Benthic macroinvertebrates sampled from 76 small streams in the Georgia Coastal Plain. Additional data includes in-situ physiochemcial water quality data, physical stream habitat data and land use data in the watershed draining to the sample stream reach, as well as in the immediate riparian zone adjacent to all stream reaches upstream of the sample reach. These data were used to develop a biological condition index for evaluating stream restoration projects in this region. Citation information for this dataset can be found in the EDG's Metadata Reference Information section and Data.gov's References section.

We used 14 years (10-01-1999 to 09-30-2014) of biological data (benthic macroinvertebrate and stream fish community data and complementary biological metrics) that was collected from Alabama streams confined to the Mobile River basin and other Gulf Coast drainages in conjunction with land use data and process-based model hydrological (i.e., Precipitation-Runoff Modeling System; PRMS), and water quality (i.e., Spatially Referenced Regression On Watershed Attributes, SPARROW) outputs to explore the effects of land use-driven high and low flow conditions on resource limited taxa abundances and three biological metrics across two landscapes. A landscape consisted of all level III ecoregions above or below the geological feature referred to as the fall line across Alabama. We created two taxa-specific datasets for each landscape by connecting taxa-specific biological samples and the corresponding biological metrics to NHDPlus COMIDs and then used this spatial reference to relate these data to PRMS stream segments. This process enabled us to compile hydrologic metrics, long-term estimates of urban and agricultural land use, and water quality gradients for each biological sample. Biological datasets were compiled from samples collected by two Alabama state agencies: the Alabama Department of Environmental Management (ADEM) and the Geological Survey of Alabama (GSA). ADEM collected all benthic macroinvertebrate samples, while GSA collected all stream fish samples. All ADEM's benthic macroinvertebrate samples included raw community data, along with biological condition gradient (BCG) and Ephemeroptera, Plecoptera, and Trichoptera scores. GSA's stream fish samples included the raw community data and fish index of biological integrity scores. For all biological samples, NHDPlus COMIDs, and PRMS segments we also integrated the following attributes into each of our four datasets; for each biological sample we included its collection date, site ID, and geographic coordinates (decimal degrees); for each COMID, we included its cumulative drainage area (square kilometers) and slope (percentage) and identified the segment’s relevant level III ecoregion; and for each PRMS segment we included its cumulative drainage area (square kilometers). For each of the four datasets, we used PRMS predicted daily streamflow data to calculate 171 biologically relevant hydrologic metrics for each PRMS stream segment and used SPARROW long-term annual, COMID-specific estimates of total nitrogen, total phosphorus, and suspended sediment to generate standardized water quality gradients by incorporating these variables into principal component analyses. We then used annual land cover datasets (2001, 2004, 2005, 2006, 2008, 2011, 2012, 2013, and 2014) to calculate long-term averages of the percentages of urban and agricultural land use associated with each PRMS stream segment, and then estimates were used to identify high and low flow metrics that were only significantly correlated with either land use type. We then integrated the standardized water quality gradients, subsets of hydrologic metrics, and taxa-specific community data into community models to identify resource-limited taxa that were responsive to land use- driven flow conditions. Finally, we used these resource-limited taxa, the three biological metrics, standardized water quality gradients and subsets of hydrologic metrics to evaluate the impact of land use-driven flow conditions on aquatic communities native to Alabama streams. References: Olden, J. D., & Poff, N. L. (2003). Redundancy and the choice of hydrologic indices for characterizing streamflow regimes. River research and applications, 19(2), 101-121. LaFontaine, J.H., Hay, L.E., and Farmer, W.H., 2019, Model Input and Output for Hydrologic Simulations of the Southeastern United States for Historical and Future Conditions: U.S. Geological Survey data release, https://doi.org/10.5066/F74X56PH. Roland, V.L., II, and Hoos, A.B., 2020, SPARROW model

