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{

 "DOI": {
   "doi": "10.5066/p946fw28",
   "identifiers": [],
   "creators": [
     {
       "name": "Legleiter, Carl J.",
       "nameType": "Personal",
       "givenName": "Carl J.",
       "familyName": "Legleiter",
       "affiliation": [],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0003-0940-8013",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     },
     {
       "name": "Harrison, Lee R.",
       "nameType": "Personal",
       "givenName": "Lee R.",
       "familyName": "Harrison",
       "affiliation": [],
       "nameIdentifiers": [
         {
           "schemeUri": "https://orcid.org",
           "nameIdentifier": "https://orcid.org/0000-0002-5219-9280",
           "nameIdentifierScheme": "ORCID"
         }
       ]
     }
   ],
   "titles": [
     {
       "title": "Digital elevation models (DEMs) and field measurements of flow velocity used to develop and test a multidimensional hydrodynamic model for a reach of the upper Sacramento River in northern California"
     }
   ],
   "publisher": "U.S. Geological Survey",
   "container": {},
   "publicationYear": 2022,
   "subjects": [
     {
       "subject": "Aquatic Biology, Geomorphology, Hydrology, Remote Sensing, Water Resources"
     }
   ],
   "contributors": [],
   "dates": [
     {
       "date": "2022",
       "dateType": "Issued"
     }
   ],
   "language": null,
   "types": {
     "ris": "DATA",
     "bibtex": "misc",
     "citeproc": "dataset",
     "schemaOrg": "Dataset",
     "resourceType": "Dataset",
     "resourceTypeGeneral": "Dataset"
   },
   "relatedIdentifiers": [
     {
       "relationType": "IsCitedBy",
       "relatedIdentifier": "10.1029/2022wr033097",
       "relatedIdentifierType": "DOI"
     }
   ],
   "relatedItems": [],
   "sizes": [],
   "formats": [],
   "version": null,
   "rightsList": [],
   "descriptions": [
     {
       "description": "This data release includes the input topographic data sets, model parameters, and validation field measurements of flow velocity used to develop and test multidimensional hydraulic models for a reach of the upper Sacramento River in northern California. Digital elevation models (DEMs) were developed by combining water depth maps of the reach, created using spectrally-based remote sensing methods, with light detection and ranging (lidar) data on water surface and terrestrial elevations. The depth maps were derived from three imagery sources: (1) airborne hyperspectral imagery (CASI); (2) uncrewed aerial survey (UAS)-based hyperspectral imagery (Nano); and (3) multispectral satellite imagery (WV3). The methods used to develop bathymetric maps for the reach are provided by Legleiter and Harrison (2019a) and the remote sensing data are available via a ScienceBase data release (Legleiter and Harrison, 2019b). The three DEMs contained in this data release were used as input to develop two-dimensional (2D) and three-dimensional (3D) hydrodynamic models using the Delft3D-Flexible Mesh (Delft3D-FM, 2022.01 release) model developed by Deltares (2022). We used a curvilinear grid with a cell size of 1 m. For the 2D models, we included a spiral flow parameter, which accounts for the effects of secondary flow induced by streamline curvature. For the 3D models, the vertical grid was divided into 10 sigma-layers that followed the bottom topography and free surface. Each sigma-layer represented 10% of the flow depth. We set the time step to ensure a Courant number less than 0.7, and specified a minimum depth for wetting/drying calculations of 0.05 m. We prescribed an upstream discharge of 260 m3/s and ran steady flow simulations. To account for turbulence in the 2D model, we used a uniform eddy viscosity value of 1 m2/s. For the 3D model, turbulence was represented using a κ-ε turbulence closure model. The flow resistance was defined using a uniform roughness height (ks) which was converted to spatially explicit Chezy C coefficients via the Colebrook-White equation. The map projection and datum for the three DEMs contained in this data release are UTM Zone 10 N and NAD83, respectively. Each of the three DEMs is provided as a comma-delimited (*.csv) text file consisting of three columns: East, North, and Elevation; the units of the spatial coordinates and the elevation are meters. Additional Delft3D-FM model input values are provided as a supplemental (*.csv) text file. These DEMs played a critical role in generating multidimensional hydrodynamic models developed from remotely sensed data. Field measurements of water velocity were acquired from a reach of the upper Sacramento River in northern California, September 12-14, 2017, to support research on salmon habitat along the Sacramento River and, more broadly, multidimensional hydrodynamic modeling. The velocity measurements included in this data release were obtained along a series of 10 cross-sections (XS) by a SonTek RiverSurveyor S5 acoustic Doppler current profiler (ADCP) deployed from a jet boat, making 5-10 passes across the channel at each XS. The spatial location of each measurement was obtained via a differential GPS included as part of the RiverSurveyor S5 ADCP instrument package. We post-processed the ADCP data using the Velocity Mapping Toolbox (VMT, version 4.09) (Parsons et al., 2013). In areas where the ADCP did not measure near-bed velocities reliably, we fitted a logarithmic profile to the measured part of the flow field and projected from the lowermost valid velocity measurement to zero velocity at the bed. The map projection and datum for these data are UTM Zone 10 N and NAD83, respectively. The ADCP-based velocity measurements in this data release are provided in a comma-delimited (*.csv) text file with six columns: East, North, Depth, Velocity_depAvg, Velocity_nearBed, and adcpXS; the units of the spatial coordinates and the depths are meters and the depth-averaged and near-bed velocities are in units of m/s. This ground-based data set played a critical role in validating multidimensional hydrodynamic models, developed from remotely sensed data.",
       "descriptionType": "Abstract"
     }
   ],
   "geoLocations": [],
   "fundingReferences": [],
   "url": "https://www.sciencebase.gov/catalog/item/624acef2d34e21f827635af1",
   "contentUrl": null,
   "metadataVersion": 1,
   "schemaVersion": "http://datacite.org/schema/kernel-4",
   "source": "mds",
   "isActive": true,
   "state": "findable",
   "reason": null,
   "viewCount": 0,
   "downloadCount": 0,
   "referenceCount": 0,
   "citationCount": 1,
   "partCount": 0,
   "partOfCount": 0,
   "versionCount": 0,
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   "created": "2022-05-04T02:55:21Z",
   "registered": "2022-05-04T02:55:22Z",
   "published": null,
   "updated": "2023-03-05T04:58:15Z"
 }

}

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