Using LiDAR surveys to document floods: A case study of the 2008 Iowa flood

Chen, Bo; Krajewski, Witold F.; Goska, Radosław; Young, Nathan

doi:10.1016/j.jhydrol.2017.08.009

Cited by 23 publications

(18 citation statements)

References 66 publications

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Section: Resultsmentioning

confidence: 99%

“…Therefore, we present two case studies where we show the timing of SWOT passes with respect to flood hydrographs and display relevant SWOT swaths over the study areas, illustrating how spatial coverage may be during real flood events. The two case studies are the 2008 flood of Eastern Iowa, USA (Chen et al, 2017;Smith et al, 2013), and the 2017 flood of the Houston metropolitan area, USA, caused by Hurricane Harvey (Risser & Wehner, 2017;Zhang et al, 2018). Figure 3a illustrates the inundation extent (in blue) of the Cedar and Iowa Rivers derived from highresolution imagery obtained by the SPOT satellite (Kollasch, 2009) acquired in the days following the peak flow (17 July 2008) and also the location of the United States Geological Survey (USGS) gages (red triangles).…”

Section: Geophysical Research Lettersmentioning

confidence: 99%

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Will the Surface Water and Ocean Topography (SWOT) Satellite Mission Observe Floods?

Frasson

Schumann

Kettner

et al. 2019

Geophysical Research Letters

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The Surface Water and Ocean Topography (SWOT) mission will measure water surface elevations and inundation extents of rivers of the world but with limited temporal sampling. By comparing flood location and duration of 4,664 past flood events recorded by the Dartmouth Flood Observatory to SWOT's orbit ephemeris, we estimate that SWOT would have seen 55% of these, with higher probabilities associated with more extreme events and with those that displaced more than 10,000 people. However, SWOT measurements will exhibit uneven temporal sampling and may require a combination of data obtained at different times to accurately characterize large events. This is illustrated using recent flooding in the United States, in eastern Iowa and in Houston and surrounding areas from Hurricane Harvey. SWOT data have significant potential to improve flood forecasting models by offering data needed to enhance flow routing modeling, provided that users can overcome the potential hurdles associated with its temporal and spatial sampling characteristics.

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Section: Resultsmentioning

confidence: 99%

Section: Geophysical Research Lettersmentioning

confidence: 99%

Will the Surface Water and Ocean Topography (SWOT) Satellite Mission Observe Floods?

Frasson

Schumann

Kettner

et al. 2019

Geophysical Research Letters

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“…The LiDAR-based DEM used in the present study for the HEC-RAS model encompassed the use of airborne LiDAR technology in order to be acquired. The importance of this type of data stands in the fact that it has greater potential of displaying terrain with higher horizontal and vertical accuracy, compared to many alternatives, and its use has been considered by several authors, especially in two-dimensional hydraulic-hydrodynamic modeling applications [44][45][46]. Lidar technology is not dependent on shadow conditions during data collection process, and the sensor provides high vertical accuracy, while also offering the option to extract a specific class of points for analysis, such as the points associated to the topographic surface.…”

Section: Generating the Digital Elevation Modelmentioning

confidence: 99%

Dam Breach Size Comparison for Flood Simulations. A HEC-RAS Based, GIS Approach for Drăcșani Lake, Sitna River, Romania

Albu

Enea

Iosub

et al. 2020

Water

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Floods are the most destructive natural phenomenon, by the total number of casualties, and value of property damage, compared to any other type of natural disaster. However, some of the most destructive flash floods are related to dam breaches or complete collapses, that release the large amounts of water, affecting inhabited areas. Worldwide, numerous dams have almost reached or surpassed the estimated construction life span, and pose an increasing risk to structure stability. Considering their continuous degrading state, increasing rainfall aggressiveness, due to climatic changes, technical error, or even human error, there are numerous, potential causes, for which dams could develop breaches and completely fail. This study aims to portray a comparative perspective of flood impact, with real-life consequences, measured by quantifiable parameters, generated from computer simulations of different breach sizes. These parameters include the total flooded surface, water velocity, maximum water depth, number of affected buildings, etc. The analysis was undergone by means of HEC-RAS based 2D hydraulic modeling and GIS, depending on high-accuracy Lidar terrain data and historical hydrological data. As a case study, Drăcșani Lake with the associated Sulița earthfill embankment dam was chosen, being one of the largest and oldest artificial lakes in Romania.

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“…This study uses light detection and ranging (LiDAR) data acquired from the OpenTopography facility (http://www.opentopography.org/). The point density over land (no water) was approximately 4.5 points/m 2 and over water was approximately 1–1.5 points/m 2 (Chen et al, ). In this study, the LiDAR bare ground data set was transformed to a 1‐m DEM by using inverse distance weighted (IDW) interpolation.…”

Section: Description Of the Study Areamentioning

confidence: 99%

A River Channel Extraction Method for Urban Environments Based on Terrain Transition Lines

Qin

Xü

Tian

et al. 2018

Water Resources Research

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A river channel network is an important geomorphological feature in a catchment. A method to extract river channels in urban environments from a high‐resolution digital elevation model (DEM) is introduced in this paper. The method utilizes terrain transition lines to delineate channel networks. First, terrain transition lines are extracted from the DEM. Then, shallow road ditches are removed based on elevation from the terrain transition lines, and then, noise is removed using the region growing method. Subsequently, most of the road ditches are removed by pixel block expansion, and then, the nonchannel pixels are removed by fitting a quadratic surface. The computational efficiency and accurate localization of river channel extraction using the proposed method is demonstrated using light detection and ranging (LiDAR) data for an urban environment in Johnson County, Iowa. The proposed method is effective for extracting channels and removing road ditches in this urban environment. A potential application of this method is to provide the river channels required for riverine flood modeling and geomorphological studies.

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Using LiDAR surveys to document floods: A case study of the 2008 Iowa flood

Cited by 23 publications

References 66 publications

Will the Surface Water and Ocean Topography (SWOT) Satellite Mission Observe Floods?

Will the Surface Water and Ocean Topography (SWOT) Satellite Mission Observe Floods?

Dam Breach Size Comparison for Flood Simulations. A HEC-RAS Based, GIS Approach for Drăcșani Lake, Sitna River, Romania

A River Channel Extraction Method for Urban Environments Based on Terrain Transition Lines

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