<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20260706</CreaDate>
<CreaTime>11581200</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>FALSE</SyncOnce>
<DataProperties>
<itemProps>
<itemName Sync="FALSE">Streams_NapaCounty_Master</itemName>
<imsContentType Sync="TRUE">002</imsContentType>
<nativeExtBox>
<westBL Sync="TRUE">6379911.425015</westBL>
<eastBL Sync="TRUE">6543286.407975</eastBL>
<southBL Sync="TRUE">1817481.723951</southBL>
<northBL Sync="TRUE">2076165.528104</northBL>
<exTypeCode Sync="TRUE">1</exTypeCode>
</nativeExtBox>
</itemProps>
<coordRef>
<type Sync="TRUE">Projected</type>
<geogcsn Sync="TRUE">GCS_North_American_1983</geogcsn>
<csUnits Sync="TRUE">Linear Unit: Foot_US (0.304801)</csUnits>
<projcsn Sync="TRUE">NAD_1983_StatePlane_California_II_FIPS_0402_Feet</projcsn>
<peXml Sync="TRUE">&lt;ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.5.0'&gt;&lt;WKT&gt;PROJCS[&amp;quot;NAD_1983_StatePlane_California_II_FIPS_0402_Feet&amp;quot;,GEOGCS[&amp;quot;GCS_North_American_1983&amp;quot;,DATUM[&amp;quot;D_North_American_1983&amp;quot;,SPHEROID[&amp;quot;GRS_1980&amp;quot;,6378137.0,298.257222101]],PRIMEM[&amp;quot;Greenwich&amp;quot;,0.0],UNIT[&amp;quot;Degree&amp;quot;,0.0174532925199433]],PROJECTION[&amp;quot;Lambert_Conformal_Conic&amp;quot;],PARAMETER[&amp;quot;False_Easting&amp;quot;,6561666.666666666],PARAMETER[&amp;quot;False_Northing&amp;quot;,1640416.666666667],PARAMETER[&amp;quot;Central_Meridian&amp;quot;,-122.0],PARAMETER[&amp;quot;Standard_Parallel_1&amp;quot;,38.33333333333334],PARAMETER[&amp;quot;Standard_Parallel_2&amp;quot;,39.83333333333334],PARAMETER[&amp;quot;Latitude_Of_Origin&amp;quot;,37.66666666666666],UNIT[&amp;quot;Foot_US&amp;quot;,0.3048006096012192],AUTHORITY[&amp;quot;EPSG&amp;quot;,2226]]&lt;/WKT&gt;&lt;XOrigin&gt;-115211800&lt;/XOrigin&gt;&lt;YOrigin&gt;-93821500&lt;/YOrigin&gt;&lt;XYScale&gt;3048.0060960121928&lt;/XYScale&gt;&lt;ZOrigin&gt;-100000&lt;/ZOrigin&gt;&lt;ZScale&gt;10000&lt;/ZScale&gt;&lt;MOrigin&gt;-100000&lt;/MOrigin&gt;&lt;MScale&gt;10000&lt;/MScale&gt;&lt;XYTolerance&gt;0.0032808333333333331&lt;/XYTolerance&gt;&lt;ZTolerance&gt;0.001&lt;/ZTolerance&gt;&lt;MTolerance&gt;0.001&lt;/MTolerance&gt;&lt;HighPrecision&gt;true&lt;/HighPrecision&gt;&lt;WKID&gt;102642&lt;/WKID&gt;&lt;LatestWKID&gt;2226&lt;/LatestWKID&gt;&lt;/ProjectedCoordinateSystem&gt;</peXml>
</coordRef>
</DataProperties>
<SyncDate>20260706</SyncDate>
<SyncTime>20244900</SyncTime>
<ModDate>20260706</ModDate>
<ModTime>20244900</ModTime>
</Esri>
<mdFileID>1731007100860r7295180003500361</mdFileID>
<mdChar>
<CharSetCd value="004">
</CharSetCd>
</mdChar>
<mdHrLv>
<ScopeCd value="005">
</ScopeCd>
</mdHrLv>
<mdContact>
<rpOrgName>Napa County</rpOrgName>
<role>
<RoleCd value="007">
</RoleCd>
</role>
<rpCntInfo>
<cntAddress addressType="both">
<city>Napa</city>
<adminArea>CA</adminArea>
<postCode>94559</postCode>
</cntAddress>
</rpCntInfo>
</mdContact>
<mdDateSt>2024-11-07</mdDateSt>
<mdTimeSt>11:18:20.63</mdTimeSt>
<dataIdInfo>
<idAbs>&lt;p style='text-align:center;'&gt;&lt;span style='font-size:24px;'&gt;&lt;strong&gt;Napa County Streams (master)&lt;/strong&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;This and it's dependent and encopmassing datasets is to represent the spatially accurate and historically rectified surface flow of water courses within Napa County, and the authoritatve GIS layer for all known or derived streams. For associated and streams or flowline layers see the following:&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Significant Streams&lt;/li&gt;&lt;li&gt;Significant Streams 