EPA/600/R-22/012 | January 2022
United States
Environmental Protection
Agency
oEPA
EPA H20
User Manual
Office of Research and Development
National Health and Environmental Effects Research Laboratory
Gulf Ecology Division
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EPA/600/R-22/012
January 2022
EPA H20
User Manual
by
Madison Myers3, Justin Bousquin2, Richard Fulford2, Parik Ranade1, Greg Soter1, Marc
Russell4, James Harvey2, and Kate Murphy3
1 Global Solutions Group, 12801 Auburn Street, Detroit Ml 48223
2 US. EPA Office of Research and Development, Center for Environmental
Measurement and Modeling, Gulf Ecosystem Measurement and Modeling Division, 1
Sabine Island Drive 32561
3 Student Service Contractor, US. EPA Office of Research and Development, Center
for Environmental Measurement and Modeling, Gulf Ecosystem Measurement and
Modeling Division, 1 Sabine Island
Drive 32561
4 US. EPA Office of Research and Development, Center for Computational Toxicology
and Exposure, Research Planning and Implementation Staff, 1 Sabine Island Drive
32561
Contract Number EP12D000276
Project Officer, James Harvey
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Notice/Disclaimer Statement
This document has been reviewed by the U.S. Environmental Protection Agency,
Office of Research and Development, and approved for publication.
Any mention of trade names, products, or services does not imply an
endorsement by the U.S. Government or the U.S. Environmental Protection Agency.
EPA does not endorse any commercial products, services, or enterprises.
Disclaimer of Liability
With respect to this multimedia system of HTML pages and the EPA H20 software
products and their documentation, neither the U. S. Government nor any of their
employees, makes any warranty, express or implied, including the warranties of
merchantability and fitness for a particular purpose, or assumes any legal liability or
responsibility for the accuracy, completeness, or usefulness of any information,
apparatus, product, or process disclosed, or represents that its use would not infringe
privately owned rights.
Disclaimer of Software Installation/Application
Execution of any EPA H20 installation program and modification to system
configuration files must be made at the user's own risk. Neither the U. S. EPA nor the
program author(s) can assume responsibility for program modification, content, output,
interpretation, or usage.
EPA H20 installation programs have been extensively tested and verified.
However, as for all complex software, these programs may not be completely free of
errors and may not be applicable for all cases. In no event will the U. S. EPA be liable
for direct, indirect, special, incidental, or consequential damages arising out of the
use of the programs.
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Notice/Disclaimer Statement 3
Table of Contents 4
Introduction 9
About EPA H20 9
About GIS 10
About QGIS 10
Definitions of GIS Terms 10
EPA H20 Download and Installation 12
System Requirements 12
Installing EPA H20 12
Uninstalling EPA H20 17
Navigating EPA H20 22
GIS Tools 22
View Menu 22
Map Navigation Toolbar 22
EPA H20 Toolbar 23
Layers/ Table of Contents Panel 24
Selection Tools 25
Getting Started 26
Basic Module 26
Advanced Module 26
Create New Project 27
Select AOI 28
By County 28
By Shapefile 31
By Drawing on Map 35
By River Basin (Advanced Module Only) 37
Saving and Moving the Project 40
Saving the Project 40
Moving a Project 40
Tampa Bay Data Layers 43
Basic Module Tampa Data 43
Advanced Module Tampa Data 46
Creating Reports 48
Basic Module Report 48
Create Report Tool 48
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Basic Module Report Analysis 50
Advanced Module Report 52
Create Scenario 52
Edit Scenarios 54
Edit Scenario Land Use 54
Edit ES Unit Values 59
Compare Scenarios 62
Advanced Module Report Analysis 64
Delete Scenario 67
Transportation Tool (Advanced Module Only) 68
Transportation Scenario Comparison Report 70
Select POI 73
Coordinate Capture 74
Geocoding Address 75
Load Point of Interest file 75
Power Mode 77
ES Calculations Theory 80
Flood Water Retention Value 80
Usable Air Value 81
Usable Water Value 83
Carbon Sequestration Value 86
Database Creation 90
Setting Up a Project Directory 92
Set Up ArcGIS Map Document 92
Set Up QGIS Map Document 93
Create HUC Watershed Boundaries 97
Download HUC Boundaries 97
Using ArcGIS 99
Using QGIS 101
Create Land Use Data Layer 107
Download Land Use Data 107
Using ArcGIS 109
Using QGIS 113
Create Land Use Comparison Data 127
Create Soil Data Layer 128
Download Soil Data 128
Pre-processing Soil Data 131
Using ArcGIS 134
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Spatially Join Soils to Land Use 143
Using QGIS 147
Spatially Join Soils to Land Use 153
Update ES Coefficients 160
Tree Canopy 160
Download Tree Canopy Data 160
Using ArcGIS 163
Using QGIS 169
Air Quality 173
Using ArcGIS 174
Using QGIS 175
Carbon Sequestration 179
Carbon Fixation Rates from Literature Review 179
Using ArcGIS 180
Carbon Fixation Rates for Developed Classes 180
Using QGIS 181
Carbon Fixation Rates for Developed Classes 182
Denitrification 183
Nitrogen Removal Rates from Literature Review 184
Determine Nitrogen Removal Rates 184
Joining Lookup Table 185
Using ArcGIS 185
Field Calculations 186
Using QGIS 189
Field Calculations 190
Create NHDPIus V2 Data Layers 193
Download NHDPIus Data 193
Using ArcGIS 194
Using QGIS 198
Grid Water Bodies 204
Create Road Layer 215
Download TIGER/Line data 215
Download Max Speed data 217
Using ArcGIS 218
Create Max Speed Dataset 219
User-Obtained Max Speed Data 220
Using QGIS 222
Create Max Speed Data 223
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User-Obtained Max Speed Data 224
Create User Point of Interest (POI) Layer 226
Importing Layers into QGIS 227
Update Land Use Comparison Datasets in Qspatialite 234
References 236
Appendices 244
Appendix A: Supplemental NLCD Lookup Table 244
Using ArcGIS 244
Using QGIS 244
Calculated as explained in the Nitrogen Removal Rates from Literature Review 246
Appendix B: Air Quality Reference Table 248
Using ArcGIS 248
Using QGIS 248
Appendix C: Roads Speeds Table 252
Using ArcGIS 252
Using QGIS 252
Appendix D: Extracting and Updating the Original FLUCCS Lookup Table 253
Using ArcGIS 253
Using QGIS 253
Appendix E: Additional Troubleshooting and Common Errors 259
New Project "No Such Table" Error 259
Cannot Run Advanced Comparison Report 260
Cannot Update Polygons in Edit Scenario Tool 261
Report Legend Crossed Out in Advanced Report 261
Flood Protection = 0 in Advanced Report 262
Total Area: 0 sq meters in Advanced Report 263
Cannot Open Qspatialite Plugin 263
Python Error When Opening or Creating Project 264
FAQ: Frequently Asked Questions 266
Appendix F: Updating QGIS Layer Symbologies 267
Appendix G: EPA H20 Development From QGIS 269
Development 269
Error catching and debugging QGIS 269
QGIS Source Code Compilation 269
Project Manager Plugin for EPAH20 271
Project Creation and User Database 272
Clip and Summary Operations 273
ES Coefficient Values and Edit User Scenarios 274
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Reporting 274
Transportation Tool 275
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About EPA TOO
EPA H20 is a Geographic Information System (GIS) based demonstration tool for assessing Ecosystem
Services (ES). ES can be defined as the use of ecological structures and functions that humans can
directly relate to their state of well-being (Russell et al., 2013). ES may also be referred to as ecosystem
goods and services (EGS). EPA H20 was developed as a preliminary assessment tool in support of
research being conducted in the Tampa Bay watershed. EPA H20 provides information, data,
approaches and guidance that communities can use to examine alternative land use scenarios in the
context of nature's benefits to the human community. Knowledge gained from using this tool may help
community representatives make strategic decisions for moving towards a more environmentally
sustainable future.
As packaged, EPA H20 allows users to:
o Gain a greater understanding of the significance of ES
o Explore the spatial distribution of ES and other ecosystem features
o Obtain map and summary statistics of ES production's potential value
o Analyze and compare potential impacts from predicted development scenarios or user
specified changes in land use patterns on ES production's potential value
o Get started with a prepackaged database specifically designed for the Tampa Bay, FL estuary
and its watershed
EPA H20 is designed to be used at a range of skill levels for use and analysis of GIS data. Database
creation does require a basic understanding of GIS tools for creating data layers, but analysis of existing
databases (e.g., Tampa) using the tool can be performed at a Basic or Advanced level as appropriate.
EPA H20 is designed for analyzing data at neighborhood to regional scales. While this software tool is
packaged with data from the Tampa Bay region, advanced users can edit existing Tampa Bay data,
substitute different datasets for the Tampa Bay region, and/or build completely new databases for new
assessment areas. The tool is transferable to other locations if the required data are available, and if the
data are processed into an EPA H20 compatible format. See the Database Creation section for guidance
on how to create EPA H2Q compatible datasets.
For general information regarding the tool please contact:
Marc J. Russell, Ph.D.
Research Ecologist
US EPA Gulf Ecology Division
One Sabine Island Drive
Gulf Breeze, FL 32561
Email: ryssell.marc@epa.gov
EPA H20 tool was developed by:
Global Solutions Group Inc.
24453 Grand River Avenue, Detroit, Ml 48219
Phone: 313.397.8311
Email: info@alobalsolaroup.com
In association with:
FutureNet Group Inc.
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12801 Auburn St, Detroit, Ml 48223
Phone: 313.544.7117
Email: info@futurenetaroup.com
About GIS
EPA H20 is a Geographic Information System (GIS) based hydro-ecology tool. A GIS is typically used to
describe and characterize the earth and other geographies to visualize and analyze spatially referenced
information. The purpose of a GIS is to create, share, and apply useful map-based information products
that strengthen the work of organizations, as well as to create and manage the supporting geographic
information.
Maps portray logical collections of geographic information as map layers. They provide an effective
metaphor for modeling and organizing geographic information as a series of thematic layers. In
addition, interactive GIS maps provide the user an interface for interacting with geographic
information.
Examples of widely used GIS systems are:
o Esri ArcGIS Suite (Commercial) - https://www.esri.com
o QGIS (Open Source) - https://www.qais.org
o Maplnfo (Commercial) - https://www.mapinfo.coni
o PostGIS (Open Source) - https://postgis.net/
About QGIS
EPA H20 is based on the open source GIS software QGIS. QGIS provides sophisticated tools to
perform advanced geographic analysis. The following links are helpful resources about QGIS
software:
O QGIS Official Website - MtpM/wwwjflK,gg/
o QGIS Help - https://download.osgeo.Org/qgis/doc/manyal/qgis-1.8.0 user guide en.pdf
o QGIS Documentation - https://www.qgis.org/en/docs/index.html
Definitions of GIS Terms
Definitions for additional terms can be found using the Esri GIS Dictionary:
https://support.esri.com/en/other-resources/qis-dictionarv
User Interface - The part of the software that allows users to interact with a GIS system through
graphical icons and visual indicators; sometimes referred to as a Graphical User Interface (GUI).
Map Projection - Describes how the curved surface of the earth is manipulated to display
properly on a plane. Map projections distort either distance, area, shape, direction, or some
combination thereof. There are a number of common map projections, and the one that is most
suitable depends on the specific area/region being mapped, the type of analysis being
performed and the end use of map product (Esri Support. 2018).
Coordinate System - A reference framework consisting of a set of points, lines, and/or surfaces, and
a set of rules, used to define the positions of points in space in either two or three dimensions (Esri
Support. 2018).
Extent-The minimum bounding rectangle (xmin, ymin and xmax, ymax) defined by coordinate
pairs of a data source. All coordinates for the data source fall within this boundary (Esri Support.
2018).
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Data Layer-The visual representation of a geographic dataset in a digital map environment (Esri
Support, 2018). Each environmental variable is represented as a distinct data layer - for example
Eagle Nests or Wetland Areas. Each data layer can be stored as either feature vector data or raster
image data.
Raster Data - In raster data, each cell, or pixel, of a given color marks a value such as elevation
or priority level. Figure 1 and Figure 2 illustrate raster data on two different scales.
Figure 1 Fine scale view of raster data
Figure 2 Sample raster data for the Tampa Bay region
Feature Data - A representation of a real-world object on a map (e.g. a specific eagle's nest or
wetland area). Feature types in a GIS are Point, Line, and Polygon (Esri Support. 2018). In
addition to geographic information that allows each feature to be visualized on a map, features
may also be associated with non-spatial attribute data (Figure 3).
Ye I l&w poi nts d e pict
Eagle nezt Iccaticps
Red shapes represent
National Wildlrfe Befuge
areas
Figure 3 Sample map showing example features with points, lines and polygons
Attribute Data - Non-spatial information associated with a geographic feature in a GIS.
Attributes are usually stored in a table and linked to the feature by a unique identifier. For
example, attributes of a river might include its name, length, and flow rate.
Symbology - The set of conventions, rules, or encoding systems that define how geographic
features are represented with symbols on a map. A characteristic of a map feature may
influence the size, color, and shape of the symbol used (Esri Support. 2018).
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EPA H20 Download and Installation
System Requirements
The EPA H20 application was developed around the open source GIS software QGIS, version 1.8.
The special EPA H2Q tools and capabilities are not all forward compatible with newer versions of
QGIS. System requirements for EPA H20 are the same as for QGIS 1.8 for Windows systems. It is
recommended that EPA H2Q be installed on a system with:
o Windows XP or newer
o 1GB of available RAM
o 1,6GHz processor
o 5GB Hard Disk Space
Installing EPA H20
This section illustrates the step-by-step procedure for installing EPA H2Q.
1. Download the latest version of EPA H20 from:
https://www.epa.aov/water-research/ecosvstem-services-scenario-assessment-usina-epa-h2o
2. Save the H20_Set_Up.exe installation file to your computer.
3. Ensure you have administrative rights to install the program on your computer or contact your
network/systems administrator.
4. Double-click on the H20_Set_Up.exe installation file. If you receive a security warning (Figure 4),
ignore it by clicking Run.
Open File - Security Warning
MM
We can't verify who created this file. Are you sure you want to
run this file?
N ame
Type
From
S:\EPA Help\H20-l-Beta-Setup.exe
Application
S:\EPA Help\H20-l-Beta-Setup.exe
Run
Cancel
This file is in a location outside your local network. Files from
locations you don't recognize can harm your PC. Only run this file if
you trust the location. What's the risk?
Figure 4 Security Warning window that may be received when running the H20_Set_Up.exe installation
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Setup may take a few moments to load, during which time a window may appear with progress
(Figure 5).
Once the EPA H20 Setup Wizard appears (Figure 6),
click the Next button to proceed.
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& EPAH20 Setup
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EPA H20
Welcome to the EPA H20 Setup
Wizard
This wizard will guide you through the installation of EPA
H20.
It is recommended that you close all other applications
before starting Setup. This will make it possible to update
relevant system files without having to reboot your
computer.
Click Next to continue,
Next >
Cancel
Figure 6 EPA H20 Setup Wizard welcome window
7, Next the EPA H20 license agreement window will appear (Figure 7). Click the I Agree button, to agree
with the EPA H2Q license agreement.
y EPA H20 Setup
License Agreement
Please review the kense term* before rataftng EPA H20.
1
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Press Page Down to see the rest of the agreement.
| EPA H20 was developed by GSG and is based on QGIS 1,8,0
This program te free software; you can redistribute it and/or modify
it under the terms of the GNU General Pubfcc License as pubkshed by
the Free Software Foundation; either version 2 of the License, or
(at your option) any fater version.
This program is distributed m the hope (hat it wl be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANT ABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
If you accept the terms of the agreement, click I Agree to continue. You must accept the
agreement to install EPA H20.
< Back
I Agree
Cancel
Figure 1 EPA H20 Setup license agreement window
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8. In the EPA H20 Setup Install Location window (Figure 8), choose the Destination Folder where EPA
H20 program files will be stored. The recommended destination folder is the Program Files directory,
as shown in Figure 8.
EPA H20 Setup
Choose Install Location
Choose the folder in which to install EPA H20,
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Setup will install EPA H20 in the following folder. To install in a different folder, dick Browse
and select another folder. Click Next to continue.
Destination Folder
Program FilesiEPA H20
Space required; 618,9MB
Space available: 199.0GB
Browse,
Nullsoft Install:
< Back Next >
Cancel
Figure 8 EPA H20 Setup Install Location window
9, EPA H20 will be selected for installation by default on the Components window (Figure 9). Click the
Install button to install the program.
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EPA H20 Setup
Choose Components
Choose which features of EPA H20 you want to install,
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Check the components you want to install and uncheck the components you don't want to
install. Click Install to start the installation.
Select components to install:
EPAH2Q
Description
Space required: 618,9MB
< Sack
IfStiil
Cancel
Figure 9 EPA H20 Setup Components window
10. An installation progress window will appear (Figure 10). Please wait while EPA H20 is being installed.
This may take a few moments.
EPA H20 Setup
Installing
Please wait while EPA H20 is being instaled.
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Extract: d.tegend.exe.manifest
Extract: d.his.exe
Extract: d.his.exe.manifest
Extract: d.Nstogram.exe
Extract: d.histograai.exe.manifest
Extract: d.info.exe
Extract: d.info.exe.manifest
Extract: d.labels.exe
Extract: d.labels.exe.mar*fest
Extract: d.legertd.exe
Extract: d.legend,exe.rnanrfest
< Back
Next >
Cancel
Figure 10 EPA H20 Setup Progress window
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11. For EPA H20 installation to take effect, the computer will have to be rebooted/restarted. On the
Setup Reboot window (Figure 11), choose to Reboot now or manually reboot later and click on the
Finish button.
<£ EPA H20 Setup
CD H S3
EPA H20
Completing the EPA H20 Setup
Wizard
Your computer must be restarted in order to complete the
installation of EPA H20, Do you want to reboot now?
o Reboot now
I want to manually reboot later
< Back
Finish
Cancel
Figure 11 EPA H20 Setup Reboot window
After installation, EPA H20 and EPA H20 Browser shortcuts wiii
automatically be created on the desktop (Figure 12). Both the EPA H20
program and EPA H20 Browser can also be accessed from the Windows All
Programs menu.
Uninstalling EPA H20
EPAH20 EPAH20
Browser
Figure 12 EPA H20 and EPA
H20 Browser shortcuts
EPA H20 does not have a separate uninstallation utility that can be accessed from the Windows All
Programs feature, this section describes how to uninstall EPA H20.
1. Access the Control Panel through the Windows start menu (Figure 13).
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Computer
Control Panel
Devices and Printers
Default Programs
Help and Support
Windows Security
Log off iHS
Figure 13 Location of Control Panel in Windows 7 start menu
Click on the Uninstall a program under Programs (Figure 14). Depending on the version of Windows,
the Uninstall a Program option may have to be accessed through the Programs and Features menu.
p|lS9 ~ Control Panel ~
Adjust your computer's settings
|0|l System and Security
Wj' A Review your computer's status
Back up your computer
Find and fix problems
Network and Internet
VBmI View network status and tasks
-**2. Choose homegroup and sharing options
Hardware and Sound
View devices and printers
Add a device
,Ff Programs
L| q * Uninstall a program
Get programs
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View by: Category '
User Accounts
^ Change account type
Appearance and Personalization
Change the theme
Change desktop background
Adjust screen resolution
Clock, Language, and Region
Change keyboards or other input methods
Change display language
Ease of Access
Let Windows suggest settings
Optimize visual display
Figure 14 Windows 7 Control Panel with Programs option
The Uninstall/Change window listing installed programs will appear. Right-click on the EPA H20
1,0.0 Beta program and select the Uninstall/Change option (Figure 15).
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Figure 15 Uninstall/Change the EPA H20 1.0.0 Beta program
Click Next in the EPA H20 Uninstall Wizard (Figure 16).
& EPA H20 Uninstall
t
EPA H20
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Welcome to the EPA H20 Uninstall
Wizard
This wizard will guide you through the uninstallation of EPA
H20.
Before starting the uninstallation, make sure EPA H20 is not
running.
Click Next to continue.
Next >
Cancel
Figure 16 EPA H20 Uninstall Wizard Startup
Click Uninstall (Figure 17). It may take a few moments for uninstallation to complete.
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. EPA H20 Uninstal! _ I
Uninstall EPA H20
Remove EPA H20 from your computer, L
EPA H20 will be uninstaled from the following folder. Click Uninstal to start the uninstaSation,
Uninstalling from: C:program Files (x86)VEPA H20\
Figure 17 Uninstall window, with file location of EPA H20
Click Finish (Figure 18).
< Back |i Uninstal
Cancel
EPA H20 Uninstall
¦
Completing the EPA H20 Uninstall
Wizard
EPA H20 has been uninstalled from your computer,
Click Finish to close this wizard,
Finish
Figure 18 Finish in the EPA H20 Uninstall Wizard
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7. The EPA H20 Setup window may appear (Figure 19). Do not continue with EPA H20 installation.
Instead click Cancel to close the EPA H20 Setup Wizard.
EPA H20 Setup
:
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Welcome to the EPA H20 Setup
Wizard
This wizard'
H20,
I guide you through the installation of EPA
It is recommended that you close all other applications
before starting Setup, This will make it possible to update
relevant system files without having to reboot your
computer,
Click Next to continue,
Next >
Figure 19 Beginning of EPA H20 Setup Wizard
8. The EPA H20 program has successfully been uninstalled.
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Navigating EPA H20
GIS Tools
QGIS software includes various GIS tools to assist users navigating, analyzing and visualizing data within
the EPA H2Q program. These tools are accessed by selecting icons from dropdown menus or by clicking
individual icons on toolbars.
View Menu
Many tools can be accessed using the View dropdown menu (Figure
20). Common tools are available on toolbars for quicker access.
Toolbars are activated/deactivated using the Wewmenu > Toolbars
and can be moved around to different locations on the screen.
Panels show the user specific information about their current map.
Panels are activated/deactivated using the View menu > Panels.
Map Navigation Toolbar
These navigation tools are in the Map Navigation Toolbar (Figure
21) and can also be accessed using the Wewmenu.
Tools in dropdown menus and in toolbars are greyed out if
prerequisite requirements for using that tool are not met. For
example, Zoom Next appears greyed out until the user moves back
to a previous zoom or pan (Figure 20 and Figure 21).
Depending on the tool, clicking a tool icon may perform a function
once or enable functionality until turned off or a different tool
functionality is enabled. Enabled functions are shown in a grey,
highlighted box; the Pari icon, for example, is highlighted when
enabled (Figure 20 and Figure 21). There may be alternative ways to
perform functions without enabling these tools.
View
~J» Pan Map
•v* Pan Map to Selection
/ Zoom In
Ctrl+t
/ Zoom Out
Ctrl+-
Select
»
v© identify Features
Ctrl+Shift+I
Measure
~
Ji Zoom Full
Ctrl +¦ Shift ¦» F
. Zoom to Layer
S Zoom to Selection
Ctrl*J
„m Zoom Last
•Q Zoom Next
/• Zoom Actual Size
Decorations
~
, New Bookmark-
Ctrl*B
Show Bookmarks
Ctrl* Shift
>a Refresh
CtrH-R
Tile scale slider
Panels
~
Toolbars
~
Toggle Full Screen Mode
Ctrl+F
Figure 20 View dropdown menu in
EPA H20
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Pan icon - When enabled, panning allows the user to click or click-and-drag to move the map
across the screen. Alternatively, holding down the mouse scroll wheel while dragging the map
will also pan.
Pan to selection icon - Pan to selected feature/features.
Zoom In/Out icons - When enabled, click or draw a rectangle to zoom in or out. Alternatively,
the mouse up-scroll will zoom in and down-scroll will zoom out.
Zoom Actual Size icon - Zoom to native pixel resolution. For example, if the selected
raster is a 30m raster, the map will zoom to a 30m by 30m area.
Zoom Full icon - Zoom to the full extent of all layers visible in the Layers panel.
Zoom to Selection icon - Zoom to selected feature/features.
Zoom to Layer icon - Zoom to a selected layer's full extent.
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Refresh icon - Update the map canvas.
Figure 21 Map Navigation Toolbar
Zoom Last/Next icons - Use this tool to return to the previous or next viewing frame (i.e. undo
and redo for zoom or pan).
EPA H20 Toolbar
The default location for the EPA H20 Toolbar is above the Layers panel. There are slight differences in
the toolbar between the Basic (Figure 22) and Advanced (Figure 23) Modules. In the Basic Module the EPA
H20 Toolbar has an added Generate Report icon that allows the user to generate a statistical report (see
Basic Module Report Section); whereas in the Advanced Module, the user instead manages and
compares different scenarios in reports (see the Create Scenario section). The main function of the EPA
H20 Toolbar is that it allows the user to move between module types, and between projects. The EPA
H20 Toolbar also allows easier access to the Identify Feature tool; alternatively found in the View menu
(Figure 20).
5
6
U
Select EPA H20 Module icon - Click to open the EPA H20 Project Manager window (Figure
22) and switch between Basic and Advanced Modules (see Getting Started section).
Select EPA H20 Project icon - Click to open a new or existing EPA H20 project (see Create
New Project section).
Generate Report icon - Click to run an analysis report in the Basic Module. The
Basic report is detailed further in the Basic Module Report Analysis
section.
Identify Feature icon - Click on a feature in a layer selected in the Layers panel, and
an Identify Results window will display attribute table information for the
Figure 22 Basic EPA clicked feature in the selected layer. This tool is also accessed using
&
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H20 Toolbar
the Wewmenu.
Figure 23 Advanced
EPA H20 Toolbar
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Layers/ Table of Contents Panel
The Layers panel, or Table of Contents, lists each data layer on the map (Figure 24). Data layers are listed
in the order they appear on the map (e.g. if the Roads_2013 layer is listed above NHD_flowlines, they will
appear in front or on top of those flowline features). The Layers panel indicates the symbology of each
layer, and whether each layer is currently visible in the map. QGIS software incorporates other tools in
the Layers panel, which may help the user manipulate EPA H20.
Layers
B- D :* User POIs
! 1 * ~
V° Roads_2013
| 56 - 70 mph
46 - 55 mph
26 - 45 mph
00 - 25 mph
B
x V
NHDflowlines
0
II C3
Land Use 2006
B
~ C3
Subwatershed
! ~
x Hi
Google Streets
X Control rendering order
Layer icons - Each data layer added to the map appears in the
Layers panel, in the order it appears on the map.
Change layer order - Rearrange the data in the Layers panel by
clicking, dragging, and dropping the name of the data layer into its
new, desired position.
Show Layer in Overview - The checkbox next to each data layer
heading demonstrates whether the layer is currently turned on in the
map. The Layers panel in Figure 24 indicates that the NHD_flowlines,
Land_Use_2006 and Google Streets layers are displayed in the map.
Collapse Symbology - Clicking the (+)/(-) sign to the left of the
checkbox expands or collapses a list of possible values for the data
layer to the right.
Figure 24 Layers/ Table of Contents
Panel in EPA H20
A list of functions can also be accessed through the Layers panel, with a right-click on each data layer
(Figure 25). This list provides shortcuts to certain QGIS operations and assists in EPA H2Q navigation.
Zoom to Layer Extent
Show in Overview
ri. Remove
Set Layer CRS
Set Project CRS from Layer
m Open Attribute Table
/ Toggle Editing
Save As...
Save Selection As,,.
Query...
Show Feature Count
Properties
Rename
Copy Style
Add New Group
T3 Expand All
Collapse All
Update Drawing Order
Remove - Click to remove the selected data layer from the Layers
panel. The removed layer will no longer appear in the Layers panel, or
in the map canvas.
Set Layer CRS - The shapefile Coordinate Reference System (CRS)
must match all spatial layers. Click to edit or add a CRS or to confirm a
match for new data layers. Details on setting CRS are given in the
database creation section.
Open Attribute Table - Click to open the attribute table of the selected
data layer. The attribute table contains characteristics for the spatial
data. In QGIS, attribute tables can only be opened for vector data.
Toggle Editing - Click to start or stop editing the selected layer. Editing
in the
Figure 25 Right-click functions
in EPA H20 Layers panel
can also be turned on and off by clicking the pencil icon
attribute table or in Layer Properties.
Properties - Click to open the Layer Properties window for the selected
data layer. This window provides information regarding metadata,
coordinate reference system, fields in the attribute table, as well as
tools for data processing and display.
24
-------
Selection Tools
EPA H20 utilizes six different Select Tools to select and highlight specific features in a layer. The
tools are located under View menu > Select (Figure 26). In the Layers panel, click on the layer the user
wants to select the features from. Once selected, a feature will be highlighted in yellow. Line and
polygon layers, such as trails or conservation areas, respectively, are grouped together to enable
faster processing time. Therefore, large areas may be highlighted outside the selection shape drawn.
& EPA H20 -1 - UseCaseOne j
File
View Help
ca
Pan Map
Pan Map to Selection
/ Zoom In
jr Zoom Out
on
s i
Ctrl+ +
Ctrl -t- -
Select
R
El
•'o Identify Features
Ctrl+Shift+I
. Select Features by Rectangle
B
Measure
~
• Select Features by Polygon
0
Zoom Full
if- Zoom to Layer
Ctrl+Shift+F
Select Features by Freehand
c. Select Features by Ftadius
0 |
y Zoom to Selection
Ctrl+J
Deselect Features from All Layers
0 |
/a Zoom Last
1 <'—-i !f <
Figure 26 The six Selection Tools located in the EPA H20 View menu > Select
Select Single Feature icon - When enabled, clicking a feature will select it. Holding down
the Control Key while Select Single Feature is enabled allows one to add features to the
current selection.
Se/ecf Features by Rectangle icon - When enabled, click and drag to draw a rectangle
around features to select.
Select Features by Polygon icon - When enabled, left click to draw vertices for the polygon,
right-click to finish the polygon and select features within it.
Select Features by Freehand icon - When enabled, click and drag to draw an abstract
shape around the area to select. The selection will follow the cursor; no vertices are drawn.
Select Features by Radius icon - When enabled, click and drag to draw a circle around the
area to select.
Deselect Features from All Layers icon - Clears the current selection; features will no
longer be highlighted.
25
-------
Getting Started
EPA H20 is opened from the program list or by double clicking the EPA H20 shortcut on the desktop.
Once opened, the first window that appears is the EPA H20 Project Manager window (Figure 27). The
user must choose which module to operate in, but the module can be changed later using the EPA H20
Select Module icon (Figure 22). This section describes the major differences between the two modules.
& EPA H20 Project Manager f || S3
Choose a Module
• Basic User - Green Report
Advanced User - Land Use Change and Comparison
Switch module in the future by clicking on this icon-
OK Cancel
Figure 27 EPA H20 Project Manager window
Basic Module
The Basic Module is designed for a user with limited GIS software experience. Basic users can explore
the various ES and other environmentally relevant features in their area of interest and generate maps
and reports to summarize what those features are and their ES values.
An example of a basic user would be a neighborhood association member who wants to explore the
value of surrounding "greenspace" in their neighborhood. The user can quickly get simple summaries for
a suite of ecosystem services the area produces and the resulting cumulative value of benefits using the
Basic Module. The user is then able to share this info with neighbors interested in preserving that
"greenspace," and/or finding hotspot areas for producing or delivering ES value.
Advanced Module
The Advanced Module is designed for a user with more GIS expertise who wishes to expand from
exploring ecosystem services to scenario creation and comparison. Users can compare preexisting
scenarios for the Tampa Bay region or create custom land use scenarios. Scenarios are then able to be
analyzed and compared, with a map and report summarizing the ES values generated for each.
An example of an advanced user would be a regional planner interested in the cumulative effects of
increased impervious surfaces on the provision and value of water retention ecosystem services. The
user can select a multi-county area and appropriate drainage areas as their area of interest. New land
use scenarios can then be generated by modifying a copy of the initial land use map. The user is then
able to compare the changes in ES value that result from their modifications to land uses.
26
-------
Create New Project
This section illustrates how to start a new EPA H20 project.
1. Select either the Basic or Advanced Module from the EPA H20 Project Manager window (Figure 27),
click OK. The user can click Cancel to exit EPA H20.
2. The Select Project window will appear (Figure 28). Select Create new project and click OK.
EPA H20 Project Manager
? S3
Select Project
Open existing project
• Create new project
Exit EPAH20
OK
Cancel
Figure 28 EPA H20 Select Project window
3. The Select Database Location window will appear (Figure 29). Click on the Select button if you want to
change the Data Folder Path from the default "C:\lisers\USERNAME\.qg\s\0.0.3". If using a different
Data Folder Path, start by navigating to the root EPA H2Q data folder.
ij) EPA H20 Project Manager
Project Configuration
-es-
Select the Top Level Folder of EPA Dataset
Select
Data Folder Path: C:\\Users\\Username\\.qgis\\\\0.0.3\\
Source Database Name: TampaBay.sqlite
Name Your Project Database Basic]
OK
Cancel
Figure 29 EPA H20 Select Database Location window
4. Enter a name for the new database in the Alame Your Project Database field (e.g. "Basic" in Figure 29)
and click OK to proceed.
The Select Area of Interest (AOI) window will appear (Figure 30 & Figure 31). Selecting an area of interest
is illustrated under the Select AOI section.
27
-------
Select AOI
This section illustrates how to select an area of interest for a new EPA H20 project starting from the
Select Area of Interest window (Figure 30 & Figure 31). The options available in this window depend on the
current project user module, where the Advanced Module has the additional option to Select by River
Basin. Each option in the EPA H20 Select Area of Interest window is detailed in its own section.
; j EPA H20 Project Manager
Select Area of Interest
Select from list of Counties
Select a polygon shapefile
Select by drawing on map
OK
Cancel
Figure 30 EPA H20 Select Area of Interest window in
Basic Module
(jj EPA H20 Project Manager
Select Area of Interest
S3
• Select from list of Counties
Select by River Basin
Select a polygon shapefile
Select by drawing on Map
OK
Cancel
Figure 31 EPA H20 Select Area of interest window in
Advanced Module
By County
1. In the EPA H20 Select Area of Interest window (Figure 30 & Figure 31), choose the Select from list of
counties option. Click OK.
2. The Select counties to create project window will appear in front of the EPA H2Q map screen (Figure
32).
3. The window in the foreground will list counties in Florida to choose a county from. Click to select or
unselect counties from the list.
4. Note that the default data are only available for areas in Pinellas, Hillsborough, Polk, Manatee,
Hardee, and Pasco counties, which drain to Tampa Bay. Selecting other counties may yield no data.
5. In the background map the program will load base layers - Counties, River basins and Google
Streets. As counties are selected from the list they will be highlighted in yellow on the map (e.g.
Alachua County in Figure 32).
28
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J
Fd» Vim Ht%>
-------
:.j EPA H20 Project Manager
f Ifc^l
Progress
Kilobytes Processed:
2559
Figure 34 Select AO! progress bar window
8. Please note: EPA H20 may display the phrase "Not responding" while processing data. This error
may be shown in the progress bar (Figure 35), or at the top of the project window. Despite the
message, the program is still actively processing. Please do not close the window, or the EPA H20
program.
Q EPA H20 Project Manager (Not Responding)
?
X
Progress
Kilobytes Processed: 279
Figure 35 Select AOI progress bar window, with (Not Responding) error shown
9. When clipping is complete the Save Project window will appear (Figure 36). To save the project,
choose the desired File name and location, and click Save. The project should be saved as a QGIS
file with the extension ".qgs" (e.g. Basic.qgs in Figure 36).
y Choose * file name to save the QGJS project file as
l"£3-l
~ Username ~ .qgis * 0.0J * projects
~ [ if II Search prefects
pf
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-
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Figure 36 Window to save the EPA H20 project
10. By default, all data layers except Google Streets and River basins will be turned off. Other layers
must be turned on to make them visible on the map (see Layers/ Table of Contents Panel). Once
30
-------
made visible, land use layer results using Hillsborough County, FL as the AOI can be examined in the
EPA H2Q map (Figure 37).
Layers 9 x
kewtinn
3 tfjglu
WooduoilL _Nmu
Par1a_ond_lt®c_Locad Tran^podaJnyi
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X ftivcr baniro
X £| Google Streets
Figure 37 EPA H20 map for Hillsborough County, with River basins, Counties, and Google Streets visible, and Land
Use layer turned on
By Shapefile
1. In the EPA H2G Select Area of Interest window (Figure 30 & Figure 31), choose the Select a polygon
shapefile option. Click OK.
2. The Select Shapefile window will appear (Figure 38), click the Select button to choose the shapefile to
use as the AOI.
§ EPA H20 Project Manager | f l|-£3-i
Select Web Mercator (EPSG:3857) Polygon Shapefile for the
Shapefile
Select
Intersect
Cancel
Figure 38 EPA H20 Select Shapefile window
3. A window will appear to select a shapefile (Figure 39). Navigate to and select a shapefile with the .shp
file extension (e.g. the EM A.shp file is used in Figure 39).
Please Note:
31
-------
a. Only one shapefile can be selected as an AOI at a given time.
b. No shapefile is included in the H20 download package.
c. The XML metadata file type with extension .shp.xml cannot be opened using EPA H20.
d. The shapefile Coordinate Reference System (CRS) must match the data CRS in EPA H20.
The Tampa data CRS is "EPSG:3857", and the Geographic Coordinate System is
"GCS_WGS_1984".
i. In Esri software (ArcGIS), this coordinate system is called
WGS_ 1984_ Web_Mercator_A uxiliary_Sphere.
ii. In QGIS, this coordinate system is named WGS 84/ Pseudo Mercator.
iii. The naming schemes are different between the two programs, but they represent the
same coordinate system.
4. Click Open to select the shapefile and return to the Select Shapefile window.
£ Sti«pefile
« Users > Usemame » .qgis ~
*• 1 Search .qgis
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EMA.shp
File name: EMA,shp
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5/4/2015 PM
5/4/3015 2:27 PM
Type
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File folder
File fodder
5/4/2015 4^
Open |-r
Caned
Figure 39 Window to select a shapefile as the AOI
5. Once selected, the shapefile will be displayed on the map in the background (Figure 40). Click
Intersect in the Select Shapefile window to clip the AOI to the shapefile area.
32
-------
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Choose a file nsme to save the QG1S project file as
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Figure 42 Window to save the EPA H20 project
8. By default, ail data layers except Google Streets and River basins will be turned off. Other layers
must be turned on to make them visible on the map (see Layers/Table of Contents Panel). Land use
layer results using a shapefile as the AOI can be examined in the EPA H20 map once made visible
(Figure 43).
0 II V" NHD FIowlines
0 i EagleNests
0 WoodstorkNests
0 ParksandRecLocations
0 I BirdingandWildlifeViewpoints
0 D V Existing Trails
0 Li V SensitiveShoreline
0 C3 EcoGreenwaysandLinkages
0 ForeverAcquiredLands
0 ! HabitatConservationAreas
0 I C~ Coastal_Barrier_ ResourceSystem
0 n C3 Fragil_ CoastalResources
0 V" Critical Erosion
0 C3 FunctionalWetlands
0 r t-1 PrioritizedRecharge
0 C WetlandHabitat
0 CT| Wildlife Refuge
0 L C Sustainabl_ Forestry
5) CTJ MitigationBanks
0 ( UsableWaterValue
0 M ( Flood Protection Value
0 ( StableClimateValue
0 C UsableAirValue
0 X Land_Use_2006
FLUCCS Classifications
| Urban and Built-Up
Agriculture
B Rangeland
I Woodlands
I Water
Wetlands
Barren Land
| Utilities and Transportation
I Tidal Flats
H Seagrass and Algae Beds
0 C NHDWaterbody
0 C Subwatershed
B X River basins
X 1I| Google Streets
Layers
Figure 43 EPA H20 map drawn by shapefile; River basins and Google Streets are visible, and the Land Use layer is
turned on
34
-------
By Drawing on Map
1. In the EPA H20 Select Area of Interest window (Figure 30 & Figure 31), choose the Select by drawing
on map option. Click OK.
2. The Draw the AOI window will appear with Navigation tools, and the Select Features by Rectangle
tool to draw the AOI onto the map (Figure 44). The map will load in the background with pre-loaded
base layers - River basins and Google Streets (Figure 45).
a. Use the Zoom In , Zoom Out
of Interest (Figure 44).
, and Pan * . icons to focus the map on the Area
Q EPA H20 Project Manager | f ||w£3i|
Draw the Shape, then Run Intersect
- Use Navigation tools to move around the map.
- Use Rectangle Tool to draw the area to report on.
p.
*
RUN
Cancel
Figure 44 Draw the AOI Shape window with navigation icons
b, Click the Select Features by Rectangle icon
desired AOI on the map.
c. Click RUN to confirm the selected AOI.
* to click and draw a rectangle around the
EPA H20 Project Manager
t £3
Draw the Shape, then Run Intersect
- Use Navigation tools to move around the map.
- Use Rectangle Tool to draw the area to report on.
P.-
*
RUN
Cancel
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IB
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Figure 45 AOI drawn by shape on the EPA H20 map
3. All the EPA H20 data will be clipped to the selected AOI and its upstream areas. Depending on the
AOI this may take several moments, during which time the user will see the progress bar (Figure 46).
35
-------
(jj EPA H20 Project Manager
PT
Progress
Kilobytes Processed: 309
Figure 46 Select AOI progress bar
When clipping is complete the Save Project window will appear (Figure 47). To save the project,
choose the desired File name and location and click Save. The project should be saved as a QGIS
file with the extension ".qgs" (e.g. Basic.qgs in Figure 47).
j Choose a file name to save the QGIS project file is
~ Usemame ~ .qgis ~ 0.0J ~ projects
Organise "» New folds/
- ¦, t a_ — Name
hT Favorites
X Desktop
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" | B Seoirfipnyt
Date modified
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'
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'
~ Hide Folders
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Cancel
Figure 47 Window to save the EPA H20 project
By default, all data layers except Google Streets and River basins will be turned off. Other layers
must be turned on to make them visible on the map (see Layers/ Table of Contents Panel). Land use
layer results using the drawn AOI can be examined in the EPA H20 map once made visible (Figure
48).
36
-------
Layees
A x
lEtti) Fiowtines
3 Coflk_N«t»
Wooduci(l,NMtt
Pa rtaa nd_ft®c_L acMlom
Birding and Wildlife Vtowpoints
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3 V" 5<*nrfiiv»_5lfcOf«ltoti
£ co_Gi m nwir)r>_ a nd_ L i nkagM
*0 FQ*c*ier_ Acquired Lands
3 Hlebifoi CijcisvfvatHjn Anj^»
a C- IHflW*_Aif_V«lu*
* land U»_2006
FLUCCS CJa*s*icalK)r.j
H Urban and ©urfJ-Up
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I J Tidal Fill's
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* River basins
* SI Google Streots
B
Figure 48 AOI drawn on map, with Google Streets arid River basins layers visible, and Land Use turned on
By River Basin (Advanced Module Only)
1, !n the EPA H20 Select Area of Interest window (Advanced Module, Figure 31), choose the Select by
River Basin option. Click OK.
2. The Watershed Selection window will appear (Figure 49). The map will load in the background with
pre-loaded base layers - River basins and Google Streets (Figure 50).
;Ji EPA H20 Project Manager
f IkaJ
Select the Watersheds, then Run Intersect
- Use Navigation tools to move around the map.
- Use Select Tool to select Watersheds. Hold Ctrl key for extras.
M
«¦>
RUN
Cancel
Figure 49 Watershed Selection window with navigation and selection icons
a. The Watershed Selection window is the same as the Draw the AOI window, except that
instead of Select Features by Rectangle, it has the Select Features tool to choose single or
multiple watershed(s) as the AOI. As watersheds are selected on the map they will appear in
yellow (Figure 50).
37
-------
„
NMOflowllnes
SubwsHmfied
g Google Streets
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V ]( £3
Select the watersheds, then Run Intersect
- Use Navigation tools to move around the mop.
- Use Select Tool to select Watersheds. Hold CM key for extras.
OS®
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RUN
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ty Choose a file name to save the QGIS project file as
, j > Usemame ~ .qgis • 0.03 ~ projects » | *f 1
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*-
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Figure 52 Save project with ,qgs extension in Save Project window
5. By default, all data layers will be turned off except Google Streets and River basins. Other layers
must be turned on to make them visible on the map (see Layers/Table of Contents Panel). Land use
layer results using the selected watersheds as the AOI can be examined in the EPA H20 map once
made visible (Figure 53).
Figure 53 Advanced Module map drawn by River Basin; Land Use, River basins, and Google Streets are visible
Layers
EH ) .*" User POIs
IB V" Roads_2D13
B XP Land_Use_2006
FLUCCS Classifications
| Urban and Built-Up
Agriculture
Rangeland
I Woodlands
| Water
Wetlands
Barren Land
I Utilities and Transportation
Tidal Flats
Seagrass and Algae Beds
ffl I C3 Land_Use_2020
E C=> Land_Use_2040
H C=> Larid_Use_2060
B x t:- River basins
0 V" NHD flowlines
@ _l C3 Subwatershed
X £| Google Streets
39
-------
Saving the Project
EPA H20 will allow the user to save work in the QGIS file format (.qgs) using Save or Save As
functions in the File menu of EPA H20. Saved projects preserve all loaded data layers, drawing
order, symbology, and view extents.
It is recommended that all EPA H2Q data and files be saved in the same folder directory to
facilitate moving of projects. EPA H20 does not support relative pathing; if a user moves the EPA
H20 project file (.qgis file) or relevant data, the EPA H20 program will no longer be able to find the
source data to map the layers. Transferring data and project files is not supported within EPA H20
default functionality, however, advanced QGIS users will be able to perform this task.
The Tampa Bay data provided with the EPA H20 software follows the recommended folder structure
with specific types of content in each folder (Table 1). Keeping this folder structure will help the
advanced QGIS user more easily navigate and move projects.
Table 1 folder structure of EPA H20 software with content descriptions
Folder/Filename
Content Description
Root Folder
0.0.3
Data
Rasters
Contains raster files for ES layers.
Databases
Legends
Contains the legend file (.qml) for each standard data layer used by
EPA H20.
TampaBay.sqlite
Contains the original data provided with EPA H20 for the Tampa
Bay region. These are standard data layers used by EPA H20.
Projects
Contains a sqlite database for each project, clipped to the user
specified Area of Interest. Database names are also user specified.
Reports
Contains reports saved by the user. Note: the user specifies the
location to save reports, it is not required to be saved to this folder.
Moving a Project
When a user moves the EPA H20 project file (.qgis file) or relevant data, the EPA H20 program is
not able to find the source data for layers in the expected location, resulting in a broken data
connection. The step-by-step procedure to fix broken data connections is as follows:
1. If there is a broken data connection(s), the Handle bad layers window will appear when opening
the project file (Figure 54). Each line represents a data layer that cannot be found in the expected
location, with the expected location shown in red under the New file column.
-------
Handle bad layers
Layer name
Type
Provider
Hew file
-
15
NHD_Waterbody
vector
spatialite
./Basic-ucl.sqlite
dbname='./Basic-uc1.sqlite' table=
16
Parks_and_Rec_Locations
vector
spatialrte
./Basic-ucl.sqlite
dbname='./Basic-uc1.sqlite' table=
17
P ri o ritize d_Re charge
vector
spatialite
,/Basic-uc1.sqlite
dbname='./Basic-uc1.sqlite' table=
18
River basins
vector
spatialite
../data/databases/TampaBay.sqlite
dbname='../data/databases/Tamp,
19
Sensitive_Shoreline
vector
spatialite
./Basic-ucl.sqlite
dbname='./Basic-uc1.sqlite' table=
20
Stable_Climate_Value
vector
spatialrte
./Basic-ucl.sqlite
dbname='./Basrc-uc1.sqlite' table=
21
Subwatershed
vector
spatialite
../data/databases/TampaBay.sqlite
dbname='../data/databases/Tamp
22
Sustainabl_ Forestry
vector
spatialite
./Basic-ucl.sqlite
dbname='./Basic-uc1.sqlite' table=
23
Usable_Air_Value
vector
spatialite
./Basic-ucl.sqlite
dbname='./Basic-uc1.sqlite' table=
24
Usable_Water_Value
vector
spatialite
,/Basic-ucl.sqlite
dbname='./Basic-uc1.sqlite' table=
25
Wetland_Habitat
vector
spatialite
,/Basic-uCl.sqlite
dbname='./Basic-uc1.sqlite' table=
26
Wildlife_Refuge
vector
spatialite
./Basic-ucl.sqlite
dbname='./Basic-uc1.sqlite' table=
27
Woodstork Nests
vector
spatialite
./Basic-ucl.sqlite
dbname='./Basic-uc1.sqlite' tabIe=
A.
<
- 1
[<>
OK
Browse
Cancel
Apply
Figure 54 Handle bad layers window in EPA H20
2. In the Handle Bad Layers window, double click on a file in the New File column. A File Selection
window will open (Figure 55). Navigate to and select the appropriate file that represents the data
layer, then click Open.
^ Select file to replace '../data/databases/TampaBay.sqlite'
ArcMap > NHD+
V
O | Search NHD+
Organize ~ New folder
m - a
Name
Date modified
Type
Size
;ft Quick access
_ NHDFIowline_reprcj,$hp
12/28/2017 8:30 AM
SHP File
44,048 KB
¦ Desktop
y
[_J NHDFIovvl[ne_reproj.shx
12/28/2017 8:30 AM
SHX File
936 KB
Downloads
y
M NHDWaterbody_reproj.cpg
12/27/2017 3:51 PM
CPG File
1 KB
||| Documents
y
0 NHDWaterbody_reproj.dbf
12/27/20173:51 PM
DBF File
7,656 KB
B Pictures
y
NHDWaterbody_reproj.prj
12/27/2017 3:51 PM
PRJ File
1 KB
MJackson
y
NHDWaterbody_reproj.sbn
12/27/2017 3:51 PM
SBN File
354 KB
l£] Sustainable_Cy"
| j NHDWaterbody_reproj.sbx
|J NHDWaterbody_reproj.shp
12/27/2017 3:51 PM
12/27/2017 3:51 PM
SBX File
SHP File
22 KB
60,809 KB
0.0.3
y
[j NHDWaterbody_reproj.shx
1 Subwatershed.cpg
12/27/2017 3:51 PM
SHX File
273 KB
DOIive
y
12/27/2017 5:22 PM
CPG File
1 KB
EPA.H20
y
[j Subwatershed.dbf
12/27/2017 5:22 PM
DBF File
8,686 KB
OneDrive - Enviro
i Subwatershed.prj
( ) Subwatershed,sbn
12/27/2017 3:40 PM
12/27/2017 3:41 PM
PRJ File
SBN File
1 KB
515 KB
CJ3 This PC
Q Subwatershed.sbx
12/27/20173:41 PM
SBX File
20 KB
HI Desktop
i Subwatershed.shp
12/27/2017 3:40 PM
SHP File
143,509 KB
Filename: Subwatershed.shp
All files (*)
Open
X
fi
©
Cancel
Figure 55 File Selection window in EPA H20 to reconnect a broken data connection
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3. The broken data connection will now appear in green and be fixed (Figure 56).
(jj Handle bad layers
X
Layer name
Type
Provider
New file
15
NHD_Waterbody
vector
spatialite
./Basic-uc1.sqlite
dbname='./Basic-uc1.sqlite' table=
16
Parks_and_Rec_Locations
vector
spatialite
./Basic-ucl .sqlite
dbname='./Basic-uc1.sqlite' table=
17
Pri o ritize d_Re ch a rg e
vector
spatialite
./Basic-uc1.sqlite
dbname='./Basic-uc1 .sqlite' table=
18
River basins
vector
spatialite
../data/databases/TampaBay.sqlite
dbname='../data/databases/Tamp;
19
Sensitive_Shoreline
vector
spatialite
./Basic-ucl .sqlite
dbname='./Basic-uc1.sqlite' table=
20
Stable_Climate_Value
vector
spatialite
./Basic-ucl .sqlite
dbname='./Basic-uc1.sqlite' table=
21
Subwatershed
vector
spatialite
C:/User5/rrvjackson/.qgis/0.0.3/T...
dbname='../data/data bases/Tamp
22
Sustainabl_ Forestry
vector
spatialite
./Basic-ucl .sqlite
dbname='./Basic-uc1.sqlite' table=
23
Usable_Air_Value
vector
spatialite
./Basic-ucl.sqlite
dbname='./Basic-uc1.sqlite' table=
24
Usable_Water_Value
vector
spatialite
./Basic-ucl .sqlite
dbname='./Basic-uc1.sqlite' table=
25
Wetland_Habitat
vector
spatialite
./Basic-ucl .sqlite
dbname='./Basic-uc1.sqlite' table=
26
Wildlife_Refuge
vector
spatialite
./Basic-ucl .sqlite
dbname='./Basic-uc1.sqlite' table=
27
Woodstork_Nests
vector
spatialite
./Basic-ucl .sqlite
dbname='./Basic-uc1 .sqlite' table=
1
<
[« >
OK
Browse
Cancel
Apply
Figure 56 Data connection fixed for Subwatershed layer in Handle bad layers window
Once all the broken data layers are fixed in this fashion, the EPA H20 project can be successfully
opened again.
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Basic Module Tampa Data
The EPA H20 download packages a variety of different Tampa Bay datasets into the Basic Module:
Note: Depending on the selected AOI not al of the datasets may be visible.
NHD Flowlines - This dataset consists of line features that make up a linear surface water
drainage network. The National Hydrography Dataset (NHD) contains Reach Codes for
networked features, flow direction, names, and centerline representations for areal water bodies
allowing upstream and downstream flow to be traced (Horizon Systems Corporation, 2016).
Eagle Nests - Point features representing eagle nests from 2008 to 2009. The Bald Eagle is the
national bird of the United States of America and was once severely endangered in the United
States. Populations have recovered, and although the Bald Eagle is no longer protected under
the Endangered Species Act, it is still protected under the Bald and Golden Eagle Protection Act
and the Migratory Bird Treaty Act (FWC, 2018).
Wood Stork Nests - Point features representing Wood Stork nests. The US Breeding
Population of Wood Storks is protected under the Endangered Species Act (Federal Register,
Feb. 1984; proposed status upgrade to Threatened, Dec. 2013). Nesting sites specifically are
protected. Wood Storks are birds of freshwater and estuarine wetlands, primarily nesting in
cypress or mangrove swamps. Primary reasons for the decline of Wood Stork populations are a
decrease in food availability (mainly small fish) and loss of wetland habitat (USFWS, 2018).
Parks and Recreational Facilities - This dataset consists of point features, indicating parks
and recreational locations. Parks provide opportunities for residents to enjoy outdoors, and
recreational activities including hiking, biking, fishing, boating, swimming, camping, wildlife
viewing and more. Parks benefit businesses such as tourism and recreational supply industries
(camping equipment etc.) and are a source of employment. They can also provide added
benefits, such as improvement in air or water quality, reduction of noise pollution, reduction of
heat island effects in urban areas, and increased habitat for wildlife.
Birding and Wildlife Viewpoints - Point features representing sites along Florida trails, which
provide opportunities for Birding and Wldlife viewing. The total spent annually in Florida for
wildlife viewing is two and a half times greater than the value of the state's annual orange crop
harvest ($3.08 billion and $1.23 billion, respectively, in 2006; Southwick Associates Inc., 2013).
Existing Trails - This dataset consists of line features that indicate existing trails. These are
publicly accessible paved or unpaved trails for motorized use (e.g. ATV, OHM, ROV), as well as
hiking, biking, equestrian, multiple-use, or paddling. In-road bike lanes and sidewalks are not
included (Florida Department of Environmental Protection, 2012).
Sensitive Shoreline - These line features exhibit shorelines that are environmentally and
economically sensitive to oil and hazardous material spills from 1993 to 2003 (FWC, 2017). The
Clean Water Act with amendments by the Oil Pollution Act of 1990 requires response plans for
immediate and effective protection of sensitive areas. These areas may contain sensitive
shoreline habitats, sensitive biological resources, and human-use resources.
Ecological Greenways and Critical Linkages - This dataset consists of polygon features that
represent ecological greenways and critical linkages. The Florida Ecological Greenways
Network outlines the largest and most intact landscapes that aid in the conservation of
biodiversity and ecosystem services in Florida (University of Florida GeoPlan Center, 2005). The
Florida Greenways project is an analysis of potential ecological connectivity, using land use data
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to identify landscape-scale areas with conservation significance (e.g. ecological hubs) and
potential landscape linkages (e.g. ecological greenways and wildlife corridors).
Forever Acquired Lands - Polygon features indicating Forever Acquired lands (Florida Natural
Areas Inventory, 2012). Florida Forever is the nation's largest conservation land buying program.
As of December 2017, collectively, the State of Florida has protected over 770,279 acres of land
with $3 billion in Florida Forever funds (Florida DEP, 2017). Florida Forever lands are proposed
for acquisition because of outstanding natural resources, opportunity for natural resource-based
recreation, or historical and archaeological resources. However, these areas may not currently
be managed for their resource value.
Strategic Habitat Conservation Areas - This dataset consists of polygon features that
represent strategic habitat conservation areas (SHCAs). SHCAs are utilized to determine the
minimum amount of land in Florida required to maintain long-term biological diversity for 33
terrestrial vertebrates (Florida Natural Areas Inventory, 2017). Over 8 million acres of privately-
owned areas have been identified as SHCAs, to conserve habitat for these 33 species. SHCAs
also include potential habitat within conservation lands for 29 other vertebrate species.
Coastal Barrier Resources System - These polygons indicate areas which were designated
under the Coastal Barrier Resources Act (CRBA). This Act limits federal expenditures that
support development, such as federal flood insurance. This, in return, promotes the
conservation of biologically diverse coastal barriers often impacted by hurricanes. Areas within
the Coastal Barrier Resources System (CBRS) can only be developed if the private developers
(or other non-federal parties) cover all costs (USFWS, 2018). The CBRA is intended to save
federal dollars, protect human lives, and conserve natural resources.
Fragile Coastal Resources - This dataset consists of polygon features that exhibit fragile
coastal resources. These areas include natural communities most susceptible to disturbance or
development, such as beach dune, coastal grassland, coastal strand, coastal scrub, maritime
hammock, salt marsh, and mangrove communities (Florida Natural Areas Inventory, 2017).
These coastal communities face a variety of threats, especially invasion by non-native species,
encroaching development and other human activities.
Coastal Critical Erosion Areas - Line dataset representing eroded coastal areas, which have
been negatively impacted by natural processes or human activity. The erosion and recession of
the beach or dune system in these areas jeopardize upland development, recreational interests,
wildlife habitat, or important cultural resources (Florida DEP, 2017). These coastlines are
necessary to protect these important resources and ecosystem services.
Functional Wetlands - This dataset consists of polygon features that indicate functional
wetland locations. In addition to being unique ecosystems, wetlands act as a filter for pollution
and sediment. When rainwater runoff laden with pesticides, excess nutrients, and other
pollutants flows through a wetland prior to reaching open water, the pollutants are naturally
filtered out. Excess sediment builds up in the wetland instead of in rivers or other water bodies.
Wetlands also offer flood protection by storing runoff and releasing it slowly. The prioritization
method was based on a Land Use Intensity index and Florida Natural Areas Inventory (FNAI)
Potential Natural Areas ranking (Florida Natural Areas Inventory, 2017). Wetlands in the most
natural state are given the highest priority.
Prioritized Recharge - These polygon features represent recharge locations, which provide
ground water recharge important to natural and human use. This recharge is critical to springs,
sinks, aquifers, natural habitats, and human water supply. The data are prioritized by aquifer
vulnerability factors; these include thickness of the intermediate aquifer confining unit and closed
topographical depressions, as well as prioritizing those that are within springshed protection
zones and in proximity to public water supply wells (Florida Natural Areas Inventory, 2017).
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Wetland Habitat - Polygon dataset indicating the distribution of 35 wetland-dependent species,
which were used to determine priority wetlands for listed species. Documented and potential
wetland habitats were identified using known occurrence records and vegetative cover derived
from 1985-1989 Landsat Thematic Mapper Imagery (FGDL, 2006). The "hot spot" dataset was
created by aggregating predictive habitat maps for each of the 35 listed species.
