FEMA 20170331 Flood Hazard Areas (FEMA) The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters of Map Revision (LOMRs) that have been issued against those databases since their publication date. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance (or 100-year) flood event, the 0.2-percent-annual-chance (or 500-year) flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth''s surface using the Geographic Coordinate System (GCS) and North American Datum of 1983. The FIRM is the basis for floodplain management, mitigation, and insurance activities for the National Flood Insurance Program (NFIP). Insurance applications include enforcement of the mandatory purchase requirement of the Flood Disaster Protection Act, which "... requires the purchase of flood insurance by property owners who are being assisted by Federal programs or by Federally supervised, regulated or insured agencies or institutions in the acquisition or improvement of land facilities located or to be located in identified areas having special flood hazards, " Section 2 (b) (4) of the Flood Disaster Protection Act of 1973. In addition to the identification of Special Flood Hazard Areas (SFHAs), the risk zones shown on the FIRMs are the basis for the establishment of premium rates for flood coverage offered through the NFIP. The FIRM Database presents the flood risk information depicted on the FIRM in a digital format suitable for use in electronic mapping applications. The FIRM Database serves to archive the information collected during the Flood Risk Project.For more information visit: https://msc.fema.gov/portal Metro downloads the NFHL data from FEMA, merges it and clips to a regional area and includes it in the Regional Land Information System (RLIS) as an added value to the programs published data. For more information regarding field definitions see: https://www.fema.gov/sites/default/files/2020-02/FIRM_Database_Technical_Reference_Feb_2019.pdf. And for more information regarding valid domain values see: https://www.fema.gov/sites/default/files/2020-02/Domain_Tables_Technical_Reference_Feb_2019.pdf 20250721 Ground condition Complete As needed -123.47121656 -121.694183 46.08065859 45.007987 None Flood FIRM FEMA emergency 100 year flood plain 100 yr flood plain 500 year flood plain 500 yr flood plain National Flood Hazard Layer Flood Insurance Rate Map Federal Emergency Management Agency Flood Hazard Zone None Portland Multnomah County Washington County Clackamas County Oregon None This database and GIS data are made available under the RLIS Open Database End User License Agreement. See https://rlisdiscovery.oregonmetro.gov/pages/open-database-license. http://library.oregonmetro.gov/rlisdiscovery/browse_graphic/flood_fema.png Polygons representing FEMA National Flood Hazard zones in the region with major arterials, the Metro boundary, and topology.. PNG The NFHL consists of vector files and associated attributes produced in conjunction with the hardcopy FEMA FIRM. The published effective FIRM and FIRM Database are issued as the official designation of the SFHAs. As such they are adopted by local communities and form the basis for administration of the NFIP. For these purposes they are authoritative. Provisions exist in the regulations for public review, appeals and corrections of the flood risk information shown to better match real world conditions. As with any engineering analysis of this type, variation from the estimated flood heights and floodplain boundaries is possible. Details of FEMA's requirements for the FISs and flood mapping process that produces these data are available in the Guidelines and Standards for Flood Risk Analysis and Mapping. Horizontal accuracy was tested by manual comparison of source graphics with hardcopy plots and a symbolized display on an interactive computer graphic system. Independent quality control testing of the individual FIRM Database components of the NFHL was also performed. Incorporated the 2004 Portland FEMA survey (area outside of survey unchanged). Added new attributes Fema and Floodway. Within the area of the new survey in addition to the 100-year floodplain (Fema = 100) polygons of the 500-year flood plain (Fema = 500) beyond the 100-year flood plain (Fema = 100) were also included. Also within area of the new survey, the polygons of the floodway (the channel of a stream plus any adjacent floodplains areas that must be kept free from encroachment so that the 100-year flood can be carried without substantial increases in flood heights) have been delineated. 