This data release contains summary metrics describing stream stage, stream water temperature, and short-term climate conditions (daily precipitation and air temperature) for 30 streams spanning gradients of forest and pasture land uses and agricultural best management practice implementation in the Shenandoah Valley region of Virginia and West Virginia, USA. This setting is the first of four settings or "typologies" that will be assessed for the USGS Chesapeake Stream Team project. High-frequency stage and water temperature (5-minute data), and air temperature (30-minute data) were measured by the U.S. Geological Survey (USGS) from May 2021 to December 2021 and are available on the USGS National Water Information System (NWIS). Stream stage, water temperature, and air temperature data for each of the 30 sites were downloaded from NWIS. Additional daily air temperature and precipitation data were acquired from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate data website. Air temperature and water temperature data were used to compute stream water temperature metrics describing stream temperature conditions in each stream during the monitoring period. Stream stage and precipitation data were used to derive stream stage metrics describing stage conditions (a surrogate for flow) for each stream during the monitoring period. Precipitation and air temperature data from PRISM were also used to compute air temperature metrics and precipitation metrics describing climate conditions during the monitoring period. The metrics include: Air temperature metrics - Mean daily minimum, mean, and maximum air temperature Precipitation metrics - Total precipitation depth - Maximum daily precipitation depth - Average precipitation depth per days with precipitation - Frequency of precipitation days Stream stage metrics - Number of runoff events - Frequency of runoff events - Standard deviation in unit-value stage - Coefficient of variation of unit-value stage Stream water temperature metrics - Coefficient of variation of mean and maximum daily water temperatures - Number of days with temperatures of 20 or 25 degrees Celsius or greater - Duration of time above 20 or 25 degrees Celsius or greater - Maximum of seven-day moving average of daily maximum temperature - Mean of daily minimum, maximum, and daily water temperature range - A thermal sensitivity metric, which is the slope estimate from linear regression model of mean daily water temperature versus mean daily air temperature This data release contains six files: 1. "Readme.pdf": This is an expanded narrative describing the methods by which the input data were compiled and screened, and metrics were computed 2. "typology_1_temperature_stage_climate_metric_data_dictionary.csv": This file contains descriptions of each metric and the time periods for which they were computed in the “typology_1_temperature_stage_climate_summary_metrics.csv" file 3. "typology_1_temperature_stage_climate_summary_metrics.csv": This file contains stream temperature metrics, stage metrics, and climate summary metrics for each of the 30 stream sites for different time periods within the overall monitoring period. 4. "typology_1_input_data_high_frequency_temperature_and_stage.zip": This zipped folder contains 30 .csv files, which contain the high-frequency stage, water temperature, and air temperature data collected at each of the 30 stream sites. The file names include the siteID, which is the four-letter site identification listed in the "typology_1_temperature_stage_climate_summary_metrics.csv" file. 5. "typology_1_input_data_daily_climate.csv": This file contains daily climate estimates (precipitation depth, daily minimum, mean, and maximum air temperatures) from PRISM paired to each of the 30 sites. 6. "typology_1_runoff_events.csv": This file contains the stage rise and precipitation data used for some of the stage metric computations.

