1. 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

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.

7. 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.

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

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

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

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

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

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

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

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

19. Compile categorical data for 6 th 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 Spatial Analyst: Zonal Statistics & Reclassify Raster Raster Calculator or Command Line: Make Grid Stack or Composite Bands Tool Spatial Analyst Tools Command Line ISOCLUSTER Processing StepProcessing Tools Fragstats Patch Class and Landscape Metrics

21. 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