HomeMy Public PortalAboutExhibit MSD 73L - Stantec Infiltration and Inflow Data Summary ReportInfiltration and Inflow Data
Summary – 3rd Draft Report
June 17, 2022
Prepared for:
Metropolitan St. Louis Sewer District
Prepared by:
Stantec Consulting Services Inc.
DRAFT Exhibit MSD 73L
This document entitled Infiltration and Inflow Data Summary – 3rd Draft Report was prepared by Stantec
Consulting Services Inc. (“Stantec”) for the account of Metropolitan St. Louis Sewer District (the “Client”). Any
reliance on this document by any third party is strictly prohibited. The material in it reflects Stantec’s
professional judgment in light of the scope, schedule and other limitations stated in the document and in the
contract between Stantec and the Client. The opinions in the document are based on conditions and
information existing at the time the document was published and do not take into account any subsequent
changes. In preparing the document, Stantec did not verify information supplied to it by others. Any use which
a third party makes of this document is the responsibility of such third party. Such third party agrees that
Stantec shall not be responsible for costs or damages of any kind, if any, suffered by it or any other third party
as a result of decisions made or actions taken based on this document.
Prepared by
(signature)
Carl Chan
Reviewed by
(signature)
Emily Sweeney
Approved by
(signature)
Dave Haverdink
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Table of Contents
1.0 INTRODUCTION ............................................................................................................... 1
2.0 WET WEATHER AND WASTEWATER FLOWS ............................................................. 3
2.1 METHODOLOGY .............................................................................................................. 3
2.1.1 Dry Weather Flow ............................................................................................ 4
2.1.2 Groundwater Infiltration ................................................................................... 4
2.1.3 Rainfall-Derived I/I ........................................................................................... 4
2.2 DRY WEATHER FLOW ANALYSIS RESULTS ................................................................ 6
2.2.1 Rainfall Analysis .............................................................................................. 6
2.2.2 Dry Weather Day Selection ............................................................................. 7
2.2.3 Average Dry Weather Flow Results ................................................................ 8
2.2.4 Key observations ........................................................................................... 12
2.3 GROUNDWATER INFILTRATION ANALYSIS RESULTS .............................................. 13
2.3.1 Groundwater Infiltration Results .................................................................... 13
2.3.2 Groundwater Infiltration Analysis ................................................................... 14
2.3.3 Groundwater Infiltration Estimation ............................................................... 16
2.3.4 Key observations ........................................................................................... 17
2.4 RAINFALL DERIVED I/I ESTIMATION ........................................................................... 18
2.4.1 Total R results ............................................................................................... 18
2.4.2 Range of Total R ........................................................................................... 19
2.4.3 I/I Breakdown ................................................................................................. 23
2.4.4 Key observations ........................................................................................... 24
2.5 FLOW ANALYSIS CONCLUSIONS ................................................................................ 24
3.0 OVERFLOW VOLUME ESTIMATES.............................................................................. 25
LIST OF TABLES
Table 1 Average Recurrence Interval for Rainfall Events ............................................................. 6
Table 2 Number of Dry Weather Days .......................................................................................... 7
Table 3 Groundwater Infiltration Estimates ................................................................................. 16
Table 4 Total R Results .............................................................................................................. 19
Table 5 I/I Estimation .................................................................................................................. 23
Table 6 Constructed SSO Activation Data Summary ................................................................. 25
Table 7 Sanitary Sewer Overflow Data Summary ...................................................................... 25
Table 8 Unpermitted CSO Discharge Data Summary ................................................................ 26
LIST OF FIGURES
Figure 1 Wastewater Treatment Facility Tributary Areas .............................................................. 1
Figure 2 Hydrograph Decomposition into GWI, BWF, and RDII ................................................... 3
Figure 3 Wastewater Treatment Facilities Tributary Area ............................................................. 5
