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EPA/600/R-13/085c | Revised September 2014 | www2.epa.gov/research

National Stormwater Calculator User’s Guide

Before After

Ofﬁce of Research and Development

National Risk Management Research Laboratory

EPA/600/R-13/085c

Revised September 2014

NATIONAL STORMWATER CALCULATOR USER’S GUIDE – VERSION 1.1

By

Lewis A. Rossman

Water Supply and Water Resources Division National Risk Management Research
Laboratory Cincinnati, OH 45268

OFFICE OF RESEARCH AND DEVELOPMENT

U.S. ENVIRONMENTAL PROTECTION AGENCY CINCINNATI, OH 45268

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.

ACKNOWLEDGEMENTS

Paul Duda, Paul Hummel, Jack Kittle, and John Imhoff of Aqua Terra
Consultants developed the data acquisition portions of the National
Stormwater Calculator under Work Assignments 4-38 and 5-38 of EPA Contract
#EP-C-06-029. Jason Berner and Tamara Mittman, both in EPA’s Office of
Water (OW), were the Work Assignment Managers for that effort. They, along
with Alex Foraste (EPA/OW), provided many useful ideas and feedback
throughout the development of the calculator.

ACRONYMS AND ABBREVIATIONS

ASCE = American Society of Civil Engineers

CMIP3 = Coupled Model Intercomparison Project Phase 3 CREAT = Climate
Resilience Evaluation and Awareness Tool EPA = United States Environmental
Protection Agency GCM = General Circulation Model

GEV = Generalized Extreme Value

GI = Green Infrastructure

HSG = Hydrologic Soil Group

IMD = initial moisture deficit

IPCC = Intergovernmental Panel on Climate Change Ksat = saturated hydraulic
conductivity

LID = low impact development

NCDC = National Climatic Data Center

NRCS = Natural Resources Conservation Service NWS = National Weather Service

OW = Office of Water

SWAT = Soil and Water Assessment Tool SWMM = Storm Water Management Model

UDFCD = Urban Drainage and Flood Control District US = United States

USDA = United States Department of Agriculture WCRP = World Climate Research
Programme

Climate Change Impacts 53

Computational Methods 58

SWMM’s Runoff Model 58

SWMM’s LID Model 59

Site Model without LID Controls 61

Site Model with LID Controls 64

Precipitation Data 65

Evaporation Data 68

Climate Change Effects 69

Post-Processing 72

References 74

LIST OF FIGURES

Figure 1. The calculator's main window 10

Figure 2. The calculator’s Location page 12

Figure 3. Bird’s eye map view with a bounding circle 13

Figure 4. The calculator’s Soil Type page 14

Figure 5. The calculator's Soil Drainage page 16

Figure 6. The calculator's Topography page 17

Figure 7. The calculator's Precipitation page 18

Figure 8. The calculator's Evaporation page 19

Figure 9. The calculator's Climate Change page 21

Figure 10. The calculator's Land Cover page 22

Figure 11. The calculator’s LID Controls page 24

Figure 12. The calculator’s Results page 25

Figure 13. The calculator’s Summary Results report 28

Figure 14. The calculator's Rainfall / Runoff Event report 30

Figure 15. The calculator’s Rainfall / Runoff Frequency report 31

Figure 16. The calculator’s Rainfall Retention Frequency report 32

Figure 17. The calculator’s Runoff by Rainfall Percentile report 34

Figure 18. The calculator’s Extreme Event Rainfall / Runoff report 36

Figure 19. Example of a LID Design dialog for a street planter. 39

Figure 20. Runoff from different size storms for pre-development conditions
on the example site. 42

Figure 21. Rainfall retention frequency under pre-development conditions for
the example site. 43

Figure 22. Rainfall retention frequency for pre-development (Baseline) and
post-development (Current) conditions 45

Figure 23. Low Impact Development controls applied to the example site. 47

Figure 24. Design parameters for Rain Harvesting and Rain Garden controls 48

Figure 25. Design parameters for the Infiltration Basin and Porous Pavement
controls 49

Figure 26. Daily runoff frequency curves for pre-development (Baseline) and
post-development with LID controls (Current) conditions 51

Figure 27. Contribution to total runoff by different magnitude storms for
pre-development (Baseline) and post-development with LID controls (Current)
conditions 52

Figure 28. Retention frequency plots under pre-development (Baseline) and
post-development with LID controls (Current) conditions 53

Figure 29. Climate change scenarios for the example site. 54

Figure 30. Target event retention for the historical (Baseline) and Warm/Wet
climate scenarios 56

Figure 31. Conceptual representation of a bio-retention cell 59

Figure 32. NWS rain gage locations included in the calculator. 66

Figure 33. NRCS (SCS) 24-hour rainfall distributions (USDA, 1986) 67

Figure 34. Geographic boundaries for the different NRCS (SCS) rainfall
distributions (USDA, 1986) 67

Figure 35. Locations with computed evaporation rates (Alaska and Hawaii not
shown) 68

Figure 36. CMIP3 2060 projected changes in temperature and precipitation for
> Omaha, NE (EPA, 2012).

....................................................................................................................................................................
70

List of Tables

Table 1. Definitions of Hydrologic Soil Groups (USDA, 2010) 15

Table 2. Descriptions of LID practices included in the calculator. 38

Table 3. Editable LID parameters 40

Table 4. Void space values of LID media. 40

Table 5. Summary results for pre-development conditions on the example site.
42

Table 6. Land cover for the example site. 44

Table 7. Comparison of runoff statistics for post-development (Current) and
pre-development (Baseline) conditions 45

Table 8. Runoff statistics for pre-development (Baseline) and
post-development with LID controls (Current) scenarios 50

Table 9. Summary results under a Warm/Wet (Current) climate change scenario
compared to the historical (Baseline) condition 55

Table 10. Depression storage depths for different land covers 62

Table 11. Roughness coefficients for different land covers 63

Table 12. Infiltration parameters for different soil types 64

Introduction

The National Stormwater Calculator is a simple to use tool for computing
small site hydrology 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 rainfall. The
analysis takes into account 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 taken from internationally
recognized climate change projections can also be considered.

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:

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 storms 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?

The calculator seamlessly 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
(http://www.epa.gov/nrmrl/wswrd/wq/models/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.

The calculator is most appropriate for performing screening level analysis
of small footprint sites up to several dozen 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.

How to Run the Calculator

The Stormwater Calculator is a desktop application that runs on any version
of Microsoft Windows with version 4 or higher of the .Net Framework
installed. An installation program for the calculator can be downloaded from
the following web page:
<http://www2.epa.gov/water-research/national-stormwater-> calculator.
After running the installer, there will be a folder named “US EPA” added to
your Windows Start Menu. The folder contains a shortcut named “EPA
Stormwater Calculator” that can be used to launch the program.

NOTE: You must have an internet connection to run the Stormwater
Calculator.

The main window of the calculator is displayed in Figure 1. It 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.

