appendix 9a screening alternatives · 9a-5 summary of alternative 1 elements and approximate costs...

2020 Facilities Plan Facilities Plan Report

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Appendix 9A

Screening Alternatives


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Table of Contents APPENDIX 9A: SCREENING ALTERNATIVES ............................................................ 9A-1 9A.1 Overview....................................................................................................................... 9A-1

9A.2 Screening Alternatives 1A, 1B, 1C, 1D – Elimination of Sewer Overflows................ 9A-1

9A.2.1 Review of State of the Art Report................................................................................. 9A-2

9A.2.2 Technology Assumptions.............................................................................................. 9A-3

9A.2.3 Models........................................................................................................................... 9A-7

9A.2.4 Alternative Analysis.................................................................................................... 9A-10

9A.3 Screening Alternative 2 – Watershed Best Management Practices ............................ 9A-25

9A.3.1 State of the Art Report ................................................................................................ 9A-25

9A.3.2 Technology Assumptions............................................................................................ 9A-27

9A.3.3 Models......................................................................................................................... 9A-31

9A.3.4 Alternative Analysis.................................................................................................... 9A-32

9A.4 Sources of Pollutant Loadings .................................................................................... 9A-34

9A.5 Resulting Modeled Water Quality from Screening Alternatives................................ 9A-43

9A.5.1 Kinnickinnic River...................................................................................................... 9A-43

9A.5.2 Menomonee River....................................................................................................... 9A-46

9A.5.3 Milwaukee River......................................................................................................... 9A-48

9A.5.4 Oak Creek ................................................................................................................... 9A-50

9A.5.5 Root River................................................................................................................... 9A-53

9A.5.6 Lake Michigan Direct Drainage.................................................................................. 9A-55

9A.5.7 Screening Alternatives Water Quality Summary........................................................ 9A-60

9A.6 Evaluation Matrix Analysis ........................................................................................ 9A-60

9A.6.1 Explanation of Absolute Scoring ................................................................................ 9A-61

9A.6.2 Subjective Goals ......................................................................................................... 9A-64

9A.6.3 Total Scores ................................................................................................................ 9A-65

9A.6.4 Relative Water Quality Scoring .................................................................................. 9A-67

Appendix 9A

Figures

9A-1 SSO Volume Cost Benefit Curves................................................................................ 9A-4

9A-2 CSO Volume Cost Benefit Curves ............................................................................... 9A-5


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9A-3 Screening Alternative 1C: Technology Combinations to End SSOs............................ 9A-8

9A-4 Screening Alternative 1C: End SSOs ......................................................................... 9A-13

9A-5 Screening Alternative 1B: End SSOs and CSOs and Screening Alternative 1C: End SSOs .................................................................................................................... 9A-15

9A-6 Combined Sewer Service Area to be Separated ......................................................... 9A-17

9A-7 Typical Current I/I Rates in the Separate Sewer Service Area................................... 9A-19

9A-8 Captured Runoff Volume and Rainfall Depth ............................................................ 9A-21

Chapter 9

Tables

9A-1 Screening Alternative Comparisons ............................................................................. 9A-6

9A-2 Facility Combinations for Screening Alternative 1c: Technology Combinations to End SSOs ...................................................................................................................... 9A-7

9A-3 Simulated Peak MIS Conveyance Capacity to South Shore Wastewater Treatment Plant........................................................................................................... 9A-10

9A-4 Facility Combinations for Screening Alternative 1B.................................................. 9A-14

9A-5 Summary of Alternative 1 Elements and Approximate Costs in Millions ................. 9A-24

9A-6 Screening Alternative 2 Infiltration Implementation by Land Use Assumptions....... 9A-30

9A-7 Summary of Screening Alternative 2 Elements and Approximate Costs in Millions 9A-35

9A-8 Primary Sources of Pollutants to Local Waterways ................................................... 9A-36

9A-9 Loads of Total Phosphorus to Greater Milwaukee Watersheds.................................. 9A-37

9A-10 Loads of Total Suspended Solids to Greater Milwaukee Watersheds........................ 9A-38

9A-11 Loads of Fecal Coliform Bacteria to Greater Milwaukee Watersheds ....................... 9A-39

9A-12 Loads of Total Nitrogen to Greater Milwaukee Watersheds ...................................... 9A-40

9A-13 Loads of Biochemical Oxygen Demand to Greater Milwaukee Watersheds ............. 9A-41

9A-14 Loads of Total Copper to Greater Milwaukee Watersheds ........................................ 9A-42

9A-15 Effect of Screening Alternatives in the Lake Michigan Outer Harbor and Beaches in Days of Compliance with the Not to Exceed 400 Counts/100ml Standard during the Swimming Season................................................................................................. 9A-57

9A-16 Effect of Screening Alternatives in the Lake Michigan Outer Harbor & Beaches in Days of Compliance with the Not to Exceed 400 Counts/100ml Standard During for the Entire Year ...................................................................................................... 9A-57

9A-17 Evaluation Matrix Scoring System of Days Meeting Standard or Guideline............. 9A-62

9A-18 Evaluation Matrix Scoring System for Total Nitrogen and Total Phosphorus Loads 9A-62


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9A-19 Subjective Scoring Categories .................................................................................... 9A-63

9A-20 Raw Watershed Scores – Study Area-Wide Score ..................................................... 9A-64

9A-21 Sums Of Watershed Scores -- Study Area Wide Score, Normalized to 10-Point Scale ............................................................................................................. 9A-64

9A-22 Scoring of Subjective Goals........................................................................................ 9A-65

9A-23 Water Quality and Subjective Scoring Combined ...................................................... 9A-66

9A-24 Study Area-Wide Score, Normalized to 10-Point Scale Quartiles Method Scores Based On River, Estuary, and Beach Locations.............................................. 9A-68

9A-25 Summary by Watersheds across all Parameters.......................................................... 9A-69


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Appendix 9A: Screening Alternatives

9A.1 Overview The water quality benefits that could be achieved by controlling combined sewer overflows (CSOs), sanitary sewer overflows (SSOs), and/or nonpoint pollution were evaluated using “Screening Alternatives.” These Screening Alternatives model various options for the Milwaukee Metropolitan Sewerage District (MMSD) 2020 Facilities Plan (2020 FP) and the Southeastern Wisconsin Regional Planning Commission (SEWRPC) Regional Water Quality Management Plan Update (RWQMPU). The approach evaluated in the first set of Screening Alternatives (1A-1D) was upgrading the MMSD treatment and conveyance system and possibly separating the sewers in the combined sewer service area (CSSA) to eliminate overflows. The remaining Screening Alternative (alternative 2) evaluated the potential benefits from wide-spread implementation of stormwater best management practices or “BMPs.” The Screening Alternative simulations were based on the 2020 Baseline conditions described as Alternative A in Section 9.4 of Chapter 9. Therefore, in addition to the other elements of the 2020 Baseline condition, the simulations used sewershed flows based on the 2020 Baseline population and land use.

The purpose of the Screening Alternatives was twofold. First, the Screening Alternatives were planned to be “bookends” or extremes in terms of approaches to water quality improvement. Screening Alternatives 1A to 1D were focused on point source overflow elimination, while Screening Alternative 2 was focused on the opposite extreme – implementation of large scale nonpoint pollution control practices or stormwater best management practices. Second, the set of Screening Alternatives responded to citizen and media concerns such as:

♦ Why not end all the overflows? (Screening Alternatives 1B-1C)

♦ Why not separate the combined sewers? (Screening Alternative 1A)

♦ Why not eliminate all the Infiltration/Inflows (I/I) and fix the leaky sewers? (Screening Alternative 1D)

♦ Why not implement a large scale BMP program? (Screening Alternative 2)

The costs presented in this appendix are intended to be used to make relative comparisons of the alternatives. The cost estimates are based on the cost functions in use while this analysis was developed. Many of these cost functions have been further refined in subsequent analyses. The Screening Alternatives are useful to estimate the approximate cost of these extreme solutions so that the various alternatives can be compared. The relative costs are important to the conclusions of this analysis. Each individual cost number is only an approximate value. Refined cost estimates are presented for the Recommended Plan in Section 9.6 of Chapter 9, Alternative Analysis.

9A.2 Screening Alternatives 1A, 1B, 1C and 1D - Elimination of Sewer Overflows The first set of Screening Alternatives is used to evaluate the water quality improvements that could be obtained from projects to eliminate SSOs and CSOs. The Screening Alternatives


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comprise four different combinations of technologies (combined sewer separation, treatment, storage, and I/I reduction) that successfully eliminate overflows for the period from January 1940 through June 2004 (the “64.5-year period of record”). Each combination of technologies defines the capacities of an ideal sewer system that can fully contain the wastewater flow, even for extreme events.

Screening Alternatives 1A and 1B are constructed to fully eliminate both SSOs and CSOs during the period of record. Screening Alternatives 1C and 1D eliminate SSOs but not CSOs (note that there is some ancillary reduction in CSOs for 1C and 1D). In all four Screening Alternatives, there is no consideration given for level of service (such as a 5- or 10-year recurrence interval).a Instead, these alternatives eliminate overflows for the most extreme conditions that were recorded in the period of record. These simulations are built on the 2020 Baseline and use sewershed flows based on 2020 Baseline population and land use. The 2020 Baseline also includes other “committed projects” as defined in Chapter 8.

9A.2.1 Review of State of the Art Report The results of the State of the Art Report (SOAR) were used to select the most cost effective technologies (see the report for the details on how cost effectiveness was determined). Various combinations of technologies were then analyzed in detail with the Streamline-MOUSE modelb to define the capacities needed to achieve the goals of the Screening Alternatives. The cost of each combination of technologies was computed from the cost functions in the SOAR.

Treatment at South Shore Wastewater Treatment Plant Treatment using full secondary treatment by physical-chemical innovative methods with ultraviolet (UV) disinfection at South Shore Wastewater Treatment Plant (SSWWTP) is the most cost effective technology for reducing SSOs. The slope of the cost benefit curve shows that adding up to an additional 185 million gallons per day (MGD) is more cost effective than other technologies because the conveyance capacity of the metropolitan interceptor sewer (MIS) to SSWWTP is approximately 485 MGD. (The existing treatment capacity is 300 MGD; therefore, an additional 185 MGD is equal to a total plant capacity of 485 MGD.) The options for treatment at SSWWTP include physical-chemical using new technologies. The MMSD has pilot tested this technology as documented in the MMSD High Rate Treatment (HRT) Report.(1) Another option is full secondary treatment, but this is a much higher cost with minimal additional water quality benefits. The increased capacity assumes full secondary treatment by physical-chemical (ballasted flocculation) with either chlorine or UV disinfection.

Inline Storage System Pumping to Jones Island Wastewater Treatment Plant Increased pumping from the inline storage system (ISS) to the Jones Island Wastewater Treatment Plant (JIWWTP) is the next most cost effective technology for reducing SSOs. In the SOAR, the cost benefit curve for increasing pumping capacity from the ISS pump station to JIWWTP was evaluated up to 200 MGD as a stand alone technology, limited by the current JIWWTP capacity, which remained unchanged for this technology.

a The recurrence interval is the inverse of the probability that the event will occur each year (e.g. a 5-year recurrence interval has a 20% probability of occurring each year, or 1/5). b See description in Chapter 3 of Conveyance Report.


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Treatment and Pumping at Jones Island Wastewater Treatment Plant Increasing the JIWWTP capacity assumes full secondary treatment by physical-chemical (ballasted flocculation) with either chlorine or UV disinfection. This technology also assumes that the pumping capacity from the ISS to JIWWTP would be increased along with the treatment capacity. Additional treatment at JIWWTP is more expensive than at SSWWTP because of the cost of additional pumping to JIWWTP from the ISS pump station, the need to construct facilities on pile foundations, and the higher cost of land.

Additional Inline Storage System Storage For CSO control, the most cost effective technology is additional storage using either additional ISS deep tunnel or near surface storage. These are the only means of fully eliminating CSOs. Deep tunnel storage has a lower cost than covered near surface storage; therefore, only deep tunnel storage was used in the Screening Alternatives. For SSO control, the following cost technologies were more cost effective than additional ISS storage: SSWWTP treatment, JIWWTP additional ISS pumping, or JIWWTP pumping and treatment.

All of the other technologies considered in the SOAR were either more expensive or were severely limited in the degree to which they could help achieve the goal of full elimination of CSOs and SSOs. Therefore, the technologies used to define the alternative combinations for 1A (alternative technology combinations after sewer separation was considered), 1B and 1C were SSWWTP treatment, JIWWTP treatment and pumping, and ISS storage.

Infiltration and Inflow Reduction Screening Alternative 1D uses the I/I reduction technology as the only technology to eliminate SSOs. To achieve zero SSOs over the period of record, I/I reduction efforts would need to reduce I/I in all sewersheds (sewershed description and development is in Chapter 3 of the Conveyance Report) to a rate less than 2,000 gallons per acre per day (gpad) for the 5-year peak hour flow. Achieving such an aggressive goal would require continuing I/I reduction in virtually all sewersheds in the separate sewer service area (SSSA).

The cost benefit curves for the various SOAR technologies are shown in Figures 9A-1 and 9A-2 for the percent of SSO volume removed and the percent of CSO volume removed.

9A.2.2 Technology Assumptions Various combinations of technologies can be used to achieve the same outcome. In the level of analysis appropriate for facility planning, it is reasonable to show system level combinations of technologies. Additional preliminary and final design engineering would be required to develop the exact combination of technologies to achieve the desired results. This analysis develops planning-level costs for successful combinations of technologies that achieve the goals of each Screening Alternative.

♦ Screening Alternative 1A assumes elimination of SSOs and CSOs through sewer separation of the combined sewer service area to the maximum extent practicable and the implementation of other technologies as needed.

♦ Screening Alternative 1B eliminates both SSOs and CSOs using combinations of treatment and storage without combined sewer separation.

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FIGURE 9A-1

SSO VOLUME COSTBENEFIT CURVES2020 FACILITIES PLAN

FP_9A.0001.07.06.01.cdr6/1/07

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Phys-Chem = Physical-Chemical Treatment

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CSSA = Combined Sewer Service Area

UV = Ultraviolet

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MIS = Metropolitan Interceptor Sewer

I/I = Infiltration and Inflow

FIGURE 9A-2

CSO VOLUMECOST BENEFIT CURVES2020 FACILITIES PLAN

FP_9A.0002.07.06.01.cdr6/1/07


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♦ Screening Alternative 1C uses treatment and storage to eliminate SSOs, but not necessarily CSOs.

♦ Screening Alternative 1D eliminates SSOs by reducing I/I.

The assumptions for each alternative are listed in Table 9A-1.