Figure 4 Depth vs Intensity Scattergraph ...................................................................................... 7
Figure 5 Yearly Average Dry Weather Flow ................................................................................. 8
Figure 6 Yearly Average Dry Weather Flow and Average Mississippi River Level ....................... 9
Figure 7 Yearly ADWF in respect of 5-year ADWF ....................................................................... 9
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Figure 8 Lemay WWTF Seasonal ADWF ................................................................................... 10
Figure 9 Coldwater WWTF DWF Yearly Weekday Diurnal Pattern ............................................ 11
Figure 10 Coldwater WWTF DWF Seasonal Weekday Diurnal Pattern ..................................... 11
Figure 11 Average Groundwater Infiltration ................................................................................ 13
Figure 12 Lemay WWTF Seasonal GWI ..................................................................................... 14
Figure 13 Bissell WWTF Groundwater Infiltration Analysis ........................................................ 15
Figure 14 Ratio Between GWI and ADWF .................................................................................. 15
Figure 15 Total R Results ........................................................................................................... 18
Figure 16 Maximum Peaking Factor ........................................................................................... 19
Figure 17 Total R Standard Deviation ......................................................................................... 20
Figure 18 Rainfall Depth-Total R Scattergraph for Coldwater WWTF ........................................ 21
Figure 19 One-Week Antecedent Rainfall-Total R Scattergraph for Coldwater WWTF.............. 21
Figure 20 One-Month Antecedent Rainfall-Total R Scattergraph for Coldwater WWTF ............. 22
Figure 21 USGS 07010000 Level-Total R Scattergraph for Coldwater WWTF .......................... 22
Figure 22 USGS River Gauges ................................................................................................... 23
LIST OF APPENDICES
SEASONAL AVERAGE DRY WEATHER FLOW GRAPHS ...................... A.1
YEARLY DIURNAL PATTERNS ................................................................ B.1
SEASONAL DIURNAL PATTERNS ........................................................... C.1
SEASONAL GROUNDWATER INFILTRATION GRAPHS ........................ D.1
GROUNDWATER INFILTRATION ANALYSIS GRAPHS .......................... E.1
TOTAL R SCATTERGRAPHS ..................................................................... F.1
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Introduction
1
1.0 INTRODUCTION
The Metropolitan St. Louis Sewer District (MSD) serves approximately 1.3 million people over 500 square
miles in the City of St. Louis and St. Louis County, Missouri. A complex system of approximately 4,700
miles of sanitary sewers and force mains and 1,400 miles of combined sewers conveys wastewater to
seven MSD wastewater treatment facilities (WWTFs): Bissell Point WWTF, Coldwater WWTF, Fenton
WWTF, Grand Glaize WWTF, Lemay WWTF, Lower Meramec WWTF, and Missouri River WWTF. The
wastewater treatment facility tributary areas are shown in Figure 1.
Figure 1 Wastewater Treatment Facility Tributary Areas
Stantec was retained by MSD to perform a systemwide infiltration and inflow (I/I) cost allocation study.
The findings of the study are documented in a report titled Infiltration and Inflow Cost Allocation, which
was provided to MSD for use in future rate proceedings.
In addition to the cost allocation study, MSD requested an updated review of systemwide I/I flow data,
which is the subject of this I/I data summary report. The I/I flow data review consisted of two components:
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Introduction
2
an analysis of wet weather and wastewater flows received at the WWTFs, and estimates of sanitary
sewer and combined sewer overflow volumes.
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Wet Weather and Wastewater Flows
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2.0 WET WEATHER AND WASTEWATER FLOWS
Stantec performed an analysis of MSD’s wet weather and wastewater flow data to better understand the
flow characteristics of the system and evaluate whether trends and relationships in the data may indicate
correlations between I/I and other factors in MSD’s overall system or in the implications of I/I that MSD
must manage. To accomplish this effort, Stantec received and reviewed 15-min inflow data for each
WWTF and gauge-adjusted radar rainfall (GARR) data between 2016 and 2020.
Section 2.1 presents the methodology used to calculate average dry weather flow, groundwater
infiltration, and rainfall-derived inflow and infiltration. The results of each analysis are then presented in
Sections 2.2 to 2.4.
2.1 METHODOLOGY
The United States Environment Protection Agency (EPA) Sanitary Sewer Overflow Analysis & Planning
(SSOAP) Toolbox was used to conduct the I/I analysis for MSD. The hydrographs were decomposed into
three components: groundwater infiltration (GWI), base wastewater flow (BWF), and rainfall-derived inflow
and infiltration (RDII) hydrographs, as shown schematically in Figure 2.