We used 14 years (10-01-1999 to 09-30-2014) of biological data (benthic macroinvertebrate and stream fish community data and complementary biological metrics) that was collected from Alabama streams confined to the Mobile River basin and other Gulf Coast drainages in conjunction with land use data and process-based model hydrological (i.e., Precipitation-Runoff Modeling System; PRMS), and water quality (i.e., Spatially Referenced Regression On Watershed Attributes, SPARROW) outputs to explore the effects of land use-driven high and low flow conditions on resource limited taxa abundances and three biological metrics across two landscapes. A landscape consisted of all level III ecoregions above or below the geological feature referred to as the fall line across Alabama. We created two taxa-specific datasets for each landscape by connecting taxa-specific biological samples and the corresponding biological metrics to NHDPlus COMIDs and then used this spatial reference to relate these data to PRMS stream segments. This process enabled us to compile hydrologic metrics, long-term estimates of urban and agricultural land use, and water quality gradients for each biological sample. Biological datasets were compiled from samples collected by two Alabama state agencies: the Alabama Department of Environmental Management (ADEM) and the Geological Survey of Alabama (GSA). ADEM collected all benthic macroinvertebrate samples, while GSA collected all stream fish samples. All ADEM's benthic macroinvertebrate samples included raw community data, along with biological condition gradient (BCG) and Ephemeroptera, Plecoptera, and Trichoptera scores. GSA's stream fish samples included the raw community data and fish index of biological integrity scores. For all biological samples, NHDPlus COMIDs, and PRMS segments we also integrated the following attributes into each of our four datasets; for each biological sample we included its collection date, site ID, and geographic coordinates (decimal degrees); for each COMID, we included its cumulative drainage area (square kilometers) and slope (percentage) and identified the segment’s relevant level III ecoregion; and for each PRMS segment we included its cumulative drainage area (square kilometers). For each of the four datasets, we used PRMS predicted daily streamflow data to calculate 171 biologically relevant hydrologic metrics for each PRMS stream segment and used SPARROW long-term annual, COMID-specific estimates of total nitrogen, total phosphorus, and suspended sediment to generate standardized water quality gradients by incorporating these variables into principal component analyses. We then used annual land cover datasets (2001, 2004, 2005, 2006, 2008, 2011, 2012, 2013, and 2014) to calculate long-term averages of the percentages of urban and agricultural land use associated with each PRMS stream segment, and then estimates were used to identify high and low flow metrics that were only significantly correlated with either land use type. We then integrated the standardized water quality gradients, subsets of hydrologic metrics, and taxa-specific community data into community models to identify resource-limited taxa that were responsive to land use- driven flow conditions. Finally, we used these resource-limited taxa, the three biological metrics, standardized water quality gradients and subsets of hydrologic metrics to evaluate the impact of land use-driven flow conditions on aquatic communities native to Alabama streams. References: Olden, J. D., & Poff, N. L. (2003). Redundancy and the choice of hydrologic indices for characterizing streamflow regimes. River research and applications, 19(2), 101-121. LaFontaine, J.H., Hay, L.E., and Farmer, W.H., 2019, Model Input and Output for Hydrologic Simulations of the Southeastern United States for Historical and Future Conditions: U.S. Geological Survey data release, https://doi.org/10.5066/F74X56PH. Roland, V.L., II, and Hoos, A.B., 2020, SPARROW model

This dataset represents land cover mapping, physical habitat measurements, continuous hydrology measurements, salt tracer measurements, and benthic macroinvertebrate sample scores from nine small streams in unincorporated King County within the Puget Sound region of Washington State. These data were collected during two periods, 2008 – 2012/2013 and 2018 – 2022, as part of a study to evaluate the performance of King County’s land use regulations at protecting stream ecosystems. Six of the streams drained watersheds that were developed or developable and were subject to King County’s land use regulations. Three of the streams drained watersheds that were largely protected from development and served as references for comparison. The initial data collection (2008 – 2012/2013) is described in a report titled, “Assessing Land Use Effects and Regulatory Effectiveness on Streams in Rural Watersheds of King County, Washington,” published in 2014. An analysis of the two combined datasets is described in a report titled, “The Effects of the Land Use Regulatory Framework on Stream Ecosystems in Unincorporated King County Watersheds,” published in 2025. See these reports for details about the sampling methods, study results, and what these data represent. Below we briefly describe the types of data included in this dataset. For questions about these data, please contact James Bower (james.bower@kingcounty.gov), Aaron David (adavid@kingcounty.gov), Ian Higgins (ihiggins@kingcounty.gov), or Rebekah Stiling (rstiling@kingcounty.gov). All data were collected by the King County Water and Land Resources Division, Science and Technical Support Section. Land cover mapping of the nine study watersheds was conducted once at the beginning and end of the first period (2007 and 2012) and once at the beginning and end of the second period (2017 and 2022). The land cover data are represented by ‘Land_cover.csv’. Physical habitat measurements were collected once a year within a defined and consistent section of each stream. Physical habitat measurements are represented by ‘Pools.csv’, ‘Reach_lengths.csv’, ‘Substrate.csv’, ‘Thalweg_depths.csv’, and ‘Wood.csv’. Continuous hydrology measurements of stream discharge, water temperature, and conductivity were collected in each stream throughout most years of the study. Continuous hydrology measurements were summarized into daily values and are represented by ‘Hydrology_daily.csv’. Samples of the benthic macroinvertebrate community were collected in each stream during late summer or early fall across all study years. These samples were used to calculate Puget Sound lowlands Benthic-Index of Biotic Integrity scores for each stream and year. Benthic macroinvertebrate sample scores are represented by ‘BIBI.csv’. Salt tracer measurements were conducted in each stream across multiple flows within each year. Salt tracer measurements are represented by ‘Tracer_measurements.csv’. The ‘Variable_names.csv’ file contains a list of each of the variable/field names within each data file, the variable type for each field, and a brief description of what each variable/field represents.

