THE EFFECTS OF INTERNAL PARTITIONING ON HYDRAULIC DETENTION
TIMES IN STORMWATER EXTENDED DETENTION BASINS
Juliane Gadd
B.S., University of the Pacific, 1989
PROJECT
Submitted in partial satisfaction of
the requirements for the degree of
MASTER OF SCIENCE
in
CIVIL ENGINEERING
at
CALIFORNIA STATE UNIVERSITY, SACRAMENTO
FALL
2010
THE EFFECTS OF INTERNAL PARTITIONING ON HYDRAULIC DETENTION
TIMES IN STORMWATER EXTENDED DETENTION BASINS
A Project
by
Juliane Gadd
Approved by:
__________________________________, Committee Chair
John R. Johnston, Ph.D.
__________________________________, Second Reader
David J. Alderete, M.S.
____________________________
Date
ii
Student: Juliane Gadd
I certify that this student has met the requirements for format contained in the University
format manual, and that this project is suitable for shelving in the Library and credit is to
be awarded for the Project.
__________________________, Graduate Coordinator
Cyrus Aryani, Ph.D, P.E., G.E
Department of Civil Engineering
iii
________________
Date
Abstract
of
THE EFFECTS OF INTERNAL PARTITIONING ON HYDRAULIC DETENTION
TIMES IN STORMWATER EXTENDED DETENTION BASINS
by
Juliane Gadd
Detention Basins (EDBs), an established stormwater Best Management Practice
(BMP), are used to treat polluted stormwater runoff from urban areas and highways.
Treatment occurs primarily through the settling of particles in the EDB. Typically, the
design volume is based on a 2-year storm event and is large enough to capture about 85
percent of the annual runoff. Effluent is discharged through an outlet orifice typically
sized to drain the entire basin in 24 to 48 hours. Because a high percentage of storm
events are smaller than the typical design storm, the 2-year storm, the storm events pass
through the EDB quickly because of the relatively large outlet orifice and receive little
treatment. This project expands on previous investigations of strategies to increase
hydraulic detention time and improve treatment in these devices. The strategy of interest
is dividing an EDB with a partition wall, thus creating primary and secondary cells in
series. The primary cell, equipped with a correspondingly small outlet orifice, captures
and holds the frequent, smaller storm events. Large storm events overflow into the
secondary cell and are treated there. The anticipated outcome is a longer average
detention time and better total suspended solids (TSS) removal.
iv
An ExcelTM Visual Basic for Applications (VBA) computer model was created to
simulate EDBs with and without a partition wall. The software can model irregularlyshaped basins and internal cells with unequal volumes. Hourly rainfall is converted to
runoff using the Rational Method and routed through hypothetical EDBs. Detention
times for each storm event are calculated from the time difference between the centroids
of the influent and effluent hydrographs. In this project, 50 years of historic hourly
rainfall data from Orange County, California were passed through a one-cell
(unpartitioned) EDB and three partitioned EDBs with primary cells sized for 75, 50, and
25 percent of the design volume.
Model results showed that event mean hydraulic detention times were increased
in the partitioned EDBs by 64 to 94 percent compared to the one-cell control EDB. The
longest detention time was achieved in the EDB with the smallest primary cell.
Partitioning also increased the volume-weighted mean hydraulic detention times by 36 to
60 percent, but the longest detention time in this case was achieved in the EDB with the
largest primary cell. Compared to the one-cell EDB, the total volume of water that
overflowed the EDB (i.e. exceeded the design volume) over the 50-year hydrologic
record decreased slightly for the basin with a 75-percent design volume primary cell, but
increased for the other two cases with smaller primary cells. Direct modeling of TSS was
not attempted in this project. When the calculated detention times are applied to TSS
removal curves from the literature, though, event mean TSS removal was estimated to
increase by up to 6 percentage points due to adding an internal partition.
v
_______________________, Committee Chair
John R. Johnston, Ph.D.
_______________________
Date
vi
ACKNOWLEDGMENTS
The author would like to thank Dr. John Johnston and David Alderete for their
support, input, guidance and review of this project. Also, she would like to thank Dr.
Ramzi Mahmood and Dr. Johnston again for their support and guidance throughout the
graduate program. Next, she would like to thank her co-workers Glenn Bielefelt and
Anna Johnson, Engineers, of Sacramento Regional Sanitation District for their
encouragement and assistance. Last, the author would like to thank her family for their
continuous support and love throughout this venture.
vii
TABLE OF CONTENTS
Page
Acknowledgments............................................................................................................... v
List of Tables .................................................................................................................. viii
List of Figures .................................................................................................................. xii
1. INTRODUCTION ........................................................................................................ 1
2. BACKGROUND .......................................................................................................... 4
2.1
Extended Detention Basin Design .................................................................... 5
2.1.1 Basin Size and Water Quality Volume ................................................. 5
2.1.2 Basin Shape and Geometry ................................................................... 8
2.1.3 Inlet and Outlet Design ......................................................................... 9
2.2
Extended Detention Basin Performance ......................................................... 11
2.3
Two-compartment EDB designs ..................................................................... 19
2.4
Previous Computer Models............................................................................. 23
2.4.1 DBSIM1A - Detention Basin Simulation Model version 1A ............. 23
2.4.2 Single Cell On-line Trapezoid Basin with multiple datasets .............. 24
2.4.3 DBSIM2 - Detention Basin Simulation Model version 2 ................... 25
2.4.4 DBSIM3A -- Proposed Computer Model Enhancements ................... 27
2.5
Mathematical Methods for Calculating Volumes of Irregular Shapes ........... 29
3. METHODS ................................................................................................................. 33
3.1
Theoretical Basis of the Model ....................................................................... 33
3.2
Types of Input and Output Data...................................................................... 35
3.2.1 Input Data – EDB Design Variables ................................................... 36
3.2.2 Input Data – Rainfall Data .................................................................. 41
3.2.3 Output Data – Summary Information.................................................. 41
viii
3.2.4 Simulations .......................................................................................... 44
3.3
Program Description ....................................................................................... 46
3.3.1 VBA Program Logic ........................................................................... 47
3.3.2 Site Characteristics Calculations ......................................................... 55
3.3.3 Basin Characteristics Calculations ...................................................... 55
3.3.4 Hourly Calculations............................................................................. 59
3.4
Limitations of DBSIM3A ............................................................................... 64
4. RESULTS AND DISCUSSION ................................................................................. 66
4.1
DBSIM3A Validation ..................................................................................... 68
4.1.1 Validating the Water Balance in a One-Cell Trapezoidal Basin ......... 70
4.1.2 Validating the Non-Uniform Shape Algorithm in a One-Cell Basin .. 71
4.1.3 Validating the Non-Uniform Shape Algorithm in a Two-Cell Basin . 72
4.2
Partitioned EDB Performance Assessment ..................................................... 74
4.2.1 Effect of Partition Wall on Storm Event and Size .............................. 75
4.2.2 Effect of Partition Wall on Hydraulic Performance ............................ 77
4.2.3 Effect of Partition on Detention Times ............................................... 79
4.2.4 Estimated TSS Removal...................................................................... 86
5. CONCLUSIONS......................................................................................................... 88
References ......................................................................................................................... 91
ix
LIST OF TABLES
Page
Table 2-1 Basin size based on Water Quality Volumes .................................................... 6
Table 2-2 Recommended Drawdown Times ................................................................... 11
Table 2-3 TSS Removal Efficiencies (Percent) for Pilot Study BMPs at full-basin (water
quality volume) drawdown time of 72 hours. (Caltrans, 2004) ....................... 12
Table 2-4 Minimum Detention Time ............................................................................... 13
Table 2-5 TSS Removal Efficiencies(Percent) ................................................................ 15
Table 2-6 Summary of Detention Timesa ......................................................................... 18
Table 2-7 Summary of Overflows and Detention Timesa................................................ 20
Table 2-8 Depth calculation based on the number of known Areas. (Weisstein, undated
Wolfram Web Resource).................................................................................. 31
Table 3-1 Input Variables Common with DBSIM1A (Alderete, 2004) .......................... 39
Table 3-2 Additional Input Variables for Irregular Shapes ............................................. 41
Table 3-3 DBSIM3A Single Cell Simulations for Validation ......................................... 45
Table 3-4 DBSIM3A Two-cell Simulations for EDB Performance ................................ 46
Table 3-5 DBSIM3A Two-Cell Basin Cycle of Hourly Computations Description ....... 53
Table 3-6 Newton-Cotes Equations for Volume Calculations in Irregularly Shaped
Basins. .............................................................................................................. 58
Table 4-1 Key Components of EDBs Modeled by DBSIM3A ....................................... 67
Table 4-2 Results of DBSIM1A and DBSIM3A BASE-100 Simulations ...................... 70
Table 4-3 Results of DBSIM3A with Varying Number of Data Point ............................ 72
Table 4-4 Comparison of Simulation Results for One-Cell EDBs and the Primary Cell of
Two-Cell EDBs ................................................................................................ 74
x
Table 4-5 Performance Summary for Basins with and without a Partition Wall (50-year
hydrologic record) ............................................................................................ 75
Table 4-6 Distribution of Storm Events by Size .............................................................. 76
Table 4-7 Cumulative Distribution of Storm Events by Size .......................................... 76
Table 4-8 Number of Storms with Overflows ................................................................. 77
Table 4-9 Volumes of Water Overflowed ....................................................................... 78
Table 4-10 Number of Overflows by Storm Size ............................................................ 79
Table 4-11 Overflow Volumes by Storm Size ................................................................. 79
Table 4-12 Comparison of Simulated Discharge Volumes for System ........................... 80
Table 4-13 Distribution of Storm Events by Detention Time.......................................... 82
Table 4-14 Cumulative Distribution of Storm Events by Detention Time ...................... 82
Table 4-15 Simulated Average Detention Times by Storm Size ..................................... 84
Table 4-16 Estimated TSS Removal Summary ............................................................... 87
Table 5-1 Summary Results from the Four DBSIM3A Simulations ............................... 88
xi
LIST OF FIGURES
Page
Figure 2-1 Adjusted Cumulative Rainfall Distribution, Orange County California
(Alderete, 2004) ................................................................................................. 7
Figure 2-2 Storm Size Distributions by Event (Fu, 2008) ................................................. 8
Figure 2-3 TSS Concentration Reduction as a Function of Length-to-Width Ratio in
EDBs (Caltrans, 2004) ....................................................................................... 9
Figure 2-4 Caltrans EDB at Lake Tahoe. Rock slope protection is visible under the inlet
channel in the background. (Courtesy, John Johnston).................................... 10
Figure 2-5 Detention Time Calculation Using Hydrograph Centroids (Hann, 1994) ...... 14
Figure 2-6 Pollutant Removal as a Function of Detention Time from Laboratory Column
Settling Tests (Grizzard et al., 1986) ............................................................... 15
Figure 2-7 Detention Time as a Function of Storm Size in Orange County (Fu, 2008) .. 17
Figure 2-8 Two-Cell On-line Trapezoid Basin ................................................................ 19
Figure 2-9 Two-Compartment Sedimentation Tank(Li et al., 2006) ............................... 22
Figure 2-10 Total particle reduction rate for different design storm size (Li et al., 2008)
.......................................................................................................................... 22
Figure 2-11 DBSIM1A Code Interaction with Worksheets(Alderete, 2004) .................. 23
Figure 2-12 Comparison of BASE-l00 and TABLEBASE Simulations (Wasilchen, 2007)
.......................................................................................................................... 27
Figure 2-13 Coefficients for formulas from 1 to 10 points.
(http://digilander.libero.it/foxes/integr/Integration_Newton_Cotes.htm 4/) .... 32
Figure 3-1 Mass Balance of Simulated Irregularly shaped Extended Detention Basin ... 34
Figure 3-2 UserForm Input Tabs for Single Cell Basin ................................................... 37
Figure 3-3 UserForm Input Tabs for Two-cell Basin ...................................................... 38
Figure 3-4 UserForm Result Tabs for Single Cell Basins ............................................... 43
xii
Figure 3-5 Example of UserForm Result Tabs for Two-cell Basin ................................. 44
Figure 3-6 UserForm Validation and Simulation Tab ..................................................... 45
Figure 3-7 DBSIM3A Program Logic Modified subroutines highlighted is shaded. ...... 49
Figure 3-8 DBSIM1A Single Cell Hourly Computations for a Storm Event modified by
DBSIM3A. Modified subroutines are shaded. ................................................. 51
Figure 3-9 Generic Plan and Cross-Sectional Views of an Irregularly Shaped EDB ...... 57
Figure 4-1 Combined Storm Comparison – Event 12/22/1948 08:00 ............................. 69
Figure 4-2 Cumulative Distribution Plot of Detention Times ......................................... 83
Figure 4-3 Distribution of Detention Times by Storm Size............................................. 84
Figure 4-4 Ratios of Detention Times to BASE-100 Detention Time............................. 86
xiii
1
Chapter 1
1. INTRODUCTION
INTRODUCTION
Stormwater runoff from rain and snowmelt events accumulates debris, chemicals,
sediment or other pollutant as it flows over impervious surfaces (i.e. paved streets and
highways) and pollutes the receiving water bodies. If untreated, these pollutants could
adversely affect water quality which is considered a threat to the environment (EPA,
2011).
Detention basins are a commonly-used device to reduce some of these pollutants
by capturing runoff and allowing pollutants to settle. In the past, detention basins were
designed to mitigate flood flows only. Flood control basins have been historically
referred to as dry detention basins. Basins intended to meet water quality requirements
are known as Extended Detention Basins (EDBs) referring to the extended time that the
water is held to treat pollutants. Extended detention basins are classified by the
Environmental Protection Agency (EPA) as a structural Best Management Practice
(BMP) for the control of stormwater runoff quality.
Volume-based BMPs such as EDBs are designed according to a standard
prescribed sizing method in which volume of the basin is chosen to capture the so-called
Water Quality Volume (WQV). The WQV is specified by water quality regulators and is
usually between the 75th and 85th percentile annual runoff volume. The design storm
that generates a runoff volume equal to the WQV is approximately equal to the 2-year
2
storm event (i.e. a storm with an annual probability of occurring of 50 percent).
Drawdown times (the time needed to completely drain a basin) are typically greater than
24 hours (e.g., Caltrans, 2004; CASQA, 2003). The drawdown rate is controlled by the
size of an orifice in the outlet structure. Stormwater runoff greater than the design storm
volume is routed to an emergency overflow weir. Stormwater runoff less than the design
storm is not detained for very long because the outlet orifice is sized to drain the whole
basin in the specified drawdown time. This results in reduced treatment for smaller
storms. The great majority of California storm events are smaller than the 2-year storm
event; meaning runoff frequently receives minimal treatment.
A hypothesized improvement to EDB design is to divide the basin into primary
and secondary treatment cells using a partition wall. The outlet orifice in the partition
wall would be sized to drain only the primary cell in the specified drawdown time.
Medium-to-large storms, up to the design storm, would overflow the partition and be
treated in the secondary cell. This design would increase the detention time and improve
treatment during the numerous smaller storms without impairing the processing of larger
storms. Recent literature suggests that a two-compartment settling tank improves both
small and large particle mass removal efficiency (Li, et al, 2008).
The objective of this project is to create a computer simulation model for EDBs
with arbitrary non-uniform shapes and an internal partition. The primary parameter of
interest is hydraulic detention time, which is calculated as the time between the centroids
of the inflow and outflow hydrographs. This model builds directly on two previous
3
projects. Alderete (2004) created a simulation model for one-cell, trapezoidal EDBs.
Wasilchen (2007) modeled two-cell EDBs by operating two, one-cell trapezoidal EDBs
in series. This is not, however, a very practical design. The shallow side slopes used in
these basins lead to a wide earthen dike between the primary and secondary cells and a
large footprint. A better approach is to divide a one-cell pond with a simple vertical wall.
To simulate this accurately requires an algorithm to model irregular non-uniform shapes.
The completed model is run using a 50-year long hydrologic data set for Orange County,
California. Three different primary-to-secondary cell configurations are simulated to
determine how an EDB should be divided to maximize the hydraulic detention time.
4
Chapter 2
2. BACKGROUND
BACKGROUND
American federal water pollution law extends back to1948 with the Federal Water
Pollution Control Act. In 1972, major amendments to the law put regulatory focus on
discharge standards by instating the National Pollutant Discharge Elimination System
(NPDES) which requires all dischargers to obtain permits. The law became known as the
Clean Water Act. Between 1978 and 1983, the Environmental Protection Agency (EPA)
sponsored the National Urban Runoff Program (NURP) study which provided important
information about the adverse effects of stormwater runoff. Subsequently, under the
authority of the Clean Water Act, the EPA developed a stormwater management program
