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3. Layers (Viewable Mapped Data)

Last updated on 2023-07-26

Model My Watershed provides a number of geospatial data layers for visualization, analysis, and modeling. Detailed information and data sources for each layer are provided below, organized by type, in the order in which they appear in the Layer selector in the lower left of the map.

Layers that are not available for visualization, but are used for analysis and modeling functions, are described in the Additional Data Layers section.

3.1 Streams

3.1.1 Continental US Medium Resolution Stream Network

From NHDplusV2 Medium Resolution (1:100,000-scale) NHDFlowlines (similar to this dataset or The National Hydrography Dataset (NHD), Medium Resolution Flowlines, DRECP)

Blue lines are rendered with styling that depends on user zoom extent and on the stream order.

  • Larger streams are attributed with thicker blue lines.
  • Small streams appear/disappear as the user zooms in and out of the map area.

3.1.2 Continental US High Resolution Stream Network

The NHD high resolution Flowline vector dataset (nominally at 1:24,000-scale) was sourced from the USGS and can be downloaded here.

The NHDPlus HR is a geospatial dataset depicting the flow of water across the Nation’s landscapes and through the stream network. The NHDPlus HR is built using the National Hydrography Dataset High Resolution data at 1:24,000 scale or more detailed.

3.1.2 Delaware River Basin High Resolution Stream Network

The Delaware River Basin High resolution stream network was derived from the 1/3 arc second (10 m) resolution digital elevation model (DEM) from the USGS national elevation dataset obtained from the National Map using FTP download options for the domain covering the Delaware River Basin.

This work was done by Model My Watershed partners at Utah State University, David Tarboton and Nazmus Sazib, using Terrain Analysis using Digital Elevation Models (TauDEM) software. Tarboton is the lead developer of the TauDEM software.

The processing steps used were:

  • Define the Delaware River Basin Terrain Analysis domain. The parts of the DEM that occupied ocean or estuary area identified from National Hydrography Dataset and other data sources were masked out in this DEM, setting a no data value for grid cells more than 100 m from the shore and -50 m for grid cells within 100 m of the coast. This ensured that grid cells adjacent to the shore drained into the ocean/estuary, while at the same time avoiding unnecessary terrain analysis for ocean/estuary areas. The DEM was then clipped to the Delaware River Basin watershed boundary from NHDPlus, with a 5 km buffer around the edges to avoid edge effects where the watershed boundary and DEM are inconsistent.
  • Pitremove. The TauDEM pitremove function was used to hydrologically condition the DEM. This raised the level of any grid cells completely surrounded by higher terrain to the level of the lowest pour point around their edge so that there is a path of non increasing elevation from each grid cell to the domain edge along which water could drain.
  • D8 flow directions. The TauDEM D8 flow direction function was used to compute the single flow direction associated with each grid cell to one of its eight adjacent neighbors.
  • D8 Contributing area. The TauDEM D8 Contributing area function was used to calculate the number of grid cells draining through each grid cell counting itself.
  • Determine outlets to the ocean/estuary. Outlet points where contributing area is greater than 5000 grid cells (Approx 0.5 km2) and the flow leaves the domain were determined as the downstream ends of a temporary stream network mapped using TauDEM with 5000 grid cell contributing area threshold. These outlet points were used in calculations below to constrain the work to areas upstream of these outlets. It was deemed not meaningful to delineate a stream network for areas less than 0.5 km2 draining directly to the ocean.
  • Peuker Douglas valley filter. The TauDEM Peuker Douglas filter was used to identify valley grid cells. This filter selects all grid cells, examines each set of 2 x 2 grid cells, and unselects the highest elevation cell. Cells remaining selected at the end are “potential valley cells.”
  • Weighted D8 Contributing area. The TauDEM D8 contributing area function was used with the Peuker Douglas valley filter result as a weighted input. This calculates the number of potential valley grid cells draining through each grid cell.
  • Define stream grid. The TauDEM threshold function was used to define as candidate stream grids the grid cells in the Weighted D8 contributing area result exceeding input contributing area thresholds. Contributing area thresholds of 20, 50, and 100 grid cells were evaluated. After visual inspection, in comparison to contour crenulations and high resolution NHD streams a threshold of 50 grid cells was chosen.
  • Calculate stream network. The TauDEM Stream Network function was used to delineate a stream network of lines (GIS vector shapes) from the 50 cell threshold stream grid. The result is a geographic feature set (set of lines) in GIS shapefile format.