TABLE 9A-1

SCREENING ALTERNATIVE COMPARISONS

Overflows Eliminated Technology Screening Alternative SSO CSO

Treatment and Storage

Sewer Separation Reduced I/I

1A X X X X

1B X X X

1C X X

1D X X

CSO = Combined Sewer Overflow I/I = Infiltration and Inflow SSO = Sanitary Sewer Overflow

The primary technological variables in this analysis are the treatment capacities of SSWWTP and JIWWTP, the storage volume of the ISS, and the ISS pumping capacities to each treatment plant. Other technologies described in the SOAR, such as near surface storage, MIS in-system storage, roof top storage, and satellite treatment, were not evaluated in these Screening Alternatives because of high cost or limited benefits.

To determine what would be required to eliminate CSOs and/or SSOs, four progressive analytical exercises were conducted. The process is discussed in Chapter 8, Combinations of Technologies of the SOAR and is summarized below:

1) First – the SOAR production theory analysis for CSO and SSO reduction was used to determine which technologies were most cost effective to reduce CSO and SSO. This resulted in the selection of SSWWTP physical-chemical treatment, ISS pumping to JIWWTP, JIWWTP physical-chemical treatment, and tunnel storage. This analysis evaluated the cost benefit relationship of each technology applied independently.

2) Second – the goals of the Screening Alternatives were studied to determine which facilities were required to end all SSOs and CSOs. Combinations of technologies were used to achieve the objective for the largest events in the period of record.


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3) Third – the elimination of SSOs by only addressing I/I reduction was evaluated using MACRO model runs.c

4) Fourth – the recommended combinations for all four Screening Alternatives were checked with MOUSE model runs to determine if the selected technology set met the selected performance criteria under detailed wet weather event conditions.

9A.2.3 Models Several combinations of technologies were compared for each alternative goal. The performance of each combination was analyzed with the MACRO and Streamline-MOUSE models in order to determine the best combination(s) of technologies. The MACRO model results were used to roughly define the relative benefits of treatment, storage, and pumping over the period of record. To refine the analysis, the Streamline-MOUSE model was used because this model simulates the routing in the MIS and the process interactions that are sensitive to the timing of the event. The March 1960 event was identified as the worst SSO event and was used to define the system requirements to eliminate SSOs. The August 1986 event was identified as the worst CSO event and was used to define the maximum CSO conditions.

Figure 9A-3 shows several combinations of technologies that successfully end SSOs for the March 1960 event. In most combinations, the additional treatment capacity at SSWWTP is assumed to be 185 MGD and the trade off is between additional treatment at JIWWTP and additional storage volume. After roughly defining these combinations using the MACRO model, simulations were run in MOUSE to refine the facility sizes, which are presented in Table 9A-2 and Figure 9A-3.

TABLE 9A-2

FACILITY COMBINATIONS FOR SCREENING ALTERNATIVE 1C: TECHNOLOGY COMBINATIONS TO END SSOs

JIWWTP Physical-chemical

SSWWTP Physical-chemical

Additional Pumping to

JIWWTP Additional

ISS Volume VRSSI (MGD) (MGD) (MGD) (MG) (MG)

0 185 246 229 406

50 185 170 162 339

100 185 100 153 330

360 185 604 0 177

ISS = Inline Storage System JIWWTP = Jones Island Wastewater Treatment Plant MG / MGD = Million Gallons / Million Gallons per Day SSOs = Sanitary Sewer Overflows SSWWTP = South Shore Wastewater Treatment Plant VRSSI = Volume Reserved for Separate Sewer Inflow

Nominal facility capacities used in this analysis: SSWWTP Capacity = 300 MGD peak day ISS pumping to SSWWTP = 40 MGD peak day JIWWTP = 330 MGD peak day plus 60 MGD blending for total of 390 MGD peak day ISS pumping to JIWWTP = 80 MGD peak day ISS volume = 432 MG

c Described in Chapter 3 of the Conveyance Report.

FIGURE 9A-3

SCREENING ALTERNATIVE 1C:TECHNOLOGY COMBINATIONSTO END SSOs2020 FACILITIES PLAN

FP_9A.0003.07.06.01.cdr6/1/07

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MACRO Model: Initial Screening and Sensitivity Analysis The MACRO model is a simple volumetric model of the MMSD system that accounts for treatment at the wastewater treatment plants, storage in the ISS, and overflows (both CSOs and SSOs). The model quickly simulates the 64.5-year period of record and tests the sensitivity of the overall system response to changes in the key parameters of treatment capacities, ISS volume, pumping capacities, and operational conditions (such as the ISS volume reserved for separate sewer inflow (VRSSI)).

The MACRO model is a screening tool; it was used in the SOAR analysis to develop the production functions and test the relative sensitivity of the overall system response to various technologies. MACRO is not a detailed design tool. Therefore, the MACRO results were used as preliminary indicators of the performance and benefits of the various technologies. The MACRO model runs indicated that substantial reductions in SSO volume could be achieved by providing additional treatment capacity at SSWWTP; this is also the most cost effective technology. An equal amount of additional treatment capacity at JIWWTP provides similar reductions in SSOs, but the cost is higher due to the additional pumping and the higher cost of land. Sanitary sewer overflows can also be efficiently removed by additional storage volume in the ISS, but the cost is higher than additional treatment capacity at either plant (see Figures 9A-1 and 9A-2 for the comparison of relative costs).

To eliminate CSOs, additional storage volume in the ISS is one of the two most efficient and cost effective technologies (see Figure 9A-2). This is because of the intense flow rates from the combined sewer service area. The ISS can accommodate high flow rates of short duration, far in excess of any reasonable treatment capacity. Additional treatment plant capacity, however, is complementary to the additional storage. For events that are closely spaced, additional treatment plant capacity (along with pumping capacity) helps to dewater the ISS quickly, making more storage volume available for closely spaced events

Approximately 1,600 MG of additional storage (in addition to the 400 MG that already exists in the ISS) would be required to contain the largest CSO event experienced during the 64.5-year period of record. The cost for the additional volume required for full elimination of CSOs is very high (approximately $4.0 billion for 1,600 MG of storage).

The MACRO model continuously simulates the full period of record; therefore, the results reflect the benefits achieved over a wide range of hydrologic conditions. MACRO, however, lacks the ability to route the flows through the MIS. This is a particular problem when the treatment capacity at SSWWTP is increased. When the model does not limit the peak flow rate to SSWWTP to 300 MGD (that is, when the flow is only limited by the conveyance capacity of the MIS) the MACRO model results are not reliable and the Streamline-MOUSE model must be used to refine the analysis.

Streamline-MOUSE: MIS Capacity to South Shore Wastewater Treatment Plant The Streamline-MOUSE model is a more detailed model than MACRO; it simulates the dynamics of hydraulic routing in the conveyance system and the time sensitive nature of pumping from the ISS.

Most of the Streamline-MOUSE simulations assumed that the treatment capacity of SSWWTP was adequate to process all the flow that can reach the plant by gravity in the MIS. The


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calculated MIS conveyance capacity is approximately 485 MGD; however, the peak gravity flow to SSWWTP varied for different storms. The maximum simulated flow was 507 MGD for the August 1986 event. For the March 1960 event, the peak flow was 486 MGD. The peak flows for the five largest events simulated with Streamline-MOUSE are listed in Table 9A-3. The model configuration for these Screening Alternatives does not limit the flow to SSWWTP (as is the case in the 2020 Baseline model simulation, which limited the flow to a maximum of 300 MGD).

TABLE 9A-3 SIMULATED PEAK MIS CONVEYANCE CAPACITY TO SOUTH SHORE WASTEWATER TREATMENT PLANT

Event Peak Flow at SSWWTP

(MGD)

March 1960 486

August 1986 507

May 1990 464

June 1997 480

July 2000 443

MGD = Million Gallons per Day SSWWTP = South Shore Wastewater Treatment Plant Note: These simulated peak flows were based on the hydrologic conditions at General Mitchell International Airport for each event listed. The model was configured for the 2020 Baseline “committed” conditions with various combinations of technologies to achieve the goals of the Screening Alternatives. These are not measured flows at SSWWTP and do not apply to current operational conditions. They are modeled estimates of the conveyance capacity of the MIS leading to SSWWTP if the flow at the plant was not limited to 300 MGD. Source: Streamline-MOUSE simulations

9A.2.4 Alternative Analysis It is critical to note that the full elimination of SSOs or CSOs in this analysis only applies to the 64.5-year period of record. It is possible to experience conditions more extreme than those contained in the period of record; therefore, it is not possible to conclude that a combination of technologies can fully eliminate overflows (CSO and/or SSO) for all future conditions. An additional consideration to note is that extreme events are rare; therefore, a technology that provides full elimination of overflows will rarely be used to its full capacity. The cost to eliminate the largest event in the period of record is typically very high.

The analysis of the Screening Alternatives started with Screening Alternative 1C (SSO control) and progressed to Screening Alternative 1B (CSO and SSO control). Then, Screening Alternative 1A (combined sewer separation) was analyzed; the results are presented in that order.


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Screening Alternative 1D (I/I reduction) is fully discussed in the SOAR; that discussion is summarized in this report.

Results: Screening Alternative 1C - Elimination of SSOs The goal of Screening Alternative 1C is to eliminate SSOs. The March 1960 event produced the largest simulated SSO during the period of record, so simulations of the March 1960 event were used to find the combinations of technologies capable of preventing SSOs. Various combinations of treatment and storage were tested in the MACRO program to determine which ones eliminated SSOs and to estimate the long-term benefit and cost of each. Subsequent simulations using the Streamline-MOUSE model refined the capacities and volume needed to achieve the goals of this alternative. Several combinations were simulated in Streamline-MOUSE and the results are compared by cost.

Even though the goal of Screening Alternative 1C is to eliminate SSOs, there are also incidental benefits of CSO reduction. However, the reductions in CSOs are generally not significant. In Screening Alternative 1B, additional technologies are employed to reduce CSOs.

The advantageous cost benefit curve for treatment at SSWWTP guided the choice of the Screening Alternative 1C technologies. Additional treatment capacity of 185 MGD was added at SSWWTP to take advantage of the full conveyance capacity of the MIS, which is approximately 485 MGD. Expanding SSWWTP capacity beyond 485 MGD would require a force main to pump the additional flow from the ISS, thereby greatly increasing the cost. Therefore, the maximum treatment capacity at SSWWTP was increased from 300 to 485 MGD for almost all of the remaining alternative combinations.

The next technology reviewed and analyzed was additional treatment at JIWWTP. The cost of additional treatment at JIWWTP is higher than at SSWWTP because of the cost of pumping and the higher cost of land.

The Streamline-MOUSE results indicated that increased ISS volume is also required to achieve full elimination of SSOs. Simulation results were used to determine the volume of ISS storage needed to fully eliminate SSOs. These simulations varied the VRSSI for each combination of technologies but kept constant the ISS volume available for combined sewer inflow. The ISS volume minus the VRSSI was equal to 255 MG in each case; this is the volume available to store inflow during the early part of an event before the combined sewer gates close. These early inflows to the ISS are predominantly from the combined sewer service area.

Costs

The cost for Screening Alternative 1C, as with all of the Screening Alternatives, includes the cost of upgrades to the conveyance system to prevent SSOs caused by hydraulic restrictions in the MIS. Forty-two sites were identified throughout the MIS that may require parallel relief sewers to avoid SSOs due to hydraulic restrictions during extreme conditions. The cost of these upgrades is $337 million.d Even though the SSO volume due to hydraulic restrictions in the MIS is small, these upgrades would be necessary to achieve the goal of eliminating all SSOs for the most extreme events. This cost is common to all Screening Alternatives.

d All costs are escalated using the Engineering News Record Construction Cost Index (ENR-CCI), which was projected to be 10,000 in 2007.


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Figure 9A-4 shows the cost of Screening Alternative 1C combinations that achieve the goal of full SSO elimination. Table 9A-2 summarizes the combinations of technologies that achieve the alternative 1C goals. The combination with the lowest cost used 100 MGD of additional treatment and pumping at JIWWTP along with 185 MGD of additional treatment at SSWWTP and 153 MG of additional ISS storage. The total present worth cost of this combination is approximately $1,200 million.

Overall, the cost benefit curve is relatively flat. This means that the cost benefit balance between treatment at JIWWTP and ISS storage is not particularly sensitive. If no additional treatment is provided at JIWWTP, then 229 MG of additional ISS volume are required. If no additional ISS storage is provided, then 360 MGD of additional treatment capacity is needed at JIWWTP.

Incidental CSO Reduction

Some technology combinations that meet the goal of Screening Alternative 1C also have an incidental benefit for reducing CSO volume however, the benefit is not equal for all events. For some events, the CSO is unchanged from the 2020 Baseline case. Three events were simulated to test the incidental benefit for CSOs: March 1960, May 1990, and June 1997.

The first two events (March 1960 and May 1990) were snow melt events with long durations. The additional treatment during these long events reduces the CSO volume. The simulated March 1960 results show a 38% reduction of CSO volume. For May 1990, 28% of the CSO volume was removed.

In contrast, the June 1997 event was an intense thunderstorm with much more concentrated flows. Consequently, the availability of additional treatment does not make a difference in this event; the CSO volume is unchanged by the Screening Alternative 1C configuration. For this type of intense event, additional storage volume is the only means of removing CSOs. The additional storage volume in the Screening Alternative 1C combinations was dedicated for SSOs. The VRSSI was adjusted in each case to limit the volume available for combined sewer inflow to 255 MG; no additional storage was provided for CSOs.

The CSO hydrographs for water quality modeling were created by the Mini-MOUSE model for the 15 year period of 1988-2002 for the 2020 Baseline “committed” conditions. For water quality modeling of Screening Alternative 1C, the CSOs are essentially the same as the 2020 Baseline “committed” CSOs. Screening Alternative 1C has little impact on the overflows from the combined sewer service area.

Summary

The goal of Screening Alternative 1C can be achieved using a combination of treatment and storage. The most cost effective combination assumes 185 MGD of additional treatment at SSWWTP, 100 MGD of additional treatment at JIWWTP, 100 MGD of additional pumping from the ISS to JIWWTP, and 153 MG of additional ISS storage. The approximate cost of Screening Alternative 1C is $1,200 million.

FIGURE 9A-4

SCREENING ALTERNATIVE 1C:END SSOs2020 FACILITIES PLAN

FP_9A.0004.07.06.01.cdr6/1/07

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

2,200

0 50 100 150 200 250 300 350 400


To

talC

os

t($

/mil

lio

ns

)

Screening Alternative 1C: End SSOs

Note: See Table 9A-4 for details


9A-14

Results: Alternative 1B - Elimination of SSOs and CSOs The goal of Screening Alternative 1B is to eliminate both SSOs and CSOs. Both the SSOs and the CSOs are eliminated in the Screening Alternative 1B simulations using combinations of treatment, storage, and pumping. Screening Alternative 1B simulations used additional storage capacity in the ISS to eliminate CSOs after the SSOs were successfully eliminated by the technologies in Screening Alternative 1C.