that required stormwater pollution to be controlled to the maximum extent practicable
(MEP) through the utilization of Best Management Practices (BMPs). EPA defines a
stormwater BMP as a technique, measure, or structural control that is used for a given set
of conditions to manage the quality and improve the quality of stormwater runoff in the
most cost effective manner 1(USEPA, 1999). BMPs are either non- structural or
structural engineered systems constructed to treat stormwater before entering the
receiving waters. The goals of stormwater BMPs are flow rate control, runoff volume
reduction, pollutant removal, and point source reduction.
1 EPA-821-R-99-012 August 1999 Preliminary Data Summary of Urban Storm Water Best Management
Practices
5
Among the BMPs commonly employed are so-called wet and dry detention
basins. Wet basins maintain a permanent pool of water; dry basins drain completely
between storm events. One type of dry basin, the extended detention basin (EDB), has
become one of the most popular solutions for the treatment of stormwater runoff in
California because of the state’s dry climate and because these devices are inexpensive
and easy to construct. EDBs can be operated in on-line or off-line mode. Off-line EDBs
bypass inflows when the EDB is full. The bypass structure, or flow splitter, is located
upstream of the basin and diverts untreated inflows around basin. On-line EDBs allow
the full inflow volume of runoff to pass through the basin. Excess runoff from storms
larger than the design volume exits through an overflow system (e.g. a broad-crested
weir) and is considered partially treated.
2.1
Extended Detention Basin Design
In EDB design, volume, drain down time, geometry, and inlet and outlet facilities
must be chosen. To allow particles and associated pollutants to settle, extended detention
basins are designed to detain the stormwater runoff from a water quality design storm for
some minimum time.
2.1.1
Basin Size and Water Quality Volume
The water storage capacity desired to capture and treat stormwater runoff at a
given site is termed the Water Quality Volume (WQV). Several methods have been are
used to calculate the WQV, including the Runoff Capture Ratio method developed by
Guo and Urbonas (1996) and the BMP Handbook Method by the California Stormwater
Quality Association (CASQA, 2003). In the BMP Handbook Method, hourly rainfall
6
hydrographs are passed through a very simple EDB model and the percentage of volume
that is captured and treated (i.e., not overflowed) is calculated. The basin size is then
adjusted until the desired volume is treated. In California practice, the capture volume is
determined by local governments. Typically, the WQV is 85 percent of annual runoff
volume (CASQA, 2003). WQVs, therefore, vary by location. Typical treated WQVs for
1- hectare highway catchments are shown in Table 2-1 for five California regions.
Table 2-1 Basin size based on Water Quality Volumes
Location
Basin Volume (ft3)
Eureka
6011
Chico
7492
San Francisco
6882
Fresno
4443
Orange County
6534
a
Adapted from Fu (2008)
Design Storm
The design storm is the particular event with runoff rates or volumes that volumebased BMPs, such as EDBs, are designed to process. In other words, it is the storm that
generates a WQV. Most storm events are much smaller than the design storm. For
example, the cumulative percentage of storm events in Orange County is plotted against
storm size in Figure 2-1. The design storm is 0.6 inches. As can be seen, about 85
percent of Orange County storm events are smaller than the design storm.
7
Figure 2-1 Adjusted Cumulative Rainfall Distribution, Orange County California
(Alderete, 2004)
Rainfall data graphed in Figure 2-2 from five different California climate regions
studied by Fu (2008) show similar storm patterns in which the number of smaller storms
far exceed the number of larger storms. Most storm events are less than 0.5 inches and
30 to 40 percent are less than 0.1 inches.
8
Figure 2-2 Storm Size Distributions by Event (Fu, 2008)
2.1.2
Basin Shape and Geometry
EDBs are constructed in both uniform shapes (e.g. trapezoids) and non-uniform,
irregular shapes. Rectangles and trapezoids are common and these shapes are easily
modeled. Basins are also constructed with irregular shapes to be visually pleasing or to
fit irregular sites. Many design guidelines for EDBs contain requirements for length-towidth ratios (e.g. 1.5:1 specified by CASQA, 2003). The Caltrans BMP Retrofit Pilot
Study (Caltrans, 2004) found little correlation between length-to-width ratio and
concentration reduction as shown in Figure 2-3. As shown, a 3:1 basin seems to treat as
well as an 11:1 basin.
9
Figure 2-3 TSS Concentration Reduction as a Function of Length-to-Width Ratio in
EDBs (Caltrans, 2004)
2.1.3
Inlet and Outlet Design
Inlet structures are typically open pipes or channels that are sized to handle all
inflows. Various measures such as rock slope protection (riprap) may be provided to
prevent scouring or erosion of the basin floor near the inlet (see Figure 2-4). Various
outlet structures have also been used. The standard Caltrans outlet includes an outflow
orifice in a vertical standpipe (see Figure 2-4) and an overflow weir, either sharp-crested
or broad-crested. In some cases, the outlet weir is built into the same vertical outlet
device as the outlet orifice. Most often, the outflow weir is built into the basin wall. To
allow complete draining of the EDB, the orifice is usually placed as close to the invert of
the basin as possible.
10
Figure 2-4 Caltrans EDB at Lake Tahoe. Rock slope protection is visible under the inlet
channel in the background. (Courtesy, John Johnston)
Outflow is controlled by the orifice size which is chosen to provide a specified
drawdown time. Drawdown time is the time required to empty a full basin. Drawdown
times recommended by various agencies range from 24 to 48 hours (see Table 2-2). To
minimize vector (mosquito) breeding, a maximum drawdown time of 96 hours is used by
Caltrans and other state agencies (Caltrans, 2010).
11
Table 2-2 Recommended Drawdown Times
Agency
Michigan Department of Environmental Quality (MIDEQ, 1991)
California Stormwater Municipal Best Management Practice
Handbook, (SWQTF, 1993)
North Central Texas Council of Governments
Residential/Commercial BMP Manual, (NCTCOG, 1993)
Virginia Department of Conservation and Recreation Stormwater
Management Handbook, (VDCR, 1999)
Caltrans Stormwater Quality Handbook: Project Planning and
Development Guide, (Caltrans, 2010)
California Stormwater BMP Handbook: New Development and
Redevelopment, (CASQA, 2003)
Agency
Caltrans BMP Retrofit Final Report (Caltrans, 2004)
Caltrans Stormwater Quality Handbook: Project Planning and
Development Guide, (Caltrans, 2010)
California Stormwater BMP Handbook: New Development and
Redevelopment, (CASQA, 2003)
Recommended
Drawdown Time
24 hours
40 hours
24 hours
30 hours
40-48 hours
48 hours
Maximum Drawdown Time
72 hours
96 hours
72 hours
One drawback to sizing the outlet orifice to pass the full WQV in a specified
drawdown time is that the resulting orifice will allow storms smaller than the design
storm to pass through the system quickly and receive less than optimal treatment.
2.2
Extended Detention Basin Performance
Although EDBs are relatively easy and inexpensive to construct and operate, dry
extended detention basins provide only moderate pollutant removal because
sedimentation is the only major removal mechanism. Several studies report on the
effectiveness of dry extended detention ponds including one recently concluded by
Caltrans (2004). Study results are summarized in Table 2-3. In this study, the lined basin
used a concrete liner. It is suspected that consecutive flows re-suspended settled solids,
12
thus limiting TSS removal efficiency. In contrast, the soil and grass in unlined basins are
thought to prevent most re-suspension (Caltrans 2004). The wet basin showed the best
removal, but it was considerably larger than the WQV, resulting in long detention times.
Table 2-3 TSS Removal Efficiencies (Percent) for Pilot Study
BMPs at full-basin (water quality volume) drawdown time of 72
hours. (Caltrans, 2004)
BMPs Type
Extended Detention Basin (Lined)
Extended Detention Basin (Unlined)
Wet Basin
TSS
40%
72%
94%
Detention Times
In contrast to the drawdown time, which is the time to empty a full basin,
detention time is defined as the time that the stormwater runoff is contained in a basin
regardless of whether the basin fills or not. Multiple agencies require a minimum
detention time of 24 hours (see Table 2-4).
13
Table 2-4 Minimum Detention Time
Agency
Michigan Department of Environmental Quality (MIDEQ, 1991)
American Association of State Highway and Transportation Officials
(AASHTO,1991)
Caltrans Stormwater Quality Handbook: Project Planning and Development
Guide, (Caltrans, 2010)
Federal Highway Administration, Evaluation and Management of Highway
Runoff Water Quality, (FHWA, 1996)
Metropolitan Council, Minnesota Urban Small Sites Best Management
Practices Manual, (Metropolitan Council, 2003).
Natural Resources Conservation Service, NRCS Planning and Design
Manual, (NRCS, 1994)
New Jersey Department of Environmental Protection, Stormwater Best
Management Practices Manual, (NJDEP, 2004)
Stormwater Manager’s Resource Center, Extended Detention Pond Fact
Sheet, (SMRC, n.d.)
Transportation Research Board, Stormwater Management for Transportation
Facilities, (TRB, 1993)
Minimum Detention
Time
24 hours
24 hours
24 hours
24 hours
24 hours
24 hours
24 hours
12 hours
24 hours
Detention time for a storm event can be calculated by the centroid method (Haan,
et al., 1994). In the centroid method the average detention time is the difference between
the centroids of the inflow and outflow hydrographs. Figure 2-5 illustrates the centroid
method.
14
Figure 2-5 Detention Time Calculation Using Hydrograph Centroids (Hann, 1994)
Total Suspended Solids Removal as a Function of Detention Time
Ideally, TSS removal efficiency can be determined by using Stokes’ Law to
calculate the required time for particles to settle. Where settling is not ideal and does not
follow Stokes’ Law, empirical testing is needed (Urbonas and Stahre, 1992). Both settling
theory and laboratory column settling tests suggest that TSS removal increases as
detention time increases (Schueler, 2000c; FHWA, 1996; Grizzard et al., 1986). Study
results reported in the literature and summarized in Table 2-5 indicate that 60 percent of
the total suspended solids settle within 6 hours and that incremental improvements in
removal efficiency with increasing time are relatively small. This can be seen in Figure
2-6, which shows similar trends for several pollutants. Approximately 90 percent of
15
settling is achieved in 48 hrs with the remaining sediments composed of extremely fine
clays and colloidal material (FHWA, 1996).
Table 2-5 TSS Removal Efficiencies(Percent)
6
Grizzard et al., 1986a
60%
Schueler, 1994
60%
Dorman, 1996
70-78%
FHWA, 1996
Schueler, 2000c
60%
Caltrans 2004
Metropolitan Council, 2003
a
Values Approximated from Graphs below.
Settling Time (Hours)
24
48
78%
90%
80%
87 - 92%
75%
90%
81%
85%
72
72%
70%-80%
Figure 2-6 Pollutant Removal as a Function of Detention Time from Laboratory Column
Settling Tests (Grizzard et al., 1986)
16
Detention Time as a Function of Storm Size
Detention time in an EDB is a function of storm characteristics and EDB design.
Ideally, runoff entering an EDB is arrested by the flow restriction built into the outflow
device. Water should accumulate, providing time for sedimentation to occur. Basins are
designed to hold the WQV and the outlet orifice is sized to empty a full basin in a given
drawdown time. When the basin is not full (i.e. in a small storm), the water exits
relatively quickly, leading to short detention times. This effect was confirmed by
Alderete using a computer model to simulate EDB operations over a 50-year hydrologic
record (Alderete, 2004). Fu (2008) found the same effect when she used Alderete’s
model to simulate EDBs in different climate regimes. The relationship between detention
time and storm size in Orange County is illustrated in Figure 2-7. Figure 2-7 shows the
effect for four different EDB sizes. The EDBs shown were designed to hold different
fractions of a WQV based on a design storm of 0.6 inches. All were designed to drain
their various volumes within 48 hours. As can be seen, basin size and storm size greatly
affect detention times. For the 100 percent WQV basin (i.e. the standard design volume),
the detention time peaks at nearly 15 hrs for a 1.0 inch storm but is only 8-9 hrs for a 0.6
inch storm and less than 5 hours for a 0.1 inch storm. The small storms escape relatively
quickly through the outlet orifice sized to empty the full basin. For storms larger than
one inch, detention time drops because water is overflowing the basin. For example, in
the basin that contains only 25 percent of the WQV, the detention time peak of more than
16 hours occurs in a 0.5-inch storm. In a 1-inch storm, for instance, the detention time is
only 8 hours because the basin overflows. In this case, the smaller basin and orifice
17
capture and hold the smaller storms effectively while medium and large storms overflow
the basin. At the design storm (0.6 inch) for this location, the longest detention time
occurs in a basin sized to hold 50 percent of the WQV. This represents a happy medium
between a basin that is too small and overflows often, and one that is too big and cannot
retain the runoff because of its relatively large outlet.
Figure 2-7 Detention Time as a Function of Storm Size in Orange County (Fu, 2008)
Alderete (2004) and Fu (2008) calculated volume-weighted and event-weighted
mean detention times based on 50-year simulations. The event mean detention time is
the sum of the detention times for each event divided by the total number of events, while
the volume-weighted mean time is the sum of the products of event detention times and
volumes divided by the total volume over the hydrologic record. As shown in Table 2-6
18
the highest event mean detention time occurs in the smallest basins while the highest
volume-based detention times occur in the 75 percent or 100 percent WQV basins. These
results reflect the effects of both the basin size and the distribution of storm sizes at these
locations. Small basins with small outlet orifices accumulate and empty slower in
numerous small storms which results in long event mean detention times. . Conversely,
because a large fraction of the annual volume is generated by large storms that overflow
small basins, volume-weighted mean detention time increases as basin size increases.
Table 2-6 Summary of Detention Timesa
Simulation
Description
Overflow Volume
(% of Events)
Overflow
Volume
(% of inflow)
Event Mean
Detention
Time (hr)
Volume-weighted
Mean Detention
Time (hr)
San Francisco
100%WQV
8%
10%
5.9
12.4
75%WQV
14%
18%
6.8
12.8
50%WQV
24%
33%
7.9
12
25%WQV
43%
58%
8.4
8.7
Orange County
a
100%WQV
12%
16%
8.6
11.9
75%WQV
21%
25%
9.7
11.8
50%WQV
35%
39%
10.6
10.6
25%WQV
55%
62%
11
7.5
Adapted from Fu (2008)
19
2.3
Two-compartment EDB designs
One approach to increasing the detention times in small storms is to subdivide an
EDB into two compartments. The upstream compartment would act as a small EDB that
would provide long detention times for the numerous small storms. Wasilchen (2007)
modified Alderete’s model to allow two EDBs in series (see Figure 2-8).
Figure 2-8 Two-Cell On-line Trapezoid Basin
20
Simulations were run for 25 percent, 50 percent, and 75 percent of the WQV in
the first basin and 75 percent, 50 percent, and 25 percent WQV in the second basin,
respectively. Wasilchen provided a Look-up table method of modeling irregularly
shaped basins, but modeled only trapezoidal EDBs at the different sizes. In this model,
the outflow from the basin primary cell was always modeled as an unsubmerged orifice.
The depth of water was not tracked in both basins simultaneously and the unaccounted
submerged orifice condition causes an unquantifiable error. This limits the usefulness of
the model because most EDB sites do not have the elevation difference needed to place
the downstream basin far enough below the upstream basin to create an unsubmerged
orifice. Despite the limitations of Wasilchen’s model, the average detention time
increased as the primary cell decreased as expected and shown in Table 2-7.
Table 2-7 Summary of Overflows and Detention Timesa
Simulation
Description
Base-100
PART-75
2
PART-50
Overflow Volume
(% of inflow)
Primary
Overall
Cell
Basin
n/a
16%
Average Detention Time (hr)
n/a
Secondary
Cell
n/a
Primary Cell
Overall Basin
8.61
25%
18%
9.46
0.58
10.04
39%
18%
10.61
2.11
12.72
PART-25
62%
17%
11.02
4.04
15.06
a Adapted from Wasilchen (1999)
b A PART-75 simulation has trapezoidal basins in series. The basins first cell is 75%WQV
and the second cell is 25%WQV.
2
A PART-75 simulation has trapezoidal basins in series. The basins first cell is 75%WQV and the second
cell is 25%WQV.
21
In a more sophisticated model, improved mass removal efficiency was
demonstrated with a two-compartment settling tank (Li et al., 2006). One compartment
was used to store the initial runoff (first flush only) and to prolong the period of settling.
The second compartment operated under continuous flow conditions for the remainder of
the runoff (see Figure 2-9). In this model, TSS removal was modeled by applying
empirical settling velocities to various particle size ranges and fractions observed in
Southern California runoff. Different design storms, ranging from 1.6 to 26 mm total
rainfall, and different relative compartment sizes were modeled. Only 16 storm events
over a single season were simulated. Figure 2-10 shows overall particle removal as a
function of total basin size (expressed as the design storm, DS) and storage compartment
size (expressed as r, the fraction of the total basin volume in the storage compartment).
For the hydrologic record simulated, as design storm increased overall particle removal
increased, from 70 percent to 80 percent. This is understandable. Larger basins retain
stormwater volumes longer. What is less understandable is the apparently small effect of
changing the relative size of the storage compartment. As shown in Figure 2-10, in a
settling tank sized for a 13-mm design storm with a storage compartment of 20 percent
and an 80-percent continuous flow compartment, the removal efficiency is about 75
percent (reading from the graph). Increasing the storage compartment to 80 percent of
the total basin volume increased the TSS removal efficiency to only about 80 percent.
Nevertheless, Li et al. (2008) concluded that the optimal ratio of storage to continuous
flow compartment size was 3:1. It is worth noting that that the compartments modeled by
22
Li et al. are arranged in parallel. The model created in this project arranges the
compartments in series.
Figure 2-9 Two-Compartment Sedimentation Tank(Li et al., 2006)
Figure 2-10 Total particle reduction rate for different design storm size (Li et al., 2008)
23
2.4
Previous Computer Models
In this project an existing EDB simulation model is modified to handle irregular
basin shapes and an internal partition. What follows is a description of the existing
model and other projects based on it.
2.4.1
DBSIM1A - Detention Basin Simulation Model version 1A
A simulation model for an online single cell trapezoidal EDB was developed by
Alderete (2004). DBSIM1A is a spreadsheet application using Microsoft Excel 2003 and
Microsoft Visual Basic for Applications (VBA) version 6.3. As seen in Figure 2-11,
DBSIM1A utilizes worksheets to store intermediate and final results used in incremental
cycling through rainfall events. Reading and writing to the worksheets is a workable
approach but it significantly slows simulation run times. The inputs variables,
calculations, and flow charts for DBSIM1A are included in Chapter 3 modified to reflect
the DBSIM3A.
Figure 2-11 DBSIM1A Code Interaction with Worksheets(Alderete, 2004)
24
Based on a mass balance, hourly time step approach, DBSIMIA simulates the
hydrologic and hydraulic operations of an EDB designed for stormwater capture and
treatment. The change in storage volume is calculated as the inflow volume minus the
outflow volume for each time step. Full rainfall volume is assumed to arrive in the
detention basin within that time step and no hydraulic routing calculations are performed.
Similarly, outflows are calculated hourly based on the conditions at the beginning of the
time step. The computer model is designed to be a planning tool, so the detention basins
are trapezoidal in shape so the volume–depth relationship can be described algebraically.
Properties, characteristics, and calculations that were not considered include:

