Wastewater Collection System Rehab

OHM-ADVISORS.COM

Wastewater Collection System Rehab

The High Hurdle of Measurable Flow

Reduction

MWEA 2013 Annual Conference

Gregory P. Kacvinsky, P.E.

OHM Advisors

ARCHITECTS. ENGINEERS. PLANNERS.

Investing to Reduce Flows

Identify System

Problems

Flow Metering

Modeling and

Analysis

Evaluation of

Alternatives

Implement CIP

Measure Success or

Identify Failures

When alternatives

are evaluated:

Do we really

understand all

potential costs for

each alternative?

How (and where)

will we measure

success?

Do we really

understand the cost

efficiencies of all

alternatives?

Why Do We Invest?

Sewer pipes and

manholes are

deteriorating

More stringent wet

weather requirements at

WWTP

Documented SSOs,

Consent Orders

Desire to reduce bill to

wastewater treatment

authority (i.e. DWSD)

How Do We Invest?

Source Removal (pipe/lateral

rehab, manhole repair,

replacement)

Wet weather storage

Transport and treat

Source Removal 101

How do you measure flow

reduction success?

Volume?

Peak?

Baseflow?

Where do you measure flow

reduction?

WWTP?

Collector sewer?

Interceptor sewer?

Measuring flow reduction at a

regional level: hard to demonstrate

Measuring flow reduction at a

neighborhood level: easier to

demonstrate

Misconceptions on flow reduction

from rehab

Source Removal 101

Important to set the goals and manage

expectations before a source removal

program

• What percentage of peak and

baseflow do we need to reduce? Is

one or the other more important?

• How much flow meter history do we

have prior to rehab?

• What is the plan for post-rehab flow

metering?

• Who will evaluate pre- vs. post-

rehab success? What method(s)

will they use?

Case Studies in I/I Removal

Case Study Communities

Municipalities tributary to key

interceptors flowing into regional

systems

• Individual communities pay

bills to regional authority

based on metered flows

• Total bills based on total

measured flow volume

• Additional charges assessed

for exceeding contractual

peak flows

• Dual pressures (local billing

and MDEQ ACOs)

Wealth of flow data

Motivation to reduce I/I

flows

Example 1

• Initiated sewer/manhole rehab

program to reduce measured

flows and wet weather peaks

• Rehab was performed in

various neighborhoods, mostly

older sewers

• Several years of pre-rehab

flow meter data (continuous)

• About 2 years of post-rehab

flow meter data

Example 1

Methods of Analysis

• Community predicted nearly 10 cfs

reduction in wet weather design

flow due to typical values for pipe

lining and manhole rehab

• 13-15 miles of pipe rehabilitated

• ~600 laterals partially lined

• ~150 manholes rehabilitated

• Defect repairs (from smoke testing)

• Independent analysis

• Baseflow analysis

• Event RDII volume vs. rainfall

• Meter Correlation

• Antecedent Moisture Modeling

Example 1

Baseflow Analysis

WAT Community Flow

Long-Term Baseflow Patterns (2007-2011)

5

6

7

8

9

10

11

12

8-Mar 27-Apr 16-Jun 5-Aug 24-Sep 13-Nov

Date

Bas

efl

ow

(cf

s)

2007

2008

2009

2010

2011

Example 1

RDII Volume v. Rainfall – Total Community

WAT Community Flow

Total RDII Volume vs. Total Event RainfallPre- vs. Post-Rehab (May - September data only)

10

100

1000

10000

0 1 2 3 4 5 6

Total Event Rainfall (inches)

Tota

l RD

II V

olu

me

(th

ou

san

d

cub

ic f

ee

t)

Pre-Rehab(2006-2008)

Post Rehab(2010-2011)

Example 1

RDII Volume v. Rainfall – Subdistrict Analysis

Flow Meter 1590 (WAT)


10

100

1000

0 1 2 3 4 5


Tota

l RD

II V

olu

me

(th

ou

san

d

cub

ic f

ee

t)

Pre-Rehab(2007-2008)

Post Rehab(2010-2011)

Example 1

Meter Correlation

Meter correlation measures the wet weather

response of a rehabilitated meter district against

that of a control (non-rehabilitated) district

-0.5

0.0

0.5

1.0

1.5

2.0

2006

2007

2008

2009

2010

2011

Co

rrela

tio

n F

acto

r

Correlation Multiplication Factor

Correlation Additive Factor (baseflow adjustment in cfs)

Example 1

Continuous Modeling

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

8/19 8/20 8/21 8/22 8/23 8/24

Flo

w (

cfs

)