Screening Alternative 1C was used as the starting point for the Screening Alternative 1B simulation because the SSOs must be eliminated before the CSOs can be addressed. The most cost effective technology for CSO control is ISS storage. Additional treatment at JIWWTP is also effective in partially reducing CSOs, but treatment at SSWWTP is not effective.

Costs

Table 9A-4 lists the various technology combinations that satisfy Screening Alternative 1B goals. Figure 9A-5 shows the cost for those various technology combinations. All of the cases assume that the treatment capacity at SSWWTP is equal to the conveyance capacity of the MIS (485 MGD). As in Screening Alternative 1C, the nominal capacity at SSWWTP is 485 MGD; however, the hydrograph briefly peaks to 507 MGD during the August 1986 event.

TABLE 9A-4

FACILITY COMBINATIONS FOR SCREENING ALTERNATIVE 1B

JIWWTP Physical-chemical

SSWWTP Physical-chemical

Additional Pumping to

JIWWTP Additional

ISS Volume VRSSI (MGD) (MGD) (MGD) (MG) (MG)

Screening Alternative 1B Facilities to End SSOs and CSOs:

0 207 260 1,671 406

50 207 310 1,634 339

100 185 100 1,622 330

360 207 620 1,451 177

CSOs = Combined Sewer Overflows ISS = Inline Storage System JIWWTP = Jones Island Wastewater Treatment Plant MG / MGD = Million Gallons / Million Gallons per Day SSOs = Sanitary Sewer Overflows SSWWTP = South Shore Wastewater Treatment Plant VRSSI = Volume Reserved for Separate Sewer Inflow

Nominal facility capacities used in this analysis: SSWWTP Capacity = 300 MGD peak day ISS pumping to SSWWTP = 40 MGD peak day JIWWTP = 330 MGD peak day plus 60 MGD blending for total of 390 MGD peak day ISS pumping to JIWWTP = 80 MGD peak day ISS volume = 432 MG

FIGURE 9A-5

SCREENING ALTERNATIVES 1B: END SSOs AND CSOsSCREENING ALTERNATIVES 1C: END SSOs2020 FACILITIES PLAN

FP_9A.0005.07.06.01.cdr6/1/07

0

400

800

1,200

1,600

2,000

2,400

2,800

3,200

3,600

4,000

4,400

4,800

5,200

0 50 100 150 200 250 300 350 400


To

talC

os

t($

/mil

lio

ns

)

Screening Alternative 1B: End SSOs and CSOs

Screening Alternative 1C: End SSOs

Note: See Table 9A-4 for details


9A-16

The additional ISS storage ranges from 1,451 to 1,671 MG depending on the additional treatment capacity at JIWWTP. The most cost effective configuration is 100 MGD of additional capacity at JIWWTP and 1,622 MG of additional storage. The cost for Screening Alternative 1B doesn’t vary much for all combinations, ranging from $4,700 to $5,000 million. The figure also shows the cost for Screening Alternative 1C, which is approximately $1,200 to $1,400 million. Thus, full elimination of both CSOs and SSOs in Screening Alternative 1B is approximately four times the cost of eliminating the SSOs in Screening Alternative 1C.

Results: Screening Alternative 1A - Combined Sewer Separation Screening Alternative 1A assumes that the combined sewer service area (CSSA) has been separated to the maximum feasible extent. This involves the conversion of 89% of the CSSA into a separate sewer service area that has separate collection systems for the sanitary sewer and the stormwater drainage. The remaining 11% of the area would be unchanged. This 11% of the CSSA is the downtown business district which was considered impractical to separate in this analysis. The model for this alternative assumes that first flush stormwater from the newly separated areas would be collected by the ISS along with any excess combined sewage from the remaining CSSA. After the ISS closes to the stormwater inflows, the excess stormwater would overflow to the waterways. In this alternative, the ISS would have sufficient volume to store all of the excess flow from the remaining CSSA that would currently become CSOs. The ISS would also have enough volume to store excess flow from the separate sewer service area to prevent SSOs.

Sewersheds to be Separated

The combined sewer service area was subdivided into 160 sewersheds for the 2020 Baseline “committed” conditions. The plan for maximum feasible separation identifies 105 sewersheds to be separated, leaving 55 sewersheds that remain combined. The 105 separated sewersheds cover approximately 13,900 acres (which is 89% of the original CSSA). Figure 9A-6 highlights the sewersheds identified for separation. The central portion of the combined sewer would remain combined while the outer ring of sewersheds would be separated.

Modeling Flow in the Newly Separated Sewersheds

The Flow Forecasting System (FFS) model generated the sewershed hydrographs for use in the Streamline-MOUSE model. For each sewershed that would be separated, the FFS model was modified to create two hydrographs. One hydrograph contains the base sanitary flow and the I/I components in the newly separated sewers. The other hydrograph contains the stormwater flow. Thus, 105 new stormwater hydrographs and 105 new separated sewer hydrographs were created to model Screening Alternative 1A in place of the original 105 combined sewer hydrographs.

The Streamline-MOUSE model was modified to represent the newly separated sewersheds by removing the combined sewer hydrograph and including the two new separated sewer hydrographs. In the original model, the combined sewer flows entered the model at load points and flowed to the ISS; some flow entered the MIS and the excess flow entered the near surface collector system to be stored in the ISS. After the ISS gates closed to combined sewer area flow, the excess flow discharged from the model as CSOs.

6/1/07

FIGURE 9A-6

COMBINED SEWER AREA TOBE SEPARATED (SCREENINGALTERNATIVE 1A)2020 FACILITIES PLAN

FP_9A.0006.07.06.01.cdr


9A-18

In the Screening Alternative 1A model, the links connecting the intercepting structures (IS) and the MIS were removed. The newly separated sewer hydrographs were loaded into the model at the location(s) where they entered the MIS directly. The new stormwater hydrographs were loaded into the model at the original locations, but the IS were closed so that the stormwater flow could not enter the MIS. The stormwater flows entered the near surface collectors and flowed to the ISS or to overflow sites.

The stormwater hydrographs contain flow generated by the surface runoff from the impervious and pervious areas. There is no dry weather infiltration included in the stormwater hydrographs in the model. In reality, the stormwater collection pipes (the existing combined sewer pipes) would have infiltration from groundwater sources. Dry weather flow in the stormwater collection system would be captured by the ISS and would not discharge as stormwater into waterways. During wet weather, the infiltration component is a very small fraction of the total flow in the stormwater system and may be neglected.

The newly separated sanitary sewer hydrographs include infiltration and inflow components. To compute the I/I components, the I/I parameters must be suitable for a newly separated system comprised of a new sanitary collection system and existing laterals (and potentially, foundation drains) on private property. Consequently, the private property sources of I/I would be essentially unchanged after separation; only the I/I into the old public combined sewer lines would be changed. There is little guidance on what the I/I characteristics of the newly separated sewers may be. It is assumed the separated system would have relatively high I/I peak hourly flows in terms of gpad.

To establish reasonable I/I characteristics for the newly separated area, the I/I characteristics of neighboring sewersheds of the same age in the existing separated area were used as a guide. A group of 137 existing sewersheds in the separate sewer service area was identified that have at least 50% of the homes built before 1954 (that is, before building codes prohibited the connection of foundation drains to the sewer collection system). This group of sewersheds has a wide range of I/I rates; most sewersheds are in the range of 4,000 to 20,000 gpad. The area weighted average is approximately 11,500 gpad.

For comparison, all of the sewersheds in the existing separate sewer service area were also used as a guide; the distribution of I/I rates is shown in Figure 9A-7. In the entire separate sewer service area, the I/I rates typically range from 600 to 10,000 gpad. The weighted average for the separate sewer service area is approximately 4,500 gpad.

The leakage parameters set in the model were selected to control the I/I for the newly separated areas so that they were leakier than most sewersheds in the current separate sewer service area, but not as leaky as the separate sewersheds with over 50% of the homes built before 1954. The characteristic I/I rate was approximately 5,600 gpad. It is assumed that the private property sources of I/I would remain after separation, but the public sources of I/I would be reduced.

FIGURE 9A-7

TYPICAL CURRENT I/I RATES INTHE SEPARATE SEWER AREA2020 FACILITIES PLAN

FP_9A.0007.07.06.01.cdr6/1/07

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000 11,000 12,000 13,000 14,000 15,000

Peak Hourly I/I per unit area (gpad)

Perc

en

to

fA

rea

wit

hI/Ile

ss

than

sp

ecif

ied

valu

e.

Area

Weighted

Average

4,500 gpad

Area Weighted

Average

11,500 gpad

Most

Sewersheds

Subset of

Sewersheds

with > 50% of

homes built

before 1954

(Foundation Drains)

Scenario 1A

Newly Separated

Sewersheds

8000


9A-20

Estimation of Stormwater Volume Captured by the ISS

Conceptually, the stormwater “first flush” (which contains a large fraction of the pollutant load in the stormwater flow) is the volume that should be captured by the ISS. At this point in the analysis, the first flush volume had not been defined. Therefore, this discussion is a rough estimate of the volume that would be captured by the ISS with the 2020 Baseline operating procedures.

In the 2020 Baseline configuration, the ISS tunnel volume is 432 MG and the VRSSI is 177 MG. The tunnel gates close to the combined sewer service area when the ISS tunnel volume reaches 255 MG so that the remaining 177 MG are available for separate sewer inflow. Therefore, the 2020 Baseline configuration captures 255 MG of combined sewer inflow. If this same operating procedure were used in Screening Alternative 1A, 255 MG also would be captured. The inflow would be composed of stormwater from the newly separated areas and combined sewage from the remaining combined sewer service area.

The captured volume can be correlated to an equivalent rainfall depth using the following water balance logic:

♦ The existing combined sewer service area (15,610 acres) is approximately 72% impervious.

♦ Surface runoff flow is generated on both the pervious and impervious areas to varying degrees. Assume that the runoff volume ranged from 70 to 100% of the rainfall volume.

♦ For this rough estimate, assume that 85% of the rainfall is collected by the sewer system (since it is the midpoint of the range).

♦ If 85% of the rainfall is collected, then three quarters of an inch of rain on 15,610 acres is equivalent to a volume of 255 MG captured in the ISS.

While the tunnel is filling, some water is simultaneously being pumped to the treatment plants; this may be an additional 100 to 200 MG of runoff that can enter the ISS before the gates close (depending on the duration of the event). Figure 9A-8 shows the relationship between rainfall depth and the volume of runoff that can be captured by the ISS. The rainfall depth necessary to fill the ISS to the 255 MG level (accounting for the volume pumped to the treatment plants before the gates close) is in the range of 0.7 to 1.3 inches. Thus, the existing 255 MG of the ISS used to collect the combined sewer inflows is roughly equivalent to 1 inch of rainfall over the current combined sewer service area. The stormwater volume collected by the ISS would be similar to the combined sewer inflow volume

Stormwater Hydrographs for Water Quality Modeling of Screening Alternative 1A

To evaluate the water quality outcome of Screening Alternative 1A, the water quality model uses hydrographs of the excess stormwater that overflows to the waterways during the 10-year period 1988-1997. The stormwater runoff hydrographs generated by the FFS program contain the total stormwater flow. The hydrographs for the excess stormwater discharge to the waterways are a subset of the total stormwater flow after volume captured by the ISS is removed from the total stormwater flow.

FIGURE 9A-8

CAPTURED RUNOFF VOLUMEAND RAINFALL DEPTH2020 FACILITIES PLAN

FP_9A.0008.07.06.01.cdr6/1/07

Combined Sewer Area = 14,970 acres

0

50

100

150

200

250

300

350

400

450

500

550

600

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

Rainfall Depth (inch)

Cap

ture

dR

un

off

Vo

lum

e(M

G)

Percent Capture

255 MG

+100 MG

Pump/Treat

+200 MG

Pump/Treat

Approximate Volume Captured by ISS

100%

85%

70%


9A-22

To remove the captured volume from the total stormwater hydrographs, the time intervals when the ISS gates were closed were identified. (This was determined by a MACRO model simulation of the system.)

During a 10-year simulation period from 1988-1997, the stormwater volume captured by the ISS was 84% of the total stormwater runoff volume; the excess 16% was discharged to the waterways. The average stormwater discharge volume from the CSSA to the waterways was approximately 1,200 MG per year.

Additional Storage and Treatment

To achieve the goal of eliminating the SSOs and CSOs, additional ISS storage and treatment is required. The Screening Alternative 1A model uses the following:

♦ 200 MGD of additional treatment at SSWWTP

♦ 100 MGD of additional treatment at JIWWTP

♦ 100 MGD of additional ISS pumping capacity to JIWWTP

♦ 234 MG of additional ISS storage

After revising the model to include separation, the SSOs and remaining CSOs were eliminated using combinations of treatment, storage, and pumping. The model captures the “first flush” of the stormwater from the newly separated areas and the excess stormwater is discharged to waterways.

Costs

The maximum feasible separation is 89% of the combined sewer service area. The cost for separation assumes that the existing combined sewer conveyance system would be used as the stormwater collection system. A new separate sewer system would be built to convey the sanitary flow. The separation assumes that all existing laterals would be connected to the new sanitary system (this includes laterals that connect to foundation drains). It assumes that roof drain downspouts will be disconnected from the collection system. The cost does not include any work to disconnect foundation drains or laterals for roof drains for private property. The approximate cost for combined sewer separation is $2,700 million, along with additional costs of approximately $1,500 million for the additional storage, treatment and pumping needed to eliminate CSOs and SSOs. Therefore the total present worth cost for this alternative is approximately $4,200 million.

Results: Alternative 1D - Infiltration/Inflow Reduction to Eliminate SSOs To reduce SSOs using infiltration/inflow reduction technologies, inflow sources must first be eliminated and then I/I in priority sewersheds (those with exceptionally high wet weather flows) must be addressed. The analysis evaluated the benefits of nine progressive steps to further reduce I/I. Initial reduction steps focused on inflow sources and priority sewersheds with high I/I rates. Further steps to reduce the wet weather peak flows required sewer rehabilitation in additional areas of the SSSA.

To achieve zero SSO over the period of record, I/I rates in all sewersheds must be reduced to less than 2,000 gpad for the 5-year peak hour flow. The total present worth cost for this reduction is approximately $6,000 million. Achieving such an aggressive goal would require I/I reduction in


9A-23

virtually all sewersheds in the separate sewer service area with extensive work on private property sources.

Summary Table 9A-5 summarizes the technology combinations and the costs of each alternative. While both Screening Alternative 1A and 1B fully eliminate CSOs and SSOs during the period of record, the cost of Screening Alternative 1A ($4,200 million) is approximately $700 million less than Screening Alternative 1B ($4,900 million). However, there are greater risks and uncertainties with combined sewer separation. This alternative uses the same 25% contingency as other technologies. Sewer separation possibly warrants a higher contingency because there are likely to be other additional costs such as replacement of deteriorated water lines and other utility systems as the sewer separation process proceeds. Furthermore, the performance of the new system is uncertain; in particular the I/I rates in the new system cannot be predicted with confidence.

