This package contains data collected by the Southeast Coast Network (SECN), a part of the Inventory and Monitoring Division (IMD) of the National Park Service (NPS). Data was collected under the Wadeable Stream Habitat Monitoring Protocol (McDonald et al. 2018) during the year 2023. Wadeable stream habitat monitoring surveys were conducted on two stream reaches at Kennesaw Mountain National Battlefield Park (KEMO), one stream reach at Horseshoe Bend National Military Park (HOBE), and one stream reach at Ocmulgee Mounds National Historical Park (OCMU). The data contained within describe geomorphic and habitat conditions observed within the monitored stream reaches at the time of the surveys. The geomorphic dimensions (cross-sectional morphology, channel widths, bank heights, bank angles, bank vegetative cover, and reach slope and sinuosity) of the selected stream reaches are measured to understand the natural range of variability of similar sized streams within and between the park units. Understanding the variability in channel morphology between study reaches will determine which reaches are being negatively impacted by upstream land use and land cover and provide an understanding of long-term trajectories of change along each stream reach. The habitat data provide an understanding of the habitats that are available for colonization by benthic invertebrates within each stream reach. Habitat measures selected for this protocol focus on inventorying large woody debris and bed sediment within each reach. These components of habitat have been shown to be highly influential in the distribution and character of biota within a stream. These data will also facilitate future complementary studies that can focus on the other physical factors (e.g., current, temperature, and oxygen) that influence biotic assemblages.

In 2022, stream reaches at Congaree National Park (CONG) were surveyed following the methods outlined in Monitoring Wadeable Stream Habitat Conditions in Southeast Coast Network Parks (McDonald et al. 2018). On each stream reach, data were collected to provide an understanding of reach- and transect-scale geomorphology and benthic habitat characteristics. In 2021, stream reaches at Chattahoochee River National Recreation Area (CHAT) were surveyed following the same methods (McDonald et al. 2018). In 2019, stream reaches at Horseshoe Bend National Military Park (HOBE), Kennesaw Mountain National Battlefield (KEMO), and Ocmulgee Mounds National Historical Park (OCMU) were surveyed following the same methods (McDonald et al. 2018). In 2018, stream reaches at Congaree National Park (CONG) were surveyed following the same methods (McDonald et al. 2018). In 2017, stream reaches at Chattahoochee River National Recreation Area (CHAT), Kennesaw Mountain National Battlefield (KEMO), and Ocmulgee National Monument (OCMU) were surveyed following the same methods (McDonald et al. 2018). McDonald JM and Others. 2018. Monitoring wadeable stream habitat conditions in Southeast Coast Network parks: Protocol narrative. Natural Resource Report. NPS/SECN/NRR—2018/1715. National Park Service. Fort Collins, Colorado https://irma.nps.gov/DataStore/Reference/Profile/2254874

This dataset represents the soil characteristic within individual, local NHDPlusV2 catchments and upstream, contributing watersheds based on the STATSGO landscape rasters. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. This data set is derived from the STATSGO landscape rasters for the conterminous USA. Individual rasters (Landscape Layers) of depth to bedrock (rckdep), organic material (om), percent clay (clay), percent sand (sand), permeability (perm), soil erodibility (KFFACT/KFACT), and water table depth (wtdep) were used to calculate soil characteristics for each NHDPlusV2 catchment. The soil characteristics were summarized to produce local catchment-level and watershed-level metrics as a continuous data type. The STATSGO data are distributed in two sets, STATSGO_Set1 and STATSGO_Set2, based on common NoData locations in each set of soil GIS layers.

This dataset represents the density of 18 USGS lithology classes within individual, local NHDPlusV2 catchments and upstream, contributing watersheds(see Data Sources for links to NHDPlusV2 data and USGS). Attributes were calculated for every local NHDPlusV2 catchment and then accumulated to provide watershed-level metrics for USGS lithology data. This data set is derived from the USGS raster map of 18 lithology classes (categorical data type) for the conterminous USA. The map was produced based on texture, internal structure, thickness, and environment of deposition or formation of materials. These 18 lithology classes were summarized by local catchment and by watershed to produce 18 local catchment-level and watershed-level metrics as a categorical data type.

This dataset represents data derived from the NLCD dataset and the National Hydrography Dataset version 2.1(NHDPlusV2) (see Data Sources for links to NHDPlusV2 data and NLCD). Attributes were calculated for every local NHDPlusV2 catchment and accumulated upstream catchments to provide watershed-level metrics for imperviousness values within the NLCD. This data set is derived from the NLCD Impervious Surfaces raster, which describes percent imperviousness (continuous data type). Values indicate the degree to which the area is composed of impervious anthropogenic materials (e.g., parking surfaces, roads, building roofs). This raster was produced based on a decision-tree classification of 2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019 Landsat satellite data. This dataset will include additional years as they become available.

