11 Level-1 Initial Channel Analysis Workflow

🪛 Practical 🔬 Theory

Level 1 Workflow

This chapter describes the tool workflows and processes to complete a Level 1 (L1) FluvialGeomorph analysis. The purpose of this level is to extract basic channel dimensions from LiDAR surveys. Developing terrain models for the project study area for all available LiDAR survey events (events).Multiple survey events provide comparable channel dimensions for a reach overtime.

Level 1

Study Area Coordinate System

Choose a horizontal and vertical coordinate system for all of the vector and raster datasets created. Using the same coordinate system for all study area datasets helps avoid errors introduced by input datasets containing differing coordinate systems, particularly incorrect handling of datums and units. The horizontal and vertical coordinate systems that you select will be used for all datasets created for this study area. It is the analyst’s responsibility to ensure that each dataset uses these specified horizontal and vertical coordinate systems. Each dataset imported into a study area geodatabase must be projected into the projected horizontal and vertical coordinate systems.

Horizontal Coordinate Systems - FluvialGeomorph currently supports any projected coordinate system with linear units of meter, feet, or US survey feet. Geographic coordinate systems (angular units, e.g., “Lat-Lon”) are not supported.
Vertical Coordinate Systems - FluvialGeomporh currently only supports vertical coordinate systems with units of feet. Since most LiDAR is currently delivered in the NAVD 88 vertical datum, it is recommended to use NAVD 88 for consistency. The analyst must be sure that the raster DEMs created for analysis in this chapter have vertical units of feet. Instructions for converting raster DEM values from meters to feet are included below.

Create Study Area Geodatabases

Creation of a folder structure to store the the study area elevation data is the first step in managing the spataial data for this workflow. Next, sub-folders will be created to store the terrain data for each available 🗺️ LiDAR survey(#units_of_analysis). Initially, you will not know what LiDAR surveys exist for your study area until you begin your search for data described below. You will repeat the following steps for each LiDAR survey that exists for this project study area. The elevation data for each LiDAR survey will be processed separately and a synthetic stream network will be derived for each LiDAR survey independently. You will begin processing the data for the 🗺️ event event LiDAR survey first, then work backward in time to process earlier LiDAR surveys in reverse chronological order. Several analysis steps require the base event data to be processed first. For some tools, surveys prior to the base event use the base event data as inputs. This is done to express earlier surveys in terms of the base event for comparison purposes.

The following is an example of how to organize the working directory:

Create a new folder on a local workstation drive. Name it for the project study area.
Within the project study area folder create an 📁 LPC folder.
Within the 📁 LPC folder, create folders to store the data.
Name each folder using the project name and suffixed with the LiDAR survey event (_<LiDAR survey 4-digit event>). For example, if the project name is “Papillion Creek” and the LiDAR survey event event is 2016, then the folder would be named 📁 Papillion_Creek_2016.
Within each LiDAR survey folder. This will be used in later steps if needed to store and process the raw LiDAR data for each survey.
Within each LiDAR survey folder.
Name each file geodatabase using the project name and suffixed with the LiDAR survey event (_<LiDAR survey 4-digit event>).
Use the following folder structure to organize the terrain data:

Project_Name
└─── LPC 
│    └─── ProjectName_event1
│    │    └─── LAS
│    └─── ProjectName_event2
│    |    └─── LAS
│    └─── ProjectName_event3
│         └─── LAS
└─── ProjectName_event1.gdb
|
└─── ProjectName_event2.gdb
|
└─── ProjectName_event3.gdb
│         ...
└─── Exports
└─── Maps

Define Study Area

Define the location and extent of the study area. FluvialGeomorph project study areas are typically of three types, distinguished by their extent:

Small Reach - Required by projects analyzing a problem at a specific location. These project study areas are typically defined by a single point location, often representing a piece of built infrastructure (e.g., bridge, culvert, stream crossing, dam, revetment, gage, etc.) or specific stream feature (e.g., stream confluence, bank failure, severe bed erosion, oxbow cutoff, etc.). Analysis of these problems usually only requires examining a fixed distance up and down stream of the feature of interest. This distance up and down stream is determined by the scale of the driving factors.
Long Reach - Required by projects analyzing a problem that spans a long set of connected stream reaches. These projects study areas are typically defined by several miles of stream, possibly including tributaries to the primary reach being analyzed.
Watershed - Required by projects analyzing watershed scale problems. FluvialGeomporh analysis of all streams in watersheds ranging in size from 1-3 HUC12 watersheds is feasible.