Wildlife Refuge - This dataset consists of polygon features that represent the location of wildlife
refuges (USFWS, 2017). The National Wildlife Refuge system is a system of public lands and
waters protected by the US Fish and Wildlife Service. These lands help to conserve America's
wildlife for future generations. The National Wldlife Refuges in the Tampa Bay area are
Passage Key and Pinellas, which are closed to the public because of their small size and
importance to wildlife, and Edgemont Key, which is open to the public for recreational activities.
These include hiking, swimming, boating, fishing, and wildlife viewing (USFWS, 2018).
Sustainable Forestry - This polygon data layer identifies existing pinelands (natural and
planted) and former pinelands that are potentially available for forest management. Prioritization
is based on four criteria set by the Florida Forest Service: whether trees are natural or planted,
size of tract, distance to market, and hydrology (Florida Natural Areas Inventory, 2017). Large
tracts of natural pine on mesic soils (compared to very dry or wet soils) that are within 50 miles
of a mill receive the highest priority. Former pinelands that currently do not have trees receive
the lowest priority.
Mitigation Banks - Polygon dataset representing the location of mitigation banks (Florida DEP,
2004). Mitigation banking is the restoration, creation, enhancement, or preservation of a
wetland, stream, or habitat conservation area, which offsets expected adverse impacts to similar
nearby ecosystems (Florida DEP, 2018). The goal is to replace the exact function and value of
the specific wetland habitats that would be adversely affected by a proposed development
project.
Usable Water Value - This polygon dataset indicates the categorized value of usable water.
Human activities produce water pollutants (University of Florida GeoPlan Center, 2006). As
water moves through a watershed, it is filtered by wetlands, forests, and aquatic areas.
Replacement costs for removing a pound of nitrogen from various sources range from less than
$10 to as high as $855 (U.S. EPA, 2016). Cost increases as the nitrogen becomes harder to
route towards treatment areas and as simpler, more cost-efficient mechanisms for removing
nitrogen need to be replaced by more centralized advanced wastewater treatment facilities.
Click to see how usable water value is determined.
Flood Protection Value* - Polygon dataset representing the categorized value of flood
protection (University of Florida GeoPlan Center, 2006). Human activities alter the way water
moves through the landscape. Natural landscapes retain and slow the movement of water,
offering protection from flooding (U.S. EPA, 2016). The loss of these natural landscapes would
result in an increased need for manmade flood protection at much higher cost. Click to see how
flood protection value is determined.
Stable Climate Value - This dataset consists of polygon features that exhibit the categorized
value of a stable climate (University of Florida GeoPlan Center, 2006). Stored carbon provides a
more stable climate by reducing greenhouse gases. In 2010, CO2 accounted for about 84% of all
U.S. greenhouse gas emissions from human activities (U.S. EPA, 2016). Click to see how stable
climate value is determined .
Usable Air Value - Polygon feature dataset that represents the categorized value of usable air
(University of Florida GeoPlan Center, 2006). Human activities produce air pollutants. Trees and
other plants remove these harmful pollutants. Pollution removal results in healthier people with
reduced health care costs (U.S. EPA, 2016). The relative air pollutant cost to human health was
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used to translate the various pollutant removal rates to decreases in human health impact costs.
Click to see how usable air value is determined.
Land Use 2006 - Polygon feature dataset that indicates land use type. Land use maps based
on Florida Land Use and Cover Classification System (FLUCCS) data derived from aerial
imagery (Southwest Florida WMD, 2007).
NHD Waterbodies - Polygon features in the National Hydrography Dataset (NHD) represent
areas that contain water such as lake/pond, swamp/marsh, stream/river, canal/ditch, area of
complex channels, estuary, ice mass, playa, reservoir, sea/ocean, and wash (Horizon Systems
Corporation, 2016).
Subwatershed - Polygon areas that define drainage basins; used to identify a hydrological
feature such as a river, river reach, lake, or area like a drainage basin. Subwatershed data are
obtained from the National Hydrography Dataset (Horizon Systems Corporation, 2016).
Counties - This dataset consists of polygon features that represent Florida counties. Population
data from 2004 and 2009 Florida Statistical Abstract was sampled for each county to create the
shapefile layer (University of Florida GeoPlan Center, 2010).
River Basins - Polygon feature dataset that represents river basins. River basins are areas of
land where rivers and tributaries drain to the same point or body of water. In this scenario tool,
that body of water is Tampa Bay. Eight-digit hydrologic unit codes (HUC) are used to identify
these hydrological features (USGS, 2018).
Google Streets - OpenLayers map of Google Street map data (Google, 2018).
*The reported values for Flood Protection will be slightly smaller in the Basic Module report
versus the Advanced Module report. This difference is less than 5% between the two modules
and is further detailed in the ES Calculations Theory section.
Advanced Module Tampa Data
The EPA H20 download packages a variety of different Tampa Bay datasets into the Advanced
Module:
Roads 2013 - Line features that define the name and speed limit of roads and highways in the
Tampa Bay area (U.S. Census Bureau, 2018).
Land Use 2006 - Polygon feature dataset that indicates land use type. Land use maps based
on Florida Land Use and Cover Classification System (FLUCCS) data derived from aerial
imagery (Southwest Florida WMD, 2007).
Land Use 2020 - Polygon feature dataset representing possible land use in 2020. Future
scenarios resulting from models or subjective tabletop exercises (U.S. EPA, 2016).
Land Use 2040 - Polygon feature dataset representing possible land use in 2040. Future
scenarios resulting from models or subjective tabletop exercises (U.S. EPA, 2016).
Land Use 2060 - Polygon feature dataset representing possible land use in 2060. Future
scenarios resulting from models or subjective tabletop exercises (U.S. EPA, 2016).
To learn more about the land use scenarios:
https://archive.eDa.aov/aed/tbesAveb/html/landuse.html
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Counties - This dataset consists of polygon features that represent Florida counties. Population
data from 2004 and 2009 Florida Statistical Abstract was sampled for each county to create the
shapefile layer (University of Florida GeoPlan Center, 2010).
NHD Flowlines - This dataset consists of line features that make up a linear surface water
drainage network. The National Hydrography Dataset (NHD) contains Reach Codes for
networked features, flow direction, names, and centerline representations for areal water bodies
allowing upstream and downstream flow to be traced (Horizon Systems Corporation, 2016).
Subwatershed - Polygon areas that define drainage basins. Subwatershed data are obtained
from the National Hydrography Dataset (Horizon Systems Corporation, 2016).
Google Streets - OpenLayers map of Google Street map data (Google, 2018).
River Basins - Polygon feature dataset that represents river basins. River basins are areas of
land where rivers and tributaries drain to the same point or body of water. In this scenario tool,
that body of water is Tampa Bay. Eight-digit hydrologic unit codes (HUC) are used to identify
these hydrological features (USGS, 2018).
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Creating Reports
Basic Module Report
Create Report Tool
This section illustrates the Create Report tool functionality in the Basic Module.
n
1. Click on the Create Report icon located in the EPA H20 Toolbar. The Create Report window
will appear (Figure 57).
a. In the Report Name box, enter the preferred report name. WARNING: re-running Create
Report with same Report Name will overwrite the previously saved report.
b. If necessary, click the Change button to designate a different Report Folder location.
f 23
Q EPA H20 Project Manager
Draw the Shape, then Run Statistics
- Use Navigation tools to move around the map.
- Use Rectangle Tool to draw the area to report on.
US
w
*
Run Stats
Cancel
Report Name:
Report Folder: change
C:/Users/Username/.qgis/reports/
c.
d.
Figure 57 Create Report window
Use either the Select by Irregular Polygon icon or the Select by Rectangle icon to select
the area to run the report on. These selection tools work much like the Select Features by
Polygon or Select Features by Rectangle tools (see GIS Tools section), except that the
report area appears as a semi-transparent blue polygon while drawing (Figure 58) and the
polygon area is closed by double clicking the final vertex instead of right-clicking, as is
done when making a selection.
Once the desired report area is drawn, click Run Stats to generate the report using that
area.
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fcj) EPA H20 Project Manager
Draw the Shape, then Run Statistics
- Use Navigation tools to move around the map.
- Use Rectangle Tool to draw the area to report on.
at.
A
*
Run Stats
Cancel
Report Name:
Report Folder: | change
C:/Users/Username/.qgis/reports/
Figure 58 Report area (indicated by the blue polygon) selected with the irregular polygon tool
2. Depending on the size of the report area, it may take a few moments to generate the report in
PDF format. A progress bar displaying the percentage of the process completed for each layer will
be displayed during this time (Figure 59).
Figure 59 Report progress bar window
3. The report area will automatically be added to the Layers panel as Area of Interest (Figure 60).
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Figure 60 EPA H20 map with report area displayed and added to the Layers pane!
4. The report will be saved as a PDF in the user specified location.
Uyets 9
K Upstream Area of Interest
~
K Arma Of Inlnresi
~
« MHDFIovrfliws
fcagft Nests
O
Wood*tork_H9tfc
•
ParksartdJJecLocations
Ftirding oudWUdlifo Viewpoints
_i V ExrttWvg Trails
So niitive_ Shoreline
Eco_Gr»enways_and_L Inkages
F oreverAcquhedLaiids
llabital,Conservation Ai
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The cover page of the Basic Module report contains four main map elements (Figure 61)\
Title - Generic description of the Basic report, "EPA H20 Green Value Analysis Report."
Legend - List of layers that are turned on/visible in the Layers panel, in the order they appear
on the map. Each layer has its name and symbology, the symbols used to represent layer
data and values.
Map - Data layers from the legend shown using their respective symbologies on a map.
Scale - Displayed as a ratio of map units to the actual measurement.
The Map and Legend both include layers defining the areas compared in the report:
Upstream Area of Interest - A red dashed line that is comprised of subwatersheds that
overlap with or drain into the chosen AOI.
Area of Interest - A black dashed line that shows the user defined AOI for the report.
The second page of the Basic report summarizes statistics for all non-water flow related features in
the user-selected AOI (Figure 62). The statistics for water flow related features, Functional Wetlands,
Prioritized Recharge, Flood Protection Value, and Usable Water, are summarized for the user-
selected AOI and its upstream area.
The report summarizes each feature data type differently:
Point Features - Displays the total number of features in the summarized area.
Polyline Features - Displays the lengths and units for each feature and the total length for all
features in the summarized area.
Polygon Features- Displays areas and units for each feature and the total area of all features
in the summarized area.
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STATISTICS FOR LAYERS IN DRAWN AREA
Bald Eagle Nests: The Bald Eagle is the naticrral bird of the United States of America arid was once severely endangered in the United States. Populations
have recovered and although the Bald Eagle is no longer protected under the Endangered Species Act, it is still protected under the Bald and Golden Eagle
Protection Act and the Migratory Bird Treaty Act tolije fcelmv is summarized for the Area of Interest (AOI) that user has selected.
Total : 1
Wood Stork Nests: The US Breeding Population of Wood Storks is protected under the Endangered Species Act (Federal Register Feb 1934; Proposed status
upgrade to Threatened, Dec 2Q13).Specifically, nesting sites are protecSed.Wood Storks are birds of freshwater and estuarine wetlands, primarily nesting in
cypress or mangrove swamps.Primary reasons for the dedine of Wood Stork populations aie a reduction in food base (mainly small fish} and loss of wetland
habitat \talue below is summarized for the Area of Interest (AOI) that user has selected.
Total : 2
Parks and Recreational Facilities:Parks provide opportunities for residents to enjoy outdccr and recreational activities indudlng hiking, biking, fishing,
boating, swimming, camping, wildlife viewing and more.Parks benefit businesses arch as tourism and recreational supply industries (camping equipment etc.)
and are a soutce of employmentThey tan also provide added benefits such as improving air or water quality, redudng noise pollution, reducing heat island
effects in urban areas, and providing habitat for wild life. Va lue below is summarized for the Area of Interest (AOI) that user has selected.
Total: 11
Great Florida Girding and Wildlife Trail Sites: These sites along Florida trails provide opportunities for Binding and Wildlife viewing. The total spent annually
in Florida for wildlife viewing is two and a half times greater Chan the value of the annual orange crop harvest (S3.08 billion and $1.23 billion respectively in
2006). Value below is summarized for the Area of Interest (AOI) that user has selected.
Total: 1
Existing Trails (meter); These paved or unpavad trails for hiking, biking, equestrian, multiple use, paddling, or motorized use (ATY, OHM, ROV) are open to
the public.In-road bike lanes and sidewalks are not included. Value below is summarized for the Area of Interest (AOI) that user has selected.
CYPRESS CREEK TRAIL : 20,009
HILLSBOROUGH RIVER STATE RECREATIONAL TRAIL : 1,834
LOWER HILLSBOROUGH WILDERNESS PRESERVE TRAIL: 40,422
MEADOW POINTE TRAIL : 8,248
UNIVERSITY FIATWOODS BKEWAY : 4,222
Total Length: 74,738 meters
Figure 62 Statistics for example features in the user's AOI report
Advanced Module Report
Create Scenario
This section illustrates the workflow to create a user-defiried land use scenario in the EPA H20 Advanced
Module.
(T) Scenario Manager (T) Edit Scenario @Compare Scenarios Editing Scenario:
Figure 63 EPA H20 Toolbar 4: Scenarios Toolbar
1. Click on the Scenario Manager button found on the EPA H20 Scenarios Toolbar (Figure 63).
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In the Scenario Manager window that appears (Figure 64), type the desired scenario name
(e.g. Demo) and click Run Scenario.
Scenario manager ; f'
Scenario Manager
Name Scenario:
Demo|
Run Scenario
Delete Scenario:
T Delete
Done Cancel
Figure 64 Scenario manager window, where user may name and run the scenario
Depending on the size of the area of interest, it may take a few moments for the scenario to
be created. A progress bar will be displayed while creation is in progress (Figure 65).
>
0 EPA H20 Project Manager
F f II S3 |
Progress
Kilobytes Processed: 12912
Figure 65 Scenario Manager progress bar
After all new scenarios of interest have been created, click Done to close the Scenario
Manager window.
Note that the new scenario(s) with the user-specified name(s) will be created in the Layers
panel (Figure 66). Each newly created scenario is an exact copy of the default land use data
loaded in the Advanced Module. New scenarios can later be modified/edited as shown in the
Edit Scenarios section.
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Layers
E) J
Scenario-Demo
FLUCC5 Classifications
¦
Urban and Built-Up
Agriculture
¦
Rangeland
¦
Woodlands
¦
Water
Wetlands
Barren Land
¦
Utilities and Transportation
¦
Tidal Flats
¦
Seagrass and Algae Beds
Figure 66 New scenario located in the Layers panel
Edit Scenarios
This section illustrates the workflow to edit a user-defined scenario in the Advanced Module of EPA
H20. For illustration purposes, land use types in the example scenario created in the Create
Scenario section will be edited for selected features for hypothetical scenarios.
Edit Scenario Land Use
1. Click the Edit Scenario button on the EPA H20 toolbar to open the Edit Scenario window
(Figure 67).
Q Edit Scenario
Modify User Scenario Land Use and/or Attributes
1. Choose a Scenario Land Use layer and start editing.
New Land Use for selection: Scenario-Demo ~ Start Editing
2. Use selection tools in the toolbar.
Update Selected Polygons Land Use to:
' BAY SWAMPS
Update
Modify EGS Algorithm Values
Flood Protection
Water Retention Value($/ft3): 2
Range (1-20) Q
Stable Climate
($/Ton carbon): 37
Range(10-240) Q
Usable Water
$/lb Nitrogen: 3
Range(l-45) @
Update Attributes
Figure 67 Edit Scenario window
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2. Make sure Scenario-Demo is selected and click on the Start Editing button (Figure 67). This
will cause several things to occur in the EPA H20 interface (labeled A-D in Figure 68):
a. The name of the scenario being edited (e.g. Scenario-Demo) will display in red on the
EPA H20 toolbar.
b. The edit icon will appear next to the layer being edited (e.g. Scenario-Demo) in the
Layers panel.
c. The Selection tools will appear in the upper left corner of the user interface.
d. The Stop Editing button will replace the Start Editing button in the Edit Scenario
window.
A ®
P Layers
B x Scenario-Demo
FLUCCS Classifications
I Urban and Built-Up
Agriculture
Rangeland
| Woodlands
I Water
[•••• Wetlands
Barren Land
| Utilities and Transportation
- I Tidal Flats
Seagrass and Algae Beds
0 User POIs
4
B Roads_2013
| 56 -70 mph
46 - 55 mph
26 -45 mph
| 00 -25 mph
B £3 Land_Use_2006
FLUCCS Classifications
I Urban and Built-Up
Agriculture
Rangeland
| Woodlands
I Water
Wetlands
hi Barren Land
| Utilities and Transportation
| Tidal Flats
Seagrass and Algae Beds
B CP Land_Use_2020
FLUCCS Classifications
I Urban and Built-Up
Agriculture
Rangeland
I Woodlands
I Water
Wetlands
Barren Land
| Utilities and Transportation
I Tidal Flats
Seagrass and Algae Beds
'5^ Q Scenario Manager (J) Edit Scenario ©Compare Scenarios Editing Scenario: Scenario-Demo
isr • A^
r - -1:4^^, maL. i
Edit Scenario
Modify User Scenario Land Use and/or Attributes
1. Choose a Scenario Land Use layer and start editing. ^
New Land Use for selection: Scenario-Demo Stop Editing
2. Use selection tools in the toolbar.
Update Selected Polygons Land Use to:
BAY SWAMPS ~ I Update I
Modify EGS Algorithm Values
Flood Protection
Water Retention Value($/ft3): 2
Range (1-20) Q
Stable Climate
($/Ton carbon): 37
Range(10-240) Q
Usable Water
$/lb Nitrogen: 3
RangeCl-45) Q
Update Attributes
/
Figure 68 Edit the scenario in the Edit Scenario window; changes to the program are indicated with letters A-D
3. The user can navigate and zoom to the to-be-edited area (Figure 69) using normal map
navigation controls (the GIS Tools section describes these). Zooming in on an area within the
AOi makes it easier to observe and update the land use of individual features. For example, in
Figure 69 it is easier to see that land use types for most of the area are Urban and Built-Up or
Agriculture.
55
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* Hi* ]vJ
II C3 Scenariio-Oemo Qp * £ J _^I^Bl»5j /
¦ Urban and BuiW-Up | "\m L f^JR J* A
s; %! * fi(% /^l * VT*5^sj
Wrt s™ ^ ^' *a 4
Wetlands > *W jT* Z4;
Barren land ^ * M Jfc ~ * T # 1 I
¦ Utitrties'TranspwIaliDn j A/j^h Jta f /
a*- ^ * m%
Figure 69 Zoomed in area within the AOI, demonstrating symboiogy of polygons
4. While EPA H20 is in edit mode (see step 2 a-d) use the Feature Selection tools (see GIS
Tools section) to select the polygon(s) the user wants to change in the scenario. Selected
polygons will appear bright yellow in color, with the vertices outlined by red crosshairs (Figure
70 shows an Agriculture polygon (TREE CROPS) from Figure 69 after being selected).
^¦zm\
81 - 4~l
i nJH Jm X < I ll ¦
V - - H UrtswandBuS-Up ™ \ L »
*-"• Agnculturt •*.
Rjr^and - l vXD^I ^
^ t
- —^ iviw. p » \ V/ all .•»t,
Barren Laid y m J m. ft - r'
¦ UtiWi.: • y J ¦¦¦
^ w 7C ¦
I v * * -*/W ¦~ *•' ^ «%*// I
. 4* _ * ^ i n ?j * l
Figure 70 Tree Crops polygon is selected during scenario editing, indicated by the blue arrow
5. In the Edit scenario window, use the dropdown list under the Update Selected Polygons Land
Use to: label to choose the land use type the selected polygons will become (e.g.
COMMERCIAL AND SERVICES in Figure 71).
56
c
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6. Click the Update button to update the selected polygon land use to the type in the dropdown
list (Figure 71).
^ Edit Scenario
Modify User Scenario Land Use and/or Attributes
1. Choose a Scenario Land Use layer and start editing.
New Land Use for selection: Scenario-Dem T Start Editing
2. Use selection tools in the toolbar.
Update Selected Polygons Land Use to:
COMMERCIAL AND SERVICES
Update
Modify EGS Algorithm Values
Flood Protection
Water Retention Value($/ft3): 2
Range (1-20) O
Stable Climate
($/Ton carbon): 37
Range(10-240) Q
Usable Water
$/lb Nitrogen: 3
Range(l-45) Q
Update Attributes
Figure 71 Edit Scenario window, allows the user to change the land use type of selected polygons
7. Updating the land use type may take a few moments depending on the area of interest and
the features selected. Do not close the program while the update process is in progress.
8. Once complete a pop-up window will appear, click OK to continue (Figure 72).
9. Click on the Stop Editing button in the Edit Scenario window to commit changes made to the
land use polygon.
57
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Edit Scenario
Modify User Scenario Laivd Use and/or Attributes
1. Choose a Scenario Land Use layer and start editing.
New land use for selection: Scenarto-Demo *
Stop Editing
2. Use selection toots in the toolbar.
Update Selected Polygons Land Use to:
COMMERC
J Wmfcrirt t anrf 1 It* 11 jvtnted
Update
Stop Editing to save your Edits.
y —1
OK
Flood Protection
Water Retention value(S/ft3): 2 Range (1-20) Q
Stabfe Climate
($/Ton carbon): 37 Range(10-240) Q
Usable Water
$/1b Nitrogen: 3 Range(l-45) Q
Update Attributes
J
Figure 72 Scenario Land Use Updated message window
10. The user can continue editing the land use scenario in this fashion to create alternative land
use scenarios for comparison and analysis.
In the example here, TREE CROPS type land use features were converted into COMMERCIAL AND
SERVICES. Figure 73 displays the newly converted land use polygon in a light red color for Urban and
Built up land use. Multiple land uses are combined into single symbology categories for better
representation on the map. In this case, the COMMERCIAL AND SERVICES land use type falls under
the Urban and Built up land use category. This hypothetical scenario could represent an urban
development project being evaluated using EPA H20. The next step of the scenario comparison is
assessment of the impact of this land use change on ES values.
58
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& 0>A M20 -
W» Vt*-n Help Transportation
* it O j ^ Q Scenario Manager Q Ed«S«rwt» QCompare Scenaoos EtWng Scenario:
ScurtiMlo D*nw>
R.UCCS Cl«»AMe<«n
| UltUBl. t/vt &g>H-Up
AgiM-uSu'a
i FUos«ir>a
¦ yv*t*
04rr»n UnO
¦ UhtoM, tnS T«an(K^ffiion
fl TkWFUss
¦ $44914$ iMAijM 8*a
llwPOU
~
Rood* 2913
B w - ro mfo
*6 - S5 mph
2f> - *5 mp»i
i J 00 -» mph
l«nd_U«» 200$
FlUCCS CI* tefeJtOH
¦ »*J 9^-Up
Ag»tCo*Ul«
¦ Ran9*l**J
IVYcWiWKh
VV«*
Wttimto
Swan Itrd
• uws*i w Tfmpwiwiw
ThmRci*
H Sjjgiisi #>ai Aijm 8»4l
l4Ui4.UM.2Q20
FlUCCS CianAcjwftt
¦ u-Mrt »«ewa-U{i
Ai/icufcute
r " R*io>lfcvi
1C Control rendering order
0 m«ct*5 on toywr
Figure 73 Edit Scenario window; the TREE CROPS polygon was converted to COMMERCIAL AND SERVICES
Technical users may also input their own land use comparison data into EPA H20. This land use data
may be edited in the same fashion, and can be used to Compare Scenarios. The Create Land Use
Comparison Data section explains how the technical user may insert their own data.
Changes in land use are summarized in the Compare Scenarios section.
Edit ES Unit Values
The ES value estimation algorithm used for each ES is explained below and detailed further in the ES
Calculations Theory section.
Stable Climate - https://archive.eDa.gov/aed/tbes/web/html/AStableClimate.html
The social cost of carbon was used to value carbon sequestration. The dollar value of carbon
reductions in the form of the greenhouse gas carbon dioxide has been estimated as $20 per ton ($0.01
per lb) of Carbon Dioxide in 2010 (US Government 2010). We applied this 2010 estimate across years
without year specific corrections for inflation. This social cost of carbon is an estimate of the monetized
damages associated with an incremental increase in carbon emissions for a given year. It is intended
to include, but is not limited to, changes in net agricultural productivity, human health, property
damages from increased flood risk, and the value of ecosystem services. Even without year specific
cost adjustments the $20 per ton of CO represents a conservative estimate that has been recalculated
as 12 times larger using a discount rate more appropriate for intergenerational cost-benefit analysis
(Johnson and Hope, 2012). Carbon sequestration rates were multiplied by the conservative cost
estimate to arrive at the total value of this ecosystem good that benefits humans by moderating climate
change and then summarized by National Hydrography Dataset Plus catchments (http://www.horizon-
systems . com/n hd pi us/).
Flood Protection - https://archive.epa.gov/qed/tbes/web/html/FioodProtection.html
The replacement cost for installing drainage infrastructure to compensate for lost water retention was
used as an estimated value of reduced flooding. Retained volume of water was multiplied by $2 per
cubic foot, a default cost of built drainage infrastructure. For our 30x30m cells:
59
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$Value = mm* 304.8 mm per ft * 9687.5 ft2 per cell * $2 per ft3 = $63.57 per mm water retained.
These values were then summarized by National Hydrography Dataset Plus catchments.
(http://www.horizon~svstems.com/nhdplus/).
Usable Air - https://archive.epa.gov/qed/tbes/web/html/UsableAir.html
The relative air pollutant cost to human health was used to translate the various pollutant removal
rates to decreases in human health impact costs. The estimated value for removal of the selected
pollutants was $959/ton Carbon Monoxide, $6752/ton Ozone, $1653/ton Sulfur Dioxide, $4508/ton
PM10, and $6752 ton N02 (Murray etal., 1994).
The total value of air pollutant removal was calculated as
Air Pollution Removed= £ Value * FluxRate * %Can * Cell Size
where i represents the individual pollutants
Value is the decrease in costs associated with a decrease in pollutant species, and FluxRate is the
removal rate of the specific pollutant species. Canopy coverage estimates were used to calculate the
total air pollution removed in U.S. dollars ($) per year summarized by National Hydrography Dataset
Plus catchments (http ://www. h o rizon-svste ms.co m/n h d pi us/).
Usable Water - https://archive.epa.gov/qed/tbes/web/html/UsableWater.html
Replacement costs for removing a pound of nitrogen from various sources range from less than $10 to
as high as $855. Costs increase as the nitrogen becomes harder to route towards treatment areas
and as simpler, more cost-efficient mechanisms for removing nitrogen need to be replaced by more
centralized advanced wastewater treatment facilities. Compton et al. (2011) reviewed the cost of
removing nitrogen from a wide range of sources and concluded that costs ranged from $1.22 - $43.54
per pound of nitrogen ($2.71 - $96 kg N). Abatement costs of reducing nitrogen from point sources
are estimated as $8.16 per pound ($18 kg) of nitrogen (Birch et al. 2011). We use this cost as our
conservative ecosystem replacement value estimate based on using traditional wastewater treatment
to remove nitrogen from upstream point sources. The values are summarized by National
Hydrography Dataset Plus catchments (http://www.horizon-systems.com/nhdplus/).
Several lifecycle estimates, however, including upgrading and maintaining existing or building
additional advanced wastewater treatment facilities and drainage structures to remove nitrogen, put
the cost as high as $855 per pound ($388 kg) of nitrogen removed (Roeder 2007). This higher
ecosystem replacement value may be more appropriate than our more conservative number for
illustrating the potential future value for bay habitats in a scenario of increasing nitrogen removal
needs.
Users can use the Edit Scenario tool to modify ES dollar values. Default dollar values for flood
protection ($2), stable climate ($37) and usable water ($3) can all be updated in the Edit Scenario
window (Figure 74, for example these were changed to $4, $47 and $6, respectively).
60
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Modify User Scenario Lard Use and/or Attributes
1. Choose a Scenario Land Use layer and start editing.
New Land Use for selection: Scenario-Demo T Stop Editing
2. Use selection tools in the toolbar.
Update Selected Polygons Land Use to:
COMMERCIAL AND SERVICES
Update
Modify EGS Algorithm Values
Flood Protection
Wate r Retenti o n Va 1 u e($/ft3): 4
Range (1-20) $
Stable Climate
($/Ton carbon): 14?)
Range(10-240) Q
Usable WSter
$/lb Nitrogen: 6
Range(l-45) Q
Update Attributes
Figure 74 Edit Scenario window allows the user to change the ES Algorithm Values
1. Click the Edit Scenario tool to open the Edit Scenario window (Figure 74).
a. In the Modify EGS Algorithm Values section, enter the preferred ES monetary value.
b. Click the Update Attributes button.
2. The progress bar will appear while attributes are being updated (Figure 75). This may take few
moments, depending on the number of the features within the area.
Modify EGS Algorithm Values
Flood Protection
Water Retention Value($/ft3): 4
Stable Climate
Range (1-20) 0
($/Ton carbon): 47 Range(10-240)
Usable Water
$/lb Nitrogen: 6
Range(l-45) O
Update Attributes ] | 1 26%
Figure 75 Modify ES Algorithm Values progress bar
3. Once the ES attributes are updated, a message will be displayed, stating the attributes have
been successfully updated, and to commit changes using the Stop Editing button (Figure 76).
61
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4. Please make sure to click Stop Editing to save the changes.
i-j Update Finished
The attributes a
You can commit
re successful
changes usi
OK
y updated.
ig "Stop Editing" button.
Figure 76 ES Algorithm Values Update Finished window
Changes to ES dollar values are summarized in the Compare Scenarios section. Please note,
updating the ES values may result in a slight change in Flood Protection; this is due to rounding
during the repopulation of the scenario's attribute table.
Compare Scenarios
This section illustrates the workflow for comparing scenarios in the Advanced Module of EPA H20.
Note that only two scenarios can be compared at a given time.
1. Click on the Compare Scenario button.
2. The Compare Scenario window will open (Figure 77):
a. In the Scenario A and Scenario B dropdown lists, select the scenarios to be compared
(e.g. Land_Use_2006 and Scenario-Demo).
b. In the Report Name box, type the preferred report name. If an existing report name is
chosen, it will overwrite the existing report.
c. The default report folder will be displayed in Compare Scenario window
(C:/Users/Username/.qgis/reports/); click on the Change button to modify the report
location.
d. Use the Zoom In , Zoom Out A ,and Pan
<3 $
^ - icons to focus on the desired area.
^ EPA H20 Project Manager
mi is i
Draw the Shape, then Run Comparison
- Choose Scenarios to compare.
- Use Navigation tools to move around the map.
- Use Rectangle or Polygon Tool to draw the area to report on.
Scenario A Land Use 2006 T
Scenario B
Scenario-Demo
Report Name:
Report Folder:
C:/Users/Username/.qgis/reports/
Change
Compare
Cancel
Figure (1 Compare Scenario window
62
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e. Click ori the Area Selection icon and draw an area on the map for which the user
wants to create the report (AOI). Please note that EPA H2Q will automatically compute
the upstream area and the statistics for it.
f. The user-selected area will be highlighted in a blue color (Figure 78). Click on the
Compare button to generate the PDF report.
I
I JT » ,
Figure 78 User-selected area is shown inside the blue box, to be used in the Compare Scenario tool
Compare
Draw Che Shape, then Run Comparison
- Choose Scenarios to compare.
- Use Navigation tools to move around the map.
- Use Rectangle or Polygon Tool to draw the area to report on.
Scenario A
Scenario 8
Report Name:
Change
Report Folder:
3. A progress bar will be displayed while the report is generated (Figure 79). It may take a few
moments, depending on the size of AOI and its upstream area.
iy EPA H20 Project Manager
f Le&J
Report Progress
Layer Processing:
Figure 79 Compare Scenario progress bar
4. New data layers, Area of Interest and Upstream Area of Interest, will be generated in the
Layers panel (Figure 80). The Upstream Area of Interest includes subwatersheds that overlap
with or drain into the chosen AOI.
63
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fd* V»**r Hrip Transportation
.« & O ®S«cnano Manager Q fdt Scenario Qcampare Scenarios f<*t)og Scene no:
Uy«>s
K Upurrtam Aim CM InUcwMt *
~
X Ar«oi IX ImaiMt
o
X SconarloDomo
FlUCCS ClaiiAcabOM
¦ UrUn tea 0uit-Up
Agncufcuia
15 RangoU-d
BWocdiands
Wat*
Watfaods
BatraflUnd
¦ UUt*t and 7/anipe*1ation
H Tidas Pises
SB S«agra« andAlga* 6«ij
IJs.tr POIi
4
Kpn
¦ Ttda) Flats
Ki Saagrass andAijwSads
Land_Us® 2W0
M Control rendering Order
Layers Srwrar
0 t»atw»|s)»»i«c I *£ en W/w Scwtan^Owno
Figure 80 EPA H20 map after the Compare Scenario tool is run
Advanced Module Report Analysis
This section overviews the contents of the Advanced Module report (Figure 81).
Ecosystem Valuation Report
¦-—i j
Legend
Upstream Area Of Interest
c.1
Area Of Interest
IZ.1
Scenario-Demo
FLUCCS Classifications
Urban and Built-Up
Agriculture
Rangeland
¦ Woodlands
¦ Water
Wetlands
Barren Land
¦ Utilities and Transportation
Tidal Flats
Seagrass and Algae Beds
Land_Use_2006
FLUCCS Classifications
¦I Urban and Built-Up
Agriculture
Figure 81 Sample Advanced Module report, map with legend
64
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The cover page of the Advanced Module report contains four main map elements (Figure 81):
Title - Generic description of the Advanced report, "Ecosystem Valuation Report."
Legend - List of layers that are turned on/visible in the Layers panel, in the order they appear
on the map. Each layer has its name and symbology, the symbols used to represent layer
data and values.
Map - Data layers from the legend shown using their respective symbologies on a map.
Scale - Displayed as a ratio of map units to the actual measurement.
The Map and Legend both include layers defining the areas compared in the report:
Upstream Area of Interest - A red dashed line that is comprised of subwatersheds that
overlap with or drain into the chosen AOI.
Area of Interest - A black dashed line that shows the user defined AOI for the report.
The second page of the sample report summarizes the total value of each ES in the AOI or areas
upstream for each scenario (Figure 82). The report also provides a short description of each ES, visit
US EPA's Archived Tampa Bay Ecosystem Services Project website to learn more about ES and their
estimations.
In this example, the user made significant changes to the land use and attribute values in the Edit
Scenarios section. Below is the interpretation of the report in relation to those changes:
o The usable water value has been increased from 2,028,898 $/yr to 4,068,561 $/yr. This is the
result of increasing the value of nitrogen removed ($/lb) from 3 to 6 in the Edit ES Unit Values
section, as well as the change in land use type from TREE CROPS to COMMERCIAL AND
SERVICES.
o The usable air value has decreased from 486,382 $/yrto 472,583 $/yr. This is a result of
converting an area of TREE CROPS to the COMMERCIAL AND SERVICES land use type (Edit
Scenario Land Use section),
o The stable climate value has increased from 2,482,571 $/yrto 2,997,867 $/yr. This is a result of
increasing the value of carbon removed ($/Ton) from 37 to 47 in the Edit ES Unit Values section,
as well as the change in land use type from TREE CROPS to COMMERCIAL AND SERVICES,
o The flood protection value significantly increased, from 27,214,370 $/yrto 50,768,155 $/yr. This
is a result of increasing the water retention value ($/ft3) from 2 to 4 in the Edit ES Unit Values
section, as well as the change in land use type from TREE CROPS to COMMERCIAL AND
SERVICES.
o The TREE CROPS area has been changed from 2,578,233 sq. meters to 893,548 sq. meters.
The reduction of the area is due to converting TREE CROPS to COMMERCIAL AND
SERVICES in the Edit Scenario Land Use section,
o The COMMERCIAL AND SERVICES area has increased from 6,903 sq. meters to 1,691,588
sq. meters. This is also a result of converting TREE CROPS to COMMERCIAL AND SERVICES
in the Edit Scenario Land Use section.
65
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STATISTICS FOR LAYERS IN DRAWN AREA
Oft AWN AREA OF INTEREST: 3,373 Hectares
Usable Watpr: Hirnan acttvtaes produce water poilutarSs, A? water mchr through a wasefshed it »s fleered by wetlands, forests, and aquatic areas-
Replacement oast* for removing a pound of nitrogen from various sources range from less than $10 to as high as $855.Cosfcs increase as the nitrogen becomes
harder to route treatment areas and as ssnptes more «*s£ efficient mechanisms for removng nerogen need to be replaced by more centralized
advaffteed waste wases- treatment facilities.
Land Use 2006 Scenario-Demo
Estimated total value (!) per year 2,028,898 Estimated total value (9) P^r year: 4,068,561
Usable Air: Human activities produce air potkitants. Trees and other plants remove Bsese harmfu pollutants. Pdkjticn rerrxwal results in hcaihier people with
reduced health care costs. The tats of trees a«J other plants would result in Increased health cane oasis and decreased human welNMing.
Land Use 2006 Scenario-Demo
Estimated total value (!) per year 486,382 Estimated total value ($) per year: 472,583
Stable ClimateiSta-Tjd carbon provides a more Aibk; dimafce by keeping greenhcxac ^aaiea out of our atmosphere. Carbon dptn.de (C02) b the primary
gnx-nlxMjsc gas emitted through human activities. Carbon sequestration helps reduce future social costs associated with a more unstable ctanate.
Land Use 2006 Scenario-Demo
Estimated trtal value ($} per year: 2,482,571 Estanatctii total value ($) per yean 2,997,867
Flood Protection: Human activities afiw the way water mores mrtwgh Che landscape. Natural landscape retain and slow the movement of watt" offering
protection from Reeding. The loss of these natural landscapes wcwld result in the need for more man made flood protection at mac*! higher cost Rood
protection value below is summarized for tte Area of Interest [AO]) that user has selected.
Land Use 2006 Scenario-Demo
Estimated to&tf value: 27,214,370 Estimated fetal value: 50,768,155
Land Use; Land maps arc made from Honda Land Use and Cover Cuiiaficatkjn System (FLLKXS) data. These are photo irttepnSaiians af aerial photographs.
Future scenarios are the result of motfels or subjective table top ewtdses.
Land Use 2006 Scenatlo-Demo
COMMERCIAL AND SERVICES : 6,903
COMMEROAL AND SERVICES : 1,691,588
CROPLAND AND PA5Tl#ELAND ; 3,013,%3
CROPLAND AND RASTUREIAND : 3,013,963
CYPRESS : 13,034
CYPRESS : 13,034
EMERGENT AQUATIC VEGETATION : 3,453
EMERGENT AQUATIC VEGETATION : 3,453
OffiWCTWE: 10,736,475
EXTRACTIVE : 10,736,479
FRESHWATER MARSHES . 540,723
FRESHWATER MARSHES : 540,723
HARBWGQO CONIFER WXH>: 990,-388
HARDWOOD CONIFER MD(H> : 990,388
INDUSTRIAL : 19,586
INDUSTRIAL : 19,586
OPEN LAND : 2 25,608
OPEN LAND : 225,608
OTHER OPEN UWDS : 1,483,836
PINE FLATWOOD5 : 1,075,387
PINE FLATWOODS: 1,075,387
RESERVOIRS : 62,145
RESERVOIRS : 62,145
RESIDENTIAL LOW DENSITY < 2 DWELLING UNITS ; 556,640
RESIDENTWi. LOW DENSITY < 2 DWELLING UNITS : 556,640
ROW CROPS : 6,655,527
ROW CROPS : 6,655,527
SHRUB AND BRUSHftATC : 2^96,880
SHRL® AND BRLSHLAND 2,596,883
SPECIALTY FARMS : 97.830
SPEGA1XY FARHS : 97.830
stream and UMCE SWAMPS (BOTTOMLAND) : 1,953,085
STREAM AMD LAKE SWAMPS (BOTTOMLAND) : J .953,085
TREE CROPS : 2,57833
TREE CROPS : 893,548
Figure 82 Sample Advanced Module report; summary of ES in each scenario
66
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Delete Scenario
This section illustrates the workflow for deleting a user-defined scenario in EPA H20's Advanced Module.
1. Click on Scenario Manager to open the Scenario Manager v/indow (Figure 83).
a. Under Delete Scenario dropdown list, select the desired scenario to-be-removed.
b. Click on the Delete button to delete the scenario. All the land use features and ES value
data for that scenario will be deleted. Deletion of a scenario is irreversible.
0 Scenario manager
f l|rS3-|
Scenario Manager
Name Scenario:
Run Scenario
Delete Scenario:
Scenario-Demo
~
Delete
Done
Cancel
Figure 83 Scenario Manager window, used to irreversibly delete a scenario
67
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Transportation Tool (Advanced Module Only)
The transportation tool allows for an assessment of connectivity between potential users and
ecosystem services by measuring the proximity in both distance and time between population
centers and ES points of interest defined by the user (e.g., parks, greenways, forests).
The Transportation tool in the Advanced Module of EPA H20 allows users to:
o Add Points of Interest (POI) to the existing transportation network,
o Edit the existing transportation network.
o Compare changes in driving and walking time to POIs for the existing and modified
transportation network.
This section illustrates use of Transportation Module features.
1. Create or choose an existing project with a defined AO! (see Select AOI section) and open
the Advanced Module (see Advanced Module section).
2. Click Transportation menu > Transportation scenario manager (Figure 84).
^ EPA H20 - Transportation
File View Help Transportation
S] £ 9
Transportation scenario manager
Edit transportation scenario
2nario (Jjcompare Scenarios Editing Scenario:
l_ay, Q Create comparison report
User POIs
4
X Roads_2013
¦ 56- 70 mph
46 - 55 mph
26 - 45 mph
00 - 25 mph
C=> Land_Use_20Q6
FLUCCS Classifications
¦ Urban and Built-Up
Agriculture
Rangeland
| Woodlands
I Water
Wetlands
Barren Land
| Utilities and Transportation
I Tidal Flats
i
Figure 84 Location of the Transportation scenario manager in EPA H20
3. The Transportation scenario manager window will appear (Figure 85):
a. In the Alame Scenario box, enter the desired scenario name.
b. Click the Run Scenario button to create a new, editable Transportation layer.
c. Click Done to close the window.
-------
Q Transportation scenarios manager
Ms-
Scenario Manager
Name Scenario:
Run Scenario
Delete Scenario:
T Delete
Done
Cancel
Figure 85 Transportation Scenario Manager window
4. Under the Transportation menu, choose Edit transportation scenario (Figure 86).
Help
Transportation |
Transportation scenario manager
^ Edit transportation scenario
zenario
Q. Create comparison report
Figure 86 Location of the Edit transportation scenario tool in the Transportation menu
5. The Edit Transportation Scenario window wiii open.
a. In the Scenario to Edit dropdown list, select a scenario to edit (e.g. Scenario- Demo,
Figure 87).
b. Click the Start Editing button.
0 Edit Transportation Scenario
f -EM
Scenario to Edit: Transportation-Scenario-Demo T Start Editing
Done
Cancel
Figure 87 Edit Transportation Scenario window
6. Click the Connector
V5
icon to add a new road to the map.
a. Single click on the map to start drawing the road
b. Single click again to add a bend or joint in the road
c. Double click to finish drawing the road
Note: Although new road lines may appear to start at an existing road, the Transportation Module will
only route to the existing road if the new road intersects it. To ensure the roads intersect, users should
69
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place the start point for new roads before the desired intersection so that the new road crosses over
the existing road. The end point for new roads will automatically snap to the nearest vertex of an
existing road, ensuring an intersection but potentially altering the end point location of the new road.
7. In the New Road Feature window (Figure 88):
a. In the Road Name text box, type the preferred road name.
b. In the Speed (mph) text box, designate a speed limit in miles per hour.
c. Click OK
Q New Road Feature
Road Name:
Speed (mph):
mi^t
OK
Cancel
Figure 88 New Road Feature window
8. The user can add multiple roads in a similar fashion (repeating steps 6 & 7).
9. The New Road Feature window can also be used to create recreational trails. Roads not
intended for driving should receive a speed limit of 1 mph.
a. The Transportation Module looks for the fastest route of travel during the Transportation
Scenario Comparison Report. A speed limit of 1 mph will decrease the likelihood that the
new trail is used for driving.
b. However, when a Point of Interest (POI) is located off the Road network, the point is
associated with the nearest road available. If a POI is closest to a user-created trail (with
1 mph speed), the Transportation Module will drive on this slow road.
10. In the Edit Transportation Scenario window click Stop Editing to save edits and click Done to
close the window.
Multiple transportation scenarios can be generated each with multiple roads added or altered. These
scenarios can then be compared using the Create Comparison Report tool.
Transportation Scenario Comparison Report
Comparison reports are tables of travel times between a starting location and all the Points of
Interest (POIs) within a given radius. Any two transportation scenarios can be compared by creating
comparison reports:
1. Under the Transportation menu, choose Create comparison report (Figure 89).
Help
Transportation I
^ Transportation scenario manager
Edit transportation scenario
cenario
H Create comparison report
Figure 89 EPA H20 transportation map and location of the Create comparison report tool
2. The transportation report window will appear (Figure 90).
70
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Transportation Scenario A
Roads_2013
Transportation Scenario B
Transportation-Scenario-Df
Transportation method
Walking
• Driving
Submit
Location:
Transportation
Destination locations:
Coordinate capture »
Coordinate capture
-
Coordinate capture
Starting location:
Ending location:
Position name:
m
I IB
Maximum distance
Add position(s)
Mile[s)
Figure 90 Two input methods for the starting point in the Transportation tool
3. The starting point can be chosen using two input methods (Figure 90):
a. Coordinate capture:
i. In the Starting location box, enter the latitude and longitude coordinates, or click the
Coordinate capture
map (Figure 91).
icon and use the crosshair cursor to select a point on the
Transportation
Location:
Coordinate capture T
Starting location:
-9125574.59186,3230701.39057
Figure 91 Coordinate capture option chosen to indicate a starting point in the Transportation tool
b. Geocoding address:
i. In the Geocoding address box, enter the full address (Figure 92). All address fields
must be filled out to geocode an address (Address, City, State, Zip code).
ii. Click Submit.
11
-------
Location:
Geocoding address T
Address:
City:
State:
Zip code:
Transportation
Main St
Trimnpi
H
Submit
Figure 92 Geocoding address option chosen to indicate a starting point in the Transportation tool
4. Once the starting point is chosen, slide the Maximum Distance buffer bar to constrain the
analysis to a set Euclidean distance (miles) to POI's. POI's outside this distance will not be
considered.
5. In the Transportation Scenario A and Transportation Scenario B dropdown lists (Figure 93),
choose two different transportation scenarios to compare.
6. Choose the Transportation method, either Walking or Driving:
a. Walking - analyzes routes using a constant walking speed of 8 miles per hour in the
scenario comparisons. It also limits analysis to roads that are safe for pedestrians. The
phrase "No Path" will appear in the comparison report if a point of interest is only
accessible using a highway.
b. Driving - analyzes routes using the speed limit designated in the scenario
comparisons.
Transportation Scenario A
Roads_2013 T
Transportation Scenario B
Transportation-Scenario-De T
Transportation method
Walking
• Driving
Submit
Figure 93 Transportation tool with two different scenarios and the Driving method selected
7. Click Submit to run the comparison and generate a report (Figure 93).
8. A Warning! window may appear (Figure 94). If satisfied with the road changes made, click
Yes. If not, click No and adjust the scenario accordingly.
72
-------
\:jl Warning!
1^1
The latest changes to a chosen scenario have not been saved
Would you like to commit the changes and create a report?
Yes
No
Figure 94 Warning! message to confirm changes to Road network
9. Once generated, a report will open in the system's default PDF reader.
10. The Transportation report contains five main components (Figure 95):
Title - General description of the report, "Transportation network report"
Starting point - When using the Geocoding address option, this is the address entered.
If using the Coordinate capture option, this is the latitude and longitude selected.
User interest point column - Lists the names of the points in the User_POIs layer.
Scenario A - Column that contains the name of the first network chosen, and the time in
hh:mm:ss it would take to drive or walk from the starting point to each POI.
Scenario B - Column that contains the name of the second network chosen, and the time
in hh:mm:ss it would take to drive or walk from the starting point to each POI.
Transportation network report
Starting point:
Longitude:-81.9536535326, Latitude:27.9533578251
User interest point
Roads_2013_Cost
T ransportation-Scenario-Dem
o_Cost
SOUTHEAST PARK
0:04:12
0:04:11
WABASH / 3RD AVE PARK
0:09:48
0:09:49
MULBERRY MUNICIPAL PARK
0:04:19
0:04:17
CENNTENNIAL PARK
0:04:12
0:04:11
MULBERRY PARK
0:04:46
0:04:46
PARKS AND RECREATION ADMIN. OFFICE
0:09:29
0:09:30
POLK STREET PARK
0:08:24
0:08:24
NORTHEAST PARK
0:03:22
0:03:23
JANIE EASTON PARK
0:03:22
0:03:23
Figure 95 Example of the Transportation Network report in EPA H20
11. Please note: starting points and ending points that are located off the Roads network are
calculated differently.
a. Starting points will snap to the nearest vertex in a road and calculate travel time from that
point.
b. Ending points will snap to the nearest line in the Road network and calculate travel time
from that spot in the road.
c. Therefore, the Transportation network report is an estimate; point locations and travel
times may vary slightly.
Select POI
The Parks_and_Recreation layer is used for User_POIs by default. However, the user may add
points of interest (POIs) to the User_POIs using the Destination Locations dropdown list in the
73
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destination locations section (Figure 96) of the transportation tool (Figure 90). There are three options in
this dropdown list for adding points of interest:
o Coordinate Capture - by POI coordinate longitude and latitude, or clicking on the map.
o Geocoding Address - by POI address,
o Load Point of Interest file - by .csv file of POI addresses.
Destination locations:
Coordinate capture
Coordinate capture
Geocoding address
Load Point of interest file
Position name:
¥
Add position(s)
Figure 96 Methods of determining Destination Location in EPA H20 Transportation tool
Coordinate Capture
1. In the Destination locations dropdown list, choose Coordinate capture (Figure 96).
2. In the Position name text box, enter the desired POI name.
3. In the following text box, enter the longitude and latitude, or click the Coordinate capture
icon and select coordinates on the map for the POI. A blue cross marker will indicate the user-
selected POI on the map (illustrated by arrow in Figure 97).
4. Click on the Add positions(s) button.
Destination locations:
Coordinate capture
Ending location:
Position name: My New Point
-9144481.20096,3260006.0301 ®
Add position(s)
Figure 97 Destination location (blue X, indicated by blue arrow) chosen by Coordinate capture
74
-------
Geocoding Address
1. In the Destination locations dropdown list, choose Geocoding address (Figure 96).
2. Type in the POI Street Address, City, State, and Zip Code (Figure 98).
3. Click the Submit button. A blue cross marker will indicate the user selected POI on the map.
4. Click on the Addpositions(s) button.
Destination locations:
Geocoding address
T
Address:
1234 Main St
City-
Tampa
State :
FL
Zip code:
l5432ll I
Submit
Add position(s)
~
Figure 98 Destination location chosen by Geocoding address in Transportation tool
Point of Interest file
In the Destination locations dropdown list, choose Load Point of interest file (Figure 99).
Destination locations:
jLoad Point of interest file j T
I IB
Add position(s)
Figure 99 Destination location chosen by Load Point of Interest file in Transportation tool
2. Click on the Browse button
Q
(under the Destination locations dropdown list) to select the
user's POI file on the computer (Figure 99).
Note: only comma delimited CSV files are acceptable. The CSV file should have the headers
Name, Address as shown in Figure 100.
75
Load
1.
-------
1 Name,Address
j£ Busch Gardens Tampa, "10165 51 Malcolm McK.ir.ley Cr, Tampa, TZ 33612"
A1 Lopez Park, "4310 N Himes Ave, Tampa, FL 33614"
Lowry Park,"7525 N Blvd, Tampa, FL 33604"
Let-'Jice Lake Park, "*6920 E Fletcher Ave, Tampa, F1 33637"
Figure 100 Sample comma delimited CSV file as Point of Interest in Transportation tool
Please note: new POIs are not visible until the user refreshes the map (see refresh in Map Navigation
Toolbar).
To run a report with the added POIs, click the Submit button under the Transportation method section
(see Transportation Scenario Comparison Report). New POIs will be located at the bottom of the list.
76
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Power Mode
This section illustrates the step-by-step procedure to set EPA H20 to Power Mode by changing the
registry settings. Power mode allows the user to enable all the default QGIS functionality in EPA
H20. A few key features available by enabling the Power Mode include:
Use of all the QGIS tools for navigation, analysis, printing etc.
Installation of QGIS plug-ins and updates to existing plug-ins.
Customization of EPA H20 user interface layout.
Ability to develop a new EPA H2Q database, as explained in the Database Creation section.
o
o
To set EPA H20 to Power Mode:
1 Ensure EPA H20 is started at least once in the default mode before switching it to the
Power mode,
2. Open Command Prompt from Windows menu on the computer (Figure 101).
Foxit Reader
^ Snipping Tool
-a Notepad
a
TearnViewer 8
Command Prompt
= WordPad
Q ArcMap 10
Core FTP Lite
~ All P
rograms
|Seonr/i programs and files
Control Panel
Devices and Printers
Default Programs
Help and Support
Windows Security
0?
« £@
Figure 101 Command Prompt located in Windows menu
3. In a command prompt window, type REGEDIT without spaces before or after the command
and press enter (Figure 102).
11
-------
I Administrator: Command Prompt
icrosoft Windows [Uersion 6.1.7601]
Copyright 2089 Microsoft Corporation, fill rights reserved.
|C:\Users\ Username >REGEDIT
Figure 102 Command Prompt window with REG EDIT command entered
4. Within the Windows registry window that opens, navigate to file path:
"HKEY_CURRENT_USER(S)\Software\EPAH20\QGIS\PythonPlugins"
5. Right-click on the userMode option and select Modify... as shown in Figure 103.
¦gjjf Registry Editor
File Edit View Favorites Help
| !> . APN PIP
, AppDataLow
BitDefender
t> J, Crtrix
Classes
C> i. Clients
> Conduit
|~Si, Crjnstaller
. Creative Tech
Cyberlink
t> da-soft
Dnldstr_Aggregator
> Embarcadero
j i ^ EPAH20
j * x- QGIS
. gps
locale
. Plugins
i Projections
PythonPlugins
j t> -j. Qgis
j | & UI
C> ij- Windows
j i rwacri wrrm
-------
FirstLoad
fTools
.aJ» GdalTools
abj open layers
@plu ginjnstaller
project_manager
.*!*] projectFolderPatl-
projectPath
_a|»J reportFolderPath
_a!> sextante
sextante_taudem
userMode
_?_!>] valuetool
*!>] zona I stats
RE6.SZ
REG.SZ
REG SZ
Edit String
Value name:
userMode
Value data:
Power
OK
REG_SZ
REG SZ
false
true
true
23
¦s
'5
Cancel
true
true
Figure 104 Change the userMode Value data to Power
7. Restart the EPA H20 program. The Project Manager window will appear as the EPA H20
program starts up (Figure 105).
-- &
FiJ» Ed« vw« l«ytr Stamp ftfgim v»dor fUi-.tf Da1ab*-.c Help
HJODwfew
Lw* tt x
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(PA KZO Prcftcl V WlW
Choose a Module
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AAi-artofd User - Land Charge and Companion
•
Sw*ch moduie tn the urt by diebeg on this tcon- ;r.
| OK ' Canf«i
X Control rcndtimg order
Laywri IrQWMf
ft. Coo*dirot*
1 12919S4 - |Jf: *
Figure 105 EPA H20 program with access to QGIS menu functionality
Menus now include File, Edit, View; Layer, Raster, etc., and the user now has access to complete
QGIS functionality.
To change EPA H20 back to Basic/default mode, repeat steps in this section but changing the
userMode key's Value data from Power to Basic.
79
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ES Calculations Theory
This section describes the assumptions and theory underlying calculations of ES values assigned in
reports. This section is for technical users who want to better understand calculations the tool makes so
that they may adjust inputs to those calculations to make results better reflect their use case. This section
starts with the Tampa dataset and FLUCCS lookup table included with EPA H20. All descriptions,
references and values used in this section are from the Tampa database and FLUCCS lookup table. The
Database Creation section provides guidance on how to generate new databases and specifics on how to
update lookup tables to reflect new user inputs. The Edit ES Unit Values section describes how to change
the specific dollar value per unit of ES used in the calculations.
Flood Water Retention Value
The value of flood water retention ($/ft3) is calculated for each land use feature based on its infiltration
rate, or ability to hold water, measured as the runoff Curve Number (CN) (Figure 106). The lower a CN is,
the lower its runoff potential. For example, a land use type with a CN of 30 has a very high-water
retention rate and a low runoff potential, whereas a land use type with a CN of 100 has a very low water
retention rate and a high runoff potential.
Figure 106 Flood Water Retention calculation model in EPA H20
An area's Curve Number (CN) is determined based on the area's main SSURGO hydrologic group
("A", "B", "C" or "D") and the area's land use type. Both these feature characteristics are stored in the
land use layer and can be updated as described in the Create Soil Data Layer section of database
creation.
80
-------
The following equations show how the flood water retention volume ("FloodProt" field) and value ($/ft3)
are calculated from a feature's CN and area:
Water retention depth is calculated using the feature's CN:
Depth (mm) of water retained = 0.05 * ((25,400mm / CN) - 254mm)
Depth (m) of water retained = (0.05 * ((25,400mm / CN) - 254mm))) /1000
Total volume (m3) of water retained is calculated using this water retention depth (m) and the feature Area
(m2):
Volume (m3) of water retained = (0.05 * ((25,400mm / CN) - 254mm))) /1000 * Area m2
The Volume (m3) of water retained can be converted from m3 to ft3:
Volume (ft3) of water retained = Volume retained (m3) * 35.3147 m3/ft3
To estimate the value of this retention, the Volume (ft3) of water retained is multiplied by the replacement
cost, the cost to retain the same volume using stormwater infrastructure ("waterRet" field, where the
default is $2/ft3):
Total Value ($/ft3) = Volume retained (m3) * 35.3147 m3/ft3 * $2/ft3
This can be simplified to:
Total Value ($/ft3) = Volume retained (m3) * $70.629265
To calculate the value of an area using a different per unit Cost (e.g. $3/ft3) a percent-change multiplier is
added:
Total Value ($/ft3) = Volume retained (m3) * $70.629265 * ($3/ft3/$2/ft3)
The full equation would be:
Total Value ($/ft3) = (0.05 * ((25,400mm / CN) - 254mm))) /1000 * Area m2 * 70.629265 *
(Cost/2)
Usable Air Value
The usable air value ($/yr) is calculated for each land use feature based on the pollutants trees on
that feature will remove, estimated using a local removal rate and the average canopy cover for that
feature's land use type (Figure 107). The method used to determine the % Canopy Cover for each
feature is described in the Tree Canopy section of database creation. Although the "Canopy" field in
the lookup table is an integer value it represents the % Canopy Cover for each land use type.
81
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Figure 107 Air Pollution Removal calculation model in EPA H20
The removal rate of carbon monoxide (CO), ozone (O3), particulate matter (PM10), sulfur dioxide, and
nitrogen dioxide (NO2) were previously estimated for 55 metropolitan areas in the continental United
States by Nowak et al. (2006), as the dry deposition to tree canopies. Removal rates vary depending on
location; different estimated rates should be used when creating a database in a different location,
following the Air Quality section. The following equations use values for Tampa, FL. The following
equations are tedious, but only need to be solved once and then the lookup table can be used to directly
relate land use classes to their value ($/m2/yr) for removal of pollutants.
