Data Documentation Report

Transcription

1 Data Documentation Report DESCRIPTION OF GIS DATA SETS AND DERIVED MAP-BASED PRODUCTS USED TO SUPPORT EVALUATION OF CANDIDATE LAND PROTECTION PROJECTS IN THE DELAWARE RIVER BASIN Produced by Barry Evans For the Open Space Institute New York NY February 6, 2015

2 Pg. 1) INTRODUCTION 2) ABILITY TO PRODUCE CLEAN ABUNDANT WATER 3) DATA USED FOR SITE-LEVEL RESOURCE QUALITY 4) DATA USED FOR ASSESSMENT OF SITE-LEVEL VULNERABILITY 5) PRIMARY AND SECONDARY DATA SETS REFERENCES APPENDIX ii

3 1) INTRODUCTION A number of map-based data sets (both primary and secondary) were downloaded and/or developed to support an evaluation of proposed land protection projects within the Delaware River Basin (DRB). Using these data sets, a number of landscape characteristics and metrics were derived that could subsequently be used to compare the relative merits of different parcels of land relative to: 1) watershed ability to produce clean, abundant water, 2) site resource quality, and 3) site vulnerability. Brief descriptions of the data sets are provided in the following sections. Also provided in the Appendix to this document are summaries of the data sets downloaded or derived and the key tabular (attribute) information associated with the GIS layers compiled or derived. Section 2 provides descriptions of the principal watershed-scale (HUC 12) metric based on primary and secondary data sets described in Section 5, at the end of this document. These will be used to evaluate potential land protection projects (i.e., the Ability to Produce Clean Abundant Water ). Section 3 describes some of the principal data sets that will be used for more detailed site-level evaluation. Section 4 covers the data sets that will be used to assess the vulnerability of sites if they were to be converted from natural land cover. The last section (5) identifies the most relevant primary and secondary data sets that were compiled to support various analytical objectives. Primary data sets were created by other sources, and were used to derive intermediate or final data sets and landscape metrics. Secondary data sets were derived from these primary data sets (or combinations of them) or other primary data derived by others (e.g., USEPA) that were of value. These datasets were used to create the data in the above section and serve as a useful compilation of data relevant to water resource revaluation. 2) ABILITY TO PRODUCE CLEAN ABUNDANT WATER The Open Space Institute sought to develop a metric to measure the relative capacity of small scale (HUC 12) watersheds to produce clean surface and ground water. In 2014, two different HUC12-based metrics (i.e., Ability to Produce Good Quality Surface Water and Ability to Produce Good Quality Ground Water ) were calculated and used by OSI to evaluate land protection projects i. In 2015, OSI combined these two metrics into one metric that directly considers watershed conditions including land cover, terrain and hydrology that affect both the abundance and quality of surface and ground water within a reasonably-sized watershed (i.e., HUC12 boundary). The new indexing scheme used to derive this metric (called the Ability to Produce Clean Abundant Water (APCAW)) is shown in Figure 1, which is followed by brief descriptions of how the different factors used in the metric were estimated. This metric retains many of the analytical components of other previously-developed watershed-rating approaches such as Forest-to-Faucet (Barnes et al., 2008), the Conservation Priority Index (WRI, 2013), and the SmartConservation initiative in southeast Pennsylvania ( upon which the earlier metrics were based. 1

4 Figure 1. Value assignment for calculating Ability to Produce Clean Abundant Water metric. Percent Forest/Wetland Cover Estimates of % Forest/Wetland were derived for each HUC12 watershed using the newest (2011) NLCD layer obtained from USGS. Percent Riparian Natural Land Cover For this factor, the Active River Area layer described in Section 5 was used to depict the riparian buffer. Then, estimates of natural land within the buffer area for each HUC 12 watershed were derived using the NLCD layer obtained from USGS. In this case, natural lands essentially includes all land areas not developed or used for agricultural purposes. Erosion Potential An average erosion potential value was derived for each HUC12 watershed within the DRB. A more detailed description of the erosion potential map used in this case is given in Section 5 below. Ground Water Recharge This factor was estimated using the results of a watershed modeling tool (MapShed) that was utilized to estimate non-point source sediment and nutrient loads for all of the HUC12 watersheds within the DRB 2