Figure 1. The calculator's main window.

The various pages of the calculator are used as follows:

Location page - establishes the site’s location
Soil Type page - identifies the site’s soil type
Soil Drainage page - specifies how quickly the site’s soil drains
Topography page - characterizes the site’s surface topography
Precipitation page - selects a nearby rain gage to supply hourly
rainfall data
Evaporation page - selects a nearby weather station to supply
evaporation rates
Climate Change page – selects a climate change scenario to apply
Land Cover page - specifies the site’s land cover for the scenario being
analyzed
LID Controls page - selects a set of LID control options, along with
their design features, to deploy within the site
Results page - runs a long term hydrologic analysis and displays the
results.

There are also three command options shown along the bottom status bar that
can be selected at any time:

Analyze a New Site: This command will discard all previously entered data
and take you to the Location page where you can begin selecting a new
site to analyze. You will first be prompted to save the data you entered for
the current site.
Save Current Site: This command is used to save the information you have
entered for the current site to a disk file. This file can then be re-opened
in a future session of the calculator by selecting the Open a previously
saved site command on the Location page.
Exit: This command closes down the calculator. You will be prompted to
save the data you entered for the current site.

You can move back and forth between the calculator’s pages to modify your
selections. Most of the pages have a Help command that will display
additional information about the page when selected. After an analysis has
been completed on the Results 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 pages will now be described in more
detail.

Location

The Location 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. 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 area. Once the site 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 red square.

Figure 2. An image of the locator's map.

Figure 2. The calculator’s Location page.

The map display can be toggled between a standard road map view and a bird’s
eye aerial view. Figure 3 shows the site located in Figure 2 with a
zoomed-in aerial view selected. You can also specify the area of the site,
which will result in a bounding red circle being drawn on the map. This is
optional since 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 start working with that data
once again. (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.

Figure 3. A bird's eye map view with a bounding circle.

Figure 3. Bird’s eye map view with a bounding circle.

Soil Type

Figure 4 shows the Soil Type 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 lists the definitions of the different soil groups.

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
(http://soils.usda.gov/survey/geography/ssurgo/).)
Simply check the View Soil Survey Data box at the top of the page’s left
panel to retrieve SSURGO data. (There will be a slight delay the first time
that the soil data is retrieved and the color-coded overlay is drawn).
Figure 4 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.

Figure 4. Image of the calculator's soil type page.

Figure 4. The calculator’s Soil Type page.

The SSURGO database houses soil characterization data for most of the U.S.
that have been collected over the past forty years by federal, state, and
local agencies participating in the National Cooperative Soil Survey. The
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, 2010).

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 page of the calculator (Figure 5) 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.

There are several options available for assigning a hydraulic conductivity
value (in inches per hour) to the site:

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).
As with soil group, conductivity values from the SSURGO database can be
displayed on the map when the View Soil Survey Data checkbox is selected.
Clicking the mouse on a colored region of the map will make its conductivity
value appear in the edit box.
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.

Figure 5. Image of calculator's soil drainage page.

Figure 5. The calculator's Soil Drainage page.

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.

Topography

Figure 6 displays the Topography 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
results 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%), moderately flat (5%), moderately steep (10%) and steep
(above 15%). As with soil type and drainage rate, any available SSURGO slope
data will be displayed on the map if the View Soil Survey checkbox is
selected. You can use the resulting display as a guide or use local
knowledge to describe the site’s topography.

Figure 6. Image of calculator's topography page.

Figure 6. The calculator's Topography page.

Precipitation

The Precipitation page of the calculator is shown in Figure 7. It is
used to select a National Weather Service rain gage that will supply
rainfall data for the site. Rainfall is the principal driving force that
produces 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 whose sizes are exceeded only once every 5, 10, 15, 30, 50
and 100 years, respectively.

Figure 7. Image of calculator's precipitation page.

Figure 7. The calculator's Precipitation page.

The calculator contains a catalog of over 8,000 rain gage locations from the
National Weather Service’s (NWS) National Climatic Data Center (NCDC).
Historical hourly rainfall data for each station have been extracted from
the NCDC’s repository, screened for quality assurance, and stored on an EPA
file server. As shown in Figure 7, 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 then choose what you consider to
be the most appropriate source of rainfall data for the site.

If the Save rainfall data … command label is clicked, a Save As dialog
window will appear allowing you to save the rainfall data to a text file in
case you want to use the data for some other application, such as SWMM. Each
line of the file will contain the recording station identification number,
the year, month, day, hour, and minute of the rainfall reading and the
measured hourly rainfall intensity in inches/hour.

Evaporation

The Evaporation page of the calculator is displayed in Figure 8. It is
used to select a weather station that will supply 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.

Figure 8. The calculator's Evaporation page.

Over 5,000 NWS weather station locations throughout the U.S. have had their
daily temperature records analyzed to produce estimates of monthly average
evaporation rates (i.e., twelve values for each station). These rates have
been stored directly into the calculator. The calculator lists the five
closest locations that appear in the table along with their period of record
and average daily evaporation rate (the average of the twelve monthly
rates). Note that these are “potential” evaporation rates, not recorded
values (there are only a few hundred stations across the U.S. with long term
recorded evaporation data). The rates have been estimated for bare soil
using the Penman-Monteith equation; and thus, transpiration or vegetative
land cover is not explicitly represented. More details are provided in the
Computational Methods section of this document.

As with rainfall, a Save evaporation data … command is available in case
you would like to save the data to a file for use in another application. If
this option is selected, the data will be written to a plain text file of
your choice with the twelve monthly average rates appearing on a single
line.

Climate Change

The 2007 Fourth Assessment Report of the Intergovernmental Panel on Climate
Change (IPCC) states that global warming is now unequivocal (IPCC, 2007).
Some of the impacts that such warming 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 9 displays the Climate Change page of the calculator. It is used
to select a particular future climate change scenario for the site. The
scenarios were derived from a range of outcomes of the World Climate
Research Program’s CMIP3 multi-model dataset (Meehl et al., 2007). This
dataset contains results of different global climate models run with future
projections of population growth, economic activity, and greenhouse gas
emissions. The results have been downscaled to a regional grid that
encompasses each of the calculator’s rain gage and weather station
locations. Three different scenarios are available that span the range of
changes projected by the climate models: one is representative of model
outputs that produce hot/dry conditions, another represents changes that
come close to the median outcome from the different models, and a third
represents model outcomes that produce warm/wet conditions. Projections for
each scenario are available for two different future time periods: 2035 and
2060.

Each choice of climate change scenario and projection year produces a
different percent change in monthly average rainfall, monthly average
temperature, and annual maximum day precipitation for each rain gage
location and weather station in the calculator’s database. The precipitation
changes for the current choice of rain gage are shown in the right hand
panel of the Climate Change page. These changes are used to adjust the
historical meteorological records for the site as follows:

The changes in monthly average rainfall are applied as a multiplier to each
historical hourly rainfall reading that occurred in the particular month for
each year of record.