Create Study Area Areal Extent

Create a rough bounding polygon of the study area. This polygon should define the “must-have” extent for both communicating the extent of the study area, as well as helping to define the area within to acquire elevation data. This extent only needs to cover the extent of the stream to be analyzed and does not need to include the entire contributing area of the watershed.

Define Study Area Longitudinal Extent

Define an initial study area longitudinal extent. This step will use existing, medium resolution hydrography to help establish the rough extent of the study area. The feature classes imported in this step will be used only as an initial coarse-scale representation of the reaches to facilitate early study area definition. This will derive high resolution delineation of the reaches.

Acquire Contributing Area Watershed Elevation Model

Acquire an existing, pre-made DEM of the entire study area contributing watershed. This DEM will help determine the following parameters:

Determine if an existing, pre-made DEM will serve for this FluvialGeomorph analysis.
Derive high resolution project study area watershed extents.
Calculate reach scale drainage area. The coverage of this DEM should cover the entire upstream contributing watershed of the study area.

Multiple LiDAR Surveys
Since the study area watershed boundaries are unlikely to have changed between LiDAR surveys, it is unnecessary to acquire the entire watershed elevation model for LiDAR survey dates prior to the 📊base event. Only the watershed elevation model representing the base event needs to be acquired.

Develop High Resolution Elevation Model

This DEM is used to derive a detailed stream terrain model that meets the resolution requirements of the study.

Download LiDAR point cloud data

LiDAR point cloud data is typically available from state or federal agencies. The following are some examples of where LiDAR point cloud data can be obtained: * USGS National Elevation Dataset (NED) * State-specific LiDAR data sources

Build a DEM from LiDAR point cloud data

The LiDAR point cloud data is processed to create a high-resolution DEM. This DEM will be used for detailed analysis of the stream and its surrounding terrain.

Verify that the DEM elevations are in feet

The DEM must have vertical units of feet. If the DEM is in meters, it must be converted to feet before proceeding with the analysis.

Create a hillshade to improve visualization

This step is optional, but creating a hillshade can help visualize the terrain and identify features of interest in the study area.

Hydro Modify DEM

Creating a hydro-modified DEM to ensure proper water flow across the study area.

Identify Flow Blockages

Developing a 🗺️ cutlines feature class representing flow blockages in the study area is used further in the workflow.

Examine the stream channel to be analyzed through the study area and determine if there are any blockages to flow in the DEM.
Focus only on flow blockages within the main channel of the study reaches. Flow blockages outside of the the channels of the study reaches do not need to be identified for FluvialGeomorph analysis.
These blockages are typically built infrastructure such as road embankments where streams are conveyed through culverts or underground storm water structures. Developing a 🗺️ cutlines feature class representing flow blockages in the study area is used further in the workflow.
If there are flow blockages in the study area reach channels, create a new line feature class named 🗺️ cutlines to store terrain modifications that remove flow blockages. This feature class must be in the same coordinate system as the DEM being modified.
In an edit session, identify human structures that block flow along the channel of the stream reach being studied.
Draw a cutline beginning at the upstream side of the blockage to a point just downstream of the blockage.
The start point and end point of the cutline must cover the area to be modified.
The downstream end of this cutline must be located in “good data”, because the lowest DEM value found along this line will be used to re-assign DEM values to all DEM pixels covered by the cutline.

Burn cutlines into the terrain

This removes flow blockages from the terrain dataset.

Use the 🛠️ Hydro DEM tool to “burn” the 🗺️ cutlines features into the study area watershed DEM. This tool creates the 🗺️ dem_hydro raster. Rename this DEM 🗺️ dem_hydro.
Use the 🛠️ Hydro DEM tool to “burn” the 🗺️ cutlines features into the high resolution DEM. This tool creates the 🗺️ dem_hydro raster.

Define Stream Reaches

Synthetically derive from the terrain the study area reaches and their watersheds.

Derive Stream Network

Derive a synthetic vector stream network from the DEM for the study area.

