Evidence map›Paper›PMID 35720912›Full record

ArticleComputational intelligence and neuroscience2022

The Compound Effect of Spatial and Temporal Resolutions on the Accuracy of Urban Flood Simulation.

Xiting Li, Leizhi Wang, Haolan Zhou, Yintang Wang, Kaijie Niu, Lingjie Li

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Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xiting LiTianjin University, Tianjin 300350, China.
Leizhi WangNanjing Hydraulic Research Institute, Nanjing, Jiangsu 210029, China.ORCID https://orcid.org/0000-0002-2533-7086
Haolan ZhouSouth China Agricultural University, Guangzhou, Guangdong 510642, China.
Yintang WangNanjing Hydraulic Research Institute, Nanjing, Jiangsu 210029, China.
Kaijie NiuNanjing Hydraulic Research Institute, Nanjing, Jiangsu 210029, China.
Lingjie LiNanjing Hydraulic Research Institute, Nanjing, Jiangsu 210029, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Flood disaster is one of the critical threats to cities. With the intellectualization tendency of Industry 4.0, refined urban flood models can effectively reproduce flood inundation scenarios and support the decision-making on the response to the flood. However, the spatiotemporal variability of rainfall and the spatial heterogeneity of the surface greatly increase the uncertainties in urban flood simulations. Therefore, it is crucial to account for spatiotemporal variability of rainfall events and grids of the model as accurately as possible to avoid misleading simulation results. This study aims to investigate the effect of temporal resolutions of rainfall and spatial resolutions of the model on urban flood modeling in small urban catchments and to explore a proper combination of spatiotemporal schemes. The IFMS Urban (integrated flood modeling system, urban) is used to construct a one-dimension and two-dimension coupled urban flood model in the typical inundated area in Dongguan, China. Based on five temporal resolutions of rainfall input and four spatial resolutions, the compound effect of spatiotemporal resolutions on the accuracy of urban flood simulations is systematically analyzed, and the variation characteristics are investigated. The results show that the finer the temporal resolution is, the higher the simulation accuracy of the maximum inundated water depth. Considering the spatial resolution, as the spatial grid becomes smaller, the relative error of the maximum inundated water depth decreases, but it also shows some nonlinear characteristics. Therefore, the smaller grid does not always mean a better simulation. The spatial resolution has a greater impact on the flood simulation accuracy than the temporal resolution. The simulation performance reaches the best when the grid interval is 100 m and the rainfall input interval is 5 min, 10 min, or 15 min. Affected by other factors such as terrain slope, the simulation accuracies under different spatiotemporal resolutions present complex nonlinear characteristics. The mechanisms of the compound effect of the spatiotemporal resolutions on the model simulation and the effect of underlying surface and topography on model simulation will be the focus of in-depth exploration for the future urban flood model.

Indexed as

FloodsRainCitiesModels, TheoreticalWaterWater

Identifiers

PMID35720912
PMCPMC9200525

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.