EPA/600/C-22/150 July 2022
https://www.epa.gov/
water-research/storm-water-management-model-swmm
vvEPA
United States
Environmental
Agency
NATIONAL STORMWATER
CALCULATOR WEB APP USER'S
GUIDE-VERSION 3.4.0
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vyEPA
United States
Environmental Protection Agency
EPA/600/C-22/150
July 2022
NATIONAL STORMWATER CALCULATOR WEB
APP USER'S GUIDE - VERSION 3.4.0
Lewis A. Rossman (retired)
Water Infrastructure Division
Center for Environmental Solutions and Emergency Response
United States Environmental Protection Agency
Cincinnati, OH 45268
Jason T. Bernagros (formerly of)
Water Infrastructure Division
Center for Emergency Environmental Solutions and Emergency Response
United States Environmental Protection Agency
Washington, DC 20460
Colleen M. Barr
Oak Ridge Institute for Science and Education (ORISE)
Corvallis, OR 97333
Michelle A. Simon
Water Infrastructure Division
Center for Environmental Solutions and Emergency Response
United States Environmental Protection Agency
By
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DISCLAIMER
The information in this document has been funded wholly by the U.S. Environmental Protection Agency
(EPA). It has been subjected to the Agency's peer and administrative review and has been approved for
publication as an EPA document. Mention of trade names or commercial products does not constitute
endorsement or recommendation for use.
Although a reasonable effort has been made to assure that the results obtained are correct, the
computer programs described in this manual are experimental. Therefore, the author and the U.S.
Environmental Protection Agency are not responsible and assume no liability whatsoever for any results
or any use made of the results obtained from these programs, nor for any damages or litigation that
result from the use of these programs for any purpose.
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ABSTRACT
EPA's National Stormwater Calculator (SWC) is a software application tool that estimates the annual
amount of rainwater and frequency of runoff from a specific site using green infrastructure as low
impact development controls. The SWC is designed for use by anyone interested in reducing runoff from
a property, including site developers, landscape architects, urban planners, and homeowners. This
User's Guide contains information on the SWC web application. SWC Version 3.4 contains has updated
historical meteorological data (from 1970 - 2006 to 1990 - 2019), updated Bureau of Labor Statistics
Cost Data (from 2018 to 2020), and the 5.1.015 Stormwater Management Model (SWMM) engine (from
5.1.007). Evaporation was calculated by the Hargreaves method (EPA, 2015), based on historical or
future daily temperature data.
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ACKNOWLEDGEMENTS
Lewis Rossman, retired from United States Environmental Protection Agency (USEPA), is the primary
developer of the Stormwater Calculator (SWC) and its computational engine, the Stormwater
Management Model (SWMM). He is the initial author of this document.
Paul Duda, Paul Hummel, Jack Kittle, and John Imhoff of Aqua Terra Consultants developed the data
acquisition portions of the National Stormwater Calculator desktop application under Work Assignments
4-38 and 5-38 of EPA Contract #EP-C-06-029. They, along with Alex Foraste (EPA/OW), provided many
useful ideas and feedback throughout the development of the calculator.
Jason Bernagros (formerly of USEPA) served as the Task Order Contracting Officer's Representative
(TOCOR) for the cost estimation task order and the TOCOR for the mobile web application under Task
Orders 0019 (PR-ORD-14-00308) and 026 (PR-ORD-15-00668). Scott Struck, Dan Pankani, and Kristen
Ekeren of Geosyntec, and Marion Deerhake of RTI International developed the cost estimation
components of the Stormwater Calculator.
Jason Bernagros served as the Work Assignment Manager for the development and maintenance of the
mobile web app. Dawn Bontempo, Fahim Chowdhury, Marie Calvo, Martina Donati, Jason Lowengrub,
Anthony Passamonti, Seth Pennington, Catherine Sweeney, and Natasha Virdy of Attain, LLC., Uyen Tran
of Tetra Tech, and developed the mobile web app version of the Stormwater Calculator under Task
Order HHSN316201200117W (EP-G15H-01113).
Michelle Simon (USEPA), Jason Bernagros, and Matthew Hopton (USEPA) were the work assignment
managers for Contract EP-C-17-041 Work Assignments 0-52 - 4-52 with Eastern Research Group. Lori
Weiss, Brad Cooper, Paul Dziemiela, Mike Liadov, Emily Savelli, Naveen Tharalla, and Anton Yakushin
provided some programming support for the mobile application for the Stormwater Calculator.
The majority of the programming for the update for the web application for the SWC since 2019 was
performed by Colleen Barr, assisted by Eastern Research Group. Ms. Barr was supported in part by an
appointment to the Postgraduate Research Program at the U.S. Environmental Protection Agency, Office
of Research and Development, Center for Environmental Solutions and Emergency Response,
administered by the Oak Ridge Institute for Science and Education through Interagency Agreement No.
(DW-8992433001) between the U.S. Department of Energy and the U.S. Environmental Protection
Agency.
Colleen Barr and Michelle Simon were the writers of the updates to the historical meteorological and
climate change data in this third edition of the SWC 3.4.0.
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ASCE
BASINS
BLS
CMIP5
COOP
CREAT
EPA
GCM
GEV
Gl
GLDAS
HPD
HSG
IMD
IPCC
ISD
Ksat
LID
NCEI
NLDAS
NOAA
NRCS
PRISM
SCS
SSURGO
SWC
SWMM
UDFCD
US
USDA
USGCRP
WCRP
ACRONYMS AND ABBREVIATIONS
American Society of Civil Engineers
Better Assessment Science Integrating point and Nonpoint Sources
United States Bureau of Labor Statistics
Coupled Model Intercomparison Project Phase 5
Cooperative Observer Program
Climate Resilience Evaluation and Awareness Tool
United States Environmental Protection Agency
Global Change Model
Generalized Extreme Value
Green Infrastructure
Global Land Data Assimilation System
Hourly Precipitation Data
Hydrologic Soil Group
initial moisture deficit
Intergovernmental Panel on Climate Change
Integrated Surface Database
saturated hydraulic conductivity
low impact development
National Centers for Environmental Information
North American Land Data Assimilation System
National Oceanic and Atmospheric Administration
Natural Resources Conservation Service
Parameter-elevation Regressions on Independent Slopes Model
Soil Conservation Service
Soil Survey Geographic Database
Stormwater Calculator
Storm Water Management Model
Urban Drainage and Flood Control District
United States
United States Department of Agriculture
United States Global Change Research Program
World Climate Research Programme
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TABLE OF CONTENTS
DISCLAIMER
ABSTRACT
ACKNOWLEDGEMENTS
ACRONYMS AND ABBREVIATIONS
TABLE OF CONTENTS
LIST OF FIGURES
LIST OF TABLES
1. Introduction
2. How to Run the Calculator
Location
Soil Type
Soil Drainage
Topography
Precipitation/Temperature
Climate Change
Land Cover
LID Controls (including cost estimation options)
Results
3. Interpreting the Calculator's Results
Summary Results
Rainfall / Runoff Events
Rainfall / Runoff Frequency
Rainfall Retention Frequency
Runoff by Rainfall Percentile
Extreme Event Rainfall/Runoff
Cost Summary
Printing Output Results
4. Applying LID Controls
5. Example Application
Pre-Development Conditions
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Post-Development Conditions 57
Post-Development with LID Practices 59
Cost Summary 66
Climate Change Impacts 70
6. Computational Methods 76
SWMM's Runoff Model 76
SWMM's LID Model 77
Site Model without LID Controls 79
Site Model with LID Controls 82
Precipitation Data 83
Temperature Data 86
Climate Change Effects 87
Cost Estimation 89
Post-Processing 102
7. References 104
LIST OF FIGURES
Figure 1. The calculator's (a) Opening page and (b) Location icon page 12
Figure 2. The calculator's Location icon page 14
Figure 3. Bird's eye map view with a bounding circle 15
Figure 4. Bird's eye map view with a bounding polygon 15
Figure 5. The calculator's Soil Type page 16
Figure 6. The calculator's warning when SSURGO is unavailable 16
Figure 7. The calculator's Soil Drainage icon page 18
Figure 8. The calculator's Topography icon page 20
Figure 9. The calculator's Precipitation/Temperature icon page 21
Figure 10. The calculator's Precipitation/Temperature icon page (weather station) 22
Figure 11. The calculator's Climate Change icon page 24
Figure 12. The calculator's Land Cover page 26
Figure 13. The calculator's LID Controls icon page 28
Figure 14. The Calculator's Project Cost icon page showing the Re-Development pop-out window (shown
by clicking Re-Development) 29
Figure 15. The Calculator's Project Cost icon page showing the Site Suitability - Poor pop-out window
(shown by clicking Poor) 30
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Figure 16. Map of BLS Regional Cost Centers (pop-out window) used for computing regional multipliers.
A multiplier for each Regional Center applied within a 100-mile radius (inside blue circles). A National
value of 1 used otherwise (in green areas) 31
Figure 17. Drop down list of closest BLS Regional Cost Centers and national value 32
Figure 18. The calculator's Results icon page 33
Figure 19. An example of the calculator's Summary Results report 36
Figure 20. The calculator's Rainfall / Runoff Event report 38
Figure 21. The calculator's Rainfall / Runoff Frequency report 39
Figure 22. The calculator's Rainfall Retention Frequency report 40
Figure 23. The calculator's Runoff by Rainfall Percentile report 41
Figure 24. The calculator's Extreme Event Rainfall / Runoff report 43
Figure 25. Graphical output option of the calculator's estimate of average capital costs 46
Figure 26. Graphical output option of the calculator's estimate of average annual maintenance costs... 48
Figure 27. Example of an LID Design dialog for a street planter 51
Figure 28. Runoff from different size storms for pre-development conditions on the example site 56
Figure 29. Rainfall retention frequency under pre-development conditions for the example site 57
Figure 30. Rainfall retention frequency for pre-development (Baseline) and post-development (Current)
conditions 59
Figure 31. Low Impact Development controls applied to the example site 60
Figure 32. Design parameters for Rain Harvesting and Rain Garden controls 61
Figure 33. Design parameters for the Infiltration Basin and Permeable Pavement controls 62
Figure 34. Daily runoff frequency curves for pre-development (Baseline) and post-development with LID
controls (Current) conditions 64
Figure 35. Contribution to total runoff by different magnitude storms for pre-development (Baseline)
and post-development with LID controls (Current) conditions 65
Figure 36. Retention frequency plots under pre-development (Baseline) and post-development with LID
controls (Current) conditions 66
Figure 37. Graphical output option of the calculator's estimate of capital costs 68
Figure 38. Graphical output option of the calculator's estimate of maintenance costs 70
Figure 39. Climate change scenarios for the example site 71
Figure 40. Daily rainfall and runoff frequencies for the historical (Baseline) and "Warm/Wet" climate
scenarios 73
Figure 41. Target event retention for the historical (Baseline) and "Warm/Wet" climate scenarios 74
Figure 42. Extreme event rainfall and runoff for the "Warm/Wet" climate change scenario and the
historical record (Baseline) 75
Figure 43. Conceptual representation of a bio-retention cell 77
Figure 44. Rain gage locations included in the calculator. Alaska, Hawaii, Puerto Rico, and the U.S. Virgin
Islands are not shown 84
Figure 45. NRCS 24-hour rainfall distributions (Merkel et al., 2017, USDA, 1986) 85
Figure 46. Rainfall distributions used in the SWC (Merkel et al., 2017, USDA, 1986). Alaska and Hawaii
(not shown) are Type SCS_1 86
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Figure 47. CREAT 3.1 illustration of ensemble-informed selection using CMIP5 projected changes in
temperature and precipitation for 2060 (EPA, 2021) 88
Figure 48. Conceptual overview showing cost estimate ranges increase with area and complexity derived
from cost curves 98
Figure 49. Sample regression cost curve for Rain Gardens 99
LISTS OF TABLES
Table 1. Definitions of Hydrologic Soil Groups (USDA, 2010a) 17
Table 2. Tabular representation of the calculator's estimate of capital costs 45
Table 3. Tabular output option of the calculator's estimate of annual maintenance costs 47
Table 4. Descriptions of LID practices included in the calculator 50
Table 5. Editable LID parameters 52
Table 6. Void space values of LID media 52
Table 7. Summary results for pre-development conditions on the example site 55
Table 8. Land cover for the example site in developed state 58
Table 9. Comparison of runoff statistics for post-development (Current) and pre-development (Baseline)
conditions 58
Table 10. Runoff statistics for pre-development (Baseline) and post-development with LID controls
(Current) scenarios 63
Table 11. Tabular output option of the calculator's estimate of capital costs 67
Table 12. Tabular output option of the calculator's estimate of maintenance costs 69
Table 13. Summary results under a "Warm/Wet" (Current) climate change scenario compared to the
historical (Baseline) condition 72
Table 14. Depression storage depths (inches) for different land covers 80
Table 15. Roughness coefficients for different land covers 81
Table 16. Infiltration parameters for different soil types 82
Table 17. Cost Variables Selected for Cost Estimation Procedure 91
Table 18. LID Control Cost Curve Regression Equations 92
Table 19. Project Complexity Computation Based on User Input 93
Table 20. Regionalized Cost Model Coefficients for BLS Center 96
Table 21. BLS Regional Centers 100
Table 22. National BLS Variables and Model Coefficients 101
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1. Introduction
The National Stormwater Calculator (https://www.epa.gov/water-research/national-stormwater-
calculator) is a simple to use tool for computing hydrology for sites up to 12 acres for any location within
the US. It estimates the amount of stormwater runoff generated from a site under different
development and control scenarios over a long-term period of historical precipitation. The analysis
considers local soil conditions, slope, land cover, and meteorology. Different types of low impact
development (LID) practices (also known as green infrastructure) can be employed to help capture and
retain rainfall on-site. Future climate change scenarios from internationally recognized climate change
projections are also available. The calculator provides planning level estimates of capital and
maintenance costs which will allow planners and managers to evaluate and compare effectiveness and
costs of LID controls.
The calculator's primary focus is informing site developers and property owners on how well they can
meet a desired stormwater retention target. It can be used to answer such questions as the following:
• What is the largest daily rainfall amount that can be captured by a site in either its pre-
development, current, or post-development condition?
• To what degree will stormwater runoffs of different magnitudes be captured on site?
• What mix of LID controls can be deployed to meet a given stormwater retention target?
• How well will LID controls perform under future meteorological projections made by global
climate change models?
• What are the relative costs (capital and maintenance) differences for various mixes of LID
controls?
The calculator accesses several national databases to provide local soil and meteorological data for a
site. The user supplies land cover information that reflects the state of development they wish to
analyze and selects a mix of LID controls to be applied. After this information is provided, the site's
hydrologic response to a long-term record of historical hourly precipitation, possibly modified by a
particular climate change scenario, is computed. This allows a full range of meteorological conditions to
be analyzed, rather than just a single design storm event. The resulting time series of rainfall and runoff
are aggregated into daily amounts that are then used to report various runoff and retention statistics. In
addition, the site's response to extreme rainfall events of different return periods is also analyzed.
The calculator uses the EPA Storm Water Management Model (SWMM) as its computational engine
(https://www.epa.gov/water-research/storm-water-management-model-swmm). SWMM is a well-
established, EPA developed model that has seen continuous use and periodic updates for 40 years. Its
hydrology component uses physically meaningful parameters making it especially well-suited for
application on a nation-wide scale. SWMM is set up and run in the background without requiring any
involvement of the user.
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The calculator is most appropriate for performing screening level analysis of small footprint sites up to
12 acres in size with uniform soil conditions. The hydrological processes simulated by the calculator
include evaporation of rainfall captured on vegetative surfaces or in surface depressions, infiltration
losses into the soil, and overland surface flow. No attempt is made to further account for the fate of
infiltrated water that might eventually transpire through vegetation or re-emerge as surface water in
drainage channels or streams.
The remaining sections of this guide discuss how to install the calculator, how to run it, and how to
interpret its output. An example application is presented showing how the calculator can be used to
analyze questions related to stormwater runoff, retention, and control. Finally, a technical description is
given of how the calculator performs its computations and where it obtains the parameters needed to
do so.
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2. How to Run the Calculator
The National Stormwater Calculator mobile web app is an HTML5, platform neutral and responsive
mobile version of the desktop version of the calculator. The mobile version supports the existing
functionality of the desktop version of the calculator. It may be used with publicly available internet
browsers on laptop and desktop computers, smartphones, and tablets—you must have an internet
connection to run the calculator. The mobile web app functions best on the following web browsers:
Google Chrome, Microsoft Edge, Apple Safari, and Mozilla Firefox. The mobile web app may be accessed
from the following web page: https://www.epa.gov/water-research/national-stormwater-calculator.
The opening and main windows of the calculator are displayed in Figure 1. The main window uses a
series of tabbed pages to collect information about the site being analyzed and to run and view
hydrologic results. A Bing Maps display allows you to view the site's location, its topography, selected
soil properties and the locations of nearby rain gages and weather stations.
National Stormwater Calculator
Location
Sol Type
Soil Drainage
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Climate Change
Land Cover
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Figure 1. The calculator's (a) Opening page and (b) Location icon page.
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Location
Directions
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The various pages of the calculator are represented by icons and used as follows:
1. Location icon - establishes the site's location.
2. Soil Type icon - identifies the site's soil type.
3. Soil Drainage icon - specifies how quickly the site's soil drains.
4. Topography icon - characterizes the site's surface topography.
5. Precipitation/Temperature icon - selects a nearby rain gage to supply hourly rainfall data and a
nearby weather station to supply temperature data.