Note that this procedure, and in particular the use of the Peuker Douglas valley filter and weighted contributing area functions results in a stream network that adapts to the complexity of the topography.

Where the topography is complex, as would be reflected by a high degree of crenulation in contours, the drainage density of the resulting stream network is high and reflects this. Where the topography is less complex (smooth contours) the drainage density is low.

The basis for this is that the mapping of valley grid cells produces a skeletonized (disconnected) stream map that reflects the variability of drainage density across the topography. These valley grid cells were then formed into a connected stream network by using them as input to a weighted contributing area calculation that counted only these grid cells.

For additional detail on the rationale for this approach refer to the following references (full citations in References section): Tarboton & Ames (2001); Tarboton et al. (1992); Tarboton et al. (1991).

For additional detail on the TauDEM software and use of each function refer to TauDEM documentation. The TauDEM software is open source and may be obtained from the following websites:

3.1.3 Delaware River Basin T(X) Concentration(s) from SRAT

Estimated in-stream baseflow concentrations of Total Nitrogen (TN), Total Phosphorus (TP) or Total Suspended Solids (TSS), derived within the Delaware River Basin from the Stream Reach Assessment Tool (SRAT) modeling effort. SRAT-estimated in-stream concentrations are shown in Model My Watershed by color-coding the NHDplusV2 stream network in colors ranging from green to yellow to orange to red, with greens indicating the lowest concentrations and reds indicating the highest.

The SRAT modeling effort was funded by the William Penn Foundation Delaware River Watershed Initiative (DRWI). SRAT is derived from calibrated MapShed model runs of all HUC-12 areas within the Delaware River Basin, downscaling MapShed results to NHDplusV2 catchment scales and routing loads through the NHDplusV2 medium resolution stream network. For more details regarding SRAT, see the SRAT overview. The Stream Reach Assessment Tool is brought to you through the collaborative work of many DRWI partners.

Many additional SRAT-derived model output data layers can be visualized and analyzed in Model My Watershed, including the visualization of pollutant loading rates and stream concentrations at the NHD catchment and stream segment level. See below for more details.

3.2 Coverage Grids

3.2.1 Land: USGS National Land Cover Database

Land coverage grids are visualized based on the United States Geological Survey National Land Cover Database (NLCD). In January of 2022, Model My Watershed Release 1.33.0 included updates to the 2019 NLCD release.

3.2.2 Soil: Hydrologic Soil Groups from gSSURGO

Gridded Soil Survey Geographic (gSSURGO) 2016. Database for the Conterminous United States. United States Department of Agriculture (USDA), Natural Resources Conservation Service (NRCS). Data can be from the USDA here.

For more information and official gSSURGO User Guide, see Description of Gridded Soil Survey Geographic (gSSURGO) Database.

Hydrologic Soil Groups is one gSSURGO soil category, based on water infiltration rates during wet, saturated conditions. Low infiltration rate soils translate to high runoff potential. For more information, see National Engineering Handbook, Part 630 Hydrology, Chapter 7 Hydrologic Soil Groups.

3.2.3 Elevation and Slope (Percent)

Elevation and Slope coverage grids are visualized based on the National Hydrography Dataset (NHD) plus National Elevation Data Snapshop Digital Elevation Model (NHDPlus V@ NED Snapshot DEM), which are publicly available from the USGS.

3.2.4 Climate: Mean Monthly Precipitation and Temperature

Gridded mean monthly values for precipitation and temperature were obtained from the PRISM Climate Group and are the AN81m datasets. Briefly, these layers were created from a modelling effort (Climatologically-Aided Interpolation process) that utilized nationally available records for the time period 1981-2010. See documentation.

3.2.5 Protected Lands

The Protected Lands data layer in Model My Watershed was sourced from the National Inventory of Protected Areas assembled and published by the U.S. Geological Survey Gap Analysis Program in 2016 (Gergely and McKerro, 2016). The Protected Areas Database of the United States (PADUS) is the official inventory of public parks and other protected open space.

Additional resources for the Protected Areas Database of the U.S.

Gergely, K.J., and McKerrow, A., 2016, PAD-US—National inventory of protected areas (ver. 1.1, August 2016): U.S. Geological Survey Fact Sheet 2013–3086, 2 p..