Use the high resolution DEM to derive the stream network.
Use the 🛠️ Stream Network tool to create a synthetic stream network from the hydro-modified DEM. The 📊 processes parameter can be safely set to approximately 2 less than the number of cores on the computer running the tool.
The 📊 threshold parameter should be set to a value of 200,000 to 500,000 depending on the study area.
If the resulting 🗺️ stream_network feature class is too dense (requiring a large amount of editing to remove extraneous tributaries), try rerunning the tool and increasing the 📊 threshold value. Conversely, if the resulting 🗺️ stream_network feature class is too sparse (not enough of the stream network was delineated), try rerunning the tool and decreasing the 📊 threshold value.
Edit the resulting 🗺️ stream_network feature class to remove all tributary streams that do not constitute the network that will be analyzed in this study.
Edit the 🗺️ stream_network feature class to ensure that stream segments are represented by a single line and that there are no gaps in the steam network.

Define Reaches

Segment the stream network into a set of sites and reaches that can be analyzed in more detail through the remainder of the study. The 🗺️ stream_networkmust be sub-divided into a set of sites and reaches that meet the following requirements:

Criteria for Creating Sites:

A project study area composed of several sub-watersheds will need to be divided into a set of 📊 sites(#units_of_analysis).
Sites within a project area are typically named tributaries that are the next hierarchical level beneath the project.

Criteria for Creating Reaches:

“Major” tributaries should be used to divide a site into reaches. How big of an increase in drainage area/discharge constitutes a major tributary depends on the size of the watershed and physiographic region.
A specific reach should contain a range of similar drainage area values.
Slope and sinuosity can be considered in the decision to subdivide a reach.
Built infrastructure may be used to divide reaches (e.g., dams, major roads).
Study objectives may drive the definition of reaches (e.g., economic benefits analysis, existing project reach definition).
The distribution of the slope and sinuosity values along the stream network may help determine the natural breaks in the stream network.

Using the criteria chosen from the list above, use the standard ESRI edit tools to subdivide the 🗺️ stream_network feature class into a set of features representing the reaches of your study.

Manually edit the 🗺️ stream_network feature class to modify the geometry to create a set of features representing the study area sites and reaches.
Set the 📊ReachName field to the value to be used to uniquely define sites and reaches throughout the remainder of the study.
Reach names are typically created using the site name and adding a suffix for the reach (e.g., R1, R2, etc.).
Site names are typically defined by the primary tributary name.
Be deliberate with the naming of sites and reaches as these names are used for all operations by each tool.

Derive Flowline

Creatng a new site geodatabase, derive the site flowline, create new reach geodatabases for each reach, and copy the flowline to each reach’s geodatabase are the multiple steps needed in the portion of the workflow.

Create the Flowline

Deriving the site flowline is next. The 🛠️ Flowline tool converts a 🗺️ stream_network feature into a 🗺️ flowline feature class. This tool smooths the 🗺️ stream_network geometry and converts the flowline into a route.

Use the 🛠️ Flowline tool to process the site 🗺️ stream_network feature class to produce a new 🗺️ flowline feature class.
Set the 📊 output_workspace parameter to the site geodatabase.
Use a 📊smooth_tolerance parameter value from 🧮 5-20. The goal is to produce a smooth flowline, but not to remove too much resolution from the line.
Ensure that the flowline remains in the channel and is not simplified into the floodplain. If this occurs, rerun reducing the degree of smoothing.
Edit the 🗺️ flowline feature class to ensure that the flowline is digitized beginning with the downstream end and digitized upstream.
In an edit session, select the flowline feature, choose to edit vertices, and ensure that the red endpoint is at the upstream end of the flowline.
If not, use the “Reverse Direction” (aka flip) command to ensure the flowline is digitized in the upstream direction.
It is critical that the flowline is digitized in the upstream direction. If this step is not performed, all subsequent tools will malfunction.