This data release contains summary metrics describing stream stage, stream water temperature, and short-term climate conditions (daily precipitation and air temperature) for 30 streams spanning gradients of forest and row-crop land uses and agricultural best management practice implementation in the Delmarva Peninsula of Delaware, Maryland, and Virginia, USA. This setting is the second of four settings, or "typologies," that will be assessed for the U.S. Geological Survey (USGS) Chesapeake Stream Team project. High-frequency stage, water temperature, and air temperature (approximately 15-minute data) were measured by the USGS from March 2022 to September 2022 and are available at McFarland and others (2024). Additional daily air temperature and precipitation data were acquired from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate data website (PRISM Climate Group, 2014). Air temperature and water temperature data were used to compute stream water temperature metrics describing stream temperature conditions in each stream during the monitoring period. Stream stage and precipitation data were used to compute stream stage metrics describing stage conditions (a surrogate for streamflow) for each stream during the monitoring period. Precipitation and air temperature data from PRISM were also used to compute air temperature metrics and precipitation metrics describing climate conditions during the monitoring period. The metrics include: Air temperature metrics - Mean daily minimum, mean, and maximum air temperature Precipitation metrics - Total precipitation depth - Maximum daily precipitation depth - Average precipitation depth per days with precipitation - Frequency of precipitation days Stream stage metrics - Number of runoff events - Frequency of runoff events - Standard deviation in unit-value stage Stream water temperature metrics - Coefficient of variation of mean and maximum daily water temperatures - Number of days with temperatures of 20 or 25 degrees Celsius or greater - Duration of time above 20 or 25 degrees Celsius or greater - Maximum of seven-day moving average of daily maximum temperature - Mean of daily minimum, maximum, and daily water temperature range - A thermal sensitivity metric, which is the slope estimate from linear regression model of mean daily water temperature versus mean daily air temperature This data release contains six files: 1. "Readme.pdf": This is an expanded narrative describing the methods by which the input data were compiled and screened, and metrics were computed. 2. "typology_2_temperature_stage_climate_metric_data_dictionary.csv": This file contains descriptions of each metric and the time periods for which they were computed in the "typology_2_temperature_stage_climate_summary_metrics.csv" file. 3. "typology_2_temperature_stage_climate_summary_metrics.csv": This file contains stream temperature metrics, stage metrics, and climate summary metrics for each of the 30 stream sites for different time periods within the overall monitoring period. 4. "typology_2_input_data_high_frequency_temperature_and_stage.zip": This zipped folder contains 30 .csv files, which contain the high-frequency stage, water temperature, and air temperature data collected at each of the 30 stream sites. The file names include the SiteID, a unique four-letter site identification listed in the "typology_2_temperature_stage_climate_summary_metrics.csv" file. 5. "typology_2_input_data_daily_climate.csv": This file contains daily climate estimates (precipitation depth, daily minimum, mean, and maximum air temperatures) from PRISM paired to each of the 30 sites. 6. "typology_2_runoff_events.csv": This file contains the stage rise and precipitation data used for some of the stage metric computations.

This data release contains summary metrics describing stream stage, stream water temperature, and short-term climate conditions (daily precipitation and air temperature) for 30 streams spanning gradients of forest and pasture land uses and agricultural best management practice implementation in the Shenandoah Valley region of Virginia and West Virginia, USA. This setting is the first of four settings or "typologies" that will be assessed for the USGS Chesapeake Stream Team project. High-frequency stage and water temperature (5-minute data), and air temperature (30-minute data) were measured by the U.S. Geological Survey (USGS) from May 2021 to December 2021 and are available on the USGS National Water Information System (NWIS). Stream stage, water temperature, and air temperature data for each of the 30 sites were downloaded from NWIS. Additional daily air temperature and precipitation data were acquired from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate data website. Air temperature and water temperature data were used to compute stream water temperature metrics describing stream temperature conditions in each stream during the monitoring period. Stream stage and precipitation data were used to derive stream stage metrics describing stage conditions (a surrogate for flow) for each stream during the monitoring period. Precipitation and air temperature data from PRISM were also used to compute air temperature metrics and precipitation metrics describing climate conditions during the monitoring period. The metrics include: Air temperature metrics - Mean daily minimum, mean, and maximum air temperature Precipitation metrics - Total precipitation depth - Maximum daily precipitation depth - Average precipitation depth per days with precipitation - Frequency of precipitation days Stream stage metrics - Number of runoff events - Frequency of runoff events - Standard deviation in unit-value stage - Coefficient of variation of unit-value stage Stream water temperature metrics - Coefficient of variation of mean and maximum daily water temperatures - Number of days with temperatures of 20 or 25 degrees Celsius or greater - Duration of time above 20 or 25 degrees Celsius or greater - Maximum of seven-day moving average of daily maximum temperature - Mean of daily minimum, maximum, and daily water temperature range - A thermal sensitivity metric, which is the slope estimate from linear regression model of mean daily water temperature versus mean daily air temperature This data release contains six files: 1. "Readme.pdf": This is an expanded narrative describing the methods by which the input data were compiled and screened, and metrics were computed 2. "typology_1_temperature_stage_climate_metric_data_dictionary.csv": This file contains descriptions of each metric and the time periods for which they were computed in the “typology_1_temperature_stage_climate_summary_metrics.csv" file 3. "typology_1_temperature_stage_climate_summary_metrics.csv": This file contains stream temperature metrics, stage metrics, and climate summary metrics for each of the 30 stream sites for different time periods within the overall monitoring period. 4. "typology_1_input_data_high_frequency_temperature_and_stage.zip": This zipped folder contains 30 .csv files, which contain the high-frequency stage, water temperature, and air temperature data collected at each of the 30 stream sites. The file names include the siteID, which is the four-letter site identification listed in the "typology_1_temperature_stage_climate_summary_metrics.csv" file. 5. "typology_1_input_data_daily_climate.csv": This file contains daily climate estimates (precipitation depth, daily minimum, mean, and maximum air temperatures) from PRISM paired to each of the 30 sites. 6. "typology_1_runoff_events.csv": This file contains the stage rise and precipitation data used for some of the stage metric computations.