Reclassification of the PADUS 

Table 1. Reclassifications

Reclassifications
Agricultural Easement
Conservation Easement
Natural Resource Area – Local
Natural Resource Area – Federal
Natural Resource Area – State
Natural Resource Area – Unknown
Park or Recreation Area – Federal
Park or Recreation Area – Local
Park or Recreation Area – Private
Park or Recreation Area – State
Park or Recreation Area – Unknown
Natural Resource Area – Private

The Protected Areas Database (PAD) for the US was downloaded via the USGS download site (link provided above). A list of 60 unique descriptions of the designated use types (d_Des_Tp) was compiled from the column in the raw PAD source dataset. From this list, a set of reclassified categories was determined that could describe each one at a more general level (Table 1). Some designated protected areas were removed if they did not fit a reclassification type. The list of unique designated types had each description assigned one of the 12 different reclassifications (Table 2).

These reclassified values were then converted to a list of integer values. This is often done with categorical data stored in a raster format to decrease the overall file size. Once the original PAD shapefile had the reclassifications and raster identification classifiers added, it was converted to a GEOTIFF raster. To do this the National Land Cover Dataset (NLCD) 2011 was used to define the final processing extent, the snap raster, and the cell size. The result is a PAD raster that perfectly overlaps the NLCD raster for the coterminous US.

Table 2. Designated type reclassification

d Des TpReclassification
Agricultural EasementAgricultural Easement
Ranch EasementAgricultural Easement
Private AgriculturalAgricultural Easement
Conservation EasementConservation Easement
Forest Stewardship EasementConservation Easement
Other EasementConservation Easement
Recreation or Education EasementConservation Easement
Unknown EasementConservation Easement
Local Other or UnknownNatural Resource Area – Local
Historic or Cultural EasementRemove
National ForestNatural Resource Area – Federal
National GrasslandNatural Resource Area – Federal
National Lakeshore or SeashoreNatural Resource Area – Federal
National Public LandsNatural Resource Area – Federal
National Wildlife RefugeNatural Resource Area – Federal
Wilderness AreaNatural Resource Area – Federal
Wilderness Study AreaNatural Resource Area – Federal
Conservation AreaNatural Resource Area – Federal
Federal Other or UnknownNatural Resource Area – Federal
Inventoried Roadless AreaNatural Resource Area – Federal
Local Conservation AreaNatural Resource Area – Local
State Resource Management AreaNatural Resource Area – State
State WildernessNatural Resource Area – State
State Conservation AreaNatural Resource Area – State
Research Natural AreaNatural Resource Area – Unknown
Resource Management AreaNatural Resource Area – Unknown
National Monument or LandmarkPark or Recreation Area – Federal
National ParkPark or Recreation Area – Federal
National Recreation AreaPark or Recreation Area – Federal
National Scenic, Botanical or Volcanic AreaPark or Recreation Area – Federal
Local ParkPark or Recreation Area – Local
Local Recreation AreaPark or Recreation Area – Local
Private Recreation or EducationPark or Recreation Area – Private
State ParkPark or Recreation Area – State
State Recreation AreaPark or Recreation Area – State
Recreation Management AreaPark or Recreation Area – Unknown
Research or Educational AreaPark or Recreation Area – Unknown
Special Designation AreaPark or Recreation Area – Unknown
Private ConservationNatural Resource Area – Private
Private Forest StewardshipNatural Resource Area – Private
Private Other or UnknownNatural Resource Area – Private
State Other or UnknownNatural Resource Area – State
Not DesignatedRemove

The source PAD dataset often had an underlying issue of overlapping polygons. An output raster of this data can only store one value for a given area. Thus, if there were two overlapping polygons with different protection descriptions only one of them will be represented in the final raster output created.

Table 3. Lookup table for reclassification values

Reclassified DescriptionColorRaster Value
Park or Recreation Area – FederalGreen/Yellow 11
Park or Recreation Area – StateGreen/Yellow 22
Park or Recreation Area – LocalGreen/Yellow 33
Park or Recreation Area – PrivateGreen/Yellow 44
Park or Recreation Area – UnknownGreen/Yellow 55
Natural Resource Area – FederalGreen Dark 16
Natural Resource Area – StateGreen Dark 27
Natural Resource Area – LocalGreen Dark 38
Natural Resource Area – PrivateGreen Dark 49
Natural Resource Area – UnknownGreen Dark 510
Conservation EasementBrown/Green11
Agricultural EasementBrown 112