The estimated values for removal of the selected pollutants in Tampa FL, (Murray et al., 1994), were:
$ 959/ton Carbon Monoxide
$6752/ton Ozone
$1653/ton Sulfur Dioxide
$4508/ton Particulate Matter (PM10),
$6752/ton Nitrogen Dioxide
To get the value of Carbon Monoxide removal by a feature:
Value ($/yr) = 0.5 g/m2/yr * %Canopy * (1 ton/1000000 g) * Area m2 * 959 $/ton/yr
To get the value of Ozone removal by a feature:
Value ($/yr) = 5.8 g/m2/yr * %Canopy * (1 ton/1000000 g) * Area m2 * 6752 $/ton/yr
To get the value of Sulfur Dioxide removal by a feature:
Value ($/yr) = 2.4 g/m2/yr * %Canopy * (1 ton/1000000 g) * Area m2 * 1653 $/ton/yr
To get the value of Particulate Matter (PM10) removal by a feature:
Value ($/yr) = 4.5 g/m2/yr * %Canopy * (1 ton/1000000 g) * Area m2 * 4508 $/ton/yr
To get the value of Nitrogen Dioxide removal by a feature:
Value ($/yr) = 1.1 g/m2/yr * %Canopy * (1 ton/1000000 g) * Area m2 * 6752 $/ton/yr
82
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Values from the removal of each pollutant are combined to get the total value of pollutant removal by
a feature. The values for %Canopy and Area m2 are consistent for a feature across all the pollutants,
allowing the following simplification of the equation:
Total Value ($/yr) = 713121.5 * 1-6 (ton/g) * %Canopy * Area m2
The Total Value can also be calculated in ($/m2/yr):
Total Value ($/m2/yr) = 0.07131215 * %Canopy
The total removal rate and value for all the pollutants removed (e.g. 0.07131215) will change when
creating a database for a new location other than Tampa, FL. In the original land use layer, the Total
Value equation was solved for each feature and stored in the "US_Air_Dol" Field. The lookup table
now includes a "canopyVal" field with the air pollutant removal rate and value as $/m2/yr. This makes
calculation of "US_Air_Dol" more transparent and allows the user to update it more easily. See the
Air Quality section for more directions on updating field values.
Usable Water Value
The usable water value ($/yr) is calculated for each land use feature based on the nitrogen that feature
will removal, estimated using a denitrification coefficient (g N/m2/yr) for that feature's land use type (Figure
108).
Figure 108 Usable Water Value calculation model in EPA H20
Denitrification coefficients (g N/m2/yr) are determined from literature values. The literature values used in
Tampa, FL are shown in Table 2. The characteristics that influence denitrification rates for the same land
use class may vary from one location to another. For example, in Tampa FL, the rate from Morris 1991 for
freshwater marshes is reflective of intertidal fresh and salt water marshes, a marsh type not present in
many other regions.
83
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For more developed land use classes, buildings and impervious surfaces will prevent denitrification.
However, developed land use classes commonly include lawns which have high denitrification rates,
particularly where lawns are well irrigated and fertilized (Raciti et al. 2011). One denitrification coefficient
rate was determined for the portion of developed land classes characterized as lawn, 1.4 N/m2/yr (Raciti
et al. 2011). For each of the developed land use classes this coefficient is reduced proportionately to the
area of that land use class that is impervious. Methods to calculate and update the coefficients are
described in in the Denitrification section.
The costs for reducing nitrogen from point sources are estimated at $8.16 per pound ($18 / kg) of
nitrogen (Birch et al. 2011). The following equation shows how the usable water value ($/yr) is
estimated for a land use feature using the feature's denitrification rate (g N/m2/yr):
Usable Water Value ($/yr) = Denitrification (g N/m2/yr) * Area (m2) * 1kg/1000g * $ 18/kg
Table 2 Denitrification rates assigned to land use classifications
FLUCCS Land Use Description
Denitrification
(g N/m2/yr)
Average
Standard
Deviation
(g N/rn2/yr}
References
Cropland and Pastureland
0.72
0.62
(Espinoza 1997; Robertson et al. 1987;
Tsai 1989; Barton et al. 1999)
Row Crops
3.15
4.75
(Espinoza 1997; Pina-Ochoa and
Alvarez-Cobelas 2006; Tsai 1989)
Tree Crops
0.45
—
(Robertson et al. 1987)
Feeding Operations
0.06
—
(E. Cooter, personal communication)
Nurseries and Vineyards
0.45
—
(Robertson et al. 1987)
Other Open Lands (Rural)
0.82
0.69
(Tsai 1989; Barton et al. 1999)
Herbaceous
0.06
—
(Tsai 1989)
Shrub and Brushland
0.06
—
(Tsai 1989)
Mixed Rangeland
0.82
0.69
(Tsai 1989; Barton et al. 1999)
Upland Coniferous Forests
0.12
0.10
(Robertson et al. 1987; Barton et al. 1999)
Pine Flatwoods
0.12
0.10
(Robertson et al. 1987; Barton et al. 1999)
Longleaf Pine - Xeric Oak
0.12
0.10
(Robertson et al. 1987; Barton et al. 1999)
Upland Hardwood Forests
0.19
—
(Barton et al. 1999)
Hardwood Conifer Mixed
0.19
—
(Barton et al. 1999)
Tree Plantations
0.45
—
(Robertson et al. 1987)
Streams and Waterways
20.73
12.52
(Pina-Ochoa and Alvarez-Cobelas 2006;
Seitzinger et al. 2006)
84
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Lakes
12.16
11.47
(James et al. 2011; Pina-Ochoa and
Alvarez-Cobelas 2006; Seitzinger 1988;
Seitzinger et al. 2006)
Reservoirs
6.73
5.34
(James et al. 2011; Brenner et al. 2001;
Seitzinger 1988; Seitzinger et al. 2006)
Bays and Estuaries
5.66
3.64
(Gardner et al. 2006; Seitzinger 1988;
Yoon and Benner 1992)
Gulf of Mexico
6.89
6.16
(Fennel et al. 2009; Gihring et al. 2010)
Wetland Hardwood Forests
25.50
7.21
(Martin and Reddy 1997; Pinay et al.
2007; Seitzinger 1994; Walbridge and
Lockaby 1994)
Bay Swamps
25.50
—
(Seitzinger 1994)
Mangrove Swamps
0.69
0.65
(Corredor et al. 1999; Kristensen et al.
1998; Nedwell et al. 1994; Rivera-Monroy
and Twilley 1996; Sutula et al. 2001)
Stream and Lake Swamps
25.50
—
(Seitzinger 1994)
Wetland Coniferous Forests
25.50
—
(Seitzinger 1994)
Cypress
24.66
7.39
(Martin and Reddy 1997; Pinay et al.
2007; Lindau et al. 2007; Walbridge and
Lockaby 1994)
Wetland Forested Mixed
25.50
8.12
(Seitzinger 1994; Walbridge and Lockaby
1994; Dodla et al. 2008)
Vegetated Non-Forested
Wetlands
28.26
8.09
(Ensign et al. 2008; Seitzinger 1994;
Reddy et al. 1989; Martin and Reddy
1997, Pinay et al. 2007)
Freshwater Marshes
28.26
8.09
(Ensign et al. 2008; Martin and Reddy
1997; Pinay et al. 2007; Reddy et al. 1989;
Seitzinger 1994)
Saltwater Marshes
4.52
2.83
(Craft et al. 2009; Morris 1991; Seitzinger
et al. 2006)
Wet Prairies
25.48
8.87
(Ensign et al. 2008; Martin and Reddy
1997, Pinay et al. 2007)
Emergent Aquatic Vegetation
26.22
12.42
(Ensign et al. 2008; Martin and Reddy
1997)
Tidal Flats
10.00
5.67
(Cabrita and Brotas 2000; Ensign et al.
2008; Trimmer et al. 2000; Trimmer et al.
2006)
Intermittent Ponds
17.44
—
(Ensign et al. 2008)
Seagrass and Algae Beds
5.00
—
(Eyre and Ferguson 2002)
85
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Carbon Sequestration Value
The carbon sequestration value ($/yr) is calculated for each land use feature based on the carbon
that feature will sequester, estimated using a carbon fixation coefficient (g C/m2/yr) for that features
land use type (Figure 109). Carbon sequestration coefficients (g C/m2/yr) will differ significantly
depending on if the carbon is being fixed into biomass or buried.
Figure 109 Stable Climate Value calculation model in EPA H20
Carbon sequestration coefficients (g C/m2/yr) are determined from literature values. The literature values
used in Tampa, FL are shown in Table 3. Carbon fixed into biomass may later be removed and re-
released (e.g. crops fix carbon but are harvested for consumption) whereas carbon that is buried is more
likely to remain in the soil even if the vegetation is removed. The characteristics that influence carbon
sequestration rates for the same land use class may vary from one location to another. For example, in
Tampa FL, the rate from Chmura et al. 2003 for saltwater marshes is reflective of mangroves, a marsh
type not present in many other regions.
For more developed land use classes buildings and impervious surfaces will not contribute to carbon
sequestration. However, developed land use classes commonly include trees and lawns which have high
carbon sequestration rates, particularly where lawns are cut and mulched in place (Pouyat et al., 2009).
One carbon sequestration rate was determined for the portion of developed land classes characterized as
having trees, 28 g C/m2/yr (average carbon sequestration rate for all tree land use types), and for lawns,
100 g C/m2/yr (Table 4 summarizes the references used to calculate the Lawn Rate coefficient for
"Recreational", "Open Land", "Residential Low Density" and "Golf Courses" land use types). For each of
the developed land use classes these per unit area coefficients are reduced proportionately to the percent
of that area that is impervious. The tree rate is reduced proportional to the canopy cover for that land use
class, and the lawn rate is reduced proportional to the percent impervious for that land use class. The
carbon sequestration by trees or lawns are then combined to get the coefficient for that developed land
use class. Methods to calculate and update the coefficients are described in the Carbon Sequestration
section.
86
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The social costs for emitting carbon to, and inversely the value of sequestering the same amount from,
the atmosphere are estimated at $37 per ton of Carbon Dioxide (US Government, 2010). To convert this
to $ per ton of Carbon removed, the molecular mass of carbon dioxide (44.0095 g/mol) is compared to
that of carbon (12.0107 g/mol), for a factor of 3.66 times, or a cost of $135.42 per ton of Carbon. The
following equation shows how the stable climate value ($/yr) is estimated for a land use feature using the
feature's carbon fixation rate (g C/m2/yr):
Stable Climate Value ($/yr) = Carbon Fixation (g/m2/yr) * Area (m2) * 16 (ton/g) * $37/ton * 3.66
Stable Climate Value ($/yr) = Carbon Fixation (g/m2/yr) * Area (m2) * 1-6 (ton/g) * $135.42/ton
Table 3 Carbon sequestration rates assigned to non-Developed land use classifications
FLUCCS Land Use Description
Carbon
Sequestration
(g C/m2/yr)
Average
Standard
Deviation
(g C/m2/yr)
References
Open Land
611
229
(Ajtay et al. 1979; Milesi et al. 2005)
Cropland and Pastureland
423
—
(Ajtay et al. 1979)
Row Crops
959
758
(Ajtay et al. 1979; Schlesinger 1999)
Tree Crops
571
283
(Ajtay et al. 1979; Clark et al. 1999;
Montagnini and Nair2004)
Feeding Operations
423
—
(Ajtay et al. 1979)
Nurseries and Vineyards
571
283
(Ajtay et al. 1979; Clark et al. 1999;
Montagnini and Nair2004)
Other Open Lands
(Rural)
673
235
(Ajtay et al. 1979; Milesi et al. 2005)
Herbaceous
743
286
(Ajtay et al. 1979)
Shrub and Brushland
945
—
(Ajtay et al. 1979)
Mixed Rangeland
540
—
(Ajtay et al. 1979)
Upland Coniferous
Forest
698
32
(Ajtay et al. 1979; Kroeger 2008)
Pine Flatwoods
698
32
(Ajtay et al. 1979; Clark et al. 1999)
Longleaf Pine - Xeric
Oak
313
359
(Ajtay et al. 1979; Clark et al. 1999;
Kroeger 2008)
Upland Hardwood
Forests
590
113
(Ajtay et al. 1979; Clark et al. 1999;
Kroeger 2008)
Hardwood Conifer Mixed
660
85
(Ajtay et al. 1979; Kroeger
2008)
Tree Plantations
731
79
(Ajtay et al. 1979; Clark et al. 1999)
Streams
180
—
(Ajtay et al. 1979)
Lakes
397
141
(Carpenter et al. 1998; Carrick et al.
1993)
87
-------
Reservoirs
368
112
(Carpenter et al. 1998; Carrick et al.
1993; Knoll et al. 2003)
Bays and Estuaries
195
205
(Zieman et al. 1999)
Ocean and Gulf of Mexico
115
—
(De Vooys 1979)
Gulf of Mexico
115
—
(De Vooys 1979)
Wetland Hardwood
Forests
808
299
(Lugo et al. 1988)
Bay Swamps
808
299
(Lugo et al. 1988)
Mangrove Swamp
778
672
(Chmura et al. 2003; Duarte et al. 2005;
Eong 1993; Estevez and Mosura 1985;
Kroeger 2008)
Stream and Lake
Swamps
(Bottomland)
808
299
(Lugo et al. 1988)
Wetland Coniferous
Forests
298
181
(Kroeger 2008)
Cypress
241
256
(Clark et al. 1999; Kroeger 2008)
Wetland Forested
Mix
552
—
(Kroeger 2008)
Vegetated Non-Forested
Wetlands
142
—
(Kroeger 2008)
Freshwater Marshes
618
—
(Smith et al. 1983)
Saltwater Marshes
492
628
(Chmura et al. 2003; Choi and Wang
2004; Duarte et al. 2005; Lewis III and
Estevez 1988; Smith et al. 1983)
Wet Prairies
142
—
(Kroeger 2008)
Emergent Aquatic Vegetation
142
—
(Kroeger 2008)
Tidal Flats
195
205
(Zieman et al. 1999)
Intermittent Ponds
142
—
(Kroeger 2008)
Seagrass
814
363
(Duarte et al. 2005; Lewis III and Estevez
1988)
Table 4 Carbon sequestration rates used to calculate the lawn rate coefficient
FLUCCS Land Use Description
Carbon
Sequestration
(g C/pixel)
Average
Standard
Deviation
(g C/m2/yr)
References
Recreational
18
—
(Pouyat et al. 2009)
Open Land
3
—
(Pouyat et al. 2010)
88
-------
Residential Low Density
382
—
(Pouyat et al. 2009, Raciti et al. 2011)
Golf Courses
95
—
(Qian and Follett 2002)
89
-------
The default database provided with EPA H20 (TampaBay.sqlite) only includes data for the Tampa Bay
estuary and watershed. However, .sqlite databases compatible with the EPA H20 tool can be created for
other areas of interest. This section illustrates the step-by-step procedure for creating .sqlite databases
for use in EPA H20's Advanced Module.
Please note:
1. Database creation requires EPA H20 to be in Power Mode.
2. EPA H20 Basic Module can only be used for the Tampa Bay region unless data layers are
updated for other areas; scenario comparisons in other regions must be done using the EPA H20
Advanced Module.
New .sqlite databases can be created for any area in the contiguous United States using default data
sources (Table 5). Depending on the area of the new database, an alternative data source may be
available. In the Tampa Bay area, most of the default data sources were used for the database (Table
6). One exception was the land use dataset used, the Florida Land Use Cover Classification System
(FLUCCS), a higher resolution dataset only available within the State of Florida. The lookup table
used to assign Ecosystem Service coefficients is based on the land use layer classification, meaning
the lookup table included in the Tampa Bay database will not work for other land use classifications
such as the default NLCD. A new national lookup table for NLCD is included in Appendix A:
Supplemental NLCD Lookup Table. The database creation section uses this lookup table and the
default NLCD dataset. Appendix D: Extracting and Updating the Original FLUCCS Lookup Table
describes how the Tampa Bay database lookup table can be updated to create databases using
FLUCCS. Both lookup tables may be updated with more regionally specific values. The NLCD
Percent Tree Canopy data do not need to be downloaded if the lookup table Canopy Cover values are
not being updating.
Table 5 Default Data Sources with national scope for new user databases
Dataset
Download Instructions
Download Link
USGS Watershed
Boundaries: HUC_8 .shp
Download HUC Boundaries
httDs://viewer,nationalmaD.aov/basic/?b
asemap=bi &cat©aorv=nhd&titf©=NHD
%20Vie
National Land Cover
Database (NLCD) 2011
Download Land Use Data
httDs://www,mrlc,aov/data/nlcd-2011 -
land-cover-conus-0
SSURGO: Soil Classification
Download Soil Data
httDs://websoilsurvev.sc.eaov.usda.aov/
App/WebSoilSurvev.aspx
NLCD 2011 Percent Tree
Canopy
Download Tree Canopy
Data
https://www.mrlc.aov/data/nlcd-2011 -
usfs-tree-canoov-cover-conus
TIGER/Line Roads
Download TIGER/Line data
https://www.census.aov/cai-
bin/aeo/shapefiles/index.php
Maximum Speed
Download Max Speed data
Must be obtained by user on a state or local
scale, or be created by user.
NHD+_V2 Hydrography
(Catchments, Basins and
Flow directions)
Download NHDPIus Data
https://nhdpIus.com/NHDPIus/NHDPIus
V2 data.php
90
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Original EPA H20 database
Included in Installing EPA
H20
User copy of TampaBay.sqlite
saved in any directory EXCEPT
'C:/Users//.qgis/
0.0.3/data/database/'
Setting Up a Project
Directory
Table 6 Data Sources used to create original TampaBay.sqlite database
Dataset
Download Link
File Names
USGS Watershed
Boundaries: HUC_8
.shp
Iiucs00m020 nt00013.tar.gz\o obtain
WBDHU8.shp
State of Florida
FLUCCS Land Use
httos i//www, swfwmd, state ,fl,us/re
sources/data-maps
2006_Land_Use_Land_Cover.zip
SSURGO: Soil
Classification
httDsi//websoilsurvev,sc,eaov,usd
a, a ov/Aoo/We bSo i IS u rve v. as dx
wss_SSA_FL049_soildb_FL_2003_[201
7-10-05J.zip (Hardee county)
wss_SSA_FL057_soildb_FL_2003_[201
7-10-04J.zip (Hillsborough county)
wss_SSA_FL081_soildb_FL_2003_[201
7-10-02j.zip (Manatee county)
wss_SSA_FL101_soildb_FL_2003_[201
7-10-02J.zip (Pasco county)
wss_SSA_FL103_soildb_FL_2003_[201
7-10-02].zip (Pinellas county)
wss_SSA_FL105_soildb_FL_2003_[201
7-10-06J.zip (Polk county)
TIGER/Line Roads
https]//www, census, qov/cqi-
biii/qeo/shapefiles2013/main
tl_2013_12049_roads.zip (Hardee)
tl_2013_12057_roads.zip (Hillsborough)
tl_2013_ 12081_roads.zip (Manatee)
tl_2013_12101_roads.zip (Pasco)
tl 2013 12103 roads.zip (Pinellas)
tl_2013_12105_roads.zip (Polk)
Maximum Speed
https ://www, a rcq is, co m/h o me/it e
m,html?id=4a81fl 7ab4784202ae
maxspeed.zip
10d 7d 5f b3 bf9d e#o ve rvi ew
NHD+_V2
Hydrography
(Catchments, Basins
and Flow directions)
https://nhdpIus.com/NHDPIus/NH
DPIusV2 data.php
NHDPIusV21 S/4 03S NHDPIusAttribute
s 02.7z
NHDPIusV21 S/4 03S NHDPIusCatchm
ent 01.7z
NHDPIus V21_ SA_ 03S_ NHDPIusBurn Co
mponents 02.7z
NHDPIusV21 S/4 03S NHDSnapshot 03
,7z
91
-------
Setting Up a Project Directory
During installation EPA H20 creates a default database for the Tampa Bay area (TampaBay.sqlite).
A new database must be created to use EPA H20 for a different area. The following steps show the
procedure to set up a directory for the new database; hereafter referred to as the User Folder.
On a Windows machine, by default QGIS data are stored in a ".qgis" folder found in the current user's
home directory .
1. Using File Explorer il, COPY the directory 'C:\Users\\.qgis\0.0.3Y to another
location in the user directory, e.g.('C:\Users\\My Documents\0.0.3\') (Figure 110).
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Figure 110 Create a copy of the 0.0.3 folder in File Explorer
2. Make sure the folder contents were copied properly, including the "data" foider, "projects" folder,
and the TampaBay.sqlite database.
3. Right-click on the new copy of the EPA H20 database (TampaBay.sqlite), choose Rename,
and rename the new database (for example, UserDatabase.sqlite in Figure 110). The
database MUST BE RENAMED; the Qspatialite plug-in cannot connect to two different
databases with the same file name regardless of their file paths.
Set Up ArcGIS Map Document
1. Open ArcMap from the Start menu > All Programs > ArcGIS > ArcMap.
2. Right-click on the Layers icon in the Table of Contents. From the dropdown list, choose the
Properties option (Figure 112).
92
-------
Table Of Contents
:: 3 O® III
P x
Add Data...
New Group Layer
^ > New Bssemsp Layer
® Copy
Tum All Layers On
Select All Layers
S C ellipse All Layers
Reference Scale
Advanced Drawing Option;.,,
Labeling
Activate
Cf Properties...
Figure 112 Layer Properties location in Arc Map
Data Frame Properties
Feature Cache Annotation Groups Extent Indicators Frame Size and Position
General Data Frame Coordinate System Illumination Grids
I S> »¦ I ® ' A
2 of 6040 items shown
B |& Projected Coordinate Systems
El IB World
13 £3 Layers
WGS1984 Web Mercator (auxiliary sphere)
Current coordinate system:
WGS_1984_Web_Mercator_Auxiliary_Sphere
WKID: 3857 Authority: EPSG
Projection: Mercator_Auxiliary_Sphere
False_Easting: 0.0
False_Northing: 0.0
Central_Meridian: 0.0
Standard_Parallel_l: 0.0
Auxiliary_Sphere_Type: 0.0
Linear Unit: Meter (1.0)
Transformations...
OK j Caned ] Apply
Figure 111 Set Coordinate System for Data Frame
3.
4.
5.
The Data Frame Properties window will open (Figure 111). Under the Coordinate System tab,
choose Web Mercator Auxiliary Sphere. It is located under Projected Coordinate System > World,
or can be located by typing 3857 in the search field and hitting enter, as shown in Figure 111.
Once the coordinate system is selected, it will appear in blue. Click OK.
It is suggested that the user save their created map document, in .mxd format (File > Save As...).
Set Up QGIS Map Document
1. Open EPA H20 in Power Mode.
2. In the Choose a Module window, click OK (Figure 113).
93
-------
^ EPA H20 Project Manager ? X
Choose a Module
• Basic User - Green Report
Advanced User - Land Use Change and Comparison
Switch module in the future by clicking on this icon- [§]
OK Cancel
Figure 113 EPA H20 Choose a Module window
In the Select Project window, select Open existing project or Create new project. For first time
Power Mode users, choose Create new project (Figure 114).
r
0 EPA H20 Project Manager
f |-£3-|
Select Project
Open existing project
• Create new project
Exit EPAH20
OK
Cancel
Figure 114 EPA H20 Select Project window
In the Project Configuration window (Figure 115), confirm that the Source Database Name is
referencing the original TampaBay.sqlite.
a. If the source database is not the original TampaBay.sqlite, click the Select button, and
navigate to the original "0.0,3" folder,
in the Name Your Project Database box, enter the preferred project name (e.g. Demo), and
click OK.
-------
0 EPA H20 Project Manager ? X
Project Configuration
Select the Top Level Folder of EPA Dataset Select
Data Folder Path: C:/Users/mjackson/.qgis/0.0.3
Source Database Name: TampaBay.sqlite
Hame Your Project Database | Demo|
OK Cancel
Figure 115 Project Configuration window
6. In the Select Area of Interest window, click Cancel.
7. From the Settings dropdown (Figure 116) open the Project Properties window (Main Menu >
Settings > Project Properties).
£ EPAH20- UseCaseTwo
File Edit View Layer
Settings
Plugins Vector Raster Database I
El Project Properties... Ctrl+Shift+P
ffl d © 0S
\ Custom CRS...
Style Manager...
Compare
Layers
^ Configure shortcuts...
Figure 116 Location of Project Properties in EPA H20
8. In the Project Properties window (Figure 117):
a. Click the Coordinate Reference System (CRS) tab and check the box labeled Enable 'on
the fly' CRS transformation.
b. In the Filter text box, type 3857. Under the Coordinate reference systems of the world
section, select l/l/GS 84/Pseudo Mercator.
c. Click OK to apply these changes and close the Project Properties window.
95
-------
Project Properties ? X
General ¦ Coordinate Reference System (CRS)
* Enable 'on the fly' CRS transformation
: Fitter 3857
Recently used coordinate reference systems
; Coordinate Reference System
WGS W / Pseudo Mercator
Identifiable layers OWS Server
"Authority ID
EPS63857
Coordinate reference systems of the world
. Coordinate Reference System
-1 Mercator
14 I m
Hide deprecated CRSs
Authority ID
+proj=merc *0=6378137 +b=6378137 +lat_ts=0,0 +lon_0=0,0 +x_0=0,0 +y_0=0 +k=1.0 *units=m
-Hiadgnds=®null +no_defs
OK Cancel Apply
Figure 117 Set the Coordinate Reference System in EPA H20
Help
It is suggested that the user save their created map document, in .qgs format (File > Save
Project As).
-------
Create HUC Watershed Boundaries
A Watershed defines the area upstream of a point (e.g. an outflow point) where flows of water will be
directed to that point. Hydrologic Unit Codes (HLJC) are unique codes assigned watershed boundaries
that vary in length (2-14 digits) depending of the scale of the watershed. At the broad scale, each
region of the United States has a unique 2-digit Hydrologic Unit (Figure 118). For example, Tampa Bay
is within the HUC 03 South-Atlantic Gulf region. At broader scales (2-digit), HUC watersheds match
the NHDPIus catchments, but at finer scale (14-digit) there may be differences. HUC boundaries are
often used to define the Area of Interest (AOI) for a new EPA H2G database because these
boundaries are similar to the NHDPIus catchments used to define upstream areas.
Download HUC Boundaries
This section illustrates the step-by-step procedure to download the HUC watershed boundary
dataset from the USGS Website by HU-2 region.
1. Navigate to the following link, to open the USGS National Map website (Figure 119):
https://viewer.nationalmap.qov/basic/?basemap=b1&cateqor¥=nhd&title=NHD%20Vie
97
-------
^ The National Map
Start Over Custom Views ^ <§" S
Advanced Search Options
yj Hydrography (NHDPIus HR, NHD, WBD)
Product Search Filter
~ All Subcategories
NHDPIus High Resolution (NHDPIus HR) Beta
Show Availability (Limited during Production)
_ National Hydrography Dataset (NHD)
Show Preview
Data Extent Zoom to
HU-2 Rei? map-
HU-4 Subregion
HU-8 Subbasin
O State
File Format
G Shapefile
FileGDB 10.1
Availability legend
Preview Leoend
NHD
WBD
3, select Data Extent, click 01
Figure 119 USGS National Map download website
2. Click-and-drag on the National Map to pan and use the Zoom in ' icon to zoom in to the user's
AOI (e.g. Tampa Bay).
3. In the Product Search Filter section, check the Watershed Boundary Dataset (WBD) option
(Figure 120).
Datasets
Products
Advanced Search Options
Data
Hydrography (NHDPIus HR, NHD. WBD)
Product Search Filter
~ All Subcategories
~ NHDPIus High Resolution (NHDPIus HR) E
Show Availability (Limiied during Production)
D National Hydrography Dataset (NHD)
Show Preview
Watershed Boundary Dataset (WBD)
Show Preview
Data Extent
G HU-2 Region
Q National
Availability legend
Preview Legend
NHD
WBD
Find Products
*
vt
Description
+ Use Map
Map Indices
Address/Place
Box/Point • Current Extent Coordinates Located Point Polygon
1 Degree 15 Minute 7.5 Minute All
Search location
mi
Clearwater' J
m" ''
geKcher Ganai
I . 71V-
ifKP"S^\\ J . Pc'r, Saint
'Lucie
Figure 120 Search for all Watershed Boundary Datasets available for the Tampa Bay area
4. Click the Find Products icon, located above the Product Search Filter box.
5. The available USGS Watershed Boundary Datasets for the user's AOI will replace the search
filters (Figure 121). The product name will include the 2-digit Hydrologic Unit (03 for Tampa).
6. Locate the USGS Watershed Boundary Dataset (WBD) file in the Product list with Format:
Shapefile. It is strongly suggested that the user download the shapefile, and not the file
geodatabase. In the Actions column, click the corresponding Download link.
98
f Use Map
Map Indices
1 Address/Place
-------
Preview
Product
Actions
Actions for all displayed products: Show Footprints /Show Thumbnails
<
USGS Watershed Boundary Dalaset (WBD) for 2-
digit Hydrologic Unit- 03 (published 20181001)
Published Date: 2018-10-01
Metadata Updated: 2018-10-03
Fonnat: FileGDB 10 1 {), Extent: MU-2 Region
USGS Watershed Boundary Dataset (WBD) for 2-
digit Hydrologic Unit- 03 (published 20181001)
Pu bfish ed Date: 2018-10-01
Metadata Updated: 2018-10-03
Format: Shapefile (), Extent: HU-2 Region
Footprint
Zoom To
Info/Metadata
Download
Footprint
Zoom To
Info/Metadata
Download
Cart
"W +
Page
"W +
-
"W +
Figure 121 Download the USGS Watershed Boundary Shapefile for Hydrologic Unit 03
7. Save the zip file to the computer and unzip the contents to a known location.
The next section illustrates the creation of EPA H20 compatible watershed boundary data from the
unzipped download file, either using Esri ArcGIS software (Using ArcGIS) or QGIS (Using QGIS).
Using ArcGIS
This section illustrates the creation of EPA H20 compatible HUC watershed boundary data using
Esri ArcGIS software (About GIS).
1. Download and unzip the HUC Watershed Boundary data, as shown in the Download HUC
Boundaries section.
2. Open your existing ArcGIS map document file (.mxd), or create one following the steps
outlined in Set Up ArcGIS Map Document.
3. Use the Add Data + " icon to navigate to the unzipped HUC watershed boundary dataset.
Select the WBDHUS.shp file and add the layer to the Table of Contents of the map document.
4. Use the Select Features
icon to select watersheds that overlap the area of interest:
a. Watersheds are selected either by clicking and dragging a rectangle around them, or by
clicking on each while holding the Shift key.
b. if an incorrect watershed is selected, clear the current selection by clicking the Clear
Selection icon.
Selected features are indicated by a cyan blue border. For example, watersheds surrounding Tampa Bay
are shown selected in Figure 122.
99
-------
Figure 122 Watersheds selected for the Tampa Bay area in ArcMap
5. Once the watersheds of interest are selected, right-click on the WBDHU8 layer in the Table of
Contents, and choose Data > Export Data, as shown in Figure 123.
Table Of Contents
P5l 3 o is
Q Layers
a 0
~
Copy
Remove
PI Open Attribute Table
Joins and Relates
~
^ Zoom To Layer
J Zoom To Make Visible
Visible Scale Range
~
Use Symbol Levels
Selection
~
Label Features
Edit Features
~
Convert Labels to Annotation...
Convert Features to Graphics-
Convert Symbology to Representation...
o
£>
Properties-
Save As Layer File-
Create Layer Package...
Repair Data S
Ky Export Data-
Export To CAD...
View Item Descrip
Export Data
Save this layer's data as a shapefile
or geodatabase feature class
Figure 123 Export the selected watershed data using the Export Data button
6. In the Export Data window (Figure 124):
a. In the Export dropdown list, select Selected features.
100
-------
b. Under Use the same coordinate system as, toggle the data frame option.
c. In the Output feature class text box, type the desired shapefile name (e.g. HUC_Tampa).
d. Click OK.
Export Data
X
Export: Selected features
Use the same coordinate system as:
O this layer's source data
® the data frame
the feature dataset you export the data into
(only applies if you export to a feature dataset in a geodatabase)
Output feature class:
C:\Users \rnjackson\.qgis\0.0.3\Tampa_H20\D2_Tampa\HUC_Tamp t—1jj
OK
Cancel
Figure 124 Export Data window
7. A window may appear that asks: "Do you want to add the export data to the map as a layer?"
(Figure 125). If so, click Yes.
ArcMap
| Do you want to add the exported data to the map as a layer?
Yes
No
Figure 125 ArcMap window, which will add the newly exported data to the Table of Contents
The Importing Layers into QGIS section details how to upload the HUC watershed boundary into the
user database in QGIS. Database creation is continued in the Create Land Use Data Layer section.
Using QGIS
This section illustrates the creation of EPA H20 compatible HUC watershed boundary data using
QGIS software (About QGIS).
1. Download and unzip the HUC Watershed Boundary data, as shown in the Download HUC
Boundaries section.
2. Open your existing QGIS map document file (.qgs), or create one following the steps outlined
in Set Up QGIS Map Document.
3. From the Layer menu (Figure 126) open the Add Vector Layer window (Main Menu > Layer >
Add Vector Layer).
101
-------
£ EPAH20
File Edit View
Layer
Settings Plugins Vector Raster Database
New ~
BlI & E
Embed Layers and Groups...
Layers
18*+ Add Vector Layer... Ctrl+Shrft+V
* Add Raster Layer.,. Ctrl+Shift+R
% Add SpatiaLite Layer... Ctrl+Shift+L
H Add Delimited Text Layer
Figure 126 Location of the Add Vector Layer tool in EPA H20
4. In the Add vector layer window (Figure 127), click Browse to locate and select the unzipped
HUC watershed boundaries file (e.g. WBDHU8,shp), then click Open.
Q Add vector layer ? X
Source type
• File Directory Database Protocol
Encoding System T
Source
Dataset .3/Tampa_H20/D2_Tampa/HUC/Shape/WBDHU8.shp
Browse
Open Cancel Help
Figure 127 Add vector layer window in EPA H20
5. Use the Zoom In icon to zoom to the area of interest.
6. From the View menu, activate the Select Single Feature tool (Main Menu > View > Select
Single Feature, Figure 128).
7. While holding the Ctrl key, select the specific watersheds in the area of interest. Alternatively,
other selection tools may be used to make the selection, such as selecting watersheds by
drawing a rectangle around them using the Select Features by Rectangle tool.
. EPAH20
File Edit
View
Layer Settings Plugins Vector Raster Database Help H20 Toolbox
Pan Map
Pan Map to Selection
jS Zoom In Ctrl++
Zoom Out Ctrl+-
K] £
El X W
T ~
Select ~
Select Single Feature
Identify Features Ctrl+Shift+I
Select Features by Rectangle
Figure 128 Select Single Feature in EPA H20
102
-------
Selected watersheds will be highlighted in yellow; Figure 129 shows watersheds selected in
the Tampa Bay area.
Figure 129 Selected watersheds in the Tampa Bay area
8. With the area-specific watersheds selected, use the Layer menu (Figure 130) to open the
Save Selection as Vector File window (Main Menu > Layer > Save Selection as Vector
File...).
& EPAH20
File Edit View
Layer
Settings Plugins Vector Raster Database
New ~
S] & c
Embed Layers arid Groups...
''•q Add Vector Layer... Ctrl+Shift+V
Layers
~ ~ r HUC Ta
r% Add Raster Layer,.. Ctrl+Shift+R
¦
0 * WBDHU!
% Add SpatiaLite Layer... Ctrl+Shift+L
^3
~
~ Add Delimited Text Layer
Copy style
'S Paste style
0 Open Attribute Table
Save Edits
/ Toggle Editing
Save As...
Save Selection as Vector File-
Figure 130 Save the selected watersheds as a vector file in EPA H20
9. in the Save vector layer as... window (Figure 131):
a. in the Format dropdown list, select ESRI Shapefile.
103
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b. In the Save as box, browse to or type the desired output shapefile name and file path
(e.g. HUC_Tampa_QGIS.shp).
c. In the CRS dropdown list, choose Layer CRS; NAD83 should show as the CRS
automatically.
d. Check Add saved file to map.
e. Do not check Skip attribute creation,
f. Click OK
^ Save vector layer as... ? X
Format ESRI Shapefile
-
Save as ?0/D2_Tampa/HUC_Tampa_QGIS.shp
Browse
Encoding System
-
Layer CRS
-
CRS
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Browse
OGR creation options
Data source
Layer
Skip attribute creation
X Add saved file to map
OK Cancel Help
Figure 131 Save vector layer as... window in EPA H20
This user-specific watershed shapefile (with NAD83 projection) will be used to clip the land use data in
the Create Land Use Data Layer section. The user must create a second copy of the watershed
shapefile to upload into the user database, with WGS84/Pseudo Mercator projection.
10. Right-click on the HUC watershed boundary layer (e.g. HUC_Tampa_QGiS) in the Layers panel
and choose Save As... (Figure 132).
Layers
S X
= ~ " HUC Tan
¦
Zoom to Layer Extern
x WBDHU8
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a Remove
Set Layer CRS
Set Project CRS from Layer
31 Open Attribute Table
/ Toggle Editing
Save As...
Figure 132 Location of the Save As... tool in EPA H20
104
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11. In the Save vector layer as... window (Figure 133):
a. From the Format dropdown list, select ESRI Shapefile.
b. In the Save as box, browse to or type the preferred file path and shapefile name (e.g.
HUC_ Tampa_reproj. shp).
c. In the CRS dropdown list, choose Selected CRS, and click Browse.
d. In the Coordinate Reference System Selector window that opens (Figure 134), type 3857
in the Filter box, choose l/l/GS 84/Pseudo Mercator and click OK.
e. Be sure to check Add saved file to map. Do not check Skip attribute creation.
f. Click OK.
Save vector layer as,., ? X
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Figure 133 Save vector idyer qs. .. window in EPA H20
105
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Figure 134 Select WGS 84/Pseudo Mercator as the Coordinate Reference System
The Importing Layers into QGIS section details how to upload this re-projected HUC watershed
boundary into the Qspatialite user database in QGIS. Database creation is continued in the Create
Land Use Data Layer section, where the other HUC watershed boundary (with NAD83 projection) will
be used to clip the land use data.
106
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Create Land Use Data Layer
The land use data layer is essential to several H20 functions. Several attributes in the land use layer
are characterized using other datasets in addition to the initial land cover classification. For example,
the EPA H20 tool computes the dollar value of flood protection based on Curve Number (CN). The
land use layer is where Curve Number (CN) values, characterized using land cover and soil type, are
attributed.
Land cover data can be obtained from a variety of sources, at a variety of resolutions or times, and
may be based on a variety of classification systems. More detailed land cover datasets are often
available at more limited scales and offer more value when differentiating between areas in EPA
H20, but more detailed land cover data is rarely available across all areas.
The Tampa database that comes with the EPA H20 tool uses the Florida Land Use Cover
Classification System (FLUCCS) as the land cover layer. Although this land cover dataset uses a
very detailed land use classification system, covering more classes than the National Land Cover
Dataset (NLCD), it is only available for Florida. Since the National Land Cover Dataset (NLCD)
covers the entire United States, and is updated at a regular interval, it is recommended for areas of
interest where other, more detailed land use data is not available. For this reason, this section will
describe how to download the National Land Cover Dataset (NLCD) and process it to prepare the
land use data layer.
Either Esri ArcMap software or QGIS can be used to prepare the land cover data. The procedure for
both software applications is explained in this section.
Download Land Use Data
This section illustrates the step-by-step procedure for downloading NLCD 2011 Land Cover datasets
from the MRLC database.
1. Navigate to https://www.mrlc.gov/viewer/ as shown in Figure 135.
MR LC
Celebrating 20+ years of Partnership
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Figure 135 MRLC website, download NLCD Land Cover by AO!
107
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2. Click-and-drag on the National Map to pan and use the Zoom in icon to zoom in to the user's AOI
(e.g. Tampa Bay).
3. in the Contents section, under the NLCD Land Cover dropdown list, check the 2011 CONUS Land
Cover option (or the preferred display year).
4. From the map viewer toolbar, click the Open Data Download Tool
bounding box around the user's AOI (Figure 136).
©
icon and click to draw a
All NLCD Land Cover 2011 CONUS Land Cover
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Figure 136 MRLC viewer with bounding box drawn around Tampa Bay AOI
5. Under the Data Download dropdown list, check the Land Cover option and toggle All Land Cover
Years (Figure 137).
Data Download Q
Select Categories:
~ Science Products
Tree Canopy
Vj Land Cover
• All Land Cover Years
2016 Land Cover ONLY
~ Impervious
Latitude (dd):
27.42081 28.46522
Longitude (dd):
-83.05887 -81.82638
user@epa.gov
Figure 137 Data Download dropdown list
108
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6. In the Email text box, enter the user's email address (e.g. user@epa.gov), then click Download.
7. A notification will appear indicating the download request has been sent. Click OK (Figure 138).
www.mrlc.gov says
Your download request has successfully been sent and will be
processed for you within 24 hours. You will receive an e-mail with
instructions on retrieving your data. Thank you.
OK
Figure 138 MRLC request notification
8. The download link will be emailed to the user by the USGS server. Click the first link in the email
to download the NLCD zip file.
9. Save the zip file to the computer and unzip the contents to a known location.
The next section illustrates the creation of EPA H20 compatible land use data from the unzipped
download file, using either Esri ArcGIS software (Using ArcGIS) or QGIS (Using QGIS).
Using ArcGIS
This section illustrates the creation of EPA H20 compatible land use data using Esri ArcGIS
software.
1. Download and unzip the NLCD datasets, as shown in the Download Land Use Data section,
and locate the appropriate HUC boundaries for the study area, as shown in the Create HUC
Watershed Boundaries section.
2. Open your existing ArcGIS map document file (.mxd), or create one following the steps
outlined in Set Up ArcGIS Map Document.
3. Use the Add Data T icon to navigate to the NLCD 2011 .tifdataset (or most recent year) and
add the layer to the Table of Contents of the map document.
4. If using a new map document, the shapefile created in the Create HUC Watershed Boundaries
section must be added in the same way.
The watershed layer should represent a smaller, more focused area, whereas the new land use layer will
be a larger bounding box around the AOI (Figure 139).
109
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Figure 139 NLCD 2011 dataset, displayed with Tampa Bay watershed shapefile
5. Click on the Toolbox % icon to open ArcToolbox.
6. From the ArcToolbox window, navigate to and open the Clip tool (ArcToolbox > Data
Management Tools > Raster > Raster Processing > Clip, Figure 140).
ArcToolbox
X
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Figure 140 Location of the Clip tool in ArcToolbox
7. In the Clip tool window (Figure 141):
a. In the Input Raster text box, select the user-specific NLCD dataset (e.g.
NLCD_2011_Land_Cover_L48_20190424_umtxeyAuXzMnsc7vNE8j.tiff).
110
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b. In the Output Extent text box, select the HUC watershed boundary shapefile (e.g.
HUC_Tampa).
c. Check the Use Input Features for Clipping Geometry option.
d. In the Output Raster Dataset text box, browse to or type the desired file name (e.g.
NLCD_Tampa) and file path.
e. Click OK.
"\ Clip
Input Raster
| NLCD.2011 _Land_Cover_L48_20190424_umtxeyAuXzMnsc7vNE3j.tiff
Output Extent (optional)
| HUC_Tampa
Rectangle
"3 £3
"3 £5
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OK
Cancel
Environments... Show Help >>
Figure 141 Clip tool window in ArcMap
8. The output is a raster dataset, which needs to be converted to a polygon layer for future
processing.
9. From the ArcToolbox window, navigate to and open the Raster to Polygon tool (ArcToolbox >
Conversion Tools > From Raster > Raster to Polygon).
10. In the Raster to Polygon window (Figure 142):
a. In the Input Raster text, box, select the clipped NLCD raster dataset (e.g. NLCD_Tampa).
b. In the Field text, box, choose VALUE.
c. In the Output polygon features text box, name the output (e.g. NLCD_Tampa_poly.shp) and
file path.
d. Check the Simplify polygons option if not already checked.
e. Click OK.
Ill
-------
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Figure 143 Location of the Project tool in ArcToolbox
12. In the Project tool window (Figure 144):
a. in the Input Dataset or Feature Class box, select the clipped NLCD polygon (e.g.
NLCD_ Tampa_poty).
112
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b. The Input Coordinate System automatically lists the input dataset coordinate system (e.g.
NAD_1983_Albers).
c. In the Output Dataset or Feature Class text box, browse to or type the desired file name (e.g.
NLCD_Tampa_poly_reproj.shp) and file path.
d. Click the Spatial Reference icon to set the Output Coordinate System to
WGS_1984_Web_Mercator_Auxiliary_Sphere, located under the World folder in Projected
Coordinate Systems. Alternatively, search for it by typing 3857 into the search box.
e. A Geographic Transformation is required to reproject the land use dataset. In the dropdown
list, choose WGS_1984_(ITRF00)_To_NAD_1983, if not already listed in the box.
f. If the wrong Geographic Transformation is listed, click on the name, and click the X button to
remove it.
g. Click OK.
Project
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Figure 144 Project tool window in ArcMap
This re-projected output is used to complete a spatial join with the soil dataset in the section.
Database creation is continued in the Create Land Use Comparison Data section.
Using QGIS
This section illustrates the creation of EPA H20 compatible land use data using QGIS software.
1. Download and unzip the NLCD land use data, as shown in the Download Land Use Data
section.
113
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2. Open your existing QGIS map document file (.qgs), or create one following the steps outlined
in Set Up QGIS Map Document.
3. In the Add vector layer window (example shown in Figure 127), click Browse to locate and
select the previously created HUC watershed boundary shapefile, then click Open.
a. Ensure this HUC watershed boundary shapefile has the correct projection of NAD83 and is
not the shapefile that was re-projected to input into the Qspatialite user database.
4. From the Layer menu, open the Add Raster Layer window (Main Menu > Layer > Add Raster
Layer..., Figure 145).
£ EPAH20
File Edit View
Layer
Settings Plugins Vector Raster Database
New ~
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Embed Layers and Groups...
Add Vector Layer... Ctrl+Shift+V
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~ 1*1 C=MHUC Ta
L; Add Raster Layer... Ctrl+Shift+R
¦
|[!?j Add SpatiaLite Layer... Ctrl+Shift+L
Figure 145 Location of the Add Raster Layer... tool in EPA H20
a. Navigate to the NLCD 2011 land use layer (or most recent year) previously downloaded in
Download Land Use Data section (e.g.
NLCD_2011_Land_Cover_L48_20190424_umtxeyAuXzMnsc7vNE8j.tiff).
b. Choose the file with the ".tif extension.
c. Click Open.
5. The NLCD 2011 layer needs to be re-projected from the "Custom" projection to l/l/GS 84/Pseudo
Mercator. From the Raster menu, open the Reproject tool (Main Menu > Raster > Projections >
Warp (Reproject), Figure 146J.
Raster Database Help Transportation H20 Toolbox!
*£j| Raster calculator...
Interpolation ~
/ Terrain analysis ~
Zonal statistics ~
Projections ~
tif Warp (Reproject)
| Conversion ~
ta Assign projection
Figure 146 Location of the Warp (Reproject) tool in EPA H20
6. In the Warp (Reproject) window (Figure 148):
a. In the Input file dropdown list, select the user-specific NLCD layer (e.g.
NLCD_2011_Land_Cover_L48_20190424_umtxeyAuXzMnsc7vNE8j.tiff).
b. Click Select next to the Output file text box to select a file path and name for the output (e.g.
NLCD_FL_reproj.tif). Be sure to name the output with a .tif extension.
c. Check the Source SRS box, and click Select to open the Select the source SRS window.
d. In the Select the source SRS window (Figure 147):
i. Under the Recently used coordinate reference systems section, choose the *
Generated CRS (+proj = aea...) SRS.
ii. Click OK.
e. Check the Target SRS box and click Select to open the Select the target SRS window.
114
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f. In the Filter box, type 3857, and under Coordinate reference systems of the world, choose
WGS 84/ Pseudo Mercator. Click OK.
g. Check Load into canvas when finished.
h. Click OK.
Wjrp (Pcp'Ojcct)
Batch mod* (for processing whole directory)
Input Me
Output file
* source SRS
* Target SRS
Resampling method
No data values
Mask layer
Memory used for caching
Resae
WICO_20JI_land_Cove - Select...
/QGIS/NLCD _FL_reproj.tif Select...
.0,0,0 *urwts=m »no_defs Select..
EPSG:3S$7 Select..
['~ear F-
| HUC_Tampa_KA063
Width |30Q0 Height 13000
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X Load into canvas when finished
gdafcwp •~fwoj=aea ~4e<_l=29.5 +I«L2=45.5 ^M_0=23
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t-towg^sOAO,0,0,0,0 +un Raster > Extraction > Clipper, Figure 149).
115
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?
Raster Database Help H20 Toolbox
1 Raster calculator
Interpolation
$ Terrain analysis
Zonal statistics
i
Projections
Conversion
Extraction
Analysis
Clipper
Figure 149 Location of the Clipper tool in EPA H20
11. In the Clipper window (Figure 150):
a. In the Input file dropdown list, select the re-projected NLCD layer (e.g. NLCD_FL_reproj), if
not selected by default.
b. Click Select next to the Output file text box to select a file path and name for the output (e.g.
NLCD_HUC_clip.tif). Be sure to name the output with a .tif extension.
c. Check the box next to No Data Value and choose the default value of 0.
d. In the Clipping mode section, choose Mask layer and select the user-specific HUC watershed
boundary shapefile as the Mask layer, if not selected by default (e.g. HUC_Tampa_QGIS).
e. Check Load into canvas when finished,
f. Click OK.
Clipper
Input file (raster)
Output file
* No data value
Clipping mode
Extent
Mask layer
NLCD_FL_reproj
- Select-
NLCD_HUC_clip.tif
Select...
0
• Mask layer
HUC_Tampa_QGIS
Select-
Create an output alpha band
X Load into canvas when finished
gdalwarp -dstnodata 0 -q -cutline
C:/Users/mjackson/.qgis/0.0.3/Tampa_H20/D2_Tampa/BuildingDataba
se_Outputs/QGIS/HUC_Tampa_WGS.shp -crop_to_cutllne -of GTiff
C:/Users/m]ackson/.qgis/0.0.3/Tampa_H20/D2_Tampa/BuildingDataba
se_Outputs/QGIS/NLCD_FL_reproj,tif NLCD_HUC_clip.tif
m
OK
Close
Help
Figure 150 Clipper tool window in EPA H20
12. When a Finished window appears, click OK to continue.
13. Click Close to close the Clipper tool after processing is complete.
116
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m..
Troubleshooting Common Errors:
Problem:
A common error with the Clipper too! results in the clipped
land use layer being shifted from the original shapefile
location, as shown in Figure 151. This shift occurs if the
wrong HUC watershed boundaries shapefile was used as
the Mask layer in the clipper tool.
Solution:
Clip the raster using the clipper tool again, repeating steps
10-13, using the re-projected NLCD layer and the HUC
watershed boundary shapefile first created in the Using
QGIS section. The HUC watershed boundary shapefile
projection should be NAD83. The outline of the resulting
raster from the clipper tool should align with the outline of
the watershed boundary.
SpllllpipSMi
Figure 151 Clipped raster shifted
from the original shapefile
location used in the tool
After the NLCD raster is clipped to the area of interest it must be converted to a polygon (vector)
dataset. First a grid of polygons aligned with the raster cells is generated, then points within each
raster cell are generated to sample the raster and copy the values over to the new grid of polygons.
14. From the Vector menu, open the Vector grid tool (Main Menu > Vector > Research Tools > Vector
grid, Figure 152).
Vector Raster Database Help Transportation H20 Toolbox
Analysis Tools ~
; Coordinate Capture ~
Data Management Tools*
Geometry Tools ~
Geoprocessing Tools *
Scenarios Editing Scenario:
Research Toots *
g Random selection
a Random selection within subsets
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Vector grid
\r Select by location
Figure 152 Location of the Vector grid tool in EPA H20
15. In the Vector grid window (Figure 153):
a. For Grid extent, select the clipped NLCD layer (e.g. NLCD_HUC_clip).
b. Check the box next to Align extents and resolution to selected raster layer and click the
Update extents from layer button.
c. Toggle the button next to Output grid as polygons.
d. In the Output shapefile text box, specify the file path and name for the output shapefile (e.g.
NLCD_HUC_poly. shp).
e. Click OK.
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Note: if processing the NLCD raster in sections the difference in X Min and Y Min parameters between
sections must be divisible by a raster cell (e.g. 30m for NLCD) for polygons to align. For example, if
section one X Mim= -9229391.18469, and section two X Min2 = -9226500, the distance between X Min is
2891.18469m. Decreasing this distance to 2880m, X Min2 = -9226511.18469, makes it divisible by 30m
and moves the sections closer.
& Vector grid
Grid extent
NLCD_HUC_clip
X Align extents and resolution to selected raster layer
X
Update extents from layer
Update extents from canvas
X Min -9229391.18469
Y Min 3182908.19827
X Max -9092391.6938
Y Max 3403559.68744
Parameters
X | 34.0455991268
34.0459017390
1
X Lock 1:1 ratio
• Output grid as polygons
Output grid as lines
Output shapefile
lingDatabase_Outputs/QGIS/Polygonize/NLCD_HUC_poly.shp
0%
OK
Browse
Close
Figure 153 Vector Grid tool window in EPA H20
Troubleshooting Common Errors:
Problem:
While running the Vector grid tool, an
error may appear that states the program
has stopped working (Figure 154). Raster
processing has size limitations, which
may cause the program to crash.
Solution:
Try repeating the process on a raster
clipped to a smaller area. If multiple
watersheds were selected in creating the
HUC watershed boundary shapefile, try
clipping the raster to each watershed
boundary individually. Follow the steps
outlined in the Create HUC Watershed Boundaries section to create shapefiles for individual
watersheds. Use the buffer tool (Main Menu > Vector > Geoprocessing Tools > Buffer) to add
a 30m buffer to each watershed to help eliminate data gaps between watershed edges.
Repeat the steps in this section (Using QGIS) to clip and prepare the NLCD raster for each
individual watershed shapefile. The land cover shapefiles created must be recombined (steps
49-52) before importing them into the .sqlite database.
112,
qgis.exe X
^ qgis.exe has stopped working
A problem caused the program to stop working
correctly. Please close the program.
—^ Close the program
Figure 154 QGIS error message, which appears when
the program has stopped working
-------
16. A Generate Vector Grid message will appear when processing is almost complete. Click Yes.
17. After the output shapefile appears in the Layers panel, and the Vector grid tool progress bar
returns to 0%, click Close to close the Vector grid window.
18. From the Vector menu, open the Regular Points tool (Main Menu > Vector > Research Tools >
Regular Points).
19. In the Regular points window (Figure 155):
a. From the Input Boundary Layer dropdown list, select the clipped NLCD raster (e.g.
NLCD_HUC_clip.tif).
b. Toggle the Use this point spacing option, and in the text box, enter the resolution of the
raster. The 2011 NLCD resolution is 30 m; units in the tool will match the units of the
coordinate system.
c. In the Initial inset from corner (LH side) text box, divide the resolution value by 2, and enter
the result (e.g. 15 m, half of 30 m).
d. In the Output Shapefile text box, specify a file path and name for the output shapefile (e.g.
NLCD_HUC_points. shp).
e. Click OK.
^ Regular points
X
Area
• Input Boundary Layer
NLCD_HUC_clip
Input Coordinates
X Min
X Max
Y Min
Y Max
Grid Spacing
• Use this point spacing 30.0000
Use this number of points
Apply random offset to point spacing
Initial inset from corner (LH side) 15.0000
r
D°/o
OK
Output Shapefile
|_0 utp uts/QG IS/Po lyg o n ize/N LCD_H U C_p o i nts. sh p
Browse
Close
Figure 155 Regular points window in EPA H20
20. A Generate Regular Points message will appear during processing. Click Yes.
21. After the output shapefile appears in the Layers panel, and the Regular Points tool progress bar
returns to 0%, click Close to close the Regular points window.
22. Sampling the raster at the generated points is done using the Point sampling tool plugin. Use the
QGIS Plugin Manager (Main Menu > Plugins > Manage Plugins) to make sure the Point sampling
tool plugin is enabled, as shown in Figure 156. If not already enabled, check the box next to Point
sampling tool (Version 0.3.3) to activate the plugin, and click OK.
119
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QGIS Plugin Manager
X
Filter
To enable / disable a plugin, click its checkbox or description
%
Plugin Installer (Version 1.2.1)
Downloads and installs QGIS python plugins
Installed in Plugins menu/toolbar
Point sampling tool (Version 0.3.3)
Collects polygon attributes and raster values from multiple layers at specified
sampling points
Installed in Plugins menu/toolbar
QConsondate (0.1.0)
a l Consolidate QGIS project into one directory
Installed in Plugins menu/toolbar
QSpatiaLite (Version 6.0.3)
jS„p.?ti.fiLl.'±A..CJ[ IT f.ox. it p.1 lo/ad. Lmmoxfc ..tin J;? b I n r f fl i i.r> nt tnArTfc1 =
Plugin Directory: C:/PR0GRA~2/EPA H20/apps/qgis/plugins
OK Select All Clear All Cancel
Figure 156 QGIS Plugin Manager, with the Point sampling tool selected and enabled
23. From the Plugins menu, open the Point sampling tool (Main Menu > Plugins > Analyses > Point
Sampling Tool).
24. In the Point Sampling Tool window (Figure 157):
a. In the Layer containing sampling points dropdown list, select the regular points layer
generated in the previous step (e.g. NLCD_HUC_points),
b. In the Layers with fields/bands to get values from list box, click to highlight the clipped NLCD
raster (e.g. NLCD_HUC_clip.tif). Only layers that are currently turned on in the Layers panel
will be available in the Layers with fields/bands to get values from list box.
c. In the Output point vector layer text box, specify a file path and name for the output point
vector layer (e.g. NLCD_HUC_samplepoints.shp).
d. Check Add created layer to the TOC.
e. Click OK.
120
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iji Point Sampling Tool
X
General Fields About
Layer containing sampling points:
NLCD_HUC_points
Layers with fields/bands to get values from:
I NLCD_HUC_points : ID (source point]
NLCD HUC clip : Band 1 (raster)
Output point vector layer:
;e_Outputs/QGIS/Polygonize/NLCD_HUC_samplepoints.shp
X Add created layer to the TOC
Browse
Status:
Complete the input fte/ds andpress OK...
OK
Close
Figure 157 Point Sampling Tool window, with NLCD_HUC_clip selected in blue
Depending on the size of the AOI this tool may take a few hours to process. The window may say Not
Responding while the tool is still actively processing.
25. After the output shapefile appears in the Layers panel, click Close to close the Point Sampling
Tool window.
26. From the Vector menu, open the Join attributes by location tool (Main Menu > Vector > Data
Management Tools > Join attributes by location, Figure 158).
Vector
Raster Database Help Transportation H20 Toolbox]
Analysis Tools ~
Coordinate Capture ~
Scenarios Editinq Scenario:
Data Management Tools*
^ Define current projection
Geometry Tools *
* Join attributes by location |
Geoprocessing Tools ~
Split vector layer |
Figure 158 Location of the Join attributes by location tool in EPA H20
27. In the Join attributes by location window (Figure 159):
a. From the Target vector layer dropdown list, select the polygon vector grid (the output from the
Vector grid tool in step 15, e.g. NLCD_HUC_poly).
b. From the Join vector layer dropdown list, select the sampled points layer (the output from the
Point sampling tool in step 24, e.g. NLCD_HUC_samplepoints).
c. In the Attribute Summary section, toggle Take attributes of first located feature.
d. In the Output Shapefile text box, specify the file path and name for the output polygon layer
(e.g. NLCD_HUC_poly_spointsJoin.shp).
e. In the Output table section, toggle Only keep matching records.
f. Click OK.