1500' Buffer&lt;/li&gt;&lt;li&gt;Intermittent and Ephemeral Streams&lt;/li&gt;&lt;li&gt;Archived Blue line Streams&lt;/li&gt;&lt;li&gt;Survey Streams (coming soon)&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;The &lt;strong&gt;Streams_NapaCounty_master (&lt;/strong&gt;Napa County Streams Layer) is an alternative layer to the county’s blueline streams layer. Historically, the county bluelines layer utilized flowline geometry directly from the USGS topographic map (TM) series and the National Hydrography Dataset (NHD). With the USGS pivoting away from future TM releases as we have known them, this additional county streams layer serves to prime county hydrological data to be incorporated into the new national standard as well as creating a more accurate and useful resource for the county, its partners, and the public.&lt;/p&gt;&lt;p&gt;Flowlines for this layer were produced with a combination of lines generated from running spatial analysis tools against the 2018 Digital Elevation Model layer by drainage boundaries, heads-up adjustment of generated lines, and fully hand drafted lines using the 2018 DEM, ESRI’s World Hillshade, and aerial imagery dating from 1940 to 2022 as reference. Segments of the lower Napa River Watershed also used line geometry from the 2015 RCD layer.&lt;/p&gt;&lt;p&gt;Attribution of fish presence was compiled from the previous county bluelines layer, RCD 2015 stream layer, fish habitat and stream inventory reports from RCD, Historical fish presence research done by Robert A. Leidy, and assorted State and National Fish and Game data. Full details can be found within a companion document at request from PBES GIS staff.&lt;/p&gt;&lt;p&gt;Each stream segment has two different Strahler order values. The field labeled “StrahlerOrder_Full” should be displayed when the layer is displaying all line segments. The field labeled “StrahlerOrder_LatestOnly” should be displayed when the layer is filtered to show only line placement referenced in the latest large-scale USGS topographical map release. By default, refer to “StrahlerOrder_Full”.&lt;/p&gt;&lt;p&gt;Future updates plan to add additional flowline geometry that falls within the county’s definition of stream, along with further attribution to keep Napa County data in line with national standards. The current layer displays flowlines that meet at least one of these qualifications: Placement matches latest USGS largest scale topographic map release blue lines, placement matches flowlines on previous county bluelines layer, flowlines with current or historical fish presence, flowlines that fall under county ordinance 1307, and flowlines listed in county resolution 94-19.&lt;/p&gt;</idAbs>
<idCitation>
<resTitle>Streams_NapaCounty_Master</resTitle>
<date>
<pubDate>2024-11-07T00:00:00</pubDate>
</date>
<citRespParty>
<rpIndName>Logan Laudano</rpIndName>
<rpOrgName>Napa County</rpOrgName>
<rpPosName>GIS Technician I</rpPosName>
<role>
<RoleCd value="006">
</RoleCd>
</role>
<rpCntInfo>
<cntAddress addressType="both">
<eMailAdd>logan.laudano@countyofnapa.org</eMailAdd>
<delPoint>1195 3rd St</delPoint>
<city>Napa</city>
<adminArea>CA</adminArea>
<postCode>94559</postCode>
<country>US</country>
</cntAddress>
<cntPhone>
<voiceNum>707-253-4346</voiceNum>
</cntPhone>
<cntHours>9:00AM - 5:30PM PST</cntHours>
<cntInstr>Mon-Fri</cntInstr>
</rpCntInfo>
</citRespParty>
<presForm>
<PresFormCd Sync="TRUE" value="005">
</PresFormCd>
</presForm>
</idCitation>
<dataExt>
<geoEle>
<GeoBndBox>
<westBL>-122.6466</westBL>
<eastBL>-122.0614</eastBL>
<northBL>38.8643</northBL>
<southBL>38.1537</southBL>
<exTypeCode>1</exTypeCode>