3.2.6 Active River Area – Northeast and Mid-Atlantic

The “Active River Area” data layer was developed to provide a conservation framework for assessment, protection, management, and restoration of freshwater and riparian ecosystems. The framework identifies five key sub-components of the active river area: 1) material contribution zones, 2) meander belts, 3) riparian wetlands, 4) floodplains and 5) terraces. These areas are defined by the major physical and ecological processes associated and explained in the context of the continuum from the upper, mid and lower watershed in the ARA framework paper (Smith et al. 2008).  More details

Smith, M.P, R. Schiff, A. Olivero, and J. MacBroom. 2008. The Active River Area: A conservation framework for protecting rivers and streams. The Nature Conservancy. Boston, MA.

3.2.7 Future DRB Urban Land Forecasts (“DRB 2011 Urban Baseline”, “DRB 2100 Centers FX”, “2100 Corridors FX”)

These Delaware River Basin (DRB)-specific data layers were created by Dr. C. Jantz et al. at the Center for Land Use and Sustainability at Shippensburg University. These layers, collectively called DRB2100 Version 3.1 – Alternative Land Cover Scenarios, represent a revised baseline and future growth forecasts (“corridors” and “centers”) for changes (increases or decreases in extent) to “developed land use” in the Delaware River Basin, out to 2100. To develop these forecasts, SLEUTH urban growth model was calibrated for modeling sub-regions over the 2001-2006 time period, and validated for the 2006-2011 time period. The National Land Cover Database (NLCD) urban classes were used to represent urban land cover as developed or not developed for the baseline 2011 layer. Learn more about this project, click here.

Fast-Zonal Statistics API delivers Future (2100) DRB Urban Land Forecasts

The Drexel University College of Computing and Informatics (CCI) and the Academy of Natural Sciences (ANS) of Drexel University developed the fast-zonal statistics (FZS) Application Programming Interface (API) which returns numerical attributes (mean, sum, and count) for a submitted polygon query region over any regular grid or raster dataset. Common applications of this technology include determining the amount of precipitation or impervious surfaces in a watershed. The API was built using a GeoDjango Web framework, Nginx, Docker, PostGIS, and a novel FZS algorithm produced by the members of this organization (Haag et al. 2020). This algorithm is labeled “fast” because to determine the zonal sum for a polygon over a raster surface, only the cells which intersect the boundary of the polygon must be traversed rather than all the interior cells. This means that computationally the approach scales much better with increased data resolution as the FZS algorithm is constant in relation to the length (meters) of the polygon perimeter rather than its area (meters square). View additional information on how to interact with the API.

  • Haag, S., Tarboton, D., Smith, M. & Shokoufandeh, A. (2020). Fast summarizing algorithm for polygonal statistics over a regular grid. Computers & Geosciences. 10.1016/j.cageo.2020.104524.

3.2.8 Pennsylvania Urbanized Areas

US EPA Urbanized Area boundaries, developed by the USEPA to support a number of analytical needs. In Pennsylvania, these boundaries are used to identify areas within which various municipal entities have a responsibility for reducing pollutant loads (primarily sediment, nitrogen and phosphorus).

Urbanized Area Maps for NPDES MS4 Phase II Stormwater Permits 2010 Urbanized Areas (Newest Maps)

3.2.9 DRB Catchment Water Quality Data, T(X) Annual Loading Rates from SRAT Catchments

Estimated average-catchment loading rates for Total Nitrogen (TN), Total Phosphorus (TP), or Total Suspended Solids (TSS), derived within the Delaware River Basin from the Stream Reach Assessment Tool (SRAT) modeling effort. SRAT-estimated loading rates are shown in MMW by shading the NHDplusV2 catchments areas, where darker shades indicate higher mean annual loading rates in mass per unit area (e.g., lbs/acre or kg/ha).

The Stream Reach Assessment Tool (SRAT) modeling effort was funded by the William Penn Foundation (WPF) Delaware River Watershed Initiative (DRWI). SRAT is derived from calibrated MapShed model runs of all HUC-12 areas within the Delaware River Basin, downscaling MapShed results to NHDplusV2 catchment scales and routing loads through the NHDplusV2 medium resolution stream network. More details regarding SRAT

Many additional SRAT-derived model output data layers can be visualized and analyzed in Model My Watershed, including the visualization of pollutant loading rates and stream concentrations at the NHD catchment and stream segment level. See below for more details.

