Hydrologic reconnaissance of Mineral Creek near Silverton, Colo., was conducted from June 25-27, 2020. Both banks of Mineral Creek and the adjacent hillsides were walked, starting near the ghost town of Chattanooga and proceeding downstream to the confluence of Mineral Creek with the Middle Fork of Mineral Creek. The purpose of this reconnaissance was to identify areas of emergent groundwater on the right (EGR) and left (EGL) banks, a task that was accomplished by following observed surface flows (seeps and springs) upgradient to the point at which they emanated from the subsurface. Coordinates, using a handheld global positioning system (GPS) device, and photographs were obtained at these locations of emergent groundwater. Water temperature and specific conductance were measured at a subset of locations. Elevation for each location was subsequently assigned using an existing LIDAR data set. Similar procedures were followed at additional sites such as where surface flows entered Mineral Creek (right (RBI) and left (LBI) bank inflows) and the main stem of Mineral Creek (STR). These data are provided in a visual format through the associated KMZ file (224 MB), which provides an HTML formatted pop-up of unique point data and photograph when a waypoint is selected. This release is complementary to a synoptic study conducted in 1999 (Kimball and others, 2007). References: Kimball, B.A., Walton-Day, K. and Runkel, R.L., 2007, Quantification of metal loading by tracer injection and synoptic sampling, 1996-2000, chap. E9 of Church, S.E., von Guerard, P., and Finger, S.E., eds., Integrated investigations of environmental effects of historical mining in the Animas River Watershed, San Juan County, Colorado: U.S. Geological Survey Professional Paper 1651, p. 417–495. https://doi.org/10.3133/pp1651.

Near-surface geophysical data from within the Bonita Peak Mining District in Silverton, Colorado, USA are presented. These data were collected in 2019. The data include fiber optic distributed temperature sensing (FO-DTS) and frequency domain electromagnetic induction (FDEM) data collected in and around roughly 1 km reaches of Cement Creek and California Gulch. Additional data, including ground penetrating radar (GPR) and self potential (SP), were gathered from a peatland that intercepts acid mine drainage from Mogul Mine into Cement Creek. The peatland is located off the eastern bank of Cement Creek in the northern portion of the reach surveyed with FO-DTS and FDEM. In 2021, an FO-DTS, FDEM, and magnetometer (MAG) dataset were collected along both banks of an approximate 3-4 km reach of the Animas River, spanning from Arrastra Gulch upstream to USGS gage 09358000.

This U.S. Geological Survey (USGS) data release contains data from stream water, groundwater, and soil samples collected in 2019 and 2020 in the North Quartz Creek watershed in central Colorado. Fourteen streambank wells were installed in pairs at seven locations in August 2020 to capture the emerging groundwater from the left bank and right banks (relative to downstream-facing direction) and a synoptic sampling campaign was conducted to quantify metal contributions to the stream. A continuous, instream injection of sodium bromide (NaBr) was initiated at the head of the 5 km study reach several days prior to the synoptic sampling campaign and maintained throughout the duration of the study. Bromide concentrations were subsequently used to determine streamflow in the primary study reach (upper 1.3 km) using the tracer-dilution method, and as an indicator of hydrologic connections between North Quartz Creek and subsurface water. Streamflow was quantified in a secondary study reach (lower 3.7 km) using data from a series of sodium chloride slug additions wherein specific conductivity readings were used as a surrogate for the tracer concentration. Surface water samples were collected along North Quartz Creek including inflows from the left (LBI) and right (RBI) banks. Soil and sediment samples were collected along the transport path from source material (natural weathering and mine tailings/mine drainage) to the stream.

This U.S. Geological Survey (USGS) data release contains data from stream water, groundwater, and soil samples collected in 2019 and 2020 in the North Quartz Creek watershed in central Colorado. Fourteen streambank wells were installed in pairs at seven locations in August 2020 to capture the emerging groundwater from the left bank and right banks (relative to downstream-facing direction) and a synoptic sampling campaign was conducted to quantify metal contributions to the stream. A continuous, instream injection of sodium bromide (NaBr) was initiated at the head of the 5 km study reach several days prior to the synoptic sampling campaign and maintained throughout the duration of the study. Bromide concentrations were subsequently used to determine streamflow in the primary study reach (upper 1.3 km) using the tracer-dilution method, and as an indicator of hydrologic connections between North Quartz Creek and subsurface water. Streamflow was quantified in a secondary study reach (lower 3.7 km) using data from a series of sodium chloride slug additions wherein specific conductivity readings were used as a surrogate for the tracer concentration. Surface water samples were collected along North Quartz Creek including inflows from the left (LBI) and right (RBI) banks. Soil and sediment samples were collected along the transport path from source material (natural weathering and mine tailings/mine drainage) to the stream.

This dataset contains environmental tracer data from surface water and groundwater samples collected by the U.S. Geological Survey in Redwell Basin, an alpine watershed in the Elk Mountains near the town of Crested Butte, Colorado. The basin is underlain by interbedded shale and sandstone that have been variably hydrothermally altered and silicified by local magmatic intrusions. Samples were collected from 2017 to 2019 from bedrock monitoring wells completed at multiple depths, shallow hand-installed piezometers and mini boreholes, springs, mine adits, and streams. The tracer data include stable isotopes of water (oxygen-18 and deuterium), tritium, dissolved noble gases (He, Ne, Ar, Kr, Xe, and helium-3/helium-4 ratio), sulfur hexafluoride, and other dissolved atmospheric gases.