121
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^ Join attributes by location
Target vector layer
NLCD_HUC_poly
Join vector layer
i N LCD_H U C_sa m p i ej3 o i nts
Attribute Summary
X
• Take attributes of first located feature
Take summary of intersecting features
II Mean Q Min Q Max ~ Sum Q Median
Output Shapefile
_0 utp uts/Q G IS/Po ly g o n ize/N LCD_H U C_p o ly_sp o i nts J o i n. sh p
Output table
• Only keep matching records
Keep all records (including non-matching target records)
Browse
0%
OK
Close
Figure 159 Join attributes by location window
28. A Join attributes message may appear when processing is almost complete. Click Yes.
29. After the output shapefile appears in the Layers panel, and the Join attributes by location tool
progress bar returns to 0%, click Close to close the Join attributes by location window.
30. Double click on the NLCD polygon layer (e.g. NLCD_HUC_poly_spointsJoin) to open Layer
Properties.
31. Under the Fields tab, click the pencil
toggle editing mode.
. i
icon to
I®
icon to add a new
32. Click the New Column
gridcode field to the attribute table.
33. In the Add Column window (Figure 160):
a. In the Name text box, type gridcode.
b. In the Type dropdown list, select Text (string).
c. In the Width text box, enter 2.
d. Click OK.
34. Click the Field Calculator
icon in Layer
Properties to open the Field Calculator window.
35. In the Field Calculator window (Figure 161):
^ Add column
Name gridcode
X
Comment
Type
Width
Precision
Text (string)
string
]:
OK
Cancel
Figure 160 Add column window, to add a new
field in the land use polygon layer
122
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a. Toggle the Update existing field option, and from the dropdown list, select the "gridcode" field.
b. In the Function List, find and expand Fields and Values. Double click the joined field from this
list (e.g. "NLCD_HUC_c").
c. The name of the joined field should appear in the Expression box.
d. Click OK.
Q Field calculator
Only update selected features
Create a new field
X Update existing field
Output field name I
Output field type Whole number (integer)
gridcode
Output field width {10 |-$-j Precision |o [-qr]
Selected Function Help
_1 [ Field
Function List
Search
GD Operators
H£) Math
ED Conversions
111 String
© Geometry
GD Record
B Fields and Values
[¦¦¦¦ ID
XMIN
XMAX
YMIN
YMAX
NLCD HUC c
Double click to add field name to
expression string.
Right-Click on field name to open context
menu sample value loading options.
gridcode
Operators
( )
Expression -
"NLCD HUC c*
Output preview:
OK ~~] Cancel Help
Figure 161 Field Calculator, with NLCD_HUC_c entered as the expression
36. Click the pencil
icon in the Fields tab of Layer Properties to toggle editing off. In the Stop
editing window that appears, click Save to save the Field Calculator edits.
Troubleshooting Common Errors:
Problem:
While processing the field calculation an
error may appear that states the program
has stopped working (Figure 162).
Depending on the size of the user's AOI,
EPA H2Q may not be able to process the
full field calculation.
qgis.exe
X
6
qgis.exe has stopped working
A problem caused the program to stop working
correctly. Please close the program.
—> Close the program
Figure 162 QGIS error message, which appears when the
program has stopped working
11T
-------
Solution:
If this occurs, reopen the EPA H20 program, and load the NLCD polygon layer (e.g.
NLCD_HUC_poly_spointsJoin). Open the attribute table to determine if the "gridcode" field and
the joined field (e.g. "NLCD_HUC_c") match completely. Double click on the joined field header
(e.g. "NLCD_HUC_c") to sort the field in descending order. If the "gridcode" field did not fully
populate, click the pencil icon in the attribute table to toggle editing on. Select the first row with a
blank "gridcode" field and drag down the attribute table to highlight the subsequent rows. If there
are many rows that did not update it is recommended that the user highlight rows in sections, to
avoid having the error repeat. For each selection of rows, click the Field Calculator icon and
populate the "gridcode" field using the Field Calculator window as shown in step 35 (Figure 161).
Toggle editing off and save (step 36) after all values in the created field match those in the joined
field.
37. In the Layers panel, right-click on the NLCD polygon layer (e.g. NLCD_HUC_poly_spointsJoin)
and open the attribute table.
38. In the Look for text box at the bottom of the attribute table, type NULL and from the in dropdown
list, select the "gridcode" field. Click Search.
39. At the bottom of the attribute table, click the Invert Selection icon. This may take significant
time to process.
40. From the Vector menu, open the Dissolve tool (Main Menu > Vector > Geoprocessing tools >
Dissolve).
41. In the Dissolve window (Figure 163):
a. In the Input vector layer dropdown list, select the NLCD polygon layer (e.g.
NLCD_HUC_poly_spointsJoin).
b. Check the Use only selected features option if not automatically checked.
c. In the Dissolve field dropdown list, select "gridcode".
d. In the Output shapefile text box, specify the file path and name for the output shapefile (e.g.
NLCD_FIUC_dissolve. shp).
e. Click OK.
^ Dissolve
? X
Input vector layer
NLCD_HUC_poly_spoints_join T
X Use only selected features
Dissolve field
gridcode T
Output shapefile
/Q G IS/Po lyg o n ize/N LCD_H U C_d i sso Ive. sh p
Browse
0%
OK
Close
Figure 163 Dissolve window, used to merge common land use polygons together
Depending on the size of the area being processed, this step may take significant time to process. Do
not close out of EPA H20.
42. Once the tool is finished, click Close to exit the Dissolve window.
124
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43. From the Vector menu, open the Multipart to singleparts tool (Main Menu > Vector > Geometry
Tools > Multipart to singleparts).
44. In the Multipart to singleparts window (Figure 164)\
a. In the Input line or polygon vector layer dropdown list, select the dissolved polygon layer (e.g.
NLCD_HUC_dis solve).
b. In the Output shapefile text box, specify the file path and name for the output shapefile (e.g.
NLCD_H UC_parts. shp)
c. Click OK.
^ Multipart to singleparts
? X
Input line or polygon vector layer
NLCD HUC dissolve
j ~
Output shapefile
. 3/0 utp uts/Q G IS/Po ly g o n ize/N LCD _H U C_p a rts. sh p
Browse
0°/o
OK
Close
A
Figure 164 Multipart to singleparts window in EPA H20
45. In the Layers panel, double click on the land use layer (e.g. NLCD_HUC_parts) to open Layer
Properties.
46. From the Fields tab of Layer Properties, click the pencil 0 icon to toggle editing on.
47. Select all fields except the "gridcode" field and remove them using the Delete column
icon.
0 ic
48. Click the pencil icon under the Fields tab to toggle Editing mode off. In the Stop editing
window that appears, click Save.
If the user had to clip the NLCD raster into smaller areas, steps 15 through 48 must be repeated for
each NLCD clip. The following steps explain how to recombine NLCD shapefiles generated for each
smaller area into one land use layer. If the NLCD raster was not split into smaller areas the NLCD
shapefile is complete and the following steps can be skipped.
49. Use File Explorer to move the shapefile output for each NLCD clip to a common folder if not
already. This common folder should only contain the final NLCD shapefile outputs (from step 44).
50. From the Vector menu, open the Merge shapefiles to one tool (Main Menu > Vector > Data
Management Tools > Merge shapefiles to one, Figure 165).
125
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Vector Raster Database Help Transportation H20 Toolbox |
Analysis Tools ~
Coordinate Capture ~
1 1
Scenarios Editinq Scenario:
Data Management Tools ~
Define current projection
^ Join attributes by location
V~ Split vector layer
Geometry Tools ~
Geoprocessing Tools ~
Research Tools ~
Road graph ~
H Merge shapefiles to one
Create spatial index
Figure 165 Location of the Merge shapefiles to one tool in QGIS
51. In the Merge shapefiles window (Figure 766):
a. In the Shapefile type dropdown list, select Polygon.
b. For the Input directory text box, click Browse and locate the common folder where each
NLCD clip output was saved (e.g. Polygonize).
c. In the Output shapefile text box, specify the file path and name for the output shapefile (e.g.
NLCD_ Tampa_poly_reproj. shp).
d. Check Add result to map canvas.
e. Click OK.
Merge shapefiles
? X
Select by layers in the folder
Shapefile type Polygon
Input directory
:>a/BuildingDatabase_Outputs/QGIS/Polygonize
Brov^se
Output shapefile
_0 utputs/Q GIS/N LCD_Ta m p a_p o ly_re p roj. sh p
Browse
Add result to map canvas
Figure 166 Merge shapefiles window in QGIS, with Polygonize folder indicated as the Input directory
52. Repeat steps 40-44 on the merged land use layer to combine any land use polygons that have
been split when processing the raster by section; however, un-check the Use only selected
features option when running the Dissolve tool (Step 41b).
The output layer is a vector (polygon) representation of the NLCD raster data layer. This layer has not
been simplified, resulting in land use polygon boundaries with vertices that follow the jagged outlines
of their former raster cells. In reality these land use areas will rarely follow straight lines like this and
removing some of the vertices to smooth and simplify the polygons is an option in ArcGIS.
126
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The layer created in this section is used in a spatial join with the soil dataset in the Spatially Join Soils
to Land Use section. Database creation is continued in the Create Land Use Comparison Data
section
The original Tampa Bay database contains land use prediction datasets for the years 2020, 2040, and
2060. These datasets can be used to create and compare scenarios with current land use; however,
the datasets are specific to the Tampa Bay area. The user can manipulate these tables in EPA H20
for use in new areas in multiple ways:
1. The user may remove these datasets from the Qspatialite plugin in EPA H20, and not include
created land use comparison data in their database.
2. The user may remove these datasets and insert their own future land use prediction data into
the Qspatialite plugin. This data must be created or obtained by the user.
3. The user may create past land use comparison data from previously published NLCD data
years and insert this comparison data into the Qspatialite plugin.
This section outlines how to process past NLCD data for EPA H20 scenario comparisons. Example
input and output layers are given for processing the NLCD 2001 land use layer.
1. Past land use data was previously downloaded in the Download Land Use Data section
(Figure 135- Figure 138).
a. If the All Land Cover Years option was toggled during data download, NLCD land cover
for years 2001, 2003, 2006, 2008, 2013, and 2016 were unzipped into the same location
as NLCD 2011.
b. Note: only 3 land use comparison datasets can be inserted into a new database at one
time.
2. Process the land use data as shown in Create Land Use Data Layer, Using ArcGIS or Using
QGIS sections.
a. Clip each land use raster to the AOI boundary,
i. In this example, the
NLCD_2001_Land_Cover_L48_20190424_umtxeyAuXzMnsc7vNE8j.tiff raster is
clipped to the HUC_Tampa AOI shapefile, with the output named NLCD2001_clip.tif.
b. Convert clipped land use raster data to polygon data.
i. In this example, the NLCD2001_clip.tif raster is converted to a shapefile, with the
output named NLCD2001_clip_poly.shp.
c. Reproject each land use shapefile into the l/l/GS 1984 Web Mercator Auxiliary Sphere
(ArcGIS) or l/l/GS 84 Pseudo Mercator (QGIS) coordinate system.
i. In this example, the NLCD2001_clip_poly shapefile is re-projected, with the output
named NLCD2001_clip_poly_reproj.shp.
The remaining steps outline the rest of the requirements for creating land use comparison data.
Similar steps for processing of the land use layer (e.g. NLCD 2011) are in the Create Soil Data Layer,
Update ES Coefficients, and Joining Lookup Table sections. However, if completing sections of this
manual in sequential order, these have not been performed for the land use layer. The reader may
wish to continue processing the land use layer and then come back to the remaining land use
comparison data steps after.
3. Spatially join each land use layer (e.g. NLCD2001_clip_poly_reproj.shp) with the soil
shapefile created in Create Soil Data Layer (e.g. Max_Type_N.shp), and continue the
processing shown in Spatially Join Soils to Land Use (ArcGIS) or Spatially Join Soils to Land
Use (QGIS).
127
-------
a. After each join, create a new "Max_Type_N" field in the new land use attribute table (e.g.
NLCD2001_MaxTypeNJoin.shp). Populate "Max_Type_N" with integer values based on
the averaged values in the "Avg_Max_Ty" field.
b. Calculate the most common soil type in the land use layer (e.g.
NLCD2001_MaxTypeNJoin.shp) and populate the "Max_Type_N" value for the NULL soil
polygons (i.e. "Avg_Max_Ty" = 0).
4. Join each land use layer with the lookup table, as shown in either the Using ArcGIS or Using
QGIS sections. Then update the ES coefficients and continue with field calculations.
a. Join the land use layer (e.g. NLCD2001_MaxTypeNJoin.shp) with the lookup table (e.g.
lookUPvars) and export the updated land use layer (e.g. LandUse_2001.shp).
b. Update the "Canopy" field in the final land use layer (e.g. LandUse_2001.shp), as shown
in the Tree Canopy section (Using ArcGIS or Using QGIS). However, the final land use
layer (e.g. LandUse_2001.shp) will be used as the input, rather than the soil/land use
layer.
i. In ArcGIS, continue following the steps outlined in the Tree Canopy Using ArcGIS
section; however, right-click on each land use layer (e.g. LandUse_2001.shp), rather
than the lookup table, to join by attributes.
ii. In QGIS, continue following the steps outlined in the Tree Canopy Using QGIS
section. However, the field calculations will occur in each land use attribute table (e.g.
LandUse_2001.shp), rather than the lookup table. The user must also select all rows
for each gridcode value (not just the first row) and complete the appropriate
calculations. This selection can be completed by clicking and dragging to highlight
rows, or by creating a query for each gridcode in the Look for search box.
c. The % canopy cover may differ between years because the land use changes. The
carbon burial rate for "Developed" land use types incorporates the % canopy values. The
user may choose to update the "CarbonFixe" field for the "Developed" land use in each
layer, as explained in the Carbon Sequestration section.
d. After the "Canopy" fields have been updated, the calculations in the Joining Lookup Table
section can be completed as written for each land use layer.
The Importing Layers into QGIS section details how to upload the land use layers into the user
database in QGIS. Database creation is continued in the Create Soil Data Layer section.
The soil data layer defines soil types in EPA H20. Soil types, along with land cover classes, are used
to characterize Curve Number (CN) values in the land use layer. These CN values are then used to
compute the dollar value of flood protection, one of the ecosystem services EPA H20 evaluates. This
section illustrates the step-by-step method used to obtain and prepare the soil data. The Joining
Lookup Table section describes how to calculate CN values for the land use data layer using the soil
data layer that results from this section.
Either Esri ArcMap software or QGIS can be used to prepare the soil data. The procedure for both
software applications is explained in this section.
Download Soil Data
This section illustrates the step-by-step procedure for downloading soil shapefiles by county from the
USDA Soil Survey Website.
1. Navigate to https]//websoilsurvev.sc.eqov.usda.qov/App/WebSoilSurvev.aspx as shown in
Figure 167.
128
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Figure 167 USDA Soil Data download website
2. Click on the Download Soils Data tab (Figure 168).
| Area of Interest (AOI) 1 f Soil Map ~|j f Soil Data Explorer
n ®
r
1 Download Soils Data for... ©
Your AOI(SSURGO)
Soil Survey Area (SSURGO)
U.S. General Soil Map (STATSG02)
1 Download SSURGO Template Databases ©
II
FOIA | Accessibility Statement | Privacy Policy | Non-Discrimination Statement | Information Quality | USA.gov | White House
Figure 168 Download options located under the Download Soils Data tab
3. Under the Dov/nload Soils Data for.... section click Soil Survey Area (SSURGO) to expand
this section (Figure 169).
4. In the newly expanded Options section, select the desired State and County from the
appropriate dropdown lists (Figure 169).
5. Check the Include Template Database option and click Update.
129
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Download Soils Data for...
lYour AO I (SSIJRGO)
Figure 169 Soil data sets are downloaded by the counties the user's area of interest is in
6. From the Soil Survey Area Download Links section, find the desired county dataset and
download it by clicking the hyperlink in the Download Link column (e.g.
wss_SSA_FL057_soildb_FL_2003_f2018-09-14J.zip, Figure 170). Multiple county datasets
may need to be downloaded to cover all parts of the user's Area of Interest.
Soil Survey Area (SSURGO) Download Links
Name
Area Symbol
Data Availability
Version
Template Database
Download Size
Download Link
Highlands
County, Florida
FLO 55
Tabular and
Spatial,
complete
Survey Area: Version 17,
Sep 17, 2018
Tabular: Version 16,
Sep 17, 2018
Spatial: Version 4,
Dec 19, 2013
soildb_FL_2003
Access 2003
Version 36
16.0 MB
wss_SSA_FL055_soildb_
_[2018-09-17].zip
_FL_
.2003
Hillsborough
County, Florida
FLO 57
Tabular and
Spatial,
complete
Survey Area: Version 17,
Sep 14, 2018
Tabular: Version 16,
Sep 14, 2018
Spatial: Version 3,
Dec 17, 2013
soildb_FL_2003
Access 2003
Version 36
23.9 MB
wss_SSA_FL057_soildb_
_[2018-09-14].zip
_FL_
.2003
Holmes County,
Florida
FLO 59
Tabular and
Spatial,
complete
Survey Area: Version 14,
Sep 5, 2018
Tabular: Version 13,
Sep 5, 2018
soildb_FL_2003
Access 2003
Version 36
15.4 MB
wss_SSA_FL059_soildb_
_[2018-09-05].zip
_FL_
.2003
Figure 170 Link to download soil data is provided by county
7. Save the zip file to the computer and unzip the contents to a known location on the C:\drive.
It may be helpful to create a special directory for the soil data (an example directory is shown
in Figure 171). By default, unzipped files for each download are saved in a folder named after
their Area Symbol, as listed in the Area Symbol column in Figure 170.
-
~
X
- ©
> Tampa_H20 > D2_Tampa > Soils >
v O
Search Soils
p
Name
[_' FL057
~ FL081
FL103
Date modified
1/25/2018 9:09 AM
1/25/2018 9:10 AM
1/25/2018 9:12 AM
Type
File folder
File folder
File folder
Size
Figure 171 Recommended workspace for Soil data
130
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The next section illustrates the pre-processing of spatial soil data using Microsoft Access.
Pre-processing Soil Data
This section illustrates pre-processing of the spatial soil data using Microsoft Access. These steps are
also detailed in the readme.txt file located in each unzipped soil data folder. Users must complete
these steps before creating the soil data layer using either Esri ArcGIS software (Using ArcGIS) or
QGIS (Using QGIS).
1. Download and unzip the SSURGO soil data, as shown in the Download Soil Data section.
2. Each unzipped soil data folder contains a ".mdb" database file. Locate the ".mdb" file in File
Explorer, right-click and choose Open to open the file in MS Access.
3. When MS Access opens the ".mdb" file a Macro Single Step window may appear (Figure 172).
Click the X button to close the window and click Enable Content to fully enable the program.
Click for more details.
Enable Content
© «
Macro Single Step
Macro Name:
AutoExec
Condition:
Action Name:
RunCode
Arguments:
X
Step
Stop All Macros
Error Number:
2001
Figure 172 Macro Single Step pop-up window in Microsoft Access
4. A SSURGO Import window will appear when MS Access is fully enabled (Figure 173).
Tables
cohydriccriteria
§3 cointerp
comonth
S3 component
S3 copm
S3 copmgrp
S3 copwindbreak
S3 corestrictions
S3 cosoilmoist
a cosoiltemp
S3 cosurffrags
m cosurfmorphgc
©
Note: This function imports the tabular data contained in a soil data
download into this database. For detailed instructions, please select the
Reports tab of the Database window, open the report titled "How to
Understand and Use this Database", and read the section titled "Importing
Data".
Enter the directory location where the files to be imported reside. Enter both the
the letter of the drive and the fully qualified path to the directory on that drive. For
example "d:\tmp\soil_mt627\tabular\". The closing backslash is optional.
Figure 173 Macro requesting the tabular folder path
131
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5. In File Explorer, locate the tabular folder within the unzipped soil data folder on the C:\ drive,
and copy the file path (e.g.
C:\Users\USERY qgis\0.0.3\Tampa_H20\D2_ Tampa\Soils\FL057\tabuiar).
6. In the SSURGO import window, paste the file path in the blank text box and click OK.
7. After the tabular data is imported into MS Access, the user will gain access to the Tables
column on the left sidebar (Figure 173). If Tables is not showing at the top of the sidebar, click
on the column dropdown button, and choose Tables (Figure 174).
Tables ®
«
Navigate To Category
JL
Custom
^ Object Type
Tables and Related Views
Created Date
Modified Date
Filter By Group
Tables
Queries
Figure 174 List of Access Objects in MS Access; Tables has been selected
8. The Tables column contains a list of tables; locate the component table and right-click on the
table name to choose Export > Text File (Figure 175).
Tables
©
«
m
co mo nth
0
m
component
Open
Design View
Import ~
m
m
copm
copmgrp
copwindbreak
m
co restrictions
Export ~
!!q
Excel
a
cosoilmoist
Rename
SharePoint List
m
cosoiltemp
Hide in this Group
d
Word RTF File
m
cosurffrags
Delete
PDF orXPS
—
m
cosurfmorphgc
&
Cut
Access
m
cosurfmorphhpf
in
Copy
1
Text File
m
cosurfmorphmr
IB
Paste
H
XML File
Figure 175 Tables column in Microsoft Access, used to export the component table as a Text File
9. The Export-Text File window will appear (Figure 176). Click the Browse button to navigate to
the soils folder and export as Component_AreaSymbol (e.g. Component_FL057.csv), with
the extension ".csv", then click OK.
132
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Export - Ted File
Select the destination for the data you want to export
Specify the destination file name and format.
File name: C;\Users\USER\.qgis\0.0.3\Tarripa_H20\D2_Tampa\Soils\FL05AComponent_FL057,c:
Specify export options.
We will not import table relationships, calculated columns, validation rules, default values, and columns of certain legacy data types
such as OLE Object.
Search for "Import' in Access 2016 Help for more information.
l~l Export data with formatting and layout.
Select this option to preserve most formatting and layout information when exporting a table, query, form, or report.
I I Open the destination file after the export operation is complete.
Select this option to view the results of the export operation. This option is available only when you export formatted data.
Export only the selected records.
Select this option to export only the selected records. This option is only available when you export formatted data and
have records selected.
Figure 176 Export - Text File window, with Component_FL057.csv arid the file path in the File name box
10. The Export Text Wizard window will appear (Figure 177). Check Delimited as the format type
if not checked by default and click Next >.
-11 Export Text Wizard
This wizard allows you to specify details on how Microsoft Access should export your data.
Which export format would you like?
(#)gelimited - Characters sucti as comma or tab separate each field
Q Fixed Width - Fields are aligned in columns with spaces between each field
Sample export format:
_1_,3,,"Felda","Series","No","","",0,1,2,30,61,91,"Very high",5,"250","1","Class l","Gras ¦
_2_,2,,"Kesson","Series","No","","tidal",0,0.5,1,30,30,61,"High",5,"0","8","None - deposj
3 90,95,99,"Canaveral","Series","Yes",0,1,2,30,61,91,"Negligible",5,"250","1","Clc
4 ,3,,"Captiva","Series","No",0,0.5,1,30,30,61,"High",5,"0","8","Class l","Tree cc
5 ,5,,"Canaveral","Series","No","","",0,1,2,,46,,"Low",5,"250","1","Class
€ ,95,,"Beaches","Miscellaneous area","Yes",1,2,3,,46,,"Very high","r
7 ,2,,"Boca","Series","No",0,1,2,30,46,91,"Very high",2,"250","1","Class l","Tree
8 35,40,45,"Pineda","Series","Yes","","wet",0,0.5,1,30,30,91,"Negligible",5,"250","1","C
^,6,,"Felda","Series","No","",0,1,2,30,46,91,"Very high",5,"250","1","Class 1","Grai
1£,2,,"Hallandale","Series","No",0,1,2,30,46,91,"Very high",1,"250","1","Class 1",
11,2,,"Valkaria","Series","No",0,1,2,30,61,91,"Very high",5,"250","1","Class 1","1
12 40,45,50,"Pineda","Series","Yes","","",0,1,2,30,61,91,"Very high",5,"250","1","Class J
13,3,,"Wabasso","Series","No",0,1,2,30,46,91,"Very high",5,"250","1","Class 1","Ti
14 ,1,,"Placid","Series","No",0,0.5,1,30,30,61,"Negligible",5,"250","1","None - dej ¦
Advanced... Cancel J | | Finish
Figure 177 Export Text wizard, with Delimited format type
133
-------
11. In the next Export Text Wizard window, select Comma as the delimiter and mark the box
Include Field Names on First Row (Figure 178).
I^H Export Text Wizard X
What delimiter separates your fields? Select the appropriate delimiter and see how your text is affected in the preview below.
Choose the delimiter that separates your fields:
Qlab Q Semicolon (*) pwnma j Q Space Q Other:
[^Include Field Names on First Row Text Qualifier: | v |
"comppct_l", "comppct_r", "comppct_h", "compname", "compkind", "majcompflag", "otherph", "local
,3,,"Felda","Series","No",0,1,2,30,61,91,"Very high",5,"250","1","Class 1","Grass/
,2,,"Kesson","Series","No","","tidal",0,0.5,1,30,30,61,"High",5,"0","3","None - deposit!
90,95,99,"Canaveral","Series","Yes",0,1,2,30,61,91,"Negligible",5,"250","1","Class
,3,,"Captiva","Series","No",0,0.5,1,30,30,61,"High",5,"0","8","Class 1","Tree cove
,5,,"Canaveral","Series","No","","",0,1,2,,46,,"Low",5,"250","1","Class 1","","","","No"
, 95,, "Beaches", "Miscellaneous area", "Yes", "", "",1,2,3, ,46,, "Very high",
,2,,"Boca","Series","No",0,1,2,30,46,91,"Very high",2,"250","1","Class l","Tree co
35,40,45,"Pineda","Series","Yes","","wet",0,0.5,1,30,30,91,"Negligible",5,"250","1","Cla
,6,,"Felda","Series","No","","",0,1,2,30,46,91,"Very high",5,"250","1","Class 1","Grass/
,2,,"Hallandale","Series","No","","",0,1,2,30,46,91,"Very high",l,"250","1","Class 1","T
,2,,"Valkaria","Series","No","","",0,1,2,30,61,91,"Very high",5,"250","1","Class 1","Tre
40,45,50,"Pineda","Series","Yes","","",0,1,2,30,61,91,"Very high",5,"250","1","Class 1",
,3,,"Wabasso","Series","No",0,1,2,30,46,91,"Very high",5,"250","1","Class 1","Tree
Advanced... Cancel I Finish
Figure 178 Export Text wizard, with Comma as the delimiter and field names included on first row
12. Click Finish to begin exporting the table.
13. Repeat steps 1-12 above to export component tables for all downloaded soil data.
14. Once ail component tables are exported the user can exit Access. The tables in the tabular
folder are now ready for use within ArcMap or QGIS.
The next section illustrates the creation of EPA H20 compatible soil data from the unzipped download
file(s), using either Esri ArcGIS software (Using ArcGIS) or QGIS (Using QGIS).
Using ArcGIS
This section illustrates the creation of EPA H2Q compatible soil data using Esri ArcGIS software.
1. Download and pre-process the soil data, as shown in the Download Soil Data and Pre-
processing Soil Data sections.
2. Open your existing ArcGIS map document file (.mxd), or create one following the steps
outlined in Set Up ArcGIS Map Document.
3. Each county soil data folder (named by Area Symbol, e.g. FL057) contains a Spatial folder.
Use the Add Data ' icon to navigate to one of these Spatial folders. Select the soil
shapefile (i.e. soilmu_a,,.shp) and add the layer to the Table of Contents of the map
document.
4. Use the Add Data icon to locate and add the corresponding component table(s) (e.g.
Component_FL057,csv), to the map document.
5. in the Table of Contents, right-click on the county soil shapefile (i.e. soilmu_a...) and open the
attribute table.
134
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6. In the attribute table, click on the Table Options
icon and choose Add Field (Figure 179).
Table
U ' H - ^ ®
Find and Replace...
Sel ect By Attri b utes..,
H Clear Selection
Switch Selection
[3 Select All
Add Field...
|:E| Turn All Fields On
s Show Field Aliases
Add Field
Arrange Tables ~
Adds a new field to the table. 1
Figure 179 Location of Add Field icon in attribute table
7. In the Add Field window (Figure 180):
a. In the Name text box, enter MUKEY2.
b. In the Type dropdown list, select Long Integer.
c. Click OK.
Add Field
Name:
I/pe:
X
MUKEY2
Long Integer
Field Properties
Precision
OK
Cancel
Figure 180 Add Field window in ArcMap
8. The "MUKEY2" field will appear in the attribute table. Right-click on the field header name and
choose Field Calculator (Figure 181).
135
-------
so
lmu_a.
_fl057
FID
Shape *
AREASYMBOL
SPATIALVER
MUSYM
MUKEY
mukey:
"*5
= Sort Ascending
W Sort Descending
Advanced Sorting...
Summarize.,.
2 Statistics,,.
0
Polygon
FLO 57
3
47
1406997
1
Polygon
FL057
3
99
1407015
2
Polygon
FLO 57
3
5
140699S
3
Polygon
FL057
3
33
1406983
4
Polygon
FLO 57
3
5
1406998
5
Polygon
FL057
3
46.
1406996
6
Polygon
FLO 57
3
29
1406979
7
Polygon
FLO 57
3
8
1407013
Iff] Field Calculator..,
S
Polygon
FLO 57
3
5
1406998
Calculate Geometry...
9
Polvoon
Fl 057
3
71
1406971
Figure 181 Field Calculator tool, accessed with a right-click on the field name
9. In the Field Calculator window (Figure 182):
a. In the Fields list box, double click on "MUKEY". The field name will appear in the
Expression box as [MUKEY],
b. Click OK.
Field Calculator
Parser
(•) VB Script O Python
Fields:
FID
Shape
AREASYMBOL
SPATIAL VER
MUSYM
MUKEY
MUKEY2
Type:
(§) Number
O String
OQate
Functions:
O Show Codeblock
MUKEY2 =
0E0BQE
About calculating fields
Clear
Load... Save...
OK
Cancel
Figure 182 Field Calculator window, with [MUKEY] entered as the expression
10. in the Table of Contents, right-click on the county soil layer (e.g. soilmu_a_fl057) and choose
Joins and Relates > Join... (Figure 183).
136
-------
Table Of Contents
m
B ^ Layers
B Q C;\Users\mjackson\.qgis\0.Q.3\Tampa_H2O\D2_Tampa\Soils\FL05Aspatial
b ~
~
B B C:\Users\mjack5
11 Component
0 Copy
X Remove
§J Open Attribute Table
Joins and Relates
Zoom To Layer
c™ Zoom To Make Visib
Visible Scale Range
Use Symbol Levels
Selection
Label Features
Join...
Rerj
Rel
Rer
Join
Join data to this layer or
standalone table based on a
common attribute, spatial
location or existing relationship
class.
Figure 183 Location of the Join feature in ArcMap
In the Join Data window (Figure 184):
a. In the first dropdown list, select Join attributes from a table.
b. In the Choose the field in this layer that the join will be based on dropdown list, select
"MUKEY2".
c. In the Choose the table to join to this layer dropdown list, select the corresponding
Component table (e.g. Component_FL057.csv).
d. In the Choose the field in the table to base the join on dropdown list, select "mukey".
e. Togg le Keep all records
f. Click OK.
Join Data
Join lets you append additional data to this layer's attribute table so you canr
for example, symbolize the layer's features using this data.
What do you want to join to this layer?
Join attributes from a table
1. Choose the field in this layer that the join will be based on:
MUKEY2
2. Choose the table to join to this layer, or load the table from disk:
|S Component_FL057.csv T |
1^1 Show the attribute tables of layers in this list
3. Choose the field in the table to base the join on:
Join Options
(§) Keep all records
All records in the target table are shown in the resulting table.
Unmatched records will contain null values for all fields being
appended into the target table from the join table.
O Keep only matching records
If a record in the target table doesn't have a match in the join
table, that record is removed from the resulting target table.
About joining data I ^ I Cance|
Figure 184 Join Data window in ArcMap
-------
12. Right-click on the county soil layer (e.g. soilmu_a_fl057) in the Table of Contents and choose
Data > Export Data, as shown in Figure 123.
13. In the Export Data window (as shown in Figure 124):
a. In the Export dropdown list, select All features.
b. Under Use the same coordinate system as, toggle the data frame option.
c. In the Output feature class text box, navigate to the preferred file path and name the
shapefile; ensure the output name will be both recognizable and distinguishable by basing
names on the county or soilmu_a_ file (e.g. soilmu_fl057Join.shp).
14. A window may appear that asks: "Do you want to add the export data to the map as a layer?"
(Figure 125). If so, click Yes.
15. From the ArcToolbox window, navigate to and open the Delete Field tool (ArcToolbox > Data
Management Tools > Fields > Delete Field, Figure 185).
ArcToolbox
X
El ^ Data ManagementTools
0 Archiving
EE) Attachments
El Data Comparison
E Distributed Geo data base
E Domains
H Feature Class
E Features
El Fields
\ Add Field
Add Incrementing ID Field
^ Alter Field
^ Assign Default To Field
^ Calculate End Time
Calculate Field
^ Convert Time Field
^ Convert Time Zone
Delete
Figure 185 Location of the Delete Field tool in ArcMap
16. In the Delete Field window (Figure 186):
a. In the Input Table dropdown list, select the exported shapefile (e.g. soilmu_fl057Join).
b. Under the Drop Field section, click the Select All button to check all the boxes. Uncheck
the boxes next to "hydgrp" and "MUKEY2".
c. Click OK to delete all checked fields from the attribute table.
138
-------
Delete Field
~ X
Input Table
soilmu_fl057join
jlJ
Drop Field
0 AREASYMBOL
A
0 SPATIALVER
0 MUSYM
0 MUKEY
~ MUKEY 2
1^1 comppctj
|V| comppctj"
M comppct_h
|v| compname
V
<
>
Select All
Unselect All
Add Field
OK
Cancel
Environments.,. Show Help »
Figure 186 Delete Field tool window, with MUKEY2 field and hydgrp (not shown) field unselected
17. Repeat steps 3-16, joining the component table to the shapefile, exporting the shapefile
and deleting extra fields, for each county soil shapefile.
18. All prepared soil shapefiles wili be combined into one feature layer, in the ArcToolbox window,
navigate to and open the Append tool (ArcToolbox > Data Management Tools > General >
Append, Figure 187).
ArcToolbox -o
X
~ Data ManagementTools
A
ffl Archiving
(+) Attachments
El Data Comparison
El Distributed Geo data base
El Domains
E) Feature Class
E Features
E i%« Fields
S % File Geodatabase
E3 i%s General
x . Analyze Tools For Pro
Append
\ Copy
Figure 187 Location of the Append tool in ArcMap
19. in the Append window (Figure 188i):
a. In the Target Dataset dropdown list, choose any one soil shapefile to append the others to
(e.g. soilmu_fl057Join).
b. In the Input Datasets dropdown list, select all other soil shapefiles (e.g. soilmu_fI081Join,
soilmu_fl103Join). As shapefiles are added they will appear in the list box.
c. Keep the Schema Type set to TEST and do not select a field map or subtype.
d. Click OK.
139
-------
Append — C
X
Input Dates®5s
d
so*nu ljon
+
>
Figure 188 Append tool window in ArcMap
Note: If the newly appended dataset (e.g. soilmu_fl057Join) doesn't appear to contain the other input
datasets (e.g. soilmu_fl081Join and soilmu_fl103Join), right-click and Remove the dataset from the
Table of Contents and re-add the layer into the map.
20. In the Table of Contents, right-click on the newly appended dataset (Target Dataset from the
append tool, e.g. soilmu_fl057Join) and open the attribute table.
i°=l »
21. In the attribute table, click on the Table Options icon, and choose Add Field (Figure 179).
22. In the Add Field window (example shown in Figure 180):
a. In the Name text box, enter the preferred name for the new field (e.g. "Max_Type_N").
b. In the Type dropdown list, select Short Integer.
c. Click OK.
The new field (e.g. "Max_Type_N") will appear in the attribute table. This field is populated based on
the "hydgrp" field, which may contain dual soil codes, such as 'A/D', 'B/D1, or 'C/D'. These codes
denote that the water table can be close to the surface, causing the soil to act as 'D' type. However,
when drained, these act as 'A', 'B\ or 'C' type soils and therefore should be coded according to the
first letter of the dual code.
23. From the main menu, choose Selection > Select By Attributes.
24. In the Select By Attributes window (Figure 189):
a. In the Layer dropdown list, select the soil shapefile (e.g. soilmu_fl057Join).
b. From the fields list box, select the "hydgrp" field and click Get Unique Values. The soii
codes will load in the values list box above.
c. Enter the following selection in the Expression box: "hydgrp" = 'A' OR "hydgrp" = "A/D"
d. Click Apply.
140
-------
Select By Attributes X
Layer:
"0" soilmu_f1057join
d
1 1 Only show selectable layers in this list
Method:
Create a new selection
V
"FID"
"MUKEY2"
"hj'dgrp"
"Max_Type_N"
=
< >
Like
'A'
/s
'A/D'
'B'
>
> =
And
'B/D'
1C'
<
< =
Or
0
Not
TC/D'
V
Null
Go To:
SELECT ' FROM Soils FLD57 WHERE:
OK
Apply
Close
Figure 189 Select By Attributes window, used to select hydgrp values A and A/D
25. In the soil attribute table, rows with "hydgrp" values 'A' and 'A/D' will be selected. Right-click
on the "Max_Type_N" field and choose Field Calculator (example shown in Figure 181).
26. In the Field Calculator window (example shown in Figure 182):
a. In the Expression box, type 1.
b. Click OK.
27. Repeat step 23-26 to change the new field values to 2, 3, and 4, for the respective "hydgrp"
field values 'B' (and 'B/D'), 'C' (and 'C/D'), and 'D'.
a. The selection for "hydgrp" value 'D' will not contain a dual code. Therefore, the selection
expression will be "hydgrp" = 'D'. Please note that not all AOIs will contain all possible
"hydgrp" values.
28. In the Table of Contents, right-click the updated soil shapefile and choose Data > Export Data
(example shown in Figure 123).
29. In the Export Data window (example shown in Figure 124):
a. In the Export dropdown list, select All features.
b. Under the Use the same coordinate system as section, toggle the data frame option on.
c. In the Output feature class text box, specify the file path and name the output
Max_ Type_ N. shp.
d. Click OK.
30. In the Table of Contents, right-click on the Max_Type_N layer and open the attribute table
31. Delete all fields from the attribute table except "Max_Type_N", "Shape" and the ID field
("FID"):
a. To delete each field, right-click on the field header and select Delete Field (Figure 190).
Note: the "Shape" field cannot be deleted.
141
-------
Table
iti
M
J* i
ax_Ty|
§• X
3£_N
FID
Shape * | MUKfi
Sort Ascending
W Sort Descending
Advanced Sorting,,,
0
Polygon
13841
1
Polygon
13641
2
Polygon
13840
3
Polygon
13640
Summarize...
T, Statistics—
4
Polygon
13640
5
Polygon
13841
6
r, t
Polygon
13-840
ill Field Calculator...
Calculate Geemet Select By Attributes.
36. In the Select By Attributes window (example shown in Figure 189)-.
a. In the Layer dropdown list, select Max_Type_N.
142
-------
b. In the Expression box, type the following expression: "Max_Type_N" = 0
c. Click OK.
37. In the Table of Contents, right-click and open the Max_Type_N attribute table.
38. Click the Delete * icon to delete the selected soil polygons.
39. In the Editor toolbar, click the Editor dropdown and choose Save Edits, and then Stop Editing
(Figure 193).
Figure 193 Editor toolbar, with the Save Edits option selected
The Max_Type_N layer is now complete; next, the values in this layer will be joined to the land use
layer.
Spatially Join Soils to Land Use
After the soil shapefile (e.g. Max_Type_N.shp) is created it must be spatially joined to the land use
layer created in the Create Land Use Data Layer section.
1. If using a new map document, use the Add Data " icon to navigate to the land use shapefile
created in the Create Land Use Data Layer section and add the layer to the Table of Contents.
2. In the Table of Contents panel, right-click on the land use layer. Under the Joins and Relates
option, select Join... (Figure 194).
Table Of Contents
0a $eis
B ^ Layers
B ~ Max_Type_N
~
n
~
® Copy
X Remove
HI Open Attribute Table
Joins and Relates ~
Join...
Zoom To Layer
Remove Join(s) ~
Figure 194 Location of the Join tool in ArcMap
3. In the Join Data window (Figure 195):
a. In the first dropdown list, select Join data from another layer based on spatial location.
b. In the Choose the layer to join to this layer dropdown list, select the updated soil layer
(e.g. Max_Type_N).
c. Toggle on the Each polygon will be given a summary of the numeric attributes of the
polygons in the layer being joined that intersect it option.
d. In the How do you want the attributes to be summarized section, check Average.
e. In the Specify output shapefile text box, designate a file path and new name for the output
shapefile (e.g. NLCD_MaxTypeNJoin.shp).
f. Click OK.
143
-------
Join Data
X
Join lets you append additional data to this layer's attribute table so you can,
for example, symbolize the layer's features using this data.
What do you want to join to this layer?
Join data from another layer based on spatial location
1. Choose the layer to join to this layer, or load spatial data from disk:
"3 £5
' Max_Type_N
2. You are joining: Polygons to Polygons
Select a join feature dass above. You will be given different
options based on geometry types of the source feature class
and the join feature dass.
(•) Each polygon will be given a summary of the numeric attributes
of the polygons in the layer being joined that intersect it, and a
count field showing how many polygons intersect it.
How do you want the attributes to be summarized?
0 Average Q Minimum Q Standard Deviation
1 I Sum HH Maximum \Z\ Variance
0 Each polygon will be given the attributes of the polygon it fells
completely inside of in the layer being joined. If a polygon falls
completely inside more than one polygon in the layers being
joined, the first one found will be joined.
3. The result of the join will be saved into a new layer.
Spetify output shapefile or feature dass for this new layer:
s'•Ac Map\N LCD_MaxType N Join\N LCD_MaxType N Join .shp
B
About joining data
OK
Cancel
Figure 195 Join land use data to soils layer (e.g. Max_Type_N), summarizing by Average
After the spatial join is complete, the "Max_Type_N" field in the spatially joined layer will be renamed
to "Avg_Max_Ty" and will contain average attribute values for each land use polygon. Where a land
use polygon does not overlap any soil polygons, either because they were missing or were deleted,
the "Avg_Max_Ty" value will be 0. These NULL polygons will be assigned the value for the most
prominent soil type (largest area) in the AOI. To determine the most prominent soil type in the AOI:
4. In the Table of Contents, right-click on the spatially joined layer (e.g. NLCD_MaxTypeNJoin)
and open the attribute table.
5. In the attribute table, click on the Table Options icon and choose Add Field (as shown in
Figure 179).
6. In the Add Field window/ (example shown in Figure 180):
a. In the Name text box, type "Max_Type_N".
b. In the Type dropdown list, select "Short Integer".
c. Click OK.
7. Click on the Table Options icon and choose Add Field again to add a second field in the
attribute table. This time in the Add Field window:
a. In the Name text box, type "Area".
b. In the Type dropdown list, select "Double".
c. Click OK.
8. In the attribute table, locate the new "Area" field, right-click on the field name and choose
Calculate Geometry (Figure 196).
144
-------
NL
CD_M
axTypeN^
oin
X
FID
Shape *
FID_1
Id
gridcode
Count_
Avg_Max_Ty
Max_Type_N
Area
>¦
Sort Ascending
W Sort Descending
Advanced Sorting...
85540
Polygon
855406
855
23
3
1.666667
0
65746
Polygon
657466
657
81
14
1.642857
0
67149
Polygon
671495
671
11
14
1.642857
0
78281
Polygon
782818
782
81
11
1.636364
0
79924
Polygon
799249
799
90
11
1.636364
0
Summarize...
X Statistics,..
|U Field Calculator...
85131
Polygon
851317
851
82
67
1.626866
0
57849
Polygon
578490
578
90
8
1.625
0
61543
Polygon
615432
615
90
8
1.625
0
61573
Polygon
615734
615
90
16
1.625
0
Calculate Geometry...
Turn Field Off
69531
Polygon
695317
695
90
8
1.625
0
73183
Polygon
731831
731
95
8
1.625
0
Figure 196 Right-click to access the Calculate Geometry option in NLCD_MaxTypeNJoin attribute table
9. The Calculate Geometry window will open, in the window (Figure 197)-.
a. In the Property dropdown list, choose Area.
b. Under the Coordinate System section, toggle Use coordinate system of the data frame.
c. In the Units dropdown list, choose Acres US [ac],
d. Click OK.
Calculate Geometry
X
Property:
Area
Coordinate System
O Use coordinate system of the data source:
| PCS: WGS 1984 Web Mercator Auxiliary Sphere
@Use coordinate system of the data frame:
PCS: WGS 1984 Web Mercator Auxiliary Sphere
Units:
Acres US [ac]
Calculate selected records only
About calculating geometry
OK
Cancel
Figure 197 Calculate Geometry window in ArcMap
The new "Max_Type_N" field is populated based on the averaged values in the "Avg_Max_Ty" field.
However, values in "Avg_Max_Ty" must be rounded to the nearest integer for the "Max_Type_N" field.
For example, for 0 < "averaged values" < 1.5, "Max_Type_N" = 7. This is completed by:
10. From the main menu, choose Selection > Select By Attributes.
11. In the Select By Attributes window (example shown in Figure 189):
a. In the Layer dropdown list, select NLCD_MaxTypeNJoin.
b. In the Expression box, type the following expression: "Avg_Max_Ty" > 0 AND
"Avg_Max_Ty" <1.5
c. Click Apply.
12. In the Table of Contents, right-click on the spatially joined layer (e.g.
NLCD_MaxTypeNJoin.shp) and open the attribute table.
13. Locate the "Max_Type_N" field, right-click on the field name and choose Field Calculator.
14. In the Field Calculator window:
a. In the Expression box, type 1.
b. Click OK.
145
-------
15. With the selection still highlighted, right-click on the "Area" field and choose Statistics...
16. From the Statistics window, copy/write down the Sum value (Figure 198). This is the total area
(acres) of the first soil type in the soil/land use layer.
Selection Statistics of NLCD_MaxTypeN join
X
Field
Area
Statistics:
Count: 282021
Minimum: 0.181705
Maximum: 5D9Q42.015864
Sum: iBBIiiEMBliSBjai
Mean: 6.634059
Standard Deviation: 1008.763246
Nulls: 0
mooi rff
50A00
Frequency Distribution
02 71657.1 143314.1 214371.0 330627.9 353334.9 429M1.8 501533.3
35628.7 107455.6 179142.5 250799.5 322456.4 334113.4 465770.3
Figure 198 Selection Statistics window, with Sum of the Area (acres) highlighted in blue
17. Close the Statistics window and clear the selection in the attribute table.
18. For each selection in Table 7, repeat steps 10-17, setting the selection using the expression in
Select By Attributes and the "Max_Type_N" field value using Field Calculator. Then find the
total area of each selection using Statistics and write down the sums for comparison.
Table 7 Expressions for selections and corresponding field calculations
Expression for Selection
"Max Type N" Value
"Avg Max Ty" > 0 AND "Avg Max Ty" < 1.5
1
"Avg Max Ty" >= 1.5 AND "Avg Max Ty" < 2.5
2
"Avg Max Ty" >= 2.5 AND "Avg Max Ty" < 3.5
3
"Avg Max Ty" >= 3.5 AND "Avg Max Ty" <= 4
4
19. Compare the areas for each soil type, and determine which classification is most prominent.
In this example, the total area for each soil type ("Max_Type_N" value) is as follows:
a. 1 = 1,870,943.6 acres
b. 2 = 102,619.9 acres
c. 3 = 7,033.8 acres
d. 4 = 4,220.2 acres
In this example, the most common soil type is "Max_Type_N" = 1. This soil type will be used
as the "Max_Type_N" values for the NULL land use polygons.
20. From the main menu, choose Selection > Select By Attributes.
21. In the Select By Attributes window (example shown in Figure 189):
a. Under the Layer dropdown list, select NLCD_MaxTypeNJoin.
b. Enter the following expression in the Expression box: "Avg_Max_Ty" = 0
c. Click Apply.
22. In the Table of Contents, right-click on the spatially joined layer (e.g. NLCD_MaxTypeNJoin)
and open the attribute table.
23. Locate the "Max_Type_N" field, right-click on the field name and choose Field Calculator.
24. In the Field Calculator window:
a. In the Expression box, type the most common soil type found in the user's AOI from
step19 (in the example this was 1).
146
-------
b. Click OK.
Database creation is continued in the Update ES Coefficients section.
Using QGIS
This section illustrates the creation of EPA H20 compatible soil data using QGIS software.
1. Download and pre-process the soil data, as shown in the Download Soil Data and Pre-
processing Soil Data sections.
2. Open your existing QGIS map document file (.qgs), or create one following the steps outlined
in Set Up QGIS Map Document.
3. Add each soil shapefile to the Layers panel:
a. From the Layer menu (Figure 126) open the Add Vector Layer window (Main Menu >
Layer > Add Vector Layer).
b. Each county soil data folder (named by Area Symbol, e.g. FL057) contains a Spatial
folder. In the Add Vector layer window (Figure 127), click Browse to locate this folder and
select the soil shapefile (i.e. soilmu_a...shp), then click Open.
4. Open File Explorer and locate each corresponding Component table. Click and drag the
".csv" files into the QGIS Layers panel.
Imported files will be displayed in the Layers panel, as shown in Figure 199.
Layers
®(x)
||| ComponentJ1057
i ffj .Component fl081
0 X soiimu a H057
B x soiimu a f!081
V • '¦
Figure 199 Soil sliapeflles and component tables displayed in the Layers panel in EPA H20
5. Double click the first soilmu_a... layer to open the Layer Properties window. Within Layer
Properties, click the Joins tab.
d8<
6. In the Joins tab, click the Add Join icon to open the Add vector join window (Figure
200).
a. In the Join layer dropdown list, select the Component table corresponding to that soil
layer (e.g. Component_FL057).
b. in the Join field dropdown list, select "mukey".
c. in the Target field dropdown list, choose "MUKEY".
147
-------
d.
e.
Check Cache join layer in virtual memory.
Click OK.
Add vector join
?
X
Join layer
Component_FL"57 T
Join field
mukey
Target field
MUKEY
JC Cache join layer in virtual memory
Cancel
Figure 200 Add Vector Join window in Joins tab. within soil layer properties
7. Right-click on the soilmu_a... layer and select the Save as... option (as shown in Figure 130).
8. In the Save as window (example shown in Figure 133):
a. In the Format dropdown list, select ESRI Shapefile.
b. In the Save as text box, browse to or type the desired output shapefile name and file
path.
c. In the CRS dropdown list, choose Selected CRS, and click the Browse button to
locate l/l/GS 84/Pseudo Mercator.
d. Check the Add saved file to map option.
e. Do not check the Skip attribute creation option.
f. Click OK.
9. Double click on the exported soil layer to open the Properties window, and click the Fields tab.
10. Toggle the editing button to start an edit session.
11. Click and drag to select all fields except "hydgrp" and "MUKEY".
Please note: field names may get lost during the join; if this occurs, "hydgrp" becomes
"Component_78". Make a new field named "hydgrp" and use the Field Calculator to populate the new
field from the original "hydgrp" data.
12. Click the Delete Column button to delete all fields except "hydgrp" and "MUKEY" (Figure
201).
13. Click OK.
148
-------
w V. I '> lufrs. 1
W , Nome , "¦jiBi : vm Jh lit1.'. ,', ¦ i, ¦> t >«" .,u , j4t» i W is
tv', if, t "• yniv; )0 « L.r«? eC.t
b;, h.di'p'P st'.ng :::i,' •;¦ L»ix- e£it
fttsier* Dcftl# St»W S>«t e As Default icji' btvie , . Save Sty k1 „
OK C-ance'i Apply Help
Figure 201 Layer Properties for joined soil layer, with required fields MUKEY and hydgrp
Repeat steps 3-13, joining the component table to the soil shapefile, exporting the shapefile
and deleting extra fields, for each county soil shapefiles. All prepared soil shapefiles will be
combined into a single layer.
14. Right-click on the first soilmu_a... layer and open the attribute table.
15. Click the Invert Selection icon, and then click the Copy rows to clipboard iconatthe
bottom of the attribute table (Figure 202).
16. Close this attribute table.
149
-------
Attribute table - soilFL057_compreproj:: 20318 / 20318 feature(s) selected — ~ X
MUKEY
hydgrp
-
0
1406997
A/D
1
1407015
NULL
2
1406998
B/D
3
1406983
A/D
4
1406998
B/D
5
1406996
C/D
6
1406979
A/D
7
1407013
A
8
1406998
B/D
9
1406971
A/D
10
1406979
A/D
11
1407011
A
12
1407001
A/D
13
1406996
C/D
14
1406998
B/D
15
1406991
A
16
1407011
A
17
1407011
A
18
1406998
B/D
0
19
1407015
NULL
20
1406998
B/D
21
1406977
A/D
??
1407011
A
0
©
U]
j | | Look for ] hi [ ItJ (_ ^earc^
Show selected only
Search selected only [JC; Case sensitive Advanced search ? Close
Figure 202 Soil layer attribute table, with all attributes selected arid copied to clipboard
17. Click on a second soilmu_a... layerto highlight it in the Layers panel.
Note: the second layer will become the combined shapefile from all the soils layers. The
user must remember which soil layer was highlighted.
18. From the main menu, select Layer > Toggle editing (Figure 203).
File Edit View
Layer Settings Plugins Vector Raster Da
K] d @
B ! C-r: soilmu
¦ :
New ~
Embed Layers and Groups...
Add Vector Layer... Ctrl+Shift+V
v Add Raster Layer... Ctrl+Shift+R
Add SpatiaLite Layer... Ctrl+Shift+L
Add Delimited Text Layer
T
Copy style
Paste style
H Open Attribute Table
Save Edits
f Toggle Editing
Figure 203 Toggle editing for the other soil layer in the Layers panel
19. With the second soilmu_a... shapefile still highlighted, from the main menu select Edit > Paste
Features (Figure 204).
150
-------
Figure 204 Paste Features tool located in the Edit menu
20. Repeat steps 14-16, copying rows, and step 19, pasting them into the selected layer, for the
remaining soil shapefiles.
21. Click Layer > Toggle editing again to stop editing.
22. Click OK when prompted to save changes.
23. in the Layers panel, double click on the combined soil layer to open Layer Properties.
24. From the Fields tab, click the pencil icon to enable Editing mode.
25. Click on the New Column icon to add a new field.
26. In the Add column window (Figure 205):
a. In the Name text box, enter a field name that is 6 characters or less (e.g. "MaxTy").
b. In the Type dropdown list, select Whole number (integer),
c. In the Width text box, enter 1.
d. Click OK.
27. Click OK to close Layer Properties.
Layer Properties - soilmu_a_ffQ57 ? X
Style Labels Fields \ General Metadata Actions Joins * Diagrams
lili
Id
Name
Type
Length
Precision
Comment
Edit widget
Alias
3
MU KEY
String
30
0
Line edit
6
hydrgp
string
80
0
Line edit
^ Add column ? X
Name | MaxTy)
Comment
Type Whole number (integer) ~
integer
Width j 1 ^
Precision
OK Cancel
Restore Default Style
Save As Default
Load Style...
Save Style...
OK ) Cancel
Apply Help
Figure 205 Create a new field in the updated attribute table with the Add column button
151
-------
The new field (e.g. "MaxTy") will appear in the combined soil layer attribute table. This field is
populated based on the "hydgrp" field, which may contain dual soil codes, such as 'A/D', 'B/D', or
'C/D'. These codes denote that the water table can be close to the surface, causing the soil to act as
'D' type. However, when drained, these act as 'A', 'B', or 'C' type soils and therefore should be coded
according to the first letter of the dual code. To avoid assigning these dual codes a "MaxTy"' value of
4, assign the "MaxTy" value for "hydgrp" 'D' first, and then go back to do 'A', 'B', and 'C'.
28. Open the combined soil layer attribute table.
29. In the Look for text box, at the bottom of the attribute table, enter the letter 'D'.
30. From the in dropdown list, choose "hydgrp", and click the Search button (Figure 206).
n
Look for D
in hydgrp ~
Search
Advanced search
?
Close
Figure 206 Search for letter D in the hydgrp field
Note: it may take a few moments for QGIS to select the attributes. Do not close the attribute table
during this time.
31. Open the Field Calculator by clicking the Field Calculator icon in the attribute table.
32. In the Field Calculator window (Figure 207):
a. Check the box next to Only update selected features.
b. Check the box next to Update existing field.
c. Choose the newly created field (e.g. "MaxTy") from the dropdown list.
d. Under the Expression section, type the value 4.
e. Click OK.
^ Field calculator ? X
X Only update selected features
I I Create a new field |ft Update existing field
Output field name | J
Output field type [ Whole number (integer) | ~ | MaxTy | ~ |
Output field width 110 \~^\ Precision |p \-^\
Function List Selected Function Help
Operators
rrmnmnr^immrT
Expression —
4
Output preview:
OK ] Cancel Help
Figure 207 Field Caicuiator window, updating Max_Type_N field with a value of 4
152
-------
33. Repeat steps 30 through 32 to find records with values 'A', 'B', and 'C' in the "hydgrp" field,
and assign the corresponding values 1, 2, and 3 to the "MaxTy" field.
34. Click the pencil icon to toggle Editing mode off and save the edits.
35. Right-click on the soil layer with updated "MaxTy" values and choose Save as.
36. In the Save as window (example shown in Figure 133):
a. In the Format dropdown list, select ESRI Shapefile.
b. In the Save as text box, browse to the desired file path, and name the file
Max_ Type_N. shp.
c. In the CRS dropdown list, choose Selected CRS, and click the Browse button to
locate l/l/GS 84/ Pseudo Mercator.
d. Check the Add saved file to map option.
e. Do not check the Skip attribute creation option.
f. Click OK.
37. In the Layers panel, right-click on Max_Type_N and open the attribute table.
38. Click the pencil icon to enable Editing mode.
39. In the Look /brtext box, type NULL, and from the in dropdown list, choose "hydgrp".
40. Click the Search button (example shown in Figure 206)
41. All the soil polygons without a soil classification are selected. Click the Delete Selected
Features icon to delete these polygons.
42. Close the attribute table.
43. In the Layers panel, double click on Max_Type_N to open Layer Properties.
44. From the Fields tab, select all fields except "MaxTy" and remove them using the Delete
column icon.
45. Click the pencil icon to toggle Editing mode off and save edits.
46. Click OK to close Layer Properties.
The Max_Type_N layer is now complete; next, the values in this layer will be joined to the land use
layer.
Spatially Join Soils to Land Use
After the soil shapefile (e.g. Max_Type_N.shp) is created it must be spatially joined to the land use layer
created in the Create Land Use Data Layer section.
1. If not in the Layers panel, add the land use layer created in the Create Land Use Data Layer
section to the project using the Add vector layer tool (example shown in Figure 126 and Figure
127).
2. Open the Join attributes by location tool (Main Menu > Vector > Data Management Tools >
Join attributes by location, Figure 158).
3. In the Join attributes by location window (Figure 208):
a. In the Target vector layer dropdown list, select the land use layer (e.g.
NLCD_ Tampa_poly_reproj).
b. In the Join vector layer dropdown list, select the updated soils layer (Max_Type_N').
c. In the Attribute Summary section, toggle on Take summary of intersecting features, and
check Mean.
d. In the Output Shapefile text box, browse to or type the file path and desired shapefile
name (e.g. NLCD_MaxTypeN_spatial.shp).
e. Toggle on the Keep all records option.
f. Click OK.
153
-------
^ Join attributes by location ? X
Target vector layer
NLCD_Tampa_poly_reproj T
Join vector layer
Max_Type_N ¦*
Attribute Summary
Take attributes of first located feature
• Take summary of intersecting features
Ml Mean ~ Min ~ Max ~ Sum C Median
Output Shapefile
uildingDatabase_Outputs/QGIS/NLCD_MaxTypeN_spatial.shp
Browse
Output table
Only keep matching records
• Keep all records (including non-matching target records)
0% | OK Close
A
Figure 208 Join attributes by location, and summarize by Mean
Note: depending on the size of the datasets and the computer processing them this spatial join may take
a few hours to complete. Do not close the EPA H20 program during this time.
