Drainage Structure Datasets and Effects on LiDAR-Derived Surface Flow Modeling

With extraordinary resolution and accuracy, Light Detection and Ranging (LiDAR)-derived digital elevation models (DEMs) have been increasingly used for watershed analyses and modeling by hydrologists, planners and engineers. Such high-accuracy DEMs have demonstrated their effectiveness in delineating watershed and drainage patterns at fine scales in low-relief terrains. However, these high-resolution datasets are usually only available as topographic DEMs rather than hydrologic DEMs, presenting greater land roughness that can affect natural flow accumulation. Specifically, locations of drainage structures such as road culverts and bridges were simulated as barriers to the passage of drainage. This paper proposed a geospatial method for producing LiDAR-derived hydrologic DEMs, which incorporates data collection of drainage structures (i.e., culverts and bridges), data preprocessing and burning of the drainage structures into DEMs. A case study of GIS-based watershed modeling in South Central Nebraska showed improved simulated surface water derivatives after the drainage structures were burned into the LiDAR-derived topographic DEMs. The paper culminates in a proposal and discussion of establishing a national or statewide drainage structure dataset.