6. Climate Change icon - selects a climate change scenario to apply.
7. Land Cover icon - specifies the site's land cover for the scenario being analyzed.
8. LID Controls icon - selects a set of LID control options, along with their design features, to
deploy within the site and specifies site and project considerations for cost estimation purposes.
9. Project Costs icon - specifies site and project considerations for cost estimation purposes.
10. Results icon - runs a long-term hydrologic analysis and displays the results including estimates of
capital costs and average annual maintenance costs.
Six commands shown in the top panel of the web app can also be used at any time:
1. U.S. EPA logo: takes you back to the homepage of the web app.
2. New: discards all previously entered data and takes you back to the Location page where a new site
can be selected. You will first be prompted to save the data you entered for the current site.
3. Save: saves the information you have entered for the current site to a disk file. The saved file can be
re-opened in a future session of the calculator by selecting the Open command.
4. Open: allows you to open a previously saved site.
5. Resources: shows you helpful resources, such as this User's Manual, general LID, green infrastructure,
and climate change information from the U.S. EPA.
6. Contact: provides the SWCffiepa.gov email address.
You can move back and forth between the calculator's icon pages to modify your selections. Most of the
pages have a Help command available that will display additional information about the page when
selected. Underlined text can be clicked to display more information. After an analysis has been
completed on the Results icon page, you can choose to designate it as a "baseline" scenario, which
means that its results will be displayed side-by-side with those of any additional scenarios that you
choose to analyze. Each of the calculator's icon pages will now be described in more detail.
Location
The Location icon page of the calculator is shown in Figure 2. You are asked to identify where in the U.S.
the site is located. This information is used to access national soils and meteorological databases as well
as Bureau of Labor Statistics (BLS) data for cost estimation purposes. It has an address lookup feature
that allows you to easily navigate to the site's location. You can enter an address or zip code in the
Search box and either click on the Search icon or press the Enter key to move the map view to that
location. You can also use the map's pan and zoom controls to hone in on a particular site. Once the site
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has been located somewhere within the map's viewport, move the mouse pointer over the site and then
left-click the mouse to mark its exact location with a drop-down point.
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Figure 2. The calculator's Location icon page.
The map display can be toggled between a standard road, aerial, bird's eye, and streetside views. Figure
3 shows the site located in Figure 2 with a zoomed~in aerial view selected with the site bounded by an
orange circle. You can specify the area of the site, which will result in a bounding orange circle, or a
polygon being drawn on the map. Figure 4 illustrates how a user may click on the polygon draw tool to
draw out polygon points that create a connected polygon boundary around the project site. The project
area cannot be larger than 12 acres. Entering the size of your site is optional because the calculator
makes all of its computations on a per unit area basis.
You can also click on Open a previously saved site to read in data for a site that was previously saved to a
file to continue working with those data (every time you begin analyzing a new site or exit the program
the calculator asks if you want to save the current site to a file). Once you open a previously saved site,
the calculator will be populated with its data.
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Figure 3. Bird's eye map view with a bounding circle.
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Figure 4. Bird's eye map view with a bounding polygon.
Directions
Bring your site into view on the map and
then mark its exact location by clicking the
mouse pointer over it or entering your
address or zip code below.
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Soil Type
Figure 5 shows the Soil Type icon page of the calculator, which is used to identify the type of soil present
on the site. Soil type is represented by its Hydrologic Soil Group (HSG). This is a classification used by soil
scientists to characterize the physical nature and runoff potential of a soil. The calculator uses a site's
soil group to infer its infiltration properties (Table 1).
You can select a soil type based on local knowledge or by retrieving a soil map overlay from the U.S.
Department of Agriculture's Natural Resources Conservation Service (NRCS) SSURGO database
(https://websoilsurvey.sc.egov.usda.gov/App/HomePage.htm). Simply select the soil type icon on the
left side of the screen to retrieve SSURGO data. (There will be a slight delay the first time that the soil
data are retrieved, and the color-coded overlay is drawn). There is an option to hide the soil polygon
data under the soil type menu box. Figure 5 displays the results from a SSURGO retrieval. You can then
select a soil type directly from the left panel or click on a color shaded region of the map. If the SSURGO
database is not available, you will see a warning as shown in Figure 6.
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Figure 5. The calculator's Soil Type page.
Warning!
Could not access the SSURGO soils data base. The service may
be unavailable.
Figure 6. The calculator's warning when SSURGO is unavailable.
Directions
Select a soil type and runoff potential from
the choices listed or by clicking a shaded
region of the map to select its value.
USDA's Web Soil Survey (WSS) I
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The SSURGO database houses soil characterization data for most of the U.S. that have been collected
over the past 40 years by federal, state, and local agencies participating in the National Cooperative Soil
Survey. These data are compiled by "map units" which are the boundaries that define a particular
recorded soil survey. These form the irregular shaped polygon areas that are displayed in the
calculator's map pane.
Soil survey data do not exist for all parts of the country, particularly in downtown core urban areas;
therefore, it is possible that no data will be available for your site. In this case you will have to rely on
local knowledge to designate a representative soil group.
Table 1. Definitions of Hydrologic Soil Groups (USDA, 2010a).
Group
Meaning
Saturated
Hydraulic
Conductivity
(in./hr.)
A
Low runoff potential. Soils having high infiltration rates even when thoroughly
wetted and consisting chiefly of deep, well to excessively drained sands or gravels.
>0.45
B
Soils having moderate infiltration rates when thoroughly wetted and consisting
chiefly of moderately deep to deep, moderately well to well-drained soils with
moderately fine to moderately coarse textures, e.g., shallow loess, sandy loam.
0.30-0.15
C
Soils having slow infiltration rates when thoroughly wetted and consisting chiefly
of soils with a layer that impedes downward movement of water, or soils with
moderately fine to fine textures, e.g., clay loams, shallow sandy loam.
0.15-0.05
D
High runoff potential. Soils having very slow infiltration rates when thoroughly
wetted and consisting chiefly of clay soils with a high swelling potential, soils with
a permanent high-water table, soils with a clay-pan or clay layer at or near the
surface, and shallow soils over nearly impervious material.
0.05 - 0.00
Soil Drainage
The Soil Drainage icon page of the calculator (Figure 7) is used to identify how fast standing water drains
into the soil. This rate, known as the "saturated hydraulic conductivity," is arguably the most significant
parameter in determining how much rainfall can be infiltrated.
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Figure 7. The calculator's Soil Drainage icon page.
There are several options available for assigning a hydraulic conductivity value (in inches per hour) to
the site:
a) The edit box can be left blank, in which case, a default value based on the site's soil type will be
used (the default value is shown next to the edit box).
b) As with soil group, conductivity values from the SSURGO database are displayed on the map
when the soil drainage icon is selected. Clicking the mouse on a colored region of the map will
make its conductivity value appear in the edit box.
c) If you have local knowledge of the site's soil conductivity you can simply enter it directly into the
edit box. This is preferred over the other two choices.
It should be noted that the hydraulic conductivity values from the SSURGO database are derived from
soil texture and depth to groundwater and are not field measurements. As with soil type, there may not
be any soil conductivity data available for your particular location.
Hide soli type data
How fast does rainwater infiltrate j
of your site (inches/hour)?
Directions
Enter your own conductivity value directly
into the input field below or click a shaded
region on the map to select its conductivity
value. If you leave the edit box blank, the
default conductivity associated with the
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Topography
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Figure 8. The calculator's Topography icon page.
Figure 8 displays the Topography icon page of the calculator. Site topography, as measured by surface
slope (feet of drop per 100 feet of length), affects how fast excess stormwater runs off a site, Flatter
slopes result in slower runoff rates and provide more time for rainfall to infiltrate into the soil. Runoff
rates are less sensitive to moderate variations in slope. Therefore, the calculator uses only four
categories of slope - flat (2%, for slopes <= 2%), moderately flat (5%, for slopes <= 7%), moderately
steep (10%, for slopes <= 15%) and steep (above 15%, for slopes > 15%). As with soil type and soil
drainage, any available SSURGO slope data will be displayed on the map when the topography icon is
selected. You can use the resulting display as a guide or use local knowledge to describe the site's
topography.
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Topography
• Flat (2% Slope)
• Moderately Flat (5% Slope)
O Moderately Sleep (10% Slope)
• Sleep (Above 15% Slope)
Directions
Select a slope from the choices listed
below or click a shaded region on the map
to select its value
USDA's Web Soil Survey (WSS) has
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Figure 8. The calculator's Topography icon page.
Precipitation /T emperature
The Precipitation/Temperature icon page of the calculator is shown in Figure 9. It is used to the select
rain gage location that will supply rainfall data for the site and the location to supply temperature data
that will be used to model evaporation. Rainfall is the principal driving force of runoff. The calculator
uses a long-term continuous hourly rainfall record to make sure that it can replicate the full scope of
storm events that might occur. In addition, it identifies a set of 24-hour extreme event storms
associated with each rain gage location. These are a set of six intense storms that would have 20-, 10-, 7-
, 3-, 2- and 1- percent exceedance probability (commonly referred to as 5-, 10-, 15-, 30-, 50- and 100-
year rainfall events or return periods, respectively).
IS Aerial
Directions
Select a slope from the choices listed
below or click a shaded region on the map
to select its value.
USDA's Web Soil Survey (WSS) I
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Figure 9. The calculator's Precipitation/Temperature icon page.
The calculator contains a catalog of over 2,600 rain gage locations from the National Oceanic and
Atmospheric Administration's (NOAA' National Centers for Environmental Information (NCEI). Historical
hourly rainfall data for each station have been extracted from the NCEI's repository, screened for quality
assurance, and processed into precipitation files formatted for SWMM, More details on the processing
steps for the precipitation data can be found in the Computational Methods section. As shown in Figure
9, the calculator will automatically locate the five nearest gages to the site and list their location, period
of record and average annual rainfall amount. You can choose what you consider to be the most
appropriate source of rainfall data for the site by selecting one of the available rain gages in the drop-
down list or the map icons.
The Precipitation/Temperature icon page of the calculator also allows the user to select a weather
station that will supply daily minimum and maximum temperature values to model evaporation rates for
the site. Evaporation determines how quickly the moisture retention capacity of surfaces and depression
storage consumed during one storm event will be restored before the next event.
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Figure 10. The calculator's Precipitation/Temperature icon page (weather station).
For each location corresponding to each rain gage location throughout the U.S., daily minimum and
maximum temperature data was obtained from Oregon State University's PRISM Climate Group. These
data were downloaded, processed, and stored in a climate file formatted for SWMM. The calculator lists
the five closest locations that appear in the table along with their period of record. The daily minimum
and maximum temperatures are used to estimate evaporation using the Hargreaves Equation (EPA,
2015). More details are provided in the Computational Methods section of this document.
When the Download precipitation data or Download temperature data commands are clicked, a Save As
dialog window will appear allowing you to save the data as text files in case you want to use those data
in some other application, such as SWMM. Each line of the rainfall data file will contain the recording
station identification number, year, month, day, hour, and minute of the rainfall reading and the
measured hourly rainfall intensity in inches/hour. The temperature data will also be downloaded as a
text file. Each line of the temperature data file will contain the recording station identification number,
year, month, day, and the daily lowest and highest temperature in degrees Fahrenheit.
Climate Change
The 2014 Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) states that
changing of the climate is now unequivocal (IPCC, 2014). Some of the impacts that such changes can
have on the small-scale hydrology addressed by the calculator include changes in seasonal precipitation
levels, more frequent occurrence of high intensity storm events, and changes in evaporation rates (Karl
et al., 2009). A climate change component has been included in the calculator to help you explore how
these impacts may affect the amount of stormwater runoff produced by a site and how it is managed.
Figure 11 displays the Climate Change icon page of the calculator. It is used to select a particular future
climate change scenario for the site. The scenarios were derived from the World Climate Research
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Record Start Date 199Q.'01'01
Record End Date 2019/12/31
Annual Precipitation 46 86
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Program's Coupled Model Intercomparison Project, Phase 5 (CMIP5) multi-model dataset (Taylor et al.,
2012). The CMIP5 dataset has been incorporated into EPA's Climate Resilience Evaluation and
Awareness Tool (CREAT) version 3.1 (EPA, 2021). The CREAT dataset contains results of global climate
models run with the Representative Concentration Pathway 8.5, a high greenhouse gas emissions
trajectory to support assessments looking at plausible future scenarios with higher potential risk. CREAT
provides results from a 38-member ensemble that have been downscaled to a regional Vz degree grid
that includes each of the calculator's rain gage and weather station locations. CREAT groups models into
three scenarios: one is representative of model outputs that produce "Hot/Dry" conditions, another
represents changes that come close to the "Central" outcome from the different models, and a third
represents model outcomes that produce "Warm/Wet" conditions. In each case, two scenarios are
available that span the projected range of changes for extreme storms (24-hour design storms): a
"Stormy" scenario that represents models with higher changes in extreme events per degree of warming
and a "Less Stormy" scenario that represents models with lower changes in extreme events per degree
of warming. Projections for the climate change and extreme storm scenarios are available for two future
time periods: 2035 (averaged change values across projections from years 2025 - 2045) and 2060
(averaged change values across projections from 2050 - 2070).
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E^^National Stormwater Calculator
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2. The changes in monthly average temperatures are applied in similar fashion to the historical daily
temperature records used to calculate evaporation.
3. The climate change influenced extreme event rainfalls are used in place of the historical ones.
The "Hot/Dry", "Central", and "Warm/Wet" scenarios can be used to better understand the uncertainty
associated with future climate projections. For example, analyzing the two scenarios resulting in the
most severe increases and decreases in rainfall respectively, brackets the range of possible rainfall
conditions likely to occur. Alternately, if multiple scenarios show increases in extreme storms, this
suggests a greater likelihood that that larger rainfall events will occur. All three scenarios should be
considered when bracketing future conditions, because the greatest projected change in extreme
storms is not always associated with the "Hot/Dry" or "Warm/Wet" total precipitation scenarios and is
different from one location to the next.
More details on the source of the climate change scenarios and how they are used to compute site
runoff are provided in the Computational Methods section of this user's guide.
Understanding regional climate impacts may help you select appropriate climate change scenarios.
Online resources highlighting regional climate change impacts for the contiguous U.S., Hawaii, Alaska,
and U.S. Territories are available at (https://nca2018.globalchange.gov/ (USGCRP, 2018) and at
http://www.globalchange.gov/explore/ (USGCRP, 2014)). Other helpful links are
EPACREAT: https://www.epa.gov/crwu/climate-resilience-evaluation-and-awareness-tool-creat-risk-
assessment-application-water
World Climate Research Programme: https://www.wcrp-climate.org/wgcm-cmip
EPA Climate Change Indicators: https://www.epa.gov/climate-indicators/weather-climate
NOAA State Climate summaries: https://statesummaries.ncics.org/
Land Cover
Figure 12 displays the Land Cover icon page of the calculator. It is used to describe the different types of
pervious land cover on the site. Infiltration of rainfall into the soil can only occur through pervious
surfaces. Different types of pervious surfaces capture different amounts of rainfall on vegetation or in
natural depressions and have different surface roughness. Rougher surfaces slow down runoff flow
providing more opportunity for infiltration. The remaining non-pervious site area is considered to be
"directly connected impervious surfaces" (roofs, sidewalks, streets, parking lots, etc. that drain directly
off-site). Disconnecting some of this area, to run onto lawns for example, is an LID option appearing on
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the next page of the calculator. You are asked to supply the percentage of the site covered by each of
four different types of pervious surfaces:
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Figure 12, The calculator's Land Cover page.
You are asked to supply the percentage of the site covered by each of four different types of pervious
surfaces:
1. Forest - stands of trees with adequate brush and forested litter cover
2. Meadow - non-forested natural areas, scrub, and shrub rural vegetation
3. Lawn - sod lawn, grass, and landscaped vegetation
4. Desert - undeveloped land in arid regions with saltbush, mesquite, and cactus vegetation
You should assign land cover categories to the site that reflects the specific condition you wish to
analyze: pre-development, current, or post-development. A pre-development land cover will most likely
contain some mix of forest, meadow, and perhaps desert. Local stormwater regulations might provide
guidance on how to select a pre-development land cover or you could use a nearby undeveloped area as
an example. Viewing the site map in bird's eye view, as shown in Figure 12, would help identify the land
cover for current conditions. Post-development land cover could be determined from a project's site
development plan map. Keep in mind that total runoff volume is highly dependent on the amount of
impervious area on the site while it is less sensitive to how the non-impervious area is divided between
the different land cover categories.
Land Cover
Directions
Describe the site's land cover for the
development scenario being analyzed
Click on a category
description.