Troubleshooting Common Errors:
Problem:
A common error in this step results in an
Incorrect field names error (Figure 209).
Three pieces of information help to
understand the cause of this error: (1) Field
names cannot be longer than 10 characters
(2) Attribute Summary by Mean renames
fields by adding MEAN in front of the original
field name (3) This results in field names with
more than 10 characters when the original is
more than 6 characters.
Solution:
The user must replace each of the fields listed in the error message with a new field. Open the
Layer Properties window for the layer and click the pencil icon to start editing. Click on the
New Column icon to add a new field to the fields list (example shown in Figure 205). The new
field name must have 6 or less characters (e.g. "MaxTy") and have the same Type as the field it
is replacing. Open Field Calculator and choose Update Existing Field from the dropdown
list. Select the newly created field (e.g. "MaxTy", example shown in Figure 207). From the Field
and Values dropdown list, double click on the field to be replaced (e.g. "Max_Type_N"). After the
field appears in the Expression box, click OK. Delete the old field from Layer Properties, using the
Delete Column
a
icon. Repeat these steps for each of the fields listed in the error. Save the
changes made to the Layer Properties and retry the Join attributes by location tool.
15*
Incorrect field names X
No output will be created.
Following field names are longer than 10 characters:
MEANMax_Type_N
OK
Figure 209 Incorrect field names error message in QGIS
-------
4. A message box will appear when Join attributes by location is finished. After this message
appears click Close to close the tool.
After the spatial join, the "MaxTy" field in the spatially joined layer will be renamed to "MEANMaxTy"
and will contain average attribute values for each land use polygon. Where a land use polygon does
not overlap any soil polygons, either because they were missing or because they were deleted, the
"MEANMaxTy" value will be NULL. The soil classification type of these NULL polygons is assigned
the most prominent soil type (largest area) in the AOI.
5. From the main menu, select Plugins > Manage Plugins.
6. In the QGIS Plugins Manager window will (Figure 210):
a. In the Filter box, type Statist.
b. The Statist (1.0.0) plugin will appear in the list of plugins. Check the box next to the plugin
name if it is not already checked.
c. Click OK.
^ QGIS Plugin Manager ? X
Filter | statist]
To enable / disable a plugin, click its checkbox or description
v Statist (l.O.O)
^ Calculate and show statistics for a field
Installed in Vector menu/toolbar
y Zonal statistics plugin
— A plugin to calculate count, sum, mean of rasters for each polygon of
a vector layer
Installed in Raster menu/toolbar
_ ZonalStats (0.0.4)
Extended zonal statistics and report generation
Installed in Raster menu/toolbar
Plugin Directory: C:/PR0GRA~2/EPA H20/apps/qgis/pIligins
OK
Select All
Clear All
Cancel
Figure 210 QGIS Plugin Manager window, with the Statist plugin enabled
7. In the layers panel, double click on the spatial join layer (e.g. NLCD_MaxTypeN_spatia!) to
open Layer Properties.
8. From the Fields tab, click the pencil icon to enable Editing mode.
9. Click the New Column icon. In the Add column window (Figure 205):
a. In the Name text box, enter "Max_Type_N".
b. In the Type dropdown list, select Whole number (integer).
c. In the Width text box, enter 1.
d. Click OK.
10. Click the New Column icon again to add a second field. In the Add column window (Figure
205):
a. In the Name text box, enter "Area".
b. In the Type dropdown list, select Decimal number (real).
c. In the Width text box, enter 10, and in the Precision text box, enter 2.
d. Click OK.
155
-------
11. Close Layer properties and open the spatial join layer attribute table.
12. Click the Field Calculator icon. In the Field Calculator window (Figure 211):
a. Check the Update existing field option.
b. In the existing field dropdown list, select "Area".
c. In the Function List list box, expand the Geometry option, and double click on $area.
d. The expression $area will appear in the Expression box.
e. Click OK.
^ Field calculator ? X
Only update selected features
Create a new field X Update existing field
Output field name | |
Output field type [ Whole number (integer) | ~ ] Area
Output field width 110 |-^~] Precision |o f-^-j
Function List Selected Function Help
Operators
=
+ 11 - II / 1
* A
II 11 c
)
Expression
Sarea
Output preview: 1184.9S828125
Cancel
Help
Figure 211 Field Calculator window, used to calculate the area of each polygon
The new "Max_Type_N" fieid is populated based on the averaged values in the "MEANMaxTy" field.
However, values in "MEANMaxTy" must be rounded to the nearest integer for the "Max_Type_N" field.
For example, for 0 < "averaged values" < 1.5, "Max_Type_N" = 1. This is completed by:
13. In the Layers panel, right-click the spatial join layer and open the attribute table.
14. In the attribute table click on the Advanced Search button (Figure 212).
m
Look for in
~
Search
Advanced search
Close
Figure 212 Advanced search button in attribute table
156
-------
15. The Search Query Builder window will open. In the Search Query Builder window (Figure 213):
a. In the SQL where clause text box, type the expression: MEANMaxTy > 0 AND
MEANMaxTy< 1.5
b. Click OK.
& Search qutiy buitdef ? X
f*CD_MaxTyp«H_5p8Sal
Ptetdf Values
Id
grid-code
MEANMtxTy
COWT
Ma*_Type_N
I Sarpe ill
Ct>er«;c5
¦ < > LIKE % W NOTIN
<¦ >- |- UJffi AN) OR HOT
SQL n^ierc clause
MEAWjkTY > 0 AND tCMMWiy < 1.5
Jest £lear £ave... ^osd... Caned Halo
Figure 213 Search query builder in EPA H20, used to select averaged values between 0 and 1.5
Please note, this selection may take a long time to process. Do not close the attribute table/program.
16. From the spatial join layer attribute table, open the Field Calculator window (example shown
in Figure 207f.
a. Check the Only update selected features option.
b. Check the Update existing field option and select "Max_Type_N" from the dropdown list.
c. Type 1 in the Expression box.
d. Click OK.
17. With the selection still highlighted, from the main menu select Vector > Statist > Statist.
18. In the Statist: Field statistics window (Figure 214):
a. In the Input vector layer dropdown list, select NLCD_MaxTypeN_spatial.
b. Check the Use only selected features option if not already checked.
c. In the Target field dropdown list, select Area.
d. Click OK. The statistics for the selection will generate within the window.
e. From the Statistics output, copy down the Sum value (e.g. 7.5714e9).
157
-------
^ Statist: Field statistics
X
Input vector layer: NLCD_MaxTypeN_spatial
'XI Use only selected features
Target field: Area
Q Enable statistics for text fields
Statistics output:
Frequency distribution
Parameter
Value
Count
282021
Unique values
114704
Minimum value
735.33
Maximum value
2.06326e+09
Range
2.06326e+09
Sum
7.57144e+09
Mean value
26847.1
Median value
2311.19
Standard deviat...
4.08232e+06
Coefficient of V...
152.058
W0000
50000
[00000
50000
00000
50000
Close
v*
•v0
Area
le9
^ o o *
m
Xmin 0.00 ^
I I Show grid
Refresh
Xmax 0.00 |-^~|
| I As plot
Figure 214 Statist: Field statistics window displaying the Area statistics for the first selection
19. Close the Statist window and clear the current attribute table selection.
20. For each selection in Table 8, repeat steps 13-18, setting the selection using the expression in
Search Query Builder and the "Max_Type_N" field value using Field Calculator. Then find the
total area of each selection using Statist and write down the sums for comparison.
Table 8 Expressions for selections and corresponding field calculations
Expression for Selection
"Max Type N" Value
MEANMaxTy > 0 AND MEANMaxTy < 1.5
1
MEANMaxTy >= 1.5 AND MEANMaxTy " < 2.5
2
MEANMaxTy >= 2.5 AND MEANMaxTy < 3.5
3
MEANMaxTy >= 3.5 AND MEANMaxTy <= 4
4
21. Compare the areas for each soil type, and determine which classification is most prominent.
The sum is expressed in scientific notation, and the units are in meters (i.e. units of the
coordinate system). In this example, the total area for each soil type ("Max_Type_N" value) is
as follows:
a. 1 = 7,571,440,000 m
b. 2 = 415,287,000 m
c. 3 = 28,464,900 m
d. 4 = 17,078,600 m
In this example, the most common soil type is "Max_Type_N" = 1. This soil type will be used
to assign the "Max_Type_N" values where "MEANMaxTy" is NULL.
22. In the Layers panel, right-click the NLCD_MaxTypeN_spatial layer and open the attribute
table.
23. In the attribute table (Figure 215):
a. In the Look for text box, type NULL.
b. In the in field dropdown list, select "MEANMaxTy".
c. Click Search.
158
-------
Look for NULL
in MEANMaxTy
Search
Advanced search
Close
Figure 215 Look for NULL values in the MEANMaxTy field
24. Click the Field Calculator icon (example shown in Figure 207):
a. Check the Only update selected features option.
b. Check the Update existing field option and select "Max_Type_N" from the dropdown list.
c. In the Expression box, enter the number corresponding to the most prominent soil from
step 21 (in the example this was 1).
d. Click OK.
Database creation is continued in the Update ES Coefficients section.
159
-------
Update ES Coefficients
EPA H20 incorporates Tree Canopy, Air Quality, Carbon Sequestration, and Denitrification
coefficients for each land use type. These coefficients are used to calculate ES values for air pollution
removal, carbon sequestration, and nitrogen removal from water.
The land use layer attribute table (Figure 216) will include fields for ES coefficients ("Canopy",
"CarbonFixe", and "denitrific") and ES values ("waterRet", "stabClirn", and "usWat"). These fields are
populated by joining the land use layer to a lookup table with the same land use classification (e.g.
NLCD); as described in the Joining Lookup Table section. The fields for ES monetary values can be
updated by Modifying ES Algorithm Values; as described in the Edit Scenarios section. National averages
for each ES coefficient are provided in the supplemental lookup table (Appendix A: Supplemental NLCD
Lookup Table) and may be imported to create a database from NLCD classified land use. However, user
database accuracy may be improved if the default national averages are updated on a more local scale.
To update coefficients, changes are first made to the lookup table, then changes are joined to the land
use layer. The ES coefficients in the lookup table and land use table must match. Either Esri ArcMap
software or QGIS can be used to update the ES coefficients. The procedure for both software
applications is explained in this section.
Table
lookUPvafsJsialienalSupp.csv
eanopyVal
A
B
C
0
LEVI
waterfiet
stabClirn
usWat
u sable wat
St&bleClim
UsAirDol
CM
Flood Prot
~
10
10
10
10
5
2
37
3
<}Wt*
*Nut»
•libit.
54
70
80
85
1
2
37
3
*Nuit>
61
75
63
87
1
2
37
3
«Mut»
«Nul»
36
56
70
77
3
2
37
3
«Mul»
39
61
74
80
2
2
37
3
< Nul>
«Nuilt»
71
81
es
91
2
2
37
3
«NuB»
49
65
72
80
6
2
37
3
«Nul»
«Hul>
< Nut>
<
H 4
1 ~ M
lookUPvars_Nation*ISupp.esv
(Ooul of 15 Selected)
Figure 216 Supplemental lookup table, with ES National Average fields; these fields may be updated to represent
more local values
Tree Canopy
Download Tree Canopy Data
This section illustrates the step-by-step procedure for downloading NLCD 2011 Percent Tree Canopy
(cartographic) data from the USGS National Map. This data is used to update the "Canopy" field in the
lookup table, which is needed to calculate the "Us_Air_Dol" field in the Joining Lookup Table section.
1. Navigate to https://www.mrlc.gov/viewer/ as shown in Figure 217.
160
-------
MRLC
Celebrating 20+ years of Partnership
Multi-Resolution Land Characteristics
Consortium
| All
New Map Window
i Dataset
M Hydrography
M NLCD Impervious Surface
M NLCD Impervious Descriptor
fei NLCD Tree Canopy
fei NLCD Land Cover
to NLCD Science Research Products
fci Orthoimagery
i Boundaries
S 0 National Atlas States
0 National Atlas Counties 2001
0 Historic Mapping Zones
i Base Layers
V Stamen Terrain
All NLCD Land Cover 2016 CONUS Land Cover
SO® -I®®
© Q © Tools
-1277251, 70 7860
Spatial Locking Tool
All NLCD Land Cover 2016 CONUS
Arrange Windows Tool
~
Figure 217 MRLC website, download NLCD Canopy Cover by AOI
2. Click-and-drag on the National Map to pan and use the Zoom in icon to zoom in to the user's AOI
(e.g. Tampa Bay).
3. In the Contents section, under the NLCD Tree Canopy dropdown list, check the 2011 CONUS
Tree Canopy option (or the preferred display year).
4. From the map viewer toolbar, click the Open Data Download Tool
bounding box around the user's AOI (Figure 218).
©
icon and click to draw a
All
3
New Map Window
i Dataset
¦l Hydrography
to NLCD Impervious Surface
-to NLCD Impervious Descriptor
m NLCD Tree Canopy
hll 0 2016 CONUS Tree Canopy
h Q 0 CONUS Tree Canopy Change
I- -y 0 2011 CONUS Tree Canopy
I- Q 0 2016 AK Tree Canopy
0 AK Tree Canopy Change
0 2011 AK Tree Canopy
| _ 0 2016 HI Tree Canopy
}-' ~ 0 HI Tree Canopy Change
0 2011 HI Tree Canopy
0 2016 PR Tree Canopy
j 0 PR Tree Canopy Change
1 ~ 0 2011 PR Tree Canopy
to NLCD Land Cover
to NLCD Science Research Products
to Orthoimagery
AO NLCD Tree Canopy 2011 CONUS Tree Canopy
\x\ (§] ® @ |©J [®|
fwP
Figure 218 MRLC viewer with bounding box drawn around Tampa Bay AOI
5. Under the Data Download dropdown list, check the Tree Canopy option and toggle All Tree
Canopy Years (Figure 219).
161
-------
Data Download
©
Select Categories:
~ Science Products
$ Tree Canopy
0 All Tree Canopy Years
O 2016 Tree Canopy ONLY
Qj Land Cover
Qj Impervious
Latitude (dd):
27.26936 29.62667
Longitude (dd):
-83.15415 -80.29508
user@epa.gov
1 Clear Download
Figure 219 Data Download dropdown list
6. In the Email text, box, enter the user's email address (e.g. user@epa.gov), then click Download.
7. A notification will appear indicating the download request has been sent. Click OK (Figure 220).
www.mrlc.gov says
Your download request has successfully been sent and will be
processed for you within 24 hours. You will receive an e-mail with
instructions on retrieving your data. Thank you.
OK
Figure 220 MRLC request notification
8. The download link will be emailed to the user by the USGS server. Click the first link in the email
to download the NLCD Canopy Cover zip file.
9. Save the zip file to the computer and unzip the contents to a known location.
NLCD Canopy cover raster values represent the percent canopy cover for each 30m x 30m raster cell.
EPA H20 requires average canopy cover for each land use classification. If using a land use
classification other than NLCD the land use classification may have a different resolution (e.g. the
FLUCCS 2006 classification used in the Tampa Bay dataset has a 5-meter resolution) resulting in a
difference in canopy cover sampling. The next section illustrates the averaging of percent canopy
cover for each land use type, using either Esri ArcGIS (Using ArcGIS) or QGIS (Using QGIS).
Averaging canopy cover over larger areas better accounts for local variability and helps to limit errors
due to differences in sampling.
162
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Usir
This section illustrates how to update the % Canopy Cover ("Canopy" field) for the user's area of interest
using Esri ArcGIS.
Note: this step requires the Spatial Analyst extension in ArcMap. If the user's ArcGIS license does not
include this extension, the user will skip this step and use the default national averages already in the
"Canopy" field for calculations. These average canopy cover values come from overlaying NLCD land
use and cartographic canopy cover. It is important to note that the cartographic canopy cover differs
from the analytical, in that it has already been corrected for impervious surfaces.
Although the following process is shown using an NLCD land use dataset, the same steps can be
performed using an alternative land use vector dataset (e.g. FLUCCS). Simply replace the "gridcode" field
with the appropriate land use code field where required.
1. Download and unzip the Canopy Cover data to a known location, as shown in the Download Tree
Canopy Data section.
2. Open your existing ArcGIS map document file (.mxd), or create one following the steps outlined in Set
Up ArcGIS Map Document.
3. Use the Add Data icon to navigate to the Canopy Cover 2011 .tif dataset (or most recent year).
Select it and click Add to add it as a layer in the Table of Contents.
4. If using a new map document, the shapefile created in the Spatially Join Soils to Land Use section
(e.g. NLCD_MaxTypeNJoin) must be located and added in the same way.
5. From the ArcToolbox window, navigate to and open the Project Raster tool, (ArcToolbox > Data
Management Tools > Projections and Transformations > Raster > Project Raster, Figure 221).
6. In the Project Raster window (Figure 222):
a. In the Input Raster dropdown list, select the NLCD canopy cover .tif (e.g.
NLCD_2011_Tree_Canopy_L48_20190831_RTDBmKOdx72K3rodhLUd.tiff).
b. In the Output Raster Dataset text, box, name the output with a .tif extension (e.g.
Canopy_reproj.tif) and the file path.
c. Click the Spatial Reference icon to set the Output Coordinate System to
WGS_1984_Web_Mercator_Auxiliary_Sphere, located under the l/l/or/d folder in Projected
Coordinate Systems. Alternatively, search for it by typing 3857 into the search box.
d. A Geographic Transformation is required to reproject the land use dataset. In the dropdown
list, choose WGS_1984_(ITRF00)_To_NAD_1983, if not already listed in the box.
e. If the wrong Geographic Transformation is listed, click on the name, and click the X button to
remove it.
f. Click OK to run Project Raster.
163
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ArcToolbox
-a x
B Data Management Tools
B Archiving
B %< Attachments
E Data Comparison
B Distributed Geodatabase
B %s Domains
B Feature Class
B %s Features
B %3 Fields
B File Geodatabase
B General
B Generalization
El Geodatabase Administration
B Geometric Network
B Graph
B Indexes
B %s Joins
B %! LAS Data set
E) Layers and Table Views
B Package
B Photos
B ^ Projections and Transformations
B l%j Raster
\ Flip
*... Mirror
Register Raster
Figure 221 Location of the Project Raster
too! in ArcToolbox
Project Raster
~
X
Input Raster
| NLCD_2011_Tree.Canopy_L48_20190831_RTDBmK0dx72K3rodhLUd.tiff
Input Coordinate System (optional)
Albers_Conical_Equal_Area
Output Raster Dataset
| C:\UsersVrijackson\.qgis\Q.Q.3\Tampa_H20V32\Canopy_reproj.tif |
Output Coordinate System
I WGS_1984_Web_Mercator_Auxiliary_Sphere
E3
L—J
ef
C Vertical (optional)
Geographic Transformation (optional)
Resampling Technique (optional)
Cancel
Environments..
Show Help >>
Figure 222 Project Raster tool window
7. Check that the Spatial Analyst extension is enabled. From the main menu, click Customize >
Extensions,.., and confirm that the Spatial Analyst option is checked. Click Close.
8. Use the Tabulate Area tool to create a table summarizing the re-projected canopy cover layer (e.g.
Canopy_reproj) by the classification in the soil/land use layer (e.g. NLCD_MaxTypeNJoin). From the
ArcToolbox window, navigate to and open the Tabulate Area tool (ArcToolbox > Spatial Analyst Tools
> Zonal > Tabulate Area, Figure 223).
9. In the Tabulate Area window (Figure 224):
a. In the Input raster or feature zone data dropdown list, select the soil/land use layer (e.g.
NL CD_ Max TypeNJoin).
b. In the Zone field dropdown list, select "gridcode".
c. In the Input raster or feature class data dropdown list, select the re-projected canopy layer
(e.g. Canopy_reproj).
d. In the Class field dropdown list, select "Value".
e. In the Output table text box, name the output table (e.g. Canopy_TabArea) and file path.
f. Click OK to run Tabulate Area.
164
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ArcToolbox
~ x
El Spatial Analyst Tools
El Conditional
S Density
B Distance
0 Extraction
E ^ Generalization
S Groundwater
B Hydrology
B Interpolation
El Local
El l%< Map Algebra
El Math
E Multivariate
B %3 Neighborhood
B Overlay
E ^ Raster Creation
B Reclass
El Segmentation and Classification
E ^ Solar Radiation
S Surface
B Zonal
Tabulate Area
Zonal Fil
Figure 223 Location of the Tabulate Area
tool in ArcToolbox
. Tabulate Area
~
Input raster or feature zone data
| N LC D_M axTyp eN j o i n
"31
£3
Zone field
| gridcode
Input raster or feature dass data
| Canopy_reproj.tif
~3
Class field
| Value
Output table
Tampa_H20p2_Tampa^uildingDatabase_Outputs\ArcMap\Canopy\Canopy_TabArea
Processing cell size (optional)
30
|B|
£3
Cancel
Environments..
Show Help >>
Figure 224 Tabulate Area tool window in ArcMap
10. In the Table of Contents, right-click to open the output table (e.g. Canopy_TabArea).
11. Add a new field in the table (example shown in Figure 179 and Figure 180•):
a. In the Name text box, type the preferred field name (e.g. "AvgCC").
b. In the Type dropdown list, select Short Integer.
c. Click OK.
12. In the attribute table, right-click on the new field, and choose Field Calculator.
13. In the expression box, copy and paste the following equation, then click OK (Figure 225):
(([VALUE_1] * 1) + ([VALUE_2] * 2) + ([VALUE_3] * 3) + ([VALUE_4] * 4) + ([VALUE_5] * 5) +
([VALUE_6] * 6) + ([VALUE_7] * 7) + ([VALUE_8] * 8) + ([VALUE_9] * 9) + ([VALUE_10] * 10) +
([VALUE_11] *11) + ([VALUE_12] * 12) + ([VALUE_13] * 13) + ([VALUE_14] * 14) + ([VALUE_15] * 15) +
([VALUE_16] * 16) + ([VALUE_17] * 17) + ([VALUE_18] * 18) + ([VALUE_19] * 19) + ([VALUE_20] * 20) +
([VALUE_21] * 21) + ([VALUE_22] * 22) + ([VALUE_23] * 23) + ([VALUE_24] * 24) + ([VALUE_25] * 25) +
([VALUE_26] * 26) + ([VALUE_27] * 27) + ([VALUE_28] * 28) + ([VALUE_29] * 29) + ([VALUE_30] * 30) +
([VALUE_31] * 31) + ([VALUE_32] * 32) + ([VALUE_33] * 33) + ([VALUE_34] * 34) + ([VALUE_35] * 35) +
([VALUE_36] * 36) + ([VALUE_37] * 37) + ([VALUE_38] * 38) + ([VALUE_39] * 39) + ([VALUE_40] * 40) +
([VALUE_41] * 41) + ([VALUE_42] * 42) + ([VALUE_43] * 43) + ([VALUE_44] * 44) + ([VALUE_45] * 45) +
([VALUE_46] * 46) + ([VALUE_47] * 47) + ([VALUE_48] * 48) + ([VALUE_49] * 49) + ([VALUE_50] * 50) +
([VALUE_51] * 51) + ([VALUE_52] * 52) + ([VALUE_53] * 53) + ([VALUE_54] * 54) + ([VALUE_55] * 55) +
([VALUE_56] * 56) + ([VALUE_57] * 57) + ([VALUE_58] * 58) + ([VALUE_59] * 59) + ([VALUE_60] * 60) +
([VALUE_61] * 61) + ([VALUE_62] * 62) + ([VALUE_63] * 63) + ([VALUE_64] * 64) + ([VALUE_65] * 65) +
([VALUE_66] * 66) + ([VALUE_67] * 67) + ([VALUE_68] * 68) + ([VALUE_69] * 69) + ([VALUE_70] * 70) +
([VALUE_71] * 71) + ([VALUE_72] * 72) + ([VALUE_73] * 73) + ([VALUE_74] * 74) + ([VALUE_75] * 75) +
([VALUE_76] * 76) + ([VALUE_77] * 77) + ([VALUE_78] * 78) + ([VALUE_79] * 79) + ([VALUE_80] * 80) +
([VALUE_81] * 81) + ([VALUE_82] * 82) + ([VALUE_83] * 83) + ([VALUE_84] * 84) + ([VALUE_85] * 85) +
([VALUE_86] * 86) + ([VALUE_87] * 87) + ([VALUE_88] * 88) + ([VALUE_89] * 89) + ([VALUE_90] * 90) +
([VALUE_91] * 91) + ([VALUE_92] * 92) + ([VALUE_93] * 93) + ([VALUE_94] * 94) + ([VALUE_95] * 95) +
([VALUE_96] * 96) + ([VALUE_97] * 97) + ([VALUE_98] * 98) + ([VALUE_99] * 99) + ([VALUE_100] *
165
-------
100))/([VALUE_0] + [VALUE_1] + [VALUE_2] + [VALUE_3] + [VALUE_4] + [VALUE_5] + [VALUE_6] +
[VALUE_9] + [VALUE_10] + [VALUE_11] + [VALUE_12] + [VALUE_13] +
[VALUE_7] +
[VALUE_14] ¦
[VALUE_21] ¦
[VALUE_28] ¦
[VALUE_35] ¦
[VALUE_42] ¦
[VALUE_49] ¦
[VALUE_56] ¦
[VALUE_63] ¦
[VALUE_70] ¦
[VALUE_77] ¦
[VALUE_84] ¦
[VALUE_91] ¦
[VALUE_98] ¦
[VALUE_8] +
n [VALUE_15]
n [VALUE_22]
n [VALUE_29]
n [VALUE_36]
n [VALUE_43]
n [VALUE_50]
n [VALUE_57]
n [VALUE_64]
n [VALUE_71]
n [VALUE_78]
n [VALUE_85]
n [VALUE_92]
n [VALUE_99]
[VALUE_16] +
[VALUE_23] +
[VALUE_30] +
[VALUE_37] +
[VALUE_44] +
[VALUE_51] +
[VALUE_58] +
[VALUE_65] +
[VALUE_72] +
[VALUE_79] +
[VALUE_86] +
[VALUE_93] +
[VALUE_100])
[VALUE_17]
[VALUE_24]
[VALUE_31]
[VALUE_38]
[VALUE_45]
[VALUE_52]
[VALUE_59]
[VALUE_66]
[VALUE_73]
[VALUE_80]
[VALUE_87]
[VALUE_94]
[VALUE_18]
[VALUE_25]
[VALUE_32]
[VALUE_39]
[VALUE_46]
[VALUE_53]
[VALUE_60]
[VALUE_67]
[VALUE_74]
[VALUE_81]
[VALUE_88]
[VALUE_95]
[VALUE
[VALUE
[VALUE
[VALUE
[VALUE
[VALUE
[VALUE
[VALUE
[VALUE
[VALUE
[VALUE
[VALUE
19]
26]
33]
40]
47]
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61]
68]
75]
82]
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96]
[VALUE_20]
[VALUE_27]
[VALUE_34]
[VALUE_41]
[VALUE_48]
[VALUE_55]
[VALUE_62]
[VALUE_69]
[VALUE_76]
[VALUE_83]
[VALUE_90]
[VALUE_97]
Field Calculator
Parser
(§) VB Script
Fields:
O Python
Rowid
a
GRIDCODE
VALUEJD
VALUE_5
VALUE_6
VALUE_7
VALUE_8
VALUE_9
VALUE_10
V
Type:
® Number
O String
ODate
I I Show Codeblock
AVGCC =
000000
(([VALUE_1] * 1) + ([VALUE_2] * 2) + {[VALUE_3] * 3) + ([VALUE_4] * 4) +
C[VALUE_5] * 5) + {[VALUE_6] * 6) + ([VALUE_7] * 7) + ([VALUE_8] * 8) +
QVALUE_9] * 9) + ([VALUE_10] * 10) + C[VALUE_11] * 11) + ([VALUE_1Z] * 12) +
GVALUE_13] * 13) + ([VALUE_14] 114) + ([VALUE_1SI * 15) + QVALUE_16] * 16) +
C[VALUE_17| 117) + ([VALUE_18] * 18) + ([VALUE_19] 1 19) + ([VALUE_20] * 20) +
([VALUE_21] * 21) + ([VALUE_22] * 22) + {[VALUE_23] * 23) + ([VALUE_24] * 24) +
([VALUE_25] 125) + ([VALUE_26] * 26) + {[VALUE_27] * 27) + QVALUE_28] * 28) +
C[VALUE_29] * 29) + ([VALUE_30] * 30) + <[VALUE_31] * 31) + C[VALUE_32] * 32) +
QVALUE_33| * 33) + C[VALUE_34] * 34) + ([VALUE_35] * 35) + QVALUE_36] * 36) +
C[VALUE_37] * 37) + ([VALUE_38] * 38) + ([VALUE_39] * 39) + QVALUE_40] * 40) +
([VALUE_4lj "= 41) + [[VALUE_42] * 42) + C[\i'ALUE_43] * 43) + ([VALUE_44] 144) +
([VALLJE_45] * 45) + ([VALUE_46] * 46) + ([VALUE_47I * 47) + ([VALUE_48] * 48) +
About calculating fields
Clear
Load...
Save..,
Cancel
Figure 225 Field Calculator, with % Canopy equation entered
The new field should contain values between 0 and 100%, indicating the average percent tree canopy
cover in each land use type.
Troubleshooting Common Errors:
Problem:
An error may occur during field calculation as shown in Figure 226. The message references the
Geoprocessing Results window, to open this window from the main menu click Geoprocessing > Results.
The Results window may list an error message that states A field name was not found or there were
unbalanced quotation marks (Figure 227). This may occur if the canopy cover for the user's area of
166
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interest does not contain all values from 0 to 100. It may also appear if one "Value" field contains all
zeros.
Field Calculator
X
There was a failure during processing, check the Geoprocessing Results window
for details.
Figure 226 Field Calculator processing error window, referencing the Geoprocessing Results window
Results -f x
Q
B tj Calculate Field [115237_OS13201S]
IH Output Feature Class: canopy_tabarea
El o Inputs
0 Environments
0 QD Messages
[J] Executing: CalculateField canopy_tabarea AVGCC {[[VALUEJ] * 1) + ([VALUE_2] * 2)
© Start Time: Mon Aug 13 11:52:36 2018
A Afield n amewas not found orthere were unbalanced quotation marks.
ERROR999999: Error executing function.
© Failed to execute (CalculateField).
(J) Failed at Mon Aug 13 11:52:37 2018 (Elapsed Time: 0.49 seconds)
ft Shared
Figure 227 Results window in ArcMap, with the Messages error shown
Solution:
Open the Tabulate Area table and confirm that fields "Value_0" through "Value_100" appear. If a
field is missing, it must be removed from both parts of the Field Calculator equation. For example,
the NLCD canopy cover for Tampa Bay does not contain values 1-4. These values must be
removed from the equation above. The expression for Tampa Bay will start with (([VALUE_5] * 5)
+ ... and will divide by /([VALUE_0] + [VALUE_5] + ... in the second half of the equation.
14. Use the Add Data " icon to navigate to the lookup table with .dbf extension (e.g. supplemental
lookup table exported from Appendix A: Supplemental NLCD Lookup Table) and add the table to the
Table of Contents.
15. Right click on the lookup table and open the Join tool (example shown in Figure 183).
16. In the Join Data window (example shown in Figure 184)\
a. In the first dropdown list, select Join attributes from a table.
b. In the Choose the field in this layer that the join will be based on dropdown list, select
"GRIDCODE".
c. In the Choose the table to join to this layer dropdown list, select the Tabulate Area table
(e.g. Canopy_TabArea).
d. In the Choose the field in the table to base the join on dropdown list, select "GRIDCODE".
e. Under Join Options, toggle the Keep all records option on.
f. Click OK.
167
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17. Open the lookup table, locate the "Canopy" field, and open the Field Calculator.
18. In the Field Calculator window (Figure 228):
a. In the Fields list box, double click on the new field name (e.g. Canopy_TabArea:AVGCC).
b. The new field should appear in the expression box. Click OK.
Field Calculator
Parser
® VB Script
Fields:
O Python
canopyjabarea: VALUE_94
canopy_tabarea: V ALUE_9 5
canopy _tabarea: VALUE_96
canopy _tabarea: V ALUE_97
canopy Jabarea: V ALUE_98
canopyjabarea: V ALUE_99
canopy _tabarea: VALUE_100
canopyjabarea: AVGCC
Type:
® Number
O String
0 Date
Functions:
Abs ( )
Atn ( )
Cos ( )
Exp [ )
Fix C )
Int( )
Log ( )
Sin C )
Sqr { )
Tan( )
I I Show Codeblock
lookUPvars_supplemental. Canopy =
000000
About calculating fields
Clear Load..
I I
Cancel
Figure 228 Field Calculator window, with the AvgCC field as the expression
19. Right click on the lookup table and choose Joins and Relates > Remove Join(s) >Tabulate Area table
(e.g. Canopy_TabArea, Figure 229).
Table Of Contents
B & Layers
q ~
~
m c°py
X Remove
J Open Attribute Table
Joins and Relates
£j> Zoom To Layer
Zoom To Make Visib
Visible Scale Range
Join..
Remove Join(s)
Relate...
Remove Relate(s) ~
canopyjabarea
Remove All Joins
Figure 229 Location of the Remove Join tool, in the Table of Contents
Although averaging canopy cover helps to limit errors, some manual corrections may be necessary.
One common instance of this is seen with aquatic land use types. Whereas aquatic areas are known
to be covered in water bordering areas with trees may cause the land use type to be assigned a small
percent canopy cover, especially when there are differences in resolution. These errors were
corrected in the lookup table by adjusting the canopy cover value to zero. The following steps
illustrate how to zero out the "Canopy" value for NLCD Open Water.
168
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20. Open the supplemental lookup table, locate the row for Open Water, and click the to the left of that
row to select it (the entire row will be highlighted in blue when selected).
21. With Open Water selected, right-click the "Canopy" field and open the Field Calculator.
22. In the Field Calculator window (example shown in Figure 228):
a. In the expression box, type 0
b. Click OK.
The average percent canopy cover for the user's AOI has replaced the national averages in the "Canopy"
field of the lookup table, and the canopy cover for Open Water has been corrected. This updated field will
be used to calculate the "Us_Air_Dol" field in the Field Calculations section.
Usir
This section illustrates how to update the % Canopy Cover ("Canopy" field) for the user's area of interest
using QGIS.
Although the following process is shown using an NLCD land use dataset, the same steps can be
performed using an alternative land use vector dataset (e.g. FLUCCS) and a lookup table with
corresponding land use classes (e.g. the original Qspatialite lookup table). Simply replace the "gridcode"
field with the appropriate land use code field where required.
1. Download and unzip the Canopy Cover data, as shown in the Download Tree Canopy Data
section.
2. Open your existing QGIS map document file (.qgs), or create one following the steps outlined
in Set Up QGIS Map Document.
3. From the Layer menu open the Add Raster Layer window (Main Menu > Layer > Add Raster
Layer, Figure 145).
4. Navigate to the cartographic canopy cover data and add the 2011 .tif file (or most recent
year) to the Layers panel (e.g.
NLCD_2011_Tree_Canopy_L48_20190831_RTDBmKOdx72K3rodhLUd.tiff).
5. From the Layer menu open the Add Vector Layer window (Main Menu > Layer > Add Vector
Layer, Figure 126).
6. In the Add vector layer window, click Browse to locate and select the soil/land use layer (e.g.
NLCD_MaxTypeN_spatial) previously created in the Spatially Join Soils to Land Use section.
Click Open to add this layer to the map document.
7. From the Raster menu, open the Warp (Reproject) tool (Main Menu > Raster > Projections >
Warp (Reproject), Figure 146).
8. In the Warp (Reproject) window (example shown in Figure 148):
a. In the Input file dropdown list, select the NLCD canopy raster (e.g.
NLCD_2011_Tree_Canopy_L48_20190831_RTDBmKOdx72K3rodhLUd.tif!).
b. Next to the Output file, click Select to select a file path and name for the output (e.g.
Canopy_reproj.tif). Be sure to name the output with a .tif extension.
c. Check the Source SRS box, and click Select to open the Select the source SRS window.
i. Under the Recently used coordinate reference systems section, choose the * Generated
CRS (+proj = aea...) SRS (Figure 147).
ii. Click OK.
d. Check the Target SRS box and click Select to open the Select the target SRS window.
e. In the Filter box, type 3857, and under Coordinate reference systems of the world, choose
l/l/GS 84/ Pseudo Mercator. Click OK.
f. Check Load into canvas when finished.
g. Click OK.
169
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9. From the Raster menu, open the Zonal Statistics tool (Main Menu > Raster > Zonal Statistics
> Zonal Statistics).
10. In the Dialog window (Figure 230):
a. In the Raster layer dropdown list, select the re-projected canopy raster (e.g. Canopy_reproj).
b. In the Polygon layer containing the zones dropdown list, select the soil/land use layer (e.g.
NLCD_MaxTypeN_spatial).
c. In the Output column prefix text box, enter LU.
d. Click OK.
Dialog
Raster layer:
Canopy_reproj
Polygon layer containing the zones:
N LCD_M axTyp e N_sp ati a I
Output column prefix:
X
LU
OK
Cancel
Figure 230 Zonal Statistics Dialog window, with LU designated as the Output column prefix
This tool may take some time to process. Do not close the Dialog window until processing is complete.
Once finished, the soil/land use layer (e.g. NLCD_MaxTypeN_spatial) will contain three new fields:
"LUcount", "LUsum", and "LUmean".
11. Open the soil/land use attribute table and click the pencil icon
to start an edit session.
12. Click the Add column icon to add a new field in the attribute table.
13. In the Add column window (example shown in Figure 205):
a. In the Name field, type Area.
b. In the Type dropdown list, select Decimal number (real).
c. In the Width text box enter 20 and in the Precision text box enter 2.
d. Click OK.
14.
15.
Click the Field Calculator icon
to open the Field Calculator window.
16.
17.
18.
19.
In the Field Calculator window (example shown in Figure 161):
a. Check Update existing field option.
b. In the Field dropdown list, select the "Area" field.
c. Click the Geometry option to open the dropdown list, and double click on $area.
d. $area will appear in the Expression box. Click OK.
Click the Add column icon again to add a second field.
In the Add column window:
a. In the Name field, enter the desired field name (e.g. new_field)
b. In the Type dropdown list, select Decimal number (real).
c. In the Width text box enter 20, and in the Precision text box enter 2.
d. Click OK.
Click the Field Calculator icon again to open the Field Calculator.
In the Field Calculator window:
170
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a. Select the Update existing field option.
b. In the Field dropdown list, select the new field (e.g. "new_field").
c. Click the Fields and Values option to open the dropdown list.
d. Double click on the "Area" field from the list; the name should appear in the Expression box.
e. Click on the multiply (*) operator; it should appear in the Expression box.
f. Double click on the "LUmean" field from the list; the name should appear in the Expression
box. The full expression is: "Area" * "LUmean"
g. Click OK.
20. Click the pencil icon to turn off editing and save changes to the attribute table.
21. In the soil/land use attribute table (e.g. NLCD_MaxTypeN_spatial), click on the Advanced search
tool (as shown in Figure 212).
22. In the Search query builder window (example shown in Figure 213):
a. In the Fields list, double click the "gridcode" field; the name should appear in the Expression
box.
b. Click the Equals (=) operator; it should appear in the Expression box.
c. Under the Values option, click the All button; the list of all gridcode values will appear.
d. Double click on the first code (this is gridcode 11 with NCLD data). The full expression is:
gridcode = 11
e. Click OK.
23. In the attribute table, click the Move selection to top icon to view the selected features.
24. While leaving the attribute table open, open the Basic Statistics tool (Main Menu >Vector>
Analysis Tools > Basic statistics).
25. In the Basic statistics window (Figure 232):
a. In the Input Vector Layer dropdown list, select the soil/land use layer (e.g.
NLCD_MaxTypeN_spatial).
b. Check the Use only selected features option if not already checked.
c. In the Target field dropdown list, select the field created in step 19 (e.g. "new_field").
d. Click OK.
The statistics output will be listed in the Basic statistics window after the tool is run (Figure 231).
171
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d f
asics statistics
Press Ctrl+C to copy results to the clipboard
X
Input Vector Layer
NLCD_MaxTypeN_spatial
X Use only selected features
Target field
inew field
i ~
Statistics output
OK
0%
Figure 232 Basic statistics window before the
Statistics output is run
Close
A
Q Basics statistics
Input Vector Layer
NLCD_MaxTypeN_spatial
X Use only selected features
Target field
new_field
Statistics output
X
Parameter
value
*
Mean
1320254.71986
StdDev
6842916.86111
Sum
1804788202.05
Min
0.0
A.
~
__
Press Ctrl+C to copy results to the clipboard
OK
0%
Close
.A
Figure 231 Basic statistics window, with Statistics
output gridcode 11 in new_fieid
26. Copy down the Sum value (e.g. 1,804,788,202.05) into a spreadsheet. This value will be used in
a later field calculation.
27. In the same Basic statistics window, change the Target field to "Area".
28. Click OK to run a new statistical output.
29. Copy down the Sum value into the same spreadsheet. This value will be used in a later field
calculation.
30. Repeat steps 21-29 above for each gridcode value:
a. Select each gridcode individually in the Search query builder window.
Copy the Sum value for the "new_field" and "Area" fields in the Basic statistics window for
each selection.
It is recommended that the user create a table of the gridcodes and sums, to keep the values
organized for later calculations.
b.
c.
Please note: the sum of the "Area" field for each gridcode is also needed to update the Carbon
Sequestration (Using QGIS section) and Denitrification coefficients. It is strongly recommended to save
the Sum values for each gridcode in Excel to avoid repeating the steps above.
31. Add the supplemental lookup table to the QGIS Layers panel following the QGIS directions in
Appendix A: Supplemental NLCD Lookup Table.
32. Right-click and open the lookup table from the Layers panel.
0
33. Click the pencil icon to start an edit session.
34. Click the "GRIDCODE" field name, to sort the field values in Ascending order.
35. Select the first "GRIDCODE" row with a value. For NLCD, the first gridcode value is 11.
to open the Field Calculator.
36. Click the Field Calculator icon
37. In the Field Calculator window (Figure 233):
a. Check the Only update selected features option.
b. Check the Update existing field option.
c. In the dropdown list, select the "Canopy" field.
172
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d. In the Expression box, type the "new_field" sum for the first gridcode, divided by the "Area"
sum for that gridcode. The expression should read "new_field" sum / "Area" sum (e.g.
1804788200.58 / 73515068.6)
e. Click OK.
Field calculator
X Only update selected features
Create a new field
Output field name
Output field type Whole number (integer)
Output field width 110 \-^\ Precision |o \-^\
Function List
X Update existing field —
Canopy
- Selected Function Help -
Operators —
+
Expression -
-
/
*
A
II
(
)
1804788200.58 / 73515068.6)
Output preview:
OK
Cancel
Help
Figure 233 Field Calculator window, with 1804788200.58/ 73515068.6 entered as the expression
38. Repeat field calculation steps 35-37 for each gridcode row, with the appropriate "new_field" sum
and "Area" sum.
Once the calculations are complete, the "Canopy" field in the lookup table will contain the average %
Canopy Cover for each land use type in the AOI. This updated field will be used to calculate the
"Us_Air_Dol" field in the Field Calculations section.
Air Quality
This section illustrates how to update the air quality value ("canopyVal") for an area of interest. The
"canopyVal" field will be used to calculate the "Us_Air_Dol" field in the Joining Lookup Table section.
Average removal rates for carbon monoxide (CO), ozone (O3), particulate matter (PM10), sulfur dioxide
(SO2), and nitrogen dioxide (NO2) have been previously estimated for 55 metropolitan areas in the
continental United States (Nowak et al., 2006; Figure 234). If the area of interest is within the
continental United States or Hawaii, the removal rates for each pollutant in the nearest city can either
be selected from the Air Quality Reference table (Appendix B: Air Quality Reference Table), or by
173
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spatially referencing the Air Quality Reference table and determining the nearest city in either ArcGIS
or QGIS. The total Air Quality value of canopy cover ($/m2/yr) has been calculated in the Air Quality
Reference table as described in the ES Calculations Theory section.
Air Quality Value $/m2 Canopy/yr
0.034 - 0.047
0.047 - 0.055
•
0.055 - 0.059
#
0.059 - 0.067
•
0.067-0.127
A
0 250 500
1,000
Vancouver
Seattle
San
Los Angeles
1,500
2,000
Miles
Ottawa
Toron ID
Chicago Detr°£
lUWfeJED STATE
Washington
•W »
DUJes
^lol||ton
AtlfSta
Monterrey
M®fni
Havana
Guadalajara
Port-au-
Prince
Figure 234 Total value ($/m2/yr) of canopy cover for each metropolitan area in Nowak et al., 2006
Using ArcGIS
This section outlines the calculation of land use air pollution removal rates based on the nearest city,
using the Air Quality Reference table as a shapefile in ArcGIS. This process is suggested if the user is
unsure which city from Appendix B: Air Quality Reference Table is closest to their AOI. However, if the
user knows which city from the table is closest, the shapefile is not required. The user can skip to step
9 and enter the appropriate "Value/m2/yr" value into Field Calculator.
1. Create a shapefile (AirQualityReference.shp) from the Air Quality Reference table as shown in
Appendix B: Air Quality Reference Table.
2. Open your existing ArcGIS map document file ( mxd), or create one following
the steps outlined in Set Up ArcGIS Map Document.
3. Use the Add Data ^ " icon to navigate to and add the AirQualityReference shapefile as a layer
in the Table of Contents.
4. if using a new map document, the AOI shapefile created in the Using ArcGIS section must be
added in the same way.
174
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5. Right click on the layer representing the AOI and select Joins and Relates > Join... (Figure 194).
6. In the Join Data window (Figure 235).
a. From the first dropdown list, select Join
data from another layer based on spatial
location.
b. In the Choose the layer to join to this layer
dropdown list, select AirQualityReference.
c. Toggle the second join option, to join only
the attributes of the nearest point.
d. In the Specify output shapefile text box,
enter the desired file path and shapefile
name (e.g. AOI_Join_AQ.shp).
7. In the Table of Contents, right-click on the output
layer (e.g. AOI_Join_AQ) and open the attribute
table.
8. Find the "Value_m2" field in the attribute table and
write down or copy the value in this field. The
value will be used to populate the "canopyVal"
field in the lookup table in step 9.
Note: if the AOI includes multiple features, for
example when multiple HUCs or counties are
analyzed at once, then the values in the
"Value_m2" field may differ across features/rows
in the nearest join table, if those features are
closer to different cities. It is recommended to
choose one value to use throughout. Alternatively,
separate lookup tables and land use layers can be
created for the different AOI features, each using
their own unique "Value_m2" and "canopyVal"
fields.
9. In the Table of Contents, right-click on the
supplemental lookup table (e.g. lookUPvars) and
open the attribute table.
a. Right-click on the "canopyVal" field in the attribute table and open the Field Calculator.
b. In the "canopyVal" Field Calculator window:
i. Enter the value (e.g. 0.0713215) from the "Value_m2" field in the output layer
(e.g. AOI_Join_AQ).
ii. Type /100 after the coefficient value in the Expression box (e.g. 0.0713215/
100).
iii. Click OK.
The lookup table "canopyVal" field contains the air pollutant removal value coefficient. This coefficient
will be multiplied by the land use average canopy cover to get values for air pollution removal for the
"Us_Air_Dol" field in the Field Calculations section.
Using QGIS
This section outlines the calculation of land use air pollution removal rates based on the nearest city,
using the Air Quality Reference table as a shapefile in QGIS. This process is suggested if the user is
unsure which city from Appendix B: Air Quality Reference Table is closest to their AOI. However, if the
Join Data X
Join lets you append additional data to this layer's attribute table so you can,
for example, symbolize the layer's features using this data.
What do you want to join to this layer?
Join data from another layer based on spatial location v
1. Choose the layer to join to this layer, or load spatial data from disk:
[*"•' AirQualityReference
~z] £5
2. You are joining: Points to Points
Select a join feature class above. You will be given different
options based on geometry types of the source feature dass
and the join feature dass.
O Each point will be given a summary of the numeric attributes of
the points in the layer being joined that are closest to it, and a
count field showing how many points are closest to it.
How do you want the attributes to be summarized?
I I Average Minimum [H Standard Deviation
I I Sum Q] Maximum Q Variance
(•) Each point will be given all the attributes of the point in the layer
being joined that is closest to it. and a distance field showing
how close that point is {in the units of the target layer).
3. The result of the join will be saved into a new layer.
Speafy output shapefile or feature dass for this new layer:
HI_Join_AQ.shp
£3
About joining data
OK
Cancel
Figure 235 Join Data window filled out as described in
the text, with the result nearest join table saved as
AOI Join AQ.shp
175
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user knows which city from the table is closest, the shapefile is not required. The user can skip to step
22 and enter the appropriate "Value/m2/yr" value into Field Calculator.
1. Create a shapefile (AirQualityReference.shp) from the Air Quality Reference table as shown in
Appendix B: Air Quality Reference Table.
2. Open your existing QGIS map document file (.qgs), or create one following the steps outlined
in Set Up QGIS Map Document.
3. From the Layer menu open the Add Vector Layer window (Main Menu > Layer > Add Vector
Layer, Figure 126).
4. In the Add vector layer window (example shown in Figure 127), click Browse to locate and
select the AirQualityReference shapefile, then click Open.
5. If using a new map document, the AOI shapefile created in the Using QGIS section must be
added in the same way.
6. From the Vector menu open the Polygon centroids tool (Vector > Geometry tools > Polygon
centroids, Figure 236).
Vector Raster Database Help H20 Toolbox |
Analysis Tools ~
Coordinate Capture ~
Data Management Tools ~
Geometry Tools ~
7m Check geometry validity
/a Export/Add geometry columns
Geoprocessing Tools ~
Research Tools ~
Road graph ~
4* Polygon centroids I
^ Delaunay triangulation
Figure 236 Polygon centroids tool in QGIS, located in Vector menu > Geometry tools
7. In the Polygon centroids window (Figure 238):
a. In the Input polygon vector layer dropdown list, select the AOI shapefile (e.g. HUC_Tampa).
b. In the Output point shapefile text box, indicate the file path and shapefile name (e.g.
HUC_ Tampa_points. shp).
c. Click OK.
The output is a point shapefile, with one point for the center of each watershed polygon (Figure 237).
Polygon centroids
Input polygon vector layer
HUCJampa
Output point shapefile
X
|_0 utp uts/Q G IS/Ai rQ li a I ity/H U C_Ta m pa_points.shp
Brov^se
0%
OK
Close
A
Figure 238 Polygon centroids window, with HUC shapefile
as input
Figure 237 HUC shapefile with centroid points
in blue; closest Air Quality Reference City
represented by purple point
-------
8. From the Vector menu open the Distance matrix tool (Vector > Analysis tools > Distance matrix,
Figure 239).
Vector
Raster Database Help H20 Toolbox
Anafysrs Tools
* (¦ Distance matrix
Coordinate Capture ~
Data Management Tools ~
^ Sum line lengths
Points in polygon
Figure 239 Distance matrix tooI in QGIS, located in Vector menu > Analysis tools
9. In the Distance matrix window (Figure 240):
a. In the Input point layer dropdown list, select the
HUC centroid points shapefile (e.g.
HUC_ Tampa_points).
b. In the Input unique ID field dropdown list,
choose "NAME".
c. In the Target point layer dropdown list, select
the AirQualityReference shapefile.
d. In the Target unique ID field dropdown list,
select "City".
e. Under Output matrix type, toggle on the Linear
option if not on by default.
f. Check Use only the nearest (k) target points
and enter 1 in the text box.
g. In the Output distance matrix text box, indicate
the file path and output name (e.g.
DistanceMatrix_HUC. csv).
h. Click OK.
10. A popup window may appear, telling the user that
the output matrix was created. Click OK.
11. Click Close to close the Distance matrix window.
12. Locate the output matrix in File Explorer and click
and drag the .csv file into the Layers panel.
13. In the Layers panel, double click on the matrix .csv
layer to open Layer Properties.
14. In the Layers Properties window, click on the Joins
&
tab and click the Add Join icon.
15. In the Add vector join window (example shown in
Figure 200):
a. In the Join layer dropdown list, select the AirQualityReference shapefile.
b. In the Join field dropdown list, select "City".
c. In the Target field dropdown list, select "TargetID".
d. Check Cache join layer in virtual memory.
e. Click OK.
16. Click OK to close Layer Properties.
17. In the Layers panel, right click on the matrix .csv layer and choose Open Attribute Table.
18. Locate the "Value ml" field in the attribute table.
^ Distance matrix ? X
Input point layer
HUC_Tampa_points ~
Input unique ID field
NAME
Target point layer
AirQualityReferenceCities »
Target unique ID field
City
Output matrix type
• Linear (N*k x 3) distance matrix
Standard (N xT) distance matrix
Summary distance matrix (mean, std. dev., min, max)
* Use only the nearest (k) target points l *
Output distance matrix
[_Outputs/QGIS/AirQuality/DistanceMatrix_HUC.csv|
Browse
0%
OK
Close
A
Figure 240 Distance matrix window, with output
as a .csv file
177
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a. Take note of the value in this field, as it will need to be typed into the Field Calculator in the
following steps.
Note: if the AOI includes multiple features, for example when multiple HUCs or counties are
analyzed at once, then the values in the "Value_m2" field may differ across features/rows in the
nearest join table, if those features are closer to different cities. It is recommended to choose one
value to use throughout. Alternatively, separate lookup tables and land use layers can be created
for the different AOI features, each using their own unique "Value_m2" and "canopyVal" fields.
19. Load the supplemental lookup table from Appendix A: Supplemental NLCD Lookup Table or
the most recently updated lookup table (e.g. if updated in the Tree Canopy section) into the
Layers panel.
20. In the Layers panel, double click on the lookup table to open Layer Properties.
21. Under the Fields tab, click the Pencil icon to start editing.
22. Click the Field Calculator
icon, and in the Field Calculator window (Figure 241):
a. Check the Update existing field.
b. From the dropdown list, select the "canopyVal" field.
c. In the Expression box, type the value from the "Value_m2" field in step 18 (e.g. 0.0713215).
d. Type /100 after the coefficient value in the Expression box (e.g. 0.0713215/100).
e. Click OK.
^ Field calculator ? X
Q Only update selected features
[Hi Create a new field X Update existing field —
Output field name | |
Output field type | Whole number ^integer) | T | canopyVal | T]
Output field width 110 |-^-| Precision 10 |-^|
Function List Selected Function Help —
Search
EQ
Operators
0-
Math
B
Conversions
B
String
0
Geometry
0-
Record
EB
Fields and Values
Operators
rnrnnmr^iFiririnnm
Expression
0.0713215 / 100
Output preview:
OK Cancel Help
Figure 241 Field Calculator in QGIS, used to update the canopyVal field
23. Click the Pencil icon to toggle editing off and save changes made to the attribute table.
24. Click OK to close Layer Properties.
178
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The lookup table "canopyVal" field now contains the air pollutant removal value coefficient. This
coefficient will be multiplied by the land use average canopy cover to get values for air pollution
removal for the "Us_Air_Dol" field in the Field Calculations section.
Carbon Sequestration
This section details how the carbon fixation rate was established for each land use type in the
Supplemental NLCD Lookup Table (Appendix A) and how rates can be further refined for an area of
interest. These rates, found in the "CarbonFixe" field (g C/m2/yr), will be used to calculate the
"StableClim" field in the Joining Lookup Table section. Carbon fixation coefficients (g C/m2/yr) will
differ significantly depending on if the carbon is being fixed into biomass or buried. The literature
values used to calculate each NLCD carbon burial rate are listed in Appendix A. These rates differ
from the FLUCCS carbon fixed into biomass listed in Table 3 and described in the ES Calculations
Theory section.
When updating carbon fixation rates, it is suggested that the user first calculate the percent of each
land use type found in the Area of Interest (AOI). This helps identify the land use types where the
model will be most sensitive to the "CarbonFixe" rates. It is possible that an AOI will not include some
land use types from the classification. When this occurs, the rate will have no impact on results and
would not need to be updated. Steps for determining the percent of each land use type in the AOI are
illustrated in the Carbon Fixation Rates from Literature Review
The following summarizes the process and criteria used to determine carbon burial rates for all NLCD
land use classes that were not "Developed" land use types from reviewed literature.
• An extensive literature review was conducted. The values obtained from these reviews were
ranked based on specificity to land use type, location, and reliability of the source.
• After the values were selected, a land use type average was calculated; this average value is
the final Carbon Burial Rate for each land use type.
• The available literature varies between land use types, location, units, and sampling duration,
as well as the method of carbon storage (sequestered, fixed, or buried). This results in some
values being more reliable than others.
• Where no carbon burial rates are available, they may be inferred from similar land use types.
This approach was used for the "Mixed Forest" land use type, where values were an average
from "Deciduous Forest" and "Evergreen Forest" rates, two land use types with reliable rates
in the literature. Likewise, when rates are available but not reliable, it may be helpful to
compare the rate against rates for other similar land use types.
Once new carbon burial rates are determined for the user's AOI, these rates must be updated in the
NLCD lookup table using Field Calculator to replace the national averages in the "CarbonFixe" field.
Using ArcGIS or Using QGIS sections.
Carbon fixation rates either come from rates in reviewed literature or are calculated for developed land
use classes based on the average characteristics (i.e. percent canopy and impervious surfaces).
Steps for calculating carbon fixation rates for developed land use types are illustrated for ArcGIS in
the Rates for Developed Classes section or for QGIS in the Rates for Developed Classes section.
Determining rates for all other land use types from literature values is detailed in the Carbon Fixation
Rates from Literature Review section.
n atu "2w
179
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The following summarizes the process and criteria used to determine carbon burial rates for all NLCD
land use classes that were not "Developed" land use types from reviewed literature.
• An extensive literature review was conducted. The values obtained from these reviews were
ranked based on specificity to land use type, location, and reliability of the source.
• After the values were selected, a land use type average was calculated; this average value is the
final Carbon Burial Rate for each land use type.
• The available literature varies between land use types, location, units, and sampling duration, as
well as the method of carbon storage (sequestered, fixed, or buried). This results in some values
being more reliable than others.
• Where no carbon burial rates are available, they may be inferred from similar land use types. This
approach was used for the "Mixed Forest" land use type, where values were an average from
"Deciduous Forest" and "Evergreen Forest" rates, two land use types with reliable rates in the
literature. Likewise, when rates are available but not reliable, it may be helpful to compare the
rate against rates for other similar land use types.
Once new carbon burial rates are determined for the user's AOI, these rates must be updated in the
NLCD lookup table using Field Calculator to replace the national averages in the "CarbonFixe" field.
Usir
The following steps summarize how to calculate the percent of each land use type using Esri ArcGIS.
If the user does not have a Spatial Analyst license, the user may be able to estimate the most
prominent land use types from the raster attribute table after clipping the raster to the AOI.
1. Tabulate the area between the NLCD raster and the AOI shapefile. In the ArcToolbox window,
navigate to the Tabulate Area tool (ArcToolbox > Spatial Analyst Tools > Zonal, Figure 223).
2. In the Tabulate Area window (example shown in Figure 224):
a. In the zone data dropdown list, select the NLCD raster.
b. In the class data dropdown list, select the AOI shapefile (i.e. the HUC boundary shapefile).
3. The output table will list each area in the land use layer units (for NLCD this in meters). Percent of
total area is calculated by:
a. Add the area of each gridcode together to find the total area of the AOI.
b. Divide each gridcode area by the total area and multiply the value by 100. This will provide
the percent land use out of 100%.
4. When listed in descending order, the percent land use table will outline which land use types are
most prominent (highest percentage) in the user's AOI.
It is strongly recommended that the user evaluate the values selected in the literature review, with a
focus on the most prominent land use types.