Create the Reach Geodatabase

Create a set of new reach geodatabases for each reach in a site and populate these reach geodatabases with initial data. This step will need to be repeated for each reach AND survey in the project study area 🗃️site. For example, if a site has five reaches (e.g., R1-R5) and three LiDAR surveys (e.g., 2016, 2010, 2006), then a total of 15 reach geodatabases must be created at this stage:

Reach Geodatabases Required for a Site with 5 Reaches and 3 LiDAR Surveys.
2016	2010	2006
y2016_R1.gdb	y2010_R1.gdb	y2006_R1.gdb
y2016_R2.gdb	y2010_R2.gdb	y2006_R2.gdb
y2016_R3.gdb	y2010_R3.gdb	y2006_R3.gdb
y2016_R4.gdb	y2010_R4.gdb	y2006_R4.gdb
y2016_R5.gdb	y2010_R5.gdb	y2006_R5.gdb

In the 📁 site data folder(#folder_structure), create a new reach geodatabase named for the reach. Use the 📊 ReachName value for the name of this new reach file geodatabase.
Reach names are typically created using the site name and adding a suffix for the reach (e.g., R1, R2, etc.).
Back in the site geodatabase, select the feature in the 🗺️ flowline feature class representing the current study reach. Use the “Data | Export Features” function to export the selected reach feature to the new reach geodatabase. Name the exported feature class 🗺️ flowline.
Ensure this new reach geodatabase version of 🗺️ flowline contains only one feature representing the current reach.
Ensure that the 📊 ReachName field contains the correct name for the reach. As this reach name value is used throughout the toolbox, it is extremely important to ensure this value is used consistently across all feature classes for this reach. Failure to be consistent with the 📊 ReachName value will lead to lots of errors that are difficult to troubleshoot. Get it right from the beginning.

Create Flowline Points

Now converting the 🗺️ flowline into a series of points along the reach is required. The 🛠️Flowline Points tool takes the 🗺️ flowline feature class, converts it to a route, calculates the distance to the mouth of the river for all vertices, and creates a 🗺️ flowline_points feature class.

Use the 🛠️ Flowline Points tool to convert the 🗺️ flowline feature class into a new feature class named 🗺️ flowline_points feature class.
Set the 📊 station_distance field to approximately 🧮 1 meter.
For a site with multiple reaches, set the 📊 km_to_mouth parameter for the downstream-most reach to 🧮 0.
Set the 📊 km_to_mouth parameter for each upstream reach to the upstream-most value i.e., the highest 📊 km_to_mouth value of the downstream reach’s 🗺️ flowline_points feature class of the downstream reach. For example, set the 📊 km_to_mouth of the Reach-2 🗺️ flowline_points feature class to 🧮 1.2345 if the maximum value of Reach-1’s 🗺️ flowline_points feature class 📊 km_to_mouth field is 🧮 1.2345.
The goal is that longitudinal stationing within a site containing multiple reaches should be sequential and unique throughout the site (i.e., lower station values at the bottom of the site and higher station values at the top of the site). This allows reach feature classes to be combined after reach-level analysis is complete.
The 📊 calibration_points, 📊 point_id_field, and 📊 measure_field parameters can be left blank when processing the 📁 base event.

Multiple Surveys
To make LiDAR surveys collected before the 📁 base event directly comparable to the base event, the 🗺️ flowline from each previous survey must be 📊 calibrated to the base event. This adjusts any changes in flowline planform between survey events to be expressed in terms of the base event longitudinal stationing.

If multiple LiDAR surveys exist for a project study area, the 🗺️ flowline_points feature classfor any previous LiDAR survey must be calibrated using the 🗺️ flowline_points feature classof the base event.
For example, if 2016 is the base event, when deriving the 🗺️flowline_points feature class for a LiDAR survey from 2010, the base event’s 🗺️ flowline_points feature class (2016) must be used for the 🛠️ Flowline Points tool’s 📊 calibration_points parameter value.
Set the 📊 point_id_field and 📊 measure_field parameters to the fields in the base event’s 🗺️ flowline_points feature class.
Set the 📊 search_radius parameter to the maximum distance between the 🗺️ flowline of the current survey and the base event 🗺️ flowline feature classes.

Define Initial Floodplain and Channel Extent

Define the initial floodplain and channel extent, for each reach and survey event.

REM DEM

Produce a relative elevation model (REM), which is a REM DEM normalizing stream bank elevations for a specific reach.

Inspect the reach to determine the width of the active floodplain. Use the measure tool to measure from the 🗺️ flowline outward to the widest extent of the active floodplain. This value will be used as the 🧮 buffer_distance value in the following step.
Use the 🛠️ REM tool to create a 🗺️ REM (REM DEM) for the study reach. Set the 🧮 buffer_distance field to a distance wide enough to capture the reach’s entire active floodplain.