0

1

2

3

4

Rain

(in

/hr)

Observed

Modeled

Rain

6.0

8.0

10.0

12.0

14.0

16.0

18.0

3/4 3/5 3/6 3/7 3/8 3/9

Flo

w (

cfs

)

0

1

2

3

4R

ain

(in

/hr)

Observed

Modeled

Rain

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

3/20 3/21 3/22 3/23 3/24 3/25 3/26 3/27

Flo

w (

cfs

)

0

1

2

3

4

Rain

(in

/hr)

Observed

Modeled

Rain

Pre-rehab calibration

Post-rehab validation

Model predicts RDII Volume to within 1% of observed

Model under-predicts observed RDII volume by 2.5%

Continuous modeling reveals that there is no

systematic under- or over-prediction when

using pre-rehab calibrated model against post-

rehab conditions

This suggests NO CHANGE in wet weather response

Example 1

Findings

• Rehab did not have a

measureable impact on peaks

or volumes

• Rehab effort was scattered,

and difficult to measure

success on a community level

• No positive economic benefit

(quarterly bills not reduced)

• Estimates used for flow

reduction from rehab

activities may be flawed

Example 2

Bloomfield Orchards Subdivision

(Auburn Hills)

• ~450-500 homes

• Footing drain disconnection for

every home

• Several years of pre-rehab flow

meter data (continuous)

• About 3 years of post-rehab flow

meter data

Example 2

Methods of Analysis

• Independent analysis (County)



• Meter correlation

• Continuous modeling

Example 2

Baseflow Analysis


Long-Term Baseflow Patterns (2000-2006)

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

1-Mar 20-Apr 9-Jun 29-Jul 17-Sep 6-Nov

Date

Bas

efl

ow

(cf

s)

2000

2001

2002

2003

2004

2005

2006

Example 2

RDII Volume v. Rainfall



1

10

100

0 0.5 1 1.5 2 2.5 3


Tota

l RD

II V

olu

me

(th

ou

san

d

cub

ic f

ee

t)

2000-2001

2005-2006

Example 2

Continuous Modeling

0.0

0.5

1.0

1.5

2.0

2.5

8/2 8/2 8/3 8/3 8/4 8/4

0

1

2

3

4

Observed

Modeled

Rain

0.0

0.5

1.0

1.5

2.0

2.5

3.0

9/10 9/10 9/10 9/10 9/10 9/11 9/11 9/11

Flo

w (

cfs

)

0

1

2

3

4

Rain

(in

/hh

r)

Observed

Modeled

Rain

0.0

0.5

1.0

1.5

2.0

2.5

6/21 6/21 6/22 6/22 6/23 6/23

0

1

2

3

4

Observed

Modeled

Rain

0.0

0.5

1.0

1.5

2.0

2.5

5/10 5/11 5/11 5/12 5/12 5/13

Flo

w (

cfs

)

0

1

2

3

4

Rain

(in

/hr)

Observed

Modeled

Rain

Pre-rehab

calibration

Post-rehab

validation

Example 2

Findings

• Rehab had a significant

impact on measured flows and

volumes

• Success is easier to measure

when rehabilitation occurs

aggressively over entire

metered district

Example 3

• Aggressive sewer, manhole,

lateral rehab over 3-year period

• $15-$16 million investment

• 2 years of pre-rehab flow meter

data (continuous)

• 12 months of post-rehab flow

meter data

• Post-rehab data is 2012-2013

(historically-dry conditions)

Example 3

Methods of Analysis

• Local analysis

• Model calibration to 2012 storms

(July and August)

• Analysis shows significant

reduction in wet weather flows

• Independent analysis

(Regional Authority)



• Continuous Modeling

Example 3

Baseflow Analysis (>25% reduction)

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

Sep-06 Mar-07 Sep-07 Mar-08 Sep-08 Mar-09 Sep-09 Mar-10 Aug-10 Feb-11 Aug-11 Feb-12 Aug-12 Feb-13 Aug-13

Community Master Meter7-day minimum flows (BASEFLOW)

2006-2013

Pre-Rehab

Post-Rehab

0.300

0.350

0.400

0.450

0.500

0.550

0.600

0.650

0.700

0.750

0.800

Jan-07 Jul-07 Jan-08 Jul-08 Dec-08 Jun-09 Dec-09 Jun-10 Dec-10 Jun-11 Dec-11 Jun-12 Dec-12 Jun-13

Control District (No Rehab)7-day minimum flows (BASEFLOW)

2006-2013

Example 3

Baseflow Analysis (non-rehab district, >20% reduction)

