Item talk:Q327776

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 "DOI": {
   "doi": "10.5066/f7qn661w",
   "prefix": "10.5066",
   "suffix": "f7qn661w",
   "identifiers": [],
   "alternateIdentifiers": [],
   "creators": [
     {
       "name": "Sando, Thomas R",
       "nameType": "Personal",
       "givenName": "Thomas R",
       "familyName": "Sando",
       "affiliation": [],
       "nameIdentifiers": [
         {
           "nameIdentifier": "https://orcid.org/0000-0003-0704-6258",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     },
     {
       "name": "Hockman-Wert, David",
       "nameType": "Personal",
       "givenName": "David",
       "familyName": "Hockman-Wert",
       "affiliation": [],
       "nameIdentifiers": [
         {
           "nameIdentifier": "https://orcid.org/0000-0003-2436-6237",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     }
   ],
   "titles": [
     {
       "title": "Streamflow Permanence Probability (SPP) rasters (PROSPER)"
     }
   ],
   "publisher": "U.S. Geological Survey",
   "container": {},
   "publicationYear": 2019,
   "subjects": [],
   "contributors": [],
   "dates": [
     {
       "date": "2019",
       "dateType": "Issued"
     }
   ],
   "language": null,
   "types": {
     "ris": "DATA",
     "bibtex": "misc",
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     "schemaOrg": "Dataset",
     "resourceType": "Dataset",
     "resourceTypeGeneral": "Dataset"
   },
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   "relatedItems": [],
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   "formats": [],
   "version": null,
   "rightsList": [],
   "descriptions": [
     {
       "description": "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.",
       "descriptionType": "Abstract"
     }
   ],
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   "created": "2019-02-12T22:56:21.000Z",
   "registered": "2019-02-12T22:56:22.000Z",
   "published": "2019",
   "updated": "2020-07-29T04:49:20.000Z"
 }

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