5 (the detailed results of this model are not reported in this document, but are available upon request). With MapShed (Evans and Corradini, 2012), which is driven by daily rainfall data, estimates are provided for evapotranspiration, surface runoff, and infiltration (called subsurface flow in the model). In this case, infiltration/subsurface flow is essentially a surrogate for groundwater recharge, which is similar to the manner in which recharge is estimated in New Jersey using the GSR32 model (Charles et al., 1993). Headwater Streams Using the 1:100,000-scale stream-order (Strahler) data set described in Section 5, the percent of each HUC12 watershed comprised of headwater streams (actually the percent of each HUC12 comprised by headwater [stream order 1] sub-watersheds) was calculated. Cool Water Streams All of the HUC12 watersheds within the DRB were characterized with respect to the percent of the total stream length within each watershed that were designated by TNC as being cold water streams (see the discussion on the cold water streams layer given in Section 5). Percent Base Flow For this estimate, the base flow index grid described in Section 5 was used. In this case, an areaweighted estimate of mean annual base flow contribution (i.e., percent base flow value) was calculated for each HUC12 watershed in the DRB. 3) DATA USED FOR SITE-LEVEL RESOURCE QUALITY A number of the data sets described in previous sections can be used to support various site-level (i.e., finer-scale) analyses of candidate sites for land protection activities. For example, the detailed tabular data associated with the SSURGO soils map can be used to assess the variability of a wide range of soil characteristics at a fairly fine resolution. In addition to these, two other data sets described below were developed to aid in site-level evaluations. Land Cover in the Active River Area As discussed previously, an active river area layer was obtained from The Nature Conservancy. This layer was used to calculate one of the parameters for the Ability to Produce Clean Abundant Water metric. It allowed evaluation of the amount of riparian region and land use within that designation for the HUC 12. It can also be used to evaluate land cover of the area at the site of a specific land protection project. To evaluate land cover, a new GIS dataset was produced that reflects the basic land cover categories (i.e., water, agricultural land, developed land, forest land, shrub/scrub land, grassland, and wetlands) within the ARA boundaries across the DRB. Sub-Watershed Recharge A more refined recharge data set was developed to help distinguish between areas of differing recharge potential at the project scale. In this case, a new GIS dataset (called Rechcat ) was created that has four 3

6 categories (values) that reflect a combination of recharge and land protection value. These categories include: High potential (value = 3) Medium potential (value = 2) Low potential (value = 1) potential/not considered for land protection (value = 0) and are based on the following assumptions/conditions: Forest/Shrub/Scrub Land In upland areas -> High In lowland areas with high recharge rates -> High In lowland areas with low recharge rates -> Medium Agricultural Land In upland areas -> Medium In lowland areas with high recharge rates -> Medium In lowland areas with low recharge rates -> Low All Other Land -> t Considered (e.g., developed land, wetlands, water bodies) 4) DATA USED FOR SITE-LEVEL ASSESSMENT OF VULNERABILITY A number of the data sets previously discussed can be used to assess the vulnerability of a given site to conversion from natural areas such as forest, shrub/scrub land, and wetlands to other land cover types that have a more negative effect on both surface and ground water quality (e.g., agricultural land and various developed land categories). For example, with regard to surface water, GIS layers that reflect land slope and soil erodibility can be used to evaluate potential problems that might occur when naturally protected landscapes are converted to uses that tend to promote or exacerbate soil erosion, thereby leading to higher sediment and nutrient loads delivered to nearby streams. Erosion Potential To more easily identify areas prone to surface erosion, a new grid was developed that is essentially a combination of the 30m slope grid and soil erodibility (k-factor) data from the detailed soils (SSURGO) data set. The procedure used to create this grid was based on the methodology utilized by the New Jersey Water Supply Authority (Zhang, 2009) DRASTIC To aid in the evaluation of groundwater vulnerability, another new data set was created using an approach developed in a collaborative effort between the U.S. Environmental Protection Agency and The National Water Well Association in the mid-1980s. With this approach, a vulnerability layer is 4

7 created by considering those factors believed by hydro-geologic professionals to be most important when evaluating the potential effects of various contaminants introduced at the land surface to underlying aquifers (USEPA, 1987). This approach is essentially a ranking system called DRASTIC in which various weights are applied to key factors to create index values that potentially range from about 23 to 230, with higher numbers indicating greater vulnerability. The term DRASTIC is an acronym reflecting those factors considered to be most important, including Depth to groundwater (D), aquifer Recharge (R), Aquifer media (A), Soil media (S), Topography (T), Impact of the vadose zone (I), and hydraulic Conductivity (C). The data sets and procedures used to create the DRASTIC layer for the DRB are summarized below. For more details on the how information from the component layers are interpreted and assigned their corresponding weights are directed to DRASTIC reference given above. Depth to Groundwater This map was created for the DRB using the 30m elevation and NHD stream layers described previously. First, an approximation of groundwater elevation was derived using streams as a surrogate for locations where groundwater intersected the land surface (i.e., elevation was 0). The elevation of all of the points comprising the stream segments within the NHD layer were then extracted from the 30m DEM, and a grid of groundwater elevation was created using GIS-based surface interpolation routines. The depth to groundwater layer was then created by subtracting the groundwater elevation layer from the surface elevation (30m DEM) layer. Aquifer Recharge Aquifer recharge values (in inches per year) were based on the results of the MapShed modeling described earlier. Aquifer Media For the purposes of this study, the DRASTIC methodology was used to assess the vulnerability of the uppermost aquifer just below the land surface. In this case, aquifer media refers to the uppermost consolidated or unconsolidated rock/material which serves as an aquifer (such as sand and gravel or limestone). For the DRB, information on rock type or surficial material was drawn from the detailed surficial geology maps compiled for the area. This information was enhanced at different locations using the detailed SSURGO data as well. Soil Media This factor is basically a representation of soil texture, and relates to the permeability of soil/surface material. In this case, the detailed soils data set (SSURGO) was used to assign ratings for different soil types. 5