Montgomery County, Maryland Department of Environmental Protection has collected datasets to assess the health of streams since the early 1990s. Datasets include geomorphic stream cross-sectional surveys, fish and benthic macroinvertebrate counts and taxa abundance, and water chemistry data collected at the time of benthic and fish sampling (dissolved oxygen, pH, specific conductance, air temperature, and water temperature). Data span years 1992 to 2020 at five watersheds within the Clarksburg study area. Watersheds include a forested reference site (Soper), an urban site with centralized stormwater management (Crystal Rock), and three treatment watersheds (TR104, TR109, and Cabin Branch) within the Clarksburg Special Protection Area that transitioned from agriculture to suburban development with distributed stormwater management. These data were used to assess the impacts of distributed stormwater management on stream ecosystem function. All datasets were collected by Montgomery County, Maryland Department of Environmental Protection.

Montgomery County, Maryland Department of Environmental Protection has collected datasets to assess the health of streams since the early 1990s. Datasets include geomorphic stream cross-sectional surveys, fish and benthic macroinvertebrate counts and taxa abundance, and water chemistry data collected at the time of benthic and fish sampling (dissolved oxygen, pH, specific conductance, air temperature, and water temperature). Data span years 1992 to 2020 at five watersheds within the Clarksburg study area. Watersheds include a forested reference site (Soper), an urban site with centralized stormwater management (Crystal Rock), and three treatment watersheds (TR104, TR109, and Cabin Branch) within the Clarksburg Special Protection Area that transitioned from agriculture to suburban development with distributed stormwater management. These data were used to assess the impacts of distributed stormwater management on stream ecosystem function. All datasets were collected by Montgomery County, Maryland Department of Environmental Protection.

This data release includes metrics from the Regional Stream Quality Assessment (RSQA) from the Southeast Region for habitat stressors related to water-quality and habitat substrate. The goals of RSQA are to characterize multiple water-quality factors that are stressors to aquatic life ‐ contaminants, nutrients, sediment, and streamflow alteration – and to develop a better understanding of the relation of these stressors to ecological conditions in streams throughout the region. In order to characterize water-quality variables and stream-habitat measurements as an aggregation of multiple measurements over a sampling period, and in support of ecological stressor modelling, metrics (summary statistics or indices) were computed from individual results by site using consistent methods over a consistent time frame. Water-quality metrics are based on discrete samples as well as long-term deployed passive samplers.

This data release includes metrics from the Regional Stream Quality Assessment (RSQA) from the Southeast Region for habitat stressors related to water-quality and habitat substrate. The goals of RSQA are to characterize multiple water-quality factors that are stressors to aquatic life ‐ contaminants, nutrients, sediment, and streamflow alteration – and to develop a better understanding of the relation of these stressors to ecological conditions in streams throughout the region. In order to characterize water-quality variables and stream-habitat measurements as an aggregation of multiple measurements over a sampling period, and in support of ecological stressor modelling, metrics (summary statistics or indices) were computed from individual results by site using consistent methods over a consistent time frame. Water-quality metrics are based on discrete samples as well as long-term deployed passive samplers.

