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Volume 21, issue 7 | Copyright
Hydrol. Earth Syst. Sci., 21, 3579-3595, 2017
https://doi.org/10.5194/hess-21-3579-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 14 Jul 2017

Research article | 14 Jul 2017

Delineating wetland catchments and modeling hydrologic connectivity using lidar data and aerial imagery

Qiusheng Wu1 and Charles R. Lane2 Qiusheng Wu and Charles R. Lane
  • 1Department of Geography, Binghamton University, State University of New York, Binghamton, NY 13902, USA
  • 2US Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 26 W. Martin Luther King Dr., Cincinnati, OH 45268, USA

Abstract. In traditional watershed delineation and topographic modeling, surface depressions are generally treated as spurious features and simply removed from a digital elevation model (DEM) to enforce flow continuity of water across the topographic surface to the watershed outlets. In reality, however, many depressions in the DEM are actual wetland landscape features with seasonal to permanent inundation patterning characterized by nested hierarchical structures and dynamic filling–spilling–merging surface-water hydrological processes. Differentiating and appropriately processing such ecohydrologically meaningful features remains a major technical terrain-processing challenge, particularly as high-resolution spatial data are increasingly used to support modeling and geographic analysis needs. The objectives of this study were to delineate hierarchical wetland catchments and model their hydrologic connectivity using high-resolution lidar data and aerial imagery. The graph-theory-based contour tree method was used to delineate the hierarchical wetland catchments and characterize their geometric and topological properties. Potential hydrologic connectivity between wetlands and streams were simulated using the least-cost-path algorithm. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset. The results demonstrated that our proposed framework is promising for improving overland flow simulation and hydrologic connectivity analysis.

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In this study, we developed new tools for identifying potential hydrologic connectivity between wetlands and stream networks, which can better inform regulatory decisions and enhance the ability to better manage wetlands under various planning scenarios. The resulting flow network delineated potential flow paths connecting wetland depressions to each other or to the river network on scales finer than those available through the National Hydrography Dataset.
In this study, we developed new tools for identifying potential hydrologic connectivity between...
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