Estimate Initial Channel Extent

The purpose of this step is to use the 🗺️ REM to visually extract an initial channel extent polygon. The 🗺️ REM created in the last step can be used to iteratively explore different inundation extents derived from various water surface elevations.

Add the 🗺️ REM raster to the map Table of Contents. Name this layer 🗺️ channel_polygon feature class.
On the Symbology tab of the 🗺️ channel_polygon feature class, use the Classified renderer to classify the raster into 2 classes. Set the first class boundary to the REM elevation that you would like to explore. Set the color of the first class (min value - REM elevation) to blue and the color of the second class (REM elevation - max value) to No Color.
Set the transparency of the 🗺️ channel_polygon feature class to 🧮 50%.
Begin to delineate the channel extent by selecting a REM elevation that inundates the channel up to at least the first terrace. The goal at this stage is to select a REM elevation that captures the extent of the channel without “spilling” too much water into the floodplain. Once you discover which REM elevation begins to allow water to access the floodplain, reduce the REM elevation value slightly to keep the water in the channel. Try several REM elevation values to help make the decision.
When you have chosen a REM elevation, use the 🛠️ Water Surface Extent tool to extract an initial channel extent area polygon. This tool creates a new polygon feature class named 🗺️ banks_raw_xxx, where xxx is the REM elevation selected.
This feature class must be edited to select the channel area polygon(s). Open the attribute table for the 🗺️ banks_raw_xxx feature class and use advanced sorting to sort first by 📊 gridcode and then by 📊 Shape_Area. Polygons with 📊 gridcode = 🧮 1 are polygons inundated at the REM elevation. Typically, the polygons with the largest area represent the channel. Begin selecting 📊 gridcode = 🧮 1 polygons with the largest area until the entire channel area is selected.
Export these selected features to a new feature class named 🗺️ initial_channel_extent.
Delete the 🗺️ banks_raw_xxx feature class created in this section.

Create the Initial Channel Mask layer

The purpose of this step is to create a layer that defines an area just beyond the initial channel extent.

Add the 🗺️ REM feature class to the map Table of Contents. Name this layer 🗺️ channel_polygon feature class.
In the symbology of this layer, change the renderer from 📊 stretched to 📊 classified. Set the number of classes to 2. In the 📊 classification dialog, set the break value between the two classes to about one to two feet higher than the initial bankfull extent estimate. A couple of feet above the initial bankfull extent estimate should define the extent of the just the channel. For example, if the initial bankfull extent was estimated at 102 REM feet, the initial bankfull height estimate would be 2 feet. One foot higher than the 2 foot initial bankfull height estimate would therefore be 103 REM feet.
Set the transparency of the 🗺️ channel_polygon feature class to 🧮 50%.

Estimate Initial Floodplain Extent

The purpose of this step is to create a layer that defines the an initial estimate of the floodplain inundation extent.

Add the 🗺️ REM feature class to the map Table of Contents. Name this layer 🗺️ floodplain_polygon feature class.
In the symbology of this layer, change the renderer from stretched to 🧮 classified. Set the number of classes to 2. In the 📊 classification dialog, set the break value between the two classes to four times the initial bankfull extent estimate. Four times the initial bankfull extent estimate should define the extent of the active floodplain. For example, if the initial bankfull extent was estimated at 102 REM feet, the initial bankfull height estimate would be 2 feet. Four times the 2 foot initial bankfull height estimate would therefore be 108 REM feet.
Set the transparency of the 🗺️ floodplain_polygon layer to 🧮 50%.

Create Regular Cross Section Geometry

The purpose of this stage is to create regularly spaced stream cross sections and extract terrain-derived hydraulic parameters for each reach and survey event.

Create Regular Cross Sections

The purpose of this step is to create regularly spaced cross sections along each reach.

