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Chris Jordan, Steve Rentmeester, Carol Volk, Mimi D’Iorio, George Pess, Tim Beechie

A landscape classification approach for watersheds of the Pacific Northwest: is aquaticecosubregionalization even a word?. Chris Jordan, Steve Rentmeester, Carol Volk, Mimi D’Iorio, George Pess, Tim Beechie NOAA-NWFSC, Seattle. What are we doing, and why?.

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Chris Jordan, Steve Rentmeester, Carol Volk, Mimi D’Iorio, George Pess, Tim Beechie

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  1. A landscape classification approach for watersheds of the Pacific Northwest: is aquaticecosubregionalizationeven a word? Chris Jordan, Steve Rentmeester, Carol Volk, Mimi D’Iorio, George Pess, Tim Beechie NOAA-NWFSC, Seattle

  2. What are we doing, and why? • Classify the aquatic-landscape of the Pacific Northwest based on “relevant” broad-scale characteristics • Major determinants of watershed processes • Immutable geomorphic characteristics • Human impact • Data analysis support • Environmental variance partitioning • Evaluation tool for site selection

  3. A Made-up Example of What We Want the Output to Look Like

  4. A couple of examples of something similar, but not quite the same… • Hessburg et al. 2000. Ecological subregions of the ICRB based on PVG, Temp-precip, solar radiation, elevation. • Omernik et al. 1999+, US EPA Level III & IV Ecoregions based on terrestrial vegetation assemblages.

  5. What are we doing, and why? • Classify the aquatic-landscape of the Pacific Northwest based on “relevant” broad-scale characteristics • Data analysis support • Evaluation tool for site selection • Assess “representativeness” of current monitoring and restoration efforts. • Locate additional monitoring and restoration projects.

  6. We are developing a Network of Intensively Monitored Watersheds E. & W. Twin, Deep Cks. Skagit R. Estuary Libby, Gold and Beaver Cks. In Methow R. Little Anderson, Seabeck, Stavis, Big Beef Cks. Lower Entiat R. Germany, Mill, Abernathy Cks. Nason, Peshastin and Chiwawa Cks. In Wenatchee R. NF Nehalem R. Tucannon R. Scappoose R. EF Trask R. Lemhi R. Mill Ck. Siletz Mill Ck. Yaquina Cascade Ck. EF Lobster Ck. Cummins, Tenmile Cks. WF Smith R. Upper MF John Day R. Lower SF John Day R. Hinkle Ck. Winchester Ck. Hollow Tree Ck. – SF Eel R.

  7. How are we doing this? • Taking commonly available spatial data w/ consistent coverage across study area. • Generating functional data layers from above. • Attributing 6th field watersheds with a single value for each input data layer. • Grouping watersheds into clusters of “like”, or classes.

  8. Input Data Climate • Annual Precipitation • Month of Max Precipitation • Growing Degree Day Topography • Median Elevation • Median Hill Slope Geology • Stream sediment production • Water chemistry Channel Network • Density (by gradient) • Complexity (valley width) • Stream power • Tributary junctions • Watershed shape

  9. How are we doing this? • Taking commonly available spatial data w/ consistent coverage across study area. • Generating functional data layers from above. • Attributing 6th field watersheds with a single value for each input data layer. • Grouping watersheds into clusters of “like”, or classes.

  10. How are we doing this? • Taking commonly available spatial data w/ consistent coverage across study area. • Generating functional data layers from above. • Attributing 6th field watersheds with a single value for each input data layer. • Grouping watersheds into clusters of “like”, or classes.

  11. Hydrologic Unit Code 6th field HUCs Sub-watersheds (10,000-40,000 ac)

  12. Five data layers: 6th field watersheds with a single values for each input characteristic.

  13. Five data layers: 6th field watersheds with a single values for each input characteristic.

  14. How are we doing this? • Taking commonly available spatial data w/ consistent coverage across study area. • Generating functional data layers from above. • Attributing 6th field watersheds with a single value for each input data layer. • Grouping watersheds into clusters of “like”, or classes.

  15. Processing Step Processing Tools Spatial Analyst: Zonal Statistics & Reclassify Raster Compile categorical data for 6th order HUCS and build as attributes into a GIS shapefile Convert features from vectors to 200m raster grids Stack separate raster integer grids into one multi-band raster file Apply ISOCLUSTER and Maximum Likelihood Classification algorithms to separate classes based on pixel spectra Evaluate spatial patterns using Fragstats Spatial Analyst : Convert Features to Raster Raster Calculator or Command Line: Make Grid Stack or Composite Bands Tool Spatial Analyst Tools Command Line ISOCLUSTER Fragstats Patch Class and Landscape Metrics

  16. Where are we and next steps • Need to resolve 200m pixel v. 6th HUC grain • Need to clean up a few more data layers • Erosion potential v. Slope x Area • %T, R, S • Month of max ppt v. hydro regime • Need to resolve classification tool • ISODATA v. MCLUST • Need to make maps and get feedback • Need to move on to anthropogenic layers

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