8 Topography In the context of DRASTIC mapping, topography refers to land slope. In this instance, the slope map derived from the 30m elevation data set was used to depict the different slope range categories used for assigning ratings with DRASTIC. Impact of the Vadose Zone The vadose zone is defined as that zone above the water table which is unsaturated or discontinuously saturated. The representation of different categories as used with DRASTIC were identified using a combination of the detailed soils (SSURGO) and surficial geology data sets. Hydraulic Conductivity Hydraulic conductivity essentially refers to the ability of aquifer materials to transmit water (and potential contaminants moving with it) downward and along a hydraulic gradient. Information on the spatial locations of different aquifer materials within the DRB were based on information provided in the surficial geology and detailed soils data sets. Information on typical hydraulic conductivity rates for these materials was drawn from tables included in the DRASTIC documentation (USEPA, 1987). 5) PRIMARY AND SECONDARY DATA SETS A number of digital map (GIS) data sets were compiled for the DRB area. All of the primary data sets (e.g., land use/cover, surface elevation, soils, hydrography, etc.) were previously developed by groups such as USDA, USEPA, and the U.S. Geological Survey, and were obtained from various websites where these data have been made publicly available. Many of the data sets described below were obtained from the Geospatial Data Gateway ( which is a GIS/environmental data portal maintained by USDA that includes data from that agency as well as many other federal, regional and state agencies. These data sets were used to both provide context with respect to various landscape conditions at the sub-watershed level (e.g., slope steepness, soil erodibility, extent of impervious surfaces, etc.), as well as to create new data sets based on a combination of one or more of the primary data sets (e.g., natural cover within the active river area and groundwater vulnerability). Brief descriptions of the primary and secondary data sets obtained or developed are provided below. Primary Data Sets The primary data sets described below are fundamental base layers which depict basic information pertaining to the landscape (i.e., land cover, surface elevation, soil type, etc.). As described, these were all previously developed by others and are available for download at multiple websites. Land Use/Cover This is one of the GIS data sets used most frequently to characterize landscape conditions within the DRB area, and to derive various metrics upon which evaluation criteria were based. In this case, GIS- 6

9 formatted National Land Cover Database (NLCD) layers were obtained from the Geospatial Data Gateway web portal mentioned above. NLCD is a 16-class land cover data set developed by the U.S. Geological Survey (USGS) that has been consistently applied across the United States at a spatial resolution of 30 meters (Fry et al., 2011). For various landscape metrics derived by OSI in 2014, a vintage NLCD layer was used as this was the most recent version available. However, in late 2014 a newer 2011-vintage data set was released by USGS. This more recent version was used to re-calculate all of the land cover-related metrics used to describe landscape conditions within the DRB. Topography Digital elevation data sets at a nominal spatial resolution of 30 meters were obtained from the U.S Geological Survey via download at These data have been developed as part of the National Elevation Dataset. For this project, these data were obtained for the DRB, and were used either to represent elevation at discrete points across the surface or to derive topographic slope for a variety of purposes. Streams The National Hydrography Dataset was used as the basis for representing stream locations within the DRB. This dataset was developed by the U.S. Geological Survey ( and data at the scale of 1:24,000 was utilized. This data set is well known to miss some small head-water streams. Digital elevation data (see above) or other locally-derived information will be used to complement this data for site-level analysis as needed. Watershed Boundaries Various landscape-related factors were summarized or derived at a sub-watershed scale to assess the importance of conservation within the context of the broader watershed. For this project, hydrologic unit code (HUC) boundaries ( were used to represent subwatersheds across the region. HUC 12 boundaries were selected as the primary unit of analysis for watershed context because the scale tends to be appropriate both for incorporating some of the values of the local project area as well as providing information about the surrounding streams and land cover. Detailed Sub-Watershed Stream Order The USEPA and USGS have recently co-developed a catchment-level dataset that identifies Strahler stream order using 1:100,000-scale NHDPlus hydrography data. These data sets have been assembled by HUC8 boundary and are available through an EPA-funded contractor website ( For the purposes of this project, 12 separate HUC8 data sets within the DRB region were seamed together, and various attribute data available at this same site were downloaded and joined to the larger catchment file to allow sub-areas to be identified as to their corresponding stream order. In the DRB region, there are approximately 20,000 polygons which average about 2 square kilometers in size. Using these identifiers, headwater areas were identified throughout the region. We assume that these headwaters on average capture the relative 7