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LID Controls (including cost estimation options)
The LID Controls icon page of the calculator is depicted in Figure 13. It is used to deploy low impact
development (LID) controls throughout the site. These are landscaping practices designed to capture
and retain stormwater generated from impervious surfaces that would otherwise run off the site. There
are seven different types of green infrastructure (Gl) LID controls available (Figure 13). You can elect to
apply any mix of these LID controls by simply telling the calculator what percentage of the impervious
area is treated by each type of control. Each control has been assigned a reasonable set of design
parameters, but these can be modified by clicking on the name of the control. You have the option to
specify a 24-hour design storm to assist you with sizing the selected LID controls. More details on each
type of control practice, its design parameters and sizing it to retain a given design storm are provided in
the LID Controls section of this user's guide. For the purposes of cost estimation, the calculator factors
in the cost implications of construction feasibility and site suitability and adjusts the cost of the LID
Controls based on regional cost differences associated with a site's location. Refer to the Cost Estimation
section of this user guide (page 89) for a brief discussion of the cost curve approach used to generate
estimates of probable capital and maintenance costs in the calculator. By indicating whether the project
is New- or Re-development and selecting from Poor, Moderate, or Excellent for site suitability for
placing LID controls along with other user input information, the calculator computes and applies the
appropriate cost curve for the project.
For additional help with selecting the options that influence project site complexity, click the blue
underlined text labeled Re-Development, New Development, Poor, Moderate, and Excellent on the LID
controls tab, to show a help window explaining the conditions that warrant the selection of each of
those options. An example of the help window for Re-Development is shown in Figure 14 and the help
window for Poor (Site Suitability - Poor) is show in Figure 15.
The calculator uses Bureau of Labor Statistics (BLS) data to compute regional cost adjustment factors
and allows the user to choose from the various computed factors as follows:
• National - this is the default selected value if your site is more than 100 miles from any of the 17
BLS Regional Centers distributed across the country (including centers from the Northeast,
Midwest, South, and West).
• Nearest 3 BLS Regional Centers - arranged in ascending order of distance from your project site.
You have the option of selecting one of the nearest three BLS Regional Centers.
• Other - select this if you are an advanced user and want to specify your own regional cost
adjustment factor.
Click on Cost Region for a map of the BLS Regional Centers (Figure 16). Regional cost multipliers for each
Region are selected as the default multiplier for areas within a 100-mile radius of the regional center
(see light blue circles in Figure 16). Areas that are not within a 100-mile radius of any regional center are
assigned a default National value of 1 (see green areas in Figure 16). The user can override the default
selection by selecting one of the three closest regions to their location from the Cost Region drop down
menu (Figure 17). Note that regional cost multipliers that are greater than 1 increase costs, while
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multipliers that are less than 1 decrease costs compared to the National average. Additional information
about the cost estimation procedure, including the BLS regional centers is provided on page 100
National Stormwater Calculator
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Figure 13. The calculator's LID Controls icon page.
LID Controls
Directions
Enter the percentage of your site's
impervious area you would like to be
treated by the listed LID Controls.
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National Stormwater Calculator
OPEN RESOURCES CONTACT
Directions
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Choose your Site Suitabiltiy
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Project Cost
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Re-Development is construction that is a change in existing development (land cover, land use, or similar development alteration) which
requires new or alteration of existing stormwater management facilities.
Costs of removal, decommissioning, or alteration of existing structures or additional (new) infrastructure is typically required to connect
existing structures and results in costs that are greater than what would be anticipated with a new development site.
Re-development and extensive retrofit costs are typically higher than
new development costs because existing structures might have to be removed or new structures may be required but may not be located in
a preferred location.
Selecting "Re-developmenr on the "Project Cost" tab of the National Stormwater Calculator influences the site complexity and shifts the
costs towards a higher complexity cost estimation.
Re-development combined with information on site suitability, topography, and soil drainage determines whether complex, typical, or simple
cost curves apply. See User Guide for more information.
Close
Figure 14. The Calculator's Project Cost icon page showing the Re-Development pop-out window
(shown by clicking Re-Development)
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Site suitability is a measure of construction feasibility and includes factors such as topography, soil type, slope- and other physical features
that might result in higher implementation costs.
Poor site suitability refers to sites that have a number of the following characteristics
• Physical obstructions,
• Utility conflicts.
• Other features that are likely to make construction of stormwater management infrastructure challenging and more costly.
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Sites determined to have poor suitability for LID practices are typically higher in cost because of the potential need for additional excavation,
accommodation for physical obstructions, required retaining walls, challenging access distant haul locations, required dewatering the
addition of engineered or custom media blends, and need to address geotechnical or groundwater concerns
Selecting "Site Suitability - Poof on the "Project Cost' tab of the National Stormwater Calculator influences the site complexity, and shifts
the costs towards a higher complexity cost estimation.
Poor site suitability combined with information on development type, topography, and soil drainage determines whether complex, typical, or
simple cost curves apply. See User Guide for more information.
Figure 15. The Calculator's Project Cost icon page showing the Site Suitability - Poor pop-out window
(shown by clicking Poor).
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Your "region" has been determined from the Location tab. Using data from the Bureau of Labor Statistics (BLS) a multiplier has been
computed representing the relative regional differences in costs for your nearest region (unless 'National" is shown) compared to National
costs. Three regions are reported from 20 of the major cities for which BLS data is available Users can select another region or select
"National' to apply a multiplier of 1. representing a national average. If you prefer to apply your own multiplier, select 'Other" and enter the
multiplier in the Regional Multiplier field (a multiplier >1 would adjust above the National average, while a multiplier < 1 would adjust below
the National average). The default multiplier for your region is shown in the Regional Multiplier box. The light blue circles in the figure below
represent areas within a 100-mile radius of each major city. See User Guide for more information.
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Figure 16. Map of BLS Regional Cost Centers (pop-out window) used for computing regional
multipliers. A multiplier for each Regional Center applied within a 100-mile radius (inside blue circles).
A National value of 1 used otherwise (in green areas).
Green infrastructure (Gl), similar to LID controls, is a relatively new and flexible term, and it has
been used differently in different contexts. However, for the purposes of EPA's efforts to
implement the Gl Statement of Intent, EPA intends the term Gl to generally refer to systems
and practices that use or mimic natural water flow processes and retain stormwater or runoff
on the site where it is generated. Gl can be used at a wide range of landscape scales in place of,
or in addition to, more traditional stormwater control elements to support the principles of LID.
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National Stormwater Calculator
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Results
The final page of the calculator is where a hydrologic analysis of the site is run; its results are displayed
along with estimates of probable capital and maintenance costs. As shown in Figure 18, by selecting the
Site Description report option you can first review data that you entered for the site and go back to
make changes if needed.
Project Cost
Choose a Project Type
Choose your Site Suitabiltiy
• Moderate
# Excellent
Choose your Cost Region
Atlanta(60 miles)
Directions
Atlanta(60 miles)
Detroit(581 miles)
Miami(595 miles)
NATIONAL(NA)
Other (NA)
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yy ER^\ National Stormwater Calculator
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Results
Directions
Options:
Years to Analyze:
Event Threshold:
0.1
O Ignore Consecutive Days
Actions:
Reports:
O Site Description
(§) Summary Results
O Rainfall / Runoff Events
O Rainfall / Runoff Exceedance Frequency
O Rainfall Retention Frequency
O Runoff Contribution by Rainfall Percentile
O Extreme Event Rainfall / Runoff
O Cost Summary
Summary Results
Current Scenario
Annual Rainfall: 44.99 in.
Statistic
Average Annual Rainfall (inches)
Average Annual Runoff (inches)
Days per Year with Rainfall
Days per Year with Runoff
Percent of Wet Days Retained
Smallest Rainfall w/ Runoff (inches)
Largest Rainfall w/o Runoff (inches)
Max Rainfall Retained (inches)
Current Scenario
44.99
22.42
68.11
47.17
30.74
Figure 18. The calculator's Results icon page.
The input controls on this page are grouped together in three sections: Options, Actions, and Reports.
The Options section allows you to control how the rainfall record is analyzed via the following settings:
1. The number of years of rainfall record to use (moving back from the most recent year on
record).
2. The event threshold, which is the minimum amount of rainfall (or runoff) that must occur over a
day for that day to be counted as having rainfall (or runoff). Rainfall (or runoff) above this
threshold is referred to as "observable" or "measurable."
3. The choice to ignore consecutive wet days when compiling runoff statistics (i.e., a day with
measurable rainfall must be preceded by at least two days with no rainfall for it to be counted).
The latter option appears in some state and local stormwater regulations as a way to exempt extreme
storm events, such as hurricanes, from any stormwater retention requirements. Normally, you would
not want to select this option as it will produce a less realistic representation of the site's hydrology.
Note that although results are presented as annual and daily values, they are generated by considering
the site's response to the full history of hourly rainfall amounts.
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The Actions section of the page contains commands that perform the following actions:
Refresh Results - runs a long-term simulation of the site's hydrology and updates the output displays
with new results (it will be disabled if results are currently available, and no changes have been made to
the site's data).
Use as Baseline Scenario - uses the current site data and its simulation results as a baseline against
which future runs will be compared in the calculator's output reports (this option is disabled if there are
no current simulation results available).
Remove Baseline Scenario - removes any previously designated baseline scenario from all output
reports.
Print Results to PDF File - writes the calculator's results for both the current and any baseline scenario
to a PDF file that can be viewed with a PDF reader at a future time.
The Reports section of the page allows you to choose how the rainfall / runoff results for the site should
be displayed. A complete description of each type of report available will be given in the next section of
this guide.
When the calculator first loads or begins to analyze a new site the following default values are used:
Soil Group: B
Conductivity: 0.4 inches/hour
Surface Slope: 5%
Rainfall Station: Nearest cataloged station
Evaporation Station: Nearest cataloged station
Climate Change Scenario: None
Land Cover: 40% Lawn, 60% impervious
LID Controls: None
Years to Analyze: 20
Event Threshold: 0.10 inches
Ignore Consecutive Days: No
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3. Interpreting the Calculator's Results
The Results page of the calculator (Figure 18) contains a list of reports that can be generated from its
computed results. Before discussing the contents of these reports, it will be useful to briefly describe
how the calculator derives its results. After you select the Refresh Results command, the calculator
computes an estimate of probable capital and maintenance costs and internally performs the following
operations:
1. A SWMM input file is created for the site using the information you provided to the calculator.
2. The historical hourly rainfall record and historical daily temperature record for the site is
adjusted for any climate change scenario selected.
3. SWMM is run to generate a continuous time series of rainfall and runoff from the site at 15-
minute intervals for the number of years specified.
4. The 15-minute time series of rainfall and runoff are accumulated into daily values by calendar
day (midnight to midnight).
5. Various statistics of the resulting daily rainfall and runoff values are computed.
6. The SWMM input file is modified and run once more to compute the runoff resulting from a set
of 24-hour extreme rainfall events associated with different return periods. The rainfall
magnitudes are derived from your choice of extreme storm scenario and year or from the
historical record if climate change is not being considered.
Thus, for the continuous multi-year run, the rainfall / runoff output post-processed by the calculator are
the 24-hour totals for each calendar day of the period simulated. A number of different statistical
measures are derived from these data, some of which will be more relevant than others depending on
the context in which the calculator is being used.
Summary Results
The calculator's Summary Results report, an example of which is shown in Figure 19, contains the
following items:
• A pie chart showing the quantity of total rainfall that infiltrates, evaporates, and becomes runoff.
Note that because the calculator does not explicitly account for the loss of soil moisture to
vegetative transpiration, the latter quantity shows up as infiltration in this chart.
• Average Annual Rainfall: Total rainfall (in inches) that falls on the site divided by the number of
years simulated. It includes all precipitation amounts recorded by the station assigned to the site,
even those that fall below the Event Threshold.
• Average Annual Runoff: Total runoff (in inches) produced by the site divided by the number of
years simulated. It includes all runoff amounts, even those that fall below the Event Threshold.
• Days per Year with Rainfall: The number of days with measurable rainfall divided by the number
of years simulated (i.e., the average number of days per year with rainfall above the Event
Threshold).
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Summary Results
Evaporation
Statistic
Current Scenario
Average Annual Rainfall (inches)
44.99
Average Annual Runoff (inches)
22,42
Days per Year with Rainfall
68.11
Days per Year with Runoff
47.17
Percent of Wet Days Retained
30.74
Smallest Rainfall w/ Runoff (inches)
0.11
Largest Rainfall w/o Runoff (inches)
0.31
Max Rainfall Retained (inches) 1.54
Figure 19. An example of the calculator's Summary Results report.
• Days per Year with Runoff: The number of days with measurable runoff divided by the number of
years simulated (i.e., the average number of days per year with runoff above the Event
Threshold).
• Percent of Wet Days Retained: The percentage of days with measurable rainfall that do not have
any measurable runoff generated. It is computed by first counting the number of days that have
rainfall above the Event Threshold but runoff below it. This number is then divided by the total
number of rainfall days above the threshold and multiplied by 100.
• Smallest Rainfall w/Runoff: The smallest daily rainfall that produces measurable runoff. All days
with rainfall less than this amount have runoff below the threshold.
• Largest Rainfall w/o Runoff: The largest daily rainfall that produces no runoff. All days with more
rainfall than this will have measurable runoff. Of the wet days that lie between this depth and the
smallest rainfall with runoff, some will have runoff and others will not.
Current Scenario
Annual Rainfall: 44.99 in.
Runoff
Infiltration
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• Max Rainfall Retained: The largest daily rainfall amount (volume) retained on site over the period
of record. This includes days that produce runoff from storms that are only partly captured.
Note if the Ignore Consecutive Wet Days option is in effect, then the retention statistics listed above are
computed by ignoring any subsequent back-to-back wet days for a period of 48 hours following an initial
wet day.
Direct interception of rainfall and transpiration by the tree canopy may be important processes
depending on the site you are modeling. While the SWC (Stormwater Calculator) does not
explicitly include these processes, the model i-Tree Hydro can be used to determine the effect of
trees on urban hydrology for stormwater management at the catchment scale (USFS, 2014). For
more information about i-Tree Hydro visit: http://www.itreetools.org/hydro/index.php .
Rainfall / Runoff Events
The calculator's Rainfall/Runoff report contains a scatterplot of the daily runoff depth associated with
each daily rainfall event over the period of record analyzed. Only days with rainfall above the event
threshold (Figure 20) are plotted. Events that are completely captured on site (i.e., have runoff below
the event threshold) show up as points that lie along the horizontal axis. There is not always a consistent
relationship between rainfall and runoff. Days with similar rainfall amounts can produce different
amounts of runoff depending on how that rainfall was distributed over the day and on how much rain
occurred in prior days. The user may hover the cursor over a data point to view the daily runoff value
and daily runoff values.
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O 2.5
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Rainfall / Runoff Events
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Rainfall / Runoff Exceedance Frequency
Rainfall | Runoff A Rainfall Baseline Runoff Baseline
Depth (inches)
Figure 21. The calculator's Rainfall / Runoff Frequency report.
The rainfall frequency curve is generated by simply ordering the measurable daily rainfall results from
the long-term simulation from lowest to highest and then counting how many days have rainfall higher
than a given value. The same procedure is used to generate the daily runoff frequency curve. Curves like
these are useful in comparing the complete range of rainfall / runoff results between different
development, control, and climate change scenarios. Examples might include determining how close a
post-development condition comes to meeting pre-development hydrology or seeing what effect future
changes in precipitation due to climate change might have on LID control effectiveness.
M N
On any of the calculator's line or bar charts you can make the numerical value of a plotted point
appear in a popup label by moving the mouse over the point on the line or bar you wish to
examine. You can also zoom in on any area of the chart by pressing the left mouse button while
dragging the mouse pointer across the area. To return to full view, you would right-click on the
chart and select Un-Zoom from the pop-up menu that appears.
Rainfall Retention Frequency
Another type of report generated by the calculator is the Rainfall Retention Frequency plot as shown in
Figure 22. It graphs the frequency with which a given depth of rainfall will be retained on site for the
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scenario being simulated. For a given daily rainfall depth X, the corresponding percent of time it is
retained represents both the fraction of storms less than X that are completely captured plus the
fraction of storms greater than X where at least X inches are captured.. A rainfall event is considered to
be completely captured if its corresponding runoff is below the user stipulated Event Threshold.
To make this concept clearer, consider a run of the calculator that resulted in 1,000 days of measurable
rainfall and associated runoff for a site. Suppose there were 300 days with rainfall below one inch that
had no measurable runoff and 100 days where it rained more than one inch but the runoff was less than
one inch. The retention frequency for a one-inch rainfall would then be (300 + 100) / 1,000 or 40
percent.
The Rainfall Retention Frequency report is useful for determining how reliably a site can meet a required
stormwater retention standard. Looking at Figure 21, any retention standard above one inch would only
be met about 32% of the time (i.e., only one in three wet days would meet the target). Note that any
rainfall events below the target depth that are completely captured are counted as having attained the
target (e.g., a day with only 0.3 inches of rainfall will be counted towards meeting a retention target of
1.0 inches if no runoff is produced). That is why the plot tails off to the right at a constant level of 31
percent, which happens to be the percent of all wet days fully retained for this example (refer to the
Percent of Wet Days Retained entry in the Summary Results report of Figure 18).
Rainfall Retention Frequency
0 Current Scenario ~ Baseline Scenario
0-
•-
0 0.5 1.0 1.5 2.0
Daily Rainfall (inches)
Figure 22. The calculator's Rainfall Retention Frequency report.
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Runoff by Rainfall Percentile
The Runoff by Rainfall Percentile report produced by the calculator is displayed in Figure 23. It shows
what percentage of total measurable runoff can be attributed to different size rainfall events. The x-axis
is divided into intervals of daily rainfall event percentiles. The x-axis also shows the rainfall depth
corresponding to each interval percentile's threshold. The bars indicate what percentage of total
measurable runoff is generated by the rainfall within each depth interval. This graph provides a
convenient way of determining what rainfall depth corresponds to a given percentile (an example of
percentiles and their corresponding depths at a site are listed along the bottom of the horizontal axis).
