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Rivers and Streams - Generalized
The digital segmented network based on watershed boundaries, ERF1-2, includes enhancements to the U.S. Environmental Protection Agency's River Reach File 1 (RF1) (USEPA, 1996; DeWald and others, 1985) to support national and regional-scale surface water-quality modeling. Alexander and others (1999) developed ERF1, which assessed the hydrologic integrity of the digital reach traces and calculated the mean water time-of-travel in river reaches and reservoirs. ERF1-2 serves as the foundation for SPARROW (Spatially Referenced Regressions (of nutrient transport) On Watershed) modeling. Within the context of a Geographic Information System, SPARROW estimates the proportion of watersheds in the conterminous U.S. with outflow concentrations of several nutrients, including total nitrogen and total phosphorus, (Smith, R.A., Schwarz, G.E., and Alexander, R.B., 1997). This version of the network expands on ERF1 (version 1.2; Alexander et al. 1999), and includes the incremental and total drainage area derived from 1-kilometer (km) elevation data for North America. Previous estimates of the water time-of-travel were recomputed for reaches with water- quality monitoring sites that included two reaches. The mean flow and velocity estimates for these split reaches are based on previous estimation methods (Alexander et al., 1999) and are unchanged in ERF1-2. Drainage area calculations provide data used to estimate the contribution of a given nutrient to the outflow. Data estimates depend on the accuracy of node connectivity. Reaches split at water- quality or pesticide-monitoring sites indicate the source point for estimating the contribution and transport of nutrients and their loads throughout the watersheds. The ERF1-2 coverage extends the earlier ERF1 coverage by providing digital-elevation-model (DEM-based estimates of reach drainage area founded on the 1-kilometer data for North America (Verdin, 1996; Verdin and Jenson, 1996). A 1-kilometer raster grid of ERF1-2 projected to Lambert Azimuthal Equal Area, NAD 27 Datum (Snyder, 1987), was merged with the HYDRO1K flow direction data set (Verdin and Jenson, 1996) to generate a DEM-based watershed grid, ERF1_2WS. The watershed boundaries are maintained in a raster (grid cell) format as well as a vector (polygon) format for subsequent model analysis. Both the coverage, ERF1-2, and the grid, ERF1-2WS are available at: http://water.usgs.gov/lookup/gisgetlist. The version of RF1 used to compile ERF1-2 was an early edition of a USGS RF1 translation and was updated by USEPA (USEPA, 1996). The capabilities of the enhanced version of RF1 (ERF1-2) and the current USEPA version have not been evaluated. The user is referred to the USEPA version. [http://www.epa.gov/owow/monitoring/rf/rfindex] for discussions of streamflow accuracy and general background on the origin of RF1.
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E2NHDPlusV2 us: Database of Ancillary Hydrologic Attributes and Modified Routing for NHDPlus Version 2.1 Flowlines
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The National Hydrography Dataset Plus, Version 2 (NHDPlusV2) is an attribute rich, digital hydrologic network for the Conterminous U.S. developed by the U.S. Environmental Protection Agency (EPA) and U.S. Geological Survey (USGS). SPAtially Referenced Regressions On Watershed attributes (SPARROW), is a process-based/statistical model that relies on a digital hydrologic network, like NHDPlusV2, in order to establish spatial relations between monitored contaminant loads, contaminant sources, and other watershed characteristics. The USGS National Water Quality Assessment (NAWQA) project adopted the medium-resolution NHDPlusV2 network as the primary framework supporting SPARROW modeling, and has become a unifying system for reporting hydrologic information. This metadata describes enhancements made to improve the routing capabilities and ancillary hydrologic attributes of NHDPlusV2 to support modeling and other hydrologic analyses. The resulting enhanced network is named E2NHDPlusV2_us.
Region B
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To improve flood-frequency estimates at rural streams in Mississippi, annual exceedance probability (AEP) flows at gaged streams in Mississippi and regional-regression equations, used to estimate annual exceedance probability flows for ungaged streams in Mississippi, were developed by using current geospatial data, additional statistical methods, and annual peak-flow data through the 2013 water year. The regional-regression equations were derived from statistical analyses of peak-flow data, basin characteristics associated with 281 streamgages, the generalized skew from Bulletin 17B (Interagency Advisory Committee on Water Data, 1982), and a newly developed study-specific skew for select four-digit hydrologic unit code (HUC4) watersheds in Mississippi. Four flood regions were identified based on residuals from the regional-regression analyses. No analysis was conducted for streams in the Mississippi Alluvial Plain flood region because of a lack of long-term streamflow data and poorly defined basin characteristics. Flood regions containing sites with similar basin and climatic characteristics yielded better regional-regression equations with lower error percentages. The generalized least squares method was used to develop the final regression models for each flood region for annual exceedance probability flows. The peak-flow statistics were estimated by fitting a log-Pearson type III distribution to records of annual peak flows and then applying two additional statistical methods: (1) the expected moments algorithm to help describe uncertainty in annual peak flows and to better represent missing and historical record; and (2) the generalized multiple Grubbs-Beck test to screen out potentially influential low outliers and to better fit the upper end of the peak-flow distribution. Standard errors of prediction of the generalized least-squares models ranged from 28 to 46 percent. Pseudo coefficients of determination of the models ranged from 91 to 96 percent. Flood Region B, located along the eastern border of Mississippi, contained 134 streamgages with drainage areas that ranged from 0.15 to 1,750 square miles. The 1% annual exceedance probability had a standard error of prediction of 35 percent.
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