Hydrological, biological, geomorphological, and geospatial datasets collected from the Arid West used to develop the Beta SDAM for the Arid West.

Hydrological, biological, geomorphological, and geospatial datasets collected from the Western Mountains of the United States used to develop the beta SDAM for the Western Mountains.

Hydrological, biological, geomorphological, and geospatial datasets collected from the Western Mountains of the United States used to develop the beta SDAM for the Western Mountains.

GP_betasdam Final data and code. This dataset is associated with the following publication: Eddy, M., S. Gross, K. Fritz, B. Topping, T. Nadeau, R. Edgerton, and J. Kelso. Data Supplement to Development and Evaluation of the Beta Streamflow Duration Assessment Method (SDAM) for the Great Plains (GP). U.S. Environmental Protection Agency, Washington, DC, USA, 2022.

GP_betasdam Final data and code. This dataset is associated with the following publication: Eddy, M., S. Gross, K. Fritz, B. Topping, T. Nadeau, R. Edgerton, and J. Kelso. Data Supplement to Development and Evaluation of the Beta Streamflow Duration Assessment Method (SDAM) for the Great Plains (GP). U.S. Environmental Protection Agency, Washington, DC, USA, 2022.

Reach-scale flow classifications (ephemeral , intermittent, and perennial) based on direct hydrologic data and field (biological and geomorphological) and geospatial (climate, geographical) indicators for northeastern and southeastern United States used to build random forest models to predict flow duration class. This dataset is associated with the following publication: Gross, S., M. Eddy, K. Fritz, B. Topping, T. Nadeau, R. Edgerton, R. Mazor, and K. Nicholas. Data Supplement to Development and Evaluation of the Beta Streamflow Duration Assessment Methods for the Northeast and Southeast. U.S. Environmental Protection Agency, Washington, DC, USA, 2023.

Reach-scale flow classifications (ephemeral , intermittent, and perennial) based on direct hydrologic data and field (biological and geomorphological) and geospatial (climate, geographical) indicators for northeastern and southeastern United States used to build random forest models to predict flow duration class. This dataset is associated with the following publication: Gross, S., M. Eddy, K. Fritz, B. Topping, T. Nadeau, R. Edgerton, R. Mazor, and K. Nicholas. Data Supplement to Development and Evaluation of the Beta Streamflow Duration Assessment Methods for the Northeast and Southeast. U.S. Environmental Protection Agency, Washington, DC, USA, 2023.

With the Surface Water Index of Permanence (SWIPe), we provide a standardized metric for describing one- to five-year anomalies of the annual minimum surface water extent of streams and wetlands for multiple spatial scales including basin (4-digit hydrologic unit codes [HUCs]) to subwatersheds (12-digit HUCs). Drier conditions are represented by negative SWIPe values that range from 0 to -3 standard deviations from zero, or the normal condition. SWIPe is calculated for the upper Missouri River basin using streamflow permanence probability estimates from the Probability of Streamflow Permanence for the upper Missouri River basin (PROSPERum) model and surface-water inundation observations from the Dynamic Surface Water Extent (DSWE) dataset for years 1989-2021. The upper Missouri River basin consists of four-digit HUCs 1002-1013. Intrinsic mode functions that describe overall and interannual trends in the underlying SWIPe time series, and the significance, are provided as part of this data release. SWIPe is calculated using several different cumulative distribution functions (CDFs) including generalized normal, generalized extreme value, generalized logistic, Pearson-3, Weibull, and generalized Pareto. The CDF with p-values < 0.05 based on the Kolmogorov-Smirnov (K-S) test and the lowest Akaike Information Criterion was used to model probabilities on which SWIPe is based. An empirical CDF was applied when all of the theoretical CDFs resulted in p-values > 0.05. The probabilities were standardized to have a mean around zero and standard deviation of one.

With the Surface-Water Index of Permanence (SWIPe) we provide a standardized metric for describing one- to five-year anomalies of the annual minimum surface-water extent of streams and wetlands for multiple spatial scales including basin (4-digit hydrologic unit codes [HUCs]) to subwatersheds (12-digit HUCs). Drier conditions are represented by negative SWIPE values that range from 0 to -3 standard deviations from zero, or the normal condition. SWIPe is calculated for the upper Missouri River basin using streamflow permanence probability estimates from the Probability of Streamflow Permanence for the upper Missouri River basin (PROSPERum) model and surface-water inundation observations from the Dynamic Surface Water Extent (DSWE) dataset for years 1989-2021. The upper Missouri River basin consists of four-digit HUCs 1002-1013. Intrinsic mode functions that describe overall and interannual trends in the underlying SWIPe timeseries, and the significance, are provided as part of this data release. SWIPe is calculated using several different cumulative distribution functions (CDFs) including generalized normal, generalized extreme value, generalized logistic, Pearson-3, Weibull, and generalized Pareto. The CDF with p-values < 0.05 based on Kolmogorov-Smirnov (K-S) test and the lowest the lowest Akaike Information Criterion was used to model probabilities on which SWIPe is based. An empirical CDF was applied when all of the theoretical CDFs resulted in p-values > 0.05. The probabilities were standardized to have a mean around zero and standard deviation of one.

This USGS data release presents tabular data and photos used to determine (1) the duration of flow, subsurface temperature, and concurrent infiltration along an ephemeral channel and (2) vertical change of soil moisture, texture, and pore-water chemistry in the unsaturated zone at selected locations. The data were collected to investigate the feasibility of managed aquifer recharge (MAR) for aquifer storage and recovery in Bedell Flat hydrographic area, Nevada. The supplemental data consist of 4 tabular datasets and time-lapse photographs of discharge events. Data in this release include: (1) Bird Springs channel site location information (tabular data), (2) Bird Springs channel stream stage and subsurface temperature data (tabular data), (3) Bird Springs channel temperature and flow sensor data; the latter dataset is uncalibrated electrical conductivity (EC) data used to determine the duration of stream discharge (tabular data), (4) Bird Springs channel time-lapse photographs (digital photographs), and (5) Soil moisture, texture, and chemical compositions of water extractions from bulk sediments and cores from Bedell Flat (tabular data).