20220504 09522400 1.0 FGDC CSDGM Metadata FALSE reach_Wilson 002 420117.076963 476975.189445 4986500.048333 5058868.048333 1 242.172 Projected GCS_North_American_1983 Linear Unit: Meter (1.000000) NAD_1983_UTM_Zone_10N <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/10.6'><WKT>PROJCS[&quot;NAD_1983_UTM_Zone_10N&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;False_Easting&quot;,500000.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-123.0],PARAMETER[&quot;Scale_Factor&quot;,0.9996],PARAMETER[&quot;Latitude_Of_Origin&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,26910]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>-9998100</YOrigin><XYScale>450445547.3910538</XYScale><ZOrigin>-546.20378238519288</ZOrigin><ZScale>4194304001953.124</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>26910</WKID><LatestWKID>26910</LatestWKID></ProjectedCoordinateSystem> 20220504 09454500 20220504 09454500 Version 6.2 (Build 9200) ; Esri ArcGIS 10.6.1.9270 reach_Wilson 0.100130 1054.975952 1 -124.025730 -123.292297 45.682981 45.027452 This dataset is intended to be used with NetMap landscape analysis software. To learn more, go to www.terrainworks.com This dataset was developed using NetMap by TerrainWorks (www.terrainworks.com). Copyright @2013. When using NetMap databases (digital landscapes) and or NetMap analysis tools, please cite as: TerrainWorks (NetMap) 20xx. www.terrainworks.com TerrainWorks (or Earth Systems Institute) assumes no responsibility and no liability for any information, misinformation, or use of information with regards to these data. There is no guarantee or warranty concerning the accuracy of the data. Users should be aware that changes may have occurred since this data set was created and that some parts of this data may no longer represent actual conditions. Users should not use this data for critical applications without a full awareness of its limitations. Regardless of the types of predictions made by the TerrainWorks/NetMap software, and including any and all applications by anyone, no warranties, express or implied, are made and in fact are disclaimed. Applying shallow landslide, gully, surface erosion and debris flow models and predictions requires careful consideration of other factors including the applicability of any models to diverse landscapes (e.g., is model appropriate), other important factors such as climate, vegetation characteristics, soils, land-use activities, wildfire history, and landslide history (at any particular site and in the larger landscape). Model users should have expertise in geotechnical disciplines in order to appropriately interpret landslide and debris flow hazards. Using models to predict erosion is never a substitute for field work and analysis. Models only provide an approximation of on the ground conditions. It is recommended to use both modeling, to provide a coarse level screening of erosion potential, followed up by field verification of model parameters (such as slope) and actual erosion conditions. The boundaries between erosion potential map elements predicted by NetMap/TerrainWorks software (e.g., digital landscapes and analysis tools) are approximate. Actual boundaries between mapping elements in any specific location need to be determined in the field, on site. In addition, not all small-scale landslide-prone features will be mapped and other features may be encountered during field inspections. Moreover, the sediment delivery potential (to streams and to other identified locations) of predicted erosion features, as well as any other erosion-prone landforms, should be verified in the field, on site. The erosion predictions in the TerrainWorks/NetMap software are based on scientific information. However, any erosion prediction will contain inaccuracies and limitations because of 1) the relatively short and unique history of storms that triggered erosion and that are used to create the science (e.g., longer and different time periods and larger storms may yield different scientific results, models and understanding) and 2) the incomplete scientific understanding of all erosion mechanisms. For these reasons, all erosion predictions made by the TerrainWorks/NetMap software will not completely identify all of the potentially erodible areas. Regardless of the types of predictions made by the TerrainWorks/NetMap software, and including any and all applications by anyone, no warranties, express or implied, are made and in fact are disclaimed. Shapefile 242.172 dataset EPSG 7.8.2(3.0.1) 109363 Simple FALSE 109363 FALSE TRUE reach_Wilson Feature Class 109363 FID FID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. ID ID Double 12 12 0 