The changes in monthly average temperatures are applied in similar fashion
to the historical daily temperature records used to calculate an average
daily evaporation rate for each month of the year.

The climate change influenced extreme event rainfalls are used in place of
the historical ones.

The hot/dry, median, 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 are
predicting increases in projected rainfall it is more likely that larger
rainfall events will occur. All three scenarios should be considered when

bracketing future conditions, since the greatest projected change is not
always associated with the hot/dry or warm/wet 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 users guide.

Figure 9. The calculator's Climate Change page.

Land Cover

Figure 10 displays the Land Cover 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 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:

Figure 10. The calculator's Land Cover page.

Forest – stands of trees with adequate brush and forested litter cover
Meadow – non-forested natural areas, scrub and shrub rural vegetation
Lawn – sod lawn, grass, and landscaped vegetation
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 9, 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.

LID Controls

The LID Controls page of the calculator is depicted in Figure 11. 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. As
seen in Figure 11, there are seven different types of green infrastructure
(GI) LID controls available. You can elect to apply any mix of these
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. This will also allow you to automatically size
the control to capture a 24-hour design storm that you specify. 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 users guide.

Figure 11. Image of calculator's LID controls page.

Figure 11. The calculator’s LID Controls page.

Results

The final page of the calculator is where a hydrologic analysis of the site
is run and its results are displayed. As shown in Figure 12, by selecting
the Site Description report option you can first review the data that
you entered for the site and go back to make changes if needed.

Figure 12. Image of calculator's results page.

Figure 12. The calculator’s Results 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:

The number of years of rainfall record to use (moving back from the most
recent year on record).
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 “measureable”.
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.

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

Interpreting the Calculator’s Results

The Results page of the calculator (Figure 12) contains a list of
reports that can be generated from its computed results. Before discussing
what these reports contain it will be useful to briefly describe how the
calculator derives its results. After you select the Refresh Results
command, the calculator internally performs the following operations:

A SWMM input file is created for the site using the information you provided
to the calculator.
The historical hourly rainfall record for the site is adjusted for any
climate change scenario selected.
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.
The 15-minute time series of rainfall and runoff are accumulated into daily
values by calendar day (midnight to midnight).
Various statistics of the resulting daily rainfall and runoff values are
computed.
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 climate change scenario 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 13, contains the following items:

A pie chart showing the percentage 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 measureable rainfall
divided by the number of years simulated, i.e., the average number of days
per year with rainfall above the Event Threshold.

An image of a pie chart for annual rainfall.

Figure 13. The calculator’s Summary Results report.

Days per Year with Runoff: The number of days with measureable 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 measureable
rainfall that do not have any measureable 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
measureable 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 measureable runoff.
Of the wet days that lie between this depth and the smallest rainfall with
runoff, some will have runoff and others will not.

Max. Retention Volume: The largest daily rainfall amount retained on
site over the period of record. This includes days that produce runoff
from storms that are only partly captured.

Note that 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.

Rainfall / Runoff Events

The calculator’s Rainfall/Runoff report contains a scatter plot 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 (see page
25) 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.

Figure 14. An image of a scatter chart showing the calculator's
rainfall/runoff event report.

Figure 14. The calculator's Rainfall / Runoff Event report.

Rainfall / Runoff Frequency

An example of the calculator’s Rainfall / Runoff Frequency report is
seen in Figure 15. It shows how many times per year, on average, a given
daily rainfall depth or runoff depth will be exceeded. As an example, from
Figure 14 we see that there are three days per year where it rains more than
two inches, but only one day per year where there is more than this amount
of runoff. Events with more than four inches of rain occur only once every
two years.

Figure 15. A graph of rainfall/runoff exceedance frequency.

Figure 15. The calculator’s Rainfall / Runoff Frequency report.

The rainfall frequency curve is generated by simply ordering the measureable
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.

Rainfall Retention Frequency

Another type of report generated by the calculator is the Rainfall
Retention Frequency plot as shown in Figure 16. It graphs the frequency
with which a given depth of rainfall will be retained on site for the
scenario being simulated. For a given daily rainfall depth X the
corresponding percent of time it is retained represents the fraction of
storms below this depth that are completely captured plus the fraction of
storms above it 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 measureable rainfall and associated runoff for a site.
Suppose there were 300 days with rainfall below one inch that had no
measureable runoff and 100 days where it rained more than an inch but the
runoff was less than an inch. The retention frequency for a one inch
rainfall would then be (300 + 100) / 1,000 or 40 percent.

Figure 16. The calculator’s Rainfall Retention Frequency report.

The Rainfall Retention Frequency report is useful for determining how
reliably a site can meet a required stormwater retention standard. Looking
at Figure 16, 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 29 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 13).

Runoff by Rainfall Percentile

The Runoff by Rainfall Percentile report produced by the calculator is
displayed in Figure 17. It shows what percentage of total measureable runoff
is attributable to different size rainfall events. The bottom axis is
divided into intervals of daily rainfall event percentiles. The top axis
shows the rainfall depth corresponding to each end-of-interval percentile.
The bars indicate what percentage of total measureable runoff is generated
by the rainfall within each size interval. This provides a convenient way of
determining what rainfall depth corresponds to a given percentile
(percentiles are listed along the bottom of the horizontal axis while their
corresponding depths are listed across the top of the axis.)

Figure 17. A bar chart for the calculator's runoff by rainfall percentile
report.

Figure 17. The calculator’s Runoff by Rainfall Percentile report.

As an example of how to interpret this plot, look at the bar in Figure 17
associated with the 90th to 95th percentile storm interval (daily rainfalls
between 1.38 and 1.81 inches). Storms of this magnitude make up 16 % of the
total runoff (for this particular site and its land cover). Note that by
definition the number of events within this 5 percentile interval is 5 % of
the total number of daily rainfall events.

Extreme Event Rainfall/Runoff

The final report produced by the calculator shows the rainfall and resulting
runoff for a series of extreme event (high intensity) storms that occur at
different return periods. An example is shown in Figure 18. Each stacked bar
displays the annual max day rainfall that occurs with a given return period
and the runoff that results from it for the current set of site conditions.
The max day rainfalls correspond to those shown on the Climate Change
page for the scenario you selected (or to the historical value if no climate
change option was chosen).

Note that the max day rainfalls at different return periods are a different
statistic than the daily rainfall percentiles that are shown in the Runoff
by Rainfall Percentile report (see Figure 17). The latter represents the
frequency with which any daily rainfall amount is exceeded while the former
estimates how often the largest daily rainfall in a year will 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 X
year event when fewer than X years of observed rainfall data are available.

Printing Output Results

As mentioned previously, all of the information displayed on the Runoff
pages 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 upper left panel of the Runoff page and then
enter a name for the file to which the results will be written.

Figure 18. Bar chart for calculator's extreme event rainfall/runoff report.

Figure 18. The calculator’s Extreme Event Rainfall / Runoff report.

