GIS INSTRUCTIONAL MANUAL

GIS INSTRUCTIONAL MANUAL: BEAVER RESTORATION AND ASSESSMENT TOOL (BRAT) CASE STUDY: ESCALANTE RIVER WATERSHED VERSION 1.0 (RELEASE DATE: JANUARY 21, 2013) Prepared by: WILLIAM W. MACFARLANE, Research Associate JOSEPH M. WHEATON, Assistant Professor Ecogeomorphology & Topographic Analysis Lab Watershed Sciences Department Utah State University 5210 Old Main Hill Logan, UT 84322-5310 FEBRUARY 17, 2013

Recommended Citation: Macfarlane WW, and Wheaton JM. 2013. GIS Instructional Manual: Beaver Restoration and Assessment Tool (BRAT) Case Study: Escalante River Watershed. Ecogeomorphology and Topographic Analysis Lab, Utah State University, Prepared for Walton Family Foundation, Logan, Utah, XXX pp. Available at: http: XXX. 2013 Macfarlane and Wheaton All Rights Reserved Page 2 of 38

CONTENTS Introduction... 4 GIS Data... 5 GIS and FIS Data Processing... 5 Data Capture... 6 BEAVER DAM-BUILDING CAPACITY MODEL GIS PROCESSING... 6 NHD Data GIS Processing (Water Input)... 7 LANDFIRE LANDCOVER GIS PROCESSING AND CLASSIFICATION (Vegetation Input)... 12 Total Stream Power Calculations (Stream Power Input)... 18 Beaver Dam Capacity FIS... 22 Joining the Output Beaver FIS with the GIS... 24 Ungulate Capacity Model GIS Processing... 26 LANDFIRE LANDCOVER GIS PROCESSING AND CLASSIFICATION (Vegetation Input)... 27 Slope Map Generation... 29 Distance to water... 29 Ungulate Capacity FIS... 33 References... 37 Page 3 of 38

INTRODUCTION This manual provides step-by-step instruction on the GIS and Fuzzy Inference System (FIS) processing tasks that were performed for the pilot/proof of concept project in the Escalante River Watershed, southern Utah to develop and test a portable assessment tool called The Beaver Restoration and assessment Tool (BRAT). As such the manual provides the beta version processing steps that we developed and performed during the pilot projects contract period (January 1, 2012 through January 1, 2013). Updated instructions will likely be available from the authors in the near future. For updated instructional information please contact Wally Macfarlane at wally.macfarlane@gmail.com. The manual was generated with the assumption that the end user possesses a good working knowledge of the Geographic Information System (GIS) software package ArcGIS 10.0 (ESRI, 2012) and at least some exposure to the MathWorks Matlab R2012b Fuzzy Logic Toolbox (MathWorks, 2012). It was also assumed that you have access to both these software packages. In addition, there is a couple other freeware software packages that you will be prompted to download during the processing steps. The manual is divided into tasks and subset by steps within each task. The tasks and steps are sequentially organized. Therefore, we suggest that you follow the manual in the order it is presented for best results. The manual contains various screen shots to help clarify the processing steps and to ensure that our method is repeatable. However, since this is pilot project and the first time the approach has been used it is highly likely that questions will arise that require further clarification. In addition, you may find other way, potentially better ways, to perform the tasks that we have outlined. Therefore, we encourage your questions and suggestions in these regards. Page 4 of 38

BRAT consists of two capacity models, a beaver-dam building capacity model and an ungulate capacity model, that work together to assess beaver restoration potential. The beaverdam building capacity model uses both existing and potential vegetation layers to show current capacity and potential capacity. Potential capacity is capacity without limiting factors such as ungulate over grazing. BRAT consists of an innovative combination of vector and raster based geoprocessing FIS processing. The processing steps are described in the following pages and are organized by heading, subheading, task, and step. GIS AND FIS DATA All the GIS data used in this pilot study is stored in a geodatabase named Escalante Watershed.gdb. For your convenience and as an instruction aid all the features classes and grids that were generated during the steps outlined in this manual are included in the geodatabase. The feature class data in the geodatabase is structured into different containers based on the data type. For example, all NHD derived data is in a container called NHD. All the raster datasets are lumped together just inside the geodatabase. All the FIS data used in this pilot study is stored in a folder name FIS. GIS AND FIS DATA PROCESSING Both the beaver dam-building and ungulate capacity models consisted of a series of straight-forward geoprocessing steps that build upon one another to generate spatially explicit output data. The resulting GIS data was then input into Fuzzy Inference Systems (FIS) to assess the relative importance of these inputs. Final output beaver-dam capacity data were in the form of NHD stream (line) layers attributed to reflect dams per km across the watershed at a reach- Page 5 of 38

