Unstructured grid generation using LiDAR data for urban flood inundation modelling

Abstract

Abstract:Inundation disasters, caused by sudden water level rise or rapid flow, occur frequently in various parts of the world. Such catastrophes strike not only in thinly populated flood plains or farmland but also in highly populated villages or urban areas. Inundation of the populated areas causes severe damage to the economy, injury, and loss of life; therefore, a proper management scheme for the disaster has to be developed. To predict and manage such adversity, an understanding of the dynamic processes of inundation flow is necessary because risk estimation is performed based on inundation flow information. In this study, we developed a comprehensive method to conduct detailed inundation flow simulations for a populated area with quite complex topographical features using LiDAR (Light Detection and Ranging) data. Detailed geospatial information including the location and shape of each building was extracted from the LiDAR data and used for the grid generation. The developed approach can distinguish buildings from vegetation and treat them differently in the flow model. With this method, a fine unstructured grid can be generated representing the complicated urban land features precisely without exhausting labour for data preparation. The accuracy of the generated grid with different grid spacing and grid type is discussed and the optimal range of grid spacing for direct representation of urban topography is investigated. The developed method is applied to the estimation of inundation flows, which occurred in the basin of the Shin-minato River. A detailed inundation flow structure is represented by the flow model, and the flow characteristics with respect to topographic features are discussed.

An Operational Method for Flood Directive Implementation in Ungauged Urban Areas

“…One of the basic factors of input data uncertainty in flood inundation modeling and mapping, especially when 2D hydraulic hydrodynamic models are used, is the Digital Elevation Model (DEM) accuracy. The DEM estimation process involves several errors, especially in complex river and riverine areas, due to the topographical technique used [10,25,26,56]. The most common approaches followed for the river and riverine areas topography estimation and the DEM generation are ground surveying topographic approaches and photogrammetric techniques.…”

Evaluating scale and roughness effects in urban flood modelling using terrestrial LIDAR data

“…These factors will contribute to increased urban flood risk in the future, and as a result improved modelling of urban flooding has been identified as a research priority (Wheater, 2002;Gallegos et al, 2009;Tsubaki and Fujita, 2010;Fewtrell et al, 2011;Sampson et al, 2012). Surface water flood, which is one of the main sources of urban flooding after fluvial and coastal, occurs when natural and man-made drainage systems have insufficient capacity to deal with the volume of rainfall.…”

“…kerbs, road surface camber, wall, buildings) and the development of numerical schemes capable of representing high-velocity shallow flow at fine spatial resolutions over low friction surfaces in urban environments. Over the last decade, studies investigating the role of topography in urban flood models have typically employed airborne LiDAR terrain models of ∼ 50 cm-3 m horizontal resolution (Mason et al, 2007;Brown et al, 2007;Fewtrell et al, 2008;Hunter et al, 2008;Gallegos et al, 2009;Neal et al, 2009;Tsubaki and Fujita, 2010). However, small scale features which have significant impact on the flood propagation and especially surface water flooding in urban environments Fewtrell et al, 2011;Sampson et al, 2012) cannot be distinguished in airborne LiDAR data.…”

Representing hydrodynamically important blocking features in coastal or riverine lidar topography

“…Where dikes, embankments, and complex topography are narrower than a practical hydrodynamic grid, the traditional solution has been use of unstructured grids designed with cell boundaries coincident to narrow blocking features (e.g., Cobby et al, 2003;Tsubaki and Fujita, 2010). Unfortunately, unstructured grids usually require significant expertise and "hands-on" artistry to develop an acceptable balance between hydrodynamic modeling practicality and fidelity to the physical topography Mandlburger et al, 2009).…”