The goal of this step is to create a set of regularly spaced cross sections that well represent the channel conditions found in this reach.
Determine the typical maximum distance from the reach 🗺️ flowline to the edge of the active floodplain. The goal is not to identify the maximum distance to the edge of the floodplain, but to identify the typical distance to the edge of the floodplain.
Determine the spacing between cross sections necessary to represent conditions along this stream. Cross section spacing for small stream of 50-100 feet works well. Larger rivers do not require such tight spacing.
Use the 🛠️XS Layout tool to create a set of regularly spaced cross sections (referred to as transects in this tool). Use the values determined in the previous steps to set this tool’s parameters.
For a site with multiple reaches, regular cross sections must be uniquely numbered across all reaches. The 📊 Seq field values of regular cross sections should not repeat within the reaches of a site.
The downstream-most cross section in the site should be numbered starting with the 📊 Seq field value of 🧮 1 and increase moving upstream.
The 🛠️ XS Layout tool automatically numbers regular cross sections 📊 Seq values starting with the value 🧮 1 at the downstream-most cross section.
Use the 🛠️ XS Resequencetool to set the starting 📊 Seq value for each reach.
For all reaches other than the first reach (downstream-most) in a site, the cross sections must be re-sequenced using the 🛠️ XS Resequence tool.
Set the 📊 Seq field value for each upstream reach to the upstream-most value (i.e., the highest 📊 Seq value of the downstream reach’s regular cross section feature class) of the downstream reach.
For example, set the 📊Seq of the Reach-2 regular cross section feature class to 58 if the maximum value of Reach-1’s regular cross section feature class 📊 Seq field is 57.

Calculate Cross Section Watershed Area

The purpose of this step is to calculate the watershed area for each regularly spaced cross section.

From the study area geodatabase, use the 🗺️ watershed_contributing_arearaster that covers the entire contributing watershed of the study area.
Use the ERSI 🛠️ Clip Raster tool to clip the 🗺️ watershed_contributing_area raster to 🗺️ stream_network_buffer to speed tool run time.
Add the 🗺️ contributing_area_buffer raster to a map and symbolize with a “hot-cold” stretch renderer.
Add the 🗺️ flowline and regular cross section features classes to the map. Place them on top of the 🗺️ contributing_area_buffer raster.
Determine the maximum distance from the intersection of each cross section and the 🗺️ flowline feature class to the nearest pixel of high flow in the 🗺️ contributing_area_buffer raster. This value will be used for the 📊 snap_distance in the next step.
Use the 🛠️ XS Watershed Area tool to calculate the watershed area for each cross section.
For the 📊 flow_accum parameter, use the 🗺️contributing_area_buffer raster.
For the 📊 snap_distance parameter, use the distance you calculated in a previous step.

Calculate Cross Section River Position

The purpose of this step is to calculate the river position for each regularly spaced cross section.

Use the 🛠️XS River Position tool to calculate the distance to the mouth of the river for each cross section.
The river position of each cross section will be used in later steps to calculate several channel parameters (i.e., gradient, sinuosity).

Calculate Cross Section Points

The purpose of this step is to convert each cross section into a set of evenly stationed points and assign DEM and REM elevation values.

Use the 🛠️ XS Points tool to calculate cross section station points for each cross section.
The 📊 station_distance parameter should be set to approximately the resolution of the DEM. For example, if the DEM has a cell size of 1 foot (0.3048 meter), set the 📊 station_distance to that distance (using the linear units of the coordinate system used for the project’s vector data).
This tool creates a new feature class named 🗺️ XSpoints.

Calculate Cross Section L1 Dimensions

The purpose of this step is to calculate the L1 dimensions for the regularly spaced cross sections.

Determine the moving window size
Many stream metrics are scale dependent, meaning these metrics are affected by the size of the moving window used in their calculation. To determine the appropriate size of the moving window for this reach, use the following steps:

Many stream metrics are typically calculated using a moving window size equal to two meander wavelengths (one upstream meander wavelength and one downstream meander wavelength).
Using the initial 🗺️ Channel_polygon layer that you created earlier, estimate the typical bankfull width for the reach.
Estimate the length of two meander wavelengths by multiplying the bankfull width estimated in the last step by 🧮 10 (e.g., 30ft bankfull width * 10 = 300ft, two meander wavelengths).
Determine how many cross sections two meander wavelengths represent. For example, if regular cross sections are spaced 100ft apart, then two meander wavelengths would be 3 cross sections (i.e., 300ft / 100ft between cross sections).

Calculate L1 Dimensions

Use the 🛠️ XS Dimensions, Level 1 tool to calculate L1 dimensions.
Set the 📊 xs_fc parameter to the regular cross sections feature class you created in a previous step.
Set the 🧮 lead_n parameter to the number of upstream cross sections that you calculated in a previous step.
If the elevations in the channel seem noisy, check the 📊 use_smoothing parameter and set the 📊 loess_span parameter to a value between 🧮 0-1.
Confirm that the 📊 vert_units of the DEM are in feet.