Evaporation, percolation and infiltration;

Irregular shapes;
The model assumes that runoff is directly proportional to rainfall and an infinitely
sized influent device has the capacity to convey inflows of any storm event.
The model also assumes that the riser and basin walls are of infinite height and
never overflow. The only overflow occurs through the outlet weir. Overflow volumes
are always be calculated with the overflow weir equation.
2.4.2
Single Cell On-line Trapezoid Basin with multiple datasets
Fu simulated basin operations for five different California rainfall datasets using
DBSIM1A with no modifications to the VBA code. Simulations included basins sized at
25 percent, 50 percent, 75 percent, and 100 percent of the WQVs for the different
locations. The variation of mean detention times between sites was relatively small,
25
ranging from11.9 to 13.1 hours for the 100 percent WQV basin (Fu, 2008). Like
Alderete, Fu found that reducing the basin size increased the frequency; volume of
overflows; and the event mean detention time. Conversely, the volume-weighted mean
detention time decreased with reduced basin size. Also, small basins showed longer
event detention times than large basins for small storms; and large basins showed longer
event detention times than small basins for large storms.
2.4.3
DBSIM2 - Detention Basin Simulation Model version 2
DBSIM2 is a modification of DBSIM1A by Wasilchen (2007). Two
modifications were made: (1) enabling two basins to be operated in series (to simulate an
internal partition) and (2) providing a Look-up Table method of modeling an irregularlyshaped basin. Specifically, a depth-volume relationship stored in a Look-up Table is
used in place of the trapezoid formula in DBSIM1A.
The volume equation used to calculate the Look-up Table's volumes for a depth-step
interval is taken from Chow (1959):
4