</GeoBndBox>
</geoEle>
<vertEle>
<vertMinVal Sync="TRUE">0.000000</vertMinVal>
<vertMaxVal Sync="TRUE">0.000000</vertMaxVal>
</vertEle>
</dataExt>
<searchKeys>
<keyword>California</keyword>
<keyword>County of Napa</keyword>
<keyword>Environment</keyword>
<keyword>Napa County</keyword>
<keyword>PBES</keyword>
<keyword>hydrography</keyword>
<keyword>inlandWaters</keyword>
<keyword>streams</keyword>
</searchKeys>
<themeKeys>
<keyword>Streams</keyword>
<keyword>County of Napa</keyword>
<keyword>Napa County</keyword>
<keyword>flowlines</keyword>
</themeKeys>
<idPurp>An accurate geographic spatial representation and visualization of stream flowlines in Napa County. Generated from LiDAR elevation models and curated from current and previous USGS designated blue lines with an emphasis on high horizontal accuracy and internally derived attributes supporting Napa County policies.</idPurp>
<idCredit>Napa County PBES Dept. GIS Division
Spatial analysis, aerial interpretation, and hand digitization of line geometry as well as attribution collection and application completed by Logan Laudano, PBES GIS Technician I.
2018 DEM layer prepared by Matt Lamborn, PBES GIS Dept Coordinator using the 2018 LiDAR USGS flew over Napa County and surrounding areas after the 2017 fires in part of the 3DEP program. Napa County Resource Conservation District (RCD) Stream layer covering the Napa River Watershed 2015 and 2019 versions. Geographic Names Information System (GNIS).
Leidy, R.A. 2007. Historical references for native stream fishes for the period 1854-1981. SFEI. Contribution No. 530 Appendix II.
California Fish and Biogeographic Information and Observation System (BIOS) ds69, ds2673, ds340, ds122.
Leidy, R.A., G.S. Becker, B.N. Harvey. 2005. Historical distribution and current status of steelhead/rainbow trout (Oncorhynchus mykiss) in streams of the San Francisco Estuary, California. Center for Ecosystem Management and Restoration, Oakland, CA.
EcoTrust 2001 Snorkel Count for Steelhead Trout in the Napa Watershed, California.
NCRCD and PCI. 2012. Northern Napa River Tributary Stream Surveys Report – May 2012.
Suisun Creek Watershed Assessment and Enhancement Plan Prepared by Laurel Marcus and Associates.</idCredit>
<resConst>
<Consts>
<useLimit>&lt;p&gt;Low – For internal county use, shareable to outside agencies/partners.&lt;/p&gt;</useLimit>
</Consts>
</resConst>
<resConst>
<LegConsts>
<accessConsts>
<RestrictCd value="008">
</RestrictCd>
</accessConsts>
<othConsts>Other Constraints</othConsts>
</LegConsts>
</resConst>
<resConst>
<LegConsts>
<useConsts>
<RestrictCd value="008">
</RestrictCd>
</useConsts>
<othConsts>Other Constraints</othConsts>
</LegConsts>
</resConst>
<resConst>
<LegConsts>
<accessConsts>
<RestrictCd value="008">
</RestrictCd>
</accessConsts>
<othConsts>Other Constraints</othConsts>
</LegConsts>
</resConst>
<resConst>
<LegConsts>
<useConsts>
<RestrictCd value="008">
</RestrictCd>
</useConsts>
<othConsts>Other Constraints</othConsts>
</LegConsts>
</resConst>
<dataLang>
<languageCode value="eng">
</languageCode>
<countryCode value="US">
</countryCode>
</dataLang>
<dataChar>
<CharSetCd value="004">
</CharSetCd>
</dataChar>
<resMaint>
<maintFreq>
<MaintFreqCd value="009">
</MaintFreqCd>
</maintFreq>
</resMaint>
<tpCat>
<TopicCatCd value="007">
</TopicCatCd>
</tpCat>
<tpCat>
<TopicCatCd value="012">
</TopicCatCd>
</tpCat>
<envirDesc Sync="FALSE">Esri ArcGIS 13.5.5.57366</envirDesc>
<spatRpType>
<SpatRepTypCd Sync="TRUE" value="001">
</SpatRepTypCd>
</spatRpType>
<dataExt>
<geoEle>
<GeoBndBox esriExtentType="search">
<exTypeCode Sync="TRUE">1</exTypeCode>