The following steps summarize how the carbon burial rate is calculated for the NLCD "Developed"
land use types (e.g. "Developed, Open Space" through "Developed, High Intensity") using Esri
ArcGIS.
1. Calculate the % Canopy Cover and populate the "Canopy" field, as shown in the Tree Canopy
section.
2. Calculate the Canopy based Carbon Burial Rate for each "Developed" land use type:
a. Copy the "Canopy" value for each "Developed" land use type into a spreadsheet.
180
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b. Determine an average Carbon Burial Rate for trees in developed areas. For NLCD
carbon burial rates listed in Appendix A, the average value for "Evergreen Forest" and
"Deciduous Forest" (i.e. "Mixed Forest") was 28.
c. Canopy Carbon Burial Rate = (% canopy /100) * 28
3. Calculate % impervious surface for the user's specific area of interest, following the same
steps outlined in the Tree Canopy section:
a. Navigate to https://www.mrlc.gov/viewer/ as shown in Figure 217, and download the
Impervious data using the All Impervious Years option.
b. Reproject the NLCD 2011 Impervious .tif dataset (or most recent year), as shown in the
Using ArcGIS section.
c. Run the Tabulate Area tool between the soil/land use layer and the re-projected
impervious layer.
i. In the Input raster zone data dropdown list, select the soil/land use layer (e.g.
NLCD_MaxTypeNJoin) and in the Zone Held dropdown list, select "gridcode".
ii. In the Input raster class data dropdown list, select the re-projected impervious
layer, and in the Class field dropdown list, select "Value".
iii. In the Output table text box, name the output table (e.g. lmp_TabArea) and file
path.
iv. Click OK.
d. In the output Tabulate Area table (e.g. lmp_TabArea) add a new field (e.g. "avglmp") with
type Short Integer.
e. Right-click on the new field (e.g. "avglmp") and open Field Calculator.
i. In the Expression box, paste the same equation used to calculate the % canopy
in step 13 of the Tree Canopy (Using ArcGIS) section (example shown in Figure
225) to calculate % impervious surface.
4. Calculate the Lawn Carbon Burial Rate for each "Developed" land use type:
a. Copy the "Impervious" (e.g. "Imp" field) value for each "Developed" land use type into a
spreadsheet.
b. Determine an average Carbon Burial Rate for lawns in developed areas. For NLCD
carbon burial rates listed in Appendix A the average lawn rate from the literature review
was 100 (Table 4).
c. Lawn Carbon Burial Rate = 100 * ((100 - % impervious) /100)
5. The final Carbon Burial Rate for the "Developed" land use types are calculated as:
Final Carbon Burial Rate = Lawn Carbon Burial Rate + Canopy Carbon Burial Rate.
6. In the lookup table use Field Calculator to update the "CarbonFixe" field value for each
"Developed" land use type to equal the new corresponding Final Carbon Burial Rate.
The lookup table "CarbonFixe" field now contains the updated carbon burial rates, which will be used to
calculate the "StableClim" field in the Field Calculations section. The database creation is continued in the
Denitrification section.
Usir
The following steps summarize how to calculate the percent of each land use type using QGIS. If the
user saved the Sum of the "Area" field for each gridcode in a separate spreadsheet (Using QGIS
section), skip to step 5.
1. From the soil/land use attribute table, open the Advanced search tool (as shown in Figure 212).
2. Select all polygons representing the first land use type. In the Search query builder window:
a. In the Expression box, enter gridcode =
181
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b. Under the Values option, click the All button; the list of all gridcode values will appear.
Double click on the first gridcode value (e.g. 11).
3. With the selection highlighted, open the Basic Statistics tool (Main Menu >Vector > Analysis
Tools > Basic statistics).
a. In the Input Vector Layer dropdown list select the soil/land use layer.
b. Check Use only selected features.
c. In the Target field dropdown list select "Area".
4. Copy down the Sum value for the first gridcode into a spreadsheet. Repeat the selection and
Basic Statistics analysis to obtain the total area for each gridcode type.
5. Add the area of each gridcode together to find the total area of the AOI.
6. Divide each gridcode area by the total area and multiply the value by 100. This will provide the
percent land use out of 100%.
7. When the percent land use is listed in descending order in the spreadsheet, the land use types at
the top are most prominent (highest percentage) in the user's AOI.
It is strongly recommended that the user evaluate the values selected in the literature review, with a focus
on the most prominent land use types.
The following steps summarize how the carbon burial rate was calculated for the NLCD "Developed"
land use types (e.g. "Developed, Open Space" through "Developed, High Intensity") using QGIS.
1. Calculate the % Canopy Cover and populate the "Canopy" field, as shown in the Tree Canopy
section.
2. Calculate the Canopy Carbon Burial Rate for each "Developed" land use type:
a. Copy the "Canopy" value for each "Developed" land use type into a spreadsheet.
b. Determine an average Carbon Burial Rate for trees in developed areas. For NLCD
carbon burial rates listed in Appendix A, the average value for "Evergreen Forest" and
"Deciduous Forest" (i.e. "Mixed Forest") was 28.
c. Canopy Carbon Burial Rate = (% canopy /100) * 28
3. Calculate % impervious surface for the user's specific area of interest, following the same steps
outlined in the Tree Canopy section:
a. Navigate to https://www.mrlc.gov/viewer/ as shown in Figure 217, and download the
Impervious data using the All Impervious Years option.
b. Reproject the NLCD 2011 Impervious .tif dataset (or most recent year), as shown in the
Using QGIS section.
c. Run the Zonal Statistics tool between re-projected impervious layer and the soil/land use
layer with a new output column prefix (e.g. IMP).
i. In the Raster layer dropdown list, select the re-projected impervious layer.
ii. In the Polygon layer containing the zones dropdown list, select the soil/land use
layer.
iii. In the Output column prefix text box, enter IMP, then click OK.
d. In the soil/land use layer, create a new field (e.g. "avglmp") with Whole number (integer)
type. Then use Field Calculator to populate the new field using the expression "Area" *
"IMPmean".
e. Follow the steps outlined in the Using QGIS section to select each "Developed" gridcode
value and use the Basic Statistics tool to find the Sum values for the newly created field
and the "Area" field.
i. Open the attribute table and use the Search query builder to select the first
"Developed" gridcode (e.g. gridcode = 21).
ii. Open the Basic Statistics tool and select the following inputs: in the Input Vector
Layer dropdown list, select the soil/land use layer, check Use only selected
features, and in the Target field dropdown list, choose "avglmp". Click OK.
182
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iii. Copy down the Sum value for the "avglmp" field, then change the Target field to
"Area" and click OK to run another statistical output. Copy down the Sum value
for the "Area" field.
iv. Repeat step e for each "Developed" gridcode".
f. In the spreadsheet, complete the following calculation to determine the % impervious
surface for each "Developed" gridcode value: "newest_field" sum / "Area" sum
4. Calculate the Lawn Carbon Burial Rate for each "Developed" land use type:
a. Each "Developed" land use type will have a % impervious in the spreadsheet calculated
in the previous step.
b. Determine an average Carbon Burial Rate for lawns in developed areas. For NLCD
carbon burial rates listed in Appendix A the average lawn rate from the literature review
was 100 (Table 4).
c. Total Carbon Burial Rate = 100 * ((100 - % impervious) /100)
5. The final Carbon Burial Rate for the "Developed" land use types are calculated as:
Final Carbon Burial Rate = Lawn Carbon Burial Rate + Canopy Carbon Burial Rate.
6. In the lookup table use Field Calculator to update the "CarbonFixe" field value for each
"Developed" land use type to equal the new corresponding Final Carbon Burial Rate.
The lookup table "CarbonFixe" field now contains the updated carbon burial rates, which will be used to
calculate the "StableClim" field in the Field Calculations section. The database creation is continued in the
Denitrification section.
Denitrification
This section details how the Denitrification rate was established for each land use type in the
Supplemental NLCD Lookup Table (Appendix A) and how rates can be further refined for an area of
interest. These rates, found in the "denitrific" field (g N/m2/yr), will be used to calculate the
"usablewat" field in the Joining Lookup Table section.
Average nitrogen removal values have been provided for each NLCD land use type, based on an
extensive literature review (Appendix A). These values may differ from the FLUCCS denitrification
values listed in Table 3 and described in the ES Calculations Theory section.
When updating denitrification rates, it is suggested that the user first calculate the percent of each
land use type found in the user's Area of Interest (AOI). This helps identify the land use types where
the model will be most sensitive to the "denitrific" rates. It is possible that an AOI will not include some
land use types from the classification. When this occurs, the rate will have no impact on results and
would not need to be updated. Steps for determining the percent of each land use type in the AOI are
illustrated in the Carbon SequestrationCarbon Fixation Rates from Literature Review
The following summarizes the process and criteria used to determine carbon burial rates for all NLCD
land use classes that were not "Developed" land use types from reviewed literature.
An extensive literature review was conducted. The values obtained from these reviews were ranked
based on specificity to land use type, location, and reliability of the source.
After the values were selected, a land use type average was calculated; this average value is the final
Carbon Burial Rate for each land use type.
The available literature varies between land use types, location, units, and sampling duration, as well
as the method of carbon storage (sequestered, fixed, or buried). This results in some values being
more reliable than others.
Where no carbon burial rates are available, they may be inferred from similar land use types. This
approach was used for the "Mixed Forest" land use type, where values were an average from
183
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"Deciduous Forest" and "Evergreen Forest" rates, two land use types with reliable rates in the
literature. Likewise, when rates are available but not reliable, it may be helpful to compare the rate
against rates for other similar land use types.
Once new carbon burial rates are determined for the user's AOI, these rates must be updated in the
NLCD lookup table using Field Calculator to replace the national averages in the "CarbonFixe" field.
Using ArcGIS or Using QGIS sections.
Denitrification rates either come from rates in reviewed literature or are calculated for developed land
use classes based on the average characteristics (i.e. percent canopy and impervious surfaces). The
Determine Nitrogen Removal Rates section describes how to update rates using both these methods.
The steps for calculating denitrification rates are very similar to those illustrated for ArcGIS in the
Carbon Fixation Rates for Developed Classes section or for QGIS in the Carbon Fixation Rates for
Developed Classes section.
N ¦ :movaI 111 111
The following summarizes the process and criteria used to determine nitrogen removal rates for all NLCD
land use classes that were not "Developed" land use types from reviewed literature.
• An extensive literature review was conducted. The values obtained from these reviews were
ranked based on specificity to land use type, location, and reliability of the source.
• After the values were selected, a land use type average was calculated; this average value is the
final Nitrogen Removal Rate for each land use type.
• The available literature varies between land use types, location, units, and sampling duration.
This results in some values being more reliable than others.
• Where no nitrogen removal rates are available they may be inferred from similar land use types.
This approach was used for the "Mixed Forest" land use type, where values were an average
from "Deciduous Forest" and "Evergreen Forest" rates, two land use types with reliable rates in
the literature. Likewise, when rates are available but not reliable, it may be helpful to compare the
rate against rates for other similar land use types.
Once new denitrification rates are determined for the user's AOI, these rates must be updated in the
NLCD lookup table using Field Calculator to replace the national averages in the "denitrific" field.
era Nitrogen Remov; •
The following steps summarize how the nitrogen removal rate was calculated for the NLCD
"Developed" land use types (e.g. "Developed, Open Space" through "Developed, High Intensity").
Calculate % impervious surface for the user's specific area of interest, as illustrated in the Carbon
Sequestration Carbon Fixation Rates from Literature Review
The following summarizes the process and criteria used to determine carbon burial rates for all NLCD
land use classes that were not "Developed" land use types from reviewed literature.
• An extensive literature review was conducted. The values obtained from these reviews were
ranked based on specificity to land use type, location, and reliability of the source.
• After the values were selected, a land use type average was calculated; this average value is
the final Carbon Burial Rate for each land use type.
184
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• The available literature varies between land use types, location, units, and sampling duration,
as well as the method of carbon storage (sequestered, fixed, or buried). This results in some
values being more reliable than others.
• Where no carbon burial rates are available, they may be inferred from similar land use types.
This approach was used for the "Mixed Forest" land use type, where values were an average
from "Deciduous Forest" and "Evergreen Forest" rates, two land use types with reliable rates
in the literature. Likewise, when rates are available but not reliable, it may be helpful to
compare the rate against rates for other similar land use types.
Once new carbon burial rates are determined for the user's AOI, these rates must be updated in the
NLCD lookup table using Field Calculator to replace the national averages in the "CarbonFixe" field.
Using ArcGIS or Using QGIS sections.
1. Calculate the final Nitrogen Removal Rate for each "Developed" land use type:
a. Use the "Impervious" (e.g. "avglmp" field) value for each "Developed" land use type.
b. Determine an average Nitrogen Removal Rate for lawns in developed areas. For
NLCD denitrification rates listed in Appendix A: Supplemental NLCD Lookup Table
the average rate from the literature review was 1.4 N/m2/yr (Raciti et al. 2011).
c. Final Nitrogen Removal Rate = ((100 - % impervious) /100) *1.4
2. In the lookup table, use Field Calculator (in ArcGIS or QGIS) to update the "denitrific" field value
for each "Developed" land use type to equal the new corresponding Final Nitrogen Removal Rate.
3. In the lookup table, use Field Calculator to also update the "dni" field to match the values in the
"denitrific" field.
The lookup table "denitrific" field now contains the updated nitrogen removal rates, which will be used to
calculate the "usablewat" field in the Field Calculations section. The "dni" field is not directly used during
field calculations; however, this field is used to recalculate the "usablewat" field in the H20 tool and must
match the "denitrific" field values exactly. The database creation is continued in the Joining Lookup Table
section.
This section illustrates the joining of the Supplemental NLCD lookup table with the land use layer using
ArcGIS or QGIS. The lookup table contains the parameter values for each land use type that are required
to compute Ecosystem Service values. After the join, field calculations are required to update these
parameter values.
The NLCD lookup table must be joined to the land use layer as part of database creation even if ES
Coefficients were not updated in the Update ES Coefficients section. If the NLCD lookup table ES
Coefficients were updated the updated lookup table should be joined, not the original found in
Appendix A: Supplemental NLCD Lookup Table. If FLUCCS data were used in the Create Land Use
Data Layer section instead of NLCD the corresponding lookup table from Appendix D: Extracting and
Updating the Original FLUCCS Lookup Table may be joined by the "FLUCCS" field instead of the
"GRIDCODE" field.
Using ArcGIS
This section illustrates how to join the lookup table and complete field calculations using Esri ArcGIS.
1. Open your existing ArcGIS map document file (.mxd), or create one following the steps
outlined in Set Up ArcGIS Map Document.
185
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2. If using a new map document, use the Add Data T icon to navigate to and add both the
soil/land use layer created in the Spatially Join Soils to Land Use section and the lookup
table updated in the Update ES Coefficients section or from Appendix A: Supplemental
NLCD Lookup Table.
3. Right-click on the soil/land use layer (e.g. NLCD_MaxTypeNJoin) and open the Join tool (as
shown in Figure 183).
4. In the Join Data window (example shown in Figure 184):
a. In the first dropdown list, select the Join attributes from a table option.
b. In the field in this layer that the join will be based on dropdown list, select "gridcode".
c. In the table to join to this layer dropdown list, select the lookup table (i.e. lookUPvars).
d. In the field in the table to base the join on dropdown list, select "GRIDCODE".
e. Under Join Options, toggle the Keep all records on.
f. Click OK.
5. Right-click on the land use layer and open the Export Data tool (Figure 123).
6. In the Export Data window (example shown in Figure 124):
a. In the Export dropdown list, select All features.
b. Under the Use the same coordinate system as section, toggle the data frame option on.
c. In the Output feature class text box, specify the file path and name the output Land_Use.shp.
d. Click OK
Field Calculations
This section illustrates how to update the blank fields joined from the lookup table (Figure 242). In the
expressions, "denitrific" is the denitrification rate (g N/M2/yr), "CarbonFixe" is the carbon sequestration
rate (g C/m2/yr), "Canopy" is percent canopy cover (%), and "CN" is Curve Number.
Table
m- m
Land Use
H M
Canopy
canopyVal
A
B
C
D
LEVI
waterRet
stabClim
us Wat
usablewat
StableClim
Us_Air_Dol
CN
FloodProt
0
0.00058932
10
10
10
10
5
2
37
3
88
0.00058932
36
60
73
79
4
2
37
3
0
0.00058932
10
10
10
10
5
2
37
3
0
0.00058932
10
10
10
10
5
2
37
3
41
0.00058932
39
61
74
80
1
2
37
3
41
0.00058932
39
61
74
80
1
2
37
3
91
0.00058932
49
65
72
80
6
2
37
3
36
0.00058932
54
70
80
85
1
2
37
3
0
0.00058932
10
10
10
10
5
2
37
3
41
0.00058932
39
61
74
80
1
2
37
3
89
0.00058932
36
60
73
79
4
2
37
3
41
0.00058932
39
61
74
80
1
2
37
3
91
0.00058932
49
65
72
80
6
2
37
3
91
0.00058932
49
65
72
80
6
2
37
3
0
0.00058932
10
10
10
10
5
2
37
3
91
0.00058932
49
65
72
80
6
2
37
3
(0 out of 126249 Selected)
Figure 242 Land_Use attribute table, with blank fields from lookup table join
The following steps detail how to update the "usablewat" field. Similar steps need to be followed to
update the "StableClim", "Us_Air_Dol", "CN" and "FloodProt" fields.
1. Right-click on the Land_Use layer and open the attribute table.
2. Right-click on the "usablewat" field and choose Field Calculator.
3. In the Field Calculator window (Figure 243):
a. In the Fields list box, locate "denitrific" and double click on the field name; [denitrific] will
appear in the Expression box.
186
-------
b. In the Expression box, type * .018 after the field name; the full expression is [denitrific] *
.018.
c. Click OK.
Field Calculator
Parser
(§) VB Script
O Python
Max_Type_N
FLUCSDESC
CarbonFixe
Canopy
A
B
C
D
Type:
(•) Number
O String
OQate
l~l Show Codeblock
usablewat =
0000QB
[denitrific] * .018
About calculatlnq fields | gear | Load... Save...
| OK | Cancel
Figure 243 Field Calculator window, with [denitrific] * .018 as the expression
For each field name listed in Table 9, repeat steps 2 and 3 to populate each field based on the
corresponding Field Calculator expression.
Table 9 Field Calculator expressions for each blank field in the Land_Use attribute table
Field Name
Field Calculator Expression
usablewat
[denitrific] * .018
StableClim
1,3542e-4 * [CarbonFixe]
Us_Air_Dol
[canopyVal] * [Canopy]
CN
See Calculation Explanation Below
FloodProt
(0.05 * (25400.00 / [CN] - 254.00)) /1000.00 * 70.629265
The following steps detail how to calculate Curve Number (CN). Please note that the "CN" field
must be calculated prior to calculating "FloodProt" field values.
4. From the main menu, choose Selection > Select By Attributes (Figure 244).
187
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Selection Geoprocessing Customize Windows Help
[%] Sel ect By Attri b utes...
: s ~ m B n ;
1^] Select By Location...
(JS Select By Graphics
Select By Attributes
Selects features by their attribute
values
±3 Zoom To Selected Featu
1 Pan To Selected Feature
Figure 244 Select By Attributes tool, located under the Selection menu in ArcMap
5. In the Select By Attributes window (Figure 245):
a. in the Layer dropdown list, select Land_Use.
b. in the Expression box, type the following expression: "Max_Type_N" =1
d. Click OK.
Select By Attributes
Layer:
Method
f# LandJJse
I I Onty show selectable layers in this list
X
-
Create a new selection
"gridcode"
A
"Count "
"Avg_Max_Ty"
"Max_Type_N"
"PKUID"
V
[<>
Like
> =
And
< =
Or
1 0
Not
In
[ Null
Go To:
SELECT * FROM Land Use WHERE:
"Max_Type_N" = 1
Clear
Verify
Help
Load...
Save...
OK
Apply
Close
Figure 245 Select By Attributes window, with Max_Type_N = 1 entered as the expression
6. Right-click on the Land_Use layer in the Table of Contents and open the attribute table.
7. Right click on the "CN" field and choose Field Calculator.
8. In the Field Calculator window (example shown in Figure 243):
a. In the Fields list box, double click on the "A" field. The expression [A] should appear in the
box below.
b. Click OK.
9. Repeat steps 4-8 to select records with "Max_Type_N" field values of 2, 3, and 4, and to
assign corresponding "CN" field values of B, C, and D (1=A, 2=B, 3=C, 4=D) using the Field
Calculator.
Regardless of the land use data used, field headers from the original Tampa database must be present in
the land use layer and lookup table. If using NLCD instead of FLUCCS, it is still necessary to include a
188
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field titled "FLUCSDESC" and "FLUCCS" for EPA H20 to function properly. In the supplemental lookup
table in Appendix A: Supplemental NLCD Lookup Table, "FLUCSDESC" should already be set equal to
"NLCDDesc". If other land use data were used, the user must populate the "FLUCSDESC" field with the
appropriate descriptions. Both the land use layer and the lookup table must be updated.
The Importing Layers into QGIS section details how to upload the land use layer into the user
database in QGIS. Although the NLCD data detailed in the Download Land Use Data section is from
2011, the naming scheme in Qspatialite must match the original Tampa Bay database (i.e.
Land_Use_2006). Database creation is continued in the Create NHDPIus V2 Data Layers section.
Using QGIS
This section illustrates how to join the lookup table and complete field calculations using QGIS.
1. Locate the soil/land use layer (e.g. NLCD_MaxTypeNJoin) created in the Spatially Join
Soils to Land Use section and locate the lookup table updated in the
189
-------
2. Update ES Coefficients section or from Appendix A: Supplemental NLCD Lookup Table.
3. Open your existing QGIS map document file ( qgs), or create one following the steps outlined
in Set Up QGIS Map Document.
4. if using a new map document, use the Add Vector Layer window (Main Menu > Layer > Add
Vector Layer) to add the soil/land use layer and lookup table.
5. In the Layers panel, double click on the land use layer to open the Properties menu.
6. In the Properties window, click on the Joins tab, then click the Add join icon.
7. In the Add vector join window (example shown in Figure 200):
a. In the Join layer dropdown list select the lookup table.
b. In the Join field dropdown list select "gridcode".
c. In the Target field dropdown list, select "Gridcode".
d. Check Cache join layer in virtual memory.
e. Click OK.
8. In the Layers panel, right-click on the land use layer and select the Save as option (Figure
132).
9. In the Save vector layer as... window (example shown in Figure 133):
a. In the Format dropdown list, select ESRI Shapefile.
b. In the Save as text box, indicate the file path, and name the output Land_Use.
c. From the CRS dropdown list, select Selected CRS, and click the Browse button.
d. In the Filter box, type 3857, choose H/GS 84/Pseudo Mercator and click OK.
e. Check Add saved file to map. Do not check Skip attribute creation.
f. Click OK.
Field Calculations
This section illustrates how to update the NULL fields joined from the supplemental lookup table (Figure
246). In the expressions, "denitrific" is the denitrification rate (g N/M2/yr), "CarbonFixe" is the carbon
sequestration into biomass rate (g C/m2/yr), "Canopy" is percent canopy cover (%), and "CN" is Curve
Number.
^ Attribute table ¦ land_Ute:: 0/ 87063 fealurefs) selected
X
~
1
LEVI | waterRet
stabGim
us Wat
tfsa-blewat
StableQim | Us_Air_DcJ
CN
FloodPfOt
-
0
1j 2
37
3
NULL
MUU NULl
NULL
NULL
1
1 2
37
3
NULL
MULL NULL
NULL
NULL
2
1j 2
37
3
NULL
NULL NULL
NULL
NULl
3
4 2
37
3
NULL
MULL NULL
NULL
NULl
4
l| 2
37
NULL
MULL NULL
NULL
NULl
5
1 2
37
NULL
MULL NULL
NULL
NULL
6
4j 2
37
NULL
MULL NULL
NULL
NULl
7
1 2
37
NULL
MULL NULL
NULL
NULl
S
l| 2
37
NULL
MULL NULL
NULL
NULl
9
1| 2
37
NULL
MULL NULL
NULL
NUU
10
4] 2
37
NULL
MULL NULL
NULL
NULl
11
1 Z
37
NULL
MULL NULL
NULL
NUU
12
4 2
37
NULL
MULL NULL
NULL
NULl
13
(| 2
37
NULL
MULL NULl
NULL
NULl
14
4 2
37
NULL
MULL NULL
NULL
NULl
-
«l
l*l>
qfe X ftl ¦ IP ~ u St
, LOOkfcr
n
Search |
Show selected only Seartfi selected only X Casesensto^e
Advanced sear ch ?
Owe
Figure 246 Land_Use attribute table, with NULL fields from lookup table join
The fields with NULL values (i.e. "usablewat", "StableClim", "Us_Air_Dol", "CN" and "FloodProt") were
added by joining to the lookup table. Values for these fields will be calculated using Field Calculator.
190
-------
The following steps show the procedure to calculate the land use layer "usablewat" field. Similar
steps need to be followed to update the rest of the fields as well.
1. In the Layers panel, double click on the Land_Use layer to open Layer Properties.
2. From the Fields tab, click the pencil icon to enable Editing mode. Click the Field
Calculator
icon to open the Field Calculator window.
3. In the Field Calculator window (Figure 247):
a. Check Update existing field
b. From the dropdown list, select "usablewat".
c. Under the Function List heading, locate the Fields and Values list box, and double click
on the "denitrific" field, "denitrific" will appear in the Expression box.
d. Type * .018 in the Expression box after "denitrific". The full expression is "denitrific" * .018.
e. Click OK.
^ Field calculator
E Only update selected features
E Create a new field
Output field name |
X Update existing field -
Output field type Whole number (integer) T |
usablewat
Output field width [ 10 |-^-j Precision |o \^\
Function List—
Search
Selected Function Help -
CarbonFixe
Canopy
canopyVal
A
B
C
D
~
I
Field
Double click to add field name to
expression string.
Right-Click on field name to open context
menu sample value loading options.
Operators -
Expression —
'denitrific* * .018
Output preview:
Cancel Help
Figure 247 Field Calculator window, with "denitrific" * .018 entered as the expression
4. Use Field Calculators populate the other NULL fields. The expressions used in step 3.d. will
be different for each field, as shown in Table 10.
Table 10 Expression for the calculation of each field
Field Name
Expression
usablewat
"denitrific" *.018
StableClim
1.3542e-4* "CarbonFixe"
Us_Air_Dol
"canopyVal" * "Canopy"
191
-------
CN
See Calculation Explanation Below
FloodProt
(0.05 * (25400.00 / "CN" - 254.00 )) /1000.00 * 70.629265
waterRet
2
stabClim
37
us Wat
3
The following steps detail how to calculate Curve Number (CN). Please note that the "CN" field
must be calculated prior to calculating "FloodProt" field values.
5. In the Layers panel, right-click the Land_Use layer, open the attribute table, and locate the
Look for search option at the bottom of the table (Figure 248).
6. In the search box, type 1, and from the in dropdown list select the field created in the Spatially
Join Soils to Land Use section (e.g. "Max_Type_N").
Attribute table -
Land_Use :: 0/855603 feature(s) selected
-
~ X
FID_1
Id
gridcode
Count_
Avg_Max_Ty
Max_Type_N
PKUID
0
0
1
22
0
0
1
1
1
1
2
23
0
0
1
2
2
2
3
23
0
0
1
2
3
3
4
42
0
0
1
23
4
4
5
22
0
0
1
1
5
5
6
22
0
0
1
1
6
6
7
42
0
0
1
23
~
<
I
|< ~
4 a*
g ||?
^ *\\t 0 Pa 16
£
m
Look for
1
in |Max_Type_N I ¦»
Search
Show selected only
Search selected only
X Case sensitive
Advanced search ?
Close
Figure 248 Land_Use attribute table, searching for value 1 in Max_Type_N field
7. Click Search to select all attributes that have a value of 1 in the "Max_Type_N" field.
8. Click the Field Calculator icon in the attribute table.
9. In the Field Calculator window (example shown in Figure 247):
a. Check the Only update selected features option.
b. Check the Update existing field option.
c. In the dropdown list, select "CN".
d. In the Fields and Values list box, double click on the "A" field. "A" should appear in the
Expression box.
e. Click OK.
10. Repeat steps 5-9 to select records with Max_Type_N field values of 2, 3, and 4 and assign
the corresponding values B, C, and D using the Field Calculator (1=A, 2=B, 3=C, 4=D).
Regardless of the land use data used, field headers from the original Tampa database must be present in
the land use layer. If using NLCD instead of FLUCCS, it is still necessary to include a field titled
"FLUCSDESC" and "FLUCCS" for EPA H20 to function properly. In the supplemental lookup table in
Appendix A: Supplemental NLCD Lookup Table, "FLUCSDESC" should already be set equal to
"NLCDDesc".
The Importing Layers into QGIS section details how to upload the land use layer into the user
database in QGIS. Although the NLCD data detailed in the Download Land Use Data section is from
192
-------
2011, the naming scheme in Qspatialite must match the original Tampa Bay database (i.e.
Land_Use_2006). Database creation is continued in the Create NHDPIus V2 Data Layers section.
Create NHDPIus V2 Data Layers
The National Hydrography Dataset (NHD) defines the flowlines, catchments and waterbodies
necessary for EPA H20 functionality. The NHD data is used to determine the upstream areas of
interest in the EPA H20 report. This section illustrates the step-by-step method used to obtain and
prepare the NHD data.
Either Esri ArcMap software or QGIS can be used to prepare the NHD data. The procedure for both
software applications is explained in this section.
Download NHDPIus Data
This section illustrates the step-by-step procedure for downloading NHD data by region from the
NHDPIus Version 2 website.
1. Navigate to https://nhdplus.com/NHDPIus/NHDPIusV2 data.php as shown in Figure 249.
NHDPIus
: Version 2
Horizon Systems => NHDPIus Version 2 => Data
Horizon
Systems
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NHDPIus Version 2 Tools
NHDPIus Version 2 Documentation
Select the data region of your choice by clicking on the map below or selecting the n
% National Data
# Global Data
SOURIS-RED-RAINY
"
V
hI
LOWER MISSOURI
CALIFORNIA
05
ARK-RED-WHITE
NORTHERN
MARIANA
ISLANDS
22M
SOUTH
TENNESSEE
LOWER U °3N
MISSISSIPPI SOUTH
08 ATLANTIC
WEST
03W
SOUTH
ATLANTIC
SOUTH
03S
01 Northeast
03S South Atlantic South
05 Ohio
08 Lower Mississippi
10L Lower Missouri
02 Mid Atlantic
03W South Atlantic West
06 Tennessee
09 Souris-Red-Rainy
11 Ark-Red-White
03N South Atlantic North
04 Great Lakes
07 Upper Mississippi
10U Upper Missouri
12 Texas
Figure 249 NHDPIus Version 2 website, published by Horizon Systems Corporation
2. On the interactive map, click on the region where the user's area of interest is located (e.g.
South Atlantic South (03S)).
Note: NHDPIus hydrological regions are similar to 2-digit HUC regions (Figure 118).
193
-------
3. In the next page, scroll down to locate the File Name download table for the selected region.
4. From the File Name table, find the following files and download each by clicking on the HTTP
button (Figure 250):
a. NHDPIusV21_SA_03S_NHDPIusAttributes_06.7z
b. NHDPIus V21_ SA_ 03S_NHDPIusBurn Components_ 02.7z
c. NHDPIusV21_SA_03S_NHDPIusCatchment_01.7z
d. NHDPIusV21_SA_03S_NHDSnapshot_06.7z
N H D PI u sV21_S A_0 3 S_N H D P1 u s Attri b utes_06.7 z
HTTP
FTP
NHDPIusV21_SA_03S_NHDPIusBurnComporients_02.7z
NHDPlusV21_SA_03S_l\l H DPI usCatchment_01. 7z
FTP
NHDPIusV21_SA_03S_NHDSriapshotFGDB_06.7z
NHDPlusV21_SA_03S_l\IHDSnapshot_06.7z
Figure 250 South Atlantic South File Names, with HTTP or FTP download available
Please note: the number at the end of the file name is the version number and changes as it is
updated. The "SA" and "03S" in the file name are specific to the South Atlantic region and South
subregion, respectively; these abbreviations will change based on the user's AOI location.
5. Save the zip file to the computer and unzip the contents to a known location.
The next section illustrates the creation of EPA H20 compatible NHD data from the unzipped
download files, using either Esri ArcGIS software (Using ArcGIS) or QGIS (Using QGIS).
Using ArcGIS
This section illustrates the creation of EPA H20 compatible NHDPIus V2 data using Esri ArcGIS
software.
1. Download and unzip the NHD datasets, as shown in the Download NHDPIus Data section.
2. Open your existing ArcGIS map document file (.mxd), or create one following the steps
outlined in Set Up ArcGIS Map Document.
3. Click the Add Data icon T , and navigate to the unzipped NHD folder (i.e. NHDPIusREGION).
Select the following files and click the Add button to add each layer to the Table of Contents.
a. NHDPIusSA\NHDPIusCatchment\Cafc/?/nenf.s/?p
b. NHDPIusSA\NHDPIusSnapshot\Hydrography\A//-/DF/ow//ne.s/?p
c. NHDPIusSA\NHDPIusSnapshot\HydrographyW/-/DI/l/aterJbody.s/?p
d. NHDP\usSA\NHDP\usAttr\butes\PlusFlowlineVAA.dbf
e. N H D PI usS A\N HDP I us Attri b utes \PlusFlow. dbf
f. N H D PI usS A\N HDP I us Attri b u\es\MegaDiv. dbf
4. Reproject the Catchment layer using the Project tool. From the ArcToolbox window, navigate to
and open the Project tool (ArcToolbox > Data Management Tools > Projections and
Transformations > Project Figure 143).
5. In the Project tool window (example shown in Figure 144):
a. In the Input Dataset or Feature Class box, select Catchment.shp.
194
-------
b. In the Output Dataset or Feature Class text box, browse to or type the desired file name (e.g.
Catchment_reproj) and file path.
c. Click the Spatial Reference icon to set the Output Coordinate System to
WGS_1984_Web_Mercator_Auxiliary_Sphere, located under the l/l/or/d folder in Projected
Coordinate Systems. Alternatively, search for it by typing 3857 into the search box.
a. A Geographic Transformation is required to reproject the land use dataset. In the
dropdown list, choose WGS_1984_(ITRF00)_To_NAD_1983 if not already selected.
d. Click OK.
6. Repeat steps 4 and 5 to reproject NHDWaterbody.shp and NHDFIowline.shp.
7. In the Table of Contents, right-click on the re-projected Catchment layer and choose Joins
and Relates > Join... {Figure 183).
8. In the Join Data window (example shown in Figure 184).
a. In the first dropdown list, select Join attributes from a table.
b. In the Choose the field in this layer that the join will be based on dropdown list, select
"FEATURED".
c. In the Choose the table to join to this layer dropdown list, select PlusFlow.
d. In the Choose the field in the table to base the join on dropdown list, select
"FROMCOMID".
e. Under Join Options, toggle Keep all records.
f. Click OK.
9. Right-click on the re-projected Catchment layer again and choose Joins and Relates > Join...
to add a second join, this time with the MegaDiv table.
a. In the Choose the table to join to this layer dropdown list, select MegaDiv.
b. Repeat all other inputs from step 8.
10. Right-click on the re-projected Catchment layer a third time and choose Joins and Relates >
Join... to add a third join, this time with the PlusFlowlineVAA table.
a. In the Choose the table to join to this layer dropdown list, select PlusFlowlineVAA.
b. In the Choose the field in the table to base the join on dropdown list select "ComID".
c. Repeat all other inputs from step 8.
11. Repeat steps 7-10 to join the re-projected NHDFIowline layer with the PlusFlow,
MegaDiv and PlusFlowlineVAA tables.
a. In the Table of Contents, right-click on the NHDFIowline layer and choose Joins and
Relates > Join... (Figure 183).
b. In the Join Data window, for the Choose the field in this layer that the join will be based on
dropdown list, select "COMID".
c. Repeat all other inputs from steps 8-10.
12. In the Table of Contents, right-click on the re-projected Catchment layer and open the
attribute table.
13. In the attribute table, click on the Table Options icon and choose Add Field (Figure 179).
14. In Add Field window (example shown in Figure 180):
a. In the Name text box, type HUC_14.
b. In the Type dropdown list, select "Text".
c. Click OK.
15. In the Catchment attribute table, right-click on the newly created HUC_14 field and choose Field
Calculator.
16. In the Field Calculator window:
a. From the Fields list box, double click the "FEATUREID" field (e.g.
Catchment_reproj.FEATUREID). The name of the field should appear in the Expression box.
b. Click OK.
17. In the Catchment attribute table, add a second new field.
a. In the Name text box, type HU_14_DS.
b. In the Type dropdown list, select "Text".
195
-------
c. Click OK,
18. There are two fields in the Catchment attribute table named "TOCOMID", one from the joined
PlusFlow table and one from the MegaDiv table.
a. Right-click on each "TOCOMID" field and choose properties to see the full field names, until
finding the "TOCOMID" with "MegaDiv.TOCOMID" as it's full field name.
b. Right-click on the correct "TOCOMID" field again and choose Sort Descending.
c. Click and drag to select the rows that contain the non-NULL "TOCOMID" values (Figure 251).
There should only be a relatively small amount of non-NULL features at the top of this
"TOCOMID" field.
» I 111 *¦
Catchment_reproj x
TOLVLPAT
NODENUMBER
DELTALEVEL
DIRECTION
GAPDISTKM
HasGeo
TotDASqKM
DivDASqKM
OID
FROMCOMID
TOCOMID
OID
ComID
V
270004662
270039658
0
709
0
Y
4938.4341
3.0303
3
21483466
21483506
32949
21483466
270006923
270027942
-1
709
0
Y
2149.6122
2149.6122
10
16628676
16943586
>7734
16628676
270034478
270033123
-2
709
0
Y
63.4878
63.4878
25
16807477
16807489
19203
16807477
270029385
270032792
-1
709
0
Y
8.5275
8.5275
9
16803011
16803009
19320
16803011
270021832
270030033
-1
709
0
Y
1.9395
1.9395
15
16682633
16682619
10790
16682633
270029583
270029857
0
709
0
Y
0.0675
0.0675
20
16682085
16682073
11354
16682085
270006546
270025934
0
709
0
Y
145.8297
0.189
18
14351364
14351352
16224
14351364
270006551
270025913
0
709
0
Y
146.2032
0.2151
2
14352656
14351300
16208
14352656
270003951
270025290
-1
709
0
Y
35263.6731
35263.6731
19
14347278
14347280
17496
14347278
270004879
270023791
0
709
0
Y
3532.9716
0.4104
7
10998965
10998945
>5707
10998965
270004713
270023738
0
709
0
Y
3550.7421
0.0702
0
10998841
10998825
>5684
10998841
270019368
270022411
0
709
0
Y
44.9442
44.9442
1
10241909
10241919
18836
10241909
270027454
270013724
-2
709
0
Y
28.278
24.8175
14
3339882
3339896
S6562
3339882
270016231
270007284
0
709
0
Y
205.8444
0.054
27
1983548
1983550
18984
1983548
270014569
270007109
-1
709
0
Y
60.3648
60.3648
32
1984284
1983176
18905
1984284
270041352
270001785
-1
709
0
Y
4.0743
4.0743
4
91826
91532
15482
91826
270041516
270000627
-1
709
0
Y
14.8491
14.8491
5
83726
83738
36840
83726
270028228
270004477
0
709
0
Y
0.9954
0.9954
1474
1058079
270013710
270015358
1
709
0
Y
4.0113
4.0113
11329
6336396
270013710
270015336
1
709
0
Y
0.7272
0.7272
11320
6335562
270040611
270004461
0
709
0
Y
2.1447
2.1447
1448
1056697
270008102
270004106
1
709
0
Y
6.4692
6.4692
1591
1055621
270011022
270015408
1
709
0
Y
1.4886
1.4886
11279
6335790
270009198
270004383
1
709
0
Y
5.5035
5.5035
1453
1056539
270009198
270004506
1
709
0
Y
6.8445
6.8445
1478
1056865
270025164
270004559
1
709
0
Y
0.7938
0.7938
1503
1057095
270024509
270015335
0
709
0
Y
16.884
16.884
11313
6335468
270040572
270004575
1
709
0
Y
1.1646
1.1646
1520
1057153
270032732
270004535
0
709
0
Y
7.8912
7.8912
1494
1057069
270028217
270004588
0
709
0
Y
2.7342
2.7342
1537
1057195
270011022
270015464
1
709
0
Y
2.2887
2.2887
11340
6335908
<
>
H i 0 > H ]M\m (17 out of 55586 Selected)
Catchment_reproj
"i
Figure 251 Catchment attribute table, with non-NULL values in TOCOMID field highlighted
19. Right-click on the new HU_14_DS field and choose Field Calculator.
20. In the Field Calculator window:
a. Clear any previous text from the expression box.
b. From the Fields list box, double click on the "MegaDiv.TOCOMID" field. The name of the field
should appear in the Expression box.
c. Click OK.
8
21. In the attribute table, invert the current selection with the Switch Selection icon.
22. Right click on the new HU_ 14_DS field again and choose Field Calculator.
23. In the Field Calculator window:
a. Clear any previous text from the expression box.
b. From the Fields list box, double click on the "PlusFlow.TOCOMID" field. The name of the field
should appear in the Expression box.
c. Click OK.
24. Clear the current selection in the attribute table and open the Select by Attributes tool.
25. In the Select by Attributes window:
a. Clear any previous text from the expression box.
b. From the Fields list box, double click on the "PlusFlowlineVAA. TerminalFI" field. The name of
the field should appear in the Expression box.
c. Type = 1 after the name of the field. The full expression is "PlusFlowlineVAA.TerminalFI" = 1.
d. Click OK.
196
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26. In the attribute table, right-click on the HU_14_DS field and choose Field Calculator.
27. In the Field Calculator window:
a. Clear any previous text from the expression box.
b. In the Expression box, type "NULL".
c. Click OK.
28. Repeat steps 12-27 for the re-projected NHDFIowline layer, using the "COMID" field in
place of the "FEATUREID" field when using field calculator on the "HUC_14" field (step
16).
29. After finishing updating the NHDFIowline layer, clear all selected features by clicking the clear
ra
selection icon on the tools toolbar.
30. From the main menu, choose Selection > Select By Attributes.
31. In the Select by Attributes window:
a. From the Fields list box, double click on the "NHDFIowline_reproj.FTYPE" field. The name of
the field should appear in the Expression box.
b. Type LIKE 'Coastline' after the name of the field. The full expression is
"NHDFIowline_reproj.FTYPE" LIKE 'Coastline'.
c. Click OK.
32. The selected flow lines must be deleted, which requires the user to be in an edit session. If the
Editor toolbar is not enabled, right-click anywhere on the main menu bar at the top of the ArcMap
window. From the list of optional toolbars that appear select Editor (Figure 252).
Help
Advanced Editing
Animation
ArcScan
COGO
Data Driven Pages
Data Frame Tools
Distributed Geodatabase
Draw
Edit Vertices
Editor
Effects
Figure 252 List of extensions and toolbars in ArcMap, with the Editor toolbar selected
33. In the Editor toolbar, click the Editor dropdown list and choose Start Editing (Figure 253).
1 Editor
' x|
Editor-
ll ~ 1 / f~ d
- 1 IS U s ^ x
¦y Start Editing
'/ Stop Editing
Figure 253 Editor toolbar, with the Start Editing option selected
34. If the Start Editing window appears, select the NHDFIowline layer and click OK.
35. In the Table of Contents, right-click and open the NHDFIowline attribute table.
36. Click the Delete * icon to delete the selected flow lines ("FTYPE" LIKE Coastline).
37. In the Editor toolbar, click the Editor dropdown and choose Save Edits, and then Stop Editing
(Figure 254).
197
-------
| Editor"pJ K 11**";, j
^ •
¦
"/ Stop Editing
ifjj Save Edit;
Catchment Layer
NHDFIowline Layer
Joined
Tables
PlusFlow.dbf, MegaDiv.dbf, and PlusFlowlineVAA.dbf
PlusFlow.dbf, MegaDiv.dbf, and PlusFlowlineVAA.dbf
HUC_14 Field
Field Type
"T ext"
"T ext"
Field
Attribute Selection
New Value
Attribute Selection
New Value
Calculator
All
"FEATUREID"
All
"COM ID"
HU_14_DS Field
Field Type
"T ext"
"T ext"
Attribute Selection
New Value
Attribute Selection
New Value
"MegaDiv.TOCOMID" IS NOT
NULL
"MegaDiv.TOCOMID"
"MegaDiv.TOCOMID" IS NOT
NULL
"MegaDiv.TOCOMID"
Field
Calculator
Invert Selection or:
"MegaDiv.TOCOMID" IS NULL
"PlusFlow.TOCOMID"
Invert Selection or:
"MegaDiv.TOCOMID" IS NULL
"PlusFlow.TOCOMID"
"PlusFlowlineVAA.TerminalFI" =
"NULL"
"PlusFlowlineVAA.TerminalFI" =
1
"NULL"
1
"NHDFIowline proj.FTYPE" LIKE
'COASTLINE'
*Delete selected
fields
Figure 254 Editor toolbar, with the Save Edits option selected
38. In the Table of Contents, right-click on the Catchment layer and choose Joins and Relates >
Remove Join(s) > Remove All Joins. Repeat this for the NHDFIowline layer.
A summary of the calculations used to prepare the NHDPIus data using Esri ArcGIS software is listed
in Table 11.
Table 11 Fields added and calculations required to prepare the Catchment and NHDFIowline layers in ArcMap
The Importing Layers into QGIS section details how to upload the NHD Catchment, Waterbodies and
Flowlines layers into the user database in QGIS. Database creation is continued in the Grid Water
Bodies section.
Using QGIS
This section illustrates the creation of EPA H20 compatible NHDPIus V2 data using QGIS software.
1. Download and unzip the NHD datasets, as shown in the Download NHDPIus Data section.
198
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2. Open your existing QGIS map document file (.qgs), or create one following the steps outlined
in Set Up QGIS Map Document.
3. In File Explorer, locate the unzipped NHD folder (i.e. NHDPIusREGION). Drag and drop each
of the following files into the QGIS Layers panel (Figure 255):
a. NHDPIusSA\NHDPIusCatchment\Cafc/?/nenf.s/?p
b. NHDPIusSA\NHDPIusSnapshot\HydrographyW/-/DF/ow//ne.s/?p
c. NHDPIusSA\NHDPIusSnapshot\HydrographyW/-/DI/l/aterJbody.s/?p
d. NHDP\usSA\NHDP\usAttr\butes\PlusFlowlineVAA.dbf
e. N H D PI usS A\N HDP I us Attri b utes \PlusFlow. dbf
f. N H D PI usS A\N HDP I us Attri b u\es\MegaDiv. dbf
Layers
B
Catchment
¦
El-
V" NHDFIowline
El-
NHDWaterbody
EH
PlusFlowlineVAA
="E
PlusFlow
zrE
MegaDiv
X Control rendering order
Figure 255 Layers panel in EPA H20, listing the hydrological tables and shapefiles
4. In the Layers panel, right-click on the Catchment layer and select the Save as option (Figure
132).
5. In the Save vector layer as... window (example shown in Figure 133):
g. In the Format dropdown list, select ESRI Shapefile.
h. In the Save as text box, browse to or type the desired file path and name the output
Catchment_reproj.
i. In the CRS dropdown list, choose Selected CRS, and click the Browse button.
d. In the Filter box, type 3857, choose l/l/GS 84/Pseudo Mercator and click OK.
e. Check Add saved file to map. Do not check Skip attribute creation.
f. Click OK.
6. Repeat steps 4 and 5 to reproject NHDWaterbody.shp and NHDFIowline.shp.
7. In the Layers panel, double click the re-projected Catchment layer to open Layer Properties.
8. From the Joins tab, click the Add Join icon to open the Add vector join window.
(example shown in Figure 200):
a. In the Join layer dropdown list, select PlusFlow.
b. In the Join field dropdown list, select "FROMCOMID".
c. In the Target field dropdown list, select "FEATUREID".
d. Check Cache join layer in virtual memory.
e. Click OK.
9. Click the Add Join icon again. In the Add vector join window:
a. In the Join layer dropdown list, choose MegaDiv.
b. In the Join field dropdown list, choose "FROMCOMID".
c. In the Target field dropdown list, choose "FEATUREID".
d. Check Cache join layer in virtual memory.
e. Click OK.
10. Click the Add Join icon a third time. In the Add vector join window:
199
-------
a. In the Join layer dropdown list, choose PlusFlowlineVAA.
b. In the Join field dropdown list, choose "ComID".
c. In the Target field dropdown list, choose "FEATUREID".
d. Check Cache join layer in virtual memory.
e. Click OK.
The completed joins are listed under the Joins tab, as shown in Figure 256.
^ Layer Properties - Catchment ? X
Of' Style Labels Fields General 4) Metadata I & Actions Joins ' Diagrams
# S
Join layer
Join field
Target field
f- PlusFlow
FROMCOMID
FEATUREID
j- MegaDiv
FROMCOMID
FEATUREID
L PlusFlowlineVAA
ComID
FEATUREID
Restore Default Style
Save As Default
Load Style ...
Save Style ...
OK
Cancel
Apply
Help
Figure 256 Layer Properties > Joins tab, listing tables joined to Catchment layer
11. Repeat steps 7-10 to join the re-projected NHDFIowline layer with the PlusFlow,
MegaDiv and PlusFlowlineVAA tables.
a. In the Layers panel, double click on the NHDFIowline layer to add the joins.
b. In the Target field dropdown list, choose "COMID".
c. Repeat all other inputs from steps 7-10.
12. In the Layers panel, right-click the Catchment layer and choose Open Attribute Table.
13. In the attribute table window, toggle editing on by clicking the pencil icon
to open the Field Calculator window.
if
14. Click the Field Calculator icon
15. In the Field Calculator window (Figure 257)\
a. Check Create a new field.
b. In the Output field name text box, type HUC_14.
c. In the Output field type dropdown list, select Text (string).
d. In the Function List, expand the Fields and Values option and double click the
"FEATUREID" field. The name of the field will appear in the Expression box.
e. Click OK.
200
-------
Q Field calculator ? X
D Only update selected features
|X Create a new field Q Update existing field —
Output field name HUC_14
Output field type Text (string) | ~ j [ GRIDCODE | ~ ]
Output field width 10 \^\ Precision [p \^\
Function List Selected Function Help
J Field
Double click to add field name to expression
string.
Right-Click on field name to open context
menu sample value loading options.
Operators
rTirnmmnmnnmrr
Expression —
TEATUREID*
lit-
Operators
Math
Conversions
L
i-
String
&
Geometry
i~
Record
B-
Fields and Values
!•••¦ GRIDCODE
FEATUREID
-
\ SOURCEFC
E
Output preview:
OK ] Cancel Help
Figure 257 Field Calculator window, used to create and populate the HUC_14 field
16. In the Attribute table window, click the Save Edits icon.
17. There are two fields in the attribute table named "TOCOMID". Locate the second or rightmost
column.
a. Click the "TOCOMID" column header twice to sort the attribute table in Descending order.
There should only be a relatively small amount of non-NULL features.
b. Click on row number 0 and drag to select the rows that contain the non-NULL
"TOCOMID" values (Figure 258).
201
-------
$ Attribute table - Catchment:: 17/ 55586 feature(s) selected
~
3
DELTALEVEL
DIRECTION
GAPDISTKM
HasGeo
TotDASqKM
DivDASqKM
TOCOMID
Fdate
c
*
0
0
709
0
Y
4938.4341
3.0303
21484382
2012/07/03
1
-1
709
0
Y
63.4878
63.4878
16807483
2012/07/03
2
0
709
0
Y
8.5275
8.5275
16802069
2012/07/03
3
-2
709
0
Y
1.9395
1.9395
16682621
2012/07/03
4
0
709
0
Y
0.0675
0.0675
16682077
2012/07/03
5
0
709
0
Y
2149.6122
2149.6122
16629300
2012/07/03
6
0
709
0
Y
145.8297
0.189
14351354
2012/07/03
7
-1
709
0
Y
146.2032
02151
14351302
2012/07/03
8
0
709
0
Y
35263.6731
35263.6731
14347282
2012/07/03
9
-1
709
0
Y
3532.9716
0.4104
10998947
2012/07/03
10
0
709
0
Y
3550.7421
0.0702
10998829
2012/07/03
11
0
709
0
Y
44.9442
44.9442
10241923
2012/07/03
12
0
709
0
Y
28278
24.8175
3339884
2012/07/03
13
0
709
0
Y
205.8444
Q.054
1983552
2012/07/03
14
0
709
0
Y
60.3648
60.3648
1983174
2012/07/03
15
0
709
0
Y
4.0743
4.0743
91510
2012/07/03
16
-1
709
0
Y
14.8491
14.8491
83734
2012/07/03
17
0
709
0
Y
0.9954
0.9954
NULL
2012/07/03
18
1
709
0
Y
4.0113
4.0113
NULL
2012/07/03
19
1
709
0
Y
0.7272
0.7272
NULL
2012/07/03
20
0
709
0
Y
2.1447
2.1447
NULL
2012/07/03
-
21
1
709
0
Y
6.4692
6.4692
NULL
2012/07/03
HI
HiJ I
m
a a an
P]®0[
1E3SI
~^\ |@| Look for
in Tidal
"*¦ Search
I Show selected only
Search selected only
X Case sensitive
Advanced search
? Close
Figure 258 Catchment attribute table, with non-NULL TOCOMID rows highlighted
18. Click the Field Calculator icon to open the Field calculator window.
19. In the Field Calculator window (example shown in Figure 257):
a. Check Only update selected features.
b. Check Create a new field.
c. In the Output field name text box, type HU_14_DS.
d. In the Output field type dropdown list, select Text (string).
e. Under the Function List, expand the Fields and Values option and double click the second
listed "TOCOMID" field name. The field name "TOCOMID" will appear in the Expression
box.
f. Click OK.
20. In the attribute table, click the Invert Selection
second "TOCOMID" field.
icon to select all the NULL values in the
21. Click the Field Calculator icon
a. Check Only update selected features.
and in the Field Calculator window:
b. Check Update existing field.
c. In the field dropdown list, select "HU_14_DS".
d. Under the Function List, expand the Fields and Values option and double click the first
"TOCOMID" field. The first "TOCOMID" field should appear in the Expression box.
e. Click OK.
22. In the attribute table, click the Save Edits icon, then click the Advanced Search
oedsea button to open a search query window.
23. In the Search query builder window (Figure 259):
a. In the Fields list box, double click on the "TerminalFI" field. The name of the field will
appear in the SQL where clause box.
b. Type = 1 after the name of the field, the full expression is TerminalFI = 1.
202
-------
c. Click OK.
Q Search query builder
X
Catchment
Fields
FromNode
ToNode
Hydroseq
LevelPathl
Path length
TerminalPa
ArbolateSu
Divergence
StartFlag
jj^TffTTfplT
Dn Level
ThinnerCod
Up Level Pat
UpHydroseq
Dn Level Pat
DnMinorHyd
Operators
<=
<
>=
Values
1
LIKE
ILIKE
Sample
%
AND
IN
OR
NOT IN
NOT
SQL where clause
TerminalFl = 1
Clear
Load..
Cancel
Help
Figure 259 Search query builder window, with TerminalFl = 1 entered in the Search box
24. Click the Field Calculator icon to open the Field Calculator window.
25. In the Field Calculator window:
a. Check Only update selected features.
b. Check Update existing field.
c. In the fields dropdown list, select "HU_14_DS".
d. In the Expression box, type NULL.
e. Click OK.
26. Toggle editing off by clicking the pencil icon and save edits when prompted.
27. Repeat steps 12-26 for the re-projected NHDFIowline layer, replacing "FEATUREID" with
"COMID" during "HUC_14" field calculation.
28. After completing updated to the NHDFIowline layer, open the NHDFIowline attribute table and
click the Advanced search button.
29. In the Search query builder window (example shown in Figure 259):
a. In the Fields list box, double click on the "FTYPE" field. The name of the field will appear
in the SQL where clause box.
b. In the Values box, click the All button. All values found in the "FTYPE" field are listed in
the Values box.
c. In the Operators list, click the LIKE button.
d. Back in the Values list box, double click on the 'Coastline' attribute. The full expression in
the search box should read FTYPE LIKE 'Coastline'.
e. Click OK.
203
-------
30. In the NHDFIowline attribute table, click the Delete selected features icon.
31. Toggle editing off by clicking the pencil icon and save edits when prompted.
32. Deleting the joins made in the beginning of this section is not required but will save disk space
and reduce memory usage when using EPA H20.
a. In the Layers panel, double click on the Catchment and NHDFIowline layers to open the
Properties window.
b. In the Join tab, highlight each join and click the green minus sign to remove it.
c. Click OK when all joins have been removed.
A summary of the calculations used to prepare the NHDPIus layers using QGIS is listed in Table 12.
Table 12 Fields added and the calculations required to prepare the Catchment and NHDFIowline layers in QGIS
Catchment Layer
NHDFIowline Layer
Joined
Tables
PlusFlow.dbf, MegaDiv.dbf, and PlusFlowlineVAA.dbf
PlusFlow.dbf, MegaDiv.dbf and PlusFlowlineVAA.dbf
HUC_14 Field
Field Type
Text (string)
Text (string)
Field
Attribute Selection
New Value
Attribute Selection
New Value
Calculator
All
"FEATUREID"
All
"COM ID"
HU_14_DS Field
Field Type
Text (string)
Text (string)
Attribute Selection
New Value
Attribute Selection
New Value
"TOCOMID" IS NOT NULL
(MegaDiv)
2nd "TOCOMID"
"TOCOMID" IS NOT NULL
(MegaDiv)
2nd "TOCOMID"
Field
Calculator
Invert Selection or:
"TOCOMID" IS NULL
(PlusFlow)
1st "TOCOMID"
Invert Selection or:
"TOCOMID" IS NULL
(PlusFlow)
1st "TOCOMID"
(PlusFlowlineVAA)
"NULL"
(PlusFlowlineVAA)
"TerminalFI" = 1
"NULL"
"TerminalFI" = 1
(NHDFIowline proj)
"FTYPE" LIKE 'COASTLINE'
*Delete selected fields
The Importing Layers into QGIS section details how to upload the NHD Catchment, Waterbodies and
Flowlines layers into the user database in QGIS. If using QGIS, database creation is continued in the
Create Road Layer section.
The EPA H20 tool uses the NFID_flowlines and Subwatershed layers to trace data from upstream.
Upstream data are used to calculate the ES values in the Ecosystem Valuation Reports. However, the
catchments in the Subwatershed layer do not overlap large bodies of water, such as Tampa Bay. If
the user's AOI extends into a large body of water, it may be unclear what data are upstream.
204
-------
The user may create an interior bay hexagon layer to link upstream data to these large bodies for
Ecosystem Valuation Reports. This grid will "fill in" the water bodies in the Subwatershed layer with
hexagonal polygons.
This section illustrates the creation of an interior bay hexagon layer using Esri ArcGIS software.
1.
2.
3.
4.
5.
6.
7.
8.
Open your existing ArcGIS map document file (.mxd), or create one following the steps
outlined in Set Up ArcGIS Map Document.
If using a new map document, use the Add Data " icon to navigate to the AOI shapefile
(e.g. HUC_Tampa.shp), and add the layer to the Table of Contents.
If not already in the Table of Contents, the re-projected NHD catchment layer (e.g.
Catchment_reproj.shp) must be added in the same way.
In the Table of Contents, right-click on Catchment_reproj and open the attribute table.
Click the Table Options icon in the attribute table and select Add Field (Figure 179).
In the Add Field window (example shown in Figure 180):
a. In the Name text box, type "AreaKM2".
b. Under the Type dropdown list, select Float.
c. Click Ok.
In the attribute table, right-click on the "AreaKM2" field and select Calculate Geometry.