Figure 2 Hydrograph Decomposition into GWI, BWF, and RDII
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2.1.1 Dry Weather Flow
The dry weather flow (DWF) consists of the GWI plus the BWF. Using the SSOAP Toolbox and the
rainfall data obtained from the nearby airports, Stantec was able to generate dry weather diurnal patterns
for each WWTF by excluding days with a rainfall influenced pattern. Stantec also calculated the yearly
and seasonal average dry weather flow at each WWTF. The results of the dry weather analysis are
discussed in Section 2.2
2.1.2 Groundwater Infiltration
The GWI is flow that seeps into sewer pipes through holes, cracks, joint failures, and faulty connections.
By calculating the minimum nighttime flow during the dry weather days, Stantec was able to estimate the
amount of GWI within the system. Typically, the GWI is defined as 80% of the minimum nighttime flow.
Stantec calculated yearly and seasonal average GWI at each WWTF. The results of the groundwater
analysis are discussed in Section 2.3.
2.1.3 Rainfall-Derived I/I
RDII is the increased portion of water flow in a sewer system that occurs during and after a rainfall event.
There are various methods to estimate RDII in a sanitary sewer system. The R value approach is the most
commonly used method in estimating RDII. The R value represents the fraction of rainfall that gets into the
sewer system. The SSOAP Toolbox was used to conduct the RDII analysis in MSD’s system. In order to
get an accurate representation of the rainfall, Stantec used the GARR data to create a rainfall timeseries
for each WWTF by averaging the rainfall over the tributary area. The RDII hydrographs were separated
from the full hydrographs and the R value was calculated using the tributary area for each WWTF as shown
in Figure 3. The results of the RDII analysis are discussed in Section 2.4.
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Figure 3 Wastewater Treatment Facilities Tributary Area
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2.2 DRY WEATHER FLOW ANALYSIS RESULTS
The dry weather flow analysis consisted of a rainfall analysis to identify dry weather periods. The dry
weather periods were used to compute yearly and seasonal average dry weather flow and dry weather
patterns. The results of the dry weather flow analysis are discussed in detail in the following sections.
2.2.1 Rainfall Analysis
Data recorded at the St. Louis Lambert International Airport and the Spirit of St. Louis Airport were used
to identify rainfall events that happened between July 1, 2015, and December 31, 2020. Stantec identified
644 distinct events. Figure 4 shows the depth-intensity scattergraph of all events. Table 1 shows the
recurrence interval1 for all events, except for 83 events that lasted less than 5 minutes and thus were not
classified.
A summary of the most significant rainfall events is as follows:
The storm event that happened between December 26, 2015, and December 28, 2015, had the
largest total depth2 (8.33 inches), however the peak intensity was only the 47th largest intensity.
The August 8, 2020, storm event had the largest peak intensity (2.68 inches per hour), however
the total depth of this event was only 3.51 inches.
The December 26, 2015, storm event also had the longest recurrence interval: between 50 and
100 years. Most of the events have a recurrence interval of less than 1 month.
Table 1 Average Recurrence Interval for Rainfall Events
Average Recurrence Interval Number of Events
<1 Month 541
1-3 Month 3
3-6 Month 7
6-12 Month 3
1-2 Year 1
2-5 Year 3
5-10 Year 2
10-25 Year 0
25-50 Year 0
50-100 Year 1
1 The average amount of time between events of a certain magnitude, based on statistical analysis
2 The cumulative amount of rainfall recorded over a period of time, expressed as the depth of water collected at a
given point
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Figure 4 Depth vs Intensity Scattergraph
2.2.2 Dry Weather Day Selection
The rain gauge data was also used to identify dry weather. If the rain gauges at both airports did not
record any rainfall for three consecutive days, the third day was identified as a dry day. Table 2 shows
the number of dry days identified per year. More than 30% of the days each year were identified as dry
days, indicating that enough days were identified for the dry weather results to be statistically accurate.