Confirm the degree of smoothing

Use a chart to verify the choice of the smoothing 📊 loess_span parameter.
Right-click on the 🗺️ *_dims_L1 feature class in the map Table of Contents and select “📊 Create Chart”, and select 🧮 Line. In the 📊 Date or Number dropdown, choose the field 🧮 POINT_M. In the 📊 Aggregation dropdown, choose 🧮 None. In the 📊 Numeric field(s) checklist, check the boxes next to 🧮 Z and 🧮 Z_smooth. Click the “Apply” button to view the chart.
Visually assess the degree of smoothing. The smoothing should be high enough to eliminate LiDAR elevation noise, but not so high as to eliminate meaningful channel elevation change.
If the smoothing is not ideal, re-run the tool and adjust the 📊 loess_span parameter.

Identify Infrastructure

The purpose of this stage is to identify salient features in the floodplain that may be affecting channel hydraulics along each reach. Here are some ideas for the features you should identify:

Significant tributaries
Built infrastructure
Significant geologic features

Create Features

The purpose of this step is to identify the longitudinal position of noteworthy stream features for graph and map labeling.

Create a new point feature class named 🗺️ features containing the following fields:
- 📊 Name - Text 🧮 50, Used to record the name of the river feature.
- 📊 km_to_mouth - 🧮 double, Used to record the feature’s longitudinal position within the reach.
Working upstream from the downstream end of the reach, examine the DEM and aerial imagery for significant river features and built infrastructure that could potentially impact stream structure and function.
Add the 🗺️ flowline_points feature class to the current map.
Set the display field to the 📊 km_to_mouth field.
Create a 🗺️ features point feature centered along the 🗺️ flowline feature class.
Assign it a descriptive label in the 📊 Name field, and record its longitudinal position along the reach (see next bullet) in the 📊 km_to_mouth field.
To determine a feature’s longitudinal position along the reach, use the identify tool to find the closest point in the 🗺️ flowline_points feature class and use the value from its 📊 POINT_M value.
Repeat these steps to record all of the significant features along each reach.

Data Management

Reports

Run the Level 1 report for each reach.

Run the Level 1 Report

The purpose of this step is to run the L1 report for each reach. The Level 1 Report displays the channel dimensions for the base event, compared with multiple previous event surveys.

In the 🧰 Reports toolset, use the 🛠️ Level 1 Report tool to produce the Level 1 Report.
For the 📊 stream parameter, use the value of the 📊 ReachName field used in the 🗺️ flowline feature class.
For the 📊 flowline_fc parameter, enter the 🗺️ flowline feature class for the base event survey.
For the 📊 xs_dimensions_fc parameter, use the 🗺️ *_dims_L1feature class calculated for the regular cross sections of the base event.
The 📊 flowline_points_* parameters should be entered with the feature class for the most recent survey first (i.e., the base event) and then the previous surveys in reverse chronological order (e.g., 2016, 2010, 2006).
The 📊 xs_points_* parameters should be entered with the feature class for the most recent survey first (i.e., the base event) and then the previous surveys in reverse chronological order (e.g., 2016, 2010, 2006).
The 📊 survey_name_* parameters are used to label the surveys in maps and graphs.
The feature classes and labels used for the 📊 flowline_points_*, 📊 xs_points_*, and 📊 survey_name_* parameters must be entered in the same order (e.g., 2016, 2010, 2006) in each set of numbered parameters.
For the 📊 features_fc parameter, enter the 🗺️ features feature class for the base event survey.
For the 📊 dem parameter, enter the 🗺️ hydroDEM for the base event survey.

Perform QA

☑️ Evaluate

Use the QA Checklist to verify the reports have run correctly and identify any data mistakes that need to be corrected.

Follow the instructions in the QA Checklist Chapter, Level 1 Report, to verify that the reports have run correctly.
Make the required changes suggested in the QA Checklist and rerun the report.
Repeat these QA iterations until the reports are correct.

Determine Next Steps

The purpose of this step is to determine what further steps need to be taken.

Review the results of the Level 1 Report and determine if the project goals require proceeding to developing the Level 2eb analysis.