Delineation and Quantification of Wetland Depressions in the Prairie Pothole Region of North Dakota
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  • 作者:Qiusheng Wu ; Charles R. Lane
  • 关键词:Wetland hydrology ; Topographic depressions ; Water storage ; LiDAR ; Prairie Pothole Region ; Geographically isolated wetland ; Non ; adjacent wetland
  • 刊名:Wetlands
  • 出版年:2016
  • 出版时间:April 2016
  • 年:2016
  • 卷:36
  • 期:2
  • 页码:215-227
  • 全文大小:1,382 KB
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  • 作者单位:Qiusheng Wu (1) (3)
    Charles R. Lane (2)

    1. Department of Geography, State University of New York, Binghamton University, Binghamton, NY, 13902, USA
    3. CSS-Dynamac c/o U.S. Environmental Protection Agency, 26 W. Martin Luther King Dr., Cincinnati, OH, 45268, USA
    2. Office of Research and Development, U.S. Environmental Protection Agency, 26 W. Martin Luther King Dr., Cincinnati, OH, 45268, USA
  • 刊物主题:Freshwater & Marine Ecology; Environmental Management; Ecology; Hydrogeology; Coastal Sciences; Landscape Ecology;
  • 出版者:Springer Netherlands
  • ISSN:1943-6246
文摘
The Prairie Pothole Region of North America is characterized by numerous, small, wetland depressions that perform important ecological and hydrological functions. Recent studies have shown that total wetland area in the region is decreasing due to cumulative impacts related to natural and anthropogenic changes. The impact of wetland losses on landscape hydrology is an active area of research and management. Various spatially distributed hydrologic models have been developed to simulate effects of wetland depression storage on peak river flows, frequently using dated geospatial wetland inventories. We describe an innovative method for identifying wetland depressions and quantifying their nested hierarchical bathymetric/topographic structure using high-resolution light detection and ranging (LiDAR) data. This contour tree method allows identified wetland depressions to be quantified based on their dynamic filling-spilling-merging hydrological processes. In addition, wetland depression properties, such as surface area, maximum depth, mean depth, storage volume, etc., can be computed for each component of a depression as well as the compound depression. We successfully applied the proposed method to map wetland depressions in the Little Pipestem Creek watershed in North Dakota. The methods described in this study will provide more realistic and higher resolution data layers for hydrologic modeling and other studies requiring characterization of simple and complex wetland depressions, and help prioritize conservation planning efforts for wetland resources.

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