level (250 m). Whereas ungulate capacity data were in the form of raster data attributed by 0-4 with 0: low and 4: high indicating the level of capacity across the landscape. DATA CAPTURE Existing, readily and freely available GIS datasets from GIS data clearinghouses were collected and used as model inputs. These datasets included environmental parameter data to build both the beaver dam-building capacity model and the ungulate capacity model. Specifically, National Hydrography Dataset (NHD) Plus data http://www.horizonsystems.com/nhdplus/, LANDFIRE land cover data http://www.landfire.gov/, USGS Digital Elevation (DEM) data http://ned.usgs.gov/ and USGS StreamStats Regional Regressions equations http://pubs.usgs.gov/sir/2007/5158/. For NHD data download both stream and water body data, for the LANDFIRE data download both Us_110evt (existing vegetation type) and us_110bps (potential vegetation type) for USGS NED download the 10 m DEM data for your area of interest and for the USGS StreamStats data select the correct region and associated equations for base flow (PQ80 for the month with the lowest flows) and 2-year incurrence peak interval. BEAVER DAM-BUILDING CAPACITY MODEL GIS PROCESSING The beaver dam-building capacity model includes three inputs. Water (NHD streams), Vegetation (LANDFIRE landcover data), and Stream Power (based on USGS regional equations) (Figure 1). Page 6 of 38

NHD Perennial Streams LANDFIRE Land Cover USGS Regional Regression Equations Figure 1. Diagram showing beaver dam capacity model inputs. NHD DATA GIS PROCESSING (WATER INPUT) The NHD data processing consisted of four straightforward GIS processing tasks: Task 1: Subset the NHD stream layer to perennial streams; Task 2: Divide the perennial streams by 250 m lengths; Task 3: Buffer the segmented streams (250 m lengths) by 30 m width, and Task 4: Buffer the segmented streams (250 m lengths) by 100 m width (Figure 2). Page 7 of 38

Figure 2. Diagram showing NHD stream GIS processing tasks. Task 1: Subset the NHD stream layer (NHD_All_Streams) to perennial (NHD_Perennial_Streams). This is accomplished through the following steps: Step 1: Open NHD_All_Streams in ArcMap Step 2: Select by attribute: the Attribute field: StreamRive Make a selection of: perennial stream or river Page 8 of 38

Step 3: Export the selection as NHD perennial stream layer. Output: NHD_Perennial_Streams Task 2: Divide the NHD perennial streams by 250 m lengths. This is accomplished through the following steps: Page 9 of 38

Step 1: Merge all segments of NHD perennial streams into one segment (needed for step 3 to work as one step). Use the merge command under Editor. Step 2: Download Editing Labs Divide Line By Length Add-in http://www.arcgis.com/home/item.html?id=d5d27ee47330434b9a96b91136a0118f Installation and use: 1. Download and double-click the file. 2. To use the add-in, you must first add it to a toolbar in ArcMap. Click the Customize menu and click Customize Mode. Click the Commands tab and type Divide Line in the search box. Drag the Divide Line By Length command from the Editing Labs category onto any toolbar, such as the Editor or Advanced Editing toolbar. 3. Click the Edit tool on the Editor Toolbar and select the line that you would like to split. 4. Click Divide Line By Length on the toolbar to which you added it. 5. Type the length value you want to use to divide the line. 6. Press ENTER to split the line. If the length entered does not divide evenly into the line s length, the remaining leftover distance is not allocated among the new features. Note: Make sure your Add-in Manger settings are as follows: Page 10 of 38