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 Stormwater Calculator allows you to apply a mix of seven
different types of LID practices to a site. These are displayed in Table 2
along with brief descriptions of each. This particular set of GI 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 have to specify what
percentage of the site’s impervious area will be treated by the practice
(see Figure 10). You can, however, modify the default settings by clicking
on the name of the particular practice you wish to edit. For example, Figure
19 displays the resulting LID Design dialog window that appears when the
Street Planter LID is selected. All of 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 (see
Figure 10). This computes a Capture Ratio (area of LID relative to area
being treated) for Rain Gardens, Street Planters, Infiltration Basins,
and Porous 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, since no storage volume is used
with this practice, and for Green Roofs, since the ratio is 100% by
definition. The methods used to automatically size the LID controls are
described in the Computational Methods section of this users guide. Note
that even when sized in this fashion, a 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.

Table 2. Descriptions of LID practices included in the calculator.

LID Practice	Description
./media/image42.jpeg	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.
./media/image43.jpeg	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.
./media/image44.jpeg	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.
./media/image45.jpeg	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.
./media/image46.jpeg	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.
./media/image47.jpeg	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.
./media/image48.jpeg	Porous 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.

Disconnect.bmp

Disconnection

BlueCistern.bmp

Rain Harvesting

RainGarden2.bmp

Rain Gardens

GreenRoof.bmp

Green Roofs

streetplanter.bmp

Street Planters

InfiltrationBasin5.jpg

Infiltration Basins

PorousPavement2.bmp

Porous Pavement

Figure 19. Image of a street planter. Example of LID design dialog for a
street planter.

Figure 19. Example of a LID Design dialog for a street planter.

There are some additional points to keep in mind when applying LID controls
to a site:

The area devoted to Disconnection, Rain Gardens, and Infiltration
Basins is assumed to come from the site’s collective amount of pervious
land cover while the area occupied by Green Roofs, Street Planters and
Porous Pavement comes from the site’s store of impervious area.
Underdrains (slotted pipes placed in the gravel beds of Street Planter and
Porous Pavement areas to prevent the unit from flooding) are not provided
for. However since 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.
The amount of void space in the soil, gravel, and pavement used in the LID
controls are listed in Table 4 below. They typically have a narrow range of
acceptable values and results are not terribly sensitive to variations
within this range.

Table 3. Editable LID parameters.

LID Type	Parameter	Default Value
Disconnection	Capture Ratio	100 %
Rain Harvesting	Cistern Size	100 gal
	Cistern Emptying Rate	50 gal/day
	Number of Cisterns	4 per 1,000 sq ft
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
Porous Pavement	Capture Ratio	100 %
	Pavement Thickness	4 inches
	Gravel Bed Thickness	18 inches

Table 4. 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 Porous Pavement	75 %
Pavement Void Ratio	Porous Pavement	12 %

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 just as well. It is a 12 acre
environmental research facility. The baseline data for the site have already
been obtained from Figures 4 through 8. These identified the site’s
hydrologic soil group as B, its hydraulic conductivity as 0.108 inches/hour,
its topography as moderately steep, its closest rain gage as having an
annual rainfall of

47.05 inches and its closest weather station averaging 0.2 inches per day of
potential evaporation. 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 what effect
a future climate change scenario might have on the site’s ability to comply
with the standard.

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 shortly. 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. 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 (see Figure 7). For the next page of the calculator no LID
Controls are selected since 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 5. It shows that there is an average of 71 days per
year with rainfall, but only 7 of these produce measureable runoff. Of the
47 inches of rainfall per year, 91 percent is retained on site. The Runoff
by Rainfall Percentile plot for this run, shown in Figure 20, indicates
that it is mainly storms above 1 inch that produce almost all of the runoff.

Table 5. Summary results for pre-development conditions on the example
site.

Figure 20. 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 95th 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 95th percentile rainfall depth is. This can be found from the
aforementioned Runoff by Rainfall Percentile plot in Figure 20. The
95th percentile storm corresponds to 1.75 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

Because the standard attaches 95 % reliability to its target rainfall,
we assume that the same would hold for its retention target. From Figure 21,
we see that a retention target of 1.3 inches could be met 95 % of the time
(i.e., of the 71 days per year on average with measureable precipitation,
for 67 of those the site will retain either the entire rainfall or the first
1.3 inches, whichever is smaller). Because this is less than the 1.75 inch,
95th percentile rainfall, the standard for this site would be to retain 1.3
inches.

Figure 21. Rainfall retention frequency under pre-development conditions
for the example site.

Post-Development Conditions

Next the calculator will be used to analyze the example site’s hydrology
under post-development conditions. Because we want to compare the results
against those for the pre-development case, we first select the Use as
Baseline Scenario option on the Results page of the calculator to tell it
to display our pre-development results as a comparison baseline scenario in
future runs. We then determine the land cover for the site in its developed
state. Table 6 shows the distribution of the different land cover categories
across the site. Impervious surfaces cover almost half of the total site
area. Selecting the Land Cover page of the calculator, we replace the
pre-development land cover with this new one (refer to Figure 10).

Table 6. 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 7
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 measureable runoff, there are 51 and the total volume of
runoff has increased more than fivefold. As seen in the Rainfall Retention
Frequency plot of Figure 22, the 1.3 inch retention target identified
earlier can only be met about 30% of the time (which consists primarily of
those days where a low amount of rainfall is entirely contained on site).

Table 7. Comparison of runoff statistics for post-development (Current)
and pre-development (Baseline) conditions.

Figure 22. Rainfall retention frequency for pre-development (Baseline) and
post-development (Current) conditions.

Post-Development with LID Practices

We will now add some LID practices to our example site to see how well they
can make its post- development hydrology more closely match that of
pre-development. Returning the calculator to the LID Controls page we see
there are seven types of LID controls available to apply in any combination
and sizing to the impervious areas of the site. From Table 6, we see that
roofs occupy 20 percent of the total impervious area, parking lots another
20 percent, and the remaining 60 percent is roads and sidewalks. Because the
site houses a research facility, we assume that we can capture runoff from
the roof of the main building (15 percent of the impervious area) in
Cisterns and use it for non-potable purposes within the site. Runoff from
the roofs, roads and parking areas on the north side of the site will be
directed into an Infiltration Basin. A portion of the south parking area
will be replaced with Porous Pavement.

Finally, strategically placed Rain Gardens will be used to intercept
runoff from the remaining roofs, roads and sidewalks.

Figure 23 shows how the LID Controls practices page of the calculator
was filled in to reflect these choices. A design storm size of 1.75 inches,
based on the 95th percentile storm, was chosen to automatically size each
LID control. Each LID’s design dialog was launched to apply automatic sizing
to it. The results of this process are shown in Figures 24 and 25 (capture
ratios for the infiltration basin, rain gardens and porous pavement; number
of cisterns / 1,000 square feet for rain harvesting).