V   Z 2 D 3   Z ( L  W ) D 2  WLD
3

where:
V=Volume of trapezoidal basin (ft3)
Z= the size slope ratio
D= the basin depth
L=the basin length, and
W=the basin width.
26
Simulations for 25 percent, 50 percent, and 75 percent of the WQV in the first
basin paired with 75 percent, 50 percent, and 25 percent of the WQV in the second basin,
respectively, assessed the effectiveness of two EDBs operated in series. The two EDBs
operating in series capture all of the WQV (i.e. 100 percent WQV).
A limitation of DBSIM2 is that the depth of water and thus the volume are
underestimated. The Look-up Table function chooses the smallest volume that is closest
to the Current Basin Volume (CBV) rather than the actual value. This is a limitation to
the Excel Lookup function. In addition, the Look-up Table interval increment method is
not practical for actual field conditions. The Lookup Table method was determined to be
fairly accurate if depth intervals of 0.5 cm were used, but that required over 4,500 known
data points. When a wider interval was used, errors increased. Figure 2-12 is a graph of
errors between the Base-100 case (using the algebraic trapezoid equation) and three
simulations that vary Lookup Table intervals (15 cm, 5 cm, and 0.5 cm). As seen in
Figure 2-12, the 15-cm and 0.5-cm interval depths yield a detention time errors of 41.7
percent and 0.35 percent respectively. This error, coupled with the inaccuracies of the
orifice flow calculations, limits the usefulness of the model.
27
Figure 2-12 Comparison of BASE-l00 and TABLEBASE Simulations (Wasilchen, 2007)
Furthermore, retrieving the volumes via worksheet spreadsheet via Look-Table
increased the runtime ten-fold over DBSIM1A, requiring several minutes to complete
each simulation. To prevent an Excel application crash during the long simulation
runtime, the default auto save function provided by most operating systems needed to be
disabled.
2.4.4
DBSIM3A -- Proposed Computer Model Enhancements
The objective of this project is to create a computer simulation model for EDBs
with irregular shapes and an internal partition. The internal partition is expected to
28
increase the hydraulic detention time for storms smaller than the design storm that make
up the majority of California storm events. DSBSIM3 will enhance previous versions as
follows:
1. The Look-up function with discrete intervals used to calculate the irregular basins
depth-to-volume relationship in DBSIM2 will be replaced with a depth-to-volume
equation based a known number of basin areas at respective depths for improved
accuracy and usability.
2. The partitioning feature will be enhanced to track water depths in both basins
simultaneously and account for the submerged orifice condition.
The VBA code will store results in arrays rather than in worksheets while the
program steps through rainfall data. After the hydrographs and detention times for all
events are completed, a single write statement will post the results to the appropriate
worksheet. This will allow a depth of water in both cells to be tracked simultaneously
and the simulation run time will be decreased from several minutes to seconds.
Proposed Two-Cell On-line Irregular Shape Basin with Internal Partition Wall
For this project, the system basin is the combination of both the primary and
secondary cell that captures the entire design storm WQV (i.e. 100 percent WQV).
Simulations for 25 percent, 50 percent, and 75 percent of the WQV in the first cell with
75 percent, 50 percent, and 25 percent WQV in the second cell, will be used to assess the
29
effectiveness of basin partitioning. The factor to be compared among the various
configurations is hydraulic detention time.
As noted, these simulations will utilize irregular shape depth to volume equations
to calculate the depth of the simulated basin at any time. Single-cell simulations for 25
percent, 50 percent, and 75 percent of the WQV will be used to validate the mathematical
method used to calculate the irregular shape depth to volume. Alderete’s DBSIM1A
simulations with the Orange County hydrologic data set will be the primary comparison
for the validation. The partition wall component will be validated with spot check
calculations for selected storm events.
2.5
Mathematical Methods for Calculating Volumes of Irregular Shapes
There are many methods to calculate the volume of basins, ranging from
simplistic rules of thumb and shape estimations used to size agricultural ponds
(Department of Primary Industries, Victoria, 2009) to very complicated mesh equations
and models developed for infiltration models (Strelkoff et al., ASCE). The goal of this
project was to allow the user to enter a practical number (2-11) of known basin areas at
specified depths to calculate the volume of an irregularly shaped basin. Several formulas
were required to provide accurate depth-to-volume calculations.
The Newton-Cotes rules, named after Isaac Newton and Roger Cotes, are a group
of formulas or numerical integration techniques useful if the values of the integrands are
at equally spaced points. The technique is applied to an unknown volume function, such
as an irregularly shaped basin, with many polynomials. The unknown basin function can
30
be obtained by summing all the polynomials. The volumes are calculated by weighting
coefficients at given function values, such as area at equal depths. Table 2-8 provides a
list of optimal formulas for different numbers of known data points. These formulas are
coded into the DBSIM3A computer model using an array modeled after Figure 2-13.
31
Table 2-8 Depth calculation based on the number of known Areas. (Weisstein, undated
Wolfram Web Resource)
Number of known
Points
2-point
Trapezoid rulea

x2
3-point
Simpson's rulea

x3
4-point
Simpson's 3/8 rulea

x4
5-point
Boole's rulea

x5
6-pointb
Formula
x1
x1
x1
x1

x6

x7
x1
7-pointb
x1
8-pointb

x8

x9

x10

x11
x1
9-pointb
x1
10-pointa
x1
11-point
x1
a
b
f ( x)dx 
1
h f 1  f 2 
2
f ( x)dx 
1
h  f1  4 f 2  f 3 
3
3
h  f1  3 f 2  3 f 3  f 4 
8
2
f ( x)dx 
h 7 f1  32 f 2  12 f 3  32 f 4  7 f 5 
45
f ( x)dx 
f ( x) dx 
5
h 19 f 1  75 f 2  50 f 3  50 f 4  75 f 5  19 f 6 
288
f ( x)dx 
 41 f1  216 f 2  27 f 3  272 f 4  27 f 5 
1

h 
140   216 f 6  41 f 7

f ( x)dx 
 751 f1  3577 f 2  1323 f 3  2989 f 4  2989 f 5 
7

h 
17280   1323 f 6  3577 f 7  751 f 8

f ( x)dx 
 989 f1  5888 f 2  928 f 3  10496 f 4  4540 f 5 
4

h 
14175   10496 f 6  928 f 7  5888 f 8  989 f 9

f ( x)dx 
f ( x)dx 
2857 f1  f10   15741 f 2  f 9   1080 f 3  f 8 
9
h

89600  19344 f 4  f 7   5778 f 5  f 6 

16067 f1  f11   106300 f 2  f10   48525 f 3  f 9 
1
h

299376  272400 f 4  f 8   260550 f 5  f 7   427368 f 6 
Ueberhuber 1997, p. 100
Abramowitz and Stegun 1972, p. 886
32
Figure 2-13 Coefficients for formulas from 1 to 10 points.
(http://digilander.libero.it/foxes/integr/Integration_Newton_Cotes.htm 4/)
33
Chapter 3
3. METHODS
METHODS
The scope of this project included the development of a Miscrosoft Excel (version
2007) with Visual Basic for Application (VBA) computer model to simulate the
operation of an irregularly shaped extend detention basin (EDB) with a partition wall.
The computer model created in this project, Detention Basin Simulation Model version
3A (DBSIM3A), builds on Detention Basin Simulation Model version 1A (DSIM1A)
developed by Alderete (2004). The DBSIM1A computer model simulated the operation
of a trapezoidal EDB utilizing different outlet structures and basin sizes. Building upon
DBSIM1A, the DBSIM3A computer model simulates the operation of irregularly shaped,
partitioned EDB with varying treatment cell volumes and outlet orifice sizes.
3.1
Theoretical Basis of the Model
DBSIM3A simulates the hydrologic and hydraulic operations of an EDB designed
for stormwater quality improvement. It uses a mass balance approach with an hourly
time step. For each time increment, the change in storage volume equals the inflow
volume minus the outflow volume. As shown in Figure 3-1, stormwater runoff exits the
basin either through the orifice in the outlet structure or over the overflow weir3. For a
two-cell, partitioned basin the stormwater runoff enters the primary cell, passes through
the partition to the secondary cell via an orifice or an overflow weir, and exits the basin
through the orifice in the secondary cell outlet structure or over the overflow weir. The
3
Storm event phenomena that occur on a minute-by-minute basis, evaporation, and infiltration are not
accounted for in DBSIM3A—consistnent with DBSIM1A.
34
two-cell detention time is the difference between the centroids of the primary cell inflow
and secondary cell outflow hydrographs. The centroid method is illustrated in Figure 25.
Figure 3-1 Mass Balance of Simulated Irregularly shaped Extended Detention Basin
35
3.2
Types of Input and Output Data
The DBSIM3A framework includes the following parts:

A Microsoft Visual Basic for Applications executable program4

A Microsoft Excel worksheet which contains the rainfall data

A Microsoft Excel UserForm which contains both the trapezoid and
irregularly shaped EDB design variables

A Microsoft Excel UserForm which contains the treatment results and
overflow storm events.

Microsoft Excel worksheets which contain the detention times, or
hydrographs, and treatment results.
One UserForm is used by DBSIM3A. The Input tabs provide all the input
variables utilized by DBSIM3A. The Rainfall worksheet provides the rainfall data that is
routed through the simulated EDB. DBSIM3A writes all of the output data to the
Hydrographs worksheet and to the Detention Times worksheet for post-processing.
DBSIM3A also writes summary results back to the UserForm Results tabs as well as the
Results worksheet if desired. All UserForms are discussed in greater detail later in this
chapter.
4
The VBA program code can be viewed using the developer add-in. The developer add-in is supplied
standard with Microsoft Excel 2007 but is not preloaded.
36
3.2.1
Input Data – EDB Design Variables
As presented in Figure 3-2, the boxes in the Input tabs of the UserForm contain
the input data which are entered by the user for one- and two-cell basins. The three
categories for the input variables are site characteristics, basin characteristics, and outlet
characteristics. Table 3-1 shows the list of input variables that are common with
DBSIM1A (Alderete, 2004).5. The list of additional input variables for the irregularly
shaped single cell basin area and depth characteristics are shown on Table 3-2. The
boxes in the Input tabs of the UserForm that contain the input data entered by the user for
an irregularly shaped two-cell basin are presented in Figure 3-3.
5
Per Alderete (2004), many of the design variables values came from Caltrans design guidance documents
since the EDB simulated in this project represents a hypothetical EDB that would be designed by Caltrans
project engineers.
37
Figure 3-2 UserForm Input Tabs for Single Cell Basin
Figure 3-3 UserForm Input Tabs for Two-cell Basin
38
39
Table 3-1 Input Variables Common with DBSIM1A (Alderete, 2004)
Site Variables
Drainage Area
The drainage area is all the land area from which runoff may run to
a common (design) point. The value of 2.4 ac (1 ha) is arbitrarily
chosen6.
Runoff Depth
The runoff depth is a design number used to calculate the WQV. 7
Runoff Coefficient
The runoff coefficient is a value derived from site characteristics
that is applied to a given rainfall volume to yield a corresponding
runoff value8.
Basin Characteristic Variables – Trapezoidal Basin
Length-to-Width Ratio
The length-to-width ratio, for this project, refers to the ratio of the
length of the basin invert to the width of the basin invert. 9
Slope
The slope is the horizontal-to-vertical ratio (H:V) of the sides of the
basin. For the DBSIM1A project, a constant slope around the basin
was selected.10
Depth of DV in Basin
This variable is the depth of water in the basin when the design
volume is in the basin. The value of 1 m (3.3 ft) is arbitrarily
chosen.
Treatment Volume
The treatment volume is the percentage of WQV to be contained in
the basin. For this project, this variable is set to 100%. Alderete
simulated 75%, 50%, and 25% as well.
6
However, the intent of this value is to represent a typical Caltrans catchment—small, impervious drainage
areas with short times of concentration.
7 The value of 0.6 inch came from Caltrans Basin Sizer (Caltrans, 2001) for Orange County, CA. Basin
Sizer is a computer program developed for Caltrans project engineers to size volume-based stormwater
BMPs. This runoff depth is a site-specific value. The runoff depth for this project is calculated based on
local rainfall data, the basin drain time, and the runoff coefficient for the drainage area.
8 The value chosen, 0.9, represents a typical Caltrans drainage area—small, impervious drainage areas with
short times of concentration.
9 The value of 2 (i.e., 2:1) is consistent with Caltrans design criteria for EDBs (Caltrans, 2002b).
10 The value of 3 (i.e., 3:1) is consistent with Caltrans design criteria for EDBs (Caltrans, 2002b).
40
Table 3-1 (cont’d)
Outlet Characteristic Variables 11
Weir Type
The weir type is defaulted to a broad-crested weir for single cell basin
simulations but it is selectable for either broad-crested or sharp-crested12. For
this project, the primary cell weir is defaulted to sharp-crested13 and secondary
cell weir is defaulted to broad-crested.
Weir Length
The weir length is arbitrarily set at 10 ft.
Weir Breadth
The weir breadth is arbitrarily set at 10 ft.
Weir Discharge
Coefficient
The weir discharge coefficient is an empirically determined multiplier that
accounts for a number of hydraulic factors difficult to describe explicitly. 14
Orifice Drain Time
The orifice drain time is the time it takes for the design volume to discharge
through the orifice. This value is used to size the orifice opening. 15 For this
project, the default value is equal to 48 hr.16
System Drain Time
The system drain time is the total time it takes for the design volume to discharge
from the EDB.17
Riser Pipe Diameter
The value is for information only. The model assumes an outlet riser of infinite
height such that runoff in excess of the design volume is routed out of the basin
over the overflow weir, NOT into the top of the outlet riser.
Number of Orifices
The number of orifices is arbitrarily set to 1.
Orifice Discharge
Coefficient
Orifice Diameter
The orifice discharge coefficient is a dimensionless proportionality constant
which accounts for the reduction of flow due to entrance head loss. The orifice
discharge coefficient value of 0.6 selected is taken from Mays (2001) and is
consistent with Caltrans design criteria for EDBs (Caltrans, 2002b).
The orifice diameter is sized according to the orifice drain time. See Chapter 4
for sizes used in the DBSIM3A simulation.
For a single cell, as seen in Figure 3-2, outlet characteristics should be entered under the “Single Basin
Outlet/ Primary Cell Basin Outlet”. For two-cell simulations, as seen in Figure 3-3, outlet characteristics
should be entered under (1) the “Single Basin Outlet/ Primary Cell Basin Outlet” for the primary cell and
(2) the “Secondary Cell Basin Outlet” for the secondary cell.
12 The weir equation in DBSIM1A is based on a broad-crested weir.
13 The sharp-crested weir is designed into the partition wall.
14 The weir discharge coefficient value of 2.64 is from Gribbin (2001).
15 If the HRV function is on, the value is equal to 24 hr. If the HRV function is off, the value is equal to 48
hr.
16
A hold-and-release (HRV) outlet valve is included in DBSIM1A. This device is not simulated in this
project, even though the program supports this function.
17 . If the hold-and-release valve function is on, the system drain time equals the valve hold time plus the
orifice drain time. If the hold-and-release valve function is off, the system drain time is equal to the orifice
drain time. The value of 48 hr is consistent with Caltrans design criteria for EDBs (Caltrans, 2002b).
11
41
Table 3-2 Additional Input Variables for Irregular Shapes
Variable Name
Description
Basin Characteristic Variables – Irregular Shape 18
Number of Known
Areas
This number can be between 2 and 11. The default value is 11, the maximum
number of inputs allowed. If a lower number is specified, then the unused area
and depth boxes become inactive.
Area0 Through 10
Depth0 Through 10
The area and depths for an irregular shape, as depicted Figure 3-9. These values
are used to calculate the volumes at each level using the Newton – Cotes rules.
The calculated volumes and respective depths are placed in a Lookup array.
3.2.2
Input Data – Rainfall Data
The rainfall data comes from a rain gauge located in Orange County, California,
and the hourly rainfall data spanned 1948 to 199819.
3.2.3
Output Data – Summary Information
Output summary information from the simulation is generated and written to the
Results UserForm tabs (Figure 3-4) as well as results worksheets.
The summary
information includes (1) water balance data (i.e. total inflow and outflow volumes), (2)
treatment data (i.e. total overflow volume, total treated outflow volume, average
detention time), and (3) storm event distributions data (i.e. number of storms, number of
For a single cell, as seen in Figure 3-2, values for these variables should be entered under the “Irregular
Surface Area – Single/Primary”. For two-cell simulations, as seen in Figure 3-3, values for area and depth
are entered under (1) the “Irregular Surface Area – Single/Primary” for the primary cell and (2) the
“Irregular Surface Area – Secondary” for the secondary cell.
19
Per Alderete (2004), “the rainfall data utilized in DBSIM1A came from the National Climatic Data
Center (National Oceanic and Atmospheric Administration) rain gauge Laguna Beach 2. The rainfall
record consists of 50 years of hourly rainfall data, from 1948 to 1998, at the rain gauge located in Orange
County, Southern California. This rain gauge was selected because of its proximity to the Caltrans SR-73
pilot projects. Prior to 1965, rainfall data was recorded to the nearest 0.01 inch. After 1965, rainfall data
was recorded to the nearest 0.1 inch. For DBSIM1A, the rainfall record was adjusted to round the data
prior to 1965 to the nearest 0.1 inch.”
18
42
overflows, the ratio of overflows to number of storms). The total inflow and outflow
volumes are compared in Chapter 4 to confirm that DBSIM3A properly accounts for all
the stormwater. In Figure 3-5, the results for a two-cell irregularly shaped partitioned
basin are shown. The results for the individual primary and secondary cells are also
generated and reported on both the UserForm and the worksheets. To reduce the file size
and run time, the hydrographs, detention times, and worksheet can be deselected and only
the results worksheet generated as seen in Figure 3-6.
43
Figure 3-4 UserForm Result Tabs for Single Cell Basins
44
Figure 3-5 Example of UserForm Result Tabs for Two-cell Basin
3.2.4
Simulations
DBSIM3A simulates the operations of an irregularly shaped partitioned basin
with primary cell sized for different design volumes. Four validation simulations were
conducted for this project, as shown in Table 3-3 to validate the single cell irregular
shape with varying area and depth data against Alderete single cell trapezoidal shape with
an algebraic depth-volume function. Five EDB performance simulations were conducted
for this project, as shown in Table 3-4 to validate the single cell irregular shape against
Alderete. For convenience, simulation inputs are preloaded and selectable as seen in
Figure 3-6. Simulation results are discussed in Chapter 4.
45
Figure 3-6 UserForm Validation and Simulation Tab
Table 3-3 DBSIM3A Single Cell Simulations for Validation
Basin Shape
Design
Volume
(% of
WQV)
Outlet
Orifice
Diameter
(in)
Number of
Data Points
Base-100
Trapezoid
100 %
1.1406
N/A
OneCell-100
Trapezoid
100 %
1.1406
N/A
OneCell-100-11pt
Irregular Shape
100 %
1.1406
11
OneCell-100-6pt
Irregular Shape
100 %
1.1406
6
OneCell-100-3pt
Irregular Shape
100 %
1.1406
3
Simulation
Name
46
Table 3-4 DBSIM3A Two-cell Simulations for EDB Performance
Simulation
Name
Base-100
(Trapezoid)
TC-100-75:25
(Irregular)
TC-100-50:50
(Irregular)
TC-100-25:75
(Irregular)
TC=TwoCell
3.3
Secondary
Cell
Orifice
Diameter
(in)
Primary
Cell
Design
Volume
(% of
Basin
WQV)
Secondary
Cell
Design
Volume
(% of Basin
WQV)
Design
Volume
(% of
WQV)
Partition
Wall
Primary
Cell
Orifice
Diameter
(in)
100 %
No
1.1406
N/A
100 %
100 %
100 %
Yes
0.9744
1.1406
75 %
25 %
100 %
Yes
0.7825
1.1406
50 %
50 %
100 %
Yes
0.5327
1.1406
25 %
75 %
Program Description
The DBSIM3A program builds on the Alderete’s DBSIM1A. The DBSIM3A
computer model logic diagrams and calculation are described below.
DBSIM3A model has a pre-calculation component that (1) calculates the design
volume based on the runoff and (2) determines the trapezoidal basin dimensions based on
the design volumes and desired trapezoidal shape ratio inputs. The hourly computations
included are (1) hourly rainfall data converted to inflow data, (2) outflow volumes
calculated using the weir and orifice equations, and (3) basin volume calculated to
determine the end of cycle (i.e., when the basin is empty).
47
3.3.1
VBA Program Logic
The logic diagrams summarizing the program simulation for (1) program
overview, (2) the cycle of hourly computations for single cell irregularly shaped basin
and (3) the cycle of hourly computations for two-cell irregularly shaped basin.
Program Overview
DBSIM1A: (1) retrieves the hourly rainfall data from a worksheet and converts it
to inflow data; (2) routes the inflow data into the computer model to assess how much
stormwater is stored and how much leaves the EDB,20 (3) calculates the total outflow
and writes it to worksheets; (4) separates the outflow into two components (weir
overflow and orifice outflow) and writes the results to worksheets; (5) calculates the
inflow and outflow hydrographs for each storm event and writes the results to a
worksheet; and (6) calculates the detention time for each storm event from the centroids
of the inflow and outflow hydrographs and writes the results to a worksheet.
A modified DBSIM1A logic diagram summarizing the DBSIM3A program
overview is presented in Figure 3-7. Modifications to the logic diagram are shown in
shaded boxes. The DBSIM3A modifications are as follows:

Retrieves the input variables from the Input tabs on the UserForm.

Calculates all simulations within VBA application modules rather than
worksheets. No calculations are performed on worksheets.
20
Alderete’s volume calculations are based on a trapezoidal basin.
48

Writes the hydrograph and detention times to arrays. If the worksheet option is
selected, information stored in the arrays is written to a worksheet.
A storm event is defined as the period between the start of rainfall and the time that
the EDB is empty. The hourly computational cycle calculates the detention time and
flows until the basin is emptied.
49
Figure 3-7 DBSIM3A Program Logic Modified subroutines highlighted is shaded.
50
Hourly Computations – Single Cell Basin
The hourly computations are summarized in the flowchart shown in Figure 3-821.
Again, the DBSIM1A processes that have been modified in DBSIM3A are shown in
shaded boxes. The hourly computational cycle continues until the EDB is empty. A
storm event is defined as the period between the start of rainfall and the time that the
EDB is empty.
The DBSIM3A hourly computation modifications are as follows:

The site and basin characteristics calculations are within VBA application
modules rather than worksheets. No calculations are performed on worksheets.

Basin volume calculations include irregular shapes as well as the original
trapezoidal algorithm. Irregular shape volumes are stored in relationship to their
depth in an array.

Calculation of the height of water in the basin (Hw) is based on a Excel Look-up
function applied to the volume array.

Sharp-crested weir selection was added as an additional overflow option.

The hydrograph and detention times are written to arrays. If the worksheet
option is selected, information stored in the array is written to a worksheet.
21
The HRV feature in DBSIM1A is still functional in DBSIM3A but has been removed from the logic
diagram because it is not used in this project.
51
Figure 3-8 DBSIM1A Single Cell Hourly Computations for a Storm Event modified by
DBSIM3A. Modified subroutines are shaded.
52
Hourly Computations – Two-cell Basin
The hourly computations for the two-cell basin are described in Table 3-5. The twocell hourly computations include determining the flow between the primary and
secondary cells using the calculated height of each basin to determine the head used in
the primary cell orifice equations. The primary cell basin volume is determined by the
(1) rainfall inflow volume and (2) outflow volume which includes both the outflow
through the primary cell orifice and the overflow over the partition wall weir. The
secondary cell basin volume is a determined by the (1) primary cell outflow volume and
(2) outflow volume which includes both the outflow through the secondary cell orifice
and the overflow over the secondary cell weir. The total basin volume is determined by
the (1) rainfall inflow volume and (2) outflow volume which includes both the outflow
through the secondary cell orifice and the overflow over the secondary cell weir.
53
Table 3-5 DBSIM3A Two-Cell Basin Cycle of Hourly Computations Description
Primary Cell Calculations
1. Convert rainfall to inflow volume (IV).
2. Calculate the Primary cell Current Basin Volume (CBV) using the rainfall inflow
volume.
3. Calculate the Primary cell current water height (Hcur) using CBV.
4. Check if primary cell water height is less than zero. If Hcur<0, then the primary cell
is empty and the storm is over.
5. Check if current height in the primary cell (Hcur) is less than or equal to overflow
weir location (Hwqv). If (Hcur Hwqv), then go to Step 6. Else go to Step 9.
6. Calculate the primary cell orifice flow (OQ) using primary cell orifice diameter (do)
and the primary and secondary cell water heights (Hcur and PSCHcur). The model
checks for and prohibits backflow, so if PSCHcur > Hcur then the primary cell
orifice outflow is set to zero.22
7. Calculate primary cell orifice outflow volume (ODV).
8. Check if height of water over the primary cell weir (Hw) is greater than zero. If
(Hw>0) then calculate weir overflow volume (WDV). Then go to Step 9; and if not,
then don’t calculate WDV and then go to Step 9.
9. Calculated Primary Cell total outflow (BQ).
10. Calculate Primary Cell Outflow volume (BDV) which is equal to primary cell orifice
outflow volume (ODV) and weir overflow volume (WDV).
11. Calculate new primary cell current basin volume (CBV) which is the current basin
volume minus the total outflow (CBV= CBV-BDV)
22
The water height of the secondary cell should not be higher than the primary cell; however, it does occur
less than 1% of the time. Though insignificant, the reason for the calculation error is probably the hourly
step function.
54
Cont. Table 3-5 DBSIM3A Two-cell Basin Cycle of Hourly Computations Description
Secondary Cell Calculations
A. Set Secondary Cell Inflow Volume (PSCIV) to Primary Cell Outflow Volume
(BDV) which is equal to primary cell orifice outflow and weir overflow volumes.
B. Calculate the Secondary Cell Current Basin Volume (PSCCBV) which is the
secondary cell volume (PSCIV) and the current basin volume (PSCCBV). PSCCBV
is set equal to zero for the first time increment of a storm.
C. Calculate the secondary cell current water height (PSCHcur) using PSCCBV.
D. Check if secondary cell water height is less than zero. If PSCHcur<0, then the
secondary cell is empty. Go to Step E.
E. Check if current height in the secondary cell (PSCHcur) is less than or equal to
overflow weir location (PSCHwqv). If (PSCHcurHwqv) , then Step F. Else go to
Step I.
F. Calculate the secondary cell orifice flow (OQ) using secondary cell orifice diameter
(do) and the secondary cell water heights (PSCHcur).
G. Calculate secondary cell orifice outflow volume (PSCODV).
H. Check if height of water over the secondary cell weir (PSCHw) is greater than zero.
If (PSCHw>0) then calculate weir overflow volume (PSCWDV) then goto Step I;
and if not, don’t calculate PSCWDV and then goto Step I.
I. Calculate Secondary Cell total outflow (PSCBQ).
J. Calculate Secondary Cell Outflow volume (PSCBDV) which is equal to secondary
cell orifice outflow volume (PSCODV) and weir overflow volume (PSCWDV).
K. Calculate new secondary cell current basin volume (PSCCBV) which is the current
basin volume minus the total outflow (PSCCBV= PSCCBV-PSCBDV). Calculate
new PSCHcur to be applied in Step 6.
55
3.3.2
Site Characteristics Calculations
The site characteristic calculations include drainage area unit conversion and
recommended design volume of the single-cell trapezoidal basin. The site characteristics
and the 50-year historical rainfall data are used to calculate the inflow volumes for the
hourly computation subroutines.
3.3.3
Basin Characteristics Calculations
The basin characteristics calculations involve either the trapezoidal basin
equations from DBSIM1A or the irregularly shaped basin algorithm developed for
DBSIM3A. If a trapezoidal basin is chosen by the user, the model sizes the basin
automatically using the drainage area, trapezoidal basin characteristics (i.e. length-towidth ratio, slope (H:V), basin depth), and the desired treatment volume as a percentage
of selected WQV. If an irregularly shaped basin is chosen, the user-supplied areas and
depths are used (see Table 3-2). The outlet characteristic calculations include unit
conversions and the cross-sectional area of the orifice.
56
Design Volume
The design volume is the volume of water that is ponded in the EDB for treatment
and is calculated as follows:
  1 ft   43560.17ft 2
DV  TV  RO  DA   
  