3.3 Boundaries

3.3.1 USGS Subbasin unit (HUC-8)

US Geological Survey Hydrologic Units of the eight-digit level (Hydrologic Unit Code 8), averaging 700 square miles (1,813 square kilometers). Although USGS names the HUC-8 level as “subbasin” scale, these hydrological units are not equivalent to true hydrographic basins or watersheds, because the main river/stream within a given HUC-8 area can often have contributions from additional, upstream HUC-8 areas.

More info: Hydrological code
Data source: NHDplusV2

3.3.2 USGS Watershed Unit (HUC-10)

US Geological Survey Hydrologic Units of the ten-digit level (Hydrologic Unit Code 10), averaging 227 square miles (588 square kilometers). Although USGS names the HUC-10 level as “watershed” scale, these hydrological units are not equivalent to true hydrographic basins or watersheds, because the main river/stream within a given HUC-10 area can often have contributions from additional, upstream HUC-10 areas.

More info: Hydrological code
Data source: NHDplusV2

3.3.3 USGS Subwatershed Unit (HUC-12)

US Geological Survey Hydrologic Units of the twelve-digit level (Hydrologic Unit Code 12), averaging 40 square miles (104 square kilometers). Although USGS names the HUC-12 level as “subwatershed” scale, these hydrological units are not equivalent to true hydrographic basins or watersheds, because the main river/stream within a given HUC-12 area can often have contributions from additional, upstream HUC-12 areas.

More info: Hydrological code
Data source: NHDplusV2

3.3.4 County Lines

County lines for each state in the continental United States.

More info: County (United States)
Data source: TIGER/Line Shapefile, 2015, nation, U.S., Current County and Equivalent National Shapefile

3.3.5 Congressional Districts

Congressional Districts for the United States House of Representatives for the 113th Congress: 1/3/2013-1/3/2015.

More info: List of United States congressional districts
Data source: https://www.census.gov/geo/maps-data/data/cbf/cbf_cds.html#cd113

3.3.6 School Districts

School District boundaries in the  continental United States.

More information: School district
Data source: School District Boundaries

3.3.7 Pennsylvania Municipalities

Sub-county municipal boundaries for the State of Pennsylvania were developed by various state agencies. Pennsylvania municipality boundaries

3.4 Observations

3.4.1 Weather Stations (214)

A database of national-scale daily weather data (temperature and precipitation) was previously compiled by USEPA for use in various environmental simulation models. In the case of MMW, these data are used to estimate daily weather data (i.e., precipitation and temperature; compiled for the time period 1961-1990) for use in driving the daily runoff and erosion calculations in the Watershed Multi-Year Model (GWLF-E model, described in Section 7.2) (see access USEPA Meteorological Data).

This layer can be visualized on the map by clicking on the “Observations” tab of the “Layer” palette and all 214 weather stations can be seen in blue (you may need to zoom in/out on the map). Clicking on the blue circle will pop-up station information specific to each point on the map. Weather data are also described in Section 7.2.4, and Custom Weather data can be uploaded a Watershed Multi-Year Model run to generate a new scenario based on user supplied weather data.

3.5 Basemaps

3.6 Additional Data Layers

In addition to the data layers that are visualized on the map, the Model My Watershed web app also has access to additional data layers (not visualized) for use by the various modeling functions.

3.6.1 Animals

Model My Watershed’s animal data come from the United States Department of Agriculture National Agricultural Statistics Service. 2015 data for each county in the United States was obtained and estimates of animal types per acre of agricultural land were calculated. Animal estimates by type are then apportioned for any given watershed based on the acres of agricultural land (cropland, hay/pasture) in that watershed.

3.6.2 Point Sources

Point source discharges of pollutants that are permitted under US EPA’s National Pollutant Discharge Elimination System (NPDES) will be listed for any selected Area of Interest under the Analyze tab and the “Pt Sources” sub-tab. These NPDES-permitted discharges are primarily from large municipal and industrial wastewater treatment plants, which are required to submit Discharge Monitoring Reports (DMR). The “Pt Sources” data were created from EPA’s DMR database, which can be accessed through EPA’s Water Pollution Search web portal. These same data are utilized as input to the MMW Watershed Multi-Year Model. For point sources collected within the Delaware River Basin measures of discharge (effluent) and concentration (nitrogen and phosphorus) were taken directly from more detailed state level Discharge Monitoring Reports.


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