Runoff Contribution by Rainfall Percentile
I Current Scenario
I Baseline Scenario
10%
0.13
20%
0.19
30%
025
40%
0.33
50%
0.42
60%
0.53
70%
0.71
75%
084
80%
1.00
85%
1.17
90%
1.44
95%
1 86
Daily Rainfall Percentile / Daily Rainfall Depth (inches)
Figure 23. The calculator's Runoff by Rainfall Percentile report.
41
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' \
The n-th percentile storm is the daily rainfall amount that occurs at least n percent of the time
(i.e., n percent of all rainfall days will have rainfall amounts less than or equal to the percentile
value). It is found by first ordering all days with rainfall above the Event Threshold from smallest
to highest value. The n-th percentile is the n-th percent highest value (e.g., if there were 1000
days with observable rainfall the 85-th percentile would be 85-th value in the sorted listing of
rainfall amounts).
, y
As an example of how to interpret this plot, look at the bar in Figure 23 associated with the 90th to 95th
percentile storm interval (daily rainfalls between 1.44 and 1.86 inches). Storms of this magnitude make
up 16% of the total runoff (at this particular site and its land cover). Note that by definition the number
of events within this 5th percentile interval is 5% of the total number of daily rainfall events. The runoff
contribution for 10 to 70% shows the incremental change in runoff for 10% increases in rainfall: 75 to
90% shows the incremental change in runoff due to by 5% increases in rainfall.
Extreme Event Rainfall/Runoff
The Extreme Event Rainfall/Runoff report shows the rainfall and resulting runoff for a series of extreme
event (high intensity) storms and their probability of occurrence at different return periods. An example
is shown in Figure 22. Each stacked bar displays the daily rainfall depth associated with a given return
period and the runoff that results from it for the current set of site conditions. The rainfall depths
correspond to those shown on the Climate Change page for the climate change scenario you selected
(or to the historical value if no climate change option was chosen).
Note that the rainfall depths at different return periods are a different statistic than the daily rainfall
percentiles that are shown in the Runoff by Rainfall Percentile report (Figure 21). The latter represents
the frequency with which any daily rainfall amount is exceeded while the former estimates how often
the largest daily rainfall may be exceeded (hence its designation as an extreme storm event). Most
stormwater retention standards are stated with respect to rainfall percentiles while extreme event
rainfalls are commonly used to define design storms that are used to size stormwater control measures.
The extreme event rainfall amounts are generated using a statistical extrapolation technique (as
described in the Computational Methods section) that allows one to estimate the once in 5-, 10-, 15-,
30-, 50-, or 100- year event (or return period) when fewer than 5, 10, 15, 30, 50, or 100 years of
observed rainfall data are available.
42
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Extreme Event Rainfall / Runoff
Extreme Event Rainfall / Runoff Depth
5 10 15 30 50 100
Return Period (years)
Extreme Event Peak Rainfall / Runoff
5 10 15 30 50 100
Figure 24. The calculator's Extreme Event Rainfall / Runoff report.
Cost Summary
The final report produced by the calculator shows estimates of probable LID construction and annual
maintenance costs. Tables and charts in the results tab, show construction and annual maintenance
costs applied to the site. All the cost estimates produced after February of the current year are adjusted
to be current for the previous year. For instance, running the calculator after February 2018 produces
cost estimates in 2017 dollars. Site complexity and suitability variables that affect costs and the cost
43
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regionalization option selected by the user are also shown below. Table 2 is an example of the tabular
output option of capital costs. All costs are presented as a range (low and high values). For more details
on how the LID cost numbers were derived, please see Bernagros et al., 2021. Note that if a baseline
scenario is provided, the calculator shows the differences in costs between the baseline scenario and
the current scenario. Figure 25 shows a graphical output option of the average capital costs. Similarly,
Table 3 shows a tabular output option of a range of annual maintenance costs, whereas Figure 26 shows
a graphical output option of the average annual maintenance costs. Note that the annual maintenance
costs are estimates of current average annual maintenance and are not based on an assumed life span
or lifecycle for the LID controls. In other words, the annual maintenance costs shown do not represent
annualized present value estimates of the cost of maintenance over the life of the LID control. Other
tools such as the Water Research Foundation (WRF) BMP and LID Whole List Cost Models may be useful
for estimating lifecycle costs. The numbers shown in the tables and charts represent the results using
the example described in Section 5.
44
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Table 2. Tabular representation of the calculator's estimate of capital costs.
Cost Summary
Estimate of Probable Capital Costs (estimates In 2020 US.$)
Maintenance Costs | Graphical View
Drainage Has Pre- Baseline
Area % Treatment? Current Scenario (C) Scenario (B) Difference (C - B)
Cost By LID
Control Type
Current 1
Baseline
Current /
Baseline
Low
High
Low
High
Low
High
Disconnection
0/0
No / No
$0.00
$0.00
$0.00
$0.00
$0
$0
Rainwater
Harvesting
10/0
No / No
$10,560.45
$12,376.94
$0.00
$0.00
$10,560.45
$12,376.94
Rain Gardens
15/0
No / NA
$14,017.37
$18,563 11
$0.00
$0.00
$14,017.37
$18,563.11
Green Roofs
0/0
No/No
$0.00
$0.00
$0.00
$0.00
$0
$0
Street Planters
20/0
No / No
$27,749.77
$38,541.61
$0.00
$0.00
$27,749.77
$38,541.61
Infiltration
Basins
4/0
No / NA
$13,568.15
$18,373.10
$0.00
$0.00
$13,568.15
$18,373.1
Permeable
Pavement
0/0
No / NA
$0.00
$0.00
$0.00
$0.00
$0
$0
Total
49/0
Varies
$65,895.74
$87,854.75
$0.00
$0.00
$65,895.74
$87,854.75
Note: site complexity variables that affect cost shown below:
Baseline
Current Scenario Scenario
Chart Key
D - Disconnection
IB -
Infiltration Basins
Dev. Type
Re-Development NA
RH - Rain Harvesting
PP-
Permeable Pavement
Site
Suitability
Poor
NA
RG - Rain Gardens
Topography
Mod. Steep {10% NA
GR - Green Roofs
oiujjc;
SP - Street Planters
Soil Type
B
NA
Cost Region Atlanta(60 miles) NA
0.92
45
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Cost Summary
Estimate of Probable Capital Costs (estimates in 2020 US.S)
Maintenance Costs | Tabular View
Current Scenario Baseline Scenario
40000 ,
35000
30000
25000
Cfl
S
©
~
-------
Table 3. Tabular output option of the calculator's estimate of annual maintenance costs.
Cost Summary
Estimate of Annual Probable Maintenance Costs
Capital Costs | Graphical View
Drainage Has Pre- Current Scenario Baseline
Area % Treatment? (C) Scenario (B) Difference (C - B)
Cost By LID
Control Type
Current /
Baseline
Current 1
Baseline
Low
High
Low
High
Low
High
Disconnection
0/0
No / No
$0.00
$0.00
$0.00
$0.00
$0
$0
Rainwater
Harvesting
10/0
No / No
$449.93
$1,079.75
$0.00
$0.00
$449.93
$1,079.75
Rain Gardens
15/0
No / NA
$56.77
$1,372.67
$0.00
$0.00
$56.77
$1,372.67
Green Roofs
0/0
No / No
$0.00
$0.00
$0.00
$0.00
$0
$0
Street Planters
20/0
No / No
$60.56
$1,439.56
$0.00
$0.00
$60.56
$1,439.56
Infiltration Basins
4/0
No / NA
$10.92
$396.75
$0.00
$0.00
$10.92
$396.75
Permeable
Pavement
0/0
No / NA
$0.00
$0.00
$0.00
$0.00
$0
$0
Total
49/0
Varies
$578.19
$4,288.73
$0.00
$0.00
$578.19
$4,288.73
Note: site complexity variables that affect cost shown below:
Current Scenario
Baseline
Scenario
Chart Key
D - Disconnection
IB-
Infiltration Basins
Dev. Type
Re-Development
NA
RH - Rain Harvesting
PP-
Permeable Pavement
Site
Suitability
Poor
NA
RG - Rain Gardens
Topography
Mod. Steep (10%
Slope)
NA
GR - Green Roofs
SP - Street Planters
Soil Type
B
NA
Cost Region
Atlanta(60 miles)
0.92
NA
47
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Cost Summary
Estimate of Annual Probable Maintenance Costs
Capital Costs | Tabular View
Current Scenario Baseline Scenario
1600
1400
1200
1000
(0
I—
JO
"o
Q
(D 800
"D
o
fxi
©
CM
600
400
200
0 I ^
D RH RG GR SP IB PR
LID Controls
Figure 26. Graphical output option of the calculator's estimate of average annual maintenance costs.
Printing Output Results
As mentioned previously, all of the information displayed in the reports on the Results icon of the
calculator can be written to a PDF file to provide a permanent record of the analysis made for a site. You
simply select the Print Results to PDF File command in the center of the page under Actions and then
enter a name and storage location for the file to which the results will be written.
48
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4. Applying LID Controls
LID controls are landscaping practices designed to capture and retain stormwater generated from
impervious surfaces that would otherwise run off the site. The SWC allows you to apply a mix of seven
different types of LID practices to a site. These are displayed in Table 4 along with brief descriptions of
each. This particular set of Gl practices was chosen because they can all be sized on the basis of just
area. Two other commonly used controls, vegetative swales and infiltration trenches, are not included
because their sizing depends on their actual location and length within the site, information which is
beyond the scope of the calculator.
Each LID practice is assigned a set of default design and sizing parameters, so to apply a particular
practice to a site, you only must specify what percentage of the site's impervious area will be treated by
the practice (Figure 13). You can, however, modify the default settings by clicking on the name of the
particular practice you wish to edit. For example, Figure 27 displays the resulting LID Design dialog
window that appears when the Street Planter LID is selected. All the LID controls have similar LID Design
dialogs that contain a sketch and brief description of the LID control along with a set of edit boxes for its
design parameters. The Learn More ... link will open your web browser to a page that provides more
detailed information about the LID practice.
Table 3 lists the various parameters that can be edited with the LID Design dialogs along with their
default factory setting. Arguably the most important of these is the Capture Ratio parameter. This
determines the size of the control relative to the impervious area it treats. Note that because the
calculator does not require that the actual area of the site be specified, all sub-areas are stated on a
percentage basis. So, total impervious area is some percentage of the total site area, the area treated by
a particular LID control is some percentage of the total impervious area, and the area of the LID control
is some percentage of the area it treats.
Pressing the Size for Design Storm button on an LID Design form will make the calculator automatically
size the LID control to capture the Design Storm Depth that was entered on the LID Control page (Figure
13). This computes a Capture Ratio (area of LID relative to area being treated) for Rain Gardens, Street
Planters, Infiltration Basins, and Permeable Pavement by taking the ratio of the design storm depth to
the depth of available storage in the LID unit. For Infiltration Basins it also determines the depth that will
completely drain the basin within 48 hours. For Rainwater Harvesting it calculates how many cisterns of
the user-supplied size will be needed to capture the design storm. Automatic sizing is not available for
Disconnection, because no storage volume is used with this practice, and for Green Roofs, because the
ratio is 100% by definition. The methods used to automatically size the LID controls are described in the
Computational Methods section of this user's guide. Note that even when sized in this fashion, an LID
control might not fully capture the design storm because it may not have drained completely prior to
the start of the storm or the rainfall intensity during some portion of the storm event may overwhelm its
infiltration capacity. The calculator is able to capture such behavior because it continuously simulates
the full range of past precipitation events.
49
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Table 4. Descriptions of LID practices included in the calculator.
LID Practice
Description
Disconnection
Disconnection refers to the practice of directing runoff from impervious
areas, such as roofs or parking lots, onto pervious areas, such as lawns
or vegetative strips, instead of directly into storm drains.
Rain Harvesting
Rain harvesting systems collect runoff from rooftops and convey it to a
cistern tank where it can be used for non-potable water uses and on-
site infiltration.
Rain Gardens
Rain Gardens are shallow depressions filled with an engineered soil mix
that supports vegetative growth. They provide opportunity to store and
infiltrate captured runoff and retain water for plant uptake. They are
commonly used on individual home lots to capture roof runoff.
Green Roofs
Green roofs (also known as vegetated roofs) are bioretention systems
placed on roof surfaces that capture and temporarily store rainwater in
a soil medium. They consist of a layered system of roofing designed to
support plant growth and retain water for plant uptake while
preventing ponding on the roof surface.
Street Planters
Street Planters are typically placed along sidewalks or parking areas.
They consist of concrete boxes filled with an engineered soil that
supports vegetative growth. Beneath the soil is a gravel bed that
provides additional storage as the captured runoff infiltrates into the
existing soil below.
Infiltration Basins
Infiltration basins are shallow depressions filled with grass or other
natural vegetation that capture runoff from adjoining areas and allow it
to infiltrate into the soil.
M//mV\\\\;
Permeable Pavement
Permeable Pavement systems are excavated areas filled with gravel and
paved over with a porous concrete or asphalt mix or with modular
porous blocks. Normally all rainfall will immediately pass through the
pavement into the gravel storage layer below it where it can infiltrate at
natural rates into the site's native soil
50
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Street Planters
Street Planters consist of concrete boxes filled with an engineered soil that supports vegetative growth. Beneath the soil is a gravel bed that
provides additional storage.
The walls of a planter extend 3 to 12 inches above the soil bed to allow for ponding withing the unit. The thickness of the soil growing
medium ranges from 6 to 24 inches while gravel beds are 6 to 18 inches in depth.
The planter's Capture Ratio is the ratio of its area to the impervious area whose runoff it captures.
Learn More (Oregon State University Extension Service LID Fact Sheet Stonmwater Planters)
Ponding Height:
6
in.
Soil Media
n 18
in.
Thickness:
Soil Media
Conductivity:
10
in./hr
Gravel Bed
Thickness:
12
in.
% Capture Ratio:
6
%
Size for Design Storm Save and Return I Restore Defaults
Figure 27. Example of an LID Design dialog for a street planter.
There are some additional points to keep in mind when applying LID controls to a site:
1. The area devoted to Disconnection, Rain Gardens, and Infiltration Basins is assumed to come
from the site's collective amount of pervious land cover whereas the area occupied by Green
Roofs, Street Planters, and Permeable Pavement comes from the site's store of impervious area.
2. Underdrains (slotted pipes placed in the gravel beds of Street Planter and Permeable Pavement
areas to prevent the unit from flooding) are not provided for. However, because underdrains
are typically oversized and placed at the top of the unit's gravel bed, the effect on the amount of
excess runoff flow bypassed by the unit is the same whether it flows out of the underdrain or
simply runs off of a flooded surface.
3. The amount of void space in the soil, gravel, and pavement used in the LID controls are listed in
Table 6. They typically have a narrow range of acceptable values and results are not terribly
sensitive to variations within this range.
51
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Table 5. Editable LID parameters.
LID Type
Parameter
Default Value
Disconnection
Capture Ratio
100%
Rain Harvesting
Cistern Size
100 gallons
Cistern Emptying Rate
50 gallons/day
Number of Cisterns
4 per 1,000 square feet
Rain Gardens
Capture Ratio
5%
Ponding Depth
6 inches
Soil Media Thickness
12 inches
Soil Media Conductivity
10 inches/hour
Green Roofs
Soil Media Thickness
4 inches
Soil Media Conductivity
10 inches/hour
Street Planters
Capture Ratio
6%
Ponding Depth
6 inches
Soil Media Thickness
18 inches
Soil Media Conductivity
10 inches/hour
Gravel Bed Thickness
12 inches
Infiltration Basins
Capture Ratio
5%
Basin Depth
6 inches
Permeable Pavement
Capture Ratio
100%
Pavement Thickness
4 inches
Gravel Bed Thickness
18 inches
Table 6. Void space values of LID media.
Property
LID Controls
Default Value
Soil Media Porosity
Rain Gardens, Green Roofs and Street Planters
45%
Gravel Bed Void Ratio
Street Planters and Permeable Pavement
75%
Pavement Void Ratio
Permeable Pavement
12%
52
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5. Example Application
An example will now be presented to show how the calculator can be used to analyze small site
hydrology. The site shown earlier in Figure 3 will be used as our study area, although, because the
calculator is national in scope, we could have chosen any other location, as well. It is a 2.64-acre
environmental research facility. Baseline data for the site were obtained as described above (Figure 4-
Figure 9. These identified the site's hydrologic soil group as B, its hydraulic conductivity as 0.11
inches/hour, its topography as moderately steep, and its closest rain gage as having an annual rainfall of
46.86 inches. We will simulate three different development scenarios (pre-development, post-
development, and post-development with LID controls) to show how one can both derive and evaluate
compliance with different stormwater retention standards. After that we will see the effect a future
climate change scenario might have on the site's ability to comply with the standard, such as the 99th
percentile rainfall event. Note that this example uses a 20-year simulation.
