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home > reports > crwr online report 2004-07

 

The Influence of Post-Spacing Density of DEMs Derived from LIDAR on Flood Modeling

by Pierre Gueudet, B.S and David R. Maidment, PhD

ABSTRACT

The primary objective of the research is to determine the optimal post-spacing for LIDAR-derived digital elevation models (DEMs) that is required to achieve different levels of accuracy in the prediction of flood risk using hydraulic models. For the study, high spatial resolution LIDAR data were collected by the University of Texas Airborne Laser Terrain Mapping System and decimated to generate a variety of DEMs with different resolutions for test and evaluation. The data were entered as input to FEMA-approved hydraulic models at varying resolutions to determine the sensitivity of the models to the changes in the densities of the LIDAR ground elevation points. Data were collected in Brownsville, Texas, in the area of the North Main Drain. A flood model was developed using HEC-RAS to delineate the 2-year, 5-year and 25-year floodplains of this drain. For each of the floodplains, 70 simulations were run using different densities of LIDAR-derived ground elevation points. These varying datasets density were also used to delineate watersheds. The work flow sequence needed to produce the flood maps was automated using the ESRI ArcGIS 9 Model Builder. Concerning floodplain delineation, results reveal that below a certain density (5 ground points per 100m2 which corresponds to a 4.34 meter post-spacing), the LIDAR data become problematical for use in the creation of accurate flood hazard maps. At lower ground point densities, flow obstructions appear on the 3D cross-sections derived from LIDAR, and the inundation polygons expand to unrealistic proportions. With densities greater than 5 ground points per 100m2, the influence of increasing LIDAR point density is weak, and the accuracy of the floodplain resulting from a simulation depends upon the initial conditions of the model run. Concerning watershed delineation, no trend was observed as the density of LIDAR points decreases. This result could be explained by the fact that the area of study is extremely flat.


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