10 amount of headwaters at the HUC 12 scale and that more detailed stream order information is needed for evaluation at a finer scale. Soil Parameters Two seamless soils datasets based on USDA s SSURGO and STATSGO databases were created for the entire DRB region, and information pertaining to various soil-related factors such as erodibility (k factor), available water-holding capacity, texture, etc. were compiled and summarized for discrete mapping units at these two scales. The SSURGO (Soil Survey Geographic) database is compiled at the detailed county-level survey scale that most soil information users are familiar with, and has two basic components: 1) digital boundaries of the detailed soil mapping units, and 2) tabular information on a wide range of soil parameters associated with each mapping unit. The STATSGO (State Soil Geographic) database summarizes similar soils information at a much more generalized soil association scale. Both of these datasets for the DRB area were downloaded from USDA s geospatial data site at Once downloaded, considerable effort was then expended to first seam together the data from the separate states overlapping the DRB, and then to populate both soil databases by linking a number of attribute tables to the soils polygons contained within the DRB boundary. In this case, over 325,000 soil polygons were populated with information extracted from about a dozen different attribute tables. Surficial Geology Surficial geology data was downloaded from the Geospatial Data Gateway, and is part of the nationalscale geology layer created by the U.S. Geological Survey. Other digital map products depicting surficial geology have been developed, but require downloading on a piecemeal basis. Roads/Streets Reasonably detailed renditions of the road network within the DRB (including streets in urban areas) are available for download at the Geospatial Data Gateway as well. These were downloaded and used to create a road/stream intersection data set as described in a later section. This data set is based on the 2010 TIGER data layer developed by the U.S. Bureau of Census. Secondary Data Sets For the purposes of conducting some of the analyses described in this report, a number of secondary data sets were used to help make slight adjustments to, or used as intermediate data sets for the creation of, some of the final GIS layers or map-based metrics upon which future land protection project evaluations will be based. As described below, some of these were previously created by other groups, whereas others were produced via combination and manipulation of these and other data sets discussed above. te that not all of these are in current use by OSI for its land protection fund. 8

11 Ecoregions A digital map depicting Level IV ecoregion boundaries was obtained from a USEPA website at IV. This map was used to help identify the location of large upland areas within the DRB, as well as to help distinguish between glaciated and non-glaciated areas. Active River Area For the stream-related buffer analyses described in a later section, an active river area layer created by The Nature Conservancy was used in lieu of creating a stream buffer using arbitrarily-defined width and condition parameters. This more dynamic stream buffer is believed to more accurately represent the fluctuating boundary around a stream which includes those lands within which the river interacts both frequently and occasionally (TNC, 2008). The original ARA data set, however, did not include buffers around many of the smaller stream segment shown on newer (1:24,000 scale) versions of the NHD layer (see earlier discussion above on streams) because many such segments were missing on earlier versions of the NHD data set. For this project, these missing buffers were generated automatically by defining a minimum buffer size around smaller stream segments based on the average buffer width used for comparable stream segments in the original ARA layer. In addition, wetland areas contiguous to the ARA buffers were also added to this modified data set. Impaired Streams As part of on-going studies and surveys, all of the states overlapping the DRB have developed GIS layers and related data sets in one form or another that identify stream segments within their respective jurisdictions that have been deemed to be impaired based on established state-specific criteria (including water quality sampling and/or rapid bio-assessment techniques). These impaired stream segments are typically recorded on a federal 303d List until identified problems have been remedied. For this project, the relevant data sets were obtained from the various state agencies, as well as from the USEPA. Using these data sets, a composite layer reflecting the most current stream impairment listings was created to aid in the identification of areas where potential land protection projects might coincide with existing (i.e., officially recorded) water quality problems. Potential Salt Water Intrusion Map In low-lying areas of New Jersey and Delaware, the intrusion of salt water into the unconfined ground water aquifers along the coast has long been recognized as a threat to potable water supplies. To aid in the identification of areas potentially threatened by salt water intrusion, a new map was derived using information on the location of salt water marshes (as reflected on the NLCD land cover layer) and surface elevation from the 30m DEM to derive a salt water intrusion map. In this case, a combination of these two factors was manipulated until the extent of such areas approximated the extent of zones of salt water intrusion shown on a hard-copy map prepared previously by the U.S. Geological Survey (Ayers and Pustay, 1986). 9