20060120 Changed native SDE storage precision from low to high 20100122 Completely reworked the RLIS version of the Flood_FEMA feature class. Updated the feature class schema to include the source data attributes. Updated the data set to the latest available studies (Benton Co., 12/8/2016; Clackamas Co., 5/5/2016; Clark Co., unknown; Columbia Co., unknown; Cowlitz Co., 12/16/2015; Lincoln Co., 6/13/2016; Linn Co., 12/8/2016; Marion Co., 5/26/2015; Multnomah Co., 10/28/2015; Polk Co., 5/26/2016; City of Portland (Multnomah, Clackamas and Washington Counties), 8/12/2016; Washington Co. and Incorporated Areas, 10/19/2018; Yamhill Co., 5/9/2013.)Expanded the data set to encompass the Intertwine Biodiversity area. 20170331 Released a beta version to solicite feedback from stakeholders. 20170407 Minor schema changes were made to reflect changes made to the National Flood Hazard Layer (NFHL). The ZONE_SUBTY field was extended to 76 characters, the STUDY_TYP field was extended to 38 characters, and a new GFID field (Text, 36 characters) was added. 20230116 Changed title from Flood Plains (FEMA) to Flood Hazard Areas (FEMA) to better reflect how FEMA refers to the data layer 20240122 Vector Simple FALSE 0 TRUE FALSE International foot D_North_American_1983_HARN Floodplain.dbf The Flood Plains (FEMA) polygon feature class contains information about the flood hazards within the Flood Risk Project area. These zones are used by FEMA to designate the Special Flood Hazard Area (SFHA) and for insurance rating purposes. These data are the regulatory flood zones designated by FEMA Feature Class 0 OBJECTID OBJECTID OID 4 10 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. DFIRM_ID DFIRM_ID String 6 0 0 VERSION_ID Version Identifier. Identifies the product version and relates the feature to standards according to how it was created. NA VERSION_ID String 11 0 0 FLD_AR_ID FLD_AR_ID String 32 0 0 STUDY_TYP Study Type. This describes the type of Flood Risk Project performed for flood hazard identification. Acceptable values for this field are listed in the D_Study_Typ table (not included in RLIS publications). NA STUDY_TYP String 38 0 0 FLD_ZONE Flood Zone. This is a flood zone designation. These zones are used by FEMA to designate the SFHAs and for insurance rating purposes. Acceptable values for this field are listed in the D_Zone table (not included in RLIS publications). A Zone A is the flood insurance rate zone that corresponds to the 1-percent annual chance floodplains that are determined in the Flood Insurance Study by approximate methods of analysis. Because detailed hydraulic analyses are not performed for such areas, no Base Flood Elevations or depths are shown within this zone. Mandatory flood insurance purchase requirements apply. AE ZonesAE is the flood insurance rate zones that correspond to the 1-percent annual chance floodplains that are determined in the Flood Insurance Study by detailed methods of analysis. In most instances, Base Flood Elevations derived from the detailed hydraulic analyses are shown at selected intervals within this zone. Mandatory flood insurance purchase requirements apply. AH Zone AH is the flood insurance rate zone that corresponds to the areas of 1-percent annual chance shallow flooding with a constant water-surface elevation (usually areas of ponding) where average depths are between 1 and 3 feet. The Base Flood Elevations derived from the detailed hydraulic analyses are shown at selected intervals within this zone. Mandatory flood insurance purchase requirements apply. AO Zone AO is the flood insurance rate zone that corresponds to the areas of 1-percent shallow flooding (usually sheet flow on sloping terrain) where average