In the Calculate Geometry window (Figure 260):
a. In the Property dropdown list, select Area.
b. Under Coordinate System, confirm Use coordinate system of the data source is toggled
and lists PCS: l/l/GS 1984 Web Mercator Auxiliary Sphere.
c. In the Units dropdown list, select Square Kilometers [sq km].
d. Click OK.
Calculate Geometry
X
Property:
Area
Coordinate System
® Use coordinate system of the data source:
PCS: WGS 1934 Web Mercator Auxiliary Sphere
O Use coordinate system of the data frame:
PCS: WGS 1984 Web Mercator Auxiliary Sphere
Units:
Square Kilometers [sq km]
Calculate selected records only
About calculating geometry
OK
Cancel
Figure 260 Calculate Geometry window in ArcMap, used to calculate area
9. From the main menu, click Selection > Select By Location.
10. In the Select By Location window (Figure 261):
a. In the Selection method dropdown list, choose select features from.
b. In the Target layer(s) box, check the NHD catchment layer (e.g. Catchment_reproj).
c. In the Source layer dropdown list, select the AOI shapefile (e.g. HUC_Tampa).
d. In the Spatial selection method for target layer feature dropdown list, select intersect the
source layer feature.
205
-------
e.
Click OK.
Select By Location
Select features from one or more target layers based on their location in
relation to the features in the source layer,
Selection method:
X
select features from
Target layer{s):
~ HUC_Tampa
0 Catchment_reproj
HI Only show selectable layers in this list
Source layer:
f3^ HUC_Tampa
"3
~ Use selected features (0 features selected)
Spatial selection method for target layer feature(s):
intersect the source layer feature
I I Apply a search distance
30000.000000 Meters
About select by location
OK
Apply
Close
Figure 261 Select By Location window in Arc Map
11. Do not clear the selection. Right-click on Catchment_reproj and open the attribute table.
12. Right-click on the "AreaKM2" field and choose Statistics,
13. In the Selection Statistics window (Figure 262):
a. In the Field dropdown list, confirm "AreaKM2" is displayed.
b. From the Statistics box, write down the Mean value (e.g. 6.215708 km2). This value is
used in later calculations.
Selection Statistics of Sub watershed
Reld
X
AreaKM2
Statistics:
Count: 3220
Minimum: 0.00115
Maximum: 522. BB39S4
Sum: 20D14.579927
Mean: 6.215708
Standard Deviation: 21.79037
Nulls: 0
Frequency Distribution
4,000
3,000
2,000
1,000
0
0.0 112.6 225.1 337.6 450.2
56.3 168.8 281.4 393.9 506.5
Figure 262 Selection Statistics for the Catchment_reproj AreaKM2 field
206
-------
14.
15.
16.
17.
18.
19.
20.
Layer Properties X
General Source Selection Display Symbology Fields Definition Query Labels Joins & Relates Time HTML Popup
Extent
Top:
3403559.687543 m
Left: -9229391.184685 m
Right: -9092391.693799 m
Bottom:
3182908.198367 m
Data Source
Data Type:
Shapefile Feature Class
A
Shapefile:
C: VJsers Vnjackson\. qgis\0.0. 3\Tampa_H20 V32_Tampa
Geometry Type:
Polygon
Coordinates have Z values:
No
Coordinates have measures:
No
Projected Coordinate System:
WGS_1984_Web_Mercator_Auxiliary_Sphere
Projection:
Mercator Auxiliary Sphere
False_Easting:
0.00000000
False_Northing:
0.00000000
V
<
>
Set Data Source...
OK ~| Cancel
Figure 263 Layer Properties window, under the Source tab, which displays the extents of the AOI
207
Various calculations are required to create the area-specific hexagonal grid. It is suggested
that the user copy values and calculations into a spreadsheet or record them on paper to
organize and track work.
Hexagon area will be set equal to the average catchment area. However, hexagons will be
created based on their width and height. Width is determined using the equation:
Hex width = 2.0*sqrt(/Wean value/6*sqrt(3))
Where the example Mean value = 6.215708,
Hex width = 2.0 * sqrt(6.215708 / 6 * sqrt(3))
Hex width = 2.0 * sqrt(6.215708 / 6 * 1.73205080757)
Hex width = 2.67904485964
Please note: all decimals listed are required throughout each calculation for accurate
hexagons.
The height of each hexagon is calculated using the hexagon width. Height is determined
using the equation:
Hex height = Hex width * sqrt(3)
Where the example hex width = 2.67904485964,
Hex height = 2.67904485964 * 1.73205080757
Hex height = 4.64024181265
To determine vertices for hexagon sides the orientation of the height and width values are
swapped. In this example, height is now 2.67904485964 km, and width is now
4.64024181265 km.
The new height and width values must be converted from kilometers into meters. In this
example, height is 2679.04485964 meters, and width is 4640.24181265 m.
In the Table of Contents, right-click on the AOI shapefile (e.g. HUC_Tampa) and select
Properties.
Under the Source tab, the Extent is listed for the Left, Bottom, Right, and Top coordinates
(Figure 263). Copy down each of these extents, indicating the specific location of each.
-------
21. New extents must be calculated for the hexagon layer by adding the width and height of the
hexagons to the original extents. Table 13 shows formulas and example calculations for the
new Left, Bottom, Right, and Top extent, where XMin is the original Left extent, YMin is the
original Bottom extent, XMax is the original Right extent, and YMax is the original Top extent.
Table 13 Formulas used to calculate the new area extents, using the original area extents, hex width, and hex
height
Extent Location
Base Formula
Example Formula
Example New Extent
LEFT
XMin + width * -2
-9229391.184685 +
4640.24181265* -2
-9238671.66831
BOTTOM
YMin + height * -2
3182908.198367 +
2679.04485964 *-2
3177550.10865
RIGHT
XMax + width * 2
-9092391.693799 +
4640.24181265*2
-9083111.21017
TOP
YMax + height * 2
3403559.687543 +
2679.04485964 *2
3408917.77726
22. In ArcMap, click the ArcToolbox icon to open ArcToolbox.
23. In the ArcToolbox window, navigate to the Create Fishnet tool (Data Management Tools >
Sampling > Create Fishnet)
24. In the Create Fishnet window (Figure 264):
a. In the Output Feature Class, name the output (e.g. Tampa_Fishnet1) and indicate the file
path.
b. Below the Template Extent option are blank fields for the Left, Bottom, Right, and Top
extents. In each text box, enter the corresponding newly calculated extent (e.g. Example
New Extent values in Table 13). Please note, the Bottom value may need to be entered
last.
c. In the Cell Size Width text box, enter the calculated hexwidth (e.g. 4640.24181265).
d. In the Cell Size Height text, box, enter the calculated hex height (e.g. 2679.04485964).
e. In the Number of Rows text box, enter 0.
f. In the Number of Columns text box, enter 0.
g. The Opposite corner of Fishnet coordinates will populate automatically.
h. Confirm the Create Label Points option is checked.
i. In the Geometry Type dropdown list, confirm POLYLINE is selected.
j. Click OK.
208
-------
Create Fishnet — ~ X
Output Feature Class
| L;V3ublicV^JacksonVH2Q_databasesV-l2Q_TampaVD2_Tampa\GridTheBay\Tampa.
Template Extent (optional)
TqP
3408917.777260
Left Right
-9238671.668310 | | -9083111.210170 |
Bottom
3177550.108650 |
Clear
Fishnet Origin Coordinate
X Coordinate Y Coordinate
-9238671.66831 |
3177550.10865 |
Y-Axis Coordinate
X Coordinate Y Coordinate
-9238671.66831 |
3177560.10865 |
Cell Size Width
4640,24131265 |
Cell Size Height
2679.04435964 |
Number of Rows
"1
Number of Columns
1 "1
Opposite corner of Fishnet (optional)
X Coordinate Y Coordinate
-9033111.210170001 |
3408917.77726
PI Create Label Points (optional)
Geometry Type (optional)
| POLYLINE
V
OK | Cancel 1 1 Environments..
[ Show Help >> j
Figure 264 Create Fishnet window in ArcMap, using the newly calculated extents
25. A second Fishnet layer must be created using offset extents. This will create an alternating
pattern of points, allowing the hexagons to fit together exactly. Formulas are similar to those
used to calculate the offset extents shown in Table 14. However, the newly created Fishnetl
extents are used as the initial extent in the calculations, instead of the original AOI extents.
Table 14 Formulas used to calculate the offset area extents, using the Fishnetl extents, hex width, and hex
height
Extent Location
Base Formula
Example Formula
New Offset Extent
LEFT
newXMin + width * 0.5
-9238671.66831 +
4640.24181265 *0.5
-9236351.5474
BOTTOM
newYMin + height * 0.5
3177550.10865 +
2679.04485964 *0.5
3178889.63108
RIGHT
newXMax + width * 0.5
-9083111.21017 +
4640.24181265 *0.5
-9080791.08926
TOP
newYMax + height * 0.5
3408917.77726 +
2679.04485964 *0.5
3410257.29969
26. Open the Create Fishnet tool (ArcToolbox >Data Management Tools > Sampling > Create
Fishnet).
27. In the Create Fishnet window (example shown in Figure 264):
a. In the Output Feature Class, name the output (e.g. Tampa_Fishnet2) and indicate the file
path.
209
-------
b. Below the Template Extent option are blank fields for the Left, Bottom, Right, and Top
extents. In each text box, enter the corresponding newly calculated offset extent (e.g.
New Offset Extent values in Table 14). Please note, the Bottom value may need to be
entered last.
c. In the Cell Size Width text box, enter the calculated hexwidth (e.g. 4640.24181265).
d. In the Cell Size Height text box, enter the calculated hex height (e.g. 2679.04485964).
e. In the Number of Rows text box, enter 0.
f. In the Number of Columns text box, enter 0.
g. The Opposite corner of Fishnet coordinates will populate automatically.
h. Confirm the Create Label Points option is checked.
i. In the Geometry Type dropdown list, confirm POLYLINE is selected,
j. Click OK.
28. Toggle both Jabel point layers (e.g. Tampa_Fishnet1 Jabel and Tampa_Fishnet2_label) on in
the Table of Contents. The_/aJbe/ point layers should create a rectangle of points around the
user's AOI in a zig-zag pattern, as shown in Figure 265. The user may right-click and remove
the Fishnet line layers (e.g. Tampa_Fishnet1 and Tampa_Fishnet2).
Figure 265 ArcMap project displaying Fishnet label layers over Tampa AOI and NHD catchments
29. Open ArcToolbox and navigate to the Define Projection tool (Data Management Tools >
Projections and Transformations > Define Projection).
30. In the Define Projection window (Figure 266):
a. In the Input Dataset or Feature Class dropdown list, select the first Fishnet label layer
(e.g. Tampa_Fishnet1Jabel).
210
-------
b. Click the Coordinate System
icon and enter 3857 into the search box. Select l/l/GS
1894 Web Mercator (auxiliary sphere) and click OK.
c. In the Coordinate System text box, WGS_1984_Web_Mercator_Auxiiiary_Sphere will
appear. Click OK.
31. Repeat steps 29-30 to define the projection for the second Fishnet label layer (e.g.
Tampa_Fishnet2_iabei).
Define Projection — ~ X
Input Dataset or Feature Class
OK
Cancel Environments... Show Help >>
|Tampa_Fishnet2Jabel
~3
e3
Coordinate System
WGS_1984_Web_Mercator_Auxiliary_Sphere
Figure 266 Define Projection window, setting the coordinate system for the Fishnet layer
32. Use the Append tool to combine both Fishnet label layers into one layer (ArcToolbox > Data
Management Tools > General > Append, Figure 187).
33. In the Append window (example shown in Figure 188):
a. In the Input Datasets dropdown list, select Tampa_Fishnet2_label.
b. In the Target Dataset dropdown list, select Tampa_Fishnet1_label.
c. Click OK.
34. Open the ArcToolbox window and locate the Create Thiessen Polygons tool (ArcToolbox >
Analysis Tools > Proximity > Create Thiessen Polygons, Figure 267).
Figure 267 ArcToolbox window, showing the location of the Create Thiessen Polygons tool
35. In the Create Thiessen Polygons window (Figure 268):
a. In the Input Features dropdown list, select the appended Fishnet layer (e.g.
Tampa_Fishnet1_label).
b. In the Output Feature Class text box, name the file path and shapefile (e.g.
Tampa_ Thiessen. shp).
c. In the Output Fields dropdown list, select ONLY_FID.
d. Click OK.
211
-------
C reate Th i essen P o lyg o n s
~
X
Input Features
| Tampa_Fishnet1 Jabel
Output Feature Class
E
L:\public\MJadtsonVH20_databasesVH20_Tampalip2_Tampa\GridTheBay\Tampa_DocC
Output Fields {optional)
ONLY FID
OK
Cancel
Environments.
Show Help >>
Figure 268 Create Thiessen Polygons window, used to create Thiessen polygons for the Fishnet points
36. Open ArcToolbox and navigate to the Minimum Bounding Geometry tool (Data Management
Tools > Features > Minimum Bounding Geometry).
37. In the Minimum Bounding Geometry window (Figure 269):
a. in the Input Features dropdown list, select the AOI shapefile (e.g. HUC_Tampa),
b. In the Output Feature Class text box, name the file path and layer name (e.g.
Tampa_Envelope.shp).
c. In the Geometry Type dropdown list, select ENVELOPE
d. Click OK.
, Minimum Bounding Geometry
~
X
Input Features
3
| HUC_Tampa
Output Feature Class
L:y3ublic\MJackson\H20_databases\H20_Tampa'JD2_Tampa\GridTheBayVrampa_DocC ^
Geometry Type (optional)
| ENVELOPE
Group Option (optional)
| NONE
Group Field (s) (optional)
~ OBJECTID
~ TNMID
1 1 MetaSource
1 1 SourceData
1 1 SourceOrig
1 1 SourceFeat
1 1 LoadDate
1 1 AreaSqKm
—1 AreaAcres
V
<
>
I I Add geometry characteristics as attributes to output (optional)
OK
Cancel
Environments...
Show Help »
Figure 269 Minimum Bounding Geometry window, used to create an envelope around the AOI extent
38. From the main menu, choose Selection > Select By Location.
212
-------
39. In the Select By Location window (example shown in Figure 261):
a. In the Selection method dropdown list, choose select features from.
b. In the Target layer(s) section, check Tampa_Thiessen.
c. In the Source layer dropdown list, select Tampa_Envelope.
d. In the Spatial selection method for target layer feature(s) dropdown list, select intersect
the source layer feature.
e. Click OK.
40. In the Table of Contents, right-click on Tampa_Thiessen and choose Data > Export Data.
41. In the Export Data window:
a. In the Export dropdown list, choose Selected features.
b. Under the Use the same coordinate system as option, toggle the data frame.
c. In the Output feature class text box, name the file path and shapefile (e.g.
Tampa_ ThiessenEnvelope. shp.
d. Click OK.
42. Open ArcToolbox and locate the Erase tool (ArcToolbox > Analysis Tools > Overlay > Erase).
43. In the Erase window (Figure 270):
a. In the Input Features dropdown list, select the Thiessen Envelope (e.g.
Tampa_ ThiessenEnvelope).
b. In the Erase Features dropdown list, select the NHD Catchment layer (e.g.
Catchment_reproj).
c. In the Output Feature Class text box, name the file path and output (e.g.
Tampa Thiessen_Erase. shp)
d. Click OK.
\
Erase
~
X
Input Features
| Tampa_ThiessenEnvelope
d
£3
Erase Features
| Catchment_reproj
jd
&
Output Feature Class
L:V3ublicVv1JacksonYH20_databases\H20_TampaliP2_Tampa\GridTheBay\Tampa_DocE
XY Tolerance (optional)
Meters
OK
Cancel
Environments... i Show Help >>
Figure 270 Erase window, used to remove Thiessen polygons that overlap the Catchment layer
44. Open ArcToolbox and locate the Merge tool (ArcToolbox > Data Management Tools >
General > Merge).
45. In the Merge window (Figure 271):
a. In the Input Datasets dropdown list, select the NHD Catchment layer (Catchment_reproj),
then select the erased Thiessen layer (e.g. TampaThiessen_Erase). Both layers will
appear in the box.
b. In the Output Dataset text box, name the file path and shapefile (e.g.
Catchment_ Grid Bay. shp).
X
c. In the Field Map section, select the "Id (Long)" field and click the Remove
d. Click OK.
icon.
213
-------
Merge
Input Datasets
~ X
-
> Catchnnent_reproj
TampaThiessen_Erase
E3
+
x
±
*
Output Dataset
L: \public ^ Jackson tyH 20_databases tyH 20_Tannpa 2_T ampa \GridTheBay \Tarmpa_
Field Map [optional)
0- GRIDCODE [Long)
EB FEATUREID (long)
(jl¦¦ SOURCEFC [Text)
El- AreaSqKM [Double)
El- HUC_14 fText)
[±]-HU_14_DS (Text)
S- AreaKT*12 [Float)
B- Input_FID [Long)
+
x
±
*
OK
Cancel
Environments.,.
Show Help >>
Figure 271 Merge window, used to combine the Catchment layer with the hexagonal grid
46. From the main menu, select Selection > Select By Attributes.
47. In the Select By Attributes window:
a. In the Layer dropdown list, select the merged layer (e.g. Catchment_GridBay).
b. In the list of fields, double click "FEATUREID". The field name will appear in the
Expression box below.
c. In the Expression box, type =0 after the field name. The full expression is "FEATUREID"
0.
d. Click OK.
48. In the Table of Contents, right-click on the merged layer (e.g. Catchment_GridBay and open
the attribute table.
49. In the attribute table, click the Show Selected Records ^ icon. The attributes for each
hexagon polygon will be listed.
50. Locate the "FID" field, right-click on the name, and choose Sort Ascending. Make note of the
first FID value (e.g. 55586); this value is used in the next Field Calculator calculation.
51. Right-click on the "FEATUREID" field and open the Field Calculator.
52. In the Field Calculator window (Figure 272):
a. In the Expression box, type the following equation: (([FID] - first "FID" value) * -1) -
1000000
b. In this example, the entered expression is: (([FID] - 55586) * -1) - 1000000
c. Click OK.
-------
Table
ilil * s - % ?
Catch m ent_G ridB ay
FID
Shape *
55586
Polygon
55587
Polygon
55588
Polygon
55589
Polygon
55590
Polygon
55591
Polygon
55592
Polygon
55593
Polygon
55594
Polygon
55595
Polygon
55596
Polygon
55597
Polygon
55598
Polygon
55599
Polygon
14 * 0 1
C ate h m ent_G r i d B ay
Field Calculator
Parser
® VBScript
Fields:
X
O Python
FID
Shape
GRIDCODE
FEATUREID
SOURCEFC
AreaSqKM
HUC_14
HU_14_DS
AreaKM2
Type:
(§) Number
O String
O^ate
Functions:
Abs( )
Atn ( )
Cos ( )
Exp [ )
Fix ( )
lnt()
Log ( )
Sin ( )
Sqr ( )
Tan [ )
1~1 Show Codeblock
FEATUREID =
(([FID] - 55586) * -1) -1000000
About calculating fields
Clear
Load..
OK
Cancel
~ X
12
lnput_FID
A
0
2995
0
344
0
72
0
38
0
39
0
73
0
3063
0
3029
0
106
0
174
0
3097
0
140
0
2996
0
2997
V
Figure 272 Field Calculator window with Catchment_GridBay attribute table
53. In the merged shapefile attribute table, right-click on "HUC_14" and open the Field Calculator.
54. In the Field Calculator window:
a. Clear the previous expression if it appears in the Expression box.
b. In the Fields list, double click on the "FEATUREID" field. The field name will appear in the
Expression box.
c. Click OK.
55. In the attribute table, locate the "SOURCEFC" field, and right-click to open the Field
Calculator.
56. In the Field Calculator window:
a. In the Expression box, type "Hex" (Please note, the quotation marks are required).
b. Click OK.
The hexagonal grid has been added to the NHD Catchment layer. The Importing Layers into QGIS
section details how to upload the updated NHD Catchment layer into the user database in QGIS.
Database creation is continued in the Create Road Layer section.
Create Road Layer
Download TIGER/Line data
215
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This section shows the step-by-step procedure for downloading the roads data for the Transportation Tool
(Advanced Module Only) in EPA H20. The Road layer is only used for the Transportation Tool and the
rest of EPA H20 functionality is available without this layer.
1. Navigate to https://www.census.gov/cqi-bin/qeo/shapefiles/index.phi to open the US Census
Bureau website (Figure 273).
2. In the Select year dropdown list, choose the most recently published year. In this example,
2018 has been selected.
3. In the Select a layer type dropdown list, select Roads.
4. Click the Submit button.
Figure 273 US Census Bureau TIGEFt/Line Shapefiles download website
5. The website will navigate to the next page, as shown in Figure 274.
6. Under the All Roads option, select the state containing the user's AOI (e.g. Florida).
7. Once a state is selected, a Select a County dropdown list will appear. Select the desired
county from the dropdown list (e.g. Hillsborough County).
8. Under the Select a County dropdown list, click the Download button.
216
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Primary Roads
1 Download national file i
Primary and Secondary Roads
Select a State: Alabama
Download
All Roads
Select a. State: Florida
¥
Select a County: H' sborough County v
1 Dow
Figure 274 TIGER/Line All Roads menu, with Florida selected from the dropdown box
9. Save the zip file and unzip the contents to a known location.
10. If the user's AOI is located across multiple counties or multiple states, the user must repeat
these steps to download all necessary data.
The Transportation Tool (Advanced Module Only) in EPA H20 requires TIGER/Line road data include
maximum speeds. TIGER does not supply this information, but there are several ways users can
generate it. Appendix C: Roads Speeds Table provides a lookup table of maximum speed national
averages for the different MTFCC codes in the TIGER/Line road data. The process for adding this
information to the Roads shapefile(s) is outlined in the ArcGIS Create Max Speed Dataset and QGIS
Create Max Speed Data sections. Maximum speeds vary from one area to the next, making local
sources that are more specific to the area of interest preferable to using the national averages. Each
state's Department of Transportation (DOT) may be a useful source of more locally specific max
speeds data. The following section outlines how a Max Speed shapefile was obtained for the state of
Florida.
A Max Speed shapefile can be downloaded for the state of Florida at:
1. Navigate to
https://www.arcais.com/home/item.html?id=4a61f17ab4784202ae10d7d5fb3bf9de#overview
to open the ArcGIS website (Figure 275).
2. Under Description > Download Data, click the hyperlink to open the login screen.
Download Max Speed data
217
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ArcGIS Features Plans Gallery Map Scene Help
m Sign In
Maximum_Speed_Limit_TDA
Data Visualization
The Maximum Speed Limit feature class shows the posted speed limit as derived
from event mapping Feature 311, characteristic MAXSPEED from the FDOT
Roadway Characteristics Inventory data.
iS< Feature Layer by mark.welsh_fdot9
Created: Jul 19, 2017 Updated: Jan 28, 2018 View Count: 666
Description
Download Data:
^ttps!7^^do^oWfne^^^/FD^^co/pianning/t^nsta^)i^shapefnes/maxspee^ip|
The FDOT GIS Maximum Speed Limits provides spatial information Maximum Speed Limits on Florida
Roadways. It is required for all designated roadways on the SHS and HPMS samples. This dataset is
maintained by the Transportation Data & Analytics office (TDA). The source spatial data for this hosted
feature layer was created on: 01/27/2018.
For more details please review the FDOT RCI Handbook here:
http://www.fdot.gov/planning/statistics/rci/RCIFC_Handbook.pdf
Layers
Open in Scene Viewer
Open in ArcGIS Desktop
Details
Source: Feature Service
Data Last Updated: Jan 28, 201 8
2:28:21 PM
Size: 11 MB
~ ~~
Owner
mark.welsh_fdot9
Tags
Figure 275 ArcGIS website, which contains FDOT MAXSPEED data for the state
3. Under Client Login, in the Username text box, enter Guest. No password is required.
4. Click Sign In.
Client Login
Username:
Guest] x
Password: (Forgot your password?)
Sign in
Figure 276 Client Login, with Guest entered as the username
5. Save the maxspeed.zip file and unzip the contents to a known location.
Using ArcGIS
218
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This section illustrates the creation of EPA H20 compatible road data using Esri ArcGIS software.
1. Open your existing ArcGIS map document file (.mxd), or create one following the steps
outlined in Set Up ArcGIS Map Document.
2. Use the Add Data ' icon to navigate to the TIGER/Line shapefile(s) and add it as a layer in
the Table of Contents.
3. If using a previously created Max Speed dataset, the layer must be added in the same way.
4. In the ArcToolbox window, navigate to and open the Project tool (ArcToolbox > Data
Management Tools > Projections and Transformations > Project, Figure 143).
5. In the Project window (example shown in Figure 144):
a. In the Input Dataset or Feature Class dropdown list, select the first TIGER/Line shapefile (e.g.
tl_2013_ 12057_roads).
b. The Input Coordinate System automatically lists the coordinate system of the selected
dataset (e.g. GCS North American 1983).
c. In the Output Dataset or Feature Class text box, browse to or type the desired file path
and name (e.g. Roads057.shp).
d. Click the Spatial Reference icon to set the Output Coordinate System to
WGS_1984_Web_Mercator_Auxiliary_Sphere, located under the World folder in
Projected Coordinate Systems. Alternatively, the user may type 3857 into the search box.
e. A Geographic Transformation is required to reproject the land use dataset. In the
dropdown list, choose WGS_1984_(ITRF00)_To_NAD_1983 if not already selected.
f. Click OK.
6. Repeat steps 4-5 to reproject any other TIGER/Line roads or max speed datasets.
If multiple Roads shapefiles were required for the AOI, the user must combine the TIGER/Line layers.
7. Open the Append tool in ArcToolbox (location shown in Figure 187).
8. In the Append window (example shown in Figure 188):
a. In the Target Dataset dropdown list, choose any one road shapefile to append the others
to (e.g. Roads057).
b. In the Input Datasets dropdown list, select all other road shapefiles.
c. Keep the Schema Type set to TEST and do not select a field map or subtype.
d. Click OK.
Create Max Speed Dataset
This section illustrates the creation of Maximum Speed data using the supplemental lookup table
(Appendix C: Roads Speeds Table). If the user obtained a Max Speed shapefile dataset, skip to the
User-Obtained Max Speed Data section.
1. Load the MaxSpeed_lookup.csv table into ArcMap, exported from Appendix C: Roads
Speeds Table.
2. Right-click on the appended Roads shapefile in the Table of Contents and choose Joins and
Relates > Join (Figure 183).
3. In the Join Data window (example shown in Figure 184):
a. In the first dropdown list, select Join attributes from a table.
b. In the Choose the field in this layer that the join will be based on dropdown list, choose
"MTFCC".
c. Under the Choose the table to join to this layer dropdown list, select
MaxSpeed_lookup.csv.
d. In the Choose the field in the table to base the join on dropdown list, select "MTFCC".
e. Togg le Keep all records
219
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f. Click OK.
6. Right click on the appended Roads shapefile and select Data > Export Data.
7. In the Export Data window (example shown in Figure 124):
a. In the Export dropdown list, select All features.
b. Under the Use the same coordinate system as option, toggle the data
c. In the Output feature class text box, navigate to the preferred file path
shapefile Roads.shp.
d. Click OK.
The Roads.shp output will contain the maximum speed data in miles per hour and
hour. Database creation is continued in the Importing Layers into QGIS section.
User-Obtained Max Speed Data
This section describes steps for using a Max Speed shapefile dataset.
1. Navigate to the Spatial Join tool in ArcToolbox, located in ArcToolbox > Analysis Tools >
Overlay (Figure 277).
Figure 277 Location of the Spatial Join tool in ArcToolbox
the Spatial Join window (Figure 278):
In the Target Features dropdown list, select the appended Roads shapefile (e.g.
Roads057).
In the Join Features dropdown list, select the max speed dataset (e.g. maxspeed_reproj).
In the Output Feature Class text, box, browse to or type the desired file name (e.g.
Roads_spatialjoin.shp) and file path.
From the Join Operation dropdown list, choose JOIN_ONE_TO_MANY.
Check Keep All Target Features.
In the Match Option dropdown list, select INTERSECT.
Click OK.
frame.
and name the
kilometers per
2. In
a.
b.
c.
d.
e.
f.
g-
220
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Spatial Join
~ X
Target Features
| Road5057
J
Join Features
| maxspeed_reproj
zi
Output Feature Class
| Dn\.qgis\0.0.3\Tampa_H2OV52_Tampa^uildingDatabase_Outputs\ArcMapV^oadsV^oads_spatialjoin.shp |
Join Operation (optional)
1 :OIN_ONE_TO_MANY
1^1 Keep All Target Features (optional)
Field Map of Join Features (optional)
LINEARID (Text)
FULLNAME 0"ext)
RTTYP (Text)
MTFCC (Text)
ROADWAY (Text)
ROAD_SIDE (Text)
OFFSET_DIR (Text)
BEGIN_POST (Double)
END_POST (Double)
SPEED (Double)
Shape_Leng (Double)
+
X
a
*
Match Option (optional)
| INTERSECT
Search Radius (optional)
Distance Field Name (optional)
Cancel Environments... Show Help >>
Figure 278 Spatial Join window, creating a join between the Roads shapefiie and max speed
Once max speeds have been successfully added to the Roads shapefiie these speeds may need to
be updated to meet the requirements of EPA H20. The field must be named "SPEED", cannot contain
zero values and should be in both miles per hour (MPH) and kilometers per hour (KMH).
3. To rename the field with the maximum speed data to "SPEED":
a. Create a new field in the Roads attribute table named "SPEED", with Short Integer type.
b. Populate this field with the maximum speed data using Field Calculator.
4. To update speeds with zero values to 25:
a. Right click on the spatially joined layer (e.g. Roads_spatialjoin) and open the attribute
table.
b. From the main menu, choose Selection > Select By Attributes (Figure 244).
c. In the Select By Attributes window (example shown in Figure 245):
i. Under the Layer dropdown list, choose the spatial join layer (e.g.
Roads_spatialjoin).
ii. From the list of fields, double click on the "SPEED" field.
iii. In the Expression box, type =0 after the field name, to search for "SPEED" =
0.
iv. Click OK.
d. Right click on the "SPEED" field and choose Field Calculator.
e. In the Field Calculator window:
i. In the Expression box, type 25.
ii. Click OK.
N
f. Clear the previous selection by clicking the Clear Selection icon in the attribute table.
5. If the max speed data are only in miles per hour:
221
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a. Add a new field in the attribute table (Table Options " > Add Field.
b. In the Add Field window:
i. In the Name text box, type SPEED_kmh.
ii. In the Type dropdown list, choose Double.
iii. Click OK.
c. Right click on SPEED_kmh in the attribute table and choose Field Calculator.
d. In the Field Calculator window:
i. From the Fields list, double click on the "SPEED" field.
ii. In the Expression box, type * 1.60934 after the field name.
iii. The full expression is [SPEED] * 1.60934
iv. Click OK.
The spatially joined layer (e.g. Roads_spatialjoin.shp) contains the maximum speed limit for the
TIGER/Line roads in miles per hour and kilometers per hour. The database creation is continued in
the Create User Point of Interest (POI) Layer section.
Using QGIS
This section illustrates the creation of EPA H20 compatible road data using QGIS software.
1. Open your existing QGIS map document file (.qgs), or create one following the steps outlined
in Set Up QGIS Map Document.
2. From the Layer menu (Figure 126) open the Add Vector Layer window (Main Menu > Layer >
Add Vector Layer).
3. In the Add vector layer window (example shown in Figure 127), click Browse to locate each
TIGER/Line roads shapefile, then click Open.
4. If using a previously created Max Speed dataset, the layer must be added in the same way.
5. Right-click on each layer, including the Max Speed layer (if available), and select the Save
as... option.
6. In the Save vector layer as... window (example shown in Figure 131):
a. In the Format dropdown list, select ESRI Shapefile.
b. In the Save as text box, browse to or type the desired output shapefile name (e.g.
Roads057.shp) and file path. The TIGER/Line outputs must be saved together in a new
folder, and the Max Speed dataset must be saved under a different file path.
c. In the CRS dropdown list, choose Selected CRS, and click the Browse button to locate
l/l/GS 84/ Pseudo Mercator.
d. Check Add saved file to map.
e. Do not check Skip attribute creation.
f. Click OK.
7. In the Layers panel, right-click on the original road shapefiles and choose Remove.
8. Open the Merge shapefiles tool to combine all TIGER/Line shapefiles (Vector > Data
Management Tools > Merge shapefiles to one (Figure 279)).
| Vector Raster Database Help Transportation H20 Toolbox |
Analysis Tools ~
Coordinate Capture ~
Scenarios Editinq Scenario:
Data Management Tools ~
^ Define current projection
W- Join attributes by location
k,r Split vector layer
Geometry Tools ~
Geoprocessing Tools ~
Research Tools ~
Road graph ~
t|l Merge shapefiles to one
Create spatial index
Figure 279 Location of the Merge shapefiles to one tool in EPA H20
-------
9. In the Merge shapefiles window (Figure 280):
a. In the Shapefile type dropdown list, choose Line.
b. Under Input directory, click Browse to navigate to the new TIGER/Line shapefile folder
created to hold the outputs from the step 6.
c. In the Output shapefile text box, name the output shapefile (e.g. TIGERJoin.shp) and file
path.
d. Check Add result to map canvas.
e. Click OK.
(31 Merge shapefiles
? X
Select by layers in the folder
Shapefile type Line
~
Input directory
:/0.0.3/Ta m p a_H 20/D 2_Ta m pa/Roads/Outputs
Browse
Output shapefile
la m p a_H 20/D 2_Ta rn p a/Ro a d s/TIG E R_j 0 i n. sh p
Browse
* Add result to map canvas
0%
0%
OK
Close
Figure 280 Merge shapefiles window, with the Roads/Outputs as the Input directory
Create Max Speed Data
This section illustrates the creation of Maximum Speed data using the supplemental lookup table
(Appendix C: Roads Speeds Table). If the user obtained a Max Speed shapefile dataset, skip to the
User-Obtained Max Speed Data section.
1. Load the MaxSpeed_lookup.csv table into the Layers panel, exported from Appendix C:
Roads Speeds Table.
2. In the Layers panel, double click on the merged Roads shapefile (e.g. TIGERJoin) to open
Layer Properties.
m
3. Under the Joins tab, click the Add Join icon.
4. In the Add vector join window (example shown in Figure 200):
a. In the Join layer dropdown list, select MaxSpeed_lookup.
b. In the Join field dropdown list, choose "MTFCC".
c. From the Target field dropdown list, select "MTFCC".
d. Check Cache join layer in virtual memory.
e. Click OK.
5. Right click on the merged Roads shapefile (e.g. TIGERJoin) and select Save as (Figure 132).
223
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6. In the Save vector layer as... window (example shown in Figure 133)\
b. In the Format dropdown list, select ESRI Shapefile.
c. In the Save as text box, browse to or type the desired file path and name the output
Roads, shp.
d. In the CRS dropdown list, choose Selected CRS, and click the Browse button to locate
l/l/GS 84/Pseudo Mercator.
e. Check Add saved file to map.
f. Do not check Skip attribute creation.
g. Click OK.
The Roads.shp output will contain the maximum speed data in miles per hour and kilometers per
hour. The database creation is continued in the Importing Layers into QGIS section.
User-Obtained M
This section describes steps for using a Max Speed shapefile dataset.
1. Open the Join attributes by location tool, as shown in Figure 158.
2. In the Join attributes by location window (example shown in Figure 159).
a. Under the Target vector layer dropdown list, choose the merged TIGER/Line shapefile
(e.g. TIGERJoin.shp).
b. In the Join vector layer dropdown list, select the saved Max Speed layer (e.g.
maxspeed_reproj).
c. Under Attribute Summary, toggle Take summary of intersecting features, and check Mean.
d. In the Output Shapefile text box, browse to or type the file path and name the shapefile
Roads.shp.
e. Under Output table, choose Keep all records (including non-matching target records)
f. Click OK.
Please note that this spatial join may take a few moments to process.
Troubleshooting Common Errors:
Problem:
A common error in this step results in an Incorrect field names error (Figure 209). Three pieces of
information help to understand the cause of this error: (1) Field names cannot be longer than 10
characters (2) Attribute Summary by Mean renames fields by adding MEAN in front of the original
field name (3) This results in field names with more than 10 characters when the original is more
than 6 characters.
Solution:
The user must create a new field for each of the fields listed in the error message. Open the
Layer Properties window for the corresponding layer and click the pencil icon to start editing.
Click on the New Column icon to add a new field to the fields list (example shown in Figure
205). The new field name must have 6 or less characters and have the same Type as the field it is
replacing. Open Field Calculator and choose Update Existing Field; from the dropdown list,
select the newly created field. From the Field and Values dropdown list, double click on the field
to be replaced. After the field appears in the Expression box, click OK. Delete the old field from
Layer Properties, using the Delete Column icon. Repeat these steps for each of the fields
listed in the error. Save the changes made to the Layer Properties and retry the Join attributes by
location tool.
224
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Once max speeds have been successfully added to the Roads shapefile these speeds may need to
be updated to meet the requirements of EPA H20. The field must be named "SPEED", cannot contain
zero values and should be in both miles per hour (MPH) and kilometers per hour (KMH).
3. To rename the field with the maximum speed data to "SPEED":
a. Create a new field in the attribute table named "SPEED", with Whole number (integer)
type.
b. Populate this field with the maximum speed data using Field Calculator.
4. To update speeds with zero values to 25:
a. In the Layers panel, locate Roads and toggle the display off, then right-click to open the
attribute table.
b. In the Roads attribute table, locate the Look for option:
In the Look fortext box, type NULL (as shown in Figure 248).
i. In the field dropdown list, select "SPEED".
ii. Click SEARCH.
Please note that the selection may take a few moments. Do not close the attribute table.
c. After the NULL values are selected, click the pencil
0;
icon to start editing.
d. Click the Field Calculator
icon to open Field Calculator. In the Field Calculator
window (example shown in Figure 247):
Check the Only update selected features option.
i. Check the Update existing field option.
ii. In the field dropdown list, select the "SPEED" field,
v. In the Expression box, type 25.
v. Click OK.
e. Click the Clear Selection
f. Toggle editing off by clicking the pencil
icon to clear the current selection.
icon and save the edits.
5. If the max speed data are only in miles per hour:
a. In the Layers panel, right-click on the Roads layer and open the attribute table.
b. Click the pencil
icon to start editing.
c. Click the Field Calculator
icon to open Field Calculator. In the Field Calculator
window (example shown in Figure 247):
Check the Create New Field option.
In the Output field name text box, type SPEED_kmh
From the Output field type dropdown list, select Decimal number (real).
Leave the Output field width and precision set to the default.
From the Fields and Values dropdown list, double click on the "SPEED" field.
In the Expression box, type * 1.60934 after the field name. The full expression is
"SPEED" * 1.60934
Click OK.
VII.
d. Toggle editing off by clicking the pencil
icon and save the edits.
The Roads.shp output will contain the maximum speed data in miles per hour and kilometers per
hour. The database creation is continued in the Create User Point of Interest (POI) Layer section.
225
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Create User Point of Interest (POI) Layer
This section illustrates the step- by -step procedure to create a user-defined Point of Interest layer.
Point features in the Point of Interest layer define the destinations in the Transportation Tool
(Advanced Module Only). The user can modify the existing transportation network based on these
points of interest.
1. Open your existing QGIS map document file (.qgs), or create one following the steps outlined
in Set Up QGIS Map Document.
2. Use the QGIS Plugin Manager (Main Menu > Plugins > Manage Plugins) to make sure the
Qspatialite plugin is enabled, as shown in Figure 290. If not already enabled, check the box next to
QSpatiaLite (Version 6.0.3) to activate the plugin, and click OK.
3. Open the Qspatialite plugin (Main Menu > Database > SpatiaLite > Qspatialite, Figure 291).
4. The Qspatialite window will open (Figure 292). Click the database dropdown list and locate the
user database. If the name of the database is not listed, it must be connected to the Qspatialite
plugin.
5. If the user-created database is not connected:
a. Connect to the UserDatabase.sqlite database by clicking the Open/Create new
Database icon
UserDatabase.sqlite is a renamed copy of TampaBay.sqlite,
created in the Setting Up a Project Directory section,
b. A warning message may appear that states "UserDatabase.sqlite already exists. Do
you want to replace it?" If this appears click Yes.
6. The name of the active database appears in the dropdown box. Make sure this is the user-
created database.
7. In the Tables list, right-click on User_POIs, and select Drop Table.
8. From the main menu, select Layer menu > New > New Spatialite Layer..., as shown in Figure 281.
& EPA H20 - UseCaseTwo
File Edit View Layer Settings Plugins Vector Raster Database Help Transportation H20 Toolbox
New ~
^ New Shapefile Layer... Ctrl+Shift+N I
\s\ & @
Embed Layers and Groups,,.
Add Vector Layer... Ctrl+Shift+V
IS1* New SpatiaLite Layer... Ctrl+Shrft+A
£% Add Raster Layer... Ctrl+Shift+R
Add SpatiaLite Layer... Ctrl+Shift+L
'H Add Delimited Text Layer
Figure 281 Add a new Spatialite layer in EPA H20 Power Mode
9. The New Spatialite Layer window will appear as shown in Figure 282. In the New Spatialite Layer
window:
a. Under the Database option, click the Choose a new database
0
icon, and navigate to the
new database created in Setting Up a Project Directory. This database does not contain POIs
for areas outside of Tampa, but using it as a template ensures the new user-defined POIs are
structured to work with the Transportation Tool (Advanced Module Only).
b. In the Layer name text box, enter User_POIs.
c. In the Type option box, select Point.
d. Click the Specify CRS button and in the Filter box, type 3857. Select l/l/GS 84/Pseudo
Mercator and click OK.
e. Check the Create an autoincrementing primary key check box.
f. Within the New Attribute section:
226
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i. In the Name text box enter "NAME".
ii. From the Type dropdown list, select "Text
data".
iii. Click Add to attributes list button. The "NAME"
attribute will appear in the Attributes list
section.
g. Repeat to add the following attributes:
i. In the Name text box enter "TYPE_DESC", and
in the Type dropdown list, select "Text data".
ii. In the Name text box enter "RECJJSE", and in
the Type dropdown list, select "Text data".
iii. In the Name text box enter "XCOORD", and in
the Type dropdown list, select "Decimal
number".
iv. In the Name text box enter "YCOORD", and in
the Type dropdown list, select "Decimal
number".
v. In the Name text box enter "xUTM", and in the
Type dropdown list, select "Decimal number".
vi. In the Name text box enter "yUTM", and in the
Type dropdown list, select "Decimal number".
vii. In the Name text box enter "Cost", and in the
Type dropdown list, select "Decimal number".
h. After the eight new attributes are listed in the
Attributes list section (Figure 282), click OK.
An empty point layer has been added to the new QSpatialite
database, which will be populated with the points of interest
when using the Transportation Tool (Advanced Module Only) in
EPA H20.
(jj) New Spatialite Layer
Database C:/Users/mjackson/.qgis/0.0.3/MobileBay_H20 ~ | ... |
Layer name User_POIs
Geometry column geometry
Type
<§> Point C Line ( Polygon
O Multipoint C Multiline ( Multipolygon
EPSG:3857 - WGS 84 / Pseudo Mercator Specify CRS
IM Create an autoincrementing primary key
New attribute
Name
Type
Attributes list
Decimal number
Add to attributes list
| Name
| Type
NAME
text
TYPE.DESC
text
RECJJSE
text
XCOORD
real
YCOORD
real
xUTM
real
yUTM
real
Cost
real
3 Remove attribute
Cancel
Help
Figure 282 New Spatialite Layer window
The database creation steps are complete. The Importing Layers into QGIS section details how to
import the finals layers into the user database using the QGIS Qspatialite plugin.
Importing Layers into QGIS
Each of the final layers created throughout Database Creation must be imported into the QGIS
Qspatialite plugin. Updating the Qspatialite table removes the Tampa-specific data from the user
database and replaces it with AOI-specific data. This section details how to upload the AOI shapefile
(HUC watershed boundary layer) into Qspatialite. The same steps must be followed to import the
other updated layers; Table 15 outlines the updated layers that need to be uploaded, and the naming
scheme required for each.
1. Open EPA H20 in Power Mode.
2. In the Choose a Module window, click OK (Figure 283).
Til
-------
i. EPA H 20 P roj ect Man a g er
Choose a Module
X
• Basic User - Green Report
Advanced User - Land Use Change and Comparison
Switch module in the future by clicking on this icon- [5]
OK
Cancel
Figure 283 EPA H20 Choose a Module window
3. I n the Select Project window, select Open existing project or Create new project. For first
time Power Mode users, choose Create new project (Figure 284).
Figure 284 EPA H20 Select Project window
4. In the Project Configuration window (Figure 285):
a. Confirm that the Source Database Name is referencing the original TarnpaBay.sqlite.
If the source database is not the original TarnpaBay.sqlite, click the Select button, and
navigate to the original "0.0.3" folder.
b. In the Name Your Project Database text box, enter the preferred project name (e.g.
Demo), and click OK.
228
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EPA H20 Project Manager ? X
Project Configuration
Select the Top Level Folder of EPA Dataset Select
Data Folder Path: C:/Users/mjackson/.qgis/0.0.3
Source Database Name: TampaBay.sqlite
Name Your Project Database | Demo|
OK Cancel
Figure 285 Project Configuration window
In the Select Area of Interest window, click Cancel.
From the Settings menu (Figure 116), open the Project Properties window (Main Menu >
Settings > Project Properties).
In the Project Properties window (Figure 286):
a. Click the Coordinate Reference System (CRS) tab and check the box labeled
Enable 'on the fly' CRS transformation.
b. In the Filter text box, type 3857.
c. Under the Coordinate reference systems of the world section, select H/GS 84/
Pseudo Mercator.
d. Click OK to apply these changes and close the Project Properties window.
(J Project Properties
? X
\ General ^ Coordinate Reference System (CRS) Hfl Identifiable layers OWS Server
X Enable 'on the fly' CRS transformation
Filter 3857
Recently used coordinate reference systems
Coordinate Reference System
[ Authority ID
WGS 84 / Pseudo Mercator
EPSG:3857
<
_l IllLl
Coordinate reference systems of the world
Hide deprecated CRSs
I Coordinate Reference System
Authority ID
G Mercator
WGS 84 / Pseudo Mercator
EPSG:3857
T
L
~
+proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 +lon_0=0.0 +x
+nadgrids=@null +no_defs
_0=0.0 +y_0=0 +k=1.0 +units=m
jk.
~
OK
Cancel Apply Help
Figure 286 Project Properties window in EPA H20
-------
8. From the Layer menu (Figure 287) open the Add Vector Layer window (Main Menu > Layer >
Add Vector Layer).
£ EPAH20
File Edit View
Layer
Settings Plugins Vector Raster Database
New ~
ISI & G
Embed Layers and Groups.,,
Layers
B,. Add Vector Layer... Ctrf+Shift+V
A^d Raster Layer... Ctrl+Shift+R
% Add SpatiaLite Layer... Ctrl+Shift+L
b Add Delimited Text Layer
Figure 287 Location of the Add Vector Layer tool in EPA H20
9. In the Add vector layer window (Figure 288), click Browse to locate and select the layer being
added (e.g. the HUC watershed boundaries layer, HUC_Tampa.shp), then click Open.
^ Add vector layer ? X
Source type
• File Directory O Database Protocol
Encoding System T
Source
Dataset se_Outputs/ArcMap/HUC_Boundary/HUC_Tampa.shp Browse
Open Cancel Help
Figure 288 EPA H20 Add Vector Layer window
10. In the Layers panel, right-click on the added layer (e.g. HUC_Tampa) and choose Set Layer CRS
(Figure 289).
Layers A x
B H r HHP Tan
j... Zoom to Layer Extent
Show in Overview
i Remove
Set Layer CRS
Set Project CRS from Layer
ill Open Attribute Table
Figure 289 Set Layer CRS in EPA H20
230
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11. In the Filter box, type 3857 and under the Coordinate reference systems of the world
section, choose M/GS 84/Pseudo Mercator. Click OK.
12. In the Layers panel, right-click on the added layer again, choose Rename, and type
the Required Qspatialite Name from Table 15 that corresponds to the layer. For the HUC
boundaries layer, Watersheds is required as the new layer name, and the layer must be
renamed "Watersheds" to function correctly in the database.
13. Use the QGIS Plugin Manager (Main Menu > Plugins > Manage Plugins) to make sure the
QSpatialite plugin is enabled, as shown in Figure 290. If not already enabled, check the box
next to QSpatiaLite (Version 6,0.3) to activate the plugin, and click OK.
^ QGIS Plugin Manager ? X
Filter
To enable / disable a plugin, click its checkbox or description
Point sampling tool (Version 0.3.3) ~
iil Collects polygon attributes and raster values from multiple layers at specified
sampling points
Installed in Plugins menu/toolbar
QConsofidate (0.1.0)
~ Consolidate QGIS project into one directory
Installed in Plugins menu/toolbar
J*
QSpatiaLite (Version 6.0.3)
SpatiaLite GUI for SpatiaLite: load/export SpatiaLite tables/Query to QGIS
Canvas, Import DBF, ...
Installed in Plugins menu/toolbar
QuickOSM (1.4.6) [ incompatible ]
Plugin Directory: C:/PROGRA~2/EPA H20/apps/qgis/plugins
OK
Select All Clear All Cancel
Figure 290 Confirm the box next to Qspatialite plugin in checked
14. Open the Qspatialite plugin (Main Menu > Database > SpatiaLite > Qspatialite, Figure
291).
Raster
Database Help Transportation H20 Toolbox
DB Manager*
SpatiaLite * ' QspatiaLite
1
® II |T] Scenario Manager |T) Edit Scenario
Figure 291 Location of the Qspatialite plugin in EPA H20
15. When the Qspatialite window opens (Figure 292), the name of the active database appears in the
database box (i.e. TampaBay.sqlite in Figure 292). Click the database dropdown (downward arrow
beside database box) to see the full dropdown list of connected databases. Both the original
TampaBay.sqlite database and the user-created database must be listed in the database
dropdown list.
231
-------
^ Qspatialite
-
~ X
TampaBay.sqlite
S JbI x
®LU
M
(A «
0 Si
Tablet-
s' V Stable_Climate
0 St? Strategic_Habitat_Conser..
® 6 Subwatershed
@ £ SustainableForestry
0 [j UCMnalysisLayer
Usable_Air
Usabte_Water
User_POIs
Watersheds
WoodstorkJMests
_sm_ext_m g mt
lookUPvars
n o I d entSu bwatershed
sqlite_stat3
E Spatial Index
E& Sys, Table
SQL Result
Option
Table Name Geometry field
SqIResult Geometry
Figure 292 Qspatialite ptugin window in EPA H20
16. If the original TampaBay.sqlite database is not listed:
a. Connect to the TampaBay.sqlite database by clicking the Open/Create new
Database icon , The database is placed in the following directory during
installation: (~\.qgis\0.0.3\data\database\TampaBay.sq!ite).
b. A warning message may appear that states "TampaBay.sqlite already exists. Do you
want to replace it?" If this appears click Yes.
17. If the user-created database is not listed:
a. Connect to the UserDatabase.sqlite database by clicking the Open/Create new
*J
Database icon . UserDatabase.sqlite is a renamed copy of TampaBay.sqlite,
created in the Setting Up a Project Directory section,
b. A warning message may appear that states "UserDatabase.sqlite already exists.
Do you want to replace it?" If this appears click Yes.
18. Make the user-created database the active database by selecting it from the database
dropdown list (Figure 293).
19. Tables in the active database are listed in the Tables box, below the active database name.
Before a new layer can be added to a database, tables with the same name as the layer (e.g. the
Watersheds tablej, must be removed by right-clicking the table name and choosing Drop Table
(Figure 293).
232
-------
(jj Qspatialite
~
X
UserDatabase.sqlite
Tables
© W Strategic_Habitat_Conservati„.
© lJ*i Sub watershed
© Sustainable_Forestry
© [J UCMnalysisLayer
© ft Usable_Air
© £ Usable_Water
© •*. User POIs
D
Waters!
:©
Woods!
! ©
_sm_e
!©
lookUP
©
noldenl
;©
s
sqlite s
3 Spatial Index
©Sys. Table
Refresh Tree
New Table
New View
Show Metadata
Drop Table
Load in QGIS
^amnlp
@PSI@0BI
SQL I Result 1
Option
(til fo
Table Name
I T | I SqIResult
Geometry field
| Geometry
Run SQL
Figure 293 Drop the original Watersheds table in Qspatialite with a right-click
20. To add the new layer in the database, click on the Import QGIS Layers icon in the
Qspatialite window. In the Import QGIS Layers window (Figure 294):
a. Highlight the layer to be added (e.g. Watersheds) from the list of layers in the current
map.
b. Check the box next to Destination SRID and type 3857 into the text box.
c. Click OK
^ Import QGIS Layers ? X
Available QGIS Layers:
Watersheds
select all
Import only selected values
X Desination SRID 3357
Prefix q
Reset
Q
OK
Cancel
Figure 294 Import Watersheds layer into Qspatialite
233
-------
The final Qspatialite table in QGIS should contain the updated tables for Watersheds, Land Use,
Roads, and Hydrology, as well as the updated lookup table. Please note, the final lookup table must
be updated in Qspatialite, even if FLUCCS land use and the original lookup table were used for
database creation. The name and description of each updated layer is detailed in Table 15, with the
name required for the user database.
Table 15 Final Qspatialite table inputs, with the description of each layer, and links to each creation section
Example File
Layer Description
Required
Qspatialite
Name
Creation Section(s)
HUC_Tampa.shp
Shapefile of user-specific
HUC watershed
boundaries
Watersheds
Create HUC Watershed
Boundaries
Land_Use.shp
Shapefile with spatially
joined land use and soil
data, updated ES
coefficients, and has been
joined with the lookup table
with complete field
calculations
Land_Use
Create Land Use Data
Layer
Create Soil Data Layer
Update ES Coefficients
Joining Lookup Table
Roads, shp
Shapefile with spatially
joined TIGER/Line roads
(appended) and Max
Speed data
Roads
Create Road Layer
Catchment reproj.shp
OR
Catchment Grid Bay. shp
NHD Catchment shapefile,
OR with hexagon layer
added (Esri ArcGIS only)
Subwatershed
Create NHDPIus V2
Data Layers
NHDFio wiine_reproj. shp
NHD Flowline shapefile
NHD_fiowiines
NHDWaterbody_reproj. shp
NHD Waterbody shapefile
NHD_ Waterbody
iookUPvars.dbf
supplemental lookup table
with updated ES
coefficients
iookUPvars
Updated throughout
Database Creation
For full functionality the Qspatialite table must contain the default tables copied from the original
Tampa Bay database.
After the tables created throughout Database Creation have been input into the Qspatialite plugin, the
user's database is functional in the Advanced Module setting of EPA H20. The user may select their
AOI By Shapefile By Drawing on Map, or By River Basin (Advanced Module Only).
To select an AOI By County in the new database, the Counties layer must be updated in the
Qspatialite plugin. This requires a Counties shapefile, containing the county boundaries from the area
of interest. The shapefile must also list the name of each county in a "NAME" field (the field name
"NAME" is required for functionality).
Update Land Use Comparison Datasets in Qspatialite
The user may choose to replace the original FUTUREtwenty, FUTUREforty and/or FUTUREsixty
tables with their own scenarios, as explained in the Create Land Use Comparison Data section. The
new land use comparison dataset(s) must be input into the Qspatialite plugin under the names
created within the Tampa Bay database. The user may add up to three land use comparison datasets,
and must rename their layer(s) FUTUREtwenty, FUTUREforty, and/or FUTUREsixty. These will
234
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appear as Land_Use_2020, Land_Use_2040, and Land_Use_2060 (respectively) in EPA H20, even
if data from other years were inserted. The user may change these display names by updating the
UC2AnalysisLayer table:
1. Open the Qspatialite plugin and locate UC2AnalysisLayer within the user database.
2. Right-click on the table and choose Load in QGIS.
3. In the Layers panel, right-click on UC2AnalysisLayer and choose Save As.
a. In the Format dropdown list, select Comma Separated Value.
b. Click Browse to save the output in a known location and name the output
UC2AnalysisLayer.
c. Click OK.
4. Locate the UC2AnalysisLayer in File Explorer, right-click, and open the file with Notepad or
the preferred text editor.
a. The user may change Land_Use_2020, Land_Use_2040, and/or Land_Use_2060 to
display a different year. For example, Land_Use_2020 can be changed to
Land_Use_2001. However, the name must start with Land_Use_20\ only the last two
digits can be changed.
b. Please note, the Land_Use_2006 name cannot be changed, and therefore other
comparison layers cannot be named Land_Use_2006.
c. Save the updated CSV file.
5. From File Explorer, drag and drop the updated file into the EPA H20 Layers panel.
6. Using the Qspatialite plugin, remove the previous UC2AnalysisLayer table from the user
database and add the new UC2AnalysisLayer (as shown in Importing Layers into QGIS).
235
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243
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Appendix A; Supplemental NLCD Lookup Table
This section contains the supplemental NLCD lookup table (Table 16), which is updated throughout database creation. The lookup table contains NLCD land use
descriptions, as well as the coefficients required for EPA H20 functionality. The table must be exported as a .csv and converted to a .dbf to make changes using Esri
ArcGIS or QGIS. Table 17 lists the references used to determine the Denitrification and Carbon Buried coefficients for each NLCD land use class in the lookup table.
Usir
1. Copy both sections of Table 16 ("PKUID" through "FloodProt" fields) into a new Excel spreadsheet. Save the file to a known location and name the output with a
.csv extension (e.g. lookUPvars_supplemental.csv).
a. Note: if an error occurs while importing the .csv file into ArcMap, resave the Excel spreadsheet with a .txt extension.
2. Open your existing ArcGIS map document file (.mxd), or create one following the steps outlined in Set Up ArcGIS Map Document.
3. Use the Add Data T icon to navigate to and add the lookup .csv file (e.g. lookUPvars_supplemental.csv) as a layer in the Table of Contents.
4. In the Table of Contents, right-click on the lookup table and choose Data > Export. In the Export Data window:
a. In the Export dropdown list, select All records.
b. Next to the Output table text box, click the Browse button and navigate to the preferred file path. In the Save as type dropdown list, select
dBASE Table, and in the Name text box, enter lookUPvars.dbf. Click Save.
c. Click OK.
The exported lookup table should be edited to update the coefficients for the user's specific area of interest following the steps outlined in the Update ES Coefficients
section. The "canopyVal", "usablewat", "StableClim", "Us_Air_Dol", "CN" and "FloodProt" fields will be populated in the Joining Lookup Table section. Once the table has
been updated for the specific area of interest, it is imported into the Qspatialite plugin as described in the Importing Layers into QGIS section.
Using QGIS
1. Copy both sections of Table 16 ("PKUID" through "FloodProt" fields) into a new Excel spreadsheet. Save the file to a known location and name the output with a
.csv extension (e.g. lookUPvars_supplemental.csv).
2. Open your existing QGIS map document file (.qgs), or create one following the steps outlined in Set Up QGIS Map Document.
3. From the main menu, select Layer > Add Delimited Text Layer.
4. In the Create a Layer from a Delimited Text File window:
a. Click the Browse button to locate the lookup .csv table.
b. Under the Selected Delimiter option, select Comma.
c. In the X field and Y field dropdown list, leave the default fields.
d. Click OK.
5. QGIS may try to map the attributes, this can be disregarded. In the Layers panel, right-click on the lookup table and choose Save as.
6. In the Save vector layer as window:
a. In the Format dropdown list, select ESRI Shapefile.
b. In the Save as text box, browse to the desired location and name the output lookUPvars.shp.
-------
c. In the CRS dropdown list, choose Selected CRS, and click the Browse button to locate l/l/GS 84/Pseudo Mercator.
d. Click OK.
7. In File Explorer, locate the .dbf file that coincides with the lookup shapefile (lookUPvars.dbf) and click and drag the file into the Layers panel.