Step 3: Selected the entire drainage network and clicked on the Divide Line by Length Tool and then in the pop-up box type 250. Because the projection is in meters the command divides the selected line into 250 m segments. Output: Segmented_250m_NHD_Perennial.shp Tasks 3: Buffer NHD perennial streams Step 1: Created a 100 meter (riparian and vicinity level) buffer using the Buffer command under the Geoprocessing Tab. Note: Use End Type FLAT Page 11 of 38

Step 2: Repeat the above step but this time generate a 30 m (bank and channel level) buffer. Note: Use End Type FLAT Outputs: Buf_100m_Seg_250m_NHD_Perennial Buf_30m_Seg_250m_NHD_Perennial LANDFIRE LANDCOVER GIS PROCESSING AND CLASSIFICATION (VEGETATION INPUT) Figure 3 show how the LANDFIRE land cover data for both existing (2008) and potential vegetation is classified by beaver vegetation food/building material preferences established in the literature. Figure 3. Diagram showing LANDFIRE land cover data classification for the beaver dam capacity model. Task 1: Classify the LANDFIRE land cover data Page 12 of 38

Step 1: Load LANDFIRE land cover type rasters: Us_110evt.img (existing vegetation type) and Us_110bps.img (potential vegetation type) and add a field called Code representing dam-building material preferences (0-4) (Table 1). Step 2: Use the Table 1 to classify the field SAF_SRM in Us_110evt and the field GROUPNAME in Us_110bps. Table 1. Suitability of LANDFIRE Land Cover as Dam-building Material O, Unsuitable Material - LANDFIRE land cover = agriculture, developed, roads, barren, nonvegetated, sparsely vegetated, grasslands or water. 1, Barely Suitable Material - LANDFIRE land cover = herbaceous wetland/riparian or shrubland, Transitional herbacous. 2, Moderately Suitable Material - LANDFIRE land cover = introduced woody riparian, woodland or conifer. 3, Suitable Material - LANDFIRE land cover = Maple, gambel oak or other deciduous upland trees, aspen/conifer. 4, Preferred Material - LANDFIRE land cover = cottonwood, willow, aspen or other native woody riparian. Outputs: Us_110evt_Code.img Us_110bps_Code.img Step 3: For Us_110evt_Code.img use the Lookup command to generate a new raster with Code as the lookup field. Step 4: For Us_110bps_Code.img use the Lookup command to generate a new raster with Code as the lookup field. Page 13 of 38

Outputs: Us_110evt_Look_Up_Code.img Us_110bps_Look_Up_Code.img Step 5: Perform Zonal Statistics: Using the Zonal Statistics command (ArcToolbox under Spatial Analyst Tools -> zonal). Statistics type: Mean Conduct this step a total of four times. 1st: Use Buf_30m_Seg_250m_NHD_Perennial as the zone data. Use the LANDFIRE land cover (Existing) Us_110evt_Look_Up_Code.img as the input value raster. 2nd: Use Buf_100m_Seg_250m_NHD_Perennial as the zone data. Use the LANDFIRE land cover (Existing) Us_110evt_Look_Up_Code.img as the input value raster. 3 rd : Use Buf_30m_Seg_250m_NHD_Perennial as the zone data. Use the LANDFIRE land cover (Potential) Us_110bps_Look_Up_Code.img as the input value raster. 4th: Use Buf_100m_Seg_250m_NHD_Perennial as the zone data. Use the LANDFIRE land cover (Potential) Us_110bps_Look_Up_Code.img as the input value raster. Page 14 of 38

Outputs: Existing_30m_Veg_Cap.img Existing_100m_Veg_Cap.img Potential_30m_Veg_Cap.img Potential_100m_Veg_Cap.img Task 2: Use the above generated raster datasets that contain the food/dam-building material suitability values (0-4) to the Segmented_250m_NHD _Perennial feature class. Step 1: Download Geospatial Modeling Environment (GME) Open Source GIS software http://www.spatialecology.com/gme/gmedownload.htm GMES has dependencies on R and ArcGIS. Therefore, select the download that matches the version or R or ArcGIS you are running. Note: GME s predecessor, was called HawthsTools, it s likely that you may have used this software in the past. Step 2: Install GME software 1. Download and extract the zip file. 2. You must use the setup.exe program, not the gme.msi program, to install GME. 3. GME is a stand-alone program that can be started from the Windows Start button -- Programs -- SpatialEcology. Page 15 of 38

