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Probability of Streamflow Permanence (PROSPER) Model Output Layers

Probabilities of annual streamflow permanence throughout the Pacific Northwest


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Sando, R., and Hockman-Wert, D.P., 2019, Probability of Streamflow Permanence (PROSPER) Model Output Layers (ver. 2.0, February 2019): U.S. Geological Survey data release,


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 [...]

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RevisionHistory2.0_PROSPER_output_layers_overview.txt 1.08 KB 8.59 MB
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This work provides end users with streamflow permanence conditions for the Pacific Northwest region at unprecedented spatial and temporal resolutions, representing the largest dynamic stream mapping effort the authors are aware of, and which is readily available for direct application to water resources. The availability of temporally dynamic streamflow permanence classifications at a regional scale not only allows for improved understanding of the spatiotemporal dynamics of streamflow permanence and the physiographic and hydroclimatic variables that control streamflow permanence, but also serves as an immediate tool to water resource managers who are increasingly challenged by limited knowledge of where and when streams and rivers maintain streamflow.


Spatial Services

ScienceBase WMS


  • Forest and Rangeland Ecosystem Science Center (FRESC)
  • National and Regional Climate Adaptation Science Centers
  • Northwest CASC



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DOI doi:10.5066/F77M0754

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