<westBL Sync="TRUE">-122.638329</westBL>
<eastBL Sync="TRUE">-122.063914</eastBL>
<northBL Sync="TRUE">38.863137</northBL>
<southBL Sync="TRUE">38.151105</southBL>
</GeoBndBox>
</geoEle>
</dataExt>
</dataIdInfo>
<mdMaint>
<maintFreq>
<MaintFreqCd value="009">
</MaintFreqCd>
</maintFreq>
</mdMaint>
<dqInfo>
<dataLineage>
<prcStep>
<stepDesc>Split by Raster -
The Napa County 2018 DEM raster layer was split by feature against the county drainage layer into 170+ raster layers.</stepDesc>
<stepDateTm>2024-05-30T00:00:00</stepDateTm>
</prcStep>
<prcStep>
<stepDesc>Derive Stream As Line - Process ran for each raster layer. Output 170+ line feature layers with a “zig-zag” rasterized look of multiple harsh right-angles, as well as each layer having their flowlines together as one feature.</stepDesc>
<stepDateTm>2024-05-31T00:00:00</stepDateTm>
</prcStep>
<prcStep>
<stepDesc>Smoothing, Simplifying, and Feature to Line/Planarizing - Before generated flowlines could be matched to USGS blue line placement, the line features had to be smoothed to remove the zig-zag rasterized look. Testing was done to find optimal smoothing amount.
Tests done with 3 of the 170+ drainage raster layers showed that a Smoothing of 40ft was too erratic in straight reaches of stream but worked well for reaches that had frequent bends. The inverse was true with a Smoothing of 80ft. Smoothing at both 40ft and 80 ft was applied creating a total of 340+ layers.
A side effect of smoothing was that the line features now had many added vertices, most of which were too close together. To resolve this, the 340+ layers were Simplified to remove excess vertices. Lastly, because the output from the Derive Stream As Line tool had each drainage as one single line feature, the layers were all planarized to creature unique features at each intersection or line break. With this final step, the 340+ layers were ready to be selected against USGS blue line placement.</stepDesc>
<stepDateTm>2024-07-10T00:00:00</stepDateTm>
</prcStep>
<prcStep>
<stepDesc>Attribution - Attribution was prioritized to fields that would directly mark or be vital in determining Napa County regulations around streams. Due to Strahler’s definition of stream order being a large part of defining significant streams in the county, line geometry had to be finalized before attribution. PBES GIS staff went through each stream segment by watershed and followed end points of streams to the next stream junction until we had full coverage across the county. Stream order attribution presented a challenge once the Napa River Watershed was complete: while the county boundary completely covers the Napa River Watershed, county boundaries only overlap comparatively small areas of the watersheds it shares with surrounding counties. However, these areas outside the NRW make up over half the county area. Since stream order must account for all upstream offshoots and branching, to designate stream order county-wide, USGS topographic maps of the 2021 release were used to inform Strahler order attribution for streams whose watersheds only partially overlap with Napa County boundaries. Beyond Strahler order, fish presence and presence source field attribution are described in greater detail in a companion document available on request from PBES GIS staff. Stream name and name variants were compiled from the previous county bluelines layer, RCD 2019 Stream Layer, Geographic Names Information System (GNIS), and local references. Attribution of Res_94_19 and Ord_1307 involved reviewing their relevant documentation and marking according to stream name and reach descriptions.