This dataset represents percent area consisting of carbonate-rock aquifers, igneous and metamorphic-rock, sandstone, sandstone and carbonate-rock, semiconsolidated sand, and unconsolidated sand and gravel aquifers within individual, local NHDPlusV2 catchments and upstream, contributing watersheds.

This hydrologic and landscape database was developed by the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service for the Clarks River National Wildlife Refuge and contributing watersheds in Kentucky, Tennessee, and Mississippi. The database was developed as an assessment and evaluation tool to use in examining refuge-specific hydrologic patterns and trends as related to water availability and water quality for refuge ecosystems, habits, and target species. The database includes hydrologic time series data, statistics on landscape and hydrologic time series data, and hydro-ecological metrics that can be used to assess refuge hydrologic conditions. The database is described in detail in Open File Report 2017-1018.

This dataset represents the Index of Watershed Integrity / Index of Catchment Integrity (IWI/ICI) within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on 23 other StreamCat metrics. The Index of Watershed Integrity (IWI) is based on first order approximations of relationships between stressors and six watershed functions: hydrologic regulation, regulation of water chemistry, sediment regulation, hydrologic connectivity, temperature regulation, and habitat provision. Link to paper: https://doi.org/10.1016/j.ecolind.2017.10.070\\nThe Index of Watershed Integrity / Index of Catchment Integrity (IWI/ICI) were summarized to produce local catchment-level and watershed-level metrics as a continuous data type.

Wadeable stream habitat data from four long-term monitoring programs (AIM, AREMP, NRSA, PIBO MP) were obtained, pre-processed, transformed, and combined using R code following the Stream Habitat Metrics Integration (SHMI) Data Exchange Standard (Scully et al., 2023b). The dataset includes 26 stream habitat metrics collected between 2000 and 2022 across the United States at ~12,000 locations from ~19,000 data collection events for a total of ~200,000 measurements. Measurements include reach characteristics (sampled reach length, channel gradient, sinuosity), channel dimensions (bankfull width and height, average bankfull width to depth ratio, mean thalweg depth, average wetted width), channel substrate particle sizes (percent fines, percent bedrock, fine sediment percentiles), pools (residual pool depth, pool tail fines), bank characterizations (angle), and water quality/chemistry (specific conductance, pH, specific conductance, turbidity, total nitrogen, total phosphorous). The dataset consists of 4 csv files: 'RecordLevel.csv', 'Location.csv', 'Event.csv', and 'MeasurementOrFact.csv'. The 4 csv data tables may be linked in a database structure using the 'entity relationship diagram.jpg' or by linking the following: Join RecordLevel primary key 'datasetID' to Location foreign key 'datasetID'. Join Location primary key 'locationID to Event foreign key 'locationID'. Join Event primary key 'eventID' to MeasurementOrFact foreign key 'eventID'. An analysis-ready file ('AnalysisStreamHabitatMonitoringMetricDataset.csv') is also published for user convenience.

Wadeable stream habitat data from four long-term monitoring programs (AIM, AREMP, NRSA, PIBO MP) were obtained, pre-processed, transformed, and combined using R code following the Stream Habitat Metrics Integration (SHMI) Data Exchange Standard (Scully et al., 2023b). The dataset includes 26 stream habitat metrics collected between 2000 and 2022 across the United States at ~12,000 locations from ~19,000 data collection events for a total of ~200,000 measurements. Measurements include reach characteristics (sampled reach length, channel gradient, sinuosity), channel dimensions (bankfull width and height, average bankfull width to depth ratio, mean thalweg depth, average wetted width), channel substrate particle sizes (percent fines, percent bedrock, fine sediment percentiles), pools (residual pool depth, pool tail fines), bank characterizations (angle), and water quality/chemistry (specific conductance, pH, specific conductance, turbidity, total nitrogen, total phosphorous). The dataset consists of 4 csv files: 'RecordLevel.csv', 'Location.csv', 'Event.csv', and 'MeasurementOrFact.csv'. The 4 csv data tables may be linked in a database structure using the 'entity relationship diagram.jpg' or by linking the following: Join RecordLevel primary key 'datasetID' to Location foreign key 'datasetID'. Join Location primary key 'locationID to Event foreign key 'locationID'. Join Event primary key 'eventID' to MeasurementOrFact foreign key 'eventID'. An analysis-ready file ('AnalysisStreamHabitatMonitoringMetricDataset.csv') is also published for user convenience.