Unique reach ID, assigned during reach delineation in Netrace DOWN_ID DOWN_ID Double 12 12 0 ID of the downstream reach CHAN_ID CHAN_ID Double 12 12 0 ID of the collection of individual channel reaches beginning at a tributary junction and continuing upstream to the maximum headwater extent (the definition of a "channel" in NetMap). At confluences, the "channel" follows the reach with the largest drainage area with the smaller tributary then initiating a new channel ID. LENGTH_M LENGTH_M Double 12 11 5 Reach length in meters. AREA_SQKM AREA_SQKM Double 12 11 4 Contributing area (square kilometers) to the downstream end of the reach. ELEV_M ELEV_M Double 12 11 5 Elevation (m) of downstream end of reach OUT_DIST OUT_DIST Double 12 11 5 Distance from downstream end of reach to the basin outlet (km) SRC_DIST SRC_DIST Double 12 11 5 Distance (km) from the downstream end of the reach to the upstream end of the upstream-most reach on the same channel. FROM_DIST FROM_DIST Double 12 11 5 Distance (km) from channel mouth to downstream end of reach GRADIENT GRADIENT Double 12 11 5 The slope gradient of each reach. Gradient is calculated for every node in the linked-node channel data structure. Reach gradients are estimated as the mean gradient of all nodes containted in the reach. The gradient at each node is iteratively calculated by fitting a 2nd-order polynomial over a window centered on the node. Window length varies linearly with gradient, from 50m for gradients of 0.2 or greater to 500m for gradients of 0.001 or less. FitElev FitElev Double 12 11 5 LAKE LAKE Double 12 11 5 If a reach is within a mapped lake, it is given the lake ID value, otherwise zero. Lake locations are from the National Hydrographic Dataset (NHD). MAX_GRAD_D MAX_GRAD_D Double 12 11 5 Maximum downstream gradient over user-specified window. STRM_ORDER STRM_ORDER Double 12 12 0 Strahler (1952) stream order AZIMTH_DEG AZIMTH_DEG Single 8 7 2 Average downstream flow direction for reach, in degrees SINUOSITY SINUOSITY Double 12 11 5 Length of the channel divided by the length of the valley measured over 30 channel widths. Basin_ID Basin_ID Double 12 11 5 Basin identifier - basins generally from NHD (HUC12) MNANPRC_M MNANPRC_M Double 12 11 5 Mean annual precipitation depth (meters) for the contributing area to the downstream end of the reach. Mean annual precipitation values are from raster data available from the PRISM project (http://www.prism.oregonstate.edu/) for the period 1981-2010. MEANANNCMS MEANANNCMS Double 12 11 4 Mean annual flow for reach (cubic meters per second) based on regional regression equations. WIDTH_M WIDTH_M Double 12 11 4 Bankfull width (m); from statistical regression. Regression terms and coefficients vary regionally. See NetMap's Network Variables tool for regression equation and source. DEPTH_M DEPTH_M Double 12 11 4 Channel bankfull depth (m); from regional regression. The terms and coefficients for the regressions vary regionally; the models used are listed by region in the NetMap online technical help. FP_WIDTH FP_WIDTH Single 8 7 2 The average width (m) of the mapped floodplain, calculated at 2x bankfull depth above the channel. VAL_WIDTH VAL_WIDTH Single 8 7 2 Valley width calculated at 5 multiples of bankfull depth for use in the fish habitat intrinsic potential models (IP); VWI_floor is valley width/channel width is used in the IP models.But note that using this index can result in less accurate IP habitat mapping, particularly using LiDAR based NetMap datasets. For IP mapping, you will want to use the flooplain tool at 2 multiples of bankfull depth, and then run the channel confinement tool, and use that output in the IP model interface. For more information, see http://www.terrainworks.com/intrinsic-potential-ip-fish-habitat-modeling-read VWI_Floor VWI_Floor Single 8 7 2 Valley width index (ratio of valley width to channel bankfull width) at an elevation of 5 multiples of bankfull depth; used in calculating fish habitat intrinsic potential (IP), generally for anadromous fish (coho, steelhead, chinook), after Burnett et al. 2007.But note that using this index can result in less accurate IP habitat mapping, particularly using LiDAR based NetMap datasets. For IP mapping, you may want to use NetMap's flooplain tool at 2 multiples of bankfull depth, and then run NetMap's channel confinement tool, and use that output in the IP model interface. For more information, see http://www.terrainworks.com/intrinsic-potential-ip-fish-habitat-modeling-read ValCnstrnt ValCnstrnt Double 13 12 4 channel confinement classes, valley width/channel width: constrained, unconstrained, transition and intermediate - see NetMap tool for additional information