v>EPA
United States
Environmental Protection
Agency
Municipal Environmental Research
Laboratory
Cincinnati OH 45268
Research and Development
EPA-600/S2-81-218 Oct. 1981
Project Summary
Hourly Diurnal Flow
Variations in Publicly-Owned
Wastewater Treatment
Facilities
. ,
Warren H. Chesner anct-Martiri Pat
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230 r'
Chicago,
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treet
60604
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Hourly diurnal flow variations at
wastewater treatment plants subject
unit operations to fluctuations that
influence their performance. These
variations are rarely addressed in the
design of these facilities.
A survey of 39 sanitary sewer
collection systems was undertaken to
determine the magnitude of hourly
peak flows and to identify the collec-
tion system parameters that were
most influential in affecting the
observed peaks. Significant collection
system parameters identified included
industrial contribution, average age of
the collection system, depth to the
groundwater, and low-lift, pre-plant
pumping stations.
Collection systems with large indus-
trial contributions were observed to
have higher peak flows than those
with small industrial contributions.
Variations in observed peak flows
were exhibited between spring and
summer periods for old systems and
for those with high groundwater as a
result of infiltration during the spring
season. Low-lift, pre-plant pumping
stations, depending on their capacity
and control, can create extremely high
peak flows and pulses that do not
reflect normal diurnal influent flow
patterns.
The mean average peak hourly flow
per day for nonindustrial collection
systems, excluding inflow, was found
to be 1.23 times the annual average
daily flow. This value did not signifi-
cantly vary with flow rate, but the
variation around this mean value
decreased with increasing flow.
This Project Summary was devel-
oped by EPA's Municipal Environ-
mental Research Laboratory, Cincin-
nati, OH, to announce key findings of
the research project that is fully
documented in a separate report of the
same title (see Project Report ordering
information at back).
Introduction
Hydraulic and organic variations of
wastewater flow at publicly owned
wastewater treatment works (POTW's)
represent design items that the engineer
must address before he undertakes his
process and hydraulic design. In the
absence of monitored flow, traditional
design practice for the hydraulic sizing
of unit wastewater treatment processes
has relied on the application of peaking
factors to estimate peak sanitary design
flows. These factors are commonly
defined as the ratio of peak to average
flow, and they have been presented in
terms of fixed values or as a function of
influent flow rates or collection system
population. To estimate the total peak
flow, the designer must add components
for infiltration and inflow to the total
peak sanitary flow. More recent inves-
tigations have sought to develop empir-
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ical equations to facilitate the prediction
of extreme peak flows that include both
dry- and wet-weather events.
The characteristics of the collectioa
system are largely responsible for the
magnitude and variations in influent
flows to wastewater treatment plants.
The correlation of collection system
parameters with peaking and flow
variation has had limited previous
investigation. As a result, peaking has
been addressed as a function of flow
rate or equivalent population.
Background
Typical diurnal variations in influent
flow are depicted by a wave form. The
flow variation is characterized by two
peaks (resulting from morning and early
evening water usage) and decreasing
flows late at night and early in the
morning. The maximum flow of the
diurnal flow period is defined as the
"peak hourly flow." Variations in the
wave form of any given collection
system can be expected to occur on a
day-to-day basis. These variations can
take the form of time lags, advances in
the wave form, or increases or decreases
in observed peaks. Systems with exces-
sive inflow can be expected to exhibit
wave forms and peak values in response
to storm events and abnormal diurnal
flow patterns. These peaks are not
included in this report.
To facilitate communication, a set of
definitions for both peaking and collec-
tion system parameters was established
for use throughout the study. A summary
of these definitions is presented in Table
1.
Various collection system parameters
have generally been assumed to have
an impact on peaking and hydraulic
diurnal variations. These collection
system parameters include annual
average flow and population, percent of
industrial contribution, topography,
average annual rainfall, soil type, shape
of collection system, groundwater table,
average age of system, number of
pumping stations, and bypasses.