Figure 23. Image of low impact development controls applied to the example
site.

Figure 23. Low Impact Development controls applied to the example site.

Figure 24. Image of rain harvesting system.

Figure 24. Design parameters for Rain Harvesting and Rain Garden
controls.

Figure 24. Design parameters for rain harvesting and rain garden controls.

Figure 25. Design parameters for the Infiltration Basin and Porous
Pavement controls.

Re-running the calculator for the developed site with LID controls produces
the summary results shown in Table 8. The site now comes very close to
matching the pre-development hydrology. It has only one more day per year,
on average, with runoff than does the pre-developed site and only one more
inch of annual runoff. Figure 26 shows that the runoff frequency of the
controlled site is quite close to the pre- developed site. Figure 27 shows
an almost identical contribution of different size storms to runoff between
the two. Finally, from Figure 28 we see that with this extensive use of LID
controls the site could meets the 1.3 inch retention standard at the
required 95% level of confidence.

Table 8. Runoff statistics for pre-development (Baseline) and
post-development with LID controls (Current) scenarios.

Figure 26. A graph for daily runoff frequency curves for baseline and
current conditions.

Figure 26. Daily runoff frequency curves for pre-development (Baseline)
and post- development with LID controls (Current) conditions.

Figure 27. A bar chart for runoff contribution by rainfall percentile.

Figure 27. Contribution to total runoff by different magnitude storms for
pre-development (Baseline) and post-development with LID controls (Current)
conditions.

Figure 28. Retention frequency plots under pre-development (Baseline) and
post- development with LID controls (Current) conditions.

Climate Change Impacts

As a final step in our analysis of the example site we will calculate what
impact a future change in local climate might have on the ability of the LID
practices we installed to control runoff. Figure 29 is the Climate
Change page for our site, showing how different scenarios projected to the
year 2060 affect monthly rainfall levels and extreme storm events. Observe
that the Warm/Wet scenario results in higher average rainfall while the
Hot/Dry scenario produces slightly larger extreme storms. To provide the
largest climate change impact we will select the Warm/Wet scenario 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 future
climate condition.

Figure 29. Image of graphs showing climate change scenarios.

Figure 29. Climate change scenarios for the example site.

The resulting Summary Results report for the adjusted rainfall record is
shown in Table 9. Remember that the Current Scenario results represent the
site response under the future set of climatic conditions while the
Baseline Scenario results are for historical conditions. We observe that
the climate change impact on the long term performance of the site is quite
modest. Although annual rainfall increases by 4 inches (8.5 %), there is
only 1.6 additional inches of runoff per year and only one more day per year
with measureable runoff.

From the Rainfall / Runoff Frequency plot of Figure 30 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., daily
rainfalls exceeding 4 inches have historically occurred only once every 3
years but are predicted to occur once every 18 months in the future.)
Regarding the retention target of 1.3 inches, the Rainfall Retention
Frequency plot of Figure 31 shows that under the future Warm/Wet scenario
there is a drop of only one percentage point in the probability of meeting
the target (from 95 to 94 %).

Table 9. Summary results under a Warm/Wet (Current) climate change
scenario compared to the historical (Baseline) condition.

Figure30. Daily rainfall and runoff frequencies for the historical
(Baseline) and Warm/Wet climate scenarios.

Figure 30. 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 32 shows the Extreme Event Rainfall / Runoff report
for the developed site subjected to the two climate scenarios. We observe
that there is only a minor increase in estimated rainfall amounts for all
return periods under the Warm/Wet scenario as compared to the baseline
historical scenario. These amounts simply mirror the numbers displayed on
the Climate Change page of the calculator for this site (see Figure 29).
None of these extreme event storms can be completely captured by the LID
controls deployed on the site. But this is to be expected since the LID
controls were only designed to capture up to 1.3 inches of rainfall. The
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.

Figure 32. A graph for extreme event rainfall/runoff

Figure 32. Extreme event rainfall and runoff for the Warm/Wet climate
change scenario and the historical record (Baseline).

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 subcatchment areas to best capture the effect that spatial
variability in topography, drainage pathways, land cover, and soil
characteristics have on runoff generation. An idealized subcatchment 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
subcatchment can be further divided into three subareas: 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 subcatchment (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 subcatchment:

𝝏𝝏𝝏𝝏 = 𝒊𝒊 − 𝒆𝒆 − 𝒇𝒇 − 𝒒𝒒 (1)

𝝏𝝏𝝏𝝏

where d = depth of water on the land surface, i = rate of rainfall + any
runon from upstream subcatchments, e = evaporation rate, f = soil
infiltration rate, q = runoff rate and t = time. Note that the fluxes
i, e, f, and q 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 q as:

𝒒𝒒 = 𝟏𝟏.𝟒𝟒𝟒𝟒𝟒𝟒𝑺𝑺𝟏𝟏/𝟐𝟐 (𝝏𝝏 − 𝝏𝝏

)𝟓𝟓/𝟑𝟑

𝑨𝑨𝑨𝑨

𝒔𝒔

(2)

where W = width of the subcatchment’s outflow face, S = subcatchment
slope, n = roughness coefficient, A = subcatchment 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 d is below ds. How the
calculator sets values for the parameters in this equation is discussed
later on in this section.

Substituting (2) into (1) produces an ordinary non-linear differential
equation that can be solved numerically for d 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 q at 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):

𝒇𝒇 = 𝑲𝑲 �𝟏𝟏 + (𝝓𝝓−𝜽𝜽𝟎𝟎)(𝝏𝝏+𝝍𝝍)� (3)

𝑭𝑭

where Ks = saturated hydraulic conductivity, φ = soil porosity, θ0 =
initial soil moisture content, ψ = suction head at the wetting front, and
F = cumulative infiltration volume. Equation (3) applies after a
sufficient time has elapsed to saturate the top layer of soil. During wet
periods the moisture content of the uppermost layer of soil increases at a
rate of 𝒇𝒇/𝑳𝑳𝒖𝒖 where Lu is the layer depth equal to 𝟒𝟒/√𝑲𝑲𝒔𝒔 (for Lu in
inches and Ks in in/hr). During dry periods the moisture content decreases
at a rate of krθ0

where the rate constant kr is estimated as �𝑲𝑲𝒔𝒔/𝟕𝟕𝟓𝟓 . At the start of
the next wet period θ0 is set equal to the current moisture content.

SWMM’s LID Model

SWMM 5 has been extended to explicitly model several types of LID practices
(Rossman, 2009). Consider a typical bio-retention cell in the form of a
street planter as shown in the left panel of Figure

Conceptually it can be represented by a series of three horizontal layers as
depicted in the figure’s right panel.

Figure 31. Conceptual representation of a bio-retention cell.