Table 2 Number of Dry Weather Days
Year Number of Dry Days
2015 89*
2016 127
2017 150
2018 112
2019 116
2020 146
*The dry days were identified only after July 1, 2015
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2.2.3 Average Dry Weather Flow Results
Figure 5 shows the fiscal year average dry weather flow from FY2016 to FY2020 for the seven WWTFs
and the total rainfall depth. As shown, FY2018 had the lowest average dry weather flow as well as the
lowest total rainfall. FY2019 had the highest average dry weather flow of the 5 years analyzed. Figure 6
shows the yearly average dry weather flow compared the average Mississippi River level. The figure
clearly shows a correlation between the river level and the average dry weather flow. When the river level
is low, the average dry weather flow is also low and reciprocally when the river level is high. Figure 7
shows the yearly average dry weather flow in respect of the 5-year average. It shows that during the 2019
fiscal year, the seven WWTFs received between 0% and 30% more flow than the 5-year average. During
the 2018 fiscal year, which was the driest year, the dry weather flow was below the 5-year average.
Figure 5 Yearly Average Dry Weather Flow
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Figure 6 Yearly Average Dry Weather Flow and Average Mississippi River Level
Figure 7 Yearly ADWF in respect of 5-year ADWF
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Figure 8 shows the seasonal dry weather average between the third quarter (July-September) of 2015
(Q3 2015) and Q4 2020 for Lemay WWTF. The graph shows the average dry weather flow is generally
higher during Q2 than the rest of the year. This is likely a result of significant water infiltration in the
system as the wastewater produced doesn’t change greatly between seasons or years. Seasonal
average dry weather flow for the seven WWTFs are included in Appendix A.
The SSOAP toolbox was used to generate weekday and weekend diurnal (24-hour) patterns using the
flow data for all dry days. A comparison between the weekday diurnal patterns for each year at the
Coldwater WWTF is shown in Figure 9. The horizontal axis represents the time of day, with “0”
representing midnight and “24” representing midnight the following day. The vertical axis represents the
fractional value of the flow data at a given time of day compared to the average daily value. Values
greater than 1.00 on the vertical axis indicate flow rates greater than the average and values less than
1.00 indicate flow rates less than the average.
Comparisons between the weekday yearly diurnal patterns and weekend yearly diurnal patterns for the
seven WWTFs are included in Appendix B. A comparison between the weekday diurnal patterns for
each quarter at the Coldwater WWTF is shown in Figure 10 Comparisons between the seasonal
weekday diurnal patterns and seasonal weekend diurnal patterns for the seven WWTFs are included in
Appendix C.
Figure 8 Lemay WWTF Seasonal ADWF
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Figure 9 Coldwater WWTF DWF Yearly Weekday Diurnal Pattern
Figure 10 Coldwater WWTF DWF Seasonal Weekday Diurnal Pattern
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2.2.4 Key observations
Key observations from the dry weather flow analysis results are:
1. The average dry weather flow appears to be influenced by the total rainfall amount through
groundwater infiltration – During the flow monitoring period, higher average dry weather flows were
observed during the years when more rainfall fell. Additionally, the lowest rainfall total occurred in
2018 and it corresponds to lower average dry weather flows at the WWTFs.
2. There appears to be significant water infiltration – The seasonal average dry weather flow can be
doubled from one quarter to the next. Most of the time, the seasonal average dry weather flow is
higher during the second quarter than during the rest of the year as a result of water infiltration.
3. The diurnal patterns look consistent – There is little variation in the diurnal patterns between years
and seasons. All patterns have at least one peak in the morning and some have a second peak
during the evening. All patterns have a minimum flow during the night.
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2.3 GROUNDWATER INFILTRATION ANALYSIS RESULTS
The dry weather periods were used to compute the average minimum nighttime flow in order to estimate
groundwater infiltration. Typically, dry weather infiltration is estimated as 80 percent of the minimum
nighttime flow. The results of the groundwater infiltration analysis are discussed in detail in the following
sections.
2.3.1 Groundwater Infiltration Results
Figure 11 shows the average groundwater infiltration at the seven WWTFs. The groundwater infiltration
follows the same trend as observed for the average dry weather flow in Figure 5. The groundwater
infiltration peaks during the 2019 fiscal year.
Figure 11 Average Groundwater Infiltration
Figure 12 shows the seasonal groundwater infiltration average between Q3 2015 and Q4 2020 for the
Lemay WWTF. The graph shows groundwater infiltration is generally higher during Q2 than the rest of the
year. Seasonal groundwater infiltration for the seven WWTFs are included in Appendix D.