Methodology
An initial survey of 145 POTW's was
undertaken to identify separate sanitary
sewer systems that has (1) annual
average daily flows between 189 and
378,500 mVday (0.05 and 100 mgd), (2)
properly calibrated diurnal influent flow
recorders and records of these flows,
and (3) sufficient information on collec-
tion system parameters. Further selec-
tion was based on the need both to
Table 1. Definitions: Peaking Factors
Peaking Factor
1. Annual peaking factor (APF) -
2. Sample peaking factor (SPF) =
Peak Flow
3. Peaking duration
4. Peaking period
5. Sample time period
6. Sample analysis
Peak Flow
7. Peaking factor examples
Average Flow
8. Annual average daily flow (ADF)
9. Average sample time period flow
Annual A verage Daily Flow (ADF)
___^ Peak Flow
Average Sample Time Period Flow ~
Unit of time that the peak represents (peak It
minutes; peak hour; peak day).
The time period over which the peak period
is compared (peak hr/day; peak day/year).
The period of time from which the data are
assessed.
Maximum value: Minimum value in the sample
time period.
Average value: Average value in the sample
time period.
Minimum value: Minimum value in the sample
time period.
#— Peaking duration
A verage peak hr_per 10-day period
\ ?Y ^Sample time period
Sample analysis ^-Peaking period
The annual volume of influent treatment
plant wastewater divided by 365 days, normally
expressed in mgd.
The volume of influent treatment plant waste-
water during the sample time period divided
by the number of days in the sample time
period.
identify sewer systems with an equal
distribution of collection system para-
meters and to establish (to the extent
possible) an equal geographic distribu-
tion of facilities investigated throughout
the country.
Preliminary screening of the 145
POTW's using the above collection
system criteria resulted in the selection
of 39 systems for study. Continuous
flow data from each of the 39 facilities
was obtained for 10 days during the
spring and 10 days during the summer.
Flow data during the spring and summer
were obtained to assess their seasonal
differences between peaking values
observed. Annual records from one
facility were obtained to determine how
well small sample time periods repre-
sented longer periods. Flow data for the
spring and summer periods were
reviewed, and systems where flow
predominated were eliminated from the
analysis.
Data collected were analyzed in a
series of steps designed to identify
collection system parameters most
influencing peak flows and to quantify
those parameters as much as possible
within the scope of this work. The
influence of flow rate and sample time
period of the peaking factor were also
investigated. Finally, the special case of
pump-dominated collection systems
was examined. Two independent
approaches were used to identify
significant collection system parameters
and to quantify their impacts. They are
termed "collection system comparative
assessments" and "data cluster analysis."
Results and Discussion
Differentiation of individual collection
system parameters as they impact peak
flows is an extremely difficult task since
each individual system contains numer-
ous variables. Quantification of these
variables exceeded the scope of this
investigation. Nonetheless, three signi-
ficant parameters stood out as dominant
throughout the comparative analysis.
these included industrial contributions,
average age of the collection system,
and depth to groundwater.
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Systems with industrial or institu-
tional contributions greater than 40
percent' of the total collection system
flow (when compared with systems
with less than 40 percent) exhibited
higher maximum hourly peaking factors,
higher average hourly peaking factors,
greater seasonal variations in average
hourly peaking factors, and peak hours
that differed from the nonindustrial
systems.
Collection systems that were old
(more than 25 years) and experienced
high groundwater exhibited marked
seasonal (spring to summer) variations
in observed peaking factors. This
marked variation was not apparent in
systems that did not have these charac-
teristics. Unlike other systems, old
systems with high groundwater exhibit
spring peaking factors 1.1 to 1.5 times
those observed in the summer. This
phenomenon results from greater
susceptibility to infiltration during the
spring season and increases both the
flow and the annual peaking factor.
Table 2 presents the mean of all
average hourly peaking factors (PFA) and
maximum hourly peaking factors (PFM)
for both spring and summer and for the
total 20 days of data. For nonindustrial
systems, the mean of all average hourly
peaking factors was 1.23, 1.30, and
1.22 for the total 20 days, spring and
summer values, respectively.
Examination of mean values for
industrial systems with flow contribu-
tions greater than 40 percent reflect the
higher average peaks exhibited by most
industrial systems (as illustrated by the
1.32, 1.42, and 1.30 average hourly
peaking factors for the total 20 days,
spring, and summer periods, respec-
tively.) Table 2 also lists a mean value of
1.59 for peak industrial seasons, where
increase in industrial activity increased
the peak flows observed.