Pre-Development Conditions
Pre-development hydrology is often cited as an ideal stormwater management goal to attain because it
maintains a sustainable and ecologically balanced condition within a watershed. It is also commonly
used to define specific stormwater retention standards, as will be discussed below. To simulate a pre-
development condition for our study area, we must identify the land cover that characterizes the site in
its natural pre-developed state. In this example, if you pan the site's map display to the left, you will
observe an adjacent natural area that suggests a pre-development land cover of 80 percent Forest and
20 percent Meadow. These values are entered on the Land Cover page of the calculator.
53
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For the next page of the calculator no LID Controls are selected because we are analyzing a pre-
development scenario. On the final page of the calculator, we select to analyze the latest 20 years of
rainfall data and to not ignore back-to-back storm events.
Running the calculator for these conditions produces the Summary Results report listed in Table 7. It
shows that there is an average of 68 days per year with rainfall, but only 7 of these produce measurable
runoff. Of the 45 inches of rainfall per year, 89 percent is retained on site. The Runoff by Rainfall
Percentile plot for this run, shown in Figure 28, indicates that it is mainly storms above 1 inch that
produce almost all the runoff.
Retention standards are developed by state and municipal governments and tailored to meet
stormwater control objectives unique to their jurisdiction. They stipulate the amount of rainfall
that must be "retained" on site and are used to determine the proper size of stormwater
controls. Standards are usually formulated in one of several ways including restoration of pre-
development conditions, rainfall depth retained, or percentile rainfall depth retained. A
summary of state post construction stormwater standards is available at:
https://www.epa.gov/sites/production/files/2016-08/documents/swstdsummary 7-13-
16 508.pdf (EPA 2016). Contact your local government to learn more about the retention
standards that apply in your area.
54
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Table 7. Summary results for pre-development conditions on the example site.
Summary Results
Current Scenario
Annual Rainfall: 44.99 in.
Statistic Current Scenario
Average Annual Rainfall (inches)
44.99
Average Annual Runoff (inches)
4.05
Days per Year with Rainfall
68.11
Days per Year with Runoff
6.95
Percent of Wet Days Retained
89.80
Smallest Rainfall w/ Runoff (inches)
0.17
Largest Rainfall w/o Runoff (inches)
2.24
Max Rainfall Retained (inches)
3.26
55
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Runoff Contribution by Rainfall Percentile
Current Scenario Baseline Scenario
60 |
50
40
o
c
ZD
QL
To
t 30
°
c
8
o!
20
10 »
0—j — — ™ — — ¦ ®®®®
10% 20% 30% 40% 50% 60% 70% 75% 80% 85% 90% 95% 99%
0.13 0.19 0.25 0.33 0.42 0.53 0.71 0.84 1.00 1.17 1.44 1.86 3.21
Daily Rainfall Percentile / Daily Rainfall Depth (inches)
Figure 28. Runoff from different size storms for pre-development conditions on the example site.
Now consider a stormwater retention standard that requires a site to capture all rainfall produced from
storms up to and including the 99th percentile daily rainfall event or the rainfall that would be retained
on the site in its natural pre-developed state, whichever is smaller. To identify the depth of runoff that
must be retained under this standard, we first need to know what the 99th percentile rainfall depth is.
This can be found from the Runoff by Rainfall Percentile plot in Figure 28. The 99th percentile storm
corresponds to 3.21 inches. To determine the rainfall retained on the undeveloped site, we can examine
the calculator's Rainfall Retention Frequency report for this run shown in Figure 29. Because the
standard attaches 99 % reliability to its target rainfall, we assume that the same would hold for its
retention target. From Figure 29, we see that a retention target of 0.7 inches could be met 99 % of the
time (i.e., of the 68 days per year on average with measurable precipitation, for 67 of those the site will
retain either the entire rainfall or the first 0.7 inches, whichever is smaller). Because this is less than the
3.21 inch, 99th percentile rainfall, the standard for this site would be to retain 0.7 inches.
56
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Rainfall Retention Frequency
Current Scenario Q Baseline Scenario
90
80
70
60
£ 50
O
| 40
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Table 8. Land cover for the example site in developed state.
Land Cover
% of Total Area
% of Impervious Area
Forest
18
-
Meadow
8
-
Lawn
25
-
Total Impervious Surfaces
49
100
Roofs
10
20
Parking
9
20
Roads & Sidewalks
30
60
We next return to the Results page and re-run the analysis. Table 9 contains the resulting comparison of
summary runoff statistics between the two conditions. Note how the developed site with no runoff
controls comes nowhere close to matching pre-development hydrology. Instead of only seven days per
year with measurable runoff, there are 47 and the total volume of runoff has increased more than
fivefold. As seen in the Rainfall Retention Frequency plot (Figure 30), the 0.7-inch retention target
identified earlier can only be met about 38% of the time (those days when a low amount of rainfall is
entirely contained on site).
Table 9. Comparison of runoff statistics for post-development (Current) and pre-development
(Baseline) conditions.
Summary Results
Current Scenario
Baseline Scenario
Annual Rainfall: 44.99 in.
Annual Rainfall: 44.99 in.
Runoff Infiltration
Runoff Infiltration
Evaporation
Evaporation
gtk
IF
Statistic
Current Scenario
w
Baseline Scenario
Average Annual Rainfall (inches)
44.99
44.99
Average Annual Runoff (inches)
2242
4.05
Days per Year with Rainfall
68.11
68.11
Days per Year with Runoff
47.17
6.95
Percent of Wet Days Retained
30.74
89.80
Smallest Rainfall w/ Runoff (inches)
0.11
0.17
Largest Rainfall w/o Runoff (inches)
0.31
2.24
Max Rainfall Retained (inches) 1.54 3.26
58
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100
90
80
70
"O
-------
ER^ National Stormwater Calculator
OPEN RESOURCES CONTACT
Figure 31. Low Impact Development controls applied to the example site.
60
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Rain Harvesting
Rain harvesting systems collect runoff from rooftops and convey it to a cistern tank where it can t>e used for non-potable water uses and on-
site infiltration.
The harvesting system is assumed to consist of a given number of fixed-sized cisterns per 1000 square feet of rooftop area captured.
The water from each cistern is withdrawn at a constant rate and is assumed to be consumed or infiltrated entirely on-site.
Learn More (The Cabell Brand Center)
Cistern Size:
100
Gal.
Emptying Rate:
50
Gal./Day
Number per 1,000
21
/1.000 sq. ft.
sq. n.:
| Size for Design Storm |
Save Return
1 Restore Defaults 1
a
Rain Gardens are shallow depressions filled with an engineered soil mix that supports vegetative growth. They are usually used on
individual home lots to capture roof runoff.
Typical soil depths range from 6 to 18 inches
The Capture Ratio is the ratio of the rain garden's area to the impervious area that drains onto it.
Learn More (Minnesota Stormwater Design Manual)
Ponding Height: 6
Soil Media
Thickness:
Soil Media
Conductivity:
% Capture Ratio:
Q Pre-Treatment
10 inJhr
Size for Design Storm
Save and Return I Restore Defaults
Figure 32. Design parameters for Rain Harvesting and Rain Garden controls.
61
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Infiltration Basins
0
Infiltration basins are shallow depressions filled with grass or other natural vegetation that capture runoff from adjoining areas and allow it to
infiltrate into the soil
The calculator assumes that the infiltration rate from the basin is the same as for site's native soil.
The basin's Capture Ratio is the area of the basin relative to the impervious area whose runoff it captures.
Learn More (California Stormwater Quality Association Infiltration Basin Fact Sheet)
Basin Depth: 6 in.
% Capture Radio: a 78 %
D Pre-Tfeatment
Size for Design Storm
Permeable Pavement
UNCOMPACTED
SUBGRADE IS
CRITICAL FOR PROPER
INFILTRATION
POROUS ASPHALT PAVEMENT
- \:i, ' UNIFORMLY GRADED
; . STONE AGGREGATE
& ^ V 49% VOID SPACE
* J FOR STORMWATER STORAGE
< ( 'i " AND RECHARGE
<•>
Continuous Permeable Pavement systems are excavated areas filled with gravel and paved over with a porous concrete or asphalt mix.
Modular Block systems are similar except that permeable block pavers are used instead.
Normally all rainfall will immediately pass through the pavement into the gravel storage layer below it where it can infiltrate at natural rates
into the site's native soil.
Pavement layers are usually 4 to 6 inches in height while the gravel storage layer is typically 6 to 18 inches high.
The Capture Ratio is the percent of the treated area (street or parking lot) that is replaced with permeable pavement.
Learn More (City of Rockville MD Permeable Pavement Design Guide)
Pavement 6 in.
Thickness:
Gravel Layer 18 in.
Thickness:
% Capture Ratio: a 56 %
D Pre-Treatment
Size for Design Storm
Save and Return I Restore Defaults
Figure 33. Design parameters for the Infiltration Basin and Permeable Pavement controls.
62
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Re-running the calculator for the developed site with LID controls produces the summary results shown
in Table 10. The site now comes very close to matching the pre-development hydrology. It has only five
more days per year, on average, with runoff than does the pre-developed site and only 1.26 more inches
of annual runoff. Figure 34 shows that the runoff frequency of the controlled site is quite close to the
pre-developed site. Figure 35 shows an almost identical contribution of different size storms to runoff
between the two. Finally, in Figure 36 we see that with this extensive use of LID controls the site could
meet the 0.7-inch retention standard at the required 99% level of confidence.
Table 10. Runoff statistics for pre-development (Baseline) and post-development with LID controls
(Current) scenarios.
Summary Results
Current Scenario
Baseline Scenario
Annual Rainfall: 44.99 in.
Annual Rainfall: 44.99 in.
Runoff Infiltration
Runoff Infiltration
Evaporation
Evaporation
j
Statistic
Current Scenario
Baseline Scenario
Average Annual Rainfall (inches)
44.99
44.99
Average Annual Runoff (inches)
5.31
4.05
Days per Year with Rainfall
68.46
68.11
Days per Year with Runoff
11.74
6.95
Percent of Wet Days Retained
82.85
8980
Smallest Rainfall w/ Runoff (inches)
0.17
0.17
Largest Rainfall w/o Runoff (inches)
1.29
2.24
Max Rainfall Retained (inches) 3.72 3.26
63
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Rainfall / Runoff Exceedance Frequency
^ Rainfall ~ Runoff A Rainfall Baseline ^ Runoff Baseline
3 4
Depth (inches)
Figure 34. Daily runoff frequency curves for pre-development (Baseline) and post-development with
LID controls (Current) conditions.
64
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Runoff Contribution by Rainfall Percentile
60
50
40
!fc
O
c
13
a:
£ 30
o
c
SB
0
1
Q.
20
10
Current Scenario Baseline Scenario
.kl
10% 20% 30% 40% 50% 60% 70% 75% 80% 85% 90% 95% 99%
0.13 0.18 0.25 0.33 0.42 0.53 0.71 0.84 0.99 1.16 1.43 1.86 3.21
Daily Rainfall Percentile I Daily Rainfall Depth (inches)
Figure 35. Contribution to total runoff by different magnitude storms for pre-development (Baseline)
and post-development with LID controls (Current) conditions.
65
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Rainfall Retention Frequency
Current Scenario | Baseline Scenario
.cooxj_clxu_ ^
i
i
o
i
i
i
o
o
i
i
9
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
i
0 0.5 1.0 1 5 2.0 2.5 3.0 3.5
Daily Rainfall (inches)
Figure 36. Retention frequency plots under pre-development (Baseline) and post-development with
LID controls (Current) conditions.
Cost Summary
In addition to runoff results, the calculator also computes capital and maintenance cost estimates. The
capital costs computed for the pre-development condition (as Baseline) and the post-development with
LID controls (Current) conditions are shown in Table 11 and Figure 37; maintenance results are shown in
Table 12 and Figure 38. For more details on how the LID cost numbers were derived, please see
Bernagros et al., 2021.
66
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Table 11. Tabular output option of the calculator's estimate of capital costs.
Cost Summary
Estimate of Probable Capital Costs (estimates in 2020 US.$)
Maintenance Costs I Graphical View
Has Pre- Baseline Scenario
Drainage Area % Treatment? Current Scenario (C) (B) Difference (C - B)
Cost By LID Control
Type
Current 1
Baseline
Current / Baseline
Low
High
Low
High
Low
High
Disconnection
0/0
No /No
$0.00
$0.00
$0.00
$0.00
SO.OO
$0.00
Rainwater Harvesting
10/0
No / No
$37,413.35
$45,321.07
SO. 00
$0.00
537,413.35
$45,321.07
Rain Gardens
20/0
Yes 1 No
$48,015.62
$64,238.11
SO. 00
$0.00
S48.015.62
$64,238.11
Green Roots
0/0
No/No
$0.00
$000
SO. 00
$0.00
SO.OO
$0.00
Street Planters
0/0
No/No
$0.00
$0.00
SO. 00
$0.00
SO.OO
$0.00
Infiltration Basins
25/0
Yes / No
$94,801.24
$131,050.97
SO. 00
$0.00
594,801.24
$131,050.97
Permeable Pavement
40/0
Yes I No
$201,342.64
$241,402.30
SO. 00
$0.00
5201,342.64
$241,402.30
Total
951 0
Varies
$381,572.86
$482,012.45
S0.00
$0.00
S381,572.86
$482,012.45
Note: site complexity variables that affect cost shown below:
Current Scenario
Baseline Scenario
Chart Key
Dev. Type
Re-Development
Re-Development
D - Disconnection
IB - Infiltration Basins
Site Suitability
Poor
Poor
RH-
Rain Harvesting
PP - Permeable Pavement
Topography
Mod. Steep (10% Slope)
Mod. Steep (10% Slope)
RG-
• Rain Gardens
Soil Type
B
B
GR-
• Green Roofs
Cost Region
Atlanta(60 miles) 0.92
Atlanta(60 miles) 0.92
SP-
Street Planters
67
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Cost Summary
Estimate of Probable Capital Costs (estimates in 2020 US.$)
Maintenance Costs | Tabular View
Current Scenario Baseline Scenario
250000
200000
150000
100000
50000
a
Figure 37. Graphical output option of the calculator's estimate of capital costs.
RH
RG
GR
LID Controls
SP
IB
PP
68
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Table 12. Tabular output option of the calculator's estimate of maintenance costs.
Cost Summary
Estimate of Annual Probable Maintenance Costs
Capital Costs | Graphical View
Drainage Area % Has Pre-Treatment? Current Scenario (C) Baseline Scenario (B) Difference (C - B)
Cost By LID Control Type
Current / Baseline Current / Baseline
Low
High
Low
High
Low
High
Disconnection
0/0
No / No
S0.00
$0.00
$0.00
50.00
$0.00
SO.OO
Rainwater Harvesting
10/0
No/No
52,362.14
$5,668.67
50.00
SO.OO
$2,362.14
55,668.67
Rain Gardens
20/0
Yes / No
S514.75
$12,445.56
50.00
SO.OO
$514.75
512,445.56
Green Roofs
0/0
No/No
S0.00
$0.00
50.00
SO.OO
$0.00
SO.OO
Street Planters
0/0
NA/NA
S0.00
$0.00
50.00
SO.OO
$0.00
SO.OO
Infiltration Basins
25/0
Yes / No
51,065.00
$38,683.29
$0.00
SO.OO
$1,065.00
538,683.29
Permeable Pavement
40/0
Yes / No
51,414.30
$7,724.65
50.00
SO.OO
$1,414.30
57,724.65
Total
95/0
Varies
55,356.19
$64,522.16
SO.OO
SO.OO
$5,356.19
S64,522.16
Note: site complexity variables that affect cost shown below:
Current Scenario Baseline Scenario
Chart Key
Dev. Type Re-Development
Re-Development
D - Disconnection
IB - Infiltration Basins
Site Suitability Poor
Poor
RH -1
Rain Harvesting
PP - Permeable Pavement
Topography Mod. Steep (10% Slope) Mod. Steep {10% Slope) RG - Rain Gardens
Soil Type B B GR - Green Roofs
Cost Region Atlanta(60 miles) 0.92 Atlanta{60 miles) 0.92 SP - Street Planters
69
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Cost Summary
Estimate of Annual Probable Maintenance Costs
Canital Costs | Tabular View
Current Scenario Baseline Scenario
40000
35000
30000
25000
U)
CO
~o
co 20000
D
o
CN
O
OJ
15000
10000
5000
0
Figure 38.
Climate Change Impacts
As a final step in our analysis of the example site we will calculate what effect a future change in local
climate might have on the ability of the LID practices we installed to control runoff. Figure 39 displays
the graphs from the Climate Change page for our example site, showing how different scenarios
projected to the year 2060 affect monthly rainfall levels and extreme storm events. To provide the
largest climate change impact we will select the "Warm/Wet" and "Stormy" scenarios for this example.
Because we want to compare the effect that a future "Warm/Wet" rainfall pattern has on the developed
site with LID controls to the previous run that used the historical rainfall record, we return to the Results
page and remove the previous Baseline Scenario (the one for the pre-developed site) and replace it with
the most current set of results—the one for the developed site with LID controls analyzed for the
historical rainfall record. We then re-run the analysis, using our same set of LID designs but now subject
to changes in the rainfall record that reflect a "Warm/Wet" and "Stormy" future climate condition.
*-}
D RH RG GR SP IB PP
LID Controls
Graphical output option of the calculator's estimate of maintenance costs.