The cost of Screening Alternative 1B is very high, but the technologies employed (deep tunnel storage and additional treatment) are proven. The cost of these technologies has less uncertainty than the cost of sewer separation. Screening Alternative 1A has a large cost that is subject to greater uncertainty. Screening Alternative 1B also has a wide range of potential benefit for both the CSSA and the SSSA. Separation only eliminates CSOs in the part of the combined sewer service area that is separated; it does not help reduce CSOs from the central business district which is not separated.

Screening Alternative 1A removes CSOs but creates stormwater instead. In this way, the separation is not solving a problem; it is just transforming it into another type of problem. Screening Alternative 1B is a superior case because it the only alternative that truly “eliminates” CSOs.

Two Screening Alternatives were proposed to eliminate all SSOs. Screening Alternative 1C (using a combination of treatment and storage) eliminated SSOs for a cost of $1,300 million. Screening Alternative 1D, using I/I reduction, also achieves the goal of eliminating SSOs, but costs five times more than Screening Alternative 1C.

The results of these analyses show the extremely high costs of eliminating all CSOs. It is approximately three to four times more expensive to eliminate CSOs than SSOs. The most suitable technology for achieving such a high level of CSO reduction is additional ISS storage. The costs for these Screening Alternatives are very high because the alternatives demand full elimination of overflows for the largest events during the period of record. The Screening Alternatives do not allow for a reasonable level of service. The level of service should be guided by the water quality impact of overflows caused by infrequent events.

ScreeningAlternative

SewerSeparation

AdditionalSSWWTPCapacity

AdditionalJIWWTPCapacity

AdditionalTunnelStorage

AdditionalTunnel

Pumping

Infiltrationand InflowReduction

ConveyanceSystem

Upgrades

TotalCapitalCosts O&M

PresentWorth

SalvageValue

NetPresentWorth

1a Elements 89%

of CSSA

185 mgd 100 mgd 234 Mg 100 mgd None

Costs $2,740 $250 $160 $580 $120 None $350 $4,200 $4 $4,249 $668 $3,581

1b Elements None 185 mgd 100 mgd 1600 Mg 100 mgd None

Costs $250 $160 $3,990 $120 None $350 $4,870 $4 $4,919 $878 $4,041

1c Elements None 185 mgd 100 mgd 160 Mg 100 mgd None

Costs $250 $160 $400 $120 None $350 $1,280 $3.5 $1,323 $171 $1,152

1d Elements None None None None None 90%

Costs None None None None None $6,670 None $6,670 $6,670 $0 $6,670

ENR-CCI = 10,000 (2007)

TABLE 9A-5

SUMMARY OF ALTERNATIVE 1ELEMENTS AND APPROXIMATECOSTS IN MILLIONS2020 FACILITIES PLAN

FP_9A.T005.07.06.01.cdr6/1/07


9A-25

9A.3 Screening Alternative 2 – Watershed Best Management Practices In contrast to the first set of Screening Alternatives, which focus on eliminating overflows, this Screening Alternative deals with implementation of stormwater best management practices (BMPs). This alternative addresses the question of, “what water quality improvement is possible from a large-scale implementation of BMPs?” This Screening Alternative assumes that the implementation of conventional BMPs to the maximum extent practicable will result in measurable water quality improvement. The technologies employed in this analysis include the most widely studied, used and advocated, including:

♦ Infiltration technologies

♦ Treatment technologies

♦ Programs

In this scenario, these BMP technologies are implemented with the goal of reducing the water pollution resulting from stormwater or other nonpoint sources. The analysis for this Screening Alternative does not consider any changes that would reduce sewer overflows.

Various technologies could be used to achieve the same outcome. In this level of analysis (facilities planning) it is reasonable to show system-level combinations of technologies; however, additional preliminary and final design engineering effort would be required to develop the exact combination of technologies required to achieve the Screening Alternative result. Therefore, the estimated cost to achieve the widespread BMP implementation was developed using a general set of technologies applied reasonably, but at a level that is well above that which would be achieved under current regulatory and institutional frameworks.

9A.3.1 State of the Art Report Screening Alternative 2 identifies the benefits of the likely maximum achievable implementation of conventional nonpoint stormwater source control practices. This alternative would reduce stormwater pollutant loadings from significant nonpoint sources as much as practicable, exceeding the scope of the Wis. Admin. Code Natural Resources 151 (NR 151) requirements as represented in the 2020 Baseline. The technologies that were considered were those that MMSD has studied in demonstration and engineering studies and technologies that the Wisconsin Department of Natural Resources (WDNR) has identified as candidate technologies for compliance with NR 151 requirements.

Thirty-nine technologies were considered for Screening Alternative 2. These technologies were selected from a comprehensive list of potential technologies using the screening process described in Chapter 2, Technology/Indicator Analysis of the SOAR. Each of the technologies can be classified by the primary indicator that it addresses: volume, total suspended solids (TSS), coliform, debris or other indicators. The technologies and their classifications are as follows:

Volume Indicators

♦ Bioretention

♦ Cisterns

♦ Downspout disconnection


9A-26

♦ Green roofs

♦ Parking lot stormwater storage and treatment (green parking lots)

♦ Porous pavement

♦ Rain barrels

♦ Rain gardens

♦ Stormwater parks

♦ Stormwater trees

Total Suspended Solids Control Technologies

♦ Agricultural bench terraces

♦ Agricultural buffer strips

♦ Catch basin cleaning

♦ Catch basin filters

♦ Conservation crop rotation

♦ Conservation tillage

♦ Constructed wetlands

♦ Fine screens (SW (stormwater)/ SSO/ CSO) – at local outfalls

♦ Infiltration basins

♦ Riparian corridors/buffers

♦ Stormwater filtration systems (sand filters)

♦ Street sweeping

♦ Wet detention basins

Coliform Control Technologies ♦ Livestock management

♦ Manure management

♦ Pet litter control

♦ Residential and on-site sewage systems management

♦ Stormwater disinfection

♦ Waterfowl control measures


9A-27

Debris Control Technologies ♦ Debris/trash management (litter control)

♦ End of pipe combined sewer overflow nets

♦ End of pipe outfall booms

♦ End of pipe vortex separators

♦ Skimmer boat operation

Other Technologies

♦ Convert land to prairie (habitat)

♦ Convert land to wetlands (habitat)

♦ Fertilizer management (nutrients)

♦ Leadership in Energy and Environmental Design (LEED) (alternative development practices)

♦ Road salt management (chloride reduction)

♦ Water softener salt alternative (chloride reduction)

Chapter 4, Summary of Nonpoint Source Technology Analysis of the SOAR describes each of these technologies in detail.

9A.3.2 Technology Assumptions Four factors were used to determine which of the technologies listed in Chapter 2, Technology/ Indicator Analysis of SOAR would be included:

♦ Preference to technologies that expand current MMSD efforts or that MMSD has evaluated for implementation

♦ Preference to technologies assumed to be applied under NR 151

♦ Preference to guidance supplied by WDNR

♦ Engineering judgment as to the application of additional technologies.

For Screening Alternative 2, a suite of technologies was chosen to represent the maximum feasible implementation of conventional practices. These are assumed to apply in addition to the technologies represented in the 2020 Baseline alternative (Screening Alternative 1), which included the technologies assumed to be employed to meet the requirements of NR 151. Generally, the development of Screening Alternative 2 assumes a greater implementation of the conventional technologies from the set assembled for NR 151 compliance.e The choice of technologies is not meant to exclude the use of other technologies where appropriate, nor is it meant to imply that these technologies are likely to be applied exactly as assumed. Instead, it is intended to represent a reasonable distribution of actions to model the water quality benefits and estimate programmatic costs. The technologies applied differ by land use, either rural or urban.

e See Appendix 8A, NR 151 Implementation Description of this report.


9A-28

Rural Nonpoint Best Management Practice Technologies To reduce nonpoint pollution from rural areas in the RWQMPU study area, implementation of the controls required by NR 151 is assumed.f The assumed NR 151 controls consist of:

♦ Full implementation of conservation tillage

♦ Implementation of manure management

♦ Implementation of increased riparian buffers

♦ Nutrient management

Five additional rural nonpoint BMPs are incorporated in Screening Alternative 2, four of which are expansions of the NR 151 controls. These are:

♦ Expanded manure management

♦ Expanded livestock management,

♦ Expanded buffer strip implementation

♦ Expanded fertilizer management

♦ Septic system management (not a part of NR 151)

The increased implementation of NR 151 programs assumed by Screening Alternative 2 includes the following:

♦ Manure management program is applied to 100% of all livestock in the watersheds as determined by available headcount data

♦ Fencing is added along both sides of 50% of all pastures adjacent to waterways for livestock management

♦ Buffers on all waterways are increased to a minimum of 50 feet on each side of the waterway

♦ An education program is added to the fertilizer management program

The septic system management program assumes that additional inspectors will be added to monitor potential failing septic systems. It also assumes that failing systems are replaced, resulting in reduced impacts to water quality.

Urban Nonpoint Best Management Practice Technologies Stormwater technologies in urban areas were selected to meet two different goals: water quality improvement and stormwater volume reduction. Volume reduction technologies can result in improved water quality by reducing the flows in combined sewers, thereby reducing the occurrence of overflows, and by intercepting pollutant loads or preventing pollutants from entering stormwater. Of the selected technologies, some are applicable throughout the planning area and others would be implemented only in selected areas. The urban nonpoint technologies assumed to be implemented under NR 151 are:

♦ Vacuum street sweeping f See Section 9.4 of Chapter 9, Alternatives Analysis of this report.


9A-29

♦ Parking lot vacuum sweeping

♦ Parking lot implementation of multi-chamber treatment trains (MCTTs)

♦ Infiltration systems

♦ Wet detention basins (new development)

The discussion on NR 151 technologies and costs is described in Appendix 8A, NR 151 Implementation Description of this report. Natural Resources 151 does not have BMP requirements for areas within the CSSA.

In addition to those implemented through NR 151, planning-area wide urban water quality BMPs in Screening Alternative 2 include:

♦ Pet litter control program

♦ Chloride reduction program for street deicing and water softeners

♦ End-of-pipe stormwater treatment devices

♦ Fertilizer management education program

The chloride reduction program would be modeled after the programs in Madison and Brookfield, and would serve to reduce road chloride application by 50% and the usage of chloride in existing water softeners by 25%. Also, new water softeners would be chloride-free. The end-of-pipe treatment devices would use Delaware filters (or equivalent) to treat runoff from parking lots and other critical pollution source areas. The assumed implementation would be twice that required in NR 151, and includes 100% treatment of existing parking areas. The fertilizer management education program would compliment the rural program and strive to promote conscientious fertilizer application in urban areas.

Three technologies would specifically address the Lake Michigan and harbor areas:

♦ Waterfowl control program

♦ Litter control program

♦ Skimmer boat operation to reduce waterborne trash

The waterfowl and litter control programs would be initiated at all Lake Michigan beaches and the litter control program would also be conducted along the watercourses and the estuary. The waterfowl control program would rely on chemical methods and the litter control program would be modeled after trash Total Maximum Daily Load (TMDL) programs implemented for California beaches. The skimmer boat operation technology assumes a new skimmer boat that would operate within the inner and outer harbors.

Planning-area wide stormwater volume reduction BMPs in Screening Alternative 2 include:

♦ Additional runoff control

♦ Rain barrels & additional downspout disconnection

♦ Additional rain gardens/bioretention

Additional runoff control would be achieved by increasing the land areas where infiltration would be required and in some cases increasing the maximum percentage of site area that could


9A-30

be required for the infiltration facilities. Compliance could involve porous pavement or other infiltration based technologies, but would be implemented so as not to increase I/I in the sanitary sewer system. The infiltration assumptions are shown in Table 9A-6.

TABLE 9A-6 SCREENING ALTERNATIVE 2 INFILTRATION IMPLEMENTATION BY LAND USE ASSUMPTIONS

Infiltration Area Cap (Percent of Site)

Land Use Location Soil Drainage Alternative

2 NR 151 Existing institutional and commercial

CSSA, SSSA

Well, Poor 2% N/A

Well 2% SSSA Poor

6% N/A

New institutional and commercial

CSSA Well, Poor 6% N/A

Well 1% New residential SSSA Poor

3% N/A

New industrial CSSA Well, Poor 6% N/A

Redeveloped institutional and commercial

CSSA, SSSA

Well, Poor 6% N/A

CSSA = Combined Sewer Service Area NR 151 = Wisconsin Administrative Code Natural Resources 151 (Runoff Management) SSSA = Separate Sewer Service Area

The assumption for rain barrels and downspout disconnection is that 15% of all homes in the study area would participate and that 200 gallons of storage (4 barrels) would be provided at houses outside of the CSSA, and 100 gallons (2 barrels) at houses within the CSSA. Rain gardens and bioretention would be provided at an additional 15% of all homes.

Also, four additional technologies would be applied within the CSSA for Screening Alternative 2. These arose out of the various MMSD stormwater BMP studies and are:

♦ Additional rooftop storage

♦ Stormwater trees

♦ Additional inlet restrictors/street storage

♦ Selected disconnection of stormwater sources

The rooftop storage and inlet restrictors would be applied at 50% of the locations identified in the MMSD downspout disconnection study, reducing the volume of CSSA stormwater discharged to the combined sewers and near surface collector system that drains to the ISS. The stormwater disconnection would be implemented at the areas designated in the MMSD study.


9A-31

9A.3.3 Models Screening Alternative 2 evaluates the implementation of a complex combination of technologies. The cumulative performance of this implementation was analyzed using three models:

♦ MOUSE

♦ Loading Simulation Program in C++ (LSPC)

♦ ECOM/RCA (Estuarine Coastal and Ocean Model / Row Column AESOP)

These are the same models that were developed under the direction of SEWRPC for the RWQMPU. Output from the LSPC and ECOM/RCA models include water quality characteristics. The changes in water quality parameters observed in the model output were used to quantify the benefits from implementing large numbers of BMPs. Water quality comparisons are based upon 10 year model simulations that used weather data from 1988 to 1997. This period includes a representative mixture of dry and wet years and other factors, which is considered to be fairly representative of average conditions. However, it is important to note that it is possible to experience conditions more extreme than those contained in the 64.5-year period of record.

MOUSE Model - Benefits from Combined Sewer Service Area Best Management Practices The Streamline-MOUSE model described under Screening Alternative 1 was modified to reflect the effects of BMPs to be applied in the CSSA under Screening Alternative 2. The BMPs were estimated to provide an additional 40 million gallons of storage within the CSSA; therefore this additional storage was incorporated into the model. The model was then run to evaluate combined sewer performance under the alternative conditions. The output from this model was not used to directly evaluate Screening Alternative 2 performance, but rather was used as input to reflect the CSOs and treatment flows within the LSPC model and the ECOM/RCA model.g

LSPC Model - Initial Screening, Watershed Loads, Watercourse Water Quality, and Sensitivity Analysis The LSPC models developed for assessing flows and pollutant loading from the planning area watersheds under future conditions were modified to represent Screening Alternative 2 conditions. These models use precipitation and other meteorological datasets applied to the land components in a given watershed to generate runoff flows and pollutant loadings from the land to the streams and rivers. These loadings are then routed to downstream areas. The models also represent pollutant reduction or pollutant changes within the watercourses. Separate models were developed to simulate the Milwaukee River, Menomonee River, Kinnickinnic River, Oak Creek, the Root River and Lake Michigan direct drainage systems.