This data release contains summary metrics describing stream stage, stream water temperature, and short-term climate conditions (daily precipitation and air temperature) for 30 streams spanning gradients of forest and row-crop land uses and agricultural best management practice implementation in the Delmarva Peninsula of Delaware, Maryland, and Virginia, USA. This setting is the second of four settings, or "typologies," that will be assessed for the U.S. Geological Survey (USGS) Chesapeake Stream Team project. High-frequency stage, water temperature, and air temperature (approximately 15-minute data) were measured by the USGS from March 2022 to September 2022 and are available at McFarland and others (2024). Additional daily air temperature and precipitation data were acquired from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climate data website (PRISM Climate Group, 2014). Air temperature and water temperature data were used to compute stream water temperature metrics describing stream temperature conditions in each stream during the monitoring period. Stream stage and precipitation data were used to compute stream stage metrics describing stage conditions (a surrogate for streamflow) for each stream during the monitoring period. Precipitation and air temperature data from PRISM were also used to compute air temperature metrics and precipitation metrics describing climate conditions during the monitoring period. The metrics include: Air temperature metrics - Mean daily minimum, mean, and maximum air temperature Precipitation metrics - Total precipitation depth - Maximum daily precipitation depth - Average precipitation depth per days with precipitation - Frequency of precipitation days Stream stage metrics - Number of runoff events - Frequency of runoff events - Standard deviation in unit-value stage Stream water temperature metrics - Coefficient of variation of mean and maximum daily water temperatures - Number of days with temperatures of 20 or 25 degrees Celsius or greater - Duration of time above 20 or 25 degrees Celsius or greater - Maximum of seven-day moving average of daily maximum temperature - Mean of daily minimum, maximum, and daily water temperature range - A thermal sensitivity metric, which is the slope estimate from linear regression model of mean daily water temperature versus mean daily air temperature This data release contains six files: 1. "Readme.pdf": This is an expanded narrative describing the methods by which the input data were compiled and screened, and metrics were computed. 2. "typology_2_temperature_stage_climate_metric_data_dictionary.csv": This file contains descriptions of each metric and the time periods for which they were computed in the “typology_2_temperature_stage_climate_summary_metrics.csv" file. 3. "typology_2_temperature_stage_climate_summary_metrics.csv": This file contains stream temperature metrics, stage metrics, and climate summary metrics for each of the 30 stream sites for different time periods within the overall monitoring period. 4. "typology_2_input_data_high_frequency_temperature_and_stage.zip": This zipped folder contains 30 .csv files, which contain the high-frequency stage, water temperature, and air temperature data collected at each of the 30 stream sites. The file names include the SiteID, a unique four-letter site identification listed in the "typology_2_temperature_stage_climate_summary_metrics.csv" file. 5. "typology_2_input_data_daily_climate.csv": This file contains daily climate estimates (precipitation depth, daily minimum, mean, and maximum air temperatures) from PRISM paired to each of the 30 sites. 6. "typology_2_runoff_events.csv": This file contains the stage rise and precipitation data used for some of the stage metric computations.