1ac
  12in  

 

(1)
DV = design volume (ft3)
TV = treatment volume, percentage of WQV23
RO24 = runoff depth, incorporating the runoff coefficient (in)
DA = drainage area (ac)
Irregular Shape Design Volume – Single Cell
Plan and cross-sectional views of a hypothetical irregularly shaped single cell
EDB are shown in Figure 3-9. DBSIM3A allows the user to enter a practical number (211) of known basin areas at specified depths to model an irregular shape. A numerical
integration technique for unknown volume functions, known as the Newton-Cotes
formulas, is then applied. Volumes are calculated by weighting coefficients at given
function values, such as areas at equal depths. Table 3-6 provides a list of optimal
formulas relative to the number of known data points. These formulas are coded into the
DBSIM3A computer model.
23
For a trapezoidal basin, the treatment volume is entered as a percentage and represents some fraction of
the WQV, i.e. 100 percent, 75 percent, etc.
24 The runoff depth in Equation (1) already accounts for a runoff coefficient of 0.9 based on a drainage area
with 100 percent imperviousness.
57
Volumes are calculated from equations V1- V10 (Table 3-6) using the user input
areas and depths entered in the Input tabs shown in Figure 3-2. To reduce simulation
errors, it is recommended that the depths between intervals be equal.
Figure 3-9 Generic Plan and Cross-Sectional Views of an Irregularly Shaped EDB
58
Table 3-6 Newton-Cotes Equations for Volume Calculations in Irregularly Shaped
Basins.
V1 =
1
d (A + A2 )
2 2 1
(V1)
Given: A1 , d1 , A2 , d2
V2 =
1
d (A − 4A2 + 1A3 )
3 3 1
Given: A1 , d1 , A2 , d2 , A 3 , d3
(V2)
V3 =
3
d (A + 3A2 + 3A3 + A4 )
8 4 1
Given: A1 , d1 , A2 , d2 , A 3 , d3 , A4 , d4
(V3)
V4 =
2
d (7A1 + 32A2 + 12A3 + 32A4 + 7A5 )
45 5
Given: A1 , d1 , A2 , d2 , A 3 , d3 , A4 , d4 , A5 , d5
(V4)
V5 =
5
d (19A1 + 75A2 + 50A3 + 50A4 + 75A5 + 19A6 )
288 6
Given: A1 , d1 , A2 , d2 , A 3 , d3 , A4 , d4 , A5 , d5 , A6 , d6
(V5)
V6 =
1
d (41A1 + 216A2 + 27A3 + 272A4 + 27A5 + 216A6 + 41A7 )
140 7
Given: A1 , d1 , A2 , d2 , A 3 , d3 , A4 , d4 , A5 , d5 , A6 , d6 , A7 , d7
(V6)
7
d (751A1 + 3577A2 + 1323A3 + 2989A4 + 2989A5 + 1323A6 + 3577A7
17280 8
+ 751A8 )
Given: A1 , d1 , A2 , d2 , A 3 , d3 , A4 , d4 , A5 , d5 , A6 , d6 , A7 , d7, , A8 , d8
(V7)
4
d (989A1 + 5888A2 − 928A3 + 10496A4 − 4540A5 + 10496A6 − 928A7
14175 9
+ 5888A8 +989A9 )
Given: A1 , d1 , A2 , d2 , A 3 , d3 , A4 , d4 , A5 , d5 , A6 , d6 , A7 , d7, , A8 , d8, , A9 , d9
(V8)
9
d (2857(A1 + A10 ) + 15741(A2 + A9 ) + 1080(A3 + A8 ) + 19344(A 4 + A7 )
89600 10
+ 5778(A5 + A6 ))
Given: A1 , d1 , A2 , d2 , A 3 , d3 , A4 , d4 , A5 , d5 , A6 , d6 , A7 , d7, , A8 , d8, , A9 , d9 , A10 , d10
(V9)
5
d (16067(A1 + A11 ) + 106300(A2 + A10 ) − 48525(A3 + A9 )
299376 11
+ 272400(A4 + A8 ) − 260550(A5 + A7 ) + 427368A6 )
Given: A1 , d1 , A2 , d2 , A 3 , d3 , A4 , d4 , A5 , d5 , A6 , d6 , A7 , d7, , A8 , d8, , A9 , d9 , A10 , d10 , A11 , d11
(V10)
V7 =
V8 =
V9 =
V10 =
59
Irregular Shape Design Volume – Two-cell
The volume calculations use the same methods as described in the single-cell
model above. The user-supplied areas and depths are entered in the Input tabs shown in
Figure 3-3.
3.3.4
Hourly Calculations
Calculations performed each hour are described below.
Inflow Volume
The hourly rainfall is converted to hourly inflow volumes using:
 1ft 
Vi  C RO  ri  DA  

 12in 
Vi = inflow volume at time i (ft3)
CRO = runoff coefficient
ri = rainfall at time i (in)
DA = drainage area (ft2)
(2)
The inflow volume is routed into the simulated EDB and is used to calculate the
depth of water in the EDB.
60
Height of Basin
For an irregularly shaped basin, the depth of water as a result of the inflow
volume is calculated using a Lookup function applied to an array populated with the
result of equations (V1) to (V10) and respective depths. Equation (3) contains the linear
interpolation method used to calculate the current height of water in the basin (hcur)
given current basin volume.
(d − d )
hcur = da + (Vb − Va ) (Vb − Va ) at the point (V)
a
b
(3)
V=current volume
Va = volume on look-up table below current volume
Vb = volume on look-up table above current volume
da = depth on look-up table relative to Va
db= depth on look-up table relative to Va
Outflows and overflows
With the height of water in the EDB known, the outflow is calculated with the
following equation based on basin type:
For Single Cell Basin or Two-cell Secondary Cell
OQi  Ao  Cd 


2  g  h cur    3600 s 
 1 hr 
OQi = orifice flow at time i (ft3/hr)
Cd = orifice discharge coefficient
g = gravitational acceleration (ft/s2)
(4)
61
For Two-cell Primary Cell
OQi  A o  C d 


2  g  PPCh cur  PSCh cur    3600 s 
 1 hr 
(5)
OQi = orifice flow at time i (ft3/hr)
Cd = orifice discharge coefficient
g = gravitational acceleration (ft/s2)
PPChcur = Current height of Primary Cell
PsChcur = Current height of Secondary Cell
For both equations, A0 is the area of the orifice, calculated from:
Ao 
π 2
do
4
(6)
Ao = area of each orifice (ft2)
do = diameter of the orifice in the riser pipe (ft)
DBSIM3A checks to see if the height of water in the EDB is greater than design
height, hDV. If the height is greater, overflow occurs over the weir, and outflow is
calculated based on the weir selection25 as follows:
25
A sharp-crested weir has a sharp upstream edge formed so that the nappe flows clear of the crest. It is
used for the primary cell in two-cell simulations. Broad-crested weirs have crests that extend horizontally
in the direction of flow far enough to support the nappe and fully develop hydrostatic pressures for at least
a short distance. It is used for the single-cell simulation and for the secondary cell in two-cell simulations.
62
For a Broad-Crested Weir

WQi  Cw  L w  h w
1.5
s

  3600
1 hr 

(7)

WQi = weir flow at time i (ft3/hr)
Cw = weir coefficient
Lw = length of broad-crested weir (UNITS)
hw = height of stormwater above the design volume depth (ft)
h w  h cur  h DV
hDV = depth of design volume in basin, as defined in Table 3-1 (ft)
(8)
For a Sharp-Crested Weir