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Figure 12 Lemay WWTF Seasonal GWI
2.3.2 Groundwater Infiltration Analysis
Figure 13 shows a comparison between the average dry weather flow and groundwater infiltration for the
Bissell WWTF. It clearly shows the average dry weather flow and the minimum nighttime flow follow the
same trend every year. When reading Figure 13, it is important to note if the green line and the blue line
are close, it means there is a significant fraction of the ADWF that is GWI. Comparisons between the
ADWF and the GWI for the seven WWTFs are included in Appendix E.
Figure 14 shows the ratio between groundwater infiltration and the average dry weather flow for all
WWTFs. The ratio varies between 20% and 70%. Bissell Point WWTF dry weather flow has the highest
share of groundwater infiltration at almost 70% whereas Missouri River WWTF dry weather flow has
consistently the lowest share of groundwater infiltration at approximately 30%.
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Figure 13 Bissell WWTF Groundwater Infiltration Analysis
Figure 14 Ratio Between GWI and ADWF
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2.3.3 Groundwater Infiltration Estimation
Stantec compared the groundwater infiltration estimation between three different calculation methods:
1. Calculated as 80% of the average minimum nighttime flow observed (first estimate)
2. Calculated from the average dry weather flow and population estimates (second estimate)
3. Calculated from the average dry weather flow and billed water usage (third estimate).
Table 3 shows the results of the comparison between the three estimation methods.
The first estimate of GWI was obtained directly from the flow data, by first extracting the average
minimum nighttime flow and then calculating 80% of this value. This value is shown in the fourth column
(80% MNF) of the table below.
The second estimate of GWI was calculated by using published values to calculate base wastewater flow
(BWF) and subtracting the BWF from ADWF. The U.S Census Bureau estimates the population of St.
Louis city and county to be approximately 1.3 million3 and the EPA estimates that on average, each
American uses 82 gallons of water per day4. Using these assumptions to calculate BWF, Stantec
calculated the GWI estimate shown in the fifth column (GWI from Population) of the table below.
The third estimate of GWI was obtained directly from the flow data and MSD’s billed water usage data, by
subtracting billed water usage from ADWF. This estimate is shown in the eighth column (GWI from Billed
Usage) of the table below.
In Table 3, the percentage difference was calculated in respect to the first method of estimation. The
results show that all three methods estimate the groundwater infiltration within an acceptable margin of
error.
Table 3 Groundwater Infiltration Estimates
First Estimate Second Estimate Third Estimate
Fiscal
Year
Total
Rain (in)
ADWF
(MGD)
80% MNF
(MGD)
GWI from
Population
(MGD)
Difference
(%)
Billed Usage
(MGD)
GWI from
Billed Usage
(MGD)
Difference
(%)
2016 41.65 291.4 169.4 185.2 9.3% 123.4 168.0 -0.8%
2017 44.79 282.2 159.4 176.0 10.4% 124.1 158.1 -0.8%
2018 32.51 226.1 121.8 119.9 -1.6% 124.1 102.0 -19.4%
2019 40.60 324.1 188.2 217.9 15.8% 122.2 201.9 7.3%
2020 43.68 315.0 186.7 208.8 11.8% 117.6 197.4 5.7%
3 source: https://www.census.gov/quickfacts/fact/table/stlouiscitymissouri,stlouiscountymissouri/PST045219
4 source: Statistics and Facts | US EPA
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2.3.4 Key observations
Key observations from the groundwater infiltration analysis results are:
1. The ratio between GWI and ADWF varies between wastewater treatment facility – The Bissell Point
WWTF ratio between GWI and ADWF is almost 70% and the Missouri River WWTF ratio is only
approximately 30%. All other WWTF ratios are between these numbers. This is a reflection of the
sewer pipe conditions allowing more or less groundwater infiltration.
2. Groundwater infiltration is significant – Except for the Missouri River WWTF and the Lower
Meramec WWTF, 40% or more of the ADWF is attributed to GWI. For the Bissell Point WWTF and
the Lemay WWTF, the two largest treatment facilities, GWI was estimated to be at least 110 MGD
combined.
3. The groundwater infiltration estimation is reasonable – Three different methods were used to
estimate GWI. The three different methods obtained similar results thus reinforcing the confidence
level in the findings.