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

𝝏𝝏𝝏𝝏𝟏𝟏 = 𝒊𝒊 + 𝒒𝒒𝟎𝟎 − 𝒆𝒆𝟏𝟏 − 𝒇𝒇𝟏𝟏 − 𝒒𝒒𝟏𝟏 (4)

𝑳𝑳𝟐𝟐 𝝏𝝏𝜽𝜽𝟐𝟐 = 𝒇𝒇𝟏𝟏 − 𝒆𝒆𝟐𝟐 − 𝒇𝒇𝟐𝟐 (5)

𝝓𝝓𝟑𝟑 𝝏𝝏𝝏𝝏𝟑𝟑 = 𝒇𝒇𝟐𝟐 − 𝒇𝒇𝟑𝟑 − 𝒒𝒒𝟑𝟑

(6)

respectively, where d1 = depth of ponded surface water, θ2 = soil layer
moisture content, d3 = depth of water in the storage layer, i = rainfall
rate, q0 = upstream run-on rate, q1 = surface runoff flow rate, q3 =
underdrain outflow rate, e1 = surface evaporation rate, e2 = soil zone
evaporation rate, f1 = surface infiltration rate, f2 = soil percolation
rate, f3 = native soil infiltration rate, L2 = depth of the soil layer,
and

φ3 = 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 (d1, θ2, and d3) 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: 𝒇𝒇𝟐𝟐 =
𝑲𝑲𝒔𝒔𝐞𝐞𝐞𝐞𝐞𝐞(−𝝆𝝆(𝝓𝝓𝟐𝟐 − 𝜽𝜽𝟐𝟐)) where ρ 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: 𝒒𝒒𝟑𝟑 = 𝜶𝜶(𝝏𝝏𝟑𝟑 − 𝝏𝝏𝝏𝝏)𝜷𝜷
where α and β are constants and dd is 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
Porous Pavement systems by replacing the soil layer with a pavement layer.

Site Model without LID Controls

To analyze a site’s hydrology without any LID controls, the calculator
creates a single SWMM subcatchment 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, 2010), while 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.

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; it is
therefore acceptable to treat them 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.

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 10 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 10. Depression storage depths 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. SWMM uses separate
values for the impervious and pervious areas of a catchment. Table 11 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.

Table 11. Roughness coefficients for different land covers.

Land Cover	SWMa	Engmanb	Yenc	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:

Saturated Hydraulic Conductivity (Ksat) - the rate at which water will
infiltrate through a completely saturated soil.
Suction Head (ψ) - capillary tension (force at which water is held within
soil pores) at the infiltration wetting front.
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, 2010), an A soil is mostly sand, a B soil is
typical of a sandy loam, a C soil is like a clay loam, and a D soil is
mostly clay. Table 12 lists the average values of Ksat, ψ, and IMD for these
four soil types from measurements made from roughly 5,000 soils (of all
types) across the U.S. (Rawls et al., 1983). Also shown, are the values that
were chosen for use in the calculator. 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.

Table 12. Infiltration parameters for different soil types.

Soil Type	Rawls et al.	Calculator
	Ksat (in/h)	ψ (in)	IMD	Ksat (in/h)	ψ (in)	IMD
Sand	4.6	1.95	0.38	4.0	2.0	0.38
Sandy Loam	0.43	4.33	0.26	0.4	4.3	0.26
Clay Loam	0.04	8.22	0.15	0.04	8.2	0.15
Clay	0.01	12.45	0.10	0.01	12.5	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 subcatchment 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 subcatchment, and the original subcatchment
has its areas reduced to reflect the presence of this second subcatchment.
SWMM’s option to internally route runoff from the impervious sub-area on to
the pervious sub-area is used with this subcatchment.

Infiltration Basin

An Infiltration Basin also adds an additional subcatchment 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 subcatchment are reduced accordingly. The impervious area in the
new subcatchment has the same parameter values as in the original
subcatchment. 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 subcatchment whose area is the portion of the original
subcatchment impervious area that is captured by cisterns. This amount of
impervious area is subtracted from that of the original subcatchment. A new
Storage Node element is added into the SWMM model to represent the combined
retention volume of the cisterns. The added subcatchment sends its runoff to
this storage node. The maximum depth of the storage node

is set to a nominal height of 48 inches. Its surface area equals the area of
its contributing subcatchment 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 since 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 gal/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 Porous Pavement do not
require additional subcatchments – they are all placed within the original
subcatchment used to model the site. The original pervious area of this
subcatchment 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 Porous 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

𝑪𝑪𝑪𝑪 = 𝑫𝑫𝒔𝒔𝝏𝝏𝑫𝑫𝑫𝑫𝑫𝑫

𝑫𝑫𝑫𝑫𝒊𝒊𝝏𝝏−(𝑫𝑫𝒔𝒔𝝏𝝏𝑫𝑫𝑫𝑫𝑫𝑫−𝟎𝟎.𝟓𝟓𝑲𝑲𝒔𝒔𝒔𝒔𝝏𝝏)

(7)

where Dstorm is the design storm depth (inches over 24 hours), Dlid is
the storage depth (inches) provided by the LID control, and Ksat is 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 National Weather Service rain gage as selected by the user. The
calculator can access historical hourly rainfall data for 8,159 stations
that are part of the data holdings for EPA’s BASINS system
(http://water.epa.gov/scitech/datait/models/basins/index.cfm).)
The data for each gage is contained in its own file on an EPA server, which
is downloaded and made available to the calculator. The national coverage
provided by these gages is shown in Figure 34.

Figure 32. An image of a map of United States.

Figure 32. NWS rain gage locations included in the calculator.

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 later on. To
simulate each storm, the calculator uses the NRCS (SCS) 24-hour
distributions (USDA, 1986) to disaggregate the event’s total rainfall depth
into a series of rainfall intensities (measured in inches per hour) at six
minute intervals. Figure 35 shows the different NRCS distributions and
Figure 35 shows which distribution applies to each region of the US.

Each precipitation station is pre-assigned a distribution type (I, IA, II,
or III) based on the region it falls in. After the long term simulation is
completed, the SWMM input file is modified as follows:

A time series object is added to the model which is the result of applying
the appropriate SCS distribution at a six minute interval to the total
24-hour rainfall amount being simulated.
The source of rainfall data for the model is set to the newly added time
series.
The duration of the simulation is changed to three days starting on June 1.
After running the model, the only output recorded is the total runoff from
the event. These steps are repeated for each return period extreme event
analyzed.

Figure 33. A chart for 24-hour rainfall distributions.

Figure 33. NRCS (SCS) 24-hour rainfall distributions (USDA, 1986).

Figure 34. Geographic boundaries for the different NRCS (SCS) rainfall
distributions (USDA, 1986).

Evaporation Data

The BASINS holdings only include 329 stations with measured evaporation data
more recent than January 1, 2000 and at least a 5-year period of record.
About 200 of the observed evaporation stations appear to have missing data
for some months of the year. Because of this sparseness of measured
evaporation, it was decided to generate evaporation values using daily
temperature data from 5,236 weather stations across the U.S. which also
measured hourly precipitation. The Penman-Monteith algorithm was extracted
from the SWAT model (Neitsch et al., 2005), and used to compute daily
potential evaporation from daily precipitation and min/max air temperature,
along with generated solar radiation, relative humidity, and wind speed.
Additional details of this calculation can be found in the Quality Assurance
Report produced for this project by Aqua Terra Consultants (Aqua Terra
Consultants, 2011). The locations for which evaporation rates were generated
are displayed in Figure 37.