70
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National Stormwater Calculator
9
f
fi
o
&
M
Climate Change
Directions v
Select a future climate change scenario to apply:
@ No Change (Historical)
Q Hot/Dry
Q Central
Q Warm/Wet
Select an extreme storm scenario to apply:
@ No Change (Historical)
Q Stormy
Q Less Stormy
Select the time period to which the climate
change scenario applies:
(§) Near Term (2035)
Q Far Term (2060)
Helpful Resources >
U.S. EPA Climate Resilience Evaluation and Awareness Tool (CREAT)
World Climate Research Programme Coupled Model Intercomparison Project
U.S. Global Change Research Program
U.S. EPA Climate Change Indicators
U.S. Global Change Research Program Fourth National Climate Assessment
NOAA State Climate Summaries
NEW SAVE OPEN RESOURCES CONTACT
Percentage Change in Monthly Rainfall for Near Term
Projections
1 4<>
2 i
® 2
Hot/Dry Central A Warm/Wet
O A
A O ^ A
OO O
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From the Rainfall / Runoff Frequency plot of Figure 40 we see that the distribution of daily rainfall
events between the two climate scenarios is quite similar for the smaller size storms but that storms
above 3 inches will occur more frequently for the future "Warm/Wet" scenario, (e.g., the historical
return period for daily rainfalls exceeding 4 inches is 5 years but is predicted to change to a 2-year
return period in the future.) Regarding the retention target of 0.7 inches, the Rainfall Retention
Frequency plot of Figure 41 shows that under the future "Warm/Wet" scenario there is no change the
probability of meeting the target.
Table 13. Summary results under a "Warm/Wet" (Current) climate change scenario compared to the
historical (Baseline) condition.
Summary Results
Current Scenario Baseline Scenario
Annual Rainfall: 50.07 in. Annual Rainfall: 44.99 in.
Runoff Infiltration
Runoff
Infiltration
Evaporation
4
Evaporation
fib
IP
Statistic
\
Current Scenario
w
Baseline Scenario
Average Annual Rainfall (inches)
50.07
44.99
Average Annual Runoff (inches)
6.44
5.31
Days per Year with Rainfall
69.91
68.46
Days per Year with Runoff
14.14
11.74
Percent of Wet Days Retained
79.77
82.85
Smallest Rainfall w/ Runoff (inches)
0.21
0.17
Largest Rainfall w/o Runoff (inches)
1.29
1.29
Max Rainfall Retained (inches) 3.72 3.72
72
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Rainfall / Runoff Exceedance Frequency
) Rainfall | Runoff A. Rainfall Baseline ^ Runoff Baseline
Depth (inches)
Figure 40. Daily rainfall and runoff frequencies for the historical (Baseline) and "Warm/Wet" climate
scenarios.
73
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Rainfall Retention Frequency
Q Current Scenario Q Baseline Scenario
Daily Rainfall (inches)
Figure 41. Target event retention for the historical (Baseline) and "Warm/Wet" climate scenarios.
Finally, we can examine how the site performs when faced with extreme, high intensity rainfall events
that are expected to occur only once every five or more years. Figure 42 shows the Extreme Event
Rainfall / Runoff report for the developed site subjected to the two climate scenarios. We observe that
there is significant increase in estimated rainfall amounts for all return periods under the "Warm/Wet"
scenario as compared to the baseline historical scenario. For example, the 100-year storm event is
projected to increase from 9.25 inches to 11.51 inches. These amounts simply mirror the numbers
displayed on the Climate Change page of the calculator for this site (Figure 39). None of these extreme
event storms can be completely captured by the LID controls deployed on the site. But this is to be
expected because the LID controls were only designed to capture up to 0.7 inches of rainfall. The
74
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increase in the amount of bypassed rainfall under the future "Warm/Wet" scenario compared to the
historical record appears to be proportional to the difference in the amount of rainfall between the two.
20
18
16
? 14
•5 12
£ 10
# 8
Extreme Event Rainfall / Runoff
Extreme Event Rainfall / Runoff Depth
| Rainfall Runoff Rainfall Baseline
¦ Runoff Baseline
¦hfcllfc
ill
10 15 30
Return Period (years)
Extreme Event Peak Rainfall / Runoff
50
100
Rainfall
Runoff Rainfall Baseline
Runoff Baseline
18
16
14
I 12
- 10
t 8
llllll
hi I
10 15 30 50
Return Period (years)
100
Figure 42. Extreme event rainfall and runoff for the "Warm/Wet" climate change scenario and the
historical record (Baseline).
75
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6. Computational Methods
The National Stormwater Calculator uses SWMM 5 (EPA, 2010) as its computational engine. SWMM is a
comprehensive model that addresses surface runoff, infiltration, groundwater, snow melt, stormwater
detention, and full dynamic wave flow routing within any configuration of open and closed channels.
Only its runoff, infiltration, and LID sub-models are used by the calculator. This section describes how
SWMM carries out its hydrology calculations, how the calculator sets up a SWMM model for the site
being analyzed, how it populates the parameter values needed to run the model, and how it post-
processes the results produced by SWMM.
SWMM's Runoff Model
SWMM allows a study area to be subdivided into any number of irregularly shaped sub-catchment areas
to best capture the effect that spatial variability in topography, drainage pathways, land cover, and soil
characteristics have on runoff generation. An idealized sub-catchment is conceptualized as a rectangular
surface that has a uniform slope and drains to a single outlet point or channel or to another sub-
catchment. Each sub-catchment can be further divided into three sub-areas: an impervious area with
depression (detention) storage, an impervious area without depression storage, and a pervious area
with depression storage. Only the latter area allows for rainfall losses due to infiltration into the soil.
SWMM uses a nonlinear reservoir model to estimate surface runoff produced by rainfall over each sub-
area of a sub-catchment (Chen and Shubinski, 1971). From conservation of mass, the net change in
depth per unit of time of water stored on the land surface is simply the difference between inflow and
outflow rates over the sub-catchment:
where d = depth of water on the land surface, i= rate of rainfall + any runoff from upstream sub-
catchments, e = evaporation rate, /= soil infiltration rate, q= runoff rate and t= time. Note that the
fluxes i, e, f, and ^are expressed as flow rates per unit area. By assuming that the overland flow across
the sub-area's width is normal, the Manning equation can be used to express the runoff rate ^as:
where W= width of the sub-catchment's outflow face, S = sub-catchment slope, n = roughness
coefficient, A = sub-catchment area and ds = depression storage depth. The latter represents initial
rainfall abstractions such as surface ponding, interception by vegetation, and surface wetting. Note that
no runoff occurs when dis below ds. A more detailed discussion of this formulation can be found in
Chapter 3.2 of (EPA, 2015). How the calculator sets values for the parameters in this equation is
discussed later on in this section.
dd . _
— = i — e — f — q
dt / f
(1)
(2)
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Substituting equation (2) into (1) produces an ordinary non-linear differential equation that can be
solved numerically fort/over a sequence of discrete time steps given externally imposed rainfall and
evaporation rates and a computed infiltration rate f. By knowing d, (2) can be evaluated to determine
the runoff qat each time step.
SWMM 5 offers a choice of three different methods for computing soil infiltration rates - the Horton,
Green-Ampt and Curve Number models. The Green-Ampt method was chosen for use in the calculator
because it is based on physical parameters that can be related to the site's soil type. SWMM uses the
well-known Mein-Larson form of this model (Mein and Larson, 1973):
/ = K,(1+2=M2i«) (3)
where Ks= saturated hydraulic conductivity,
-------
The surface layer receives both direct rainfall and run-on from other areas. It loses water through
infiltration into the soil layer below it, by evaporation of any water stored in depression storage and
vegetative capture, and by any surface runoff that might occur. The soil layer contains an amended soil
mix that can support vegetative growth. It receives infiltration from the surface layer and loses water
through evaporation and by percolation into the storage layer below it. The storage layer consists of
coarse crushed stone or gravel. It receives percolation from the soil zone above it and loses water by
either infiltration into the underlying natural soil or by outflow through a perforated pipe under drain
system.
The hydrologic performance of this LID unit can be modeled by solving the mass balance equations that
express the change in water volume in each layer over time as the difference between the inflow water
flux rate and the outflow flux rate. The equations for the surface layer, soil layer, and storage layer can
be written as
respectively, where di = depth of ponded surface water, 62 = soil layer moisture content, ds= depth of
water in the storage layer, i= rainfall rate, qo= upstream run-on rate, qi = surface runoff flow rate, qs =
underdrain outflow rate, ei= surface evaporation rate, ez = soil zone evaporation rate, fi = surface
infiltration rate, £2= soil percolation rate, /?= native soil infiltration rate, L,2= depth of the soil layer, and
(f>3 = porosity of the storage layer.
The flux terms (q, e, and f) in these equations are functions of the current water content in the various
layers (di, 62, and dj) and specific site and soil characteristics. The surface and native infiltration rates
are determined using the Green-Ampt model. The soil percolation rate decreases exponentially from Ks
with decreasing soil moisture: /2 = Ksexp (—p(02 — ^2)) where p is a percolation constant
typically in the range of 5 to 15. Under drain outflow rate is modeled as a power function of head of
water above the drain outlet: q3 = — d^ where a and 6 are constants and ddis the offset
distance of the drain from the bottom of the unit.
This set of equations can be solved numerically at each runoff time step to determine how an inflow
hydrograph to the LID unit is converted into some combination of runoff hydrograph, sub-surface
storage, sub-surface drainage, and infiltration into the surrounding native soil. In addition to Street
Planters and Green Roofs, the bio-retention model just described can be used to represent Rain Gardens
by eliminating the storage layer and also Permeable Pavement systems by replacing the soil layer with a
pavement layer.
UUl . r
— =i + q0-e1-f1-q1
J dQ'l £ £
L2~ST-fl~e2~f2
03 = f2~f3~Q3
(4)
(5)
(6)
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Site Model without LID Controls
To analyze a site's hydrology without any LID controls, the calculator creates a single SWMM sub-
catchment object and populates it with the following parameter values:
Site Area:
A nominal area of 10 acres is used. As mentioned earlier, because all results are expressed per unit of
area, there is no need to use an actual site area.
Width:
This is the width of the outflow face of a conceptual rectangular plane over which runoff flows. In most
SWMM models, it is initially set to the site area divided by the length of the overland flow path that
runoff follows, and is then refined by calibration against measured runoff hydrographs.
When assigning an overland flow path length, particularly for sites with natural land cover, one must
recognize that there is a maximum distance over which true sheet flow prevails. Beyond this, runoff
consolidates into rivulet flow with much faster travel times and less opportunity for infiltration.
There is no general agreement on what distance should be used as a maximum overland flow path
length. The NRCS recommends a maximum length of 100 ft (USDA, 2010b), whereas Denver's Urban
Drainage and Flood Control District uses a maximum of 500 ft. (UDFCD, 2007). For the calculator, a
conservative value of 150 ft. is used. The resulting width parameter for the SWMM input file is therefore
set to the nominal area (10 acres) divided by this length.
Slope:
A value of 2% is used for flat slopes, 5% for moderately flat slopes, 10% for moderately steep slopes, and
20% for steep slopes. These values are derived from the SSURGO dataset (USDA, NRCS, 2019)
Percent Impervious:
SWMM only considers two types of land surfaces - impervious and pervious - each with its own
depression storage depth and surface roughness parameters. It does not explicitly consider the different
types of land covers that comprise these two categories and how their characteristics affect depression
storage and roughness. Impervious surfaces, such as roads, roofs, sidewalks, and parking lots show
minor variation in these parameters; therefore, they are treated as a single category.
To provide more refinement in characterizing pervious areas, the calculator allows the user to specify
the percentage of the site's area devoted to four different sub-categories of land surface cover: Forest,
Meadow, Lawn, and Desert. These sub-categories were chosen from a distillation of categories used in
the Western Washington Hydrology Model (Clear Creek Solutions, Inc., 2006) and the National Green
Values Calculator (Center for Neighborhood Technology, 2009). The remaining area is assigned as
Impervious Cover.
79
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Depression Storage Depth:
Depression storage corresponds to a depth that must be filled prior to the occurrence of any runoff. It
represents initial abstractions such as surface ponding, interception by flat roofs and vegetation, and
surface wetting. Separate values are supplied for the pervious and impervious areas of a catchment.
Depression storage for impervious surfaces is relatively small, ranging from 0.05 to 0.1 inches (ASCE,
1992). For the remaining pervious area, the calculator uses an area-weighted average of the storages
associated with each type of pervious land surface that covers the site. Table 14 contains depression
storage depths that have been suggested by different organizations for each land cover category. The
last column contains the value used in the calculator.
Table 14. Depression storage depths (inches) for different land covers.
Land Cover
ASCE(1992)
UDFCD (2006)
USDA (2010)a
Calculator
Forest
0.3
0.53
0.40
Meadow
0.2
0.4
0.56
0.30
Lawn
0.1-0.2
0.35
0.50
0.20
Desert
0.27
0.25
Impervious
0.05-0.1
0.05-0.1
0.04
0.05
a Set equal to the initial abstraction computed for the land cover's Curve Number and a Group D
soil (to minimize any contribution from infiltration).
Roughness Coefficient:
The roughness coefficient reflects the amount of resistance that overland flow encounters as it runs off
of the land surface (EPA, 2015). SWMM uses separate values for the impervious and pervious areas of a
catchment. Table 15 lists roughness coefficients published by several different sources for each land
cover category, along with those selected for use in the calculator. The value presented to SWMM, as
representative of the site's pervious area, is the area-weighted average of the roughness for each land
cover category.
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Table 15. Roughness coefficients for different land covers.
Land Cover
SWMa
Engmanb
Yen0
Calculator
Forest
0.4
0.06-0.12
0.40
Meadow
0.01-0.32
0.04-0.18
0.20
Lawn
0.2-0.35
0.3-0.63
0.03-0.12
0.30
Desert
0.032-0.045
0.04
Impervious
0.01-0.014
0.01-0.013
0.01-0.025
0.01
a Stanford Watershed Model (Crawford and Linsley, 1966)
b Engman (1986)
c Yen (2001)
Percent of Impervious Area without Depression Storage:
This parameter accounts for immediate runoff that occurs at the beginning of rainfall before depression
storage is satisfied, caused by impervious areas immediately adjacent to storm drains. The calculator
assumes a value of 0 to give a maximum credit to the small amount of depression storage used for
impervious surfaces.
Infiltration Parameters:
There are three parameters required by the Green-Ampt infiltration model used in the calculator:
1. Saturated Hydraulic Conductivity (Ksat) - the rate at which water will infiltrate through a
completely saturated soil.
2. Suction Head (y) - capillary tension (force at which water is held within soil pores) at the
infiltration wetting front.
3. Initial Moisture Deficit (IMD) - the difference in moisture content between a completely wet
and completely dry (or drained) soil (i.e., the difference between the soil's porosity and its field
capacity)
Values for these parameters can be assigned based on soil group. Using the NRCS's definitions (USDA,
2010a), an A soil is mostly sand, a B soil is typical of a sandy loam, a Csoil is like a clay loam, and a D soil
is mostly clay. Table 16 lists the average values of Ksat, y, and IMD for these four soil types from
measurements made from roughly 5,000 soils (of all types) across the U.S. which are used in the
calculator (Rawls et al., 1983). Note that the calculator Ksat values are defaults. The user can also use
values extracted from the SSURGO data base or enter their own site-specific numbers.
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Table 16. Infiltration parameters for different soil types.
Soil Type
Rawls et al.
Ksat (in./hr.)
Y(in.)
IMD
Sand
4.6
1.95
0.38
Sandy Loam
0.43
4.33
0.26
Clay Loam
0.04
8.22
0.15
Clay
0.01
12.45
0.10
Site Model with LID Controls
The basic SWMM model used by the calculator is extended when LID controls are applied to the site.
These extensions depend on the type of LID that is deployed.
Disconnection
A second sub-catchment is added to the model when Disconnection is employed. Its impervious area
equals the fraction of the site's total impervious area that is disconnected, while its pervious area equals
the Capture Ratio times the latter area. Both of these areas are assigned the same parameters as the
original sub-catchment, and the original sub-catchment has its areas reduced to reflect the presence of
this second sub-catchment. SWMM's option to internally route runoff from the impervious sub-area on
to the pervious sub-area is used with this sub-catchment.
Infiltration Basin
An Infiltration Basin also adds an additional sub-catchment to the model that contains the impervious
area treated by the basin plus a pervious area equal to the area of the basin. The impervious and
pervious areas of the original sub-catchment are reduced accordingly. The impervious area in the new
sub-catchment has the same parameter values as in the original sub-catchment. However, the pervious
area has its depression storage set equal to the Basin Depth as specified by the calculator user. Its
roughness coefficient is set to 0 which forces SWMM to treat any ponded water in excess of the Basin
Depth as immediate runoff. All runoff from the impervious sub-area is internally routed on to the
pervious (i.e., infiltration basin) sub-area. This setup is similar to that used for Disconnection, except
instead of allowing for sheet flow with infiltration across a pervious area it utilizes this area as an
infiltrating storage unit with overflow.
Rain Harvesting
This LID option is modeled by introducing an additional, completely impervious sub-catchment whose
area is the portion of the original sub-catchment impervious area that is captured by cisterns. This
amount of impervious area is subtracted from that of the original sub-catchment. A new Storage Node
element is added into the SWMM model to represent the combined retention volume of the cisterns.