The LSPC models of future watershed conditions were modified to reflect the stormwater storage, infiltration and treatment provided by the technologies selected for this Screening Alternative. The effects of the BMPs were represented at the subbasin level because it would not be possible to represent individual BMPs in the regional scale model. After the models were configured to represent BMP implementation at a regional level, the models were run using the

g Detailed discussion of the MOUSE modeling effort can be found in the Chapters 3 and 4 of the Conveyance Report.


9A-32

meteorological data and MOUSE model flows as inputs. Model output included simulated water quality at assessment points within the watersheds and pollutant loading to the downstream receiving water, all on an hourly basis. The simulated loads were used as input to the ECOM/RCA model and the model output at the assessment points in the watersheds was used to evaluate changes in water quality.h

In order to better understand the implications of individual BMPs within the Screening Alternative 2 model runs, two submodels were developed from the larger models, one representing Underwood Creek in the Menomonee River watershed, and the other representing the West Branch Root River Canal in the Root River watershed. Underwood Creek represents a highly urbanized subbasin that is relatively unaffected by combined sewer overflows and the West Branch represents a more agricultural subbasin. In the models of these two subbasins, the BMPs were more explicitly modeled, and a sensitivity analysis was conducted to evaluate the factors that govern the effectiveness of the BMPs regarding regional water quality improvement. The sensitivity analyses are described further in Section 9A.3.4.

ECOM/RCA Model - Lake/Estuary Water Quality A hydrodynamic and water quality model of the Milwaukee Harbor and Estuary was used to evaluate the changes expected due to Screening Alternative 2. This model, referred to as the “Estuary Model,” simulates bacterial and eutrophication processes coupled directly to a three-dimensional model of estuarine physical processes. The model represents the lower portions of the Milwaukee, Menomonee and Kinnickinnic Rivers, the Milwaukee Harbor and near-shore Lake Michigan. It extends to approximately the 30-60 meter bathymetric contour in Lake Michigan from Fox Point to the north to Wind Point to the south. Detailed discussion of the Lake/Estuary modeling effort can be found in Chapter 10 of SEWRPC Technical Report No. 39, Water Quality Conditions and Sources of Pollution in the Greater Milwaukee Watersheds.

The Estuary Model uses the loads and flows generated by the LSPC river watershed models for the Milwaukee, Menomonee and Kinnickinnic, Rivers and Oak Creek, and the direct stormwater inputs to Lake Michigan also calculated by LSPC. MOUSE model outputs were used to represent contributions from the CSSA. Point loads from the MMSD WWTPs, the South Milwaukee WWTP, the WE Energies Menomonee Valley and Oak Creek Power Plants, and two flushing tunnels were also incorporated in the hydrodynamic and water quality models. The models also required water surface elevation, water temperature and meteorological parameters to simulate estuarine conditions. Detailed output was generated at each water quality location every six hours and this data was analyzed to develop the water quality statistics at the assessment points in the estuary.

9A.3.4 Alternative Analysis

Because of the large number of potential combinations for implementation, the alternative analysis conducted for Screening Alternative 2 differs from those conducted for Screening Alternative 1. For Screening Alternative 2, judgment was used to establish a model of an appropriate level of effective technologies. With that model as a 2020 Baseline, the influence of different mixes of technologies was determined by running sensitivity analyses that focused on

h Detailed discussion of the Lake/Estuary modeling effort can be found in SEWRPC Technical Report No. 39, Chapter 10.


9A-33

specific representative areas and the technologies applied in those areas. The focused modeling efforts served to verify the assumptions of the larger-scale models and determine which technologies most affected the assessed water quality parameters. These analyses were then used to guide the most effective implementation by highlighting which aspects of water quality needed to be further addressed and the specific technologies to address them.

Rural Best Management Practices The effects of the rural BMPs are represented within the Screening Alternative 2 LSPC models as reductions in the sediment/pollutant loading from the land surface. To represent the manure management and livestock management programs, coliform loading from all crop and pasture lands was reduced by 50%. The effects of riparian buffers and the fertilizer management program were represented by reducing the TSS loads by an additional 10% over the NR 151 requirements (from 40% to 50%), reducing the total phosphorus (TP) loads by 7% and the total nitrogen (TN) loads by 4%.

To evaluate these assumptions, a sensitivity analysis was conducted by more explicitly modeling these practices for the West Branch subwatershed of the Root River. The sensitivity analysis assumed that cattle would be excluded from streams, that all manure was collected and composted prior to application (99% reduction in coliform levels), and that composted manure would be applied twice during the year. The effects of these practices were converted to reduce buildup and wash-off rates using the Fecal Coliform Loading Estimation spreadsheet. Riparian buffers were modeled by estimating the increased area of buffer in the subbasin, assigning a treatment effectiveness to that area based on the buffer width, and assuming that an area 20 times the buffer width was effectively treated.

This analysis indicated that the model assumptions for Screening Alternative 2 reduce pollutant loadings to a degree generally consistent with the reductions observed when these practices are more explicitly represented. Enhanced manure and livestock management was found to be the most effective way to address rural fecal coliform, reducing downstream load by 75%. The riparian buffer simulation indicated that TSS, TN and TP would experience nearly the same amount of reduction, which was approximately 12% of the loads from cropland and pasture land; estimating the reduction using 10% TSS, 7% TN and 4% TP is generally consistent with these results because the sensitivity analysis model may have slightly overestimated the trapping efficiency of TN and TP.

Urban Best Management Practices The effects of the urban BMPs are represented in the Screening Alternative 2 model by applying a reduction of pollutant loads within the NR 151 area relative to Screening Alternative 1: 10% of TSS loads, 7% of TP loads and 4% of TN loads. Infiltration and extended detention (wet ponds) are incorporated within each subbasin as explicit “per-acre” representations. TSS removal is estimated from these practices, and from overflow from the infiltration facilities, and the removal of other pollutants is represented as a percentage of the TSS reduction.

A sensitivity analysis was conducted by modeling these practices for the Underwood Creek subwatershed of the Menomonee River. The sensitivity analysis assumed:


9A-34

♦ Rain barrels and downspout disconnection applied to 7.5% of residential impervious area, with the water directed from these technology applications assumed to be routed to pervious areas

♦ Rain gardens/bioretention applied to 7.5% of residential impervious area from new and existing residences where soils allow infiltration into the ground

♦ Increase TSS reduction for existing land uses to 50% (NR151 requires 40% TSS reduction from existing land uses)

♦ Additional 30% reduction of fecal coliform load in discharge from infiltration BMPs due to sediment trapping

The area treated by infiltration was also expanded by:

♦ Reducing the minimum soil infiltration capacity under which infiltration BMPs would be required

♦ Applying infiltration BMPs to new industrial land uses

♦ Infiltrating 25% of existing impervious area associated with existing industrial, commercial and institutional development where soils allow

This analysis indicated that the model assumptions for Screening Alternative 2 reduce pollutant loadings to a degree consistent with the reductions observed when these practices are more explicitly represented. The explicit modeling simulated a 12% reduction in TSS, a 6% reduction in TP and a 7% reduction in TN. The conclusion from this analysis is that the designated combination of technologies would meet the “10% / 7% / 4%” removal assumed in the larger model, with the exception that there may be some extra effort necessary to achieve 7% removal of TP.

Costs The costs for Screening Alternative 2 are shown in Table 9A-7.

The total present worth cost of Screening Alternative 2 is $1,400 M – essentially the same cost as Screening Alternative 1C, which eliminates SSOs from the MMSD sewer service area.

9A.4 Sources of Pollutants/Pollutant Loadings The primary sources of pollutants to the waterways are as follows:

♦ Stormwater Runoff (rural and urban)

♦ Industrial Discharges

♦ CSOs and SSOs

♦ Publicly Owned Treatment Works (POTWs)

♦ Wildlife (seagulls, etc.)

These sources of pollutants are identified as point or nonpoint as shown in Table 9A-8.

TABLE 9A-7

SUMMARY OF SCREENINGALTERNATIVE 2 ELEMENTS ANDAPPROXIMATE COSTS IN MILLIONS2020 FACILITIES PLAN

FP_9A.T007.07.06.01.cdr6/1/07

Component Capital O&M Present Worth Salvage Value Net Present Worth

Manure Management (Includes Livestock

Management) $246 $16 $445 $28 $416

Buffer Strips $1.7 $0.4 $6.2 $0.4 $5.8

Septic Systems $110 $0.6 $118 $0 $118

Ru

ral

Fertilizer Management $0 $0 $0 $0 $0

Fertilizer Management $0 $0 $0 $0 $0

Pet Litter $0 $0 $0 $0 $0

Waterfowl Control $0 $0.1 $1.5 $0 $1.5

Litter Control $0 $5.2 $64 $0 $64

Skimmer Boat $1.0 $0.2 $2.8 $0 $2.8

Chloride Reduction $0.4 $1.2 $15 $0 $15

Infiltration Systems $112 $5.5 $179 $0 $179

Rain Barrels and Downspout

Disconnection $49 $0.9 $60 $0 $60

Rain Gardens and Downspout

Disconnection $125 $4.7 $184 $0 $184

Stormwater Treatment $260 $7.1 $347 $57 $290

Rooftop Storage $25 $0 $25 $0 $25

Inlet Restrictors $33 $0.7 $41 $7.1 $33

Urb

an

Stormwater Disconnections $7.3 $0 $7.3 $1.6 $5.7

TOTAL $969 $43 $1,495 $94 $1,400

ENR-CCI = 10,000 (2007)


9A-36

TABLE 9A-8

PRIMARY SOURCES OF POLLUTANTS TO LOCAL WATERWAYS

Point Sources Nonpoint Sources1

Process and

Cooling Water

Overflows SSOs/ CSOs

Treatment Plant Effluent

Urban Stormwater

Runoff2

Rural Stormwater

Runoff Responsible Entities

Industries and other non-industrial facilities

MMSD and local municipalities

MMSD and local municipalities

Municipalities (and all parties they serve), homeowners, and commercial & industrial properties

Landowners and farmers

1) While stormwater runoff can enter a waterway through a designated outlet or pipe, it is generally defined as a nonpoint source because the nature of the pollutant source is nonspecific and diffuse. Pollutants from wildlife, such as seagull droppings, may enter the waterways in both urban and rural stormwater runoff. 2) Includes construction and developed sites. The projected average annual pollutant loading summary to the watersheds for each pollutant is presented in Tables 9A-9 to 9A-14. These projected pollutant loadings were developed from the water quality model simulation of watershed conditions using 2020 Baseline population and land use, with the assumption that the MMSD committed projects were completed and all regulated entities in urban areas were in full compliance with NR 151. The nonpoint sources include urban and rural stormwater runoff. The rural nonpoint sources include agricultural runoff. The urban nonpoint sources include all stormwater runoff sources that are non-agricultural

As shown in these tables, the majority of fecal coliform and TSS loadings come from nonpoint sources (urban and rural runoff). The BOD and copper loadings are split between point and nonpoint sources. Approximately 72% of the total nitrogen loading comes from point sources, with POTWs being the largest source of total nitrogen. Approximately 65% of the total phosphorous loading comes from point sources.

Tables 9A-9 to 9A-14 show that the total annual load from the existing situation (approximates year 2000) combination of SSOs and CSOs contributes less than 6.4% of the fecal coliform load, less than 2% of the phosphorus load, approximately 1 % of the BOD and total copper loads and approximately 0.5% of the TSS and total nitrogen loads.

TABLE 9A-9

LOADS OF TOTAL PHOSPHORUSTO GREATER MILWAUKEEWATERSHEDS (LBS/YR)2020 FACILITIES PLAN

FP_9A.T009.07.06.01.cdr6/1/07

Point Sources Nonpoint Sources

ScreeningAlternative Industrial SSOs CSOs WWTPs Subtotal Urban Rural Subtotal Total

Existing 2020 112,982 1,320 5,086 366,005 485,392 64% 118,981 159,311 278,292 36% 763,684

2020 Baseline 101,246 3,846 6,387 382,135 493,614 65% 102,939 157,702 260,641 35% 754,255

1A 101,246 0 0 382,135 483,382 65% 104,357 157,702 262,059 35% 745,441

1B 101,246 0 0 382,135 483,382 65% 102,939 157,702 260,641 35% 744,023

1C 101,246 0 6,387 382,135 489,768 65% 102,939 157,702 260,641 35% 750,409

1D 101,246 0 6,387 382,135 489,768 65% 102,939 157,702 260,641 35% 750,409

2 101,246 5,095 3,385 382,135 491,862 67% 96,078 148,684 244,762 33% 736,624

Source: SEWRPC (preliminary data)

TABLE 9A-10

LOADS OF TOTAL SUSPENDEDSOLIDS TO GREATER MILWAUKEEWATERSHEDS (TONS/YR)2020 FACILITIES PLAN

FP_9A.T010.07.06.01.cdr6/1/07


ScreeningAlternative Industrial SSOs CSOs WWTPs Subtotal Urban Rural Subtotal

Total

Existing 2020 264 46 300 3,593 4,202 5.7% 25,070 44,612 69,682 94.3% 73,885

2020 Baseline 253 109 355 3,640 4,357 5.4% 19,867 56,972 76,839 94.6% 81,196

1A 253 0 213 3,640 4,107 5.1% 20,201 56,972 77,172 94.9% 81,279

1B 253 0 0 3,640 3,894 4.8% 19,867 56,972 76,839 95.2% 80,733

1C 253 0 355 3,640 4,248 5.2% 19,867 56,972 76,839 94.8% 81,088

1D 253 0 355 3,640 4,248 5.2% 19,867 56,972 76,839 94.8% 81,088

2 253 150 184 3,640 4,228 5.6% 19,256 52,440 71,696 94.4% 75,924


TABLE 9A-11

LOADS OF TOTAL FECAL COLIFORMBACTERIA TO GREATER MILWAUKEEWATERSHEDS (CELLS/YR)2020 FACILITIES PLAN

FP_9A.T011.07.06.01.cdr6/1/07



Existing 2020 1.2E+13 1.1E+15 4.5E+15 2.1E+15 7.7E+15 8.8% 5.0E+16 3.0E+16 8.0E+16 91.2% 8.8E+16