Figure 35. Locations with computed evaporation rates (Alaska and Hawaii
not shown).

The original result of these calculations was an average potential
evaporation rate for each day of the year (365 values) for each station. A
sensitivity analysis was performed with the calculator to see what effect
there would be in using a monthly average value instead (12 values per
station). Using the monthly values produced annual runoff volumes that were
only 2 to 5% different than those from the daily values. It was therefore
decided to use just the monthly average evaporation values for the
calculator. Each NWS station is identified by its latitude, longitude, and
twelve monthly average evaporation rates that are contained in a table built
into the calculator. This table is used to supply evaporation rates to the
SWMM model constructed by the calculator.

Climate Change Effects

The calculator obtains its climate change scenarios and their effect on
local precipitation and temperature directly from another EPA project called
CREAT (Climate Resilience Evaluation and Analysis Tool) (EPA, 2012). 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 uses statistically downscaled General Circulation Model (GCM)
projections from the World Climate Research Programme (WCRP) Coupled Model
Intercomparison Project Phase 3 (CMIP3) archive (Meehl et al., 2007) as the
source of its climate change data. The CMIP3 archive was chosen by CREAT
because:

it contains 112 runs from 16 internationally recognized models using several
emission scenarios;

it supported model-based analyses presented in the IPCC Fourth Assessment
Report (IPCC, 2007);

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;

it has a high degree of scientific credibility and the archive encompasses a
broad range of assumptions concerning demography, economic integration,
technological advance, energy use, and greenhouse gas emissions.

CREAT limited its use of CMIP3 results to the nine GCM models that were most
representative of US climate conditions and used the IPCC’s “middle of the
road” projection of future economic growth. The latter is characterized by
(1) rapid economic growth, (2) global population that peaks in mid-century,
(3) the quick spread of new and efficient technologies, (4) the global
convergence of income and ways of life, and (5) a balance of both fossil
fuel and non-fossil energy sources (IPCC, 2007).

Each of the nine models produces a different set of results for each future
year within each downscaled

½ degree grid cell. To represent this type of uncertainty inherent in
predicting future climate conditions, CREAT defined three scenarios that
span the range of results produced by the models for any given projection
year. The Warm/Wet scenario used the model that came closest to the 5th
percentile of annual temperature change and 95th percentile of annual
rainfall change. The Median scenario selected the model that was closest to
the median temperature and rainfall changes. The Hot/Dry scenario used the
model that was closest to the 95th percentile temperature change and 5th
percentile rainfall change. Two different projection years were selected:
2035 and 2060.

Figure 36. CMIP3 2060 projected changes in temperature and precipitation
for Omaha, NE (EPA, 2012).

An example of how the scenarios were defined is pictured in Figure 38 for
the 2060 projections for the grid cell containing Omaha, NE. In this figure,
the square symbols are results from the nine different climate models, the
green circles are the target scenarios (5T/95P = warm/wet, 50T/50P = median,
and

95T/5P = hot/dry), and the three blue squares are the models selected for
this particular location. Note that the selection of which GCM model output
goes with which scenario can change depending on grid cell and projection
year.

Once the model output to use for each scenario in each projection year in
each grid cell was identified, CREAT extracted its CMIP3 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 US. For precipitation impacts,
the stormwater calculator used this 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 8,159 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 one
downloaded from the EPA server. 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.

Regarding temperature changes, the monthly changes in CREAT’s database were
used to generate new sets of monthly average evaporation rates for the
calculator. The same procedure described earlier, using the SWAT model’s
Penman-Monteith procedure, was used to compute bare soil evaporation rates
for each day of temperature recorded at 5,236 different NWS weather
stations. However now the daily temperatures were first modified by applying
the monthly temperature changes belonging to the climate change scenario for
the grid cell in which the weather station was located. The multi-year daily
evaporation values were then averaged into a set of twelve daily rates, one
for each month of the year. This process was repeated for each climate
change scenario and projection year at each weather station location. The
result was another set of six tables, each containing a set of modified
monthly evaporation rates for all weather stations for a particular scenario
and projection year.

It turned out that the climate change modified evaporation rates showed
little variation between the different scenarios for a given month at any
particular location, with most differences being 0.02 inches/day or less.
One possible reason for this is that climate change effects for the other
variables that influence the Penman-Monteith estimates, such as wind speed,
relative humidity, and solar radiation, were not considered. Even though the
variations are slight, the tables were still constructed and utilized for
each of the climate scenarios as was done for monthly precipitation. The
monthly evaporation rates appearing in the table for the user’s choice of
climate change scenario are inserted into the SWMM input file for a
particular site instead of the rates based on historical temperatures.

The third climate-influenced outcome that the calculator considers is the
change in the size and frequency of intense precipitation events. CREAT
considered this effect of climate change 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 period
simulated by the CMIP3 GCM used for each scenario. Under the cumulative GEV
distribution, the annual maximum daily rainfall amount x that is exceeded
only once every Y years is:

𝒙𝒙 = 𝝁𝝁 − �𝝈𝝈� �𝟏𝟏 + (𝐥𝐥𝐥𝐥 �𝟏𝟏 − 𝟏𝟏�)−𝝃𝝃� (8)

𝝃𝝃 𝒀𝒀

where µ is a location parameter, σ is a scale parameter, and 𝝃𝝃 is a
shape parameter. These GEV parameters can be estimated from a series of
annual data.

CREAT 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. 8 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.

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 rainfall intensity and the runoff results it computes at this 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 with no measureable rainfall occur for each day with
measureable rainfall. Measureable rainfall and runoff is 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 measureable 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 (refer to Figure 13)
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 scatter plot (see Figure 14) 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 measureable runoff for those days).

The Rainfall / Runoff Frequency report (see Figure 15) 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, j 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 (see Figure 17) is generated as
follows:

The daily measureable rainfall values are sorted by size and a set of
different percentile values are identified (the 10, 20, 30, 40, 50, 60, 70,
75, 80, 85, 90, 95, and 99-th percentiles).
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.
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 (see Figure 16) 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 measureable 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 thirteen pre-selected retention volumes and the resulting pairs of
retention volume – retention frequency values are plotted.

The Extreme Event Rainfall / Runoff report (see Figure 18) is generated
by simply plotting the rainfall and accompanying computed runoff in stacked
fashion for each extreme event return period.

7. References

American Society of Civil Engineers (ASCE) (1992). “Design and Construction
of Urban Stormwater Management Systems.” American Society of Civil
Engineers, New York, NY.