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2.4 RAINFALL DERIVED I/I ESTIMATION
The SSOAP Toolbox was used to conduct the RDII analysis for MSD’s service area. The SSOAP Toolbox
was used to estimate the total R value (i.e., percent of the rainfall that enters the sewer system) for each
rainfall event that occurred between January 2016 and December 2020. The results of the RDII analysis
are discussed in detail in the following sections.
2.4.1 Total R results
Figure 15 shows the average total R for the seven WWTFs. In Figure 15, the continuous lines show the
yearly average, and the dashed lines show the 5-year average for each plant. Table 4 contains the same
information in a tabular format. Lemay WWTF and Bissell Point WWTF have the highest total R: 13.3%
and 13.9% respectively for the 5-year average, most likely because these sewer networks are combined
sewer systems. The Missouri River WWTF 5-year average total R is below one percent, and the 5-year
average total R for the remaining WWTFs is between 1% and 5%.
Figure 15 Total R Results
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Table 4 Total R Results
2016 2017 2018 2019 2020 Overall
Bissell Point WWTF 11.5% 13.7% 11.7% 12.7% 19.3% 13.9%
Coldwater WWTF 3.0% 4.4% 3.1% 4.3% 5.2% 4.0%
Fenton WWTF 1.4% 2.5% 1.5% 4.7% 2.0% 2.6%
Grand Glaize WWTF 1.6% 2.5% 1.9% 2.5% 2.6% 2.2%
Lemay WWTF 7.7% 12.7% 9.8% 22.9% 10.3% 13.3%
Lower Meramec WWTF 1.6% 4.4% 1.9% 10.5% 2.6% 4.3%
Missouri River WWTF 0.8% 0.9% 0.7% 1.0% 1.0% 0.9%
Figure 16 shows the maximum peaking factor for each for the seven WWTFs. The peaking factor, which
represents the magnitude of difference between maximum flow and average flow, is calculated as the
ratio between the maximum instantaneous flow (i.e., peak flow) and the average dry weather flow. Unlike
the total R analysis, Bissell Point WWTF and Lemay WWTF exhibited the lowest peaking factors.
Coldwater WWTF and Lower Meramec WWTF exhibited peaking factors higher than 7.
Figure 16 Maximum Peaking Factor
2.4.2 Range of Total R
Figure 17 shows the standard deviation of the total R. This is an indicator of how much the total R values
for each individual event vary. A higher standard deviation means that the total R values vary more
between events. A higher variation indicates that the total R is likely influenced by factors such as the
rainfall depth, antecedent conditions, and the groundwater level.
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Figure 17 Total R Standard Deviation
Figure 18 through Figure 21 show scattergraphs of the total R and rainfall depth, 1-week antecedent
rainfall depth, 1-month antecedent rainfall depth, and Mississippi River at USGS 07010000, respectively,
for the Coldwater WWTF. The graphs show the spread of total R values for each individual event and
how much the R values are influenced by each factor. Figure 22 shows the location of the four river
gauges Stantec used to create total R scattergraphs. Total R scattergraphs for the seven WWTFs are
included in Appendix F.
These graphs show very scattered results when trying to compare R values with any single wet-weather
related parameter. This observation is typical for most communities with I/I challenges. The scatter results
indicate that there is no simple correlation between I/I and any one component. The causes of I/I are
often complicated and depend on multiple factors that are not simply represented.
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Figure 18 Rainfall Depth-Total R Scattergraph for Coldwater WWTF
Figure 19 One-Week Antecedent Rainfall-Total R Scattergraph for Coldwater WWTF
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Figure 20 One-Month Antecedent Rainfall-Total R Scattergraph for Coldwater WWTF
Figure 21 USGS 07010000 Level-Total R Scattergraph for Coldwater WWTF
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Figure 22 USGS River Gauges
2.4.3 I/I Breakdown
Stantec calculated the proportion of I/I due to groundwater infiltration (“dry” I/I) and the proportion due to
rainfall (“wet I/I”). This calculation was performed using total flow, average dry weather flow, and MSD
billed usage data. Table 5 shows the results of the calculation. The results indicate that the majority of I/I
received by the WWTFs is due to infiltration.
Table 5 I/I Estimation
Fiscal Year Dry I/I Wet I/I
2016 80% 20%
2017 76% 24%
2018 71% 29%
2019 74% 26%
2020 78% 22%
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2.4.4 Key observations
Key observations from the RDII analysis results are:
1. The total R value varies greatly between wastewater treatment facilities – Bissell Point WWTF
and Lemay WWTF are the plants with the highest total R values: 13.9% and 13.3% 5-year
average respectively. The total R values for the five other WWTFs are below 5%.
