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Utilizing the National Hydrologic Data Set in a GIS Based Model to Delineate Riparian Zones: An Intelligent Approach

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Monday, October 26, 2009, 4 pm

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Ann Maclean
School of Forest Resources
and Environmental Science
Michigan Tech

The National Hydrologic Data (NHD) is a comprehensive set of digital spatial data representing the surface water of the United States using common features such as lakes, ponds, streams, rivers, canals, and oceans. These data are designed to be used in general mapping and in the analysis of surface-water systems using geographic information systems (GIS). The data is key source of information in delineating riparian zones.

Riparian zones are unique, diverse networks of vegetation and soils in close proximity to freshwater streams, rivers and lakes. These zones are linked to the watercourse network via flooding and intercepting upland runoff. Vegetation communities along stream banks often delineate riparian boundaries. However, geology, soil chemistry, and hydrologic changes need to be considered as well. Previous approaches to riparian boundary delineation utilized fixed width buffers, but this methodology has proven to be inadequate as there are two factors that all riparian zones are dependent on: the watercourse and its associated floodplain. Using a fixed width riparian buffer only takes the watercourse into consideration. Past research has determined the 50-year floodplain is the optimal hydrologic descriptor of a riparian zone. By hydrologically defining a riparian zone to occur at the 50-year flood height and incorporating digital elevation data, the spatial modeling capabilities of GIS are utilized to map riparian zones accurately and efficiently.

A GIS based model using the NHD has been developed to delineate a variable-width riparian boundary that characterizes a stream’s ecotone. This approach offers advantages over other previously used methods of riparian zone mapping by better characterizing the watercourse and its associated floodplain. The riparian zones delineated using 10 and 30 meter DEMs, along with stream course information from the National Hydrological Data, which is derived from remotely sensed imagery were found to be statistically significant (p < 0.001).

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