DROPMAX DROPMAX Double 19 0 0 Maximum downstream waterfall drop. User-specified parameters. IP_Chinook IP_Chinook Single 7 6 4 Chinook intrinsic habitat potential (IP) from Busch et al., River Research and Applications, 2011 (http://www.onrc.washington.edu/MarinePrograms/IPmodeling/Discussion/IPModels/rra1597.pdf). Index values vary from 0-1, with higher values indicating greater intrinsic potential for development of chinook spawning habitat. Index values are dependent on channel gradient, channel width, and channel confinement, expressed as the ratio of valley width (delineated at 5 active channel depths above the channel from the DEM) to channel width. Index curves are piece-wise continuous linear functions: Gradient <= 0.02, IG=1; = 0.07, IG = 0.05; > 0.07, IG = 0 Width < 4m, IW = 0; > 20m, IW = 1 Confinement =1, IC = 0.25, >8.87, IC = 1 IP = (IG*IW*IC)^(1/3). Source=Busch et al., 2011. River Research and Applications, DOI: 10.1002/rra.1597 IP_Steelhd IP_Steelhd Single 7 6 4 Steelhead intrinsic habitat potential (IP) from Burnett et al. (2007; http://andrewsforest.oregonstate.edu/pubs/pdf/pub3854.pdf). Index values vary from 0-1, with higher values indicating greater intrinsic potential for development of steelhead rearing habitat. Index values are dependent on mean annual discharge (calculated using regional regressions to contributing area and mean annual precipitation), channel gradient, and the ratio of valley width (delineated from the DEM) and channel width (calculated using regional regressions to mean annual flow). Index curves are piece-wise continuous linear functions:However, be aware that IP model results can be out of date, see for more details:http://www.terrainworks.com/intrinsic-potential-ip-fish-habitat-modeling-read source=Burnett et al., 2007 IP_Pink IP_Pink Single 7 6 4 Pink salmon Habitat Intrinsic Potential IP_Chum IP_Chum Single 7 6 4 p_trib p_trib Single 7 6 5 Probability of a reach segment having a tributary confluence effect, based on the estimated probability of tributary effects (Benda et al., 2004 a&b, http://www.earthsystems.net/docs/Benda_etal_WRR_2004.pdf, http://www.fsl.orst.edu/clams/download/pubs/Brenda_et_al%202004%20BioScience.pdf). For each tributary junction, the probability of effects in the mainstem channel is calculated as a function of the ratio of tributary to mainstem channel contributing area. This probability is assumed to decrease linearly from a maximum at the junction to zero at a distance from the junction dependent on mainstem size. The modeled probability for each tributary is calculated for each node within this patch-length distance, and the conditional probability of effects at the node is determined accounting for all near by tributaries. The reach value is the mean probability of tributary effects for all nodes within the reach. Source = Benda et al., 2004, Water Resources Research, V40, DOI: 10.1029/2003WR002583, Benda et al., 2004, BioScience, V54, p 413-427. FlowVel FlowVel Single 7 6 4 Flow velocity (m/s) at bankfull depth BFQ BFQ Double 9 8 3 Bank full discharge (m3/s); calculated using bankfull depth, width and flow velocity StrmPow StrmPow Double 11 10 3 Stream power is calculated as: PgQs where P is density of water (1000 kg/m3), g is acceleration due to gravity (9.8 m/s2), Q is discharge (m3/s) and S is channel slope. Q is calculated as WdV where W is bankfull channel width (m), d is bankfull channel depth (m), and v is velocity (m/s). BeavHab BeavHab Integer 10 10 0 Intrinsic habitat potential for beaver, from Pollock et al., 2004 (http://gis.ess.washington.edu/grg/publications/pdfs/Pollock.pdf). Source=Pollock et al. 2004, North American Journal of Fisheries Management, V 24, p. 749-760. Fish Fish Integer 10 10 0 Each reach segment has a "fish" or "no fish" identifier, defined by the tool user or by an imported shapefile.Note that in the Nehalem watershed, the ODFW salmon (coho) distribution was used to define fish-bearing streams. FISH_RESID FISH_RESID Integer 10 10 0 P_DF_AVE P_DF_AVE Single 7 6 5 A relative potential for landslide-triggered debris flow effects (including scour, traversal, or deposition) within the reach. This value takes into account the number of upslope landslide sources, the potential for landsliding from each source, and the potential for a debris flow to travel from the source to the reach. Values are based on empirical models described in Miller and Burnett, 2007 & 2008 (http://www.fsl.orst.edu/clams/download/pubs/2008Geo_Miller_Burnett.pdf and http://www.fsl.orst.edu/clams/download/pubs/2007WRR_miller_burnett.pdf), which were calibrated to data from the Oregon Coast Range following the large storm of 1996. The values