Field measurements of saturated hydraulic conductivity were used to characterize the streambed permeability for two reaches of the lower Merced River in California's Central Valley to support research intended to evaluate the extent to which large-scale restoration projects provided improved salmon spawning habitat. A related goal of this study was to improve our understanding of the geomorphic factors influencing spawning site selection by salmon. Saturated hydraulic conductivity, denoted by K, was measured with a backpack permeameter and modified Mark VI groundwater standpipe using the constant head method of Terhune [1958]. For each reach, permeameter measurements were collected at ten sites spanning a single pool-riffle transition.

Surveys of channel and floodplain topography were used to characterize the morphology of two reaches of the lower Merced River in California's Central Valley and to parameterize a hydraulic model. These data were collected to support research intended to evaluate the extent to which large-scale restoration projects provided improved salmon spawning habitat. A related goal of this study was to improve our understanding of the geomorphic factors influencing spawning site selection by salmon. At the Merced River Ranch field site, river channel and floodplain topography was measured using a combination of real-time kinematic (RTK) GPS for wadable parts of the channel, an echo sounder for deep pools, and photogrammetry on dry land [CFS, 2013]. The raw point data were used to generate a triangular irregular network (TIN) and the TIN was converted to a 1 m raster using natural neighbor interpolation. For the 2.5 km long Robinson Reach field site, bed topography was surveyed during the summer of 2012 using real-time kinematic (RTK) GPS, with a mean cross-section spacing of 7 m. The original survey points were interpolated to form a continuous surface using kriging methods developed for curved river channels [Legleiter and Kyriakidis, 2008]. The result of the kriging was a digital elevation model (DEM) of the river channel and 10 m of the floodplain adjacent to each bank, with a spatial resolution of 1 m.

IMPORTANT NOTE: This dataset includes spatial locations where streamflow permanence observations (continuous flow, discontinuous flow, and dry) were recorded using the FLOwPER (FLOw PERmanence) field survey available in the Survey 123. Additional information to describe the field conditions are included as part of the survey. Field observations in the FLOwPER Database have not been processed for quality control including spatial data accuracy or association with a stream network such as the National Hydrography Dataset. Streamflow permanence observations are collected from several governmental and non-governmental organizations on a continuing basis. This data release is formatted as a shapefile that includes streamflow permanence observations with associated information. Photographs associated with FLOwPER data points are included. The spatial extent of this dataset is the western United States and includes the following states: Oregon, Washington, Idaho, Nevada, and California.

This Data Release provides supporting data to characterize and identify influences of streamflow permanence in headwater streams in the Huachuca Mountains, Arizona, U.S.A. Relative conductivity as a proxy for surface water presence was measured in headwater streams in the Huachuca Mountains from 2010-2014. These data are summarized as mean daily values. Geologic influences on the timing of surface flow conditions were evaluated. The Data Release includes the following components that are zipped files containing both data and metadata files. 1.) Daily mean relative conductivity values for electrical resistivity sensors installed in headwater streams in the Huachuca Mountains from 2010-2014 and the geographic coordinates of the sensor locations. 2.) Spatial data in the form of surficial geology, faults, and locations of springs and wells for the Huachuca Mountains that were manually digitized from plate 1 of Brown and others (1966). Brown, S. G., Davidson, E. S., Kister, L. R., & Thomsen, B. W. (1966). Water Resources of Fort Huachuca Military Reservation, Southeastern Arizona (No. 1819-D). US Government Printing Office, https://doi.org/10.3133/wsp1819D.

This Data Release provides supporting data to characterize and identify influences of streamflow permanence in headwater streams in the Huachuca Mountains, Arizona, U.S.A. Relative conductivity as a proxy for surface water presence was measured in headwater streams in the Huachuca Mountains from 2010-2014. These data are summarized as mean daily values. Geologic influences on the timing of surface flow conditions were evaluated. The Data Release includes the following components that are zipped files containing both data and metadata files. 1.) Daily mean relative conductivity values for electrical resistivity sensors installed in headwater streams in the Huachuca Mountains from 2010-2014 and the geographic coordinates of the sensor locations. 2.) Spatial data in the form of surficial geology, faults, and locations of springs and wells for the Huachuca Mountains that were manually digitized from plate 1 of Brown and others (1966). Brown, S. G., Davidson, E. S., Kister, L. R., & Thomsen, B. W. (1966). Water Resources of Fort Huachuca Military Reservation, Southeastern Arizona (No. 1819-D). US Government Printing Office, https://doi.org/10.3133/wsp1819D.