Metrics describing watershed hydrology, stream hydraulics, stream geomorphology, physicochemical processes, and aquatic biology were used to assess a 1.72 km reach of stream above the U.S. Geological Surveys (USGS) Flatlick Branch (station ID 01656903) monitoring station restored using natural channel design. The monitoring station has been continually operated since the start of water year 2008 (water years begin October 1, end September 30th, and are named for the year in which they end). The stream restoration was constructed and completed in water year 2018, and the assessment uses a pre- versus post-restoration study design. The study period spans water year 2008 through 2024. Hydrologic metrics derived from data retrieved from the National Water Information System are provided. Hydraulic metrics are supported by semi-annual cross-sectional surveys collected by USGS staff following standard procedures (Noll and Rylund, 2020). Nutrient and suspended sediment concentrations and loads were computed using a surrogate (multiple-linear regression) approach with lab analyzed nitrogen, phosphorus, and suspended sediment samples as the response variable and basic water-quality parameters (e.g. turbidity, specific conductance, water temperature, pH), streamflow, a baseflow separation Boolean term, and time and seasonal terms as predictor (surrogate) variables. Load results represent the mass of nitrogen, phosphorus, and suspended sediment exported from the watershed. Calibration data, high-frequency surrogate timeseries, and model coefficients, diagnostics, and residuals are provided for each model. High-frequency estimates of concentration and load are provided for all nutrient and sediment constituents. Fairfax County collected benthic macroinvertebrate and habitat data annually, and fish data triennially. These data were used to compute numerous geomorphological and biological metrics and explore patterns and trends before and after the stream restoration. This data release contains seventeen comma-delimited (.csv) files with corresponding data dictionary files (.csv), one text (.txt) file with corresponding data dictionary file (.csv), and one R script. • AEP.csv contains annual exceedance probabilities for peak streamflows derived with the USGS program PeakFQ version 7.2. • Benthic_macroinvertebrates.csv contains raw, field collected benthic macroinvertebrate counts classified by taxonomic hierarchy. Data were collected by Fairfax County. • Benthic_scores.csv contains benthic macroinvertebrate annual scores for 31 metrics describing assemblage richness and composition, and the Fairfax County index of biotic integrity (IBI). • Cross-sections_annual.csv contains annual cross-sectional survey data collected at the monitored cross-section at Flatlick Branch (USGS Station ID 01656903). • Cross-sections_average.csv contains two cross-sections. Each an average of channel cross-sections in the pre-restoration (2008-2017) or post-restoration (2019-2024) periods. • Depth.csv contains an estimate of channel depth based on data collected during manual streamflow measurements from water year 2008 through 2024. • Fish.csv contains fish survey data collected by Fairfax County triennially at Flatlick Branch and Frog Branch. • Floodplain_innundation_events.csv contains gage height data used to quantify the number and duration of events when streamflows exceeded the left bank elevation, causing floodplain inundation. • Floodplain_innundation_event_duration.csv contains the duration, in hours, of each event when streamflows exceeded the left bank elevation, causing floodplain inundation. • Floodplain_innundation_annual_duration.csv contains the total duration, in hours, of each water year when streamflows exceeded the left bank elevation, causing floodplain inundation. • Habitat.csv contains habitat metrics collected by Fairfax County annually at Flatlick Branch and Frog Branch. Habitat assessments are conducted in the late summer or early fall

The United States Geological Survey Virginia and West Virginia Water Science Center (USGS VA-WV-WSC) and Fairfax County assembled this data release in support of ongoing USGS VA-WV-WSC monitoring and evaluations of stream conditions overtime of two previously restored, urban-suburban streams in Reston, Virginia – Snakeden Branch and The Glade. The aquatic benthic macroinvertebrate, fish, and habitat sampling and surveying were conducted on the same eight, 100-meter stream reaches (four reaches in Snakeden Branch and four reaches in The Glade) by the USGS VA-WV-WSC. Aquatic benthic macroinvertebrate sampling and physical habitat surveys were conducted in both Spring and Fall of 2021 and a fish survey was conducted in the Summer 2021. Data provided are of five general types: 1. Site locations and characteristics for each of the eight sampling and surveying sites within the two monitored streams; 2. Benthic macroinvertebrate identifications and analytical laboratory results; 3. Fairfax County benthic macroinvertebrate Index of Biotic Integrity (IBI) scores and individual metric results; 4. Fish assemblages, and; 5. Physical habitat measurements. The metadata file “Metadata_for_Reston_Ecological_Data.xml” contains important information pertaining to the attributes of each entity of data, field and laboratory methods, and caveats associated with the Fall benthic macroinvertebrate IBI and metric scores. The "README.txt" file contains a description of each file contained in this data release. This database contains the aquatic benthic macroinvertebrate taxonomic identification and abundance data derived from samples collected at each of the eight total reaches within Snakeden Branch and The Glade in Fall and Spring of calendar year 2021. Samples were collected by the USGS VA-WV-WSC using the Fairfax County standard operating procedures (FCSOP) and specimen identification and abundance calculations were performed by a third-party laboratory. Fairfax County benthic macroinvertebrate IBI scores and individual metrics were calculated by Fairfax County following FCSOP. It is important to note for this data release that the IBI scores presented for Fall samples have caveats associated with them and the ratings (e.g. Excellent, Good, Fair, etc.) for the Fall samples have been intentionally excluded. Please read the methods section of the “Metadata_for_Reston_Ecological_Data.xml” file carefully for further explanation. This data release also contains the fish assemblages data, collected during the Summer of 2021, from the eight total reaches in Snakeden Branch and The Glade. Electrofishing surveys were conducted following FCSOP by the USGS VA-WV-WSC to obtain these results. Finally, this data release contains the physical habitat data surveyed in both Fall and Spring of 2021. Multiple habitat metrics were measured throughout each of the eight total reaches on Snakeden Branch and The Glade.