Step 3: Click on the Geospatial Modeling Icon and run the software. Step 4: Use the isectlinerst command Conduct this step a total of four times. 1 st for the in use Segmented_250m_NHD_Perennial, for the raster use Existing_30m_Veg_Cap.img and for the prefix use ex_30. Page 16 of 38

2 nd for the in use Segmented_250m_NHD _Perennial for the raster use Existing_100m_Veg_Cap.img and for the prefix use ex_100. 3 rd for the in use Segmented_250m_NHD _Perennial for the raster use Potential_30m_Veg_Cap.img and for the prefix use pot_30. 4th for the in use Segmented_250m_NHD_Perennial for the raster use Potential_100m_Veg_Cap.img and for the prefix use pot_100. Step 5: For the output feature class Segmented_250m_NHD _Perennial remove the fields with the suffix MIN, MAX, END. Keep the field with the suffix Length Weighted Mean (LWM). LWM is calculated by multiplying the length of each segment by the raster cell value of that segment, summing this value across all segments, and finally dividing that sum by the total length of the polyline: where l is the length of a segment, v is the value of the raster cell for that segment, and L is the total line length. Below is what the resulting feature class attribute table should look like. Do the same for the 30m buffer data. Page 17 of 38

Below is what the resulting feature class attribute table should look like. Do the same for the 30m buffer data. The above generated tables (30 m and 100 m) become the inputs for the FISl Outputs: Need to list TOTAL STREAM POWER CALCULATIONS (STREAM POWER INPUT) Stream power is an expression of flow strength at a given point in a river (Worthy, 2005). Total stream power was calculated at base flow to gauge the maximum stream power at which beaver can build dams and at the 2-year recurrence interval to gauge the likelihood of dams persisting from year to-year due to stream power. Equation: Page 18 of 38

Where Ω is the stream power, ρ is the density of water (1000 kg/m 3 ), g is acceleration due to gravity (9.8 m/s 2 ), Q is discharge (m 3 /s), and S is the channel slope. Calculating discharge required discharge data and the generation of drainage area grids. Discharge estimates were obtained from USGS StreamStats Regional Regression Equations (region 6 for Escalante River Watershed). The base flow equation (Q p80 for August) Q P80 = 9.4102E-02 DRNAREA 0.7404 was obtained from Kenney et al. (2008). Whereas, the peak 2-year recurrence interval flow equation P K2 = 4,150 DRNAREA 0.553 (ELEV/1,000) 2.45 was obtained from Wilkowske et al. (2008). Task 1: Calculate Drainage Area (using a flow accumulation raster) Step 1: Clip the DEM to the watershed or area of interest Use the Extract by Mask command. Step 2: Fill the pits in the DEM Navigate to the Spatial Analyst > Hydrology Tools > Fill in the Toolbox or search for the Fill tool. Page 19 of 38

In the Fill dialog (below), specify the original input DEM and the name of the output raster you wish to create (make sure the name designates that it is a filled DEM). Make sure that all subsequent Hydrology Analyses are run on this filled DEM. Output: (name)_dem_fill Step 3: Calculate flow directions Again in the Toolbox, go to Spatial Analyst Tools -> Hydrology Tools -> Flow Direction. Specify the pit-filled DEM (NOT the original DEM) as the Input raster, and specify the new output raster as a flow direction raster. You will use this flow-direction grid for other hydrology analyses. Output: (name)_dem_flow_direction.img Step 4: Calculate flow accumulation Spatial Analyst Tools > Hydrology > Flow Accumulation. Page 20 of 38

The dialog box prompts you to input your flow direction raster. The output should be named something that designates the grid as a flow accumulation raster. Output: (name)_dem_flow_accumulation.img The flow accumulation raster provides the requisite information on Drainage Area. Task 2: Calculate channel slope Step 1: Generate a slope map in percent using the slope function within the spatial analysis extension Step 2: Extract raster DEM elevations to a polyline Click on the Geospatial Modeling Icon and run the software. The following tool isectlinerst (Intersect Lines With Raster) will do the trick. Page 21 of 38