Within the range of values tested, the
average hourly peaking factors for most
nonindustrial systems did not vary
significantly with flow rates and main-
tained a mean value of approximately
1.23.
Maximum hourly peaking factor
values exhibited.some slight decrease
with flow, but the outlying values
produced poor correlation with any
attempted flow/peaking factor relation-
ship! As flow increased, however, the
standard deviation or fluctuation around
the average peak hour per day decreased.
This result implies that greater flow
variation around the mean value can be
expected in the lower-flow ranges.
Table 2. Mean Average Hourly and
Maximum Hourly Peaking
Factors*
I. 14 Nonindustrial Systems
PF* = 1.23 for 20 days
PF* = 1.30 for 10 days in spring
PFn = 1.22 for 10 days in summer
II. 14 Nonindustrial Systems
PFM = 1.70 for 20 days
PFu - 1:61 for 10 days in spring
PFM = 1.54 for 10 days in summer
III. 7 Industrial Systems
PF*. = 1.32 for 20 days
PFt, = 1.42 for 10 days in spring
PF* = 1.30 for 10 days in summer
PFu = 1.59 for industrial season
(either 10 days in spring or
10 days in summer)
IV. 7 Industrial Systems
PFM = 2.05 for 20 days
PF» = 1.76 for 10 days in spring
PFM = 1.63 for 10 days in summer
*The mean peaking factors summarized
in this table are calculated independ-
ently from sample data taken during
the applicable time period. Thus 20-
day mean peaking factors cannot be
calculated simply by noting the 10-day
spring and summer mean peaking
factors shown here. Sect ion 4 of the
report elaborates on the statistical
approach used to calculate these peak-
ing factors.
whereas smaller flow variations are
expected in the higher-flow ranges.
Annual flqw data for one facility was
collected and analyzed for 1 full year, for
20 days during the spring, and for 10
days during the summer. Some shifting
in the peak hour exists among the time
periods. The annual, spring, and summer
peak hours occurred for approximately
1,500, 1,300, and 1,400 hours, respec-
tively. The average hourly and maximum
hourly peaking factors for the annual
time period were 1.3.5 and 2.70,
respectively. For the spring period,
these yalues were 1.38 and 1.80,
respectively; for the summer periods,
these values were 1.05 and 1.15,
respectively. For the 20-day sample
time period, these values were 1.18 and
1.80, respectively.
Maximum hourly peaking factors
increased as the time period increased.
Data from limited time periods (i.e.,
spring or summer) do not represent the
annual time period. Note that the
annual flow ratio includes potential
inflow, which was not eliminated when
these data were examined. The result is
that the maximum observed events will
be greater. The average analysis over
the year tends to reduce the severity of
inflow.
The average hourly peaking factor for
the annual period of 1.35 was very close
to the 1.38 observed during the spring
period. The summer period's low value
of 1.05 was the result of a decreasing
population and flow rate during the
summer in the collection system. The
sanitary sewer system was classified as
an industrial system because of the high
institutional flow that decreased during
the summer months. The annual value
(PFA) of 1.35 was slightly higher than
the mean value of 1.32 forthe industrial
collection systems previously examined.
Many wastewater treatment plants
contain low-lift pumping stations.
Depending on the station's design, it
can control the diurnal variations and
peaking at the facility. The pumping
station can minimize or eliminate the
collection system as a factor. Eight
facilities surveyed fell into this particular
category.
Maximum instantaneous flow ratios
(peaking factors) varied from 1.3 to 4.7.
The frequency of pulses or number of
peaks per hour ranged from 1 to 17.
Minimum instantaneous flow ratios
ranged from 0 to 0.8.
Clearly, low-lift pumping stations
designed to provide the required head
and capacity without consideration of
peaking effects can be the dominant
factor influencing peak-flow magnitudes
received at a facility.
Conclusions
Sanitary sewer collection system
factors found to have the most impact
on the average hourly peaking factor-
include the percentage of the total flow
to the POTW contributed by industries
or institutions, the average age of the
system, the depth to groundwater, and
the impact of low-lift, pre-plant pumping
stations.