indicate the spatial density of modeled debris flow potential - the model indicates, for example, that we expect to find evidence of debris flows twice as often in reaches with a value of two than in reaches with a value of one, but it does not provide information on what the actual frequency is. Source = Miller and Burnett 2007, Water Resources Research, V43, doi::10.1029/2005WR004807; 2008, Geomorphology, V94 184-205 DF_Junct DF_Junct Single 6 5 4 Potential for debris flow effects in any reach (scour, traversal, deposition) - reported only at reaches intersecting another reach (e.g., tributary junction reaches); the reach value is the debris flow potential originating from the smaller tributary in the stream reach immediately upstream of the junction; see tool GEP_Cum GEP_Cum Double 13 12 4 The GEP (Generic Erosion Potential) value integrated over the entire upstream contributing area to the downstream end of the reach. GEP is found empirically to correlate with sediment yield, although the relationship is generally nonlinear. GEP_Cum thus provides a relative value proportional to total sediment production for the entire contributing area to the reach. GEP is a topographic index calculated for each DEM cell: GEP = A(r)*Slope/Bcontour, where A(r) is the contributing area to a DEM cell from within a radius r (here set to the DEM cell spacing), Slope is the surface gradient of the cell, and Bcontour is the contour length crossed by flow tubes entering the cell (a measure of topographic convergence). GEP values are truncated to a maximum of 1.0. GEP GEP Double 13 12 4 The GEP (Generic Erosion Potential) value integrated over the adjacent contributing area to the reach. GEP is found empirically to correlate with sediment yield, although the relationship is generally nonlinear. GEP thus provides a relative value proportional to total sediment production for the local (adjacent) contributing area to the reach. GEP is a topographic index calculated for each DEM cell: GEP = A(r)*Slope/Bcontour, where A(r) is the contributing area to a DEM cell from within a radius r (here set to the DEM cell spacing), Slope is the surface gradient of the cell, and Bcontour is the contour length crossed by flow tubes entering the cell (a measure of topographic convergence). GEP values are truncated to a maximum of 1.0. GEP_DEL GEP_DEL Double 13 12 4 The product GEP*DELIV integrated over the adjacent contributing area to a reach, where GEP is the Generic Erosion Potential of a DEM cell and DELIV is the modeled potential for delivery of material from the cell to a stream channel with a gradient less than or equal to a specified value. GEP_DEL provides a relative value proportional to the total sediment production delivered to stream channels from shallow landsliding, debris flow, and gullying from the local, adjacent contributing area (the drainage wings). GEP is a topographic index calculated for each DEM cell: GEP = A(r)*Slope/Bcontour, where A(r) is the contributing area to a DEM cell from within a radius r (here set to the DEM cell spacing), Slope is the surface gradient of the cell, and Bcontour is the contour length crossed by flow tubes entering the cell (a measure of topographic convergence). GEP values are truncated to a maximum of 1.0. DELIV is based on the model for debris flow delivery described by Miller and Burnett 2008 (http://www.fsl.orst.edu/clams/download/pubs/2008Geo_Miller_Burnett.pdf). DELIV values vary from zero to one. See Generic Erosion Potential and Sediment Delivery Tools Strm_Name Strm_Name String 30 0 0 REACHCODE REACHCODE String 8 0 0 w10_25cm w10_25cm Double 19 0 0 Predicted single year wood recruitment, pieces/100 m, using LEMMA vegetation data, for the diameter class indicated, using NetMap Watershed Scale wood recruitment tool - see NetMap Technical Help for additional information. w25_50cm w25_50cm Double 19 0 0 Predicted single year wood recruitment, pieces/100 m, using LEMMA vegetation data, for the diameter class indicated, using NetMap Watershed Scale wood recruitment tool - see NetMap Technical Help for additional information. w50_75cm w50_75cm Double 19 0 0 Predicted single year wood recruitment, pieces/100 m, using LEMMA vegetation data, for the diameter class indicated, using NetMap Watershed Scale wood recruitment tool - see NetMap Technical Help for additional information. w75_100cm w75_100cm Double 19 0 0 Predicted single year wood recruitment, pieces/100 m, using LEMMA vegetation data, for the diameter class indicated, using NetMap Watershed Scale wood recruitment tool - see NetMap Technical Help for additional information. GT100cm GT100cm Double 19 0 0 Predicted single year wood recruitment, pieces/100 