This point dataset contains geologic information concerning regolith thickness and top-of-bedrock altitude at selected well and test-hole locations in the Lower Gunnison River Basin in Delta, Montrose, Ouray, and Gunnison Counties, Colorado. Regolith-thickness data were compiled from lithologic logs of wells and boreholes reported by the Colorado Division of Water Resources, U.S. Geological Survey, and Bureau of Reclamation. Bedrock-altitude values were computed from the bedrock altitude raster dataset (bralt). The U.S. Geological Survey prepared this dataset in cooperation with the Colorado Water Conservation Board.

This point dataset contains geologic information concerning regolith thickness and top-of-bedrock altitude at selected well and test-hole locations in the Lower Gunnison River Basin in Delta, Montrose, Ouray, and Gunnison Counties, Colorado. Regolith-thickness data were compiled from lithologic logs of wells and boreholes reported by the Colorado Division of Water Resources, U.S. Geological Survey, and Bureau of Reclamation. Bedrock-altitude values were computed from the bedrock altitude raster dataset (bralt). The U.S. Geological Survey prepared this dataset in cooperation with the Colorado Water Conservation Board.

This data collection includes spatial and tabular datasets related to the delineation and characterization of surface moisture zones (SMZs) in the vicinity of springs mapped in the National Hydrography Dataset (NHD) in southeastern Oregon using time-series analysis of Normalized Difference Vegetation Index (NDVI) data derived from Landsat Thematic Mapper 5 imagery from 1985-2011. The study area is within and adjacent to the Steens Mountain Cooperative Management and Protection Area (CMPA), which is a protected area of approximately 1,732 km2 managed by the Bureau of Land Management (BLM) in Harney County, Oregon. Within or adjacent to the Steens Mountain CMPA, approximately 1,100 springs are mapped in the NHD, however very little hydrologic data exists for these springs. Data in this data release were produced using a set of scripts written in the R programming language, which are also included in this data release (see ‘larger works citation’ to access R scripts and associated metadata). These data processing scripts, data products, and associated metadata provide documentation for a novel remote-sensing based approach to assess the potential resilience of spring-dependent ecosystems to inter-annual changes in water availability. This approach uses time-series analysis of NDVI to (1) delineate SMZs in the vicinity of mapped springs in a semi-arid sage-steppe landscape, (2) derive quantitative indicators of the relative resilience of these SMZs to inter-annual changes in water availability, and (3) synthesize these indicators into an overall resilience score for each cluster of springs. Specifically, for 39 spring clusters in Harney County, Oregon, USA, these scripts process Landsat-derived NDVI and precipitation data from 1985-2011 to derive 7 potential indicators of SMZ resilience to water-cycle changes. For detailed information on the resilience indicators, including their conceptual basis, methods of calculation, and interpretation, see Cartwright and Johnson (2018) and the R scripts and their associated metadata in this data release. References: Cartwright and Johnson (2018), Springs as hydrologic refugia in a changing climate? A remote sensing approach. Ecosphere X(X).

This data collection includes spatial and tabular datasets related to the delineation and characterization of surface moisture zones (SMZs) in the vicinity of springs mapped in the National Hydrography Dataset (NHD) in southeastern Oregon using time-series analysis of Normalized Difference Vegetation Index (NDVI) data derived from Landsat Thematic Mapper 5 imagery from 1985-2011. The study area is within and adjacent to the Steens Mountain Cooperative Management and Protection Area (CMPA), which is a protected area of approximately 1,732 km2 managed by the Bureau of Land Management (BLM) in Harney County, Oregon. Within or adjacent to the Steens Mountain CMPA, approximately 1,100 springs are mapped in the NHD, however very little hydrologic data exists for these springs. Data in this data release were produced using a set of scripts written in the R programming language, which are also included in this data release (see ‘larger works citation’ to access R scripts and associated metadata). These data processing scripts, data products, and associated metadata provide documentation for a novel remote-sensing based approach to assess the potential resilience of spring-dependent ecosystems to inter-annual changes in water availability. This approach uses time-series analysis of NDVI to (1) delineate SMZs in the vicinity of mapped springs in a semi-arid sage-steppe landscape, (2) derive quantitative indicators of the relative resilience of these SMZs to inter-annual changes in water availability, and (3) synthesize these indicators into an overall resilience score for each cluster of springs. Specifically, for 39 spring clusters in Harney County, Oregon, USA, these scripts process Landsat-derived NDVI and precipitation data from 1985-2011 to derive 7 potential indicators of SMZ resilience to water-cycle changes. For detailed information on the resilience indicators, including their conceptual basis, methods of calculation, and interpretation, see Cartwright and Johnson (2018) and the R scripts and their associated metadata in this data release. References: Cartwright and Johnson (2018), Springs as hydrologic refugia in a changing climate? A remote sensing approach. Ecosphere X(X).

This dataset consists of altitude values representing the top surface (in feet) of well-consolidated bedrock at the base of the shallow groundwater system in the Lower Gunnison River Basin in Delta, Montrose, Ouray, and Gunnison Counties, Colorado. Bedrock-altitude values were computed as the difference between land-surface altitude and the thickness of regolith sediments represented by dataset rglth. The U.S. Geological Survey prepared this dataset in cooperation with the Colorado Water Conservation Board.