Collection systems with industrial or
institutional flow contributions greater
than 40 percent were found consistently
to have higher daily peak flows than
those below 40 percent. Industrial flows
can also be seasonal, with flows during
the industrial season resulting in higher
peaking factors. Peak flow hours of the
day tended to occur at earlier hours in
industry-dominated systems.
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Nonindustrial collection systems with
an average age greater than 25 years
and high groundwater tables are more
susceptible to infiltration and, as a
result, exhibit higher peaking factors
during the spring or infiltration season.
The mean average hourly peak flow
for nonindustrial systems, excluding
inflow, was found to be 1.23 times the
annual average daily flow (PFA = 1.23)
and did not vary significantly with the
average collection system flow rate.
As collection system flow rate in-
creases, variations around the mean
value decrease. The mean flow estimate
for larger systems has greater reliability
than that of smaller systems.
Individual average hourly peaking
factor values for the spring were as
much as 1.5 times those that occurred
during the summer for old-age systems
with high groundwater tables.
The mean average hourly peaking
factor for industry-dominated systems
was found to be 1.32 (PFA = 1.32). The
industrial season mean average hourly
peaking factor was found to be 1.59.
The peak hours for nonindustrial
collection systems fell predominantly
between 10 a.m. and 4 p.m. Industrial
and institutional system peaks fell
largely between 10 a.m. and 2 p.m.
The mean maximum hourly (PFM =
1.70) peaking factor for nonindustrial
collection systems was found to be 1.70
for 20 days of data. Maximum hourly
peaking factors were calculated as high
as 2.82 during the 20-day sampling
period. Maximum hourly peaking factors
increased with increasing sampling
time periods.
Instantaneous maximum peaking
factors for low-lift, pump-dominated
systems ranged from 1.3 to 4.7, and the
minimum instantaneous flow factors
varied from 0 to 0.8. Low-lift pumping
stations designed to provide the re-
quired head and capacity without
consideration of peaking effects can be
the most dominant factor influencing
peak-flow magnitudes.
Recommendations
Several factors significantly affect
daily dry-weather influent flow peaks
and fluctuations at POTW's. The follow-
ing factors must be addressed in any
study of influent wastewater so that
unit operations of the treatment plant
can be properly designed and operated.
Industrial wastewater discharge
schedules as well as magnitude and
make-up should be defined to determine
the wastewater impact on treatment
plant performance. When industrial
wastewater contributes greater than 40
percent of the total flow to the POTW,
careful assessment should be made of
its impact on peak flows.
Surveys characterizing influent waste-
water from nonindustrial sanitary
sewer collection systems greater than
25 years old should pay particular
attention to potential seasonal infiltra-
tion from high groundwater tables.
Low-lift, pre-plant pumping station
operation can be the most important
factor influencing hydraulic diurnal flow
variations experienced at the POTW.
Pump capacity and control should be
taken into account in the design of new
POTW's or in the investigation of
performance problems in existing
facilities.
Though this report primarily addresses
hydraulic flow variations at the POTW's,
wastewater constituent characteristics
.also vary. Wastewater hydraulic and
concentration measurements must
both be made for proper characteriza-
tion of the total mass loading entering
the treatment plant.
The full report was submitted in
fulfillment of Contract No. 68-03-2775
by Roy F. Weston, Inc., under sponsor-
ship of the U.S. Environmental Protec-
tion Agency.
Warren H. Chesner and Martin Pai are with Roy F. Weston, Inc., West Chester,
PA 19380.
Jon H. Bender is the EPA Project Officer (see below).
The complete report, entitled "Hourly Diurnal Flow Variations in Publicly-Owned
Wastewater Treatment Facilities." (Order No. PB 82-107 954; Cost: $11.00,
subject to change) will be available only from:
National Technical Information Service
5285 Port Royal Road
Springfield, VA 22161
Telephone: 703-487-4650
The EPA Project Officer can be contacted at:
Municipal Environmental Research Laboratory
U.S. Environmental Protection Agency
Cincinnati, OH 45268
United States
Environmental Protection
Agency
Center for Environmental Research
Information
Cincinnati OH 45268
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