WQ i  C wsc  L w  .1  n  h w   h w
1.5
s

  3600
1 hr 


(9)
WQi = weir flow at time i (ft3/hr)
Cw = weir coefficient
Cwsc = 2/3 Cw (2g)1/2
Lw = length of broad-crested weir (ft)
n= number of sides = 2
hw = height of stormwater above the design depth (ft) as defined in eq. 8.
Total outflow, also referred to as basin discharge, is calculated as follows:
BQi  OQi  WQi
(10)
BQi = basin discharge at time i (ft3/hr)
All of the outflows calculated are converted to volumes:
WDVi  WQi  t i
WDVi = weir discharge volume at time i (ft3)
ti = time increment i (hr)
ODVi  OQi  t i
ODVi = orifice discharge volume at time i (ft3)
BDVi  BQi  t i
BDVi = basin discharge volume at time i (ft3)
(11)
(12)
(13)
63
Detention Times
For each storm event DBSIM3A creates a hydrographs array and writes the
results to the Hydrographs worksheet if specified by the user. From this information, the
total inflow volume, total discharge volume, total treated volume, and total overflow
volume are determined. The centroids and detentions times are calculated as follows:
Centroid 
 t  Q 
Q
i
i
(14)
i
Qi = inflow or total outflow at time i
Detention Time  Outflow Centroid  Inflow Centroid
(15)
The average detention time over the 50-year hydrologic record is calculated by
summing the detention times for all the storms and dividing by the total number of
storms. The flow-weighted average detention time is calculated by multiplying the
detention time by the total volume for each storm event, summing the products, and then
dividing by the sum of all the inflow volumes.
64
3.4
Limitations of DBSIM3A
Both DBSIM1A and DBSIM3A are relatively simple water accounting models
based on hourly time steps. Runoff routing by hydrologic or hydraulic simulation and
infiltration of stormwater are not taken into account. The models also assume that the
influent pipe(s) are large enough that there is always sufficient capacity to convey the
inflow to the detention basin.
DBSIM3A simulates irregular shapes using Newton-Cotes simplified integral
methods, a more flexible alternative to DBSIM1A model’s trapezoidal equations. A
limitation to the Newton-Cotes rules method is that depth intervals should be equal to
improve accuracy. Using a simple linear interpolation between points on the area-todepth curve yields a smaller error than using polynomial interpolations of the curve.
Using polynomial interpolation, however, is more difficult for novice Excel users and
was abandoned for this project considering that the error can be mitigated by careful
selection of areas and depths. The LINEST worksheet object can be used to determine
the coefficients of the area-to-depth curve and integrate the function into the VBA
program, but it was not used in this project in order to minimize the use of worksheet
objects and speed up the program. A potential future approach would be to develop a
subroutine that mimics the LINEST worksheet object since there is not a current
application object or subroutine that easily performs this function.
65
This project assumes that the primary cell orifice outflow volume is zero when the
height of the water in the secondary cell is greater than the primary cell because of the
insignificant calculation error mentioned above.
Another limitation is assuming that orifice and weir flows are constant over the
hourly time step, and basing their values on the water depths at the beginning of the time
step. Throughout the time step, water levels will decline, which reduces flows, especially
for weirs. A more accurate method that could be implemented in a future project would
be to use an estimate of the expected average depth over the hour. How much error is
introduced by this process is unknown.
66
4.
Chapter 4
RESULTS AND DISCUSSION
RESULTS AND DISCUSSION
Presented in this chapter are the results of DBSIM3A computer simulations. The
simulation results are first used to determine if the computer model is working properly
and then used to determine if the EDB performance for a basin is improved by the
addition of a partition wall. Validation simulations are presented (1) to determine if the
non-uniform volume algorithm is functioning correctly, and (2) to determine if the
partition wall is being simulated correctly. The EDB performance simulations assess the
volume of water treated and the hydraulic detention times of different EDB
configurations subjected to a historic 50-year record of hourly rainfall. The key
components of the EDBs being simulated are summarized in Table 4-1.
67
Table 4-1 Key Components of EDBs Modeled by DBSIM3A 26
26
OneCell
Simulation
Name
Design
Volume
(% of
WQV)
Partition
Wall
Overall
Cell
Orifice
Diameter
(in)
BASE-100
100 %
No
1.1406
OneCell-100
100 %
No
1.1406
Base-75
75 %
No
0.9744
Base-50
50 %
No
0.7825
Base-25
25 %
No
0.5327
TwoCell
Simulation
Name
Design
Volume
(% of
WQV)
Partition
Wall
Primary
Cell
Orifice
Diameter
(in)
Secondary
Cell
Orifice
Diameter
(in)
Primary Cell
Design
Volume
(% of
WQV)
Secondary
Cell
Design
Volume
(% of
WQV)
TC-100-75:25
100 %
Yes
0.9744
1.1406
75 %
25 %
TC-100-50:50
100 %
Yes
0.7825
1.1406
50 %
50 %
TC-100-25:75
100 %
Yes
0.5327
1.1406
25 %
75 %
Nomenclature examples: TC-100-75:25 consists of a non-uniform, two-cell EDB with a design volume
equal to 100% of the WQV (TC-100), a primary cell sized to 75% of the WQV and a secondary cell sized
to 25% of the WQV (75:25). The outlet structure of the primary cell is designed to drain it in 48 hours and
the outlet structure of the secondary cell is designed to drain the whole basin in 48 hours. Base-75 consists
of a trapezoidal, one-cell EDB with a design volume equal to 75% of the WQV and outlet structure sized to
drain the basin in 48 hours.
68
4.1
DBSIM3A Validation
Validation of DBSIM3A will be accomplished by comparing selected simulation
results to the results from DBSIM1A. BASE-100 from DBSIM1A is the base condition
for comparison. The DBSIM1A BASE-100 results were generated by software provided
by Alderete. The various output data from each simulation presented to demonstrate that
DBSIM3A is working acceptably include water balance results (i.e. inflow, outflow, and
overflow volumes), storm event distribution (i.e. the number of storms events and storm
events with overflows) and hydraulic detention times.
All the simulations use the same 50-year hydrologic record, so the total inflow
and outflow volumes are expected to be identical. Overflow volumes are determined by
outflow orifice sizes and storage volumes, so overflow volumes are expected to change
with the addition of a partition wall.
Storm event distributions for one-cell and two-cell EDBs will also be compared.
It is expected that the total number of storms for the irregularly shaped one-cell EDB to
be the same for the base case (a one-cell trapezoid basin of equal size). It is also
expected that the total number of storms in the irregularly shaped two-cell basin
simulation to be fewer than in the one-cell trapezoid basin simulation. A storm event in
DBSIM1A and DBSIM3A is defined as the period between the start of rainfall and the
time that the EDB is empty. The two-cell partitioned basins are expected to increase the
EDB detention time and the rainfall captured per event. Rainfall events that would
produce separate storms in a one-cell basin simulation might be combined in the two-cell
69
simulations due to the longer retention times, leading to a decrease in the total number of
storm events. In this example for storms starting on 12/22/1948 at 08:00, two rain
showers are treated as two storms in the BASE-100 model because the basin empties
completely between them. In contrast, the TC-100-25:75 basin retains water from the
first shower until the start of the second shower. Both showers are incorporated into a
single storm event by DBSIM3A.
TC-100-25:75 Storm#4 (12/22/1948 08:00)
Inflow
800
Flow Rate (cfh)
700
600
500
Base-100 Storm #4 Combined Outflow
400
300
Base-100 Storm #5 Combined Outflow
200
TC-100-25:75 Storm #4
Combined Outflow
100
0
0
10
20
30
40
Time (Hr)
50
60
70
Figure 4-1 Combined Storm Comparison – Event 12/22/1948 08:00
80
70
4.1.1
Validating the Water Balance in a One-Cell Trapezoidal Basin
DBSIM1A BASE-100 (Alderete, 2004) consists of a uniform trapezoidal single-
cell EDB with a design volume equal to the WQV and the outlet structure sized to drain
the WQV in 48 hours. DBSIM3A BASE-100 uses the same algorithm as the DBSIM1A
BASE-100, including the trapezoidal equation, producing essentially identical results as
shown in Table 4.2.
Table 4-2 Results of DBSIM1A and DBSIM3A BASE-100 Simulations
Parameter 100% WQV
DBSIM1A BASE-100
DBSIM3A BASE-100
3,974,460
3,974,460
Total Discharge Volume (ft )
3,974,490
3,974,488
Total Treated Discharge Volume (ft3)
3,323,937
3,323,938
Total Overflow Volume (ft )
650,560
650,560
Average Detention Time (hr)
8.61
8.61
Maximum Storm #
817
817
Number of Storms w/ Overflows
99
99
3
Total Inflow Volume (ft )
3
3
In the following text, the BASE-100 shown results were generated by DBSIM3A.
BASE-75, BASE-50, and BASE-25 simulations representing basins with 75, 50, and 25
percent of the WQV respectively were also generated by DBSIM3A.
71
4.1.2
Validating the Non-Uniform Shape Algorithm in a One-Cell Basin
To test whether the non-uniform shape algorithm is working correctly, trapezoidal
EDBs are modeled by the non-uniform algorithm and simulations are compared with
simulations using the trapezoidal equations of Alderete (2004). OneCell-100-11pt
consists of a non-uniform single-cell EDB with a design volume equal to the WQV and
an outlet structure sized to drain 100% of the WQV in 48 hours. It is modeled with 11
area and depth inputs. OneCell-100-6pt and OneCell-100-3pt are the same basins
modeled with 6 and 3 area-depth pairs respectively. A comparison of the simulation
results is shown in Table 4-3. As can be seen, errors increase as the number of inputs
decreases. The errors in this case are quite small, mainly because trapezoids are regular
Figures. The errors due to the number of area-depth inputs may be larger for more
irregular shapes. Nevertheless, these results indicate that the algorithms for non-uniform
shapes are working correctly.
72
Table 4-3 Results of DBSIM3A with Varying Number of Data Point
BASE-100
OneCell100-11pt
OneCell100-6pt
OneCell100-3pt
3,974,460
3,974,460
3,974,460
3,974,460
3,974,488
3,974,547
3,974,463
3,974,506
3,323,938
3,323,762
3,323,042
3,318,001
650,560
650,774
651,422
656,509
8.61
8.66
8.73
9.25
817.00
812.00
811.00
796.00
99
99
99
99
Total Inflow Volume (ft3)
0.000%
0.000%
0.000%
Total Discharge Volume (ft3)
Total Treated Discharge Volume
(ft3)
Total Overflow Volume (ft3)
0.003%
0.001%
0.000%
0.006%
0.027%
0.179%
0.041%
0.132%
0.914%
Average Detention Time (hr)
0.522%
1.403%
7.350%
Maximum Storm #
0.612%
0.734%
2.570%
Number of Storms w/ Overflows
0.000%
0.000%
0.000%
Parameter 100% WQV
Total Inflow Volume (ft3)
3
Total Discharge Volume (ft )
Total Treated Discharge Volume
(ft3)
Total Overflow Volume (ft3)
Average Detention Time (hr)
Maximum Storm #
Number of Storms w/ Overflows
Error (compared to BASE-100)
4.1.3
Validating the Non-Uniform Shape Algorithm in a Two-Cell Basin
There are no other two-cell models to compare with DBSIM3A. It is possible,
however, to compare primary cell results from two-cell simulations with results from
one-cell EDB simulations. Base-75, Base-50, and Base-25 are one-cell trapezoidal EDB
simulations with basin volumes of 75, 50, and 25 percent of the WQV and outlet orifices
sized to drain the basins in 48 hours. TC-100-75:25pc, TC-100-50:50pc, and TC-10025:75pc are two-cell trapezoidal EDB simulations with primary cell volumes equal to75,
50, and 25 percent of the WQV. For validation purpose only, the pc (primary cell)
designations indicate that the hydraulic connections between the primary and secondary
73
cells have been severed so that the primary cell outlet orifices are free-flowing as they
would be for one-cell basins. This is a special case and not the way two-cell basins are
modeled elsewhere in this project. The primary cell outlet orifices are also sized to drain
the cells in 48 hours.
In these simulations, runoff in excess of the EDB design volume is routed over
the overflow weir. The one-cell model has one broad-crested weir located on the outlet
side. The two-cell models have two weirs -- a sharp-created weir located on the partition
wall and a broad-crested weir on the outlet side of the secondary cell. One geometric
difference between the two basins is that the one-cell EDB has a trapezoidal shape with
four sloped walls while the primary cell has three sloped walls and one straight, vertical
wall.
The number of storm events, the number of overflows, and the calculated
hydraulic detention times are compared to validate model operations. The simulation
results are shown in Table 4-4. The slight difference might also be attributable to
differences in basin geometry since the volume to depth relationship is slightly different.
74
Table 4-4 Comparison of Simulation Results for One-Cell EDBs and the Primary Cell
of Two-Cell EDBs
Number of
Storm Events
Number of
Storm
Events with
Overflow
Percent of
Storm
Events with
Overflow
Average Hydraulic
Detention Time (hr)a
DBSIM3A One-Cell Simulation
Base-75
793
168
21%
9.7
Base-50
754
262
35%
10.6
Base-25
717
395
55%
11.0
DBSIM3A Two-Cell Simulation – Primary Cell Results Only
TC-100-75:25pc
778
169
22%
9.9
TC-100-50:50pc
739
259
35%
11.1
TC-100-25:75pc
688
384
55%
11.9
a
Event-weighted mean values over the 50-year hydrologic record.
Taken together, the similarities in the number of storms, storms with overflows, and detention times
indicate that the DBSIM3A model is operating as intended.
4.2
Partitioned EDB Performance Assessment
The results from the simulations to assess the effects of partitioning on EDB
performance are presented here. The 50-year long hydrologic record for the Laguna
Beach #2 rain gauge in Orange County, CA was used in each simulation. Basin
parameters are summarized in Table 4-1. The partition wall will be evaluated for its
effects on: (1) the distribution of storm events (i.e. storm events as a function of storm
size), (2) hydraulic performance (i.e. number and occurrences of overflows) and (3)
hydraulic detention time. A summary of the simulation results is shown in Table 4-5.
75
Table 4-5 Performance Summary for Basins with and without a Partition Wall (50year hydrologic record)
Parameters
Total Inflow Volume (ft3)
Total Discharge Volume (ft3)
Total Treated Discharge Volume
(ft3)
Total Overflow Volume (ft3)
Average Detention Time (hr)
Maximum Storm #
Number of Storms w/ Overflows
Percentage of Storms with
Overflow
Total Overflow Volume as
Percentage of Total Discharge
Volume
3,974,460
3,974,488
TC-10075:25
3,974,460
3,975,221
TC-10050:50
3,974,460
3,975,093
3,323,938
3,367,443
3,235,165
3,304,183
650,560
8.61
817
99
607,772
14.09
715
61
739,917
15.05
701
115
670,465
16.74
663
108
12%
9%
16%
16%
16%
15%
19%
17%
0%
0%
0%
0%
0%
0%
1%
-3%
-1%
-7%
64%
14%
75%
3%
94%
-4%
4%
4%
BASE-100
TC-100-25:75
3,974,460
3,974,648
Improvement
3
Total Inflow Volume (ft )
Total Discharge Volume (ft3)
Total Treated Discharge Volume
(ft3)
Total Overflow Volume (ft3)
Average Detention Time (hr)
Percentage of Storms with
Overflow
4.2.1
Effect of Partition Wall on Storm Event and Size
The distribution of storm events by size and the cumulative distribution are shown
in Tables 4-7 and 4-8 respectively. As can be seen, the percentage of small storms in the
partitioned EDB simulations is smaller than those in the BASE-100 simulation.
Concurrently, the percentage of storms in the largest size category is larger. This effect is
caused by the grouping of rainfall events into larger storms due to the longer detention
times of the partitioned basins, an effect that is illustrated in Figure 4-1. Differences
76
among the three partitioned EDB simulations are smaller and show no particular pattern.
As expected from the rainfall pattern shown in Chapter 2, the large majority of storms are
small. In Table 4-7, 28 to 35 percent of the storms are less than or equal to 0.1 inch and
68 to 74 percent are less than or equal to 0.6 inch.
Table 4-6 Distribution of Storm Events by Size
Percent of Total Number of Storms
Storm Size
(inch)
BASE-100
TC-100-75:25
TC-100-50:50
TC-100-25:75
 0.1
35%
31%
32%
28%
> 0.1 and  0.6
38%
39%
38%
40%
> 0.6 and  1.0
10%
10%
11%
11%
> 1.0 and  2.5
12%
14%
14%
15%
Table 4-7 Cumulative Distribution of Storm Events by Size
Percent of Total Number of Storms
Storm Size
(inch)
BASE-100
TC-100-75:25
TC-100-50:50
TC-100-25:75
 0.1
35%
31%
32%
28%
. 0.6
74%
71%
70%
68%
 1.0
84%
81%
81%
79%
 2.5
96%
95%
95%
94%
77
4.2.2
Effect of Partition Wall on Hydraulic Performance
If using a partition results in a shift of the storm size distribution toward the larger
sizes, then it should be expected that the number of overflow events should also increase.
This expectation is only partially supported by the EDB simulations. The total number of
storm events and the number of storm events in which overflow occurred for each
simulation are presented in Table 4-8. The total volumes of water leaving the simulated
EDBs through the overflow weir in the secondary cell are shown in Table 4-9. As can be
seen, adding a partition did increase the number and volume of overflows for the 50:50
and 25:75 configurations, compared to the BASE-100, one-cell case. For the 75:25
configuration, it was unexpected that the number of overflows decreased; the reason is
unknown and requires further investigation. The storm distribution and sequencing
maybe one reason; however this has not been verified.
Table 4-8 Number of Storms with Overflows
Simulation
Number of
Storm Events
Number of Storm
Events with Overflow
Percent of Storm
Events with Overflow
BASE-100
817
99
12%
TC-100-75:25
715
61
9%
TC-100-50:50
701
115
16%
TC-100-25:75
663
108
16%
78
Table 4-9 Volumes of Water Overflowed
100% WQV
Simulation
Total
Discharge Volume
(ft3)
Total
Overflow
Volume
(ft3)
Total Overflow Volume as
Percentage of
Total Discharge Volume
BASE-100
3,974,488
650,560
16% a
TC-100-75:25
3,975,221
607,772
15%
TC-100-50:50
3,975,093
739,917
19%
TC-100-25:75
3,974,648
670,465
17%
a
Note that 16% of the volume overflowed in the BASE-100 case, which verifies the WQV
being the volume of basin required to capture about 85% of the runoff volume.
To better understand the effect of partitioning on overflows, the numbers and
volumes of overflows are grouped by storm size in Tables 4-11 and 4-12 respectively.
As seen, the numbers and volumes of overflows for EDBs with primary cells sized for 50
and 25 percent of the WQV increased for storms larger than 1.0 inch27. In contrast, for
the EDB with a primary cell sized for 75% of the WQV, the number of overflow events
decreased by 4 percentage points and the volume decreased by one percentage point. As
shown in Table 4-11, these decreases occur in the storm size range between 1.0 and 2.5
inches. This appears to be a function of the particular rainfall distribution for Orange
County, California.
Wasilchen’s DBSIM2A model showed that EDBs in series increased the overflow from one to two
percent as seen on Table 2-7. DBSIM3A shows EDBs with primary cells sized for 50 and 25 percent of the
WQV similarly increases the overflow from one to three percent. In both DBSIM2A and DBSIM3A, the
largest overflow volume occurred in the EDB with primary cells sized for 50 percent of the WQV. Note
that in DBSIM2A, two trapezoidal basins were placed in series and first basin outflow did not consider the
height of water in the second basin.
27
79
Table 4-10 Number of Overflows by Storm Size
Percent of total storms with overflows
Storm Size
(inch)
BASE-100
TC-100-75:25
TC-100-50:50
TC-100-25:75
. 0.1
0%
0%
0%
0%
> 0.1 and  0.6
0%
0%
0%
0%
> 0.6 and  1.0
0%
0%
1%
1%
> 1.0 and  2.5
8%
4%
10%
10%
> 2.5
4%
4%
5%
5%
Total
12%
9%
16%
16%
Table 4-11 Overflow Volumes by Storm Size
4.2.3
Storm Size
(inch
)
BASE-100
TC-100-75:25
TC-100-50:50
TC-100-25:75
. 0.1
0%
0%
0%
0%
> 0.1 and  0.6
0%
0%
0%
0%
> 0.6 and  1.0
0%
0%
0%
0%
> 1.0 and  2.5
5%
4%
6%
5%
> 2.5
11%
11%
13%
12%
Total
16%
15%
19%
17%
Overflows as Percent ages of total volume discharged
Effect of Partition on Detention Times
The simulated detention time is the time difference between the outflow centroid
and the inflow centroid. The event mean (also referred to as the average detention time)
is the sum of the detention times for each event divided by the total number of events. It
represents the average detention time per storm event. The volume-weighted mean is the
sum of the product of the detention time and volume divided by the total volume. It is
the average detention time per unit volume of water. Both averages are shown in Table
4-12.
80
Table 4-12 Comparison of Simulated Discharge Volumes for System
Simulation
Average (Event Mean)
Detention Time
(hr)
Volume-weighted
Detention Time
(hr)
BASE-100
8.61
11.94
TC-100-75:25
14.09
19.07
TC-100-50:50
15.05
17.11
TC-100-25:75
16.74
16.18
As shown in Table 4-12, the average detention time increases as the primary cell
volume size decreases because the majority of the events are small. Small events are
captured and retained longer in smaller detention basins. The volume-weighted detention
time increases substantially compared to the BASE-100 case, then decreases as the
primary cell volume size decreases. The decrease in detention time with decreasing
primary cell size is due to the fact that water entering small primary cells overflows more
often into the secondary cell where it drains out quickly because the secondary cell
orifice is sized for 100 percent of the WQV. The reason for the dramatic increase in
volume-weighted detention time from 11.94 hours (BASE-100) to 19.07 hours (TC-10075:25) is not obvious. At first glance, one might presume that the BASE-100 and TC100-75:25 results would be similar because the basin configurations are similar. The
primary cell orifice is sized to drain 75 percent of the basin volume in 48 hours and is
only slightly smaller than the secondary cell orifice. When the basin is full, however, the
flow out of the primary cell is inhibited by the head of water in the secondary cell.
(Recall that orifice sizing is based on free-flow conditions.) So the actual drawdown time
81
for the primary cell is much longer than the design value. This effect occurs in the
smaller primary cells (50:50 and 25:75) as well, but it is overwhelmed by the increased
frequency of overflows into the secondary cell, as described above.
Storm Events as a Function of Detention Time
Tables 4-13 and 4-14 and Figure 4-2 show the percentages of storms achieving or
exceeding various calculated detention times for basins with and without partition walls.
As shown in Table 4-14, 37 percent of the storms passing through the BASE-100 EDB
showed detention times less than 5 hours. None (0 percent) of the storms passing through
the partitioned EDBs showed detention times less than 5 hours, which shows the value of
the partition wall. The results from the 75:25 and 50:50 EDBs are similar, showing that
64 and 66 percent of storms, respectively, receiving more than 10 hours of detention and
23 and 29 percent, respectively, receiving more than 20 hours. The 25:75 EDB results
are somewhat different, showing that 99 percent of storms receiving more than 10 hours
of detention, but only 14 percent receiving more than 20 hours. The differences are more
apparent in Figure 4-2.
82
Table 4-13 Distribution of Storm Events by Detention Time
Percent of Total Number of Storm Events
Detention Time
(hr)
BASE-100
TC-100-75:25
TC-100-50:50
TC-100-25:75
5
37%
0%
0%
0%
> 5 and  10
28%
36%
34%
1%
> 10 and  15
29%
26%
21%
36%
> 15 and  20
6%
15%
17%
48%
> 20 and  25
0%
17%
29%
14%
> 25 and  30
0%
6%
0%
0%
Table 4-14 Cumulative Distribution of Storm Events by Detention Time
Detention
Time
(hr)
BASE-100
TC-100-75:25
TC-100-50:50
TC-100-25:75
5
37%
0%
0%
0%
 10
65%
36%
34%
1%
 15
94%
62%
54%
37%
 20
100%
77%
71%
86%
 25
100%
93%
100%
100%
 30
100%
100%
100%
100%
>5
63%
100%
100%
100%
> 10
35%
64%
66%
99%
> 15
6%
38%
46%
63%
> 20
0%
23%
29%
14%
> 25
0%
7%
0%
0%
> 30
0%
0%
0%
0%
Percent of Total Number of Storm Events
83
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0
5
10
15
20
25
30
Detention Times (Hours)
Base-100
TC-100-25:75
TC-100-50:50
TC-100-75:25
Figure 4-2 Cumulative Distribution Plot of Detention Times
Detention Time as a Function of Storm Size
Average detention times for different storm size categories are shown in Table 415 and Figure 4-3. The partitioned basin simulations showed increased detention times
for all storm event sizes. For small storms, detention times increase as primary basin
volumes decrease (i.e. the smallest primary basin showed the longest average detention
time). For storms larger than about 0.6 inch, this pattern reverses. As noted earlier,
moderate-to-large storms overflow smaller primary cells more often and the overflow
volumes are not retained in the secondary cells very long.
84
Table 4-15 Simulated Average Detention Times by Storm Size
Storm Size
(in)
Average Detention Time of Storm Events for Each Simulation
100% WQV
BASE-100
TC-100-75:25
TC-100-50:50
TC-100-25:75
. 0.1
4.62
7.20
8.96
13.41
> 0.1 and  0.6
8.60
13.64
16.67
18.65
> 0.6 and  1.0
14.08
22.04
21.32
18.68
> 1.0 and  2.5
14.78
23.40
19.37
17.56
> 2.5
11.81
18.66
14.98
13.81
Average
Detention Time
8.61
14.09
15.05
16.79
25
Average Detention Time (hr)
20
15
10
5
0
=< 0.1
0.1 - 0.6
0.6 - 1.0
1.0 - 2.5
> 2.5
Storm Size (inch)
Base-100
TC-100-75:25
TC-100-50:50
TC-100-25:75
Figure 4-3 Distribution of Detention Times by Storm Size
85
The difference between single-cell and partitioned basins is demonstrated in
Figure 4-4 where ratios of detention times are plotted. The ratios are calculated by
dividing the average detention times of the partitioned simulations by the respective
BASE-100 average detention times. Ratios greater than 1.0 indicate that the partitioned
simulation has a longer detention time than the BASE-100 simulation. For the smaller
storm events (i.e., storms less than 0.6 inch), smaller primary cells resulted in larger
detention times. For example, the TC-100-25:75 average detention time is almost 3 times
longer than the BASE-100 for the smallest storm category. The ratio for TC-100-50:50 is
about 2 in this storm size category. For the larger storms, all of the ratios drop toward
1.0. This is expected because in large storms, both cells of the EDBs fill up and the
partition has relatively little effect on the hydraulics compared to a one-cell basin.
Nevertheless, it is important to note that the ratios were always greater than one, for all
storm sizes and for all combinations of primary and secondary cells.
86
3.5
Ratio to Base-100 Detention Time
3
2.5
2
1.5
1
0.5
0
=< 0.1
0.1 - 0.6
0.6 - 1.0
1.0 - 2.5
> 2.5
Storm Size (inch)
TC-100-75:25
TC-100-50:50
TC-100-25:75
Figure 4-4 Ratios of Detention Times to BASE-100 Detention Time
4.2.4
Estimated TSS Removal
The purpose for increasing detention time is to allow more time for settling to
occur, thus producing better treatment. Direct settling of particles was not modeled in
this project. A rough estimate of potential total suspended solids (TSS) removal,
however, can be made by applying the average detention times to the suspended sediment
removal curve in Figure 2-3. The resulting estimated TSS removal percentages are
shown in Table 4-16. The results are disappointing. Although the average detention in
the TC-100-25:75 basin is almost twice as long as in the BASE-100 basin, the TSS
removal is only 6 percentage points greater.
It is important to recognize that this estimate is very approximate. The suspended
sediment removal curve in Figure 2-3 is not based on field tests but rather on a laboratory
87
column. Many factors other than detention time affect sedimentation removal, such as
influent water quality, infiltration, short circuiting and scouring. Also, applying the
detention time calculated from the centroid of the overall discharge (orifice and overflow)
may not be accurate. In an overflow situation, the water in the basin will receive
substantial time to settle while the overflow volumes will experience no settling. For
example, the improvement in TSS removal from 0.1-inch storms, which don’t overflow,
is as high as 21 percentage points (see Table 4-16). Although a more sophisticated
accounting for mixing downstream of the basin might give a different answer, it would
not necessarily be a better one considering the artificial nature of the TSS removal curve.
Despite these caveats, it is interesting to note that the results shown in Table 4-16 are not
very different from those presented by Li et al. (2008), which are based on a much more
sophisticated calculation of particle removal.
Table 4-16 Estimated TSS Removal Summary
All Storms
0.1-inch Storms
Average Detention
Time (hr)
TSS Removal
Average Detention
Time (hr)
TSS Removal %
BASE-100
8.61
74%
4.62
58%
TC-100-75:25
14.09
79%
7.20
70%
TC-100-50:50
15.05
79.5%
8.95
75%
TC-100-25:75
16.74
80%
13.41
79%
88
Chapter 5
5. CONCLUSIONS
CONCLUSIONS
In this project, hypothetical on-line extended detention basins with and without an
internal partition wall were simulated with an Excel Visual Basic for Applications (VBA)
computer model. The simulations were driven by a 50-year historical rainfall record
from a rain gage station in Orange County, California. Various configurations were
created by changing the location of the partition wall which affected the relative sizes of
the primary and secondary cells. In all cases, though, the total basin volume was set at
the water quality volume appropriate for Orange County. The purpose of the simulations
was to assess how hydraulic detention time is affected by basin partitioning. The
simulation results are summarized in Table 5-1.
Table 5-1 Summary Results from the Four DBSIM3A Simulations
Simulation
a
Overflow Volume
(% of inflow)
Average
Detention Time (hr)
Base-100 (control)
16%
8.61
TC-100-75:25 a
15%
14.09
TC-100-50:50 b
19%
15.05
TC-100-25:75 c
17%
16.74
Primary cell = 75% of the WQV; secondary cell = 25% of the WQV.
Primary cell = 75% of the WQV; secondary cell = 25% of the WQV.
c
Primary cell = 75% of the WQV; secondary cell = 25% of the WQV.
b
89
The following conclusions can be drawn from the results:

In all cases simulated, basins with a partition wall experience longer hydraulic
detention times than the one-cell basin.

As primary cell volume and its orifice size decreases, the average hydraulic detention
time increases by up to 94 percent for the basin with a 25% WQV primary cell.

As primary cell volume and orifice size decrease, overflows from the primary cell
increase. Compared to the control basin, overflows from the secondary cells are
smaller for the basin with a 75-percent WQV primary cell, but larger for the two
cases with smaller primary cells.

Based on a relationship between detention time and total suspended solids (TSS)
removal found in the literature and the detention times calculated in this model,
average event TSS removal increases by up to 6 percentage points due to adding an
internal partition. For the 0.1 inch storm size, adding a partition wall increases the
estimated TSS removal from 58 percent to 79 percent.
Recommendations
Despite the simulation results that showed the greatest increase in detention times
in the basin with a 25% WQV primary cell, the projected TSS removal rates were not
significantly different from the basins with larger primary cells for the Orange County
50-year historical record. Therefore, the basin with the 75%WQV primary cell is
recommended because it is the simulation that showed a decrease in overflow volume.
90
For smaller storms events without overflows (0.1 inch), the greatest increase in
average detention time was in the basin with a 25% WQV primary cell, the projected TSS
removal rates was increased as primary cell decreased.
Recommendations for future work include:

Test with hydrologic data sets from various climates in California to verify that the
results from this project are not unique to Orange County.

Test different configurations of primary and secondary cells in basins of different
sizes (i.e. not just the WQV). It may be possible to attain the same detention time as
a standard one-cell designs in basins that are smaller, but equipped with partitions.

Incorporate infiltration into the simulation.

Incorporate better modeling of TSS removal to more accurately estimate the benefits
of increased hydraulic detention time.
91
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