12 Road/Stream Intersections For this data set, the roads and streams data layers described in the previous sub-section on primary data were overlaid to create a new GIS layer that depicts intersections between the two. These intersections were then summarized as the number of road/stream intersections per linear mile of stream for each HUC 12 boundary. As noted on page 42 of the report by the New Jersey Highlands Water Protection and Planning Council (2008), this data set provides a refined ability to assess the quality of the riparian area since road crossings often impact the geomorphology and degree of sedimentation along the stream bank. Percent Impervious Surface Along with land use/cover classes, the newest 2011-vintage NLCD product just released by USGS (see previous discussion on Land Use/Cover) also includes a national data layer depicting percent impervious surface. In this case, each grid cell value ranges from 0-100, which represents the percent impervious surface value for that cell. This particular data set is of interest because estimates of percent impervious surface for any given area are informative when compared against broad classes of water quality degradation as described by Schueler (2003) on the basis of percent impervious surface (cover) within a watershed. For this project, area-weighted values of percent impervious surface were derived for each of the HUC12 watershed boundaries within the DRB. Base Flow Estimates A 1-kilometer raster (grid) dataset for the conterminous United States is now available from the U.S. Geological Survey (Wolock, 2003). This layer was created by interpolating base-flow index (BFI) values estimated at USGS stream gages located around the country. In this case, the value for each 1-km grid cell indicates the component (i.e., percent) of streamflow that can be attributed to ground-water discharge into nearby streams. For this project, an area-weighted estimate of mean annual base flow contribution was calculated for each HUC12 watershed in the DRB. Cold Water Streams The Nature Conservancy (TNC) has recently developed a stream-based GIS dataset for 13 northeastern states (ME, NH, VT, MA, CT, RI, NY, NJ, PA, MD, DC, DE, VA, WV) using their rtheastern Aquatic Habitat Classification System (NAHCS), which provides information on stream size, stream temperature, stream gradient, stream geology, lakes and catchments (see ). Stream and river centerlines were extracted from the USGS National Hydrography Dataset Plus (NH-Plus) :100,000 data. These reaches were attributed by TNC and placed into classes representing their biophysical setting in terms of stream size, gradient, geology, and expected natural water temperature regime (i.e., cold, transitional cool, transitional warm, and warm ). 10

13 n-point Source Pollutant Load Estimates As described in a previous section related to deriving the Ability to Produce Clean Abundant Water metric in (i.e., Section 2), a watershed modeling tool called MapShed was used to estimate groundwater recharge for each of the HUC12 watersheds within the DRB. As part of the modeling process, nitrogen, phosphorus and sediment loads were also estimated for each of the HUC12 watersheds. Since point source discharges (e.g., from wastewater treatment plants) were not included in the simulation, the loads estimated only represent those originating from non-point sources such as agricultural fields and urban developments. From these, unit area loading rates were also calculated, which have been stored in separate fields in the HUC12 watershed layer described previously. 11

14 REFERENCES Ayers, Mark A. and Edward A. Pustay, National Water Summary 1986 Ground Water Quality: New Jersey. U.S. Geological Survey Water Supply Paper 2325, pp Barnes, Martina C., Albert H. Todd, Rebecca Whitney, and Paul K. Barten, Forests, Water and People: Drinking water supply and forest lands in the rtheast and Midwest United States. USDA Forest Service, rtheastern Area State and Private Forestry, NA-FR Newtown Square PA. Charles, E.G., C. Behroozi, J. Schooley and J. Hoffman, A Method for Evaluating Ground-Water Recharge Areas in New Jersey. New Jersey Geological Survey, Geological Survey Report GSR-32, 103 pp. Evans, B.M. and K.J. Corradini, MapShed Users Manual. Penn State Institute of Energy and the Environment, 137 pp. Fry, J., Xian, G., Jin, S., Dewitz, J., Homer, C., Yang, L., Barnes, C., Herold, N., and Wickham, J., Completion of the 2006 National Land Cover Database for the Conterminous United States, PE&RS, Vol. 77(9): New Jersey Highlands Water Protection and Planning Council, Land Preservation and Stewardship, TechnicalReport. Schueler, T., Impacts of Impervious Cover on Aquatic Systems. Watershed Protection Research Monograph. 1, Center for Watershed Protection, Elliott City, MD, 158 pp. The Nature Conservancy, The Active River Area: A Conservation Framework for Protecting Rivers and Streams. 64pp. USEPA, DRASTIC: A Standardized System for Evaluating Ground Water Pollution Potential Using Hydrogeologic Settings. Robert S. Kerr Environmental Research Laboratory, EPA/2-87/035, 641 pp. Wolock, D.M., Base-flow index grid for the conterminous United States: U.S. Geological Open-File Report World Resources Institute, Natural Infrastructure: Investing in Forested Landscapes for Source Water Protection in the United States, 140 pp. Zhang, J., Preservation of Sensitive Water Resource Areas : A Technical Report about the GIS Model to Identify Sensitive Water Resources in Need of Protection for the Open Space Acquisition Program of the New Jersey Water Supply Authority, 19 pp. 12