2. The RDII is influenced by external factors – Stantec observed that the individual R values for
each event were not identical, which is typical for infiltration-dominated systems. This shows a
complex influence from factors such as the rainfall depth and antecedent rainfall conditions.
3. Some WWTFs observe high peaking factors – Lower Meramec WWTF and Coldwater WWTF,
despite having R values lower than 5%, observed peaking factors above 5 each year between
2016 and 2020. This shows that there is significant rainfall inflow in their tributary areas compared
to the amount of average dry weather flow produced.
2.5 FLOW ANALYSIS CONCLUSIONS
The analysis of MSD’s flow and rainfall data provided insights on the amount of I/I within the sewer
network. In summary, the project team completed the following:
The dry weather flow analysis revealed an influence from the rainfall amount on the average dry
weather flow observed at the plants. It also showed that the average dry weather flow varies
greatly between season with the dry weather flow being typically higher during Q2. This suggests
significant groundwater infiltration in the system.
The groundwater infiltration analysis revealed that up to 70 percent of the average dry weather
flow could come from groundwater infiltration on average over a year. Overall, the groundwater
infiltration was estimated as 57 percent of the average dry weather flow between 2016 and 2020.
The RDII analysis indicated that except for the Missouri River WWTF, all other facilities have high
RDII. The total-R values (i.e., percent of the rainfall that enters the sewer system) are more than
1%. Bissell Point WWTF and Lemay WWTF total-R values are above 10% because their tributary
areas are mostly combined sewers.
The total-R scatter results indicate that there is no simple correlation between I/I and any one
component. The causes of I/I are often complicated and depend on multiple factors that are not
simply represented.
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Overflow Volume Estimates
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3.0 OVERFLOW VOLUME ESTIMATES
The analysis in the previous section focused on I/I measured in the total wastewater flow received at the
WWTFs. A portion of the flow in the sewer system may exit the sewer system before reaching the
WWTFs, and is therefore not included in the I/I analysis. Flow can exit the system through constructed
outfalls intended to relieve the system (e.g., to protect homes from sewer backup) or overflow out of the
system through manholes, broken pipes, or other system features. Overflow conditions can occur for
various reasons, including pipe blockages, broken pipes, pump outages, and overcharged sewers.
Overflow volumes are often problematic to measure in the field, but MSD makes reasonable efforts to
provide and record estimated volumes.
MSD reports estimated volumes for constructed sanitary sewer overflow (SSO) activations and other
sanitary sewer overflows in semi-annual reports to EPA. MSD also reports estimated volumes for
unpermitted combined sewer overflow (CSO) discharges in annual reports to EPA. Stantec compiled the
available overflow volume estimates from the semi-annual and annual reports and summarized them in
the tables below.
Table 6 Constructed SSO Activation Data Summary
Year Total
Events
Events with
Unknown Volume
Events with
Estimated Volume
Total Estimated
Volume (Gallons)
2016 618 443 175 14,008,058
2017 479 405 74 13,814,774
2018 254 207 47 4,147,190
2019 728 620 108 24,444,605
2020 506 439 67 9,806,227
Source: MSD’s EPA Semi-Annual Report Data, Table A-1
Table 7 Sanitary Sewer Overflow Data Summary
Year Total
Events
Events with
Unknown Volume
Events with
Estimated Volume
Total Estimated
Volume (Gallons)
2016 168 30 138 9,895,860
2017 170 16 154 52,746,393
2018 152 4 148 8,907,950
2019 209 35 174 203,697,996
2020 148 6 142 11,299,035
Source: MSD’s EPA Semi-Annual Report Data, Table C-1
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Overflow Volume Estimates
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Table 8 Unpermitted CSO Discharge Data Summary
Year Total
Events
Events with
Unknown Volume
Events with
Estimated Volume
Total Estimated
Volume (Gallons)
2015 68 0 68 94,171,470
2016 43 1 42 12,851,421
2017 71 0 71 54,540,707
2018 45 0 45 5,652,230
2019 125 0 125 281,778,905
Source: MSD’s EPA Annual Report Data, Appendix J
MSD’s CSO Long Term Control Plan Update dated February 2011 included an estimated systemwide
CSO volume for the typical year (year 2000) rainfall. This estimate, 13.3 billion gallons, was based on
MSD’s hydraulic models at that time. MSD’s progress toward achievement of CSO Control Measures is
ongoing, and is documented in the annual reports to EPA. An updated estimate of the systemwide CSO
volume is not currently available.