Aqua Terra Consultants (2011). “Quality Assurance Project Plan – Stormwater
Calculator Technical Support.”EPA Contract #EP-C-06-029, Work Assignments
#4-38 and 5-38.

Center for Neighborhood Technology (2009). “National Stormwater Management
Calculator.”

\<<http://greenvalues.cnt.org/national/calculator.php>\>

Chen, C.W. and Shubinski, R.P. (1971). “Computer Simulation of Urban Storm
Water Runoff.” Journal of the Hydraulics Division. ASCE, 97(2):289-301.

Clear Creek Solutions, Inc. (2006). “Western Washington Hydrology Model
Version 3.0 User Manual.”

\<<http://www.ecy.wa.gov/programs/wq/stormwater/wwhm_training/wwhm/wwhm_v3/index.html>\>

Crawford, N.H. and Linsley, R.K. (1966). “Digital Simulation in Hydrology:
Stanford Watershed Model IV.”

Technical Report No. 39, Civil Engineering Department, Stanford
University, Palo Alto, CA.

Engman, E.T. (1986). “Roughness Coefficients for Routing Surface Runoff.”
Journal of Irrigation and Drainage Engineering, ASCE, 112(1):39-53.

IPCC (Intergovernmental Panel on Climate Change) (2007). Climate Change
2007: Synthesis Report - Summary for Policymakers. Available online at:

<http://www.ipcc.ch/pdf/assessment-report/ar4/syr/ar4_syr.pdf>

Karl, T.R., Melillo, J.M., and Peterson, T.C. (eds.) (2009). Global Climate
Change Impacts in the United States. Cambridge University Press.

Meehl, G. A., C. Covey, T. Delworth, M. Latif, B. McAvaney, J. F. B.
Mitchell, R. J. Stouffer, and K. E. Taylor. (2007). “The WCRP CMIP3
multi-model dataset: A new era in climate change research”, Bulletin of the
American Meteorological Society, 88, 1383-1394.

Mein, R.G. and Larson, C.L. (1973). “Modeling infiltration during a steady
rain.” Water Resources Research, 9(2):334-394.

Neitsch S.L., J.G. Arnold, J.R. Kiniry, and J.R. Williams (2005). “Soil and
Water Assessment Tool Theoretical Documentation.” Version 2005,
Agricultural Research Service and Texas Agricultural Experiment Station,
January 2005.

Rawls, W.J., Brakensiel, D.L., and Miller, N. (1983). “Green-Ampt
Infiltration Parameters from Soils Data”, Journal of Hydraulic Engineering,
ASCE, Vol. 109, No. 1, 62-70.

Rossman, L.A. (2009). “Modeling Low Impact Development Alternatives with
SWMM.” In Dynamic Modeling of Urban Water Systems, Monograph 18, W. James,
ed., CHI, Guelph, ON, Canada.

Urban Drainage and Flood Control District (UDFCD) (2007). “Drainage Criteria
Manual, Chapter 5 – Runoff”, Urban Drainage and Flood Control District,
Denver, CO.
(http://www.udfcd.org/downloads/down_critmanual_volI.htm).)

U.S. Department of Agriculture (USDA) (1986). “Urban Hydrology for Small
Watersheds, TR-55”, Natural Resources Conservation Service, USDA,
Washington, DC.

U.S. Department of Agriculture (USDA) (2010). “National Engineering
Handbook.” Natural Resources Conservation Service, USDA, Washington, DC.

U.S. Environmental Protection Agency (EPA) (2014). “Climate Change Impacts
and Adapting to Change.”
(http://www.epa.gov/climatechange/impacts-adaptation/).)

U.S. Environmental Protection Agency (EPA) (2010). “Storm Water Management
Model User’s Manual, Version 5.0.” U.S. Environmental Protection Agency,
Washington, D.C., Pub No. EPA/600/R-05/040 (Revised 2010).

U.S. Forest Service (USFS) (2014). “i-Tree Hydro User’s Manual v. 5.0.”
(http://www.itreetools.org/resources/manuals.php).)

U.S. Global Change Research Program (USGRP) (2014). “Explore Regions &
Topics.”
(http://www.globalchange.gov/explore).)

Wang, J., T.A. Endreny, and D. J. Nowak, 2008. “Mechanistic Simulation of
Tree Effects in an Urban Water Balance Model.” Journal of the American Water
Resources Association (JAWRA) 44(1):75-85.

Yen, B.C., (2001). “Hydraulics of Sewer Systems.” Chapter 6 in Stormwater
Collection Systems Design Handbook, L.M. Mays, ed., McGraw-Hill, New York.

ICM SWMM & ICM InfoWorks, SWMM5

Markdown of National Stormwater Calculator User’s Guide Manual

Markdown of National Stormwater Calculator User’s Guide Manual

DISCLAIMER

ACKNOWLEDGEMENTS

ACRONYMS AND ABBREVIATIONS

TABLE OF CONTENTS

LIST OF FIGURES

List of Tables

Introduction

How to Run the Calculator

Location

Soil Type

Soil Drainage

Topography

Precipitation

Evaporation

Climate Change

Land Cover

LID Controls

Results

Interpreting the Calculator’s Results

Summary Results

Rainfall / Runoff Frequency

Rainfall Retention Frequency

Runoff by Rainfall Percentile

Extreme Event Rainfall/Runoff

Printing Output Results

Applying LID Controls

Example Application

Pre-Development Conditions

Post-Development Conditions

Post-Development with LID Practices

Figure 23. Low Impact Development controls applied to the example site.

Related

Storm/Sewer Modeler with a 45 yr association with EPASWMM. Now at Autodesk supporting InfoWorks ICM_SWMM Founder http://robertdickinson.org, Chair/TAC at http://CIMM.ORG

robert.dickinson@gmail.com

Leave a ReplyCancel reply

search

Markdown of National Stormwater Calculator User’s Guide Manual

Markdown of National Stormwater Calculator User’s Guide Manual

DISCLAIMER

ACKNOWLEDGEMENTS

ACRONYMS AND ABBREVIATIONS

TABLE OF CONTENTS

LIST OF FIGURES

List of Tables

Introduction

How to Run the Calculator

Location

Soil Type

Soil Drainage

Topography

Precipitation

Evaporation

Climate Change

Land Cover

LID Controls

Results

Interpreting the Calculator’s Results

Summary Results

Rainfall / Runoff Frequency

Rainfall Retention Frequency

Runoff by Rainfall Percentile

Extreme Event Rainfall/Runoff

Printing Output Results

Applying LID Controls

Example Application

Pre-Development Conditions

Post-Development Conditions

Post-Development with LID Practices

Figure 23. Low Impact Development controls applied to the example site.

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Related

Storm/Sewer Modeler with a 45 yr association with EPASWMM. Now at Autodesk supporting InfoWorks ICM_SWMM Founder http://robertdickinson.org, Chair/TAC at http://CIMM.ORG

robert.dickinson@gmail.com

Leave a ReplyCancel reply

search

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