2020 Baseline 1.2E+13 3.4E+15 6.1E+15 2.1E+15 1.2E+16 16.6% 3.5E+16 2.3E+16 5.8E+16 83.4% 6.9E+16

1A 1.2E+13 0.0E+00 1.3E+14 2.1E+15 2.2E+15 3.7% 3.5E+16 2.3E+16 5.9E+16 96.3% 6.1E+16

1B 1.2E+13 0.0E+00 0.0E+00 2.1E+15 2.1E+15 3.5% 3.5E+16 2.3E+16 5.8E+16 96.5% 6.0E+16

1C 1.2E+13 0.0E+00 6.1E+15 2.1E+15 8.2E+15 12.3% 3.5E+16 2.3E+16 5.8E+16 87.7% 6.6E+16

1D 1.2E+13 0.0E+00 6.1E+15 2.1E+15 8.2E+15 12.3% 3.5E+16 2.3E+16 5.8E+16 87.7% 6.6E+16

2 1.2E+13 4.4E+15 3.5E+15 2.1E+15 1.0E+16 16.2% 3.1E+16 2.1E+16 5.2E+16 83.8% 6.2E+16




Existing 2020 138,800 3,966 39,808 8,274,249 8,456,823 69.5% 859,638 2,860,168 3,719,806 30.5% 12,176,629

2020 Baseline 106,921 9,499 45,619 8,317,026 8,479,065 71.6% 725,937 2,644,322 3,370,260 28.4% 11,849,325

1A 106,921 0 6,579 8,317,026 8,430,526 71.4% 733,618 2,644,322 3,377,940 28.6% 11,808,466

1B 106,921 0 0 8,317,026 8,423,947 71.4% 725,937 2,644,322 3,370,260 28.6% 11,794,207

1C 106,921 0 45,619 8,317,026 8,469,566 71.5% 725,937 2,644,322 3,370,260 28.5% 11,839,826

1D 106,921 0 45,619 8,317,026 8,469,566 71.5% 725,937 2,644,322 3,370,260 28.5% 11,839,826

2 106,921 13,190 24,269 8,317,026 8,461,405 71.9% 706,550 2,601,212 3,307,762 28.1% 11,769,167

TABLE 9A-12

LOADS OF TOTAL NITROGENTO GREATER MILWAUKEEWATERSHEDS (LBS/YR)2020 FACILITIES PLAN

FP_9A.T012.07.06.01.cdr6/1/07


TABLE 9A-13

LOADS OF BIOCHEMICAL OXYGENDEMAND TO GREATER MILWAUKEEWATERSHEDS (LBS/YR)2020 FACILITIES PLAN

FP_9A.T013.07.06.01.cdr6/1/07



Existing 2020 427,091 14,656 119,469 7,716,594 8,277,810 47.2% 3,444,041 5,814,570 9,258,611 52.8% 17,536,421

2020 Baseline 383,210 43,487 172,443 7,843,055 8,442,195 46.8% 2,978,420 6,631,727 9,610,148 53.2% 18,052,343

1A 383,210 0 10,627 7,843,055 8,236,892 46.1% 3,017,926 6,631,727 9,649,654 53.9% 17,886,546

1B 383,210 0 0 7,843,055 8,226,265 46.1% 2,978,420 6,631,727 9,610,148 53.9% 17,836,412

1C 383,210 0 172,443 7,843,055 8,398,708 46.6% 2,978,420 6,631,727 9,610,148 53.4% 18,008,856

1D 383,210 0 172,443 7,843,055 8,398,708 46.6% 2,978,420 6,631,727 9,610,148 53.4% 18,008,856

2 383,210 56,586 82,888 7,843,055 8,365,739 46.9% 2,982,617 6,472,714 9,455,330 53.1% 17,821,069


TABLE 9A-14

LOADS OF TOTAL COPPERTO GREATER MILWAUKEEWATERSHEDS (LBS/YR)2020 FACILITIES PLAN

FP_9A.T014.07.06.01.cdr6/1/07



Existing 2020 14 11 124 10,950 11,099 54.7% 5,685 3,500 9,185 45.3% 20,284

2020 Baseline 14 30 167 11,140 11,351 57.6% 4,711 3,650 8,360 42.4% 19,711

1A 14 11 146 11,140 11,310 57.3% 4,784 3,650 8,434 42.7% 19,744

1B 14 11 85 11,140 11,249 57.4% 4,711 3,650 8,360 42.6% 19,610

1C 14 11 167 11,140 11,332 57.5% 4,711 3,650 8,360 42.5% 19,692

1D 14 11 167 11,140 11,332 57.5% 4,711 3,650 8,360 42.5% 19,692

2 14 38 90 11,154 11,297 57.6% 4,704 3,613 8,317 42.4% 19,614



9A-43

9A.5 Resulting Modeled Water Quality from Screening Alternatives The general water quality benefits achievable by individual approaches to controlling CSOs and SSOs or application of high levels of stormwater BMPs were evaluated using five Screening Alternatives. Screening Alternatives 1A and 1B were constructed to eliminate both SSOs and CSOs during the period of record. Screening Alternatives 1C and 1D were designed to eliminate SSOs but not CSOs. Screening Alternative 2 focuses on the implementation of stormwater best management practices.

Each of the Screening Alternatives was modeled to determine the resulting water quality in the six watersheds in the MMSD planning area. Modeling was completed for the following parameters: fecal coliform, DO, TSS, TN, TP, and copper. Summary statistics of resulting water quality for each parameter were compiled and are presented in this section. Modeled water quality of the existing conditions, as previously presented in Chapter 4, Section 4.13, were first compared to the 2020 Baseline. Then Screening Alternatives 1A, 1B, 1C, 1D, and 2 were compared to 2020 Baseline.

Refer to Chapter 4, Section 4.13 and Chapter 6, Section 6.3 for a description of terms and regulatory standards used in the following discussion, and refer to Appendix 9B for detailed modeled data tables and graphs.

In this discussion of water quality, the data analysis makes note of whether or not a watershed meets the applicable standard or guideline 85% of the time. The 85% figure was used as a guideline because if a watershed exceeds WDNR water quality standards 15% of the time (based upon water quality samples over a three year period) the watershed stream reach is classified as impaired by WDNR. The “impaired” designation is significant as it then required WDNR to list the watershed or stream reach on the “303(d)” list of state waters that do not meet water quality standards.(see discussion of this issue in Chapter 6, Section 6.3.3.

The technical team uses this 85% compliance level as an illustration and guideline of how close a watershed it to meeting water quality standards. The figure was assumed as it is the inverse of the 15% non compliance used for the 3030 (d) listing criteria. WDNR does not have specific critera on removal of stream reaches from the 303(d) list. Thus, the use of the 85% value in this analysis is meant to show what stream reaches or watersheds may be improved by various alternatives to the a guideline or point of reference which may possibly influence continued placement on the 303(d) list.

9A.5.1 Kinnickinnic River Water quality parameters were modeled for resulting water quality at two assessment points located along the mainstem of the Kinnickinnic River (that is, the principal waterway, as opposed to its tributaries).i Assessment point RI-12 is upstream of point RI-13, which is closer to the estuary portion of the river.j The mainstem of the Kinnickinnic River is categorized as a special variance water, but the other tributary streams within the watershed have been categorized as fish and aquatic life (FAL) waters by default, because no specific use

i See Appendix 9B Figures 9B-1-KK through Figure 9B-3-KK. j See Appendix 9B, Tables 9B-1-KK and 9B-2-KK for a summary of the modeling results for these assessment points.


9A-44

classification is identified in NR 102. Both assessment points RI-12 and RI-13 are within special variance waters as defined in NR 104.06(2).k

Fecal Coliform The water quality improved from existing conditions to 2020 Baseline for each assessment point as described below.

The mean fecal coliform counts for the entire year improved approximately 15% and 16% for assessment points RI-12 and RI-13, respectively. For the swimming season (defined as the 153-day period from May 1 to September 30), there was a 11% improvement at assessment point RI-12 and a 12% improvement for assessment point RI-13. The percent of time the water met the variance standard improved less than 1% for the entire year for both assessment points and deteriorated less than 1% for the swimming season for both points. Only the swimming season data set met the variance standard a minimum of 85% of the time, which indicates that the water quality may not be impaired with respect to the fecal coliform variance standard during the swimming season.

Mean fecal coliform counts showed a 7 to 9% improvement for each of the five Screening Alternatives for both assessment points when evaluated for the entire year. This compares to a 20 to 24% improvement found for Screening Alternatives 1A through 1D and a 1 to 2% improvement for Screening Alternative 2 for the swimming season data set. The change in mean counts, however, does not significantly improve the percent time the variance standard is met. Screening Alternatives 1A through 1D showed no improvement in meeting the variance standard at both assessment points. Screening Alternative 2 showed about a 1% improvement for time meeting the fecal coliform variance standard for both assessment points during the swimming season.

Each assessment point’s modeled mean fecal coliform data for the swimming season was approximately 50% better than the entire year data. The existing conditions and the six alternatives met the variance standard at least 85% of the time during the swimming season. When evaluated for the entire year, the modeled data for the Screening Alternatives met the compliance standard 75% of the time.

In general, the modeled data suggest that the Kinnickinnic River would experience minimal improvement in days of compliance with fecal coliform variance regulatory standards if all overflows were eliminated, all combined sewers were separated, I/I was eliminated, or a high level of BMPs were implemented. The most improvement occurred when the high level of BMPs was applied to the model and evaluated for the swimming season.

Dissolved Oxygen Mean DO concentrations did not vary between the Screening Alternatives for each assessment point. Water quality for DO was in compliance 100% of the time for all Screening Alternatives.

k Refer to Chapter 6, Section 6.3.3.


9A-45

Total Suspended Solids The mean concentrations of TSS improved approximately 21% from existing conditions to 2020 Baseline, which translates into a 2 to 3% improvement in number of days the mean concentration met the guideline. The existing conditions met the guideline at least 92% of the time.

The mean TSS concentrations varied 1% or less between the Screening Alternatives and the 2020 Baseline for each assessment point. The TSS guideline of 100 mg/l was met at least 94% of the time under any of the Screening Alternatives.

Total Nitrogen The mean concentrations of TN improved approximately 7% from existing conditions to 2020 Baseline for assessment points RI-12 and RI-13.

The mean TN concentrations varied 1% or less between the Screening Alternatives for each assessment point, which indicates that there is a nominal difference among the Screening Alternatives in water quality improvement. There is no compliance standard or planning guideline to which the mean concentration could be compared.

Total Phosphorus The mean concentrations for TP improved between 3 and 4% from existing conditions to 2020 Baseline for both assessment points.

When comparing the Screening Alternatives to the 2020 Baseline, Screening Alternative 2 showed a 1 to 2% improvement in the mean TP concentration for assessment points RI-12 and RI-13, respectively. Screening Alternatives 1A through 1D showed a 1% improvement. Overall, the Screening Alternatives met the guideline of 0.1 mg/L TP 24 to 25% of the time for assessment point RI-12 and 27 to 28% of the time for point RI-13.

Copper The mean concentration of copper improved approximately 14% from existing conditions to 2020 Baseline for both assessment points.

The mean copper concentrations did not vary between the Screening Alternatives for each assessment point. There is no compliance standard or planning guideline to which the mean concentration could be compared.

Summary In summary, water quality in the Kinnickinnic River showed improvements in mean concentrations from existing conditions to 2020 Baseline for fecal coliform, TSS, and copper, but little change for mean concentrations of DO, TN, and TP. Water quality under 2020 Baseline did not meet the fecal coliform variance standard 85% of the entire year nor did it meet the TP guideline 85% of the year. In other words, water quality was worse than the standard or guideline for these two parameters more than 15% of the time.

When the Screening Alternatives were applied to the model, the fecal coliform variance standard was met 85% of the swimming season. The percent of time that the DO, TSS, and TP standards and guidelines were met did not improve the 2020 Baseline. Overall, little variation in model results occurred between the Screening Alternatives.


9A-46

9A.5.2 Menomonee River Water quality parameters were modeled at five assessment points in the Menomonee River Watershed.l Assessment point RI-16 is in the upstream portion of the river, points RI-21 and RI-22 are in the central portion of the river, and points RI-09 and RI-10 are in the downstream portion of the river.m Assessment point RI-10 is also located within the estuary. Assessment points RI-09 and RI-10 are in streams categorized as special variance waters; and points RI-16, RI-21, and RI-22 are in streams categorized as FAL waters.n

Fecal Coliform Water quality deteriorated from existing conditions to 2020 Baseline for upstream assessment points and improved for downstream points. Mean fecal coliform counts at point RI-16 worsened 13% for the entire year and 10% for the swimming season. In the central portion of the watershed, the mean fecal coliform counts improved 4 to 10% for the entire year and 8 to 13% for the swimming season but the geomean at RI-21 showed no improvement and the median at RI-21 and RI-22 showed a 7 to 15% increase in fecal counts. In the downstream portion of the watershed, the mean counts improved 16 to 18% for the entire year and 13 to 15% for the swimming season. Even with these improvements in water quality for the majority of the assessment points, only waters in the downstream portion of the watershed, where the variance standard applies, met the applicable standard at least 85% of the time.

In the upstream and central portions of the watershed, mean fecal coliform counts showed little to no improvement between the 2020 Baseline and Screening Alternatives 1A through 1D. However, improvements of 11 to 16% for the entire year and swimming season data sets were modeled when Screening Alternative 2 was applied. For downstream assessment points RI-09 and RI-10, Screening Alternatives 1A, 1B, and 2 showed a 9 to 11% improvement in the mean fecal coliform counts during the swimming season. The percent of time the water meets the fecal coliform standard does not vary significantly between any of the alternatives and does not significantly improve upon the 2020 Baseline. Only downstream waters complied with their respective standard at least 85% of the time when evaluated for the swimming season.

In general, the Menomonee River modeled data suggest that there would be minimal to no improvement in days of compliance with fecal coliform regulatory standards if all overflows were eliminated, all combined sewers were separated, I/I was eliminated, or a high level of BMPs were implemented. The most improvement of 1 to 2 days occurred when a high level of BMPs (Screening Alternative 2) was applied to the model.

Dissolved Oxygen The mean DO concentrations did not vary between the Screening Alternatives for each assessment point. Water quality for DO was in compliance 99 to 100% of the time under any of the Screening Alternatives.

l See Appendix 9B, Figures 9B-1-ME through 9B-1-5-ME. m See Appendix 9B, Tables 9B-1-ME_RI-16 through 9B-5-ME_RI-10 for a summary of the modeling results for these assessment points. n See Chapter 6, Section 6.3.3.


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Total Suspended Solids The mean concentrations of TSS improved approximately 16 to 18% from existing conditions to 2020 Baseline for assessment points RI-21 downstream to RI-10, which translates into a 1 to 2% improvement in the number of days the mean concentration met the guideline. For the most upstream assessment point RI-16, mean TSS concentrations and the number of days the concentration met the guideline varied less than 1%. Water quality at each assessment point under the 2020 Baseline met the TSS guideline of 100 mg/l at least 94% of the time.