For prefix use Elev for elevation. Task 3: The equations were carried out in the raster calculator BEAVER DAM CAPACITY FIS The beaver dam capacity model consists of two FISs, a vegetaion_fis and a combined_fis. The VEG FIS is a two input FIS that uses the 30 m (riparian vegetation) and 100 m (adjacent vegetation)buffer data to calculated a dam-building capacity based on land cover classification values (i.e., beaver preferences 0-4 values) (Figure 4). Note: if you are new to fuzzy logic and the Matlab Fuzzy Logic Toolbox a good place to start would be to read: http://www.mathworks.com/help/pdf_doc/fuzzy/fuzzy.pdf. Page 22 of 38

Figure 4. Vegetation FIS, two inputs, based on the 30 m and 100 m LANDFIRE land cover beaver dam capacity classification data. The Combined_FIS is a three input FIS that uses the output from the above VEG_FIS and the two stream power calculations base flow and two-year peak flow as the other inputs (Figure 5). Page 23 of 38

Figure 5. Combined beaver dam capacity FIS based on output from the vegetation FIS and stream power calculations baseflow and Peak 2-year interval. A successful run of the software produces the statement below: Done writing output file K:\etal\Projects\USA\Utah\Escalante\BRAT_FIS\Inputs\BRAT_BeaverCapacity_Escalante_pote ntial_veg_input_formatted.csv. Program Completed. JOINING THE OUTPUT BEAVER FIS WITH THE GIS Task 1: Prepare the shapefile and join the FIS Output with the NHD perennial stream layer Page 24 of 38

In this case, FIS output is: BRAT_ Beaver Capacity Escalante _potential_veg_input_formatted.csv. Prior to joining the csv table and the shapefile the following preparation steps must be taken. Step 1: Add the NHD perennial streams layer to ArcMap Step 2: Export it as a new shapefile: I called it /dlvdata/escalante_brat.shp. Step 3: Open the attribute table of the newly generated shapefile and delete all the fields except FID, Shape and you must have at least one other field in this case I had a field called ENABLED Step 4: Use Add Data to load BRAT_BeaverCapacity_Escalante_potential _veg_ input_ formatted.csv. Step 4: Join Escalante_BRAT.shp and BRAT_BeaverCapacity_Escalante_potential_ veg_input _formatted.csv based on the field FID. Page 25 of 38

In order to make the join permanent it needs to be exported as a new shapefile. Output: This becomes the final data that is attributed and shown on the maps. Beaver combined FIS field gives the dams per km per stream segment. UNGULATE CAPACITY MODEL GIS PROCESSING The ungulate capacity model includes three inputs. Distance to Water (NHD streams and water bodies), Vegetation (LANDFIRE landcover data), and Slope (based on USGS 10-m DEM) (Figure 6). Page 26 of 38

NHD Perennial Streams and water bodies LANDFIRE Land Cover USGS Regional Regression Equations Figure 4. Diagram showing ungulate capacity model inputs. LANDFIRE LANDCOVER GIS PROCESSING AND CLASSIFICATION (VEGETATION INPUT) Figure 7 shows how the LANDFIRE land cover data for existing (2008) was classified by ungulate forage preferences established in the literature. Page 27 of 38

Figure 7. Diagram showing LANDFIRE land cover data classification for ungulate capacity model. Task 1: Classify the LANDFIRE land cover data Step 1: Load LANDFIRE land cover type raster: Us_110evt.img (existing land cover type) Step 2: Export the Existing LANDFIRE Raster as Grazing_Veg_Capacity.img Step 3: Add a new field and name it Code to Grazing_Veg_Capacity.img to represent ungulate grazing preferences (0-4) (Table 2). Step 4: Assign the ungulate land cover preferences (0-4) to the field named Code based on Table 2 using field SAF_SRM in Us_110evt.img Table 2. Suitability of LANDFIRE land cover classes for ungulate grazing O = Unsuitable - LANDFIRE land cover = Cropland, developed, roads, barren, or water. 1 = Barely Suitable - LANDFIRE land cover = sparsely vegetated. Page 28 of 38

