ANALYSIS OF RAINFALL AND ITS INFLOW INTO MOBILE, ALABAMA’S,
ESLAVA SEWER SHED SYSTEM
Jerrod Frederking, Department of Earth Sciences, University of South Alabama, Mobile, AL
36688. E-mail: twisterj@gmail.com.
Every city across the nation has to deal with a common problem, sewage. Infiltrating
rainwater filling sewer systems beyond capacity affects your neighborhood, community and
region. The City of Mobile in Dog River Watershed has been forced to address recurrent
problems with infiltrating rainwater and Sanitary Sewer Overflows. Overflows have been a
common and complex problem combined with century old pipes and rain water infiltration. Not
only do overflows caused by rainwater decrease system capacity to collect and treat raw sewage,
they also degrade water quality in the water shed by overflowing into storm drains, yards, homes
and businesses. This study utilized rainfall and system flow data collected by Mobile Area Water
and Sewer System as well as data from National Weather Service. The rainfall and flow data was
compared and evaluated with National Weather Service Doppler radar rainfall estimates to gauge
how much water due to infiltration enters the Eslava Creek sewer shed. A sewer shed, defined
similarly to a watershed, collects sewage from a delineated area and concentrates it into a main
line to flow into treatment plants. Although metering and rainfall data have been collected for
several years, it is difficult to relate this data as to what will cause an overflow. This study found
that overflows can be exacerbated by excessive rainfall infiltration.
Keywords: Infiltration, Sanitary Sewer Overflows, Alabama
Introduction
The Dog River Watershed has experienced an increasing number of events that affect
water quality over the past years. Sewage overflowing into the watershed is a repeated and high
priority problem for the City of Mobile and the company that combats that problem, Mobile Area
Water and Sewer System (MAWSS). One of the major problems that MAWSS encounters in the
Dog River Watershed is the problem of Sanitary Sewer Overflows (SSO’s). An SSO is an event
that is defined as an overflow of untreated sewage into the environment. SSO’s can occur
whenever blockages, excess water, or combinations of these cause raw sewage in the system to
overflow into the watershed. SSO events are hazardous to health, cause damage to buildings and
businesses, threaten the environment and are also illegal by the Clean Water Act (Irving 2007).
Because SSOs contain raw sewage they can carry bacteria, viruses, protozoa (parasitic
1 organisms), helminths (intestinal worms), and borroughs (inhaled molds and fungi) (EPA 1996).
It can clearly be seen even if SSOs are unintended, they cause water quality degradation quickly
and prove to spread disease and cause large amounts of cleanup cost.
In the City of Raleigh, North Carolina, heavy rainfall events account for nearly thirty
percent of all SSO’s (Raleigh 2009). Excess water infiltrating into a sewer system decreases
system capacity to treat water and can cause sewage to back up and overflow. Common
conditions in sewer pipes that exacerbate the infiltration include, breaks in old pipes, settlement
of pipes causing joint expansion, and connections with building water runoff catchments
(MAWSS defects 2010) . These overflows are clearly undesirable and unwanted in places of
work and homes as it affects nearly all aspects of the inhabitants from water quality to air
quality.
Research Question
Does rainwater infiltration into the Eslava sewer shed sewer system cause increased flow
in lines contributing to Sanitary Sewer Overflows (SSO’s)?
Methods
This project has multiple and complex datasets associated with it. This project started
with a meeting with MAWSS officials to determine a “sewer shed” area to research. On Friday
February 26th,2010, a meeting with MAWSS managers was set to discuss the scope of the project
and gain access to the rain gauge data and system flow data. This meeting was successful and
data was readily and quickly made available for this project. Once data and project direction was
established in a particular sewer shed, radar data and rain gauge and flow data were procured for
2 representative stations. For this project, a major precipitation event of an inch or more of
precipitation was chosen. When a particular event was found, it was determined to define the
event as the time from when rain was nearly continuous and steady for several hours resulting in
a daily total above 1 inch.
