrain and digital surface model (DTM and DSM) data. Flood calculations were performed using 2D shallow water and kinematic equations in the integrated multiscale simulation scheme developed in recent literature and tested for an extreme flood event in an urbanized area in the Philippines. The results show that the underestimated and overestimated flood tendencies for DTM and DSM, respectively, were adequately resolved in MDEM simulations, which were able to accurately capture the flood propagation along the natural and artificial barriers in the urban area, as compared to untreated DTM and DSM data, with root mean square error (RMSE) improvements from RMSEDTM = 30.64 and RMSEDSM = 17.28 to RMSEMDEM = 0.17. The proposed method significantly improved the accuracy of the simulations. It would allow high-resolution urban flood modeling with limited detailed elevation data, which is crucial to propose adequate flood action plans specifically for developing countries experiencing frequent rainfall events.

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Urban surface water flood modelling – a comprehensive review of current models and future challenges

Cited by 4 publications

References 72 publications

LISFLOOD-FP 8.1: New GPU accelerated solvers for faster fluvial/pluvial flood simulations

LISFLOOD-FP 8.1: New GPU accelerated solvers for faster fluvial/pluvial flood simulations

Optimal Domain Scale for Stochastic Urban Flood Damage Assessment Considering Triple Spatial Uncertainties

Urban Flood Simulations with Modified Digital Elevation Model

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