Although the exported lookup table is saved as a "shapefile", the output is an editable table (lookUPvars.dbf), which is updated throughout database creation to change
the coefficients for the user's specific area of interest. The "canopyVal", "usablewat", "StableClim", "Us_Air_Dol", "CN" and "FloodProt" fields will be populated in the
Joining Lookup Table section. Once the table has been updated for the specific area of interest, it is imported into the Qspatialite plugin as described in the Importing
Layers into QGIS section.
Table 16 Supplemental NLCD lookup table, with land use descriptions and coefficients needed for EPA H20
PKUID
FLUCCS
FLUCSDESC
GRIDCODE
NLCDDesc
denitrific
CarbonFixe
Canopy
canopyVal
32
5400
Open Water
11
Open Water
8.3
155
0
11
1900
Developed Open Space
21
Developed Open Space
1.27
105
22
1
1100
Developed Low Intensity
22
Developed Low Intensity
0.98
78
10
2
1200
Developed Medium
Intensity
23
Developed Medium Intensity
0.6
45
3
3
1300
Developed High Intensity
24
Developed High Intensity
0.24
17
1
6
1600
Barren Land
(Rocks/Sand/Clay)
31
Barren Land (Rocks/Sand/Clay)
1.1
0
1
26
4200
Deciduous Forest
41
Deciduous Forest
0.2
8
71
23
4100
Evergreen Forest
42
Evergreen Forest
0.1
47
57
27
4340
Mixed Forest
43
Mixed Forest
0.1
28
75
21
3200
Shrub/Scrub
52
Shrub/Scrub
0.9
20
5
20
3100
Grassland/ Herbaceous
71
Grassland/Herbaceous
0.1
30
3
12
2100
Pasture/Hay
81
Pasture/Hay
1.4
49
6
16
2400
Cultivated Crops
82
Cultivated Crops
0.9
43
1
41
6300
Woody Wetlands
90
Woody Wetlands
17.2
194
67
42
6400
Emergent Herbaceous
Wetlands
95
Emergent Herbaceous
Wetlands
12.9
187
8
245
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A
B
C
D
LEVI
dni
waterRet
stabClim
usWat
usablewat
StableClim
Us_Air_Dol
CN
FloodProt
100
100
100
100
5
8.3
2
37
3
39
61
74
80
1
1.27
2
37
3
54
70
80
85
1
0.98
2
37
3
61
75
83
87
1
0.6
2
37
3
77
85
90
92
1
0.24
2
37
3
77
86
91
94
7
1.1
2
37
3
36
60
73
79
4
0.2
2
37
3
36
60
73
79
4
0.1
2
37
3
36
60
73
79
4
0.1
2
37
3
35
56
70
77
3
0.9
2
37
3
30
58
71
78
3
0.1
2
37
3
39
61
74
80
2
1.4
2
37
3
72
81
88
91
2
0.9
2
37
3
49
65
72
80
6
17.2
2
37
3
49
65
72
80
6
12.9
2
37
3
Table 17 References used to determine Denitrification and Carbon Buried coefficients for each NLCD land use class
NLCD Land Use Classes
Denitrification References
Carbon Buried References
Open Water
An et al. 2001; An and Gardner 2002; Bianchi et al. 1999;
Brenner et al., 2001; DeLaune et al. 2005; Fennel et al.
2009; Gardner et al. 2006; Gihring et al. 2010; Heffernan
and Cohen 2010; James et al., 2011; Joye and Anderson
2008; Messer and Brezonik 1983; Mortazavi et al. 2000;
Pina-Ochoa and Alvarez-Cobelas 2006; Pina-Ochoa and
Alvarez-Cobelas 2006; Seitzinger 1988; Seitzinger et al.
2006; Smith et al. 1985
Boyd et al. 2010; Brenner et al. 2001; Craft and
Richardson 1993; Munsiri et al. 1995; Tepe and Boyd
2002
Developed Open Space
Calculated as explained in the Determine Nitrogen
Removal Rates section
Calculated as explained in the Carbon Fixation Rates
for Developed Classes section
Developed Low Intensity
Developed Medium Intensity
Developed High Intensity
Barren Land (Rocks/Sand/Clay)
Jackson et al. 1990
N/A
246
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Deciduous Forest
Barton et al 1999; Chestnut et al. 1999
Downing et al. 2008; Johnston et al. 1996; Laffoley
and Grimsditch 2009; Mcleod et al. 2011; Vesterdal et
al. 2002
Evergreen Forest
Barton et al 1999; Henrich and Haselwandter 1997;
Robertson et al. 1987
Garten Jr 2002; Hooker and Compton 2003;
Huntington 1995; Richter etal 1999; Schiffman and
Johnson 1989
Mixed Forest
Barton et al. 1999; Dutch and Ineson 1990; Goodroad
and Keeney 1984
Calculated average based on "Deciduous Forest" and
"Evergreen Forest" references
Shrub/Scrub
Jackson et al. 1990
Lawrence et al. 2012
Grassland/Herbaceous
Frank and Groffman 1998; Robertson et al. 1987; Tsai
1989
Burke et al. 1995; Downing et al. 2008; Gebhart et al
1994; Knops and Tilman 2000; Laffoley and
Grimsditch 2009; Post and Kwon 2000
Pasture/Hay
Barton et al. 1999; Espinoza 1997; Seitzinger et al.
2006
Downing et al. 2008
Cultivated Crops
Barton et al. 1999, Espinoza 1997, Tsai 1989
Pacala et al. 2001; Houghton 1999
Woody Wetlands
Bowden 1987; DeLaune et al. 1998; Gale et al. 1993;
Lindau et al. 2008; Seitzinger 1994; Walbridge and
Lockaby 1994
Breithaupt et al. 2012; Engle 2011; Hanson and
Nestlerode 2014
Emergent Herbaceous Wetlands
Craft et al. 2009; DeLaune et al. 1989; Dodla et al. 2008;
Gale et al. 1993; Morris 1991; Nixon and Lee 1986;
Reddy et al. 1989; Seitzinger 1988; Wigand et al. 2004
Brenner et al. 2001; Chmura et al. 2003; Day et al.
2004; DeLaune et al. 1981; Downing et al. 2008;
Duarte et al. 2005; Laffoley and Grimsditch 2009
247
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Appendix B: Air Quality Reference Table
This section contains the supplemental Air Quality reference table (Table 18), which details the average pollutant removal rates for 55 metropolitan areas in the
continental United States (Nowak et al., 2006). The "TOTgm2" field contains the sum of the pollutant rates, and "Value_m2" is the sum of each monetary value
multiplied by that total. The estimated values ($) for removal of each pollutant were $959/ton Carbon Monoxide, $6752/ton Ozone, $1653/ton Sulfur Dioxide,
$4508/ton Particulate Matter (PM10), and $6752/ton Nitrogen Dioxide (Murray et al., 1994).
The user may locate the city nearest their area of interest and use the appropriate "Value_m2" value in the Air Quality section. If the user is unsure which city is
closest to their area of interest, the user may alternatively copy Table 18 into an Excel spreadsheet, and export the table to create a shapefile using Esri ArcGIS
or QGIS.
Usir
1. Copy Table 18 into a new Excel spreadsheet. Save the file to a known location and name the output with a .csv extension (e.g. AQ_AttributeTable.csv).
2. Open your existing ArcGIS map document file (.mxd), or create one following the steps outlined in Set Up ArcGIS Map Document.
3. From the main menu choose File > Add Data > AddXY Data. In the AddXY Data window:
a. In the Choose a table from the map or browse for another table dropdown list, click the Browse button and navigate to the exported .csv file. The
file name will appear in the dropdown list.
b. In the X Field dropdown list select the "X" field, and in the Y Field dropdown list, select the "Y" field (if not already populated).
c. Under the Coordinate System of Input Coordinates box, click the Edit button. In the XY Coordinate System search box, type 4326 and select l/l/GS
1984. Click OK.
d. Click OK.
4. A message will appear that explains "Table Does Not Have Object-ID Field". Click OK.
5. The table will appear in the Table of Contents. Right-click on the table and choose Data > Export Data (as shown in Figure 123 and Figure 124).
6. In the Export Data window:
a. In the Export dropdown list, select All features.
b. Under the Use the same coordinate system as section, toggle the data frame option.
c. In the Output feature class text box, name the output AirQualityReference.shp.
d. Click OK.
The exported shapefile can be used in the Air Quality section, to calculate the land use air pollution removal rates based on the nearest city.
Using QGIS
1. Copy Table 18 into a new Excel spreadsheet. Save the file to a known location and name the output with a .csv extension (e.g. AQ_AttributeTable.csv).
2. Open your existing QGIS map document file (.qgs), or create one following the steps outlined in Set Up QGIS Map Document.
3. From the main menu, select Settings > Project Properties.
4. In the Project Properties window:
a. Toggle on the Enable 'on the fly' CRS transformation option if not already on by default.
b. In the Filter box, type 4326, and under Coordinate reference systems of the world, select l/l/GS 84.
c. Click OK.
248
-------
5. From the main menu, select the Layer > Add Delimited Text Layer.
6. In the Create a Layer from a Delimited Text File window:
a. Click the Browse button to locate the exported .csv file (e.g. AQ_AttributeTable.csv).
b. Under the Selected Delimiter option, select Comma.
c. In the X field dropdown list select the "X" field, and in the Y field dropdown list, select the "Y" field (if not already populated),
e. Click OK.
7. In the Layers panel, right-click on the Air Quality table and choose Save as.
8. In the Save vector layer as window:
a. In the Format dropdown list, select ESRI Shapefile.
b. In the Save as text box, browse to the desired location and name the output AirQualityReference.shp.
c. In the CRS dropdown list, choose Selected CRS, and click the Browse button to locate l/l/GS 84/Pseudo Mercator.
d. Check Add saved file to map.
e. Click OK.
9. Repeat steps 3 and 4 to change the project coordinate system back to WGS 84/Pseudo Mercator.
Note: after the coordinate system is changed back, layers that were previously in the Layers panel may need to be removed and re-added into the map to draw
correctly.
The exported shapefile can be used in the Air Quality section, to calculate the land use air pollution removal rates based on the nearest city.
Table 18 Average removal rates for carbon monoxide (CO), ozone (03), particulate matter (PM10), sulfur dioxide (S02), and nitrogen dioxide (N02) for 55 U.S. cities
FID
X
Y
City
State
COgm2
03gm2
SOgm2
PMgm2
NOgm2
TOTgm2
Value_m2
0
-73.7562
42.65258
Albany
NY
0.1
3.4
0.5
2.4
1
7.4
0.04145
1
-106.606
35.0853
Albuquerque
NM
0.3
2.4
1.1
2.6
1.2
7.6
0.038134
2
-84.3863
33.75374
Atlanta
GA
0.3
4.6
0.8
3.8
1.2
10.7
0.057902
3
-97.7505
30.26693
Austin
TX
0.6
5.2
1.7
3.1
2
12.6
0.065975
4
-76.6094
39.29923
Baltimore
MD
0.3
4
1.3
3.7
2.7
12.1
0.064355
5
-91.1474
30.47116
Baton Rouge
LA
0.5
4.8
0.9
3.5
1.3
11
0.058932
6
-71.0571
42.36114
Boston
MA
0.3
3.8
1.1
2.8
2.1
10.2
0.054565
7
-73.1952
41.18649
Bridgeport
CT
0.3
3.4
0.8
2.8
1.6
9
0.047993
8
-78.8787
42.88023
Buffalo
NY
0.2
3.7
1.5
2.1
1
8.5
0.043873
9
-81.6326
38.34981
Charleston
WV
0.1
2.7
1
1.9
0.9
6.7
0.034621
10
-84.512
39.10312
Cincinnati
OH
0.3
3
1.2
3.3
1.8
9.5
0.049557
11
-81.6813
41.50549
Cleveland
OH
0.3
3.7
1.4
4.7
1.5
11.6
0.0589
12
-81.0348
34.0007
Columbia
SC
0.4
4.1
1.3
3
0.7
9.6
0.048466
13
-82.9988
39.96119
Columbus
OH
0.2
3.7
0.6
3
1.8
9.2
0.051844
14
-96.797
32.7767
Dallas
TX
0.5
4.7
0.4
3.6
1.2
10.5
0.057206
249
-------
15
-104.99
39.73919
Denver
CO
0.2
2.1
0.7
3.1
1.8
7.9
0.041656
16
-83.0458
42.3314
Detroit
Ml
0.2
3.1
0.9
3.4
1.1
8.7
0.045365
17
-106.485
31.7619
El Paso
TX
0.4
3.1
1.1
4
0.4
9
0.043866
18
-119.773
36.7468
Fresno
CA
0.3
5.1
0.6
6.7
1.6
14.3
0.076721
19
-157.858
21.3069
Honolulu
HI
0.6
6.6
0.5
5
0.5
13.3
0.071881
20
-95.3698
29.7604
Houston
TX
0.4
4.5
1.8
4.7
2
13.4
0.068435
21
-86.1581
39.7684
Indianapolis
IN
0.2
4.5
1.1
3.4
1
10.3
0.054473
22
-81.6557
30.33219
Jacksonville
FL
0.3
5
0.9
3.4
1.1
10.7
0.05829
23
-74.0776
40.7282
Jersey City
NJ
0.7
3.6
1.6
4.1
2.7
12.7
0.064337
24
-94.5786
39.09969
Kansas City
MO
0.3
4
0.8
3.3
0.7
9.2
0.048221
25
-118.244
34.0522
Los Angeles
CA
1.2
6.9
0.6
8
6.3
23.1
0.127333
26
-85.7585
38.25269
Louisville
KY
0.3
4.3
1.9
3.5
1.4
11.3
0.057693
27
-90.049
35.1495
Memphis
TN
0.4
4.8
1
3.6
2.3
12.1
0.066205
28
-80.1918
25.7617
Miami
FL
0.5
5.5
0.4
4.6
1.7
12.7
0.070492
29
-87.9065
43.0389
Milwaukee
Wl
0.2
3.3
0.5
2.2
1.2
7.4
0.04132
30
-93.265
44.9778
Minneapolis
MN
0.3
3.1
0.2
1.1
1.5
6.2
0.036636
31
-86.7816
36.1627
Nashville
TN
0.3
3.4
0.8
3.4
1.2
9.1
0.047996
32
-90.0715
29.9511
New Orleans
LA
0.6
4.8
1
4.8
1.6
12.8
0.06708
33
-74.006
40.71279
New York
NY
0.7
3.7
1.7
3.7
3.6
13.5
0.069451
34
-74.1724
40.7357
Newark
NJ
0.3
3.6
1.1
4.8
2.7
12.5
0.066282
35
-97.5164
35.4676
Oklahoma City
OK
0.3
5.7
0.8
2.8
0.8
10.4
0.05812
36
-95.998
41.25239
Omaha
NE
0.2
2.6
0.7
3.4
0.7
7.6
0.038958
37
-75.1652
39.9526
Philadelphia
PA
0.3
3.8
2
5.5
2
13.7
0.067549
38
-112.074
33.4484
Phoenix
AZ
0.9
4.3
0.2
7.2
2.3
15
0.078215
39
-79.9959
40.4406
Pittsburgh
PA
0.2
3.6
2.4
3.8
1.6
11.6
0.0564
40
-122.677
45.52309
Portland
OR
0.6
3
1
3.1
1.5
9.2
0.046587
41
-71.4128
41.82399
Providence
Rl
0.2
3.7
1
3.7
1.2
9.8
0.051609
42
-79.9414
37.271
Roanoke
VA
0.2
4.6
1.1
4
1
11
0.057853
43
-121.494
38.58159
Sacramento
CA
0.4
4.9
0.3
3.8
1.4
10.8
0.060547
44
-111.891
40.76079
Salt Lake City
UT
0.3
3
0.5
5.2
1.6
10.5
0.055615
45
-117.161
32.7157
San Diego
CA
0.7
7.6
0.8
5.6
2.8
17.4
0.097459
46
-122.419
37.77489
San Francisco
CA
0.7
3.5
0.5
4.7
2.7
12.1
0.064548
250
-------
47
-121.886
37.33819
San Jose
CA
0.5
4.6
0.4
3.7
2.8
12
0.067785
48
-122.332
47.6062
Seattle
WA
0.6
3.3
1.5
3.1
1.5
10
0.049439
49
-90.1994
38.62699
St. Louis
MO
0.3
3.3
1.8
3.8
1.5
10.7
0.052803
50
-82.4572
27.95059
Tampa
FL
0.5
5.8
2.4
4.5
1.1
14.2
0.071321
51
-110.927
32.2217
Tucson
AZ
0.4
4.6
0.3
3.8
1.3
10.3
0.057847
52
-95.9928
36.154
Tulsa
OK
0.4
5.3
1.2
3.6
0.9
11.4
0.060458
53
-75.978
36.85289
Virginia Beach-
Norfolk
VA
0.2
5.8
1.2
2.8
1.5
11.5
0.064087
54
-77.0369
38.90719
Washington
DC
0.5
3.9
1.6
3.3
2
11.3
0.057838
251
-------
Appendix C; Roads Speeds Table
This section contains the supplemental Max Speed reference table (Table 19) with the average speed limits for
the various road types in shapefiles from TIGER roads. Speed data is required to create the road network in
the Create Road Layer section and is implemented in the Transportation Module of EPA H20. The table must
be exported as a .csvto use in Esri ArcGIS or QGIS.
Usir
1. Copy Table 19 into a new Excel spreadsheet. Save the file to a known location and name the output
with a .csv extension (e.g. MaxSpeed_lookup.csv).
2. Open your existing ArcGIS map document file (.mxd), or create one following the steps outlined in Set
Up ArcGIS Map Document.
3. Use the Add Data T icon to navigate to and add the lookup .csv file (e.g. MaxSpeedJookup.csv) as a
layer in the Table of Contents.
The imported table can be used in the Create Road Layer section, to calculate the speed limits for the road
network.
Using QGIS
1. Copy Table 19 into a new Excel spreadsheet. Save the file to a known location and name the output
with a .csv extension (e.g. MaxSpeedJookup.csv).
2. Open your existing QGIS map document file (.qgs), or create one following the steps outlined in Set
Up QGIS Map Document.
3. In File Explorer, locate the Max Speed .csv table. Click and drag to load the table into the Layers
panel.
The imported table can now be used to calculate the speed limits for the road network in the Create Road
Layer section.
Table 19 Max Speed reference table, with speed limits in mph and kmh
MTFCC
Road_Desc
Speed
Speed_kmh
S1100
Primary Road
70
112.6538
S1200
Secondary Road
65
104.6071
S1400
Local Neighborhood Road/ Rural Road/ City Street
25
40.2335
S1500
Vehicular Trail (4WD)
0
0
S1630
Ramp
25
40.2335
S1640
Service Drive usually along a limited access highway
25
40.2335
S1710
Walkway/Pedestrian Trail
0
0
S1730
Alley
15
24.1401
S1740
Private Road for service vehicles (logging/ oil fields/ ranches/ etc.)
0
0
S1750
Drive for census use
0
0
S1780
Parking Lot Road
15
24.1401
S1820
Bike Path or Trail
0
0
S1830
Bridle Path
0
0
S2000
Road Median
0
0
S1720
Stairway
0
0
252
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Appendix D: Extracting and Updating the Original FLUCCS Lookup Table
The steps outlined throughout database creation were written using a land use layer based on NLCD and the supplemental lookup table (Appendix A:
Supplemental NLCD Lookup Table). The supplemental lookup table was intended for users creating a database extending outside of the Tampa Bay
area, where the FLUCCS land use data and original coefficients may not apply.
However, if the user is creating a new database completely within the state of Florida, and intends to use FLUCCS land use data, the original lookup table
may be used with a few modifications. This lookup table contains all available FLUCCS land use types for the Tampa Bay area. If the new FLUCCS data
include additional land use types it is suggested that the user add each to the lookup table and update the rates accordingly. The FLUCCS classification
codes are hierological (e.g. code 1110 is a subset of 1100) and joining the land use layer to the lookup table may require codes to be generalized.
Depending on the software, different steps are required to modify the original lookup table (Using ArcGIS or Using QGIS).
Usir
This section contains the original lookup table for Tampa, extracted from the TampaBay.sqlite database with some modifications (Table 20). The table
must be exported as a .csv and converted to a .dbf to make changes using Esri ArcGIS.
1. Copy both sections of Table 20 ("PKUID" through "FloodProt" fields) into a new Excel spreadsheet. Save the file to a known location and name the
output with a .csv extension (e.g. lookUPvars.csv).
2. Open your existing ArcGIS map document file (.mxd), or create one following the steps outlined in Set Up ArcGIS Map Document.
3. Use the Add Data " icon to navigate to and add the lookup .csv file (e.g. lookUPvars.csv) as a layer in the Table of Contents.
4. In the Table of Contents, right-click on the lookup table and choose Data > Export.
5. In the Export Data window:
a. In the Export dropdown list, select All records.
b. Next to the Output table text box, click the Browse button and navigate to the preferred file path. In the Save as type dropdown
list, select dBASE Table, and in the Name text box, enter lookUPvars.dbf. Click Save.
c. Click OK.
The exported lookup table should be edited to update the coefficients for the user's specific area of interest following the steps outlined in the Update ES
Coefficients section. The "canopyVal", "usablewat", "StableClim", "Us_Air_Dol", "CN" and "FloodProt" fields will be populated in the Joining Lookup Table
section. Once the table has been updated for the specific area of interest, it is imported into the Qspatialite plugin as described in the Importing Layers
into QGIS section.
Using QGIS
1. Copy both sections of Table 20 ("PKUID" through "FloodProt" fields) into a new Excel spreadsheet. Save the file to a known location and name the
output with a .csv extension (e.g. lookUPvars_supplemental.csv).
253
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2. Open your existing QGIS map document file (.qgs), or create one following the steps outlined in Set Up QGIS Map Document.
3. From the main menu, select Layer > Add Delimited Text Layer.
4. In the Create a Layer from a Delimited Text File window:
a. Click the Browse button to locate the lookup .csv table.
b. Under the Selected Delimiter option, select Comma.
c. In the X field and Y field dropdown list, leave the default fields.
d. Click OK.
5. QGIS may try to map the attributes, this can be disregarded. In the Layers panel, right-click on the lookup table and choose Save as.
6. In the Save vector layer as window:
a. In the Format dropdown list, select ESRI Shapefile.
b. In the Save as text box, browse to the desired location and name the output lookUPvars.shp.
c. In the CRS dropdown list, choose Selected CRS, and click the Browse button to locate l/l/GS 84/Pseudo Mercator.
d. Click OK.
7. In File Explorer, locate the .dbf file that coincides with the lookup shapefile (lookUPvars.dbf) and click and drag the file into the Layers panel.
Although the exported lookup table is saved as a "shapefile", the output is an editable table (lookUPvars.dbf), which is updated throughout database
creation to change the coefficients for the user's specific area of interest. The "canopyVal", "usablewat", "StableClim", "Us_Air_Dol", "CN" and "FloodProt"
fields will be populated in the Joining Lookup Table section. Once the table has been updated for the specific area of interest, it is imported into the
Qspatialite plugin as described in the Importing Layers into QGIS section.
Table 20 Original lookup table for Tampa Bay with FLUCCS land use. The vital rates for H20 are denitrification rate (denitrific), carbon fixation rate (CarbonFixe), percent
canopy cover(Canopy), and soil type categories (A, B, C).
PKUID
FLUCCS
FLUCSDESC
denitrific
CarbonFixe
Canopy
A
B
C
1
1100
RESIDENTIAL LOW DENSITY < 2 DWELLING UNITS
1.3
148
22
54
70
80
2
1200
RESIDENTIAL MED DENSITY 2->5 DWELLING UNIT
1.13
138.5
23
61
75
83
3
1300
RESIDENTIAL HIGH DENSITY
0.85
91
12
77
85
90
4
1400
COMMERCIAL AND SERVICES
0.62
56.5
5
89
92
94
5
1500
INDUSTRIAL
0.6
50.5
3
81
88
91
6
1600
EXTRACTIVE
1.18
116.5
13
77
86
91
7
1650
RECLAIMED MINE LAND
1.18
116.5
13
39
61
74
8
1700
INSTITUTIONAL
0.87
73.11111
4
81
88
91
9
1800
RECREATIONAL
1.4
127.5
11
49
69
79
10
1820
GOLF COURSES
1.4
132.5
13
49
69
79
254
-------
1900
2100
2140
2200
2300
2400
2500
2540
2600
3100
3200
3300
4100
4110
4120
4200
4340
4400
5100
5200
5300
5400
5700
5720
6100
6110
6120
6150
6200
1.4
132.5
13
0.72
423.1256
3.15
959.0622
0.45
570.5556
16
0.06
423.1256
0.45
570.5556
10
19
0.82
673.3333
0.06
742.5
16
0.06
945
28
0.82
540
31
0.12
697.5
56
0.12
697.5
49
0.12
312.9
46
0.19
590
55
0.19
660
65
0.45
730.8333
56
20.73
180
22
12.16
396.5722
6.73
367.7989
5.66
195
115.3367
6.89
115.3367
25.5
808
76
25.5
808
79
0.69
777.9744
76
25.5
808
81
25.5
298.2
72
OPEN LAND
CROPLAND AND PASTURELAND
ROW CROPS
TREE CROPS
FEEDING OPERATIONS
NURSERIES AND VINEYARDS
SPECIALTY FARMS
TROPICAL FISH FARM
OTHER OPEN LANDS
HERBACEOUS
SHRUB AND BRUSHLAND
MIXED RANGELAND
UPLAND CONIFEROUS FOREST
PINE FLATWOODS
LONGLEAF PINE -XERIC OAK
UPLAND HARDWOOD FORESTS - PART 1
HARDWOOD CONIFER MIXED
TREE PLANTATIONS
STREAMS AND WATERWAYS
LAKES
RESERVOIRS
BAYS AND ESTUARIES
OCEAN AND GULF OF MEXICO
GULF OF MEXICO
WETLAND HARDWOOD FORESTS
BAY SWAMPS
MANGROVE SWAMPS
STREAM AND LAKE SWAMPS (BOTTOMLAND)
WETLAND CONIFEROUS FORESTS
-------
40
6210
CYPRESS
24.66
241.25
66
49
65
72
41
6300
WETLAND FORESTED MIXED
25.5
552.4
73
49
65
72
42
6400
VEGETATED NON-FORESTED WETLANDS
28.26
141.7
21
49
65
72
43
6410
FRESHWATER MARSHES
28.26
618
30
49
65
72
44
6420
SALTWATER MARSHES
4.52
492.2544
30
49
65
72
45
6430
WET PRAIRIES
25.48
141.7
20
49
65
72
46
6440
EMERGENT AQUATIC VEGETATION
26.22
141.7
29
49
65
72
47
6510
TIDAL FLATS
10
195
0
98
98
98
48
6520
SHORELINES
0
0
0
98
98
98
49
6530
INTERMITTENT PONDS
17.44
141.7
10
98
98
98
50
6600
SALT FLATS
0
0
10
98
98
98
51
7100
BEACHES NO SWIM
0
0
0
98
98
98
52
7200
SAND OTHER THAN BEACHES
0
0
0
98
98
98
53
7400
DISTURBED LAND
0
25
10
98
98
98
54
8100
TRANSPORTATION
1.2
96
4
98
98
98
55
8200
COMMUNICATIONS
1.16
105.5
9
98
98
98
56
8300
UTILITIES
1.4
132.5
9
98
98
98
57
9113
SEAGRASS PATCHY
5
813.6667
0
100
100
100
58
9116
SEAGRASS CONTINUOUS
5
813.6667
0
100
100
100
59
9121
ALGAE BEDS
5
0
0
100
100
100
D
LEVI
waterRet
stabClim
us Wat
canopyVal
usablewat
StableClim
Us_Air_Dol
CN
FloodProt
85
1
2
37
3
87
1
2
37
3
92
1
2
37
3
95
1
2
37
3
93
1
2
37
3
94
1
2
37
3
80
1
2
37
3
256
-------
93
1
2
37
3
84
1
2
37
3
84
1
2
37
3
80
1
2
37
3
80
2
2
37
3
89
2
2
37
3
82
2
2
37
3
89
2
2
37
3
91
2
2
37
3
89
2
2
37
3
93
2
2
37
3
78
2
2
37
3
78
3
2
37
3
77
3
2
37
3
83
3
2
37
3
79
4
2
37
3
79
4
2
37
3
79
4
2
37
3
79
4
2
37
3
79
4
2
37
3
82
4
2
37
3
100
5
2
37
3
100
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2
37
3
258
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Appendix E: Additional Troubleshooting and Common Errors
New Project "No Such Table" Error
When starting a new project, an error window may appear while the selected AOI is processing (Figure
295). This error states "The SQL query seems to be invalid. No such table:" and lists the table name
that cannot be found (e.g. FUTUREsixty). The error message may appear behind the progress bar.
^ error X
The SQL query seems to be invalid.
_ Ia
no such table: FUTUREsixty
OK
Figure 295 SQL no such table error message
This message occurs when a table has been deleted or doesn't have the expected name in the
Qspatialite plugin. EPA H20 searches for each table name from the original Tampa Bay database; if a
name does not appear, or it has been renamed incorrectly, the user will receive an error.
If the named table was deleted intentionally, the user only needs to click the OK button. The rest of
the data layers will continue to process for the AOI. Please note, this error will appear every time a
new project is created, and the rest of the data will not load until the OK button is clicked.
If the named table was deleted unintentionally, or the table was renamed incorretly, the user must
make changes in the Qspatialite plugin. In a blank map project, the user must rename the table to
match the Tampa Bay naming scheme or add a new table into Qspatialite with the correct name.
An exception may occur if the "no such table" name in the error message is Land_Use (Figure 296).
This may occur if the land use layer was originally named Land_Use_2006.
£i error X
The SQL query seems to be invalid,
no such table: Land_Use
OK
Figure 296 EPA H20 Land_Use error window
The user database requires the name Land_Use_2006 the first time the land use layer is inserted into
Qspatialite. However, if the user updates the land use layer later, and reuploads it into the Qspatliate
plugin, the database may require the name Land_Use. Change the name of the land use layer to
match that in the error message, reupload the table into Qspatialite, and the error should not appear
again.
259
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Cannot Run Advanced Comparison Report
EPA H20 requires that all layer names in the Qspatialite plugin maintain the naming scheme found in
the Tampa Bay database. The program also requires that the layer names stay the same in the
Layers panel. If the user right clicks on a layer in the Layers panel and renames it, two different errors
may occur when running a comparison report.
The first error occurs if Land_Use_2006 is renamed. A No Project error message appears that states
"Please Create a Project, then run Scenario Manager" (Figure 297). The user must right-click on the
appropriate layer in the Layers panel and rename the layer Land_Use_2006 to run a comparison
report.
^ No Project X
Please Create a Project, then run Scenario Manager.
OK
Figure 297 No Project error message when comparing scenarios
A second error may appear if the land use scenario layers (e.g. Land_Use_2020, Land_Use_2040,
and Land_Use_2060) are renamed and the renamed layer is used in a comparison report. A Python
error window appears that indicates one of the scenario layers (e.g. scenarioLayerB) is out of range
(Figure 298).
^ Python error ? X
An error has occured while executing Python code:
Traceback (most recent call last):
File ,rC:/PROGRA~2/EPA
H20/apps/qgis/./python/plugins\project_manager\project_manager.py", line
2663, in preWriterUC2
self.testWriter2()
File ,rC:/PROGRA~2/EPA
H20/apps/qgis/./python/plugins\project_manager\project_manager.py"r line
2901, in testWriter2
scenarioLayerB = data[l][0][0]
IndexError: list index out of range
J
Python version:
T
Close
Figure 298 Python error window while running a comparison report
The user must rename the layer to match one of the original Future Scenario layer names, even if the
layers represent NLCD data from a different time.
260
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Cannot Update Polygons in Edit Scenario Tool
After a user database is created, the user can update land use polygons with the Edit Scenarios tool.
A Python error may occur after the Update button is selected in the tool (Figure 299). The error window
indicates that the CN Value is out of range.
^ Python error ? X
An error has occured while executing Python code:
Jk.
Traceback (most recent call last):
File ,rC:/PROGRA~2/EPA
H20/apps/qgis/./python/plugins\project manager\project manager.py", line
4385, in updateSelectedAttributes
CNValue = int(theData[l][0][0])
IndexError: list index out of range
F*ython version:
2.7.13 (v2.7.13:a06454blafal, Dec 17 2016, 20:42:59) [MSC v.1500 32 bit
(Intel)]
A
T
Close
Figure 299 Python error window while updating land use polygons
This error occurs when the "FLUCSDESC" field in the land use layer does not match the attributes in
the lookup table "FLUCSDESC" field. Both "FLUCSDESC" fields must contain the updated land use
descriptions (e.g. "NLCDDesc"); this is explained in the Field Calculations sections.
To fix the error, the user must use Field Calculator to update the "FLUCSDESC" fields with the
"NLCDDesc" attributes. The updated layer (land use or lookup table) must then be reuploaded into the
Qspatialite plugin. Create a new project using the user database, and the Edit Scenario tool will be
fully functional.
Report Legend Crossed Out in Advanced Report
When running an Ecosystem Valuation Report (as shown in the Compare Scenarios section), the
output Legend may appear partially crossed out (Figure 300).
261
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Figure 300 Advanced Report legend, with cross hatch error
This occurs when the layers were not "turned on" in the Layers panel before the comparison was run.
Both layers must be toggled on prior to running a scenario comparison report; the report, does not
require the layers to stay turned on for the report, they simply must be turned on and off once.
The user must close the current project and create a new project for the AOI. Turn each land use
layer on once before the first comparison report is run.
Flood Protection = 0 in Advanced Report
When running an Advanced report in a user-created database, the Flood Protection value for
Land_Use_2006 may equal zero (Figure 301).
STATISTICS FOR LAYERS IN DRAWN AREA
DRAWN AREA OF INTEREST: 3,963 Hectares
Usable Water: Human activities produce water pollutants. As water moves through a watershed it is filtered by wetlands, forests, and aquatic areas.
Replacement costs for removing a pouid of nitrogen from various sources range from less than S10 to as high as S855.Costs increase as the nitrogen becomes
harder to route towards treatment areas and as simpler; more cost efficient mechanisms for removing nitrogen need to be replaced by more centralized
advanced waste water treatment farilities.
Land Use 2006 Scenario-test
Estimated total value {$) per year: 1,738,087 Estimated total value ($) per year: 1,749,379
Usable Air: Human activities produce air pollutants. Trees and other plants remove these harmful pollutants. Pollution removal results in healthier people with
reduced health care costs. The loss of trees and other plants would result in increased health care costs and decreased human well-being.
Land Use 2006 Scenario-test
Estimated total value ($) per year: 95,252,132 Estimated total value ($) per year: 91,502,472
StaWe Climate:Stored carbon provides a more stable climate by keeping greenhouse gasses out of our atmosphere. Carbon dioxide (C02) is the primary
greenhouse gas emitted through human activities. Carbon sequestration helps reduce future social costs associated with a more unstable climate.
Land^Use 2006 Scenario-test
Estimated total value (S) per year: 2,380,473 Estimated total value (S) per year: 2,306,371
Flood Protection: Human activities alter the 'way water moves through the landscape. Natural landscapes retain and slow the movement of water offering
protection from flooding. The loss of these natural landscapes would result in the need for more man made flood protection at much higher cost Flood
protection value below is summarized for the Area of Interest (AOI) that user has selected.
Land Use 2M>6 Scenario-test
I^E^mated^totej^alue^Oj Estimated total value: 206,111
Figure 301 Statistics page of the Advanced Ecosystem Valuation Report
262
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This issue may be rooted in an incorrect field calculation in the Joining Lookup Table section.
1. Open the Land_Use_2006 attribute table and sort the "Max_Type_N" field in ascending order.
2. If the "Max_Type_N" field contains values of 0, this may be the source of the issue above.
a. Recalculate the missing "Max_Type_N" values, as shown in the Spatially Join Soils to
Land Use (ArcGIS) or Spatially Join Soils to Land Use (QGIS) section.
b. Recalulate the "CN" field, then recalculate the "FloodProt" field, as shown in the Joining
Lookup Table section.
3. Drop and re-add the updated Land_Use_2006 table into Qspatialite.
4. When a comparison report is run in the user database, the Flood Protection value should no
longer be zero.
Total Area: 0 sq meters in Advanced Report
When running an Advanced report, the Total Area may report as 0 sq meters, with no land use types
listed.
STATISTICS FOR LAYERS IN DRAWN AREA
DRAWN AREA OF INTEREST: 1,317 Hectares
Usable Water: Human activities produce water pollutants. As water moves through a watershed it is filtered by wetlands, forests, and aquatic areas
Replacement costs for removing a pouxJ of nitrogen from various sources range from less than 510 to as high as 5855.Costs increase as the nitrogen becomes
harder to route towards treatment areas and as simp ten more cost efficient mechanisms for removing nitrogen need to be replaced by more centralized
advanced waste water treatment facilities.
Land^Use 2006 Scenario-test
Estimated total value (5) per year: 2,966,159 Esti mated total value (S) per year: 2,969,952
Usable Air: Human activities produce air pollutants. Trees and other plants remove these harmful pollutants. Pollution removal results in healthier people with
reduced health care costs. The Idss of trees and other plants would result in increased health care costs and decreased human well-being.
Land Use 2006 Scenario-test
Estimated total value (S) per year: 446,323 Estimated total value ($) per yea*: 437,533
Stable Climate:Stored carbon provides a more stable climate by keeping greenhouse gasses out of our atmosphere. Carbon dioxide (C02) is the primary
greenhouse gas emitted through human activities. Carbon sequestration helps reduce future social costs associated with a more unstable climate.
Land Use 2006 Scenario-test
Estimated total value ($) per year: 957,453 Estimated total value (S) per year: 941,813
Flood Protection : Human activities alter the way water moves through the landscape. Natural landscapes retain and slow the movement of water offering
protection from flooding. The loss of these natural landscapes would result in the need for more man made flood protection at much higher cost Flood
protection value below is summarized for the Area of Interest (AQI) that user has selected.
Land Use 2006 Scenario-test
Estimated total value: 7,460,643 Estimated total value: 7,370,798
Land Use: Land maps are made from Florida Land Use and Cover Classification System (FLUCCS) data. These are photo interpretations of aerial photographs.
Future scenarios are the result of models or subjective table top exercises.
Land Use 2006 Scenario-test
Total Area: 0 sq meters Total Area; 0 sq meters
Figure 302 Statistics page of the Advanced Ecosystem Evaluation Report
This is simply a processing error. Close the report and remove the Upstream Area of Interest and
Area of Interest layers from the Layers panel (right-click > Remove). Run another report using the
Compare Scenarios tool, with a new Report Name; the correct areas will be reported.
Cannot Open Qspatialite Plugin
An error may appear when trying to open the Qspatialite plugin in EPA H20 (Database menu >
SpatiaLite > QspatiaLite). The error message states "The SQL query seems to be invalid. No such
table: geometry_columns".
263
-------
tj) error X
The SQL query seems to be invalid.
!
no such table: geometry_colurnns
OK
Figure 303 SQL error window when opening Qspatialite
This message may appear if a database was renamed or moved within the user's .qgis folder. All
databases that were once opened in EPA H20 and/or Qspatialite are linked to the plugin. If a
database is moved or renamed, the plugin searches for a database that is no longer there.
The user must delete the connection between Qspatialite and the database.
1. Close the error messages that appear.
2. Open the Qspatialite plugin and select the old database from the dropdown box.
ra
3. Click the Delete Link to Database icon.
The user should now be able to reopen the Qspatialite window with no errors.
If the user completely deleted a database folder from their C:/ drive, a different error will appear. This
error message states "Can't connect to DataBase. Error unable to open database file". The error
window also lists the file path of the missing database (Figure 304).
£
x
Can't connect to DataBase:
! C:/Users/mjackson/.qgis/0,0,3/UserDatabase/0,0,3/data/databases/UserDatabase2,sqlite
Error unableto open database file
i
OK
Figure 304 Missing database error window in EPA H20
Qspatialite cannot be opened until a database is returned to the exact file path listed in the error.
1. Create a copy of the original Tampa Bay database, as shown in the Setting Up a Project
Directory section.
2. The file path for the copied database must exactly match the file path listed in the error
message received.
3. Rename the copied Tampa Bay database to match the deleted database name (e.g.
UserDatabase2. sqlite).
4. The Qspatialite plugin should now open in EPA H20. Select the database from the dropdown
box.
i 1 i r
5. Click the Delete Link to Database icon.
6. The user may then delete the copied database folder from their C:/ drive.
Python Error When Opening or Creating Project
A Python error may appear after selecting an AOI for a new project, or when opening a previously
saved project (Figure 305). The error window states "UnboundLocalError: local variable 'olRes'
264
-------
referenced before assignment". After clicking the Close button, a second message may appear,
explaining that the Google Streets layer cannot be drawn (Figure 306).
^ Python error ? X
An error has occured while executing Python code:
Traceback (most recent call last):
File "C:/PROGRA~2/EPA
H20/apps/qgis/./python/plugins\openlayers\openlayers_layer.py", line 109, in
draw
se If. re n d e r( re n d e re rCo ntext)
File "C:/PROGRA~2/EPA
H20/apps/qgis/./python/plugins\openlayers\openlayers_layer.py", line 164, in
render
olWidth = rendererContext.extent().width() / olRes
UnboundLocalError: local variable 'olRes1 referenced before assignment
Python version:
Close
Figure 305 Python error while creating a new project, or opening a previous project
& qgi*
X
Could not draw Google Streets because:
Close
Figure 306 qgis message window, stating Google Streets cannot be drawn
These error messages appear together when there is an issue with the user's internet connection. A
connection to the internet is required to display the Google Streets layer. The user must close the
program, troubleshoot the internet connection, and reopen EPA H20 to draw Google Streets.
If the internet is connected and Google Streets continues to fail, right-click on the layer in the Layers
panel and choose Remove. From the main menu select Plugins > OpenLayers plugin > Add Road
layer. Google Streets may be experiencing a licensing issue, and the Bing road layer may be used
instead.
Please note, the program is completely functional without the streets layer but may be desired when
exporting reports.
265
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¦¦ ins
This section addresses common questions users may have about the program, its use, and its
development.
How do I get the EPA H20?
EPA H20 is a free software distributed by US EPA's Gulf Ecology Division, and can be
downloaded at the following link: https://www.epa.gov/water-research/ecosvsteni-services-
scenario-assessment-using-epa-h2o
If you are unable to download EPA H20, please contact US EPA's Gulf Ecology Division.
Do I need to pay for EPA H20?
No. It is distributed free of charge by US EPA's Gulf Ecosystem Measurement and Modeling
Division. For questions regarding commercial application, the license agreement can be
found in the Setup Wizard of the EPA H20 Download and Installation section.
Are there any constraints on use of EPA H20?
Yes. EPA H20 relies on the QGIS application, and inherits all QGIS use constraints
(licensed under the GNU General Public License).
Where did the EPA H20 data come from? How up to date is the data?
The Tampa Bay database used in EPA H20 is comprised of data collected by various
governmental agencies including Florida Natural Areas Inventory (FNAD. Florida Geographic
Data Library (FGDD. and EPA. Please refer to source agency websites for more information
on specific datasets (Table 6). Data were further processed for optimum use in EPA H20. All
data were downloaded from agency websites in July 2013. However, the last updated date
of each data are different.
I am an advanced QGIS user, can I use QGIS functionality in EPA H20?
Yes. Users can run EPA H20 with full QGIS functionality in power mode by changing the
EPA H20 settings in the computer registry as shown under the Power Mode section of the
help manual.
Can I use EPA H20 on any operating system?
No. EPA H20 is currently only compatible with Windows operating systems. Please check
the System Requirements for further details.
Can I modify the report style and format in EPA H20?
No. The current version of EPA H20 does not allow users to modify the report style and
format.
What does the "EPA H20 version 1" popup box mean?
This box appears when a user action is not supported in the current EPA H20 mode. The
functionality may be supported when the EPA H20 power mode is enabled, as described in
the Power Mode section of the help manual.
Can I simultaneously and seamlessly work on Basic and Advanced Modules of the
EPA H20? No. Users can operate EPA H20 only in one mode at a given time. Please save
your work as an EPA H20 project, and then switch modules using the "EPA H20 Module"
tool, as shown in the Navigating EPA H20 section.
Can I save the EPA H20 project and share it with others?
Yes. Please refer to the Saving and Moving the Project section of the manual.
266
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Appendix F; Updating QGIS Layer Symbologies
When starting a new project in the user's database, the symbology in the Layers panel will match
that of the original Tampa Bay database. This legend incorporates the user's land use
classifications but appears to display FLUCCS categories. Table 21 shows how the Layers panel
legend categorizes the NLCD descriptions.
Table 21 NLCD descriptions condensed into EPA H20 legend descriptions
Legend
NLCD Description
Urban and Built-Up
Developed, Open Space
Developed, Low Intensity
Developed, Medium Intensity
Developed, High Intensity
Agriculture
Pasture/Hay
Cultivated Crops
Rangeland
Shrub/Scrub
Grassland/Herbaceous
Woodlands
Deciduous Forest
Evergreen Forest
Mixed Forest
Water
Open Water
Wetlands
Woody Wetlands
Emergent Herbaceous Wetlands
Barren Land
Barren Land (Rocks/Sand/Clay)
Utilities and Transportation
N/A
Seagrass and Algae Beds
N/A
Tidal Flats
N/A
The original Tampa Bay database utilized FLUCCS land use data, which incorporated Utilities and
Transportation, Tidal Flats, and Seagrass and Algae Beds as land use types. Although these land
use types are not found in NLCD data, they are still listed in the Layers panel.
Only data that is present in the selected AOI will appear in the Advanced Module Scenario
Comparison Report; therefore, Utilities and Transportation, Tidal Flats, and Seagrass and Algae
Beds, as well as any other land use type not located in the AOI, will not appear in the report
description.
Land use types and their symbology are condensed for a cleaner, more simplified map. However,
the user may update the symbology to display the NLCD descriptions, rather than the condensed
legend descriptions.
Note: if the symbology is changed in the land use layer and a comparison report is run, the AOI
and Upstream AOI boundaries will draw behind the land use layer in the report. The AOI
boundaries will therefore not display directly on the map in the report output.
1. In the Layers panel, double click on the Land_Use_2006 layer.
2. From the Layer Properties window, click on the Style tab, and in the first dropdown box,
choose Categorized (Figure 307).
267
-------
igj Layer P ro p erti es - La n d_U se_2006
v Style
Labels
Fields \ General
% Categorized
Sinqle Symbol
Graduated
Rule-based
Point displacement
| Symbol
change
Value
Label
Figure 307 Land_Use_2006 Layer Properties, with Categorized selected in the Style tab
3. In the Column dropdown box, choose the "FLUCSDESC" field (Figure 308).
4. Click Classify. The land use descriptions from the user's land use layer will appear in an
alphabetical list, as shown in Figure 308.
3) Layer Properties - Land_Use_2006
v- Style Labels Fields
Ifc Categorized "
Column FLUCSDESC
\ General I ® Metadata ,> ? Actions Joins ' Diagrams
Old symbology
Symbol
J change
Color ramp
| Symbol
| Value
| Label
U
Barren Land (Rocks\Sand\Clay)
Barren Land (Rocks\Sand\Clay)
; :
Cultivated Crops
Cultivated Crops
~
Deciduous Forest
Deciduous Forest
~
Developed, High Intensity
Developed, High Intensity
~
Developed, Low Intensity
Developed, Low Intensity
~
Developed, Medium Intensity
Developed, Medium Intensity
[ ]
Developed, Open Space
Developed, Open Space
Li
Emergent Herbaceous Wetlands Emergent Herbaceous Wetlands
Evergreen Forest
Evergreen Forest
~
Grassland/Herbaceous
Grassland/Herbaceous
Mixed Forest
Mixed Forest
Open Water
Open Water
Pasture/Hay
Pasture/Hay
Shrub/Scrub
Shrub/Scrub
¦
Woody Wetlands
Woody Wetlands
Classify
Restore Default Style
Save As Default
Load Style ...
OK
Save Style ...
Apply Help
Figure 308 Land_Use_2006 Layer Properties window, with NLCD descriptions listed in the Style tab
5. Under the Symbol column, right-click on the first square, and choose Change color.
6. Select a new color to appropriately represent the first land use type and click OK.
7. Change the color of the symbol for each land use type, then click OK.
8. Repeat the same changes in symbology for any other land use comparison datasets the
user input into the EPA H20 Qspatialite plugin.
9. The correct land use descriptions will appear in the Layers panel, and in any reports ran
during the current project. These steps must be repeated with every new project created.
268
-------
Appendix G: EPA H20 Development From QGIS
This section provides additional information for developers to understand the EPA H20
architecture and coding structure.
>pmer»t
The EPA H20 program is created by customizing the base QGIS program. There are different
Integrated Development Environments (IDEs) to customize QGIS that are dependent on the
development operation system platform used. For the EPA H20 tool, the platform used for
development was a Windows 32bit operating system and the IDE used to customize QGIS was
Microsoft Visual Studio 2008. The customization consists of creating a Plugin for QGIS
developed using the Python language. The QGIS plugin is made with Python scripts combined
into a package. These scripts follow an object-oriented methodology.
User interface creation:
The QGIS user interface is based on Qt and PyQt technology. It consists of Qt widgets and
graphic tools that are generated by "QtDesigner" and compiled using Python code.
Qt and PyQt libraries are embedded in "0SGE04W" and accessible by QGIS.
Spatialite database:
QGIS accesses the Project database using the "Spatialite" library. This library provides functions
to access and read the main database, create user scenarios, and edit existing attributes.
QGIS Python package:
The QGIS python package has the necessary GIS functionalities required by EPA H20 and the
ability to programmatically access the existing QGIS features.
Through the QGIS python package, the QGIS window can be customized by adding menus,
toolbars, and QDockWidget.
Cmake and Microsoft Visual C++:
Customizations made to the QGIS program and plugins need to be compiled in order to create
the executable file. Running a compilation can be done using Cmake. It will create the Project
Solution, which can be compiled and released as the package.
Error catchi < id debuggii
QGIS has a Python and PyQt debugger console that facilitates error catching.
npilation
The compilation process of QGIS is listed below:
Set 0SGE04W and MVS environment variables.
To setup the necessary environment dependencies for the code compilation:
1. All the software below must be installed first.
269
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a. Cmake
b. Flex
c. Bison
d. MS Server 2003 R2 SDK
2. Edit OSGeoMSC.bat in the QGIS source folder and set the right paths.
a. Execute OSGeoMSC.bat in a Command console. It is preferable to execute
OSGeoMSC.bat with administrative privileges.
Generate QGIS Microsoft Visual Studio solution
This step links all required QGIS libraries using Cmake. CMake Files define all the necessary
rules for solution generation; however, paths linking the source to the libraries may be null or
wrong. Please correct these paths if required.
3. Generate a build folder using the command « MKdir build» the «Cd build».
4. Execute «Cmake-gui» and set the source and the build folders path similar to what is
shown in Figure 309.
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Figure 310 Documents library window after the source and build folders path have been set
Compile the source
Microsoft Visual Studio Solution Builder is used in this step.
1. Run the command «MSbuild QGIS1 .S.O.sIn /p:Configuration=Release»
2. Please make sure the build is successfully done. Any kind of error might affect the
compilation later.
3. Run the command «MSbuild INSTALL.vcproj /p:Configurafion=Release»
Generate the installer package
Installer package creation requires the installation of Cygwin (https://www.cvawin.com/).
To run the install:
1. Run a Cygwin console as an Administrator.
2. Locate to the path Trunk\QGIS-1,8.0\ms-windows\
3. Run the command « ,/quickpackage.sh»
4. The quickpackage.sh script could be edited to set installer name and version.
5. The installer file will be generated in a MS Windows folder.
Project Manager Plugin for EPAH20
The Project Manager Plugin is a custom plugin that controls all the functions of the EPA H20
program. The sample in Figure 311 shows the directory structure of a typical plugin (Source:
https://docs.aais.ora/testina/en/docs/pvaais developer cookbook/intro.html#pvthon-pluains').
PYTHON_PLIJGINS_PATH/
MyPlugin/
.init =py --> *required* mainPlugin. py
—> ^required* metadata.txt --> *required*
resources . qrc —> *l.ikely useful*
resources.py --> ^compiled version, likely useful* form.ui
—> *likely useful*
form.py --> *compi.led version, likely useful*
Figure 311 Python plugins path
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Plugin files include:
1. init py = The starting point of the plugin. It needs the classFactoryO method and may
have any other initialization code.
2. mainPlugin.py = The main working code of the plugin. It contains all the information about
the actions of the plugin and the main code.
3. resources.qrc = The .xml document created by Qt Designer. It contains relative paths to
resources of the forms.
4. resources.py = The translation of the .qrc file described above to Python.
5. form.ui = The GUI created by Qt Designer.
6. form.py = The translation of the form.ui described above to Python.
7. metadata.txt = Required for QGIS >= 1.8.0.
The Project Manager Plugin's components relate to other familiar components of EPA H20
(conceptual diagram shown in Figure 312).
Main Database
User Area Of
Interest
EGS Coefficients
Value
Project type (by Use
Case)
User Database
Upstream AOI
Layer Summary
Menu Manager
Figure 312 Conceptual diagram of the Project Manager Plugin's components
Project Creation and User Database
EPA H20 is based on the "Use Case". Each use case has a different user interface and
functionality. The project creation has three major components:
1. Select the Main Database's and the user database's names. The main database path will
be saved in the system registry in order to reload it for future use.
2. Select the AOI and clip the main database.
3. Load all layer in the Table of Contents.
Main Database and user database management
QGIS accesses the project database using the "Spatialite" library. This library provides functions
to access and read the main database, creates the user database, and edits existing attributes.
AOI selection and clip using Spatialite
The function "runListlntersect" in project_manager.py presents the table creation from the
intersection between AOI and Main Database. The intersection query is in SQL as shown in the
sample query below.
Note: countyRect represents the extent of the county selected by the user. This example
represents the intersection query for a county AOI selection.
"consSQL = ('create table '+theLayer+' as select * from '+theLayer+' where
MBRIntersects('+theLayer+'.geometry, GeomFromText(VPOLYGON(('+str(countyRect.xMinimum())+'
'+str(countyRect.yMinimum())+'.'+str(countyRect.xMinirnum())+'
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'+str(countyRect.yMaximumO)+7+str(cQuntyRect.xMaximum())+,
'+str(countyRect.yMaximumO)+7+str(countyRect.xMaximum())+'
'+str(countyRect.yMiriimum())+','+str(countyRect.xMinimumO)+' '+str(countyRect.yMiriimumO)+'))V))')"
Load Layers in the Table of Contents
The function "runSelectConservationLands" in project_manager.py loads a layer from the user
spatialite database depending on parameters such as table name, symbology and user database
path.
Clip and Summary Operations
Each use case has the appropriate clip and summarize operations for the calculation needed.
Use Case I:
A Vector Clip operation is performed in Use Case I in order to summarize the layer's statistics.
The calculation requires going through different attributes in the data. Based on the specific
operation to execute, the project manager will loop over features and read data attributes. The
summary of a layer requires running specific operations to a particular attribute for the input AOI.
Figure 313 displays the conceptual diagram of the sequential steps to clip and summary
operations.
Figure 313 Conceptual diagram detailing the steps to clip and summary operations in Use Case I
A separate table named AnalysisLayer is used to determine the attributes used and the summary
operation to be executed for the given layer. The list below shows the types of operations
performed on layers:
1. Total area calculation
2. Total length calculation
3. Features count within the area
4. Dollar or dollar/area value summation
5. Total area categorized by feature description
The user can choose the AOI three different ways:
1. By County selection (Counties are listed in "Counties" layer).
2. By a Polygon shapefile (Shapefile should be loaded from the file system).
3. By drawing on the map (Drawing tools will appear in order to select the AOI)
"utils.Cliplt.clip" is the function responsible for the vector clip.
"runStats" function in Project Manager is responsible to run the summary statistic calculation for
each layer.
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Use Case II:
For Use Case II, a raster clip and summary operation are used. The summary operation
calculates the mean of pixel values. Figure 314 demonstrates the conceptual diagram of
sequential steps to the clip and summary operations.
User
AOI(considered
as a mask)
Vector Layer
Attribute
RasterClip
Pixel value
Figure 314 Conceptual diagram detailing the steps to clip and summary operations in Use Case II
A separate table named UC2AnalysisLayer is used to determine the attributes used and the
summary operation to be executed for the given layer. The list below shows the types of
operations performed on layers.
AOI selection choices for this use case are the same as Use Case I, with the addition of
"Selection by river basins." River basins are listed in "River basins" layer.
"vectorToRasterGridClip" function lists layers to summarize from the UC2AnalysisLayer table.
"clipLandUseGrid" function runs the raster clip for a vector layer.
ES Coefficient Values and Edit User Scenarios
Editing ES coefficients affects the ES value calculations. A field's recalculation must be executed
after every ES coefficient edit is complete. These coefficients are stored in the scenario layer
table and are considered as default values for future edits. "EGSUpdateAttThread.py" is the
source of the class responsible for ES coefficient edits and related recalculation executions.
The user can also edit the land use feature descriptions. EPA H20 will recalculate the ES values
based on the new descriptions and attribute values found in the "LookUPvars" table. The
recalculation is executed for all edited features. The "updateSelectedAttributes" function in
"project_manager.py" performs all the ES values recalculations upon land use feature editing.
Reporting
Project Manager generates two different types of reports - one for each Use Case I and Use
Case II. After calculating the summary statistics based on the use case, EPA H20 Project
Manager generates the report. It combines the map, the legend, and the summarizing
description of each ES variable within area of interest and its upstream area.
Below are the critical functions required for the report generation:
"writeMap" function in 'project_manager.py' exports the map and legend to a PNG image.
"writeReport" function in 'project_manager.py' generates the PDF report for Use Case I.
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"writeReport2" function in 'project_manager.py' generates the PDF report for Use Case II.
Transportation Tool
The Transportation Tool is an additional functionality in Use Case II. It provides the user with
ability to:
1. Customize the roads network
2. Check the change effects
3. Add new points of interest
Figure 315 shows the conceptual diagram for the Transportation Tool workflow.
Starting point
Buffer
Points of
Interest layer
¦
Network
| Buffered Points
Summary
¦
¦
analysis
User
Transportation
scenario
Figure 315 Conceptual diagram of the Transportation network workflow
Starting point
The user can choose the starting point two different ways
1. By coordinate capture in the map
2. By geocoding an address
The "StPointCapButtonClick" function in 'project_manager.py' serves to capture a map point and set
it as the starting point.
The "StPointGeocodeButtonClick" function in 'project_manager,py' serves to geocode an address
and set it as the starting point.
Points of interest
EPA H2Q lists standard points of interest and lets the user add extra points using three methods:
1. By coordinate capture
2. By geocoding an address
3. By loading a .csv file containing a list of addresses
User transportation scenario
The User transportation scenario is an exact copy of the Roads layer, but with user ability to edit.
"TrScenarioManager.py" is the Ul class for the user transportation scenario's creation and deletion.
"TransportationEditScenario.py" is the Ul class responsible for editing the scenario.
"TrNewRoad.py" is the Ul class responsible for adding new roads to the edited user scenario.
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Network Analysis Library
Network Analysis Library from the QGIS API provides the functionality to build the topology and
perform network analysis on it.
"SpeedProperter "class in 'ShortestPathCalculator.py' describes the strategy pattern based on road
speed used by the network analysis.
Summary and reporting
The output of the network analysis updates the cost in time to reach each of the points of interest
using the starting point as a reference. Upon running the analysis, Project Manager writes the
cost in the buffered user points of interest layer. The report generated for the transportation
module compares the main road network to a selected user transportation scenario.
"TrWriteReport" function in project_manager.py is used for writing the report.
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vvEPA
United States
Environmental Protection
Agency
PRESORTED STANDARD
POSTAGE & FEES PAID
EPA
PERMIT NO. G-35
Office of Research and Development (8101R)
Washington, DC 20460
Official Business
Penalty for Private Use
$300
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