The first set of data manipulated was rain gauge data. Nearly all of the MAWSS sites
(MAWSS data 2010) are co-located with flow meters making rain totals concurrently located
above the with flow data sensor. This co-location allows the flow meter and rain gauge to be
powered from a common power source. The data from the rain gauge network is recorded in 1
minute increments by hundredths of an inch. The data was entered into a spreadsheet program.
The minute precipitation data was summed by hour to match the hourly storm total radar data.
The rainfall data was kept in increments of 0.01 inches. This was done for the event to compute
sums comparable for an event in a unit per hour time scale.
Flow data was the second collection of data to be manipulated. Flow data is recorded in
15 minute increments and measured in million gallons per day (mgd). The flow measured in mgd
needs to be converted to gallons per hour to be of similar spatial resolution to the hourly rainfall
and hourly summed radar data. Daily flow in mgd was converted to gallons per hour (gph). The
flow meter measurements were plotted simultaneously on the same graph to compare the values
of flow data from larger to smaller collection pipes.
To compare radar rainfall data to the rainfall data recorded by the gauges, an average
hydrologic method to weigh the precipitation was used, specifically a Thiessen polygon. A
Thiessen polygon analysis takes a set of rain gauge data and weighs the individual values to
create an average precipitation for an entire shed. A sewer shed map was obtained from MAWSS
specifically for the Eslava sewer shed. A sewer shed map is the area of Mobile defined by
3 draining a certain area of sewer pipes to a common point. A scaled sewer shed map was obtained
from MAWSS and overlaid on standard engineering graph paper. On this A4 letter sheet one
mile is equal to a 6 by 6 square block. This leads to calculating a square mile by 36 blocks. The
rain gauges were connected by triangle to the next closest two stations. These triangles allowed
the ability to section off weighted areas for each rain gauge and calculate the specific area
weight. The number of blocks was counted and summed to determine what percentage of the
total area each sub shed contains. This total area must add up to 100 percent of the sewer shed to
produce a representative aerial Theissen precipitation average.
The last area of data needed to compare is National Weather Service radar data. Archived
radar data can be procured by visiting the National Climatic Data Center (NCDC) site and by
using a program provided by NCDC, converting that archived data into a readable format by a
radar display program. The program used to display and manipulate the radar data is created by
Gibson Ridge Software and is the Level 3 radar program. The Level 3 program was used to view
storms as they passed over the sewer shed and rain gauge network over a period of a several
hours for each specific rainfall event. At the end of the event, a storm total precipitation map was
generated to compare the estimated rainfall from the radar to the data recorded by the rain gauge
network. Radar data from each hour was ingested into the program and then totaled for an events
total precipitation. The total radar estimated precipitation was used to estimate how well the
radar estimated precipitation compares to the actual rain gauge values. The Thiessen estimate is
used to calculate the estimate of how much water runoff would be available to flow into the
sewer shed from a given rainfall event.
4 Results
The results of this research are as follows. I first chose a rainfall event of which to
compare data. This event was chosen due to more uniform precipitation which would provide an
even precipitation distribution over the entire Eslava sewer shed. The significant event chosen
was a heavy rainfall event from January 16th 2010.
Beginning the event, radar data was taken from the Mobile Doppler Radar site. Showers
and thunderstorms were
shown to have moved over
the area in fairly steady and
uniform manner from shortly
before 6am and continued
until 3pm that afternoon.
When calculating an average
Thiessen value, it returns a
Figure 1 : Storm total precipitation for the event on 1/16/2010 showing
1.25-1.75inch Storm Total Precipitation
1.65 inch value of
precipitation falling over the area from 5am until 3pm. As the storm total precipitation shows
average precipitation was estimated to be between 1.25 and 1.75 inches of precipitation. This
close correlation shows that while Thiessen values may be more precise, radar would have been
sufficient to estimate rainfall values well in this particular case. Radar data also shows a slight
yellow area over the USA campus on the radar which fits with the slightly higher 1.67 value
measured at that site.