The mean TSS concentrations varied less than 1% between the Screening Alternatives 1A through 1D for each assessment point when compared to 2020 Baseline. However, there was improvement in mean TSS concentrations when Screening Alternative 2 was applied to the model. The largest improvement, 7%, was modeled at the most upstream assessment point RI-16, while an improvement of 3 to 4% was modeled in the central portion of the watershed and a 2% improvement was modeled at the downstream points RI-09 and RI-10. The water quality at each assessment point met the TSS guideline of 100 mg/l at least 96% of the time under all of the alternatives.

Total Nitrogen The mean concentrations of TN improved between 12 and 14% from existing conditions to 2020 Baseline for upstream and downstream sections of the river and improved 15 to 16% along the central portion of the river.

The mean TN concentrations did not vary between Screening Alternatives 1A through 1D at each assessment point and did not improve upon the 2020 Baseline. There was one exception to this. When Screening Alternative 2 (employ a high level of BMPs) was applied to the model, there was a 2 to 3% improvement over the 2020 Baseline alternative at all five assessment points. There is no compliance standard or planning guideline to which the mean concentration could be compared.

Total Phosphorus The mean concentrations for TP improved 1 to 3% from existing conditions to 2020 Baseline for assessment points RI-22, RI-09, and RI-10. Further upstream at assessment points RI-21 and RI-16, modeled water quality worsened 2% and 8%, respectively. The 2020 Baseline did not improve upon the percent time the TP guideline was met at all assessment points, and water quality under the existing conditions and 2020 Baseline did not meet the TP guideline 85% of the time.

When comparing the Screening Alternatives to 2020 Baseline, only Screening Alternative 2 showed an improvement of 3 to 5% in the mean TP concentration for all assessment points. Screening Alternatives 1A through 1D showed no improvement. None of the Screening Alternatives improved the water quality enough to comply with the TP guideline 85% of the time.

Copper The mean concentration of copper worsened in the upstream section and gradually improved toward the central and downstream portions of the river between existing conditions and 2020 Baseline.


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The mean copper concentrations did not vary between Screening Alternatives 1A through 1D, and they did not vary from 2020 Baseline. However, there was a 2 to 7% improvement in the mean concentration when Screening Alternative 2 was applied to the model. There is no compliance standard or planning guideline to which the mean concentration could be compared.

Summary In summary, water quality in the Menomonee River showed improvements in mean concentrations between existing conditions and 2020 Baseline for TSS, TN and showed little change in mean concentrations of DO. Mean fecal coliform counts, TP, and copper improved in the lower portion of the river and worsened in the upper portion of the river under the 2020 Baseline condition. Water quality under 2020 Baseline did not meet the fecal coliform standard 85% of the year in the upper and central sections of the river, and the TP guideline was not met 85% of the time at all assessment points.

When the Screening Alternatives were applied to the model, the water quality met the DO standard and the TSS guideline. However, the fecal coliform standard and TP guidelines were not met 85% of the time. Overall, little variation in model results occurred between Screening Alternatives 1A through 1D. Screening Alternative 2 showed modest improvement for most of the parameters.

9A.5.3 Milwaukee River Water quality parameters were modeled at four assessment points along the Milwaukee River mainstem.o Assessment points RI-01, RI-02, RI-04, and RI-05 extend from the Milwaukee River where it enters the MMSD planning area (RI-01) to North Avenue (RI-05). Assessment point RI-02 is located along the Milwaukee River at Brown Deer Road, and point RI-04 is located along the Milwaukee River at Port Washington Road, just east of Interstate Highway 43.p

The lowest reach of the Milwaukee River, from the location of the abandoned North Avenue Dam to the confluence with Lake Michigan, and two tributaries, Indian Creek and Lincoln Creek, have been categorized as variance waters. The mainstem categorization is designated in NR 104.06(2)(b)(1), and the categorization of the two tributaries is given in NR 104.06(2)(a)(5) and NR 104.06(2)(a)(9). The rest of the mainstem and tributaries have been categorized as FAL waters by default because no specific use classification is identified in NR 102. Assessment points RI-01, RI-02, RI-04, and RI-05 are within FAL designated waters.

Fecal Coliform The modeled water quality for the fecal coliform parameter improved from existing conditions to 2020 Baseline for each assessment point. At assessment point RI-01, an improvement in mean fecal coliform counts of 44% for the entire year and 56% over the swimming season from the existing conditions to 2020 Baseline was modeled. In the downstream assessment points, the mean counts improved 17 to 25% for the entire year and 3 to 15% for the swimming season. At assessment point RI-04, however, mean fecal counts during the swimming season worsened 3%.

o See Appendix 9B, Figure 9B-1-MI. p See Appendix 9B, Tables 9B-1-MI_RI-01 through 9B-4-MI_RI-05 for a summary of the modeling results for these assessment points.


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Only waters at the upstream assessment point RI-01 and downstream point RI-05 met the coliform standard at least 85% of time when evaluated for the swimming season.

Screening Alternatives 1A through 1D showed no change or up to 3% improvement in mean fecal coliform counts over the 2020 Baseline alternative at assessment points RI-01 and RI-02. Improvements of 2 to 18% were modeled at downstream assessment points RI-04 and RI-05 with alternatives 1A and 1B showing a greater improvement during the swimming season than alternatives 1C and 1D. Improvements of 7 to 12% were modeled when Screening Alternative 2 was applied. The number of days the Screening Alternatives met the fecal coliform standard either did not change or improved 1 to 3 days over the 2020 Baseline condition. Only waters at the upstream assessment point RI-01 and downstream point RI-05 complied with the fecal coliform standard greater than 85% of the time when evaluated for the swimming season.

In general, the Milwaukee River modeled data suggest minimal to no improvement in days of compliance with fecal coliform regulatory standards if all overflows were eliminated, all combined sewers were separated, or I/I was eliminated when compared to 2020 Baseline. A slight improvement occurred when the high level of BMPs (Screening Alternative 2) was applied to the model.

Dissolved Oxygen The mean DO concentrations varied less than 1% from the existing conditions to 2020 Baseline. Comparing the Screening Alternatives to the 2020 Baseline also showed little variance for each assessment point. Water quality for DO was in compliance 98 to 100% of the time under all alternatives.

Total Suspended Solids The mean concentrations of TSS improved approximately 1 to 9% from existing conditions to 2020 Baseline from the upstream assessment point RI-01 to the downstream point RI-05. No change (0%) to 1% improvement in number of days the mean concentration met the guideline was modeled. Water quality at each assessment point achieved the TSS guideline of 100 mg/l at least 98% of the time under 2020 Baseline.

The mean TSS concentrations of Screening Alternatives 1A through 1D did not vary from the 2020 Baseline alternative mean concentration for each assessment point. There was a 7 to 8% improvement in mean TSS concentrations when Screening Alternative 2 was applied to the model. Water at each assessment point achieved the TSS guideline of 100 mg/l at least 98% of the time under all alternatives.

Total Nitrogen The mean concentrations of TN improved 4 to 5% from existing conditions to 2020 Baseline at all assessment points.

The mean TN concentrations did not vary between Screening Alternatives 1A through 1D for each assessment point and did not improve water quality when compared to 2020 Baseline. There was a 1% improvement over 2020 Baseline at all five assessment points when Screening Alternative 2 was applied to the model. There is no compliance standard or planning guideline to which the mean concentration could be compared.


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Total Phosphorus The mean concentrations for TP deteriorated 8 to 3% from upstream to downstream between existing conditions and 2020 Baseline. Water quality for both the existing conditions and 2020 Baseline did not meet the TP guideline 85% of the time.

When comparing the Screening Alternatives to the 2020 Baseline, only Screening Alternative 2 showed an improvement of 3%. Screening Alternatives 1A through 1D showed no improvement. None of the Screening Alternatives improved the water quality enough to comply with the TP guideline 85% of the time or more.

Copper The mean concentrations for copper deteriorated 7 to 1% from upstream to downstream between existing conditions and 2020 Baseline.

The mean copper concentrations did not vary between the Screening Alternatives, and the Screening Alternatives did not vary from 2020 Baseline. There is no compliance standard or planning guideline to which the mean concentration could be compared.

Summary In summary, water quality in the Milwaukee River showed improvements in mean concentrations from existing conditions to 2020 Baseline for fecal coliform, total suspended solids, TN, and TP. Little change was exhibited for mean concentrations of DO and mean copper concentrations increased slightly. Water quality under 2020 Baseline did not meet the fecal coliform standard 85% of the year in the central portion of the Milwaukee River in the MMSD planning area. Also, the water quality did not meet the DO standard at the upper and central section of the watershed and the TP guideline was not met 85% of the year.

When the Screening Alternatives were applied to the model, the water quality met the DO standard and TSS guideline at least 85% of the year, but the fecal coliform standard and TP guideline were not met at least 85% of the year. Overall, little variation in model results occurred between Screening Alternatives 1A through 1D. Screening Alternative 2 showed slight improvement for most parameters in the percent time the standards and guidelines were met.

9A.5.4 Oak Creek Water quality parameters were modeled at seven assessment points located along the mainstem of Oak Creek.q Assessment point OC-01 is the most upstream and is located near the Upper Oak Creek subwatershed outlet. Assessment point OC-02 is located at the North Branch Oak Creek subwatershed outlet. Assessment points OC-03 and OC-04 are located in the central portion of the watershed, and point OC-04 is located on the MMSD planning area boundary where Oak Creek enters South Milwaukee. Assessment points OC-05, OC-06, and OC-07 are located along the Oak Creek mainstem in the Lower Oak Creek subwatershed in South Milwaukee.r

q See Appendix 9B, Figures 9B-1-OC through Figure 9B-8-OC. r See Appendix 9B, Tables 9B-1-OC and 9B-7-OC for a summary of the modeling results for these assessment points.


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Oak Creek and its tributary streams have been categorized as FAL waters by default, because no specific use classification is identified in NR 102.s

Fecal Coliform The modeled water quality for mean fecal coliform counts improved from existing conditions to 2020 Baseline for each assessment point. An improvement of 13 to 20% and 11 to 21% over the existing conditions was modeled for the entire year and swimming season, respectively. None of the modeled waters met the fecal coliform standard 85% of the year for both the existing conditions and 2020 Baseline.

Screening Alternatives 1A through 1D did not show improvement over 2020 Baseline for mean fecal coliform counts. A 10% improvement was modeled when Screening Alternative 2 was applied. None of the modeled waters met the fecal coliform standard >85% of the time under any of the Screening Alternatives.

In general, the Oak Creek modeled data suggest minimal to no improvement in days of compliance with fecal coliform regulatory standards if all overflows were eliminated, or if I/I was eliminated when compared to the 2020 Baseline condition. There are no combined sewer overflow locations in the Oak Creek watershed, so sewer separation does not impact fecal coliform loads or concentrations in Oak Creek. A slight improvement in mean fecal coliform counts occurred when the high level of BMPs (Screening Alternative 2) was applied to the model, but this was not enough to have the waters meet the compliance standard >85% of the year.

Dissolved Oxygen The mean DO concentrations in the upstream and central sections of the river deteriorated 2 to 3% from existing conditions to 2020 Baseline and showed no change in concentration at downstream assessment points OC-05, OC-06, and OC-07. Only the waters in the downstream section of the Oak Creek mainstem within South Milwaukee met the DO standard >85% of the year.

The mean DO concentrations varied less than 1% between the Screening Alternatives over 2020 Baseline for each assessment point.

Total Suspended Solids The mean concentrations of TSS improved approximately 47% from existing conditions to 2020 Baseline for the upstream assessment point OC-01 and between 36 and 38% for points OC-02 downstream to OC-07. All the assessment points improved by about 2 to 3% with regard to the number of days they met the TSS guideline. Water quality for both the existing conditions and the 2020 Baseline alternative met the guideline a minimum 93% of the time.

The mean TSS concentrations of the five Screening Alternatives did not vary from 2020 Baseline for each assessment point. Water quality at each assessment point achieved the TSS guideline of 100 mg/l at least 93% of the time under all of the alternatives.

s See Chapter 6, Section 6.3.3.


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The mean TN concentrations did not vary between Screening Alternatives 1A through 1D for each assessment point, and they did not improve water quality compared to 2020 Baseline. There was a 1 to 2% improvement over 2020 Baseline at all five assessment points when Screening Alternative 2 was applied to the model. There is no compliance standard or planning guideline to which the mean concentration could be compared.

Total Phosphorus The mean concentrations for TP from existing conditions to 2020 Baseline improved approximately 9 to 11% at the assessment points OC-01, OC-02, and OC-03. The mean concentration did not vary from the existing conditions from assessment point OC-04 to point OC-05. The mean concentration then improved 5 to 8% over the existing conditions from assessment point OC-06 downstream to OC-07. Water quality at each assessment point did not meet the TP guideline >85% of the year for both the existing conditions and the 2020 Baseline.

When comparing the Screening Alternatives to 2020 Baseline, only Screening Alternative 2 showed an improvement of 4% in the mean TP concentration for all assessment points. Screening Alternatives 1A through 1D showed no improvement. None of the Screening Alternatives improved the water quality enough to comply with the TP guideline >85% of the time.

Copper The mean concentrations for copper improved 20 to 22% from existing conditions to 2020 Baseline at all assessment points.

The mean copper concentrations for each Screening Alternative did not vary from 2020 Baseline, indicating little difference in these Screening Alternatives in improving water quality. There is no compliance standard or planning guideline to which the mean concentration could be compared.

Summary In summary, water quality in the Oak Creek mainstem showed improvements in mean concentrations from existing conditions to 2020 Baseline for fecal coliform, TSS, TN, TP, and copper. The mean concentrations declined for DO at the upstream section of the river and improved towards the downstream section. Water quality under 2020 Baseline did not meet the standards and guidelines >85% of the year with respect to fecal coliform, DO at the upper and central sections of the creek, and TP.

When the Screening Alternatives were applied to the model, the water quality met the TSS guideline >85% of the year but did not meet the fecal coliform standard, the DO standard, and TP guideline >85% of the year. Overall, little variation in model results occurred between Screening Alternatives 1A through 1D. Screening Alternative 2 showed slight improvement in the percent of time the standards and guidelines were met for most of the parameters.


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9A.5.5 Root River Water quality parameters were modeled at seven assessment points located along the mainstem of the Root River.t There are four assessment points in the Upper Root River subwatershed. Assessment point RR-01 is the most upstream. Assessment points RR-02 and RR-03 are located downstream at the confluences of Hale Creek and Wildcat Creek with the Root River mainstem. Assessment point RR-04 is the most downstream point along the Root River mainstem in the Upper Root River subwatershed. Assessment point RR-05 is located along the Root River mainstem above its confluence with the Ryan Creek, and point RR-06 is located where the Root River first crosses into Racine County and outside the MMSD planning area. Finally, assessment point RR-Mouth represents the most downstream point and is located where the Root River flows into the Lake Michigan Direct Drainage Area.u

The Root River mainstem and many of its tributaries have been categorized as FAL waters by default because no specific use classification is identified in NR 102.v Within the MMSD planning area, two tributary reaches have been categorized as limited forage fish (LFF) waters: Tess Corners Creek and Hales Corners Creek downstream from the former Hales Corners Sewage Treatment Plant. Four reaches within the planning area have been categorized as limited aquatic life (LAL) waters: an unnamed tributary between the former Rawson Homes Sewage Treatment Plant and Root River, Hales Corners Creek upstream of the former Hales Corners Sewage Treatment Plant, diffuse surface drainage from the former New Berlin Memorial Hospital Sewage Treatment Plant to a Root River tributary, and tributary to the Root River downstream from the former New Berlin Memorial Hospital Sewage Treatment Plant.