15 APPENDIX Contained on the following pages are listings of data sets (GIS Layers) prepared to support the evaluation of potential land protection projects within the Delaware River Basin. Some of these data sets also extend into the Kirkwood-Cohansey aquifer areas of New Jersey. Also included are descriptions of the tabular (attribute) information associated with many of the more important data sets. 13

16 Primary and Secondary Data Sets Name Format Description NLCD Drbdem30m Drbslope Drbgwdepth3 Ara30m Arastrmbuf4 Bfi48drb Drbclusters Drbcounties Drbecoregions Drbgeology Drbgovunits Drbhuc12sv3 Drbsoils Drbnhd Drbroadstreamintersect Drbstreets Pa_nonattain_utm18v3 Drb303dv2 Drb_bnd_polygon National Land Cover Dataset (USGS) with 16 classes 30m DEM data from USGS Derived slope (%) from DEM Depth to groundwater (meters) Active River Area (from TNC) (1 = in buffer, 0 = outside) Modified ARA grid with wetlands and small stream buffers National base flow index grid from USGS clipped to DRB William Penn clusters DRB counties EPA Level IV ecoregions Surficial geology Government units/protected lands Basins (HUC12) with key analysis data fields STATSGO soils data NHD streams data Road/stream intersections Roads/streets Impaired streams for PA Impaired streams for non-pa areas DRB boundary 14

17 Primary and Secondary Data Sets (cont.) Name Format Description Drbssurgo Drbssurgov2 Drbssurgov3 Saltmap2 Erospoten Rechcat Ara4land2011 Drb_flowlines_habguide SSURGO soils data (see field descriptions in table below) SSURGO soils data with new fields SSURGO soils data with new fields Salt water intrusion map (1 = saltwater, 0 = not) Erosion potential (Low: , Medium: , High: ) Recharge categories (3 = high, 2 = medium, 1 = low, 0 = not considered [see Section 5 for details) Expanded riparian (ARA) buffer with grid cell values set to USGS 2011 NLCD land use/cover categories. Stream-based layer developed by TNC that provides stream temperature among many attributes Table Description for Drbgeology shapefile Field New Field? Description Orig_label Sgmc_label Unit_link Source Unit_age Rocktype1 Rocktype2 Eco_Region Mapping unit label provided with original shapefile Mapping unit label provided with original shapefile t sure provided with originalshapefile State from which data were derived Geologic age of unit (part of original data) Primary rock type (part of original data) Secondary rock type (part of original data) Ecologic region based on overlap with other layer (Drbecoregions.shp) 15

18 DATA SETS FOR THE COMBINED DRB/KC REGION Name Format Location Description Allhuc12sv2 FinalDRBdata\Files Combined HUC12s with data fields Allsheds FinalDRBdata\Files Catchments with stream order data Mergedara FinalDRBdata\Files Merged ARA grids for DRB and K-C areas (1 = natural land, 0 = not natural land) Allaraland FinalDRBdata\Files ARA boundaries with 8 classes of land cover (1 = Water, 2 = Developed, 3 = Barren land, 4 = Wooded, 5 = Shrub, 7 = Grassland, 8 = Agriculture, 9 = Wetland) Allaranlcd FinalDRBdata\Files ARA boundaries with original NLCD land cover classes Allnlcd FinalDRBdata\Files NLCD land cover map for combined area Allrechcat FinalDRBdata\Files Map of site-level recharge potential (30m) Headwater FinalDRBdata\Files Derived from the Allsheds shapefile above. Values of 1 = headwater catchment. Table description for allsheds shapefile Field New Field? Description Comid Areasqkm Strahler Headwater ID for linking with NHDPlus attribute files Catchment area in square kilometers Strahler stream order Headwater has value of 1 (stream has value of 1 at hydrography scale of 1 100,000) 16