m, using LEMMA vegetation data, for the diameter class indicated, using NetMap Watershed Scale wood recruitment tool - see NetMap Technical Help for additional information. SolShd SolShd Double 9 8 2 Solar energy to stream reach (watt-hours/m2) as a result of current (LEMMA) shade along with bare earth solar radiation - see NetMap technical Help for this tool result SolShdMax SolShdMax Double 9 8 2 Solar energy to stream reach (watt-hours/m2) as a result of bare earth radiation and a watershed maximum shade value (0.85) - see NetMap technical Help for this tool result SolDifMax SolDifMax Double 9 8 2 Solar energy to stream reach (watt-hours/m2) as a result of current (LEMMA) shade along with bare earth solar radiation, the difference between actual reach value and a watershed maximum value - see NetMap technical Help for this tool result SolBare SolBare Double 9 8 2 NetMap's prediction of thermal loading for bare Earth conditions; users provide input data on vegetation height, width [buffer width] and density. The model uses the parameters of direct beam and diffuse solar radiation with respect to 1) topographic shading, 2) channel width, 3) aspect, 4) latitude, and 5) streamside vegetation height and density. NTLT uses ArcMap's Solar Radiation tool and it calculates incoming solar radiation for every vertex in the stream network (each stream segment may have numerous vertices based on a channel's path across pixels). ArcMap's solar radiation model uses hourly intervals on July 20, typically the hottest day of the year. Incoming diffuse, direct, and total radiation values are computed for every hour, with the bare-earth DEM providing topographic shading. Thermal energy (watt-hours/m2) is calculated as an average of all intersecting vertices for each reach summed over the daylight period. shdLeft shdLeft Single 13 0 0 shdRight shdRight Single 13 0 0 SolDifShd SolDifShd Double 9 8 2 Solar energy to stream reach (watt-hours/m2), the difference between current (LEMMA) shade and the bare earth solar radiation - see NetMap technical Help for this tool result SolMean SolMean Double 13 12 4 Solar energy to stream reach (watt-hours/m2) as a result of current (LEMMA) shade along with bare earth solar radiation, aggregated downstream creating a downstream running average - see NetMap technical Help for this tool result TrbThrm TrbThrm Double 9 8 3 The variable Solshd is routed downstream and aggregated; the values represent differences in these values between tributaries and mainstem channels, providing an index of thermal refugia - see NetMap Technical Help TrbThrmSc TrbThrmSc Double 9 8 3 The variable Solshd is routed downstream and aggregated; the values represent differences in these values between tributaries and mainstem channels and multiplied by the ratio of tributary to mainstem drainage area, providing a relative index of thermal cooling or warming, scaled by the size of the tributary (and thus flow), providing an index of thermal refugia - see NetMap Technical Help FPchg FPchg Single 8 7 3 The difference in floodplain width (2x) from one stream reach to the next, indicating potential thermal refugia (upwelling) - see NetMap technical help tdif_l tdif_l Double 9 8 4 Hist-2040 JJA air temp chg degC-segment scale, from Climate Impacts Group tdif_c tdif_c Double 9 8 4 Hist-2040 JJA air temp chg degC-averaged downstream, from Climate Impacts Group FDSum_l FDSum_l Double 9 8 4 Hist-2040 summer flow %change-segment scale, from Climate Impacts Group FDSum_C FDSum_C Double 9 8 4 Hist-2040 summer flow %change-averaged downstream, from Climate Impacts Group FDWin_l FDWin_l Double 9 8 4 Hist-2040 winter flow %change-segment scale, from Climate Impacts Group FDWin_C FDWin_C Double 9 8 4 Hist-2040 winter flow %change-averaged downstream, from Climate Impacts Group prdif_l prdif_l Double 9 8 4 Hist-2040 precip %change-segment scale, from Climate Impacts Group prdif_c prdif_c Double 9 8 4 Hist-2040 precip %change-averaged downstream, from Climate Impacts Group LOCAR_KM2 LOCAR_KM2 Double 11 10 4 IP_Coho IP_Coho Double 13 12 4 20220504 iVBORw0KGgoAAAANSUhEUgAAASwAAADICAYAAABS39xVAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO xAAADsQBlSsOGwAAIABJREFUeJzsvdmTpPd1JXZ+375kZu1VvXcD3QABgiQIEKRGi6XhSOPwaOzw g18cfvBfMhH+RxSh8IsfPLYfbI5HomckesSdxEYAJAAC6G50N7pr6arK7dsXx7n3+6pbsjgjxRDo JPhdqQNELZlZBeTBveeee47Ttm2LoZ5o5XmOP/vzP8PbN99GvOlje2sNoe3CKUf45//sT3H18lX4 vv9rea66rjGdTvHGG2/ga1/7GtbW1vDrKv6rxJ/lP/zNd3B0cgde2GBzZ4yNzTHaukWZN+C/bffu 7mN+2uBLz38Nr7zyjV/b8w/1+S/nSb+AoSBg9PLLX8NHs5t4UN7FZGJh4rko7h/gr/76W/gn3/gj 3Lj+BYxGo/9ssDo+PsaPfvwjpEkif//rqv6xf/jj7+Pg6GNMNhzsnlvHaBITyQD5z6KBMQbbO5s4 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