The added sub-catchment sends its runoff to this storage node. The maximum depth of the storage
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node is set to a nominal height of 48 inches (EPA, 2016). Its surface area equals the area of its
contributing sub-catchment times the number of cisterns per unit area (as supplied by the user) times
the area per cistern. The latter is found by dividing the user-supplied volume per cistern by the nominal
depth. Note that any nominal depth can be used because the area per cistern will adjust itself
accordingly to maintain an equal amount of total cistern storage volume. The rate at which the cisterns
empty is converted into an equivalent "infiltration" rate for the storage node, equal to the user-supplied
emptying rate (in gallons/day) divided by the area per cistern. When the cisterns become full, any
overflow shows up as node flooding in SWMM, which gets added to the runoff from other portions of
the site.
Other LID Controls
Rain Gardens, Green Roofs, Street Planters, and Permeable Pavement do not require additional sub-
catchments - they are all placed within the original sub-catchment used to model the site. The original
pervious area of this sub-catchment is reduced by the amount of area devoted to Rain Gardens, while
the original impervious area is reduced by the area taken up by any Green Roofs, Street Planters and
Permeable Pavement.
LID Sizing
When the user supplies a design storm depth, the LID controls can be automatically sized to retain this
depth. For Rain Harvesting, the number of cisterns required per unit area is simply the design storm
depth divided by the volume of a cistern. For the other controls, the Capture Ratio (CR), which is the
ratio of the LID control area to the impervious area being treated, is computed as
„ „ D storm
CR = : (7)
Dlid-(Dstorm-0.5Ksat)
where Dstorm is the design storm depth (inches over 24 hours), Dlidis the storage depth (inches)
provided by the LID control, and Ksatis the saturated hydraulic conductivity of the native soil
underneath the LID control (inches/day). The 0.5 factor accounts for the average amount of infiltration
occurring over the duration of the design storm. The LID storage depth Dlid consists of any ponding
depth, plus the depths of any soil and gravel layers, times their respective void fractions.
Precipitation Data
The SWMM model built by the calculator includes a single Rain Gage object that provides it with hourly
precipitation data. These data come from a nearby rain gage as selected by the user. Specifically,
stations from the Integrated Surface Database (ISD) and the Cooperative Observer Program (COOP)
Hourly Precipitation Data (HPD). Version 2 with at least 10 years of data were used. Stations were
included in the calculator if at least ten years of data was available. Previously, the calculator relied on
precipitation data in EPA's Better Assessment Science Integrating point and Nonpoint Sources (BASINS)
system^When ISD or COOP-HPD version 2 stations were co-located with a station in EPA's BASINS
system and were continuous temporally with the BASINS station, data from BASINS after the year 1990
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was combined with new data. ISD stations can be identified as having a station ID that consists
exclusively of numbers. Precipitation data for ISD was included only if it had a quality code of 5,
indicating it passed all quality control checks. COOP-HPD version 2 stations can be identified as having a
station ID that typically starts with 'US'. The measurement and quality flags were checked.
Missing data was filled using gridded datasets in this priority order: the NLDAS grid cell corresponding to
the precipitation station, the GLDAS grid cell corresponding to the precipitation station, or the nearest
GLDAS grid cell with available data. Data for each gage are contained in their own file; all files are
available to the calculator. The national coverage provided by these gages is shown in Figure 44
Figure 44. Rain gage locations included in the calculator. Alaska, Hawaii, Puerto Rico, and the U.S.
Virgin Islands are not shown.
In addition to simulating a long-term record of hourly rainfall, the calculator also computes the runoff
produced from a series of 24-hour rainfall events that represent extreme, high intensity storms with
different annual return periods. How the depths of these storms are estimated for each rain gage is
discussed in the Climate Change sub-section. To simulate each storm, the calculator uses NRCS 24-hour
distributions to disaggregate the event's total rainfall depth into a series of rainfall intensities (measured
in inches per hour) at six-minute intervals. NRCS has produced updated rainfall distributions derived
from NOAA Atlas 14 (Merkel et al., 2017) for some regions; where available, the calculator uses those
rainfall distributions. Otherwise, the calculator uses the legacy NRCS Soil Conservation Service (SCS)
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rainfall distributions (USDA, 1986). Figure 45 shows the different NRCS distributions and Figure 46 shows
which distribution applies to each region of the US.
Each precipitation station is pre-assigned a distribution type based on the region it falls in. After the
long-term simulation is completed, the SWMM input file is modified as follows:
1. A time series object is added to the model which is the result of applying the appropriate rainfall
distribution at a six-minute interval to the total 24-hour rainfall amount being simulated.
2. The source of rainfall data for the model is set to the newly added time series.
3. The duration of the simulation is changed to three days starting on June 1.
4. After running the model, the output recorded is the total runoff from the even and the event's
peak rainfall and runoff.
These steps are repeated for each return period extreme event analyzed.
Time (hours)
Time (hours)
Time (hours)
Figure 45. NRCS 24-hour rainfall distributions (Merkel et ai., 2017, USDA, 1986).
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Figure 46. Rainfall distributions used in the SWC (Merkel et al., 2017, USDA, 1986). Alaska and Hawaii
(not shown) are Type SCSJ.
Temperature Data
Evaporation is modeled using SWMM's Hargreaves method (EPA, 2015), which uses the daily minimum
and maximum temperatures and the study area's latitude. The equation for calculating the evaporation
rate E is:
1
E = 0.0023 T~z(Ta + 17.8) (8)
where Ra is the water equivalent of incoming extraterrestrial radiation, A is the latent heat of
vaporization, Tr is the average daily temperature range for a period of days, and Ta is the average daily
temperature for a period of days. SWMM uses a 7-day running average of the daily temperature range
and daily temperature.
The daily minimum and maximum air temperatures were found at all locations where precipitation data
was available. Where possible, PRISM was used as the daily temperature source. When not available,
GLDAS data was used. If GLDAS data was not available, the closest grid cell with available GLDAS data
was used.) Temperature values were obtained for each rain gage location displayed in Figure 44.
Each station is identified by its latitude and longitude. Temperature data are stored in a file that can be
downloaded by the user. Each line of the file has the format station ID, year, month, day, maximum
temperature, and minimum temperature in degrees Fahrenheit.
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Climate Change Effects
The calculator obtains its climate change scenarios and their effect on local precipitation and
temperature directly from another EPA's CREAT 3.1 (Climate Resilience Evaluation and Analysis Tool)
(EPA, 2021). CREAT is a decision support tool to assist drinking water and wastewater utility owners in
understanding, evaluating, and addressing climate change risks. It contains a database of climate change
effects across the US localized to a grid of 0.5 degrees in latitude and longitude (about 30 by 30 miles).
These effects include changes in monthly average precipitation, monthly average temperature, and
extreme event 24-hour rainfall amounts for each of three different climate change scenarios in two
different future time periods.
CREAT 3.1 uses statistically downscaled Global Change Model (GCM) projections from the World Climate
Research Programme (WCRP) Coupled Model Intercomparison Project Phase 5 (CMIP5) archive (Taylor
et al., 2012) as the source of its climate change data. The CMIP5 archive was chosen by CREAT because:
• it contains runs from more than 50 models using several emission scenarios (Taylor et al., 2012);
• it supported model-based analyses presented in the IPCC Fifth Assessment Report (IPCC, 2014);
• it facilitates the comparison and diagnosis of model outputs by standardizing many of the
assumptions and boundary conditions used;
• it is downscaled to appropriate spatial (regional, watershed) and temporal (monthly) scales
using a proven downscaling technique;
• it contains well-documented model output that is widely available to researchers;
CREAT 3.1 uses data from model simulations using the Representative Concentration Pathway 8.5 (van
Vuuren et al., 2011; Riahi et al., 2007). This scenario is characterized by a higher trajectory of
greenhouse gas emissions and does not include any specific climate mitigation target. CREAT 3.1 uses an
ensemble approach to downscale from a subset of the CMIP5 model runs using SimCLIM software
(CLIMsystems, Ltd. 2011; Warrick, 2009).
Each of the 38 models used in CREAT 3.1 produces a different set of results for each future year within
each downscaled Vz degree grid cell. To represent this type of uncertainty inherent in predicting future
climate conditions, CREAT 3.1 defined three scenarios that use an ensemble-informed approach to
incorporate the range of results produced by the models for any given projection year. The
"Warm/Wet" scenario uses the average of five models that are closest to the 5th percentile of annual
temperature change and 95th percentile of annual rainfall change. The "Central" scenario selected the
average of five models that were closest to the median (50th percentile) temperature and rainfall
changes. The "Hot/Dry" scenario used the average of five models that were closest to the 95th percentile
temperature change and 5th percentile rainfall change. For all three scenarios, two representative
projection years were selected: 2035 (based on projection data for 2025-2045) and 2060 (based on
projection data for 2050-2070).
An illustration of how the scenarios were selected using an ensemble-informed approach is shown in
Figure 47. In this figure, the square symbols are results from the different climate model runs and the
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circles include the five models closest to the targets that were averaged to generate the three target
scenarios (blue = "Warm/Wet", gray = "Central", and peach = "Hot/Dry". Note that the selection of
which GCM models are incorporated into the ensemble for each scenario can change depending on grid
cell and projection year.
Figure 4. Illustration of Ensemble-informed Selection of Model Projections to Define Potential Future Conditions
Figure 47. CREAT 3.1 illustration of ensemble-informed selection using CMIP5 projected changes in
temperature and precipitation for 2060 (EPA, 2021).
Once the models to use for each scenario in each projection year in each grid cell was identified, CREAT
3.1 extracted its CMIP5 results to produce a database of percent changes in monthly average
precipitation and absolute changes in monthly average temperature for each scenario in each of the two
projection years in each grid cell across the U.S. For precipitation impacts, the National Stormwater
Calculator used these data to construct a table for each combination of climate scenario and projection
year (six in total) containing the change in monthly (January - December) average precipitation for each
of its 2,667 rain gages. When the calculator runs SWMM to evaluate the long-term rainfall / runoff for a
site under a particular climate change scenario, it first creates a new hourly rainfall file from the original.
In this new file each historical hourly rainfall is adjusted by the percent change (up or down) for the gage
and month of the year contained in the appropriate climate change scenario table.
Similarly, the monthly changes in degrees of temperature were extracted from CREAT 3.1 to produce a
set of tables for each of the six combinations of climate scenario and projection year. When the
calculator runs SWMM, it models the change in temperature by applying an adjustment to each monthly
temperature value from the climate file.
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The third climate-influenced outcome the calculator considers is the change in the size and frequency of
intense precipitation events. CREAT 3.1 considered this effect of climate change using an ensemble-
based approach. A subset of previously used GCMs provide spatially explicit scalars (via ClimSystems) for
changes in precipitation per degree of warming for storm events. The scalars for the 5-year return
interval were ranked. Models producing scalars corresponding to lower values were ensemble-averaged
to produce a "Less Stormy" future scenario, while models producing higher scalars were ensemble-
averaged to produce the "Stormy" future scenario. New Generalized Extreme Value (GEV) probability
distributions were generated using the ensemble-averaged scalars for all five events ("Historic", and for
two future years, "Stormy" and "Less Stormy").
The historical GEV values were generated in CREAT 3.1 by fitting a Generalized Extreme Value (GEV)
probability distribution to the collection of annual maximum 24-hour (midnight to midnight) rainfall
amounts over a 30- year (1981-2010) period simulated by the CMIP5 GCM used for each scenario. Under
the cumulative GEV distribution, the annual maximum daily rainfall amount x is:
-1
F(x; p, a, 0 = exp {- [l + f (^)] f } (9)
where ^uis a location parameter, cris a scale parameter, and £ is a shape parameter.
CREAT 3.1 estimated GEV parameters for both the historical record and all six of the future climate
scenarios for each rain gage location in the calculator's database. From these parameters, values of the
annual maximum 24-hour rainfall depths for return periods of 5-, 10-, 15-, 30-, 50-, and 100- years were
calculated using Eq. 9 and were placed in a set of seven tables, one for the historical record and six for
the future climate change scenarios (three different model outcomes in each of two future years). Each
set of extreme event storms corresponding to the six return periods for either the historical record or
for a future climate change scenario at a given rain gage location was simulated in SWMM using the
procedure described earlier in the Precipitation Data sub-section of this guide.
Cost Estimation
The cost estimation procedure was developed by evaluating the input parameters to the calculator to
determine the type of information and the limits of user inputs supported by the tool that affect costs
(capital and maintenance). Critical and influential unit cost items were evaluated for how they could be
incorporated into costs estimates that accurately reflect changes in design input variables available in
the calculator. For critical cost items in which there was no existing design variable within the calculator,
these items were added as selectable options in the calculator. The following design variables selected
by the user influence itemized costs of the LID controls: footprint ratio (% capture ratio), cistern size,
number of LID controls per 1,000 ft2, soil media thickness, gravel bed thickness, basin depth, and
pavement thickness. For each of the design variables that affect costs, one or more corresponding line
items were included to account for the effect of that design variable. Other line items were added to the
cost estimates that are not directly related to the size of the LID control but are necessary to account for
other activities, design features, and processes necessary for construction such as mobilization.
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Based on user input for select variables (soils, slope, and added variables such as pretreatment and site
suitability), three design scenarios (simple, typical, and complex) are available for selection by the user
for the project scenario the user is evaluating. Using the influential design variables and known
properties of the LID controls, cost curves (simple, typical, and complex) were developed for each of the
7 LID controls included in the calculator, using nationally available unit cost estimates.
The cost estimation approach implemented in the calculator is based on the use of previously developed
cost curves for each of the LID controls supported. The process of creating the cost curves is described in
detail in a report titled "Low Impact Development Stormwater Control Cost Estimation Analysis" (RTI
International and Geosyntec Consultants, 2015). The RTI International and Geosyntec Consultants (2015)
report included a literature review to develop a cost estimation procedure based on the unit cost
information to create curves for varying complexities of LID control implementation. The resulting cost
estimates report a range in costs to demonstrate the potential variability with LID control
implementation to communicate uncertainties in cost estimates.
The literature review (Bernagros et al., 2021) included collection of cost data through web-based
searches to determine and document sources, including peer-reviewed publications, literature that is
widely cited by the stormwater LID community, and online data sources. In addition, existing cost tools
and current or previous Geosyntec projects were used as data sources. Many of the Geosyntec projects
include LID cost information datasets that have been peer-reviewed and/or include cost estimation
procedures and tools that use primary and secondary literature.
A review of literature indicated that stormwater control type, extent of required detail, drainage area
and type of land use, development condition, and design standards all result in wide ranges in cost
information for stormwater controls. Some cost variables affect the cost of all LID controls (e.g., size,
design criteria, and new vs. redevelopment), whereas other cost variables are more specific to an
individual LID control project (e.g., type of permeable pavement, type of cistern, necessity of an
underdrain).
Key project and site-specific variables, including whether the project is being applied as part of a new
development or redevelopment, as well as site characteristics such as slope, soils, and other aspects of
site preparation and design, are often dictated by the site condition. Site condition, in turn, influences
cost. Another key project variable is the size of the LID control, which is dictated by the stormwater
runoff generated by the impervious tributary area. A larger volume of stormwater runoff will generally
require a larger and more costly LID control to treat and/or store the runoff.
Four cost variables were recommended for inclusion in the calculator's cost estimation procedure, due
to the feasibility, resolution, sensitivity, consistency, and measurability of each variable. Cost variables
such as the presence and absence of pretreatment; project type; project scale; site characteristics; and
suitability are all variables that met four or more of the evaluation criteria. Table 17 highlights the cost
variables selected for inclusion in the cost estimation procedure for the calculator.
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Table 17. Cost Variables Selected for Cost Estimation Procedure
(RTI International and Geosyntec Consultants, 2015).
Cost Variable
Significance of Variable
Presence or absence of pretreatment
Plays a large role in cost, availability of cost data,
common design variable
Project type
(e.g., new development, redevelopment,
retrofit)
One of the largest factors influencing cost; typically
known, even at planning stages of project
Project scale/size
Large factor influencing cost
Site characteristics and suitability (e.g.,
slope, required reinforcement for stability)
Plays a large role in cost, greatly affects site design
The following general guidelines were used to develop the simple, typical, and complex cost curves. The
cost curves are believed to bracket expected costs appropriately.
• Simple: Design criteria are generally lower than current design practices and site conditions are
conducive for BMP installation; likely representative of privately constructed and maintained BMPs in
new development, on a suitable parcel of land, sited as part of an effective site design process.
• Typical: Design criteria are consistent with typical design practices (e.g., sizing for capture of 85%
storm event or similar) found in current design manuals, and site conditions represent "median"
conditions for new construction; likely representative of BMPs designed per public maintenance
standards (generally more stringent) and sited as part of an effective site design process in new
development or large redevelopment.
• Complex: Design criteria are stringent and site conditions are difficult or constrained; cost curves
represent higher end estimates for all line items to meet project difficulty, may overpredict costs for
many sites that do not face these difficulties or constraints. Small redevelopment projects and retrofit
projects may tend toward this end of the range.
One of the primary benefits of the cost curve approach to cost estimation is the relative ease of
programming when properly implemented. The approach selected for curve development simplifies cost
estimation conceptually by incorporating the complexities related to the analysis using unit costs and
other critical design variables into curves based simply on LID footprint. The curves themselves can be
reduced to regression equations by plotting trend lines and obtaining equations for the trend lines. Once
regression equations have been developed, it is relatively straightforward to program the equations.
