Filters: partyWithName: David P Hockman-Wert (X) > partyWithName: Roy Sando (X)
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This dataset includes spatial locations in the Pacific Northwest where streamflow observations were recorded. For the purpose of this investigation, all streamflow observations were converted into wet or dry indicator values.
Categories: Data;
Tags: California,
Climatology,
Data Visualization & Tools,
Data Visualization & Tools,
Decision-Making Support and Tools,
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...
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...
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