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

Dates

Start Date
2013-10-01
End Date
2015-06-30
Start Date
2013-10-01 05:00:00
End Date
2015-06-30 05:00:00

Citation

Zhenghong Tang(Author), Ruopu Li(Author), Xu Li(Author), Jessie Winter(Author), 2013-10-01(Start), 2015-06-30(End), Drainage Structure Datasets and Effects on LiDAR-Derived Surface Flow Modeling, http://www.mdpi.com/2220-9964/2/4/1136

Summary

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 [...]

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Purpose

The major objective of this paper is to propose a method for developing LiDAR-derived hydrologic DEMs, which includes collecting data on drainage structures (i.e., culverts and bridges), and the preprocessing and burning of the drainage structures. This method was demonstrated in a study area where surface runoff contributes to several wetlands. Based on the case study, a data model for a drainage structure dataset to be used for hydrologic burning is proposed. The hypothesis is that hydrologic burning of drainage structures such as culverts can result in differences in simulated surface water derivatives.

Additional Information

Identifiers

Type Scheme Key
info:doi/ info:doi/ 10.3390/ijgi2041136

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citationTypepublication
languageeng

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