Research of sediment transport dynamics, a persistent topic since the early twentieth century, provides valuable insights into fluvial processes, engineering applications, and aquatic habitats. The complex and stochastic nature of stream systems provides numerous challenges to researchers and new studies can benefit from a dynamic geospatial test bed that contains tools as well as other researchers’ models to test their hypotheses. An application of sediment transport dynamics, the control of bedload sediment size on salmonid distribution, is presented here in an effort to create this test bed.
Exotic trout species encroachment is confining brook trout, the only salmonid native to the southern Appalachian headwater streams. Land managers wish to understand the controls upon the ebb and flow cycles of encroachment and retreat of invasive salmonid species. Previous region-specific studies have investigated the impact of hydrologic, biologic, and land use controls as a function of stream reach elevation on salmonid distributions. Streambed grain size availability may be an additional control on species reproductive ability since brook trout use a significantly smaller grain size than the invasive salmonids to construct redds, the streambed mounds in which salmonids deposit their eggs. Further, field data confirms that streambed grain size decreases upstream, likely due to a higher prevalence of logjams upstream that impound fine sediment, which is consistent with the brook trout's requirement for finer grains in redd construction.
This project creates a streambed grain size model to compare stream reach-averaged median grain size with surveys of native and nonnative salmonid locations obtained from previous studies. The Shields equation is used along with established hydraulic equations to model grain sizes in four Smoky Mountains streams. Watershed and stream morphometrics obtained from a digital elevation model and summer 2010 field surveys provide model inputs and validation, respectively.
Spatial median streambed grain-size distribution can be relevant in solving many problems. Channel design and engineering, pollutant transport, and paleoenvironment reconstructions are among topics that can benefit from modeling grain-size distribution throughout streams. This model is generalized such that it can be used for numerous applications.
National Park Service managers need data from the National Register of Historic Places (NRHP) to evaluate the attributes of historic sites on park grounds. NRHP data is available only in KML format which can be viewed in Google Earth or ArcGIS, but the attributes cannot be searched. This tool parses the KML and builds a corresponding file GDB feature class containing the attribute information.
The NRHP KML file contains a header followed by a series of placemark tags. Each placemark tag encloses information about a historic place. The description includes the name of the Historic Place, the geographic coordinates, and several other attributes. Each placemark tag is wrapped around a name tag, a description tag, a styleUrl tag, and a point tag. The name is repeated in the description and the styleURL encodes how the point should be drawn in Google Earth. Hence, only the description and point coordinates are needed for the feature class. The latitude and longitude within the description tag is not used because the coordinate information contained under the point tag is more precise.
A special CDATA tag within the description tag tells the KML parser to ignore any special symbols found within it, so that description can contain any needed special symbols without misleading the KML parser. The CDATA tags must be stripped away for Python to parse the description contents. This tool parses the KML file and outputs a point feature class in a file geodatabase, selectively adding the pertinent fields.