Using GIS and LIDAR to Map Headwaters Stream Networks in the Piedmont Ecoregion of North Carolina

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dc.contributor.advisor James Gregory, Committee Member en_US
dc.contributor.advisor George Hess, Committee Member en_US
dc.contributor.advisor Heather Cheshire, Committee Chair en_US
dc.contributor.author Garcia, Valerie Cover en_US
dc.date.accessioned 2010-04-02T17:55:18Z
dc.date.available 2010-04-02T17:55:18Z
dc.date.issued 2005-03-03 en_US
dc.identifier.other etd-12012004-164943 en_US
dc.identifier.uri http://www.lib.ncsu.edu/resolver/1840.16/423
dc.description.abstract A large percentage of nonpoint source pollution found in our Nation's waterbodies is suspected to occur through first- and second-order (headwaters) streams. Such streams drain a much greater proportion of watershed area and have a much greater length of riparian zone interaction with the land than the higher-order streams typically studied for nonpoint source water quality problems. The State of North Carolina and the U.S. EPA are interested in examining the contribution of lowerorder streams to the overall nonpoint source pollution problem; however, the mapping of first- and second-order streams is extremely poor. The recent availability of fine resolution Light Detection and Ranging (LIDAR) data for portions of the State of North Carolina provides the opportunity for developing improved methods of mapping lower-order streams using Geographic Information System (GIS) approaches. In this study, I investigated the state-of-science for mapping topography and extracting headwaters stream networks using LIDAR data and GIS approaches. I applied these techniques to map headwaters streams at a study site in the Piedmont Ecoregion of North Carolina. I found that LIDAR produced more accurate elevation maps (elevation accuracy within 1.2') than currently available maps, such as the USGS 7.5 minute Digital Elevation Models (elevation accuracy within 49'). The Triangulated Irregular Network (TIN) produced the best topographic maps, but the Digital Elevation Model (DEM) was better for automatically extracting headwaters streams. The best headwaters stream maps were derived by using a hydro-enforced TIN for generating the base DEM,and extracting the stream network from this base DEM using ArcHydro and the AGREE algorithm. These improved headwaters stream maps will enable decision-makers to assess and mitigate nonpoint source water quality problems. en_US
dc.rights I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. en_US
dc.subject headwaters streams en_US
dc.subject GIS en_US
dc.subject LIDAR en_US
dc.subject topographic maps en_US
dc.subject stream extraction en_US
dc.subject stream maps en_US
dc.title Using GIS and LIDAR to Map Headwaters Stream Networks in the Piedmont Ecoregion of North Carolina en_US
dc.degree.name MS en_US
dc.degree.level thesis en_US
dc.degree.discipline Forestry en_US


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