19 Table description for allhuc12sv2 shapefile Field New Field? Description A2pgqsw2 A2pgqgw2 Devrank2 Slprank2 Ripnatrnk Qualsw2 Qualgw2 Qualify2 Njhuc12 Drbhuc12 Mask Pctheadwtr Ability to produce good quality surface water score Ability to produce good quality ground water score The developed land rank based on percent developed land in HUC The slope rank based on average slope within the HUC The riparian rank based on percent of natural land within the boundaries of an ARA buffer within a given HUC Does the HUC qualify based on a2pgqsw score? (Y or N) Does the HUC qualify based on a2pgqgw score? (Y or N) Does the HUC qualify based on a2pgqgw or a2pgqsw score? (Y or N) HUC12 ID used to identify New Jersey HUCs HUC12 ID used to identify DRB HUCs ID used to create preliminary grid Percent of HUC12 comprised of headwater area (Strahler = 1) te: Field names and descriptions given previously for the Drbhuc12v2 shapefile table described below are not repeated here. 17

20 Table Description for the Drbhuc12sV3 shapefile Included below are brief descriptions of the key attribute fields associated with this shapefile. Field Description Huc12 Forwetrnk Ripforrnk Erodrnk Rechrank Cmrech Inrech Pctprotect Cleanwat Pctimperv2 Pctbaseflo Erospoten Temp1pct Temp2pct Temp3pct Temp4pct Pctaranat Pctforwet2 Pctheadwat Headrank Coolrank Baserank Hydrologic Unit Code assigned by USGS Rank calculated for A2PACW score for % forest/wetland area of a given HUC12 Rank calculated for A2PACW score for % ARA buffer with natural lands in a HUC12 Rank calculated for A2PACW score for mean erosion potential value in a HUC12 Rank calculated for A2PACW score for mean recharge value in a HUC12 Mean annual recharge (in cm) for a given HUC12 Mean annual recharge (in inches) for a given HUC12 Percent of area in a HUC12 with protected land status Final score for Ability to Produce Clean Abundant Water for the HUC12 Mean percent impervious surface within a HUC12 Value representing the mean contribution of baseflow to stream flow for the HUC12 Mean erosion potential value based on the Erosion Potential grid (see Section 5) Percent of total stream length designated as Cold water in a HUC12 Percent of total stream length designated as Cool Transitional water in a HUC12 Percent of total stream length designated as Warm Transitional water in a HUC12 Percent of total stream length designated as Warm water in a HUC12 Percent of ARA buffers within a HUC12 that are comprised of natural land Percent of HUC12 that is covered by forests or wetlands Percent of HUC12 comprised of headwater areas Rank calculated for A2PACW score for % headwater value in a HUC12 Rank calculated for A2PACW score for % cold water value in a HUC12 Rank calculated for A2PACW score for % base flow value in a HUC12 18

21 Table Description for Drbhuc12v2 shapefile Included below are brief descriptions for each of the attribute fields associated with the above shapefile. Many of the fields were included with the original HUC12 layer, and in some cases it is not known what the fields represent. Where this occurs, it is so noted. Otherwise, descriptions for the new fields created as part of this project (i.e., New Field = are given). Field New Field? Description Huc12 Name Ptpermile Acres Hectares Sq_miles ID Pctripfor Pctagland Pctdevland Avg_kf Avg_slp Forwetrnk Ripforrnk Agrank Devrank Erodrnk Slprank Rechrank USGS HUC designation Name of HUC Number of road/stream intersections per linear mile of streams within the HUC boundary Area of HUC polygon in acres Area of HUC polygon in hectares Area of HUC polygon in square miles Unique ID that was added to simplify differentiation between HUCs Percent of riparian buffers within a HUC that are forested Percent of HUC that is agricultural land Percent of HUC that is developed (i.e., Devel_cnt / Huc_cnt) The average soil erodibility (K) factor within a HUC that was derived from detailed soils (SSURGO) data The average slope within a HUC that was derived using the 30m DEM of the basin The forest/wetland rank based on the Pctforwet value above The riparian forest rank based on the Pctripnat value below The agricultural land rank based on the Pctagland value above The developed land rank based on the Pctdevland value above The soil erodibility rank based on the Avg_kf value above The slope rank based on the Avg_slp value above The recharge rank based on the average recharge value (Inrech) given below 19