Attribution of the Flowline field was done by splitting stream segments where they overlapped with the county’s water bodies layer and marking those streams as Artificial – WaterBody. An issue was discovered where some flowlines didn’t fully align with water body polygons, leaving to many small segments alternating between “Surface Water” and “Artificial – WaterBody” attribution. Effort was made to review these areas and correct them by re-merging segments and attributing them as “Artificial – WaterBody” and reviewing new line segments around a foot of length. Any concerns of incorrect attribution should be directed to pbes.gis@countyofnapa.org and/or Logan Laudano, PBES GIS Technician II.</stepDesc>
<stepDateTm>2024-10-07T00:00:00</stepDateTm>
</prcStep>
<prcStep>
<stepDateTm>2025-12-11T09:25:00</stepDateTm>
<stepDesc>2025/12/11 Updated Stream Name -
Minor update to reflect BGN August 2025 vote to vacate the 2017 naming of the surface water feature previously named "To Kalon Creek". With the feature now officially being an unnamed creek in GNIS, the relevant feature has had its "StreamName" field set to NULL and has had it's "StreamName_Variant" field untouched. This is in line with how the layer has already been handling cases of water features with unclear names that cannot be verified by GNIS entries: Leaving the official name field NULL and listing name(s) under the variant name field.</stepDesc>
<stepProc>
<role>
<RoleCd value="009">
</RoleCd>
</role>
<rpCntInfo>
<cntAddress addressType="postal">
<eMailAdd>logan.laudano@countyofnapa.org</eMailAdd>
<city>Napa</city>
<adminArea>California</adminArea>
<postCode>94559</postCode>
<country>US</country>
</cntAddress>
<cntPhone>
<voiceNum>7072534346</voiceNum>
</cntPhone>
</rpCntInfo>
<rpOrgName>Napa County</rpOrgName>
<rpIndName>Logan Laudano</rpIndName>
<rpPosName>GIS Technician II</rpPosName>
</stepProc>
</prcStep>
</dataLineage>
<report>
<measResult>
<ConResult>
<conPass>1</conPass>
</ConResult>
</measResult>
</report>
</dqInfo>
<eainfo>
<detailed Name="Streams_NapaCounty_Master">
<enttyp>
<enttypl>Stream_NapaCounty</enttypl>
<enttypd>Stream flowlines generated over current and previous USGS blue lines with an emphasis on high horizontal accuracy and attributes supporting existing County policies.</enttypd>
<enttypds>Napa County PBES Dept.</enttypds>
<enttypt Sync="TRUE">Feature Class</enttypt>
<enttypc Sync="TRUE">7895</enttypc>
</enttyp>
<attr>
<attrlabl Sync="TRUE">OBJECTID</attrlabl>
<attalias Sync="TRUE">OBJECTID</attalias>
<attrtype Sync="TRUE">OID</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdef Sync="TRUE">Internal feature number.</attrdef>
<attrdefs Sync="TRUE">Esri</attrdefs>
<attrdomv>
<udom Sync="TRUE">Sequential unique whole numbers that are automatically generated.</udom>
</attrdomv>
</attr>
<attr>
<attrlabl>StreamName</attrlabl>
<attalias>Stream Name</attalias>
<attrdef>Name of stream segment.</attrdef>
<attrdefs Sync="FALSE">Napa County PBES Dept. GIS Division</attrdefs>
<attrtype>Text</attrtype>
<attwidth>512</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl>StreamName_Variant</attrlabl>
<attalias>Stream Name Variant</attalias>
<attrdef>Known variant names of stream segment.</attrdef>
<attrdefs Sync="FALSE">Napa County PBES Dept. GIS Division</attrdefs>
<attrtype>Text</attrtype>
<attwidth>512</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl>Flowline</attrlabl>
<attrdef>Differentiates artificial flowlines from all other surface water paths. Layer currently includes only the roads and bridges along major roads and crossings along the Napa River. Future updates plan to add surface water flowline types such as river, canal/ditch, and drainageway that will enable the data to be relevant to the USGS 3DHP standards. Surface Water: Any flowline that is not a water body and transports its water above ground. Artificial – Roads/Bridges: Non-encompassing. Marks flowline crossings with roads and bridges along the Napa River along with any flowline crossings of major roadways. Artificial – SD: Flowpaths created using storm drain maps as reference. Detailed direct transfer of line geometry was generalized into a smoother feature. Original digitization is kept in separate gdb. Artificial – Unspecified: Flowpaths connecting surface water flowlines. Artificial – WaterBody: Flowpaths connecting flowlines that cross bodies of water. Water body boundaries sourced from county Water_Bodies layer, with minor alterations where aerial imagery revealed changes in water body boundaries not yet captured in the water bodies layer.</attrdef>
<attrdefs Sync="FALSE">Napa County PBES Dept. GIS Division</attrdefs>
<attrtype>Text</attrtype>
<attwidth>254</attwidth>
<attalias Sync="TRUE">Flowline</attalias>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl>StrahlerOrder_Full</attrlabl>
<attalias>Strahler Order Full Stream Segments</attalias>
<attrdef>Values: 0, 1, 2, 3, 4, 5, 6