MSD has made a substantial investment in the past decade to address the issue of overflows from the
sewer system, primarily by increasing collection and treatment capacity. Because I/I is one of the
contributing factors to overflows, MSD has also taken steps to reduce I/I in portions of the sewer system.
MSD will continue to address overflow issues for a number of years under the terms of its Consent
Decree.
While MSD’s actions to address overflows have been considerable, as it pertains to allocation of I/I costs
the improvements do not represent a material change in MSD’s overall system or in the implications of I/I
volumes or characteristics that MSD must manage. On a systemwide basis, I/I characteristics will
continue to reflect the makeup of the MSD collection system, which includes a significant portion of
combined sewers (designed to collect inflow) and separate sanitary sewers. Similarly, as overflows are
eliminated, the total I/I volume will continue to make up a large portion of the total flow volume to the
treatment plants. While I/I reductions may occur in some parts of the system, these flow reductions may
be offset by flow increases in other parts of the system, such as areas where overflows are eliminated
due to capacity increases (which capture flows that previously would have exited the system).
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INFILTRATION AND INFLOW DATA SUMMARY – 3RD DRAFT REPORT
Appendix A Seasonal Average Dry Weather Flow Graphs
SEASONAL AVERAGE DRY WEATHER FLOW
GRAPHS
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Appendix A Seasonal Average Dry Weather Flow Graphs
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Appendix A Seasonal Average Dry Weather Flow Graphs
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Appendix A Seasonal Average Dry Weather Flow Graphs
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Appendix A Seasonal Average Dry Weather Flow Graphs
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INFILTRATION AND INFLOW DATA SUMMARY – 3RD DRAFT REPORT
Appendix B Yearly Diurnal Patterns
YEARLY DIURNAL PATTERNS
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Appendix B Yearly Diurnal Patterns
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Appendix B Yearly Diurnal Patterns
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Appendix B Yearly Diurnal Patterns
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Appendix B Yearly Diurnal Patterns
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Appendix B Yearly Diurnal Patterns
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Appendix B Yearly Diurnal Patterns
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Appendix B Yearly Diurnal Patterns
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INFILTRATION AND INFLOW DATA SUMMARY – 3RD DRAFT REPORT
Appendix C Seasonal Diurnal Patterns
SEASONAL DIURNAL PATTERNS
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Appendix C seasonal Diurnal Patterns
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Appendix C seasonal Diurnal Patterns
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Appendix C seasonal Diurnal Patterns
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Appendix C seasonal Diurnal Patterns
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Appendix C seasonal Diurnal Patterns
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Appendix C seasonal Diurnal Patterns
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Appendix C seasonal Diurnal Patterns
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INFILTRATION AND INFLOW DATA SUMMARY – 3RD DRAFT REPORT
Appendix D Seasonal Groundwater Infiltration Graphs
SEASONAL GROUNDWATER INFILTRATION
GRAPHS
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Appendix D Seasonal Groundwater Infiltration Graphs
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Appendix D Seasonal Groundwater Infiltration Graphs
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Appendix D Seasonal Groundwater Infiltration Graphs
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Appendix D Seasonal Groundwater Infiltration Graphs
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INFILTRATION AND INFLOW DATA SUMMARY – 3RD DRAFT REPORT
Appendix E Groundwater Infiltration Analysis Graphs
GROUNDWATER INFILTRATION ANALYSIS
GRAPHS
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Appendix E Groundwater Infiltration Analysis Graphs
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Appendix E Groundwater Infiltration Analysis Graphs
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Appendix E Groundwater Infiltration Analysis Graphs
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Appendix E Groundwater Infiltration Analysis Graphs
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INFILTRATION AND INFLOW DATA SUMMARY – 3RD DRAFT REPORT
Appendix F Total R Scattergraphs
TOTAL R SCATTERGRAPHS
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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Appendix F Total R Scattergraphs
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