Example 3


100

1000

10000

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

Tota

l RD

II V

olu

me

(th

ou

san

dcu

bic

fe

et)


Community Master MeterTotal RDII Volume vs. Total Event Rainfall

Pre- vs. Post-Rehab (April - October data only)

2006-2009

2011-2012

Example 3


1

10

100

1000

0 1 2 3 4 5 6

Tota

l RD

II V

olu

me

(th

ou

san

dcu

bic

fe

et)


Control District (No Rehab)Total RDII Volume vs. Total Event Rainfall

Pre- vs. Post-Rehab (April - October data only)

2006-2009

2011-2012

Example 3

Continuous Modeling

• 2012 data show a “nudging of

the needle” to reduced peaks

and volumes

• 2013 data (only 3 storms)

show similar response to pre-

rehab conditions

Example 3

Findings

• Early data suggests little to

no flow reduction (peak and

baseflow)

• More data needed to confirm

this hypothesis (meter data

through 2013 would be ideal)

• Success is easier to measure

when rehabilitation occurs

aggressively over entire

metered district

Limits of Source Removal

Chasing I/I is difficult. This is what

we’re learning by observing

numerous City-wide efforts at I/I

reduction:

• Problems migrate to next

downstream defect

• Sanitary sewer acts as an

“unofficial” dewatering pipe for

groundwater in developed

areas

• ENTIRE system (Pipes, MHs

and laterals) needs to be

rehabilitated to have a

measurable impact (VERY

EXPENSIVE)

Wet Weather Alternatives

0.4

$0

$100,000

$200,000

$300,000

$400,000

$500,000

$600,000

$700,000

$800,000

$900,000

$1,000,000

0 0.5 1 1.5 2 2.5

Storage Cost Curve

Inflow Source Removal

Manhole Rehab

Private I/I Sources (FDD)

Notes1. Flow removal based on SSES report estimates2. Assumes a flow removal of 4 gpm per home at $10,000 cost per home

Cost to remove 0.40 cfs of private sources (e.g. FDD) = $897,600Cost to store 0.40 cfs = $122,000

Cumulative Peak Flow Removed (cfs)

Cu

mu

lati

ve C

apit

al E

xpe

nse

(U

SD)

Cost to remove 0.96 cfs of direct inflow sources = $40,000Cost to store 0.96 cfs = $294,000

Cost to remove 0.81 cfs of manhole sources = $365,000Cost to store 0.81 cfs = $250,000

Cost to Construct 10.6 MG to store excess peak flow (43 cfs) = $12.2 M

Economics of System Rehab

Rehabilitation may be sought for the

wrong reasons. It is ultimately

about:

• Structural integrity of pipes and

manholes

• Adding 20+ years to pipe

longevity through lining

• Lower O&M costs through

reduced frequency of

emergency repairs

Literature Review

Reviewed specific programs across the

country

Read technical/academic papers on wet

weather flows in wastewater collection

systems

Municipal Experience

Urbana-Champaign Sanitary District (UCSD), IL

Naperville, IL

Concord, MA

Various municipalities, Oakland County, MI

European Communities

Dresden University Study (2007)

Study of communities in UK, Germany, Switzerland

European Communities

Non-sanitary flows are the norm in separate

wastewater collection systems

(30%-50% of total sewer flows are typical)

Typically, about 5% to 10% of total I/I can be

cost-effectively removed

Aggressive rehabilitation programs have

mixed results. Often, only complete rehab

programs can “nudge the needle”

Key Takeaways

Many communities have invested in significant

rehabilitation programs with little to no

measureable peak or volume reduction

Flow meter data is often the weakest link –

flow metering should be extended well beyond

rehab period for statistically-meaningful data

The key benefit of sewer rehabilitation may be

structural (extending the life of the asset)

Financial-Driven Decisions

• What is the economic impact of reduced

baseflows or peaks? Present value?

• What is the most economically-efficient way

to reduce I/I?

• Is a regional solution possible (i.e. storage

or conveyance)?

• Local rate payers ultimately will expect the

most cost-effective solution

Recommended Steps

• Know the goals - set appropriate hurdles

• Establish a reliable and long-term metering

program (extend beyond rehab period)

• Fully vet the wet weather control options at

your disposal

• Don’t overpromise

• Asset Management Plans – great opportunity

to put these steps to the test

OHM-ADVISORS.COM

Questions

Contact info:

Gregory P. Kacvinsky, P.E.

OHM Advisors

[email protected]

ARCHITECTS. ENGINEERS. PLANNERS.

Wastewater Collection System Rehab

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