22 Field New Field? Description A2pgqgw A2pgqsw Cmrech Inrech Strmxrnk Pctsalt Saltrank Pctprotect Anscode Ans_pcrank Ans_rarank Ans_rurank Tpkgha Pctripnat Pctimperv Ability to produce good quality ground water index (see additional text regarding calculations below) Ability to produce good quality surface water index (see additional text regarding calculations below) Groundwater recharge (cm) estimated using MapShed model Groundwater recharge converted to inches Stream crossing rank based on quartiles of Ptpermile above Percent of a HUC believed to be influenced by saltwater intrusion Saltwater intrusion rank based on quartiles of Pctsalt above Percent of a HUC with protected land Code assigned for each HUC12 by ANS as a result of previous work Rank based on ANS tiers for land protection/conservation (Tier 1 = 1, Tier 2 = 2, Tier 3 = 3, and Tier 4 = 4) Rank based on ANS tiers for agricultural restoration (Tier 1 = 1, Tier 2 = 2, Tier 3 = 3, and Tier 4 = 4) Rank based on ANS tiers for urban restoration (Tier 1 = 1, Tier 2 = 2, Tier 3 = 3, and Tier 4 = 4) Total P loading rate (kg/ha) based on MapShed model results Recalculation of the percentage of the riparian buffer (ARA) that is natural land instead of forest only. Percent of HUC estimated to be impervious surface 20

23 Table Description for SSURGO shapefiles (Drbssurgo, Drbssurgov2, and Drbssurgov3) (te: The fields described below may occur in one or more of the above shapefiles) Field New Field? Description Musym Mukey Muname Slopegradd Slopegradw Brockdepmi Wtdepannmi Pondfreqpr Aws025wta Aws050wta Aws0100wta Aws0150wta Drclassdcd Drclasswet Hydgrpcd Hydclprs Table Mapping unit symbol found on soil map (part of SSURGO data) Mapping unit key used to link with soil attribute tables (part of SSURGO data) Mapping unit name (soil mapping name part of SSURGO data) Slope gradient (part of SSURGO) Slope gradient weighted (part of SSURGO) Minimum depth to bedrock in centimeters (part of SSURGO Data) Minimum annual depth to water table in cm (part of SSURGO data) Ponding frequency (part of SSURGO data) Available water-holding capacity (in cm) within the top 25 cm of soil (part of SSURGO data) Available water-holding capacity (in cm) within the top 50 cm of soil (part of SSURGO data) Available water-holding capacity (in cm) within the top 100 cm of soil (part of SSURGO data) Available water-holding capacity (in cm) within the top 150 cm of soil (part of SSURGO data) Drainage class (part of SSURGO data) Also drainage class not sure why different than above (part of SSURGO data) Hydrologic Soil Group (part of SSURGO data) Hydric class (part of SSURGO data) Specific SSURGO table from which various values were extracted 21

24 Field New Field? Description Kffact Mu_awc Mu_kf Muhsg_dom First_text First_textd First_textc First_lieu Erodibility (k) factor for soil mapping unit. Specific field for available water used in MapShed modeling Specific field for k factor used in MapShed modeling Specific field for hydrologic soil group used in MapShed modeling. Soil texture code (part of SSURGO data) Soil texture description (part of SSURGO data) Soil texture description (part of SSURGO) Additional description of surface soil horizon (part of SSURGO data) i Data layer updates for 2015: For our 2015 Request for Proposals, OSI has combined and updated the watershed context score. The new score combines the relevant indicators for Ground Water and Surface Water into a single index. The changes did have an effect on some of the HUC 12 watershed scores. Below is a summary of the changes that were made and the final index: Removed % Agricultural land and % Developed land. These indices, which favored low values, were triple counting land cover. %Forest/Wetland was retained. Removed stream/road intersections. This dataset did not consistently cover dirt and gravel roads across the basin and did not account for stream proximity to roads, which could have as much or more influence on the stream than a crossing. Combined slope and soils erodibity into a single indicator called Erosion Potential. The combined value provides a strong assessment of potential sedimentation and avoids double counting these values with two separate fields. Expanded the Riparian Natural Cover (i.e. Active River Area) indicator to include smaller scale streams. Added datasets that augment information about hydrological health. The Ground Water Recharge dataset, which remains unchanged from 2014, indicates the watershed s ability to capture surface water for ground water storage. It does not provide information about the contribution of ground water to stream flow (i.e. baseflow), which can be a very strong indicator of stream quality even in watersheds with lower forest/wetlands land cover scores. To better identify watersheds with a strong contribution from groundwater sources, we add a Base Flow 22

25 indicator using data from 1000 meter scale data from USGS. In addition, we ve added data from the TNC Eastern Regional Science office that measures Cool Water Streams. We evaluate the percent of the streams in the watershed with the coldest stream values. Lastly, we added % Headwaters to the index. This is the same dataset that had been considered independently in