Streamflow Permanence Class (SPC) rasters represent the classification of the raw streamflow permanence probabilities produced by the PRObability of Streamflow PERmanence (PROSPER) model into categorical wet and dry classes, annually for years 2004 through 2016, and overall mean. Raw probabilities were classified into a -5 (dry) to +5 (wet) scale based on the spatially variable threshold (i.e., value that predicts the wet/dry break point) and confidence interval rasters. In general, the farther a raw probability value is from the threshold value for a given pixel, the farther the categorical value is from zero for that pixel. For example, a raw probability that is less than the threshold value minus the critical value for the 95-percent confidence interval for a given pixel would be assigned an SPC value of -5. Conversely, if a raw probability is greater than the threshold value plus the critical value associated with the 95-percent confidence interval for a given pixel, it would be assigned an SPC value of 5. The PROSPER model is a GIS raster-based empirical model of probabilistic predictions of a stream channel having year-round flow for any unregulated and minimally-impaired stream channel in the Pacific Northwest region, U.S. The model provides predictions of annual streamflow permanence probabilities at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions and static physiographic variables associated with the upstream basin. Predictions correspond to pixels on the channel network consistent with the medium resolution National Hydrography Dataset channel network stream grid.

Streamflow Permanence Class (SPC) rasters represent the classification of the raw streamflow permanence probabilities produced by the PRObability of Streamflow PERmanence (PROSPER) model into categorical wet and dry classes, annually for years 2004 through 2016, and overall mean. Raw probabilities were classified into a -5 (dry) to +5 (wet) scale based on the spatially variable threshold (i.e., value that predicts the wet/dry break point) and confidence interval rasters. In general, the farther a raw probability value is from the threshold value for a given pixel, the farther the categorical value is from zero for that pixel. For example, a raw probability that is less than the threshold value minus the critical value for the 95-percent confidence interval for a given pixel would be assigned an SPC value of -5. Conversely, if a raw probability is greater than the threshold value plus the critical value associated with the 95-percent confidence interval for a given pixel, it would be assigned an SPC value of 5. The PROSPER model is a GIS raster-based empirical model of probabilistic predictions of a stream channel having year-round flow for any unregulated and minimally-impaired stream channel in the Pacific Northwest region, U.S. The model provides predictions of annual streamflow permanence probabilities at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions and static physiographic variables associated with the upstream basin. Predictions correspond to pixels on the channel network consistent with the medium resolution National Hydrography Dataset channel network stream grid.

Streamflow Permanence Class (SPC) rasters represent the classification of the raw streamflow permanence probabilities produced by the PRObability of Streamflow PERmanence (PROSPER) model into categorical wet and dry classes, annually for years 2004 through 2016, and overall mean. Raw probabilities were classified into a -5 (dry) to +5 (wet) scale based on the spatially variable threshold (i.e., value that predicts the wet/dry break point) and confidence interval rasters. In general, the farther a raw probability value is from the threshold value for a given pixel, the farther the categorical value is from zero for that pixel. For example, a raw probability that is less than the threshold value minus the critical value for the 95-percent confidence interval for a given pixel would be assigned an SPC value of -5. Conversely, if a raw probability is greater than the threshold value plus the critical value associated with the 95-percent confidence interval for a given pixel, it would be assigned an SPC value of 5. The PROSPER model is a GIS raster-based empirical model of probabilistic predictions of a stream channel having year-round flow for any unregulated and minimally-impaired stream channel in the Pacific Northwest region, U.S. The model provides predictions of annual streamflow permanence probabilities at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions and static physiographic variables associated with the upstream basin. Predictions correspond to pixels on the channel network consistent with the medium resolution National Hydrography Dataset channel network stream grid.

IMPORTANT NOTE: More recent versions of these data release are available at this link. This dataset includes spatial locations where streamflow permanence observations (continuous flow, discontinuous flow, and dry) were recorded using the FLOwPER (FLOw PERmanence) field survey available in the Survey 123 and S1 mobile application. Additional information to describe the field conditions are included as part of the survey. Field observations in the FLOwPER Database have not been processed for quality control including spatial data accuracy or association with a stream network such as the National Hydrography Dataset. Streamflow permanence observations are collected from several governmental and non-governmental organizations on a continuing basis. This data release is formatted as a shapefile that includes streamflow permanence observations with associated information. Photographs associated with FLOwPER data points are included.

IMPORTANT NOTE: More recent versions of these data release are available at this link. This dataset includes spatial locations where streamflow permanence observations (continuous flow, discontinuous flow, and dry) were recorded using the FLOwPER (FLOw PERmanence) field survey available in the Survey 123 and S1 mobile application. Additional information to describe the field conditions are included as part of the survey. Field observations in the FLOwPER Database have not been processed for quality control including spatial data accuracy or association with a stream network such as the National Hydrography Dataset. Streamflow permanence observations are collected from several governmental and non-governmental organizations on a continuing basis. This data release is formatted as a shapefile that includes streamflow permanence observations with associated information. Photographs associated with FLOwPER data points are included.