Cost curves were developed for three design scenarios (simple, typical, and complex) for each LID
control by varying the quantities of unit costs and other cost items commensurate with the intricacy of
implementation, LID control design parameters, and site feasibility constraints. Table 18 shows the
regression equations that were developed for the cost estimation procedure using the cost curve
production framework. These regression equations reflect 2014 dollars; an inflation factor is used to
adjust later years.
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Table 18. LID Control Cost Curve Regression Equations
(RTI International and Geosyntec Consultants, 2015).
LID Control
Simple Cost Curve
Typical Cost Curve
Complex Cost Curve
Impervious Area
Disconnect
y = 0.2142x+ 159.75
y = 3.65x+ 1922.8
y = 5.7238x +3806.5
Rainwater
Harvesting
y = 0.3844x + 61.8
y = 0.7697x + 3564
y = 1.4085x + 4350
Rain Garden
y = 0.2717x + 346.08
y = 1.5691x + 3696
y = 4.6378x + 10052
Green Roof
y = 0.5421x+ 1975.2
y = 2.5009x + 3288
y = 7.5401x + 20824
Street Planter
y = 0.5592x+ 1928.2
y = 2.7125x +2580.6
y = 10.357x + 14163
Infiltration Basin
y = 0.8205x + 1928.2
y = 0.8473x + 3864
y = 3.7531x + 13050
Permeable
Pavement
y = 2.3502x + 1545
y = 4.7209x + 1800
y = 7.8694x + 3750
Project complexity, based on site characteristics and user input information determines whether simple,
typical, or complex cost curves (curves developed based on unit cost for items used in construction of
each LID control practice that are volumetric or area based) are used to estimate costs for a user
selected project. The three types of cost curves, represent the complexity of a given project site selected
by the user. Project complexity is computed by assigning binary values to choices for the criteria shown
in the first column of Table 19. Note that these criteria are from various screens of the calculator
including the LID Controls icon page (Table 16). For example, when a user indicates that a project is new
development, a value of 1 is assigned to "new development" in the table and a value of 0 is assigned to
redevelopment because the two criteria are mutually exclusive. This process is followed for all 15
criteria (Table 19). Next, the binary representations of the user's input values in the second column of
the table are multiplied by the categorization strike assignments in columns 3 to 5 of the table and the
results saved in columns 6 to 8 respectively. Finally, the contents of columns 6 to 8 are summed and the
user selected project is assigned a complexity rating for the highest column. In the example shown in the
table, both simple and complex have high scores of 2. When there is a tie the more complex option
wins, therefore the project is considered complex, and the complex cost curve is applied to compute
cost estimates for the project.
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Table 19. Project Complexity Computation Based on User Input.
Categorization Strike
User's
Assignments
Categorization Strike Tally
Adjustment Variables
Values
Simple
Typical
Complex
Simple
Typical
Complex
Is New Development
1
1
0
o
1
0
0
Is Redevelopment
0
0
1
1
0
0
0
Has Pretreatment
0
0
1
1
0
0
0
Site Suitability - Poor
1
0
0
1
0
0
1
Site Suitability - Moderate
0
0
1
0
0
0
0
Site Suitability - Excellent
0
1
0
0
0
0
0
Topography - Flat (2%)
0
1
0
0
0
0
0
Topography - Moderately
Flat (5%)
1
1
1
0
1
1
0
Topography - Moderately
Steep (10%)
0
0
1
1
0
0
0
Topography - Steep (15%)
0
0
0
1
0
0
0
Soil Type - A
0
1
0
0
0
0
0
Soil Type - B
0
0
1
0
0
0
0
Soil Type - C
1
0
0
1
0
0
1
Soil Type - D
0
0
0
1
0
0
0
Count or Total
4
5
6
7
2
1
2
*Note: Compare project categorization strikes to determine if project is low, typical, or high.
The cost curves have been designed to provide a range of costs that bracket potential project costs using
the three project design scenarios (simple, typical, or complex). Once an applicable design scenario has
been selected by the user, a cost range is obtained. This cost range is a necessary approach because it
communicates to the user that there is uncertainty associated with the estimates. A simple design
reports a range with the low curve value as the low end of the range and the typical curve value as the
upper end of the range. A typical design similarly reports the range as the value determined from the
typical curve and complex curve values. The complex curve computes the difference between the
complex and the typical and adds it to the complex value to produce the range representing the
complex design scenario. The range for this scenario, therefore, has the complex curve value as the
lower bound of the range and the difference between complex and typical curve values as the upper
bound of the range. To facilitate the incorporation of the cost estimation procedure into the calculator,
trend lines have been created for each curve and regression equations have been computed based on
the trend lines. Refer to Figure 48 for a conceptual overview of how cost estimate ranges are derived
from the cost curves.
An automated Microsoft Excel spreadsheet with a simple macro was programmed; and then applied to
incrementally input various sizes of LID controls into the unit cost estimation tables in the spreadsheet
to obtain capital and annual maintenance costs that were then plotted as regression curves. Refer to
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Figure 49 for an example of a cost curve for a rain garden. The cost curves are plotted with LID control
footprint surface areas in square feet (cistern as storage capacity in gallons) on the x-axis and total
capital cost on the y-axis.
A brief summary of the steps taken to program and implement the cost estimation steps into the
calculator is provided below:
1. Define calculator user input limits and allowable LID control size variable limits.
2. Define and select design variables for LID controls, including calculator defaults for each
variable, and eliminate variables that do not significantly affect cost estimates.
3. Define and select simple, typical, and complex values for remaining variables that are influential
for costs.
4. Line-item costs developed for variables that significantly affect magnitude of costs.
5. Use of an automated Excel spreadsheet to repeatedly size and estimate costs for all LID controls
under all three design scenarios (simple, typical, and complex) to produce regression cost curves
for each LID control.
The cost estimation procedure programmed into the calculator is based on the use of the regression
cost curves approach described above to produce both capital and annual maintenance costs. To
account for inflation and regional variability in costs, data from BLS have been used to compute regional
cost multipliers for BLS regional centers around the country (U.S. Department of Labor, BLS, 2017).
Many cost estimation techniques employ nationwide, disaggregated data to provide more robust,
tailored regional estimates. Several data sources such as Engineering News Record (ENR) and RS Means
(The Gordian Group) provide the ability to develop regionalized costs (e.g., for select cities). The
selected approach provides reasonable approximations to express national cost values in regional terms
using readily available BLS data. The BLS data set can be obtained online at monthly and annual
intervals, with calculated indices providing annual cost adjustments as well. Due to online accessibility,
the calculator can dynamically obtain BLS data in real-time during calculator program executions, as is
currently done with soil, precipitation, and evapotranspiration data. The end-product of this effort is a
regional cost multiplier that is applied to the calculator cost estimate to provide more current, tailored,
regionally representative cost.
All available data have been analyzed from all of the BLS regional centers where BLS Consumer Price
Index (CPI) data are available. BLS regional centers or areas are broken into four major regions, including
the Northeast, Midwest, South, and West. BLS publishes CPI data for 23 local regions, of which 17 local
regions have been programmed into the calculator based on availability of long-term data (> 20 years)
pertinent to typical consumer expenditures on LID controls. More information on CPI and the regional
centers for which CPI data are maintained is available here.
BLS Producer Price Index (PPI) data categories/variables were assessed for costs that are most likely to
be included in LID controls construction. PPI variables are the outputs of industries such as service,
construction, utilities, and other goods-producing entities, and are only available on a national scale.
Documentation of data collection and quality assurance and quality control procedures for these data
are available from the BLS website at http://www.bls.gov/bls/qualitv.htm. Relevant PPI data include
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items/categories such as concrete storm sewer pipe, asphalt paving mixture, engineering services, and
construction sand and gravel.
When a user specifies their location in the calculator, the calculator computes a regional cost
adjustment factor for the three closest BLS regions. If all three BLS regions are more than 100 miles from
the users' location a National multiplier of 1 is selected as the default. On the LID controls tab the user
has the option of overriding the default selections and either choosing one the three nearest BLS centers
or specifying their own multiplier by choosing Other. The regionalized cost model shown in equation 9,
documents how BLS data for each BLS center is used to calculate a cost index value. Table 20 shows the
regional and national coefficient values for the shovel loader and fuels and utilities BLS data series. A
regional multiplier for each BLS center is calculated by dividing the cost index value of each BLS center
by the national index. A regional multiplier greater than one indicates that regional cost index for that
city is higher than the national average. A regional multiplier less than one indicates that the cost index
in that location is lower than the national average. The BLS centers used in the calculator are shown in
Table 21. The calculator directly accesses the BLS data using the BLS API (application program interface).
Using the BLS Regional Center and the model year from, the calculator queries the BLS API and retrieves
the values for the variables in the regionalization model as shown Table 22. More information about the
BLS API is available at http://www.bls.gov/developers/api_signature_v2.htm.
The final regionalized cost model is shown in equation (10).
Cost lndexyear n = —19.4 + (0.113 * Ready mix concreteyearn)
+(0.325 * Tractor shovel loaderyear n)
+(0.097 * Energyyearn)
+(0.398 * Fuels and utilitiesyear n) (10)
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Table 20. Regionalized Cost Model Coefficients for BLS Center.
BLS Center
Tractor Shovel Loader
Coefficient
Fuels and Utilities
Coefficient
NATIONAL
0.325493
0.398318
Anchorage
0.325493
0.398318
Atlanta
0.304932
0.283199
Boston
0.325493
0.4592194
Chicago
0.396454
0.44202
Dallas
0.264
0.3392
Denver
0.325493
0.398318
Detroit
0.325493
0.398318
Honolulu
0.325493
0.398318
Houston
0.325493
0.398318
Los Angeles
0.325493
0.398318
Miami
0.325493
0.398318
Minneapolis
0.357176
0.421136472
New York
0.4395572
0.4831199
Philadelphia
0.40557176
0.462920184
San Diego
0.325493
0.398318
San Francisco
0.325493
0.398318
Seattle
0.325493
0.398318
The itemized unit costs used in developing the cost curves for all the LID controls were year 2014-unit
costs. To adjust cost estimates for inflation that may have occurred after the curves were first
developed, the calculator applies an inflation adjustment factor computed using National BLS data
derived from CPI and PPI variables for 2014 and comparing it to the value of the same index computed
96
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using CPI and PPI variables for the current year. The inflation factor is calculated by dividing the current
National Index by the 2014 National Index.
In order to validate the model, data for five regional case studies (Dillwyn, VA, Chesterland, OH, Mission,
KS, and two in Portland, OR) were used to compare actual costs with the predicted SWC costs adjusted
by applying the regional cost multiplier. Three of the five cost estimates were within the range
estimated by the calculator. Of the two that were not well-predicted, one was under-predicted by 38%
(Mission, KS), and one was over-predicted by 37% (Portland, OR). There are potentially many causes for
these differences. This analysis did not complete a detailed design assessment to determine what may
have caused these differences for these locations. Although there are many factors that influence the
cost of actual projects, such as those that were highlighted in RTI International and Geosyntec
Consultants (2015), it is expected that the calculator's cost model with regional BLS-based cost indices
will provide a reasonable range of cost estimates for stormwater construction and operation and
maintenance costs.
The intent of these cost data and estimation procedure programmed in the calculator, is to produce
general estimates for relative comparisons of LID control alternatives. It is expected that in most cases,
planning-level estimates are sufficient for users of the calculator to evaluate LID control alternatives
based on relative cost differences of various LID controls as estimated using this procedure.
97
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WJ
o
O
S
o
\CP
<3+^ a ¦" v
y0™ <\e> e\
6*°
vk*-'
$<4€<«*
A^t>
>?>
Complex design range
Typical design range
Simple design range
Area
Figure 48. Conceptual overview showing cost estimate ranges increase with area and complexity
derived from cost curves.
98
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10 100 1,000 10,000 100,000
Surface Area (square feet)
Figure 49. Sample regression cost curve for Rain Gardens.
99
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Table 21. BLS Regional Centers.
BLS Series ID
State
Regional Center Name
2020 Computed Regional Multiplier
Latitude
Longitude
0000
NA
NATIONAL
1.000
0
0
S49G
AK
Anchorage
1.23
61.2181
-149.9003
S35C
GA
Atlanta
0.92
33.749
-84.388
SUA
MA
Boston
1.15
42.3601
-71.0589
S23A
IL
Chicago
1.06
41.8781
-87.6298
S37A
TX
Dallas
0.87
32.7767
-96.797
S48B
CO
Denver
0.98
39.7392
-104.9903
S23B
Ml
Detroit
1.04
42.3314
-83.0458
S49F
HI
Honolulu
1.23
21.3069
-157.8583
S37B
TX
Houston
0.87
29.7604
-95.3698
S49A
CA
Los Angeles
1.22
34.0522
-118.2437
S35B
FL
Miami
0.86
25.7617
-80.1918
S24A
MN
Minneapolis
1.00
44.9778
-93.265
S12A
NY
New York
1.13
40.7128
-74.006
S12B
PA
Philadelphia
1.09
39.9526
-75.1652
S49E
CA
San Diego
1.22
32.7157
-117.1611
S49B
CA
San Francisco
1.41
37.7749
-122.4194
S49D
WA
Seattle
1.11
47.6062
-122.3321
100
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Table 22. National BLS Variables and Model Coefficients.
BLS Variable
Model
Coefficients
Model Year Values (2020)
Anchorage
National
Ready-mix concrete manufacturing
0.113
NA - use
national
290.2
Tractor shovel loaders (skid steer, wheel,
crawler, and integral design backhoes)
0.325
NA - use
national
277.2
Energy
0.096
269.756
196.949
Fuels and utilities
0.398
351.932
243.949
NA - Not Applicable
101
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Post-Processing
For the long-term continuous simulation of rainfall / runoff, the calculator runs its site model through
SWMM using a 5-minute computational time step over each year of the period of record selected by the
user, and requests that SWMM use a 15-minute reporting interval for its results. SWMM writes the
computed rainfall intensity and runoff results at the 15-minute reporting interval to a binary output file.
The calculator then reads this output file and aggregates rainfall and runoff into daily totals, expressed
as inches, for each day of the simulation period. It also keeps track of how many previous days occur
with no measurable rainfall, for each day with measurable rainfall. Measurable rainfall and runoff are
taken as any daily amount above the user-supplied threshold (whose default is 0.1 inches). For days that
have runoff but no rainfall, the runoff is added to that of the previous day. After the aggregation process
is complete, the long-term simulation results have been distilled down into a set of records equal in
number to the number of days with measurable rainfall; where each record contains a daily rainfall,
daily runoff, and number of antecedent dry days.
For extreme 24-hour storm events, SWMM makes a separate run for each event over a three-day time
period to allow for LID storage to drain down. Each run has different values in its time series of rainfall
intensities reflecting the different total depth associated with each extreme event return period. For
these runs the only output recorded is the total runoff from the site.
The Summary Results report produced by the calculator (Figure 14) comes from a direct inspection of
the long-term daily rainfall/runoff record. The Maximum Retention Volume statistic is simply the largest
difference between daily rainfall and its corresponding runoff among all records.
The Rainfall / Runoff Event scatterplot (Figure 15) is generated by plotting daily each daily rainfall and
its associated runoff for those days where rainfall exceeds the user-supplied threshold limit. For wet
days where the runoff is below the threshold value, the runoff value is set to zero (i.e., there is no
measurable runoff for those days).
The Rainfall / Runoff Frequency report (Figure 16) is generated by first sorting daily rainfall values by
size, ignoring consecutive rainfall days if the user selected that option. The days per year for which each
rainfall value is exceeded, is computed as (N-j)/ Y, where N is the total number of rainfall values, / is
the rank order of the rainfall in the sorted list, and Y is the total years simulated. Then each rainfall -
exceedance frequency pair is plotted. The same set of operations is used to generate the runoff
exceedance frequency curve, except now N is the total number of runoff values and j is the rank order of
a runoff value in the sorted list.
The Runoff by Rainfall Percentile report (Figure 18) is generated as follows:
1. The daily measurable rainfall values are sorted by size and a set of different percentile values
are identified (the 10th, 20th, 30th, 40th, 50th, 60th, 70th, 75th, 80th, 85th, 90th, 95th, and
99th percentiles).
2. The days with rainfall that fall within each percentile interval are identified, honoring the user's
choice to either include or exclude consecutive wet days.
102
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3. The total runoff from events in each interval, as a percentage of the total runoff from all events,
is computed and plotted.
The Rainfall Retention Frequency report (Figure 22) is generated by taking the same set of rainfall
percentiles used in the Runoff by Rainfall Percentile report, only referring to them as retention
volumes. For each retention volume, the percentage of daily rainfall events providing that amount of
retention is computed. This is done by examining each day with observable rainfall, ignoring back-to-
back wet days if that option was selected. If there was no measurable runoff for the day, then the count
of retained events for the retention volume being analyzed is incremented. Otherwise, if the rainfall was
at least as much as the target retention and the difference between rainfall and runoff was also at least
this much, then the count of retained events is also incremented. The retention provided for the given
retention target is simply the number of retained events divided by the total number of daily events.
This process is repeated for each of the 13 pre-selected retention volumes and the resulting pairs of
retention volume - retention frequency values are plotted.
The Extreme Event Rainfall / Runoff report (Figure 24) is generated by simply plotting the rainfall and
accompanying computed runoff in stacked fashion for each extreme event return period.
103
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