2 = Moderately Suitable - LANDFIRE land cover = conifer forest. 3 = Suitable - LANDFIRE land cover = woodland or evergreen shrubland. 4 = Preferred - LANDFIRE land cover = grasslands, scrubland steep or riparian Output file: Grazing_Veg_Capacity.img Step 4: Using the raster to ASCII command to convert the.img raster to an ASCII raster for used in metlab. Output file: Grazing_Veg_Capacity.asc SLOPE MAP GENERATION Task 1: Created a slope map Step 1: Open the 30 m DEM in ArcMap Step 2: Generate a slope map using the Slope Tool (ArcToolbox under Spatial Analyst Tools -> Surface). Use the Percent option for the output measurement. Step 3: Use Extract by Mask with your project area boundary layer to confine the slope map to the project area. Output file: Ungulate_Capacity_Slope.img Step 4: Use the raster to ASCII command to convert the.img raster to an ASCII raster format for use in Matlab. Output file: Ungulate_Capacity_Slope.asc DISTANCE TO WATER Task 1: Convert NHD waterbodies (nhd24kwb_a_140700005 and nhd24kar_a_140700005_1) to polyline for use in the ungulate capacity model (distance to water.) Step 1: Use the Polygon to Line command as follows: Page 29 of 38

Output: NHD_Lakes_As_Polyline Step 2: Use the Merge command to combine the resulting polyline lakes with the NHD perennial streams include streams outside your project area. Page 30 of 38

Output: NHD_Lakes_Perennial_Streams Task 2 Use the Euclidean Distance command to calculate line of sight distance of the landscape to water Step 1: Load the input layer, which is the layer that was generated in the previous task NHD_Lakes_Perennial_Streams Step 2: Assign an output grid name Output: Euclidean_Distance_Perennial_and_Lakes_30m.img Page 31 of 38

Step 3: Clip the output raster Euclidean_Distance_Perennial_and_Lakes_30m.img by your area of interest. Use Extract by Mask Page 32 of 38

Output: Distance_to_Water.img Step 4: Convert raster to ASCII raster using the Raster to ASCII command. Output: Distance_to_Water.asc UNGULATE CAPACITY FIS Task 1: Run the grazing capacity three input FIS Step 1: click on the MATLAB R2012a icon to start the program. Step2: Browse to the location were GrazingCapacity_3input is stored Page 33 of 38

Step 3: In the command window type FIS_IT and press enter The below dialog box should open and prompt you to select and FIS. Page 34 of 38

Step 4: Select GrazingCapacity_3input.fis The below dialog box should open and prompt you to select RiparianVegPrefCover input raster. Step 5: Path to the Escalante Watershed.gdb and selected the grazing_veg_capacity.asc The below dialog box should open and prompt you load Slope Input raster. Page 35 of 38

Step 5: Path to the Escalante Watershed.gdb and selected the ungulate_capacity_slope.asc The below dialog box should open and prompt you load WaterSource Input raster Step 6: Path to the Escalante Watershed.gdb and selected the distance_to_water.asc The FIS should now start Calculating this may take a few minutes. Page 36 of 38

The below dialog box should open and prompt you to save your FIS output Then it will need to save the FIS Grid to a File this will take even a bit longer. Step 7: Open ArcMap Step 8: Calculate Statistics on the Output FIS grid REFERENCES Kenney, T.A., Wilkowske, C.D., Wright, S.J., 2008. Methods for Estimating Magnitude and Frequency of Peak Flows for Natural Streams in Utah, U.S. Geological Survey, Prepared in cooperation with Utah Department of Transportation and the Utah Department of Natural Resources, Divisions of Water Rights and Water Resources. http://pubs.usgs.gov/sir/2007/5158/pdf/sir2007_5158_v4.pdf Wilkowske, C.D., Kenney, T.A., and Wright, S.J., 2008, Methods for estimating monthly and annual streamflow statistics at ungaged sites in Utah: U.S. Geological Survey Scientific Investigations Report 2008-5230, 63 p. Available at http://pubs.usgs.gov/sir/2008/5230 Page 37 of 38

Worthy, M. 2005. High-resolution total stream power estimates for the cotter river, namadgi national park, australian capital territory. Pages 338-343 in Regolith 2005 Ten Years of the Centre for Resource and Environment Studies. Australian National University, Canberra, Australia. Page 38 of 38