Streamflow Permanence Probability (SPP) rasters represent the raw streamflow permanence probabilities produced by the PRObability of Streamflow PERmanence (PROSPER) model, annually for years 2004 through 2016, and overall mean and standard deviation. 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 Probability (SPP) rasters represent the raw streamflow permanence probabilities produced by the PRObability of Streamflow PERmanence (PROSPER) model, annually for years 2004 through 2016, and overall mean and standard deviation. 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 Probability (SPP) rasters represent the raw streamflow permanence probabilities produced by the PRObability of Streamflow PERmanence (PROSPER) model, annually for years 2004 through 2016, and overall mean and standard deviation. 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.

The U.S. Geological Survey (USGS) has developed the PRObability of Streamflow PERmanence (PROSPER) model, a GIS raster-based empirical model that provides streamflow permanence probabilities (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 annual predictions for 2004-2016 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 (Raw streamflow permanence probability rasters). Predictions correspond to pixels on the channel network consistent with the medium resolution National Hydrography Dataset channel network stream grid. Probabilities were converted to wet and dry streamflow permanence classes (Categorical wet/dry rasters) with an associated confidence (Threshold and confidence interval rasters).

The U.S. Geological Survey (USGS) has developed the PRObability of Streamflow PERmanence (PROSPER) model, a GIS raster-based empirical model that provides streamflow permanence probabilities (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 annual predictions for 2004-2016 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 (Raw streamflow permanence probability rasters). Predictions correspond to pixels on the channel network consistent with the medium resolution National Hydrography Dataset channel network stream grid. Probabilities were converted to wet and dry streamflow permanence classes (Categorical wet/dry rasters) with an associated confidence (Threshold and confidence interval rasters).

The U.S. Geological Survey (USGS) has developed the PRObability of Streamflow PERmanence (PROSPER) model, a GIS raster-based empirical model that provides streamflow permanence probabilities (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 annual predictions for 2004-2016 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 (Raw streamflow permanence probability rasters). Predictions correspond to pixels on the channel network consistent with the medium resolution National Hydrography Dataset channel network stream grid. Probabilities were converted to wet and dry streamflow permanence classes (Categorical wet/dry rasters) with an associated confidence (Threshold and confidence interval rasters).

The U.S. Geological Survey (USGS) has developed the PRObability of Streamflow PERmanence (PROSPER) model, a GIS raster-based empirical model that provides streamflow permanence probabilities (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 annual predictions for 2004-2016 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 (Raw streamflow permanence probability rasters). Predictions correspond to pixels on the channel network consistent with the medium resolution National Hydrography Dataset channel network stream grid. Probabilities were converted to wet and dry streamflow permanence classes (Categorical wet/dry rasters) with an associated confidence (Threshold and confidence interval rasters).

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.