When comparing the flow data, a clear trend is shown in the flow rates shortly lagging
the heavy rainfall. The flow data has some degree of variability as most flow is usually
5 considered turbulent and changes with time as the data shows (Mays 2004). Heavy and steady
precipitation begins around the 5am time period and continues through the 9am time period. As
seen on the Comparison Graph (Appendix A: Comparison), as water infiltrates, flow from the
runoff increases steadily through the 9 to 11 am period with only slight additions through the end
of the event through 3pm. As the flow data show, there is a noted increase in all of the flow
meters in Eslava sewer shed as the event progresses through the end. Major pipes, notably meters
1, 9 and 13 staying at nearly double the flow capacity load measured less than 6 hours earlier.
With similar baseflow usage, some arguments could made that residents would be increasing
sewer use as they wake up in the morning. There is some truth that can be shown that as large
uses in the morning increase flow, peak baseflow factors decrease downstream pipes(Delleur
2007). Another fact can be mentioned that a 43 inch pipe such as EL-01, will not be as sensitive
to small changes but will be large changed. A rapid change this large, on the order of millions of
gallons in a rapid increase could only be attributed to the hundreds of thousands of gallons of
rainwater infiltrating into the system. For this event, if you estimate thirty percent infiltrating
from 1.65 inches, that equates to roughly 160 million gallons of infiltration!
Conclusion
The data explored in the Eslava sewer shed can show beyond reasonable doubt that
rainwater does in fact infiltrate the sewer system. This impact has costly and potentially
hazardous consequences when overflowing into the Dog River Watershed. Several facts are clear
that if SSO’s can be prevented or first drastically reduced as large line replacement and
conditioning has been done, the water quality in Dog River and its tributaries will improve. Since
6 all of us are dependent on sewer systems as a way of life, we each are responsible for the care
and treatment of sewage collection systems in the City of Mobile.
Bibliography
City of Irving, Texas. 2007. Sanitary 101. Handbook. Irving, Texas.
City of Raleigh, North Carolina. 2009. 2008-2009 Wastewater Collection and Treatment System
Report. Raleigh, North Carolina.
Delleur, Jacques, Lavere Merritt, and Howard Selznick. Gravity Sanitary Sewer Design and
Construction. Reston, Virginia: American Society of Civil Engineers, 2007. Pages 50-53.
Mays, Larry W.. Urban Stormwater Management Tools. New York: McGraw-Hill Inc., 2004.
Page 4.8-4.10.
Mobile Area Water and Sewer System(MAWSS defects). 2010. Possible Sanitary Sewer Lateral
Defects. Mobile Alabama.
Mobile Area Water and Sewer System(MAWSS data). 2010. GIS Rain gauge and Flow metering
data. Jan 14, Jan 16, 2010.
Mobile Area Water and Sewer System(MAWSS data). 2010. GIS Data outlining Eslava Sewer
Shed Rehabilitations. Jan 14, Jan 16, 2010. National Climatic Data Center(NCDC). Radar data from site Mobile, AL from 5am 3pm(11UTC-21UTC) Jan 16, 2010.
United States Environmental Protection Agency. 1996. Sanitary sewer overflows what are they
and how can we reduce them? Southcat Electronic Format.
http://www.epa.gov/npdes/pubs/ssodesc.pdf. 16 April 2010.
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Appendix A: Flow Meter Data for 1/16/2010 and a dry event on 1/14/2010
Dry Day Flow Compared to Rainfall Flow(Gallons/hour)
1200000
1000000
800000
600000
400000
EL‐01 Dry Day Flow
200000
EL‐01 Wet Flow(1/16/10)
0
Comparison of Rainfall Flow Meter data(Gallons/hour) for 1/16/2010
1200000
EL‐03
1000000
EL‐02
800000
EL‐01
EL‐05
600000
EL‐07
EL‐09
400000
EL‐10
200000
EL‐11
EL‐12
0
EL‐13
8 EL‐14
EL‐15
Appendix A: Thiessen Polygon
9 Appendix A: Eslava Sewer Shed Rehabilitation
10