This Data Release provides hourly records of air and water temperature within 5 watersheds (Beaver Creek, Dry River, Mossy Creek, Passage Creek & Spout Run) in the Shenandoah Valley, VA in the summer of 2017. Data loggers were deployed and retrieved by Trout Unlimited personnel and volunteers.

This Data Release provides hourly records of air and water temperature within 5 watersheds (Beaver Creek, Dry River, Mossy Creek, Passage Creek & Spout Run) in the Shenandoah Valley, VA in the summer of 2017. Data loggers were deployed and retrieved by Trout Unlimited personnel and volunteers.

This database contains hourly water and air temperature data from 120 site locations within 17 watersheds in Shenandoah National Park, Virginia between June 23,2012 and October 25, 2016. The database includes three separate table files (i.e, entities) in csv format: 1) Water temperature data, 2) air temperature data, and 3) site location data. All temperature data were collected using HOBO Pro V2 thermographs (accuracy = 0.2 degrees Celsius, drift = <0.1 degrees Celsius per year per year). These raw data were summarized to mean daily air and water temperatures for the analysis used in Johnson et al. (cited above).

This database contains hourly water and air temperature data from 120 site locations within 17 watersheds in Shenandoah National Park, Virginia between June 23,2012 and October 25, 2016. The database includes three separate table files (i.e, entities) in csv format: 1) Water temperature data, 2) air temperature data, and 3) site location data. All temperature data were collected using HOBO Pro V2 thermographs (accuracy = 0.2 degrees Celsius, drift = <0.1 degrees Celsius per year per year). These raw data were summarized to mean daily air and water temperatures for the analysis used in Johnson et al. (cited above).

In cooperation with the West Virginia Division of Transportation, Department of Highways (WVDOH), precipitation and streamflow were measured at four streamgages in West Virginia to compute time of concentration (Tc) and compare it to Tc estimates made using accepted methods. Precipitation and streamflow data were collected during 2017-2020. Storms were identified and classified through an iterative process relying heavily on inspection of graphs. Three hydrograph time metrics that represent Tc were computed for this study: time to rise, time to recede from a high point on the hydrograph to an inflection on the recession, and the time between an inflection on the hyetograph and an inflection on the recession of the hydrograph (PI-to-RI). Seven-minute running averages were used to compute time metrics for the sites with flow data collected at 1-minute intervals. Storms were designated as beginning when precipitation began. A new storm was designated if six or more hours had passed since the previous rain. Periods of intermittent rain were classified as part of the same storm if breaks were less than six hours. Inspection of graphs confirmed that for all sites and storms, a six-hour break in precipitation was enough time for stormflows to end. Subsequent periods were included in the previous storm until another storm began or until flows reached zero. Cumulative total precipitation was computed for each storm. Storms that did not result in measurable flow were identified and excluded from further analysis. This process through this step resulted in the identification of 529 storms. Storms were then ranked by peak flow. The storms with the smallest peaks and therefore the least relevance for design were discarded. The 50 biggest storms from each site were retained for analysis. Three types of hydrograph time metrics were delineated: time to rise, time to recede, and PI-to-RI. To be counted, the rise needed to be (1) at a steady rate, (2) clearly the result of a specific spate of rain, (3) visually distinct, and (4) representative of a meaningful change in flow magnitude. Time to recede was assessed similarly, with the additional constraint that when repeated or sustained rain fell during the recession and caused flow to rise, the event was excluded. The time between PI-to-RI was determined as the difference between a (1) final inflection on the hyetograph before a visually distinct storm peak and (2) the inflection on the receding limb of the hydrograph from a steep decrease in stormflow to a part of the hydrograph with a flatter slope. Hydrograph events were included in analyses if (1) their maximum values were above the flow threshold for the site, (2) the event was not affected by snow, (3) the slope of the rise or recession was consistent and steady during a relevant part of an event, (4) the flow record during the hydrograph event was complete without estimated values, (5) the event in question represented a meaningful change in flow, (6) for recessions, rain that continued while flow receded was minimal and did not appear to interrupt the recession with secondary rises in flow, and (7) whether changes between successive unit flow measurements during the hydrograph event were primarily either increases or decreases, indicating it was primarily stormflow, or largely stable, which characterized minor rises and recessions that exceeded flow thresholds only because they began when baseflow was already high. Quality-assurance metrics were developed and computed to show how well the hydrograph time metrics met these criteria; these metrics are included in this data release.