Strahler order value inclusive of every stream segment captured in the current layer version. At default, this field should be used to display stream order value for the layer. To note: Previous county layers have only included Strahler order within the Napa River Watershed. Due to the nature of Strahler order, an entire watershed must be considered to get an accurate value per stream segment. In this new layer, Strahler order values were added county-wide by carefully reviewing areas outside county boundaries but within their relevant watersheds. The Strahler number method of ordering streams counts the end node / the outermost stream lines as order 1. When two order 1 segments meet, they form an order 2 stream. This forking pattern continues down into the main steam of the stream network. Braided streams “break” Strahler order, so have some segments marked as “0” to be ignored.</attrdef>
<attrdefs>Napa County PBES Dept.</attrdefs>
<attrtype>Short</attrtype>
<attwidth>Numeric</attwidth>
<atprecis Sync="TRUE">5</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl>StrahlerOrder_LatestOnly</attrlabl>
<attalias>Strahler Order Latest Stream Segments Only</attalias>
<attrdef>Values: 0, 1, 2, 3, 4, 5, 6 Strahler order value exclusive to stream segments with line placement referenced in the latest large-scale USGS topographical map release. This field should be displayed when layer is queried to segments with a UBL_Latest value of Yes or a Fish value of Yes or an Ord_1307 value of Yes or a Res_94_19 value of Yes. Segments otherwise not applicable are labeled "0". The Strahler number method of ordering streams counts the end node / the outermost stream lines as order 1. When two order 1 segments meet, they form an order 2 stream. This forking pattern continues down into the main steam of the stream network. Braided streams “break” Strahler order, so segments not along main flowline have been marked as “0” to be ignored in the stream order.</attrdef>
<attrdefs Sync="FALSE">Napa County PBES Dept. GIS Division</attrdefs>
<attrtype>Short</attrtype>
<attwidth>Numeric</attwidth>
<atprecis Sync="TRUE">5</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl>Fish</attrlabl>
<attrdef>Yes: Designates the stream segment as having historic or current fish presence recorded. Napa County holds regulations around streams with fish presence and/or historical fish habitat, this field marks streams that have previously been surveyed and documented as such. Surveys have historically been focused within the Napa River Watershed. Due to the limitations of survey access and availability, current attribution is not to be taken as fully reflective of actual habitat and is to be used only as a county-wide reference with its limitations in mind. Future updates to the layer plan to expand attribution by reviewing and referencing internal county documents.</attrdef>
<attrdefs Sync="FALSE">Napa County PBES Dept. GIS Division</attrdefs>
<attrtype>Text</attrtype>
<attwidth>254</attwidth>
<attalias Sync="TRUE">Fish</attalias>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl>Res_94_19</attrlabl>
<attalias>Resolution 94-19</attalias>
<attrdef>Yes: Streams segments listed under Exhibit C of Resolution 94-19.</attrdef>
<attrdefs Sync="FALSE">Napa County PBES Dept. GIS Division</attrdefs>
<attrtype>Text</attrtype>
<attwidth>255</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl>Ord_1307</attrlabl>
<attalias>Ordinance 1307</attalias>
<attrdef>Yes: Stream segment is within the reaches described in Ordinance 1307. Stream segments that fall under Ordinance 1307 and are listed within code of ordinances 16.04.510. Ordinance 1307 superseded Ordinance 1095. The previous county blueline layer lists a similar field as Ord_1095. Limitations: Extent of reaches described use proximity to adjacent buildings and other features. USGS Topo maps were used when elevation was referenced.</attrdef>
<attrdefs Sync="FALSE">Napa County PBES Dept. GIS Division</attrdefs>
<attrtype>Text</attrtype>
<attwidth>512</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl>UBL_Latest</attrlabl>
<attalias>USGS Blue Lines: As displayed in the latest (2021) topographical map release at the largest scale (1:24,000 aka 7.5 min maps)</attalias>
<attrdef>Yes: Stream segments with line placement referenced in the latest large-scale USGS topographic map release.</attrdef>
<attrdefs Sync="FALSE">Napa County PBES Dept. GIS Division</attrdefs>
<attrtype>Text</attrtype>
<attwidth>512</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl>UBL_Prev</attrlabl>
<attalias>USGS Blue Lines: As displayed in the previous county "bluelines" layer</attalias>
<attrdef>Yes: Stream segments with line placement referenced in the previous PBES GIS bluelines stream layer. This includes both line geometry from the penultimate USGS 2018 topographical map release as well as additional line geometry added for county purposes.</attrdef>
<attrdefs Sync="FALSE">Napa County PBES Dept. GIS Division</attrdefs>
<attrtype>Text</attrtype>
<attwidth>512</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl>FishSource</attrlabl>
<attalias>Fish Source</attalias>
<attrdef>Text field where shorthand sources of fish presence are listed.
