Scientific Investigations Report 2009–5015
U.S. GEOLOGICAL SURVEY
Scientific Investigations Report 2009–5015
A suite of geospatial datasets has been compiled for estimating streamflow statistics in Idaho, to support statistical modeling of perennial streams. The supporting datasets and metadata are described in detail in Rea and Skinner (2009).
The final map of estimated perennial streams consists of “synthetic” lines or vector representations of streams from the gridded model and is provided in Environmental Systems Research Institute (ESRI) shapefile format. The map and associated files and metadata are available for download at: http://water.usgs.gov/lookup/getspatial?ds412_syntheticperennialstreams
Although the synthetic streams derived from the regression models provides a consistent, connected representation of the stream network, many users need the results referenced to a commonly recognized hydrography framework, such as the NHD. Therefore, the modeled stream lines were merged with the 1:100,000-scale NHD dataset. Details of this process are beyond the scope of this report but are described in detail in Rea and Skinner (2009).
Although the full map of perennial streams in Idaho is too dense to display in this report, figure 6 shows a screen capture of the perennial streams map in the same area shown in figure 2. Most of the area shown is in region 2, and the original regression equation by Hortness (2006) was applied. The pattern of perennial streams shown is more reasonable than that derived from the NHD Hi-Res and shown in figure 2. However, HUC 17010305, in the northwest area of figures 2 and 6, is known as the Rathdrum Prairie and is an area of very porous soils with very few surface-water streams. Based on the authors’ knowledge of the area, the streams shown in figure 2 for HUC 17010305 are a better representation of the perennial streams than what is shown in figure 6. This is a good example of an area where the surface-water hydrography is dominated by local hydrogeologic effects and does not follow the general trend represented by the regression equations.