depths are between 1 and 3 feet. Average flood depths derived from the detailed hydraulic analyses are shown within this zone. In addition, alluvial fan flood hazards are shown as Zone AO on the Flood Insurance Rate Map. Mandatory flood insurance purchase requirements apply. X Zone X is the flood insurance rate zones that correspond to areas of moderate flood hazard, usually the area between the limits of the 100- year and 500-year floods – Areas protected from the 1-percent annual chance flood by levees. No Base Flood Elevations or depths are shown within this zone. Insurance purchase is not required in these zones. NA FLD_ZONE String 17 0 0 ZONE_SUBTY Flood Zone Subtype. This field captures additional information about the flood zones not related to insurance rating purposes. For example, Zone X could have “AREA WITH REDUCED FLOOD RISK DUE TO LEVEE” or “0.2 PCT ANNUAL CHANCE FLOOD HAZARD” as a subtype. Types of floodways are also stored in this field. Floodways are designated by FEMA and adopted by communities to provide an area that will remain free of development to moderate increases in flood heights due to encroachment on the floodplain. Normal floodways are NA ZONE_SUBTY String 76 0 0 SFHA_TF Special Flood Hazard Area. If the area is within a SFHA this field would be true. This field will be true for any area coded as an A or V flood zone area. It should be false for any X or D flood areas. Acceptable values for this field are listed in the D_TrueFalse table (not included in RLIS publications). NA SFHA_TF String 1 0 0 STATIC_BFE Static Base Flood Elevation. This field will be populated for areas that have been determined to have a constant Base Flood Elevation (BFE) over a flood zone. The BFE value will be shown beneath the zone label. In this situation the same BFE applies to the entire polygon. This normally occurs in lakes or coastal zones. NA STATIC_BFE Double 8 38 8 V_DATUM Vertical Datum. The vertical datum indicates the reference surface from which the flood elevations are measured. Normally this would be North American Vertical Datum of 1988 for new studies. This field is only populated if the STATIC_BFE field is populated. Acceptable values for this field are listed in the D_V_Datum table (not included in RLIS publications). NA V_DATUM String 17 0 0 DEPTH Depth This is the depth for Zone AO areas. This value is shown beneath the zone label on the FIRM. This field is only populated if a depth is shown on the FIRM. NA DEPTH Double 8 38 8 LEN_UNIT Length Units. This unit indicates the measurement system used for the BFEs and/or depths. Normally this would be feet. This field is only populated if the STATIC_BFE or DEPTH field is populated. Acceptable values for this field are listed in the D_Length_Units table (not included in RLIS publications). NA LEN_UNIT String 16 0 0 VELOCITY Velocity. This is the velocity measurement of the flood flow in the area. Normally this is applicable to alluvial fan areas (certain Zone AO areas). This value is shown beneath the zone label on the FIRM. This field is only populated when a velocity is associated with the flood zone area. NA VELOCITY Double 8 38 8 VEL_UNIT Velocity Unit. This is the unit of measurement for the velocity. This field is populated when the VELOCITY field is populated. Acceptable values for this field are listed in the D_Velocity_Units table (not included in RLIS publications). NA VEL_UNIT String 20 0 0 AR_REVERT Flood Control Restoration Zones – Zone AR Classification. If this area is Zone AR in FLD_Zone field, this field would hold the zone that area would revert to if the AR zone were removed. This field is only populated if the corresponding area is Zone AR. Acceptable values for this field are listed in the D_Zone table (not included in RLIS publications), but should only include one of AE, AO, AH, A, and X domain values. NA AR_REVERT String 17 0 0 AR_SUBTRV Flood Control Restoration Zones – Zone AR Classification Zone Subtype. If this area is Zone AR in FLD_Zone field, this field would hold the zone subtype the area would revert to if the AR zone were removed. This field is only populated if the corresponding area is Zone AR. NOTE: The symbol ‘%’ is a reserved symbol in most software packages, so the word ‘percent’ was abbreviated to ‘PCT.’ Acceptable values for this field are listed in the D_Zone_Subtype_ table (not included in RLIS publications) and must be one of the allowable subtypes for NA AR_SUBTRV String 57 0 0 BFE_REVERT Flood Control Restoration Zones – BFE Revert. If zone is Zone AR in FLD_Zone field, this field would hold the static base flood elevation for the reverted zone. This field is populated when Zone equals AR and the reverted zone has a static BFE. NA BFE_REVERT Double 8 38 8 DEP_REVERT Flood Control Restoration Zones – Depth Revert. If zone is Zone AR in FLD_Zone field, this field would hold the flood depth for the reverted zone. This field is populated when Zone equals AR and the reverted zone has a depth assigned. NA DEP_REVERT Double 8 38 8 DUAL_ZONE Flood Control Restoration Zones – Dual Zone Classification. If the flood hazard areas shown on the effective FIRM shall be designated as “dual” flood insurance rate zones (i.e., Zone AR/AE, Zone AR/AH, Zone AR/AO, Zone AR/A), this field will be coded as true. It should be false for any for AR Zones that revert to Shaded X. Acceptable values for this field are listed in the D_TrueFalse table (not included in RLIS publications). NA DUAL_ZONE String 1 0 0 SOURCE_CIT Source Citation. Abbreviation used in the metadata file when describing the source information for the feature. The abbreviation must match a value in L_Source_Cit (not included in RLIS publications). NA SOURCE_CIT String 21 0 0 GFID GFID String 36 0 0 Shape Shape Geometry 8 0 0 Feature geometry. Esri Coordinates defining the features. Shape.STArea() Shape.STArea() Double 0 0 0 Shape.STLength() Shape.STLength() Double 0 0 0 Floodplain.dbf The Flood Plains (FEMA) polygon feature class contains information about the flood hazards within the Flood Risk Project area. These zones are used by FEMA to designate the Special Flood Hazard Area (SFHA) and for insurance rating purposes. These data are the regulatory flood zones designated by FEMA Metro Data Resource Center
600 NE Grand Ave.
Portland OR 97232 503 797-1742 503 797-1909 drc@oregonmetro.gov The information in this file was derived from digital databases on Metro's GIS. Care was taken in the creation of this file. Metro cannot accept any responsibility for errors, omissions, or positional accuracy. There are no warranties, expressed or implied. Shapefile 1 DVD or CD-ROM ISO9660 http://www.oregonmetro.gov/rlisdiscovery Email drc@oregonmetro.gov or call 503-797-1742 for further instructions. No cost 20250721 Metro Data Resource Center Alicia Wood mailing and physical address
600 NE Grand Ave.
Portland OR 97232 503-813-7561 503-797-1909 alicia.wood@oregonmetro.gov FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998 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Esri ArcGIS 13.5.2.57366 Flood_Hazard_Areas__FEMA Flood_Hazard_Areas__FEMA 002 Projected GCS_North_American_1983_HARN Linear Unit: Foot (0.304800) NAD_1983_HARN_StatePlane_Oregon_North_FIPS_3601_Feet_Intl <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'><WKT>PROJCS[&quot;NAD_1983_HARN_StatePlane_Oregon_North_FIPS_3601_Feet_Intl&quot;,GEOGCS[&quot;GCS_North_American_1983_HARN&quot;,DATUM[&quot;D_North_American_1983_HARN&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic&quot;],PARAMETER[&quot;False_Easting&quot;,8202099.737532808],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-120.5],PARAMETER[&quot;Standard_Parallel_1&quot;,44.33333333333334],PARAMETER[&quot;Standard_Parallel_2&quot;,46.0],PARAMETER[&quot;Latitude_Of_Origin&quot;,43.66666666666666],UNIT[&quot;Foot&quot;,0.3048],AUTHORITY[&quot;EPSG&quot;,2913]]</WKT><XOrigin>-111333600</XOrigin><YOrigin>-98152500</YOrigin><XYScale>3048</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.0032808398950131233</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>2913</WKID><LatestWKID>2913</LatestWKID></ProjectedCoordinateSystem> 20251023 08372000 20251023 08372000 Enterprise Geodatabase Feature Class dataset EPSG 6.3(9.0.0) 0 20251023