Every stream segment with a “Fish” field value of “Yes” has one or multiple sources listed.
For a full list of sources and their full reports attached, please contact PBES GIS team for fish source documentation.</attrdef>
<attrdefs Sync="FALSE">Napa County PBES Dept. GIS Divisionv</attrdefs>
<attrtype>Text</attrtype>
<attwidth>254</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl>Length_ft</attrlabl>
<attalias>Length in feet</attalias>
<attrdef>Length of flowline segment in feet.</attrdef>
<attrdefs Sync="FALSE">Napa County PBES Dept. GIS Division</attrdefs>
<attrtype>Double</attrtype>
<attwidth>Numeric</attwidth>
<atprecis Sync="TRUE">38</atprecis>
<attscale Sync="TRUE">8</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">GlobalID</attrlabl>
<attalias Sync="TRUE">GlobalID</attalias>
<attrtype Sync="TRUE">GlobalID</attrtype>
<attwidth Sync="TRUE">38</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Shape</attrlabl>
<attalias Sync="TRUE">Shape</attalias>
<attrtype Sync="TRUE">Geometry</attrtype>
<attwidth Sync="TRUE">8</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdef Sync="TRUE">Feature geometry.</attrdef>
<attrdefs Sync="TRUE">Esri</attrdefs>
<attrdomv>
<udom Sync="TRUE">Coordinates defining the features.</udom>
</attrdomv>
</attr>
<attr>
<attrlabl Sync="TRUE">Shape.STLength()</attrlabl>
<attalias Sync="TRUE">Shape.STLength()</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">0</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
</detailed>
</eainfo>
<mdLang>
<languageCode Sync="TRUE" value="eng">
</languageCode>
<countryCode Sync="TRUE" value="USA">
</countryCode>
</mdLang>
<distInfo>
<distFormat>
<formatName Sync="TRUE">Enterprise Geodatabase Feature Class</formatName>
</distFormat>
</distInfo>
<mdHrLvName Sync="TRUE">dataset</mdHrLvName>
<refSysInfo>
<RefSystem>
<refSysID>
<identCode Sync="TRUE" code="2226">
</identCode>
<idCodeSpace Sync="TRUE">EPSG</idCodeSpace>
<idVersion Sync="TRUE">5.3(9.0.0)</idVersion>
</refSysID>
</RefSystem>
</refSysInfo>
<spatRepInfo>
<VectSpatRep>
<geometObjs Name="Streams_NapaCounty_Master">
<geoObjTyp>
<GeoObjTypCd Sync="TRUE" value="002">
</GeoObjTypCd>
</geoObjTyp>
<geoObjCnt Sync="TRUE">7895</geoObjCnt>
</geometObjs>
<topLvl>
<TopoLevCd Sync="TRUE" value="001">
</TopoLevCd>
</topLvl>
</VectSpatRep>
</spatRepInfo>
<spdoinfo>
<ptvctinf>
<esriterm Name="Streams_NapaCounty_Master">
<efeatyp Sync="TRUE">Simple</efeatyp>
<efeageom Sync="TRUE" code="3">
</efeageom>
<esritopo Sync="TRUE">FALSE</esritopo>
<efeacnt Sync="TRUE">7895</efeacnt>
<spindex Sync="TRUE">TRUE</spindex>
<linrefer Sync="TRUE">TRUE</linrefer>
</esriterm>
</ptvctinf>
</spdoinfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO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</Data>
</Thumbnail>
</Binary>
</metadata>