In cooperation with the West Virginia Division of Transportation, Department of Highways (WVDOH), precipitation and streamflow were measured at four streamgages in West Virginia to compute time of concentration (Tc) and compare it to Tc estimates made using accepted methods. Precipitation and streamflow data were collected during 2017-2020. Storms were identified and classified through an iterative process relying heavily on inspection of graphs. Three hydrograph time metrics that represent Tc were computed for this study: time to rise, time to recede from a high point on the hydrograph to an inflection on the recession, and the time between an inflection on the hyetograph and an inflection on the recession of the hydrograph (PI-to-RI). Seven-minute running averages were used to compute time metrics for the sites with flow data collected at 1-minute intervals. Storms were designated as beginning when precipitation began. A new storm was designated if six or more hours had passed since the previous rain. Periods of intermittent rain were classified as part of the same storm if breaks were less than six hours. Inspection of graphs confirmed that for all sites and storms, a six-hour break in precipitation was enough time for stormflows to end. Subsequent periods were included in the previous storm until another storm began or until flows reached zero. Cumulative total precipitation was computed for each storm. Storms that did not result in measurable flow were identified and excluded from further analysis. This process through this step resulted in the identification of 529 storms. Storms were then ranked by peak flow. The storms with the smallest peaks and therefore the least relevance for design were discarded. The 50 biggest storms from each site were retained for analysis. Three types of hydrograph time metrics were delineated: time to rise, time to recede, and PI-to-RI. To be counted, the rise needed to be (1) at a steady rate, (2) clearly the result of a specific spate of rain, (3) visually distinct, and (4) representative of a meaningful change in flow magnitude. Time to recede was assessed similarly, with the additional constraint that when repeated or sustained rain fell during the recession and caused flow to rise, the event was excluded. The time between PI-to-RI was determined as the difference between a (1) final inflection on the hyetograph before a visually distinct storm peak and (2) the inflection on the receding limb of the hydrograph from a steep decrease in stormflow to a part of the hydrograph with a flatter slope. Hydrograph events were included in analyses if (1) their maximum values were above the flow threshold for the site, (2) the event was not affected by snow, (3) the slope of the rise or recession was consistent and steady during a relevant part of an event, (4) the flow record during the hydrograph event was complete without estimated values, (5) the event in question represented a meaningful change in flow, (6) for recessions, rain that continued while flow receded was minimal and did not appear to interrupt the recession with secondary rises in flow, and (7) whether changes between successive unit flow measurements during the hydrograph event were primarily either increases or decreases, indicating it was primarily stormflow, or largely stable, which characterized minor rises and recessions that exceeded flow thresholds only because they began when baseflow was already high. Quality-assurance metrics were developed and computed to show how well the hydrograph time metrics met these criteria; these metrics are included in this data release.