Fecal Coliform The modeled water quality for the fecal coliform parameter improved from existing conditions to 2020 Baseline at each assessment point. The modeled results showed improvements in mean fecal coliform counts of 13 to 18% for the entire year and 14 and 18% for the swimming season. None of the modeled waters met the fecal coliform standard for existing conditions or 2020 Baseline as none of the modeled data complied with the standard >85% of the time.

Screening Alternatives 1A through 1D did not show improvement over 2020 Baseline for mean fecal coliform counts. Improvements of 10 to 11% were modeled when Screening Alternative 2 was applied. None of the modeled waters met the fecal coliform standard for more than 85% of the year under any of the Screening Alternatives.

In general, the Root River modeled data suggest that minimal to no improvement in days of compliance with the fecal coliform regulatory standards would occur if all overflows were eliminated, or if I/I was eliminated when compared to 2020 Baseline. There are no combined sewer overflow locations in the Root River watershed, so sewer separation does not impact fecal coliform loads or concentrations in the Root River. A slight improvement in mean fecal coliform counts occurred when a high level of BMPs (Screening Alternative 2) was applied to the model, but this was not enough to have the waters meet the compliance standard >85% of the time.

t See Appendix 9B, Figures 9B-1-RR through Figure 9B-8-RR. u See Appendix 9B, Tables 9B-1-RR and 9B-7-RR for a summary of the modeling results for these assessment points. v See Chapter 6, Section 6.3.3.


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Dissolved Oxygen The mean DO concentrations did not change from existing conditions to 2020 Baseline. There was also no change in concentrations between 2020 Baseline and the Screening Alternatives. The water quality for the DO parameter was in compliance with the standard 88 to 99% of the time under all alternatives.

Total Suspended Solids The mean concentrations of TSS improved approximately 22 to 33% from existing conditions to 2020 Baseline. Waters for both the existing conditions and the 2020 Baseline alternative met the guideline a minimum of 89% of the time.

The mean TSS concentrations of Screening Alternatives 1A through 1D did not vary from 2020 Baseline for all assessment points. Screening Alternative 2 showed an improvement of 6% in the mean TSS concentration at downstream assessment points RR-06 and RR-Mouth. Water quality at each assessment point met the TSS guideline of 100 mg/l at least 93% of the time under all alternatives.


The mean TN concentrations did not vary between the Screening Alternatives 1A through 1D for each assessment point, indicating little difference among these Screening Alternatives in improving water quality when compared to 2020 Baseline. When Screening Alternative 2 was applied to the model, there was a 1 to 2% improvement over the 2020 Baseline alternative at all assessment points. There is no compliance standard or planning guideline to which the mean concentration could be compared.

Total Phosphorus The mean concentrations for TP improved approximately 10 to 15% between existing conditions to 2020 Baseline for all assessment points. Water quality at all assessment points except the most upstream point RR-01 did not meet the TP guideline >85% of the year.

When comparing the Screening Alternatives to 2020 Baseline, only Screening Alternative 2 showed an improvement of 4 to 5% in the mean TP concentration for all assessment points. Screening Alternatives 1A through 1D showed no improvement. With the exception of the most upstream assessment point RR-01, none of the Screening Alternatives improved the water quality enough to comply with the TP guideline >85% of the time.

Copper The mean concentrations for copper improved 18 to 23% at all assessment points, except RR-06, from existing conditions to 2020 Baseline. The mean concentration at RR-06 showed a very minute increase.

The mean copper concentrations for each Screening Alternative did not vary from 2020 Baseline, indicating little difference between these Screening Alternatives in improving water quality. There is no compliance standard or planning guideline to which the mean concentration could be compared.


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Summary In summary, water quality in the Root River showed improvements in mean concentrations from existing conditions to 2020 Baseline for fecal coliform, TSS, TN, TP, and copper. There was little variation in mean DO concentrations. Water quality under 2020 Baseline did not meet the fecal coliform standard at all assessment points, and the TP guideline was not met >85% of the year at all assessment points except point RR-01.

When the Screening Alternatives were applied to the model, water quality met the DO standard and TSS guideline >85% of the year. However, the fecal coliform standard and TP guidelines were not met >85% of the year. Overall, little variation in model results occurred between the Screening Alternatives 1A through 1D and 2020 Baseline. Screening Alternative 2 showed slight improvement for most of the parameters in the mean concentration.

9A.5.6 Lake Michigan Direct Drainage Water quality parameters were modeled at twelve assessment points located along the estuary portions of the Kinnickinnic (RI-18), Menomonee (RI-11), and Milwaukee Rivers (RI-06 and RI-08), under the Hoan Bridge (OH-01), the harbor (OH-03, OH-04, OH-07, and OH-11), and Bradford, McKinley, and South Shore beaches.w

Assessment points within the Kinnickinnic, Menomonee, and Milwaukee Rivers and the Hoan Bridge portion of the estuary are categorized as special variance waters. Natural Resources 104.25 requires all Lake Michigan waters to meet the standards for water supplies and the standards for recreational use and fish and aquatic life.x

The U.S. Environmental Protection Agency (USEPA) has promulgated criteria for body contact waters that call for an Escherichia coli (E. coli) geometric mean standard of 126 counts per 100 ml and a single sample maxima ranging from 235 counts per 100 ml to 575 counts per 100 ml, depending on the frequency of use of the recreational waters and in accordance to the federal Beaches Environmental Assessment and Coastal Health (BEACH) Act of 2000.y There has not been a determination as to which maxima would apply at each assessment area of the lake. It would appear that the lower standard would apply at the bathing beaches, and the higher standard would apply in the outer harbor portion of the lake as this area is designated for no swimming by signage around the outer harbor and by the WDNR at the new state park being constructed in the outer harbor.

Note that the BEACH Act refers to an E. coli standard versus the state’s fecal coliform standard required under NR 102 and NR 104. This affects the data evaluation for assessment points in the harbor (OH-03, OH-04, OH-07, and OH-11) and at the Bradford, McKinley, and South Shore beaches.

Fecal Coliform and E. coli This section presents two discussions on resulting water quality with respect to bacteria for the Lake Michigan Direct Drainage Area. This separation of bacteria data is because the rivers are

w See Appendix 9B, Figure 9B-1-DD and Tables 9B-1-DD to 9B-12-DD for a summary of the modeling results for these assessment points. x See Chapter 6, Section 6.3.3. y See Chapter 6, Section 6.3.3.


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regulated under NR 102 and NR 104, which use fecal coliform as the indicator parameter, and the harbor and beaches are regulated by the BEACH Act, which uses E. coli as the indicator parameter. In addition, the water quality model computes only fecal coliform counts. E. coli counts are estimated from the modeled fecal coliform data using a conversion factor of 240 E. coli to 400 fecal coliform, which equals the 0.6 ratio generally accepted by the wastewater treatment community.(2,3) This ratio is further substantiated by research completed by the Great Lakes WATER Institute.(4) Water samples collected for the study were taken from the confluence of the Kinnickinnic, Menomonee, and Milwaukee Rivers, the outer harbor, and Lake Michigan following six CSO events occurring in 2001, 2002, and 2004. Bacteria counts from the samples had a range of 0.3 to 0.7 E. coli to fecal coliform ratio at the river confluence, 0.15 to 0.55 ratio at the outer harbor, and a 0.1 to 0.38 ratio in Lake Michigan. This locally derived data indicates that using the commonly accepted 0.6 ratio is reasonable for estimating E. coli at the river confluence and is conservative when estimating E. coli in the outer harbor and beaches. The data also indicates that E. coli viability significantly decreases as river water flows into the outer harbor and into Lake Michigan.

The resulting modeled water quality of the fecal coliform parameter from existing conditions to 2020 Baseline varied among the assessment points. An improvement in mean fecal coliform counts of 8 to 29% for the entire year and 6 to 26% for the swimming season over the existing conditions was modeled at the Milwaukee River, Menomonee River, and Hoan Bridge (OH-01) estuary assessment points, but their geometric means both increased and decreased. In contrast, mean fecal coliform counts at the Kinnickinnic River estuary point RI-18 degraded 11% for the entire year and 20% for the swimming season from the existing conditions. In the outer harbor, the mean fecal counts for the entire year and swimming season improved 9 to 14% over the existing conditions. The mean counts improved 13 to 15% and 7 to 18% at the beaches for the entire year and swimming season, respectively.

Water quality in the Milwaukee River, and Kinnickinnic River, and Hoan Bridge (OH-01) portion of the estuary met the applicable variance standard >85% of the year under 2020 Baseline. Water quality at the Menomonee River portion of the estuary met the applicable variance standard 65% of the entire year and 87% of the swimming season. Water quality under the 2020 Baseline condition at the outer harbor either did not change or met the not to exceed standard 1 day more compared to the existing conditions. Water quality at Bradford and McKinley Beaches under the 2020 Baseline condition did not meet the not to exceed standard more than the existing conditions. The not to exceed standard at South Shore Beach was met 4 more days than the existing conditions for the entire year and 3 more days than the existing conditions for the swimming season. Water quality in the outer harbor and at the beaches met the state fecal coliform standard 97 to 100% of the time for the entire year and swimming season, respectively. Refer to Tables 9A-15 and 9A-16 for the number of days the fecal coliform counts met the standard for the outer harbor and beaches.


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TABLE 9A-15 EFFECT OF SCREENING ALTERNATIVES IN THE LAKE MICHIGAN OUTER HARBOR AND

BEACHES IN DAYS OF COMPLIANCE WITH THE NOT TO EXCEED 400 COUNTS/100ML STANDARD DURING THE SWIMMING SEASON

Screening Alternative* Assessment

Point

Existing 2020

Baseline 1A 1B 1C 1D 2 OH-03 149 149 151 151 150 150 150 OH-04 152 152 153 153 152 152 152 OH-07 150 150 151 151 150 150 151 OH-11 150 151 152 152 151 151 151 Bradford 153 153 153 153 153 153 153 McKinley 153 153 153 153 153 153 153 South Shore 148 151 153 153 151 151 151 * = the swimming season is 153 days

As illustrated in the above table, elimination of sewer overflows results in only minimal additional days of compliance with applicable water quality standards. Screening Alternative 2 also results in minimal improvement in days that comply with the coliform water quality standard.

The same comparison as above is shown below for data based upon the entire year.

TABLE 9A-16 EFFECT OF SCREENING ALTERNATIVES IN THE LAKE MICHIGAN OUTER HARBOR AND

BEACHES IN DAYS OF COMPLIANCE WITH THE NOT TO EXCEED 400 COUNTS/100ML STANDARD DURING FOR THE ENTIRE YEAR

Screening Alternative*

Assessment Point Existing

2020 Baseline 1A 1B 1C 1D 2

OH-03 352 354 357 357 354 354 356 OH-04 359 361 362 362 361 361 361 OH-07 356 358 360 360 358 358 359 OH-11 356 359 361 361 359 359 360 Bradford 365 365 365 365 365 365 365 McKinley 365 365 365 365 365 365 365 South Shore 355 359 364 364 360 360 361

* = the entire year is 365 days


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This table shows the same conclusions as Table 9A-15, which represents compliance during the swimming season. Overflow elimination or reduction does not result in any significant additional days of compliance with applicable water quality standards.

In general, mean fecal coliform counts in the estuary improved the most over 2020 Baseline with Screening Alternatives 1A and 1B and mean counts showed greater improvement when data was evaluated for the swimming season versus the entire year. Screening Alternatives 1C, 1D, and 2 showed slight improvements in the estuary with the exception of the Kinnickinnic River assessment point RI-18, where Screening Alternatives 1C and 1D had a larger improvement over Screening Alternative 2. Similar patterns were modeled at the outer harbor and beaches. Mean fecal coliform counts improved the most over 2020 Baseline with Screening Alternatives 1A and 1B, and Screening Alternatives 1C, 1D, and 2 showed slight improvements.

Mean E. coli counts were estimated from the modeled mean fecal coliform counts. Because the E. coli counts were estimated using a 0.6 E. coli-to-fecal coliform ratio for each alternative, the same trends described above for fecal coliform would apply.

Even though the mean fecal counts improved, the Screening Alternatives showed only slight improvements over 2020 Baseline in the number of days they complied with the coliform standards, as shown in the summary tables above. Screening Alternatives 1C and 1D did not improve the 2020 Baseline condition. Modeled waters in the Milwaukee and Kinnickinnic River portion of the estuary met the fecal coliform standard >85% of the time when evaluated for the entire year and the swimming season. Waters in the Menomonee River portion of the estuary met the fecal coliform standard at least 85% of the swimming season.

Even though the outer harbor and beaches are not regulated by the state, they were analyzed against fecal coliform standards for comparison purposes. A similar trend in days met was modeled among the Screening Alternatives compared to the 2020 Baseline. Water quality at the outer harbor and beaches met the fecal coliform standard >85% of the time when evaluated for the entire year and swimming season. The data showed that the outer harbor and beaches are in compliance with respect to fecal coliform 97 to 100% of the swimming season for the existing conditions, which suggests that beach water quality and resulting closings are an outcome from sources in the areas of the beaches and not water originating from the riverine watersheds.(5)

The water quality model does not determine the number of days in a year that E. coli counts met the BEACH Act standard, but if the 0.6 ratio is a direct translation for all modeled conditions, then compliance shown with the 200 counts per 100ml and 400 counts per 100ml fecal coliform standards would be the same with respect to E. coli under the BEACH Act.

In general, the modeled data suggest that a slight improvement in days of compliance with fecal coliform regulatory standards would occur if all overflows were eliminated with and without all combined sewers separated (Screening Alternative 1A and 1B), or a high level of BMPs were implemented (Screening Alternative 2) when compared to the 2020 Baseline. Ending all SSOs (Screening Alternative 1C) and eliminating I/I (Screening Alternative 1D) did not improve upon the 2020 Baseline.

Dissolved Oxygen The mean DO concentrations showed no change or improved up to 2% from the existing conditions to 2020 Baseline and showed no change or improved up to 2% between the Screening


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Alternatives and the 2020 Baseline for each assessment point. Water quality for DO was in compliance with the standard 99 to 100% of the time under any of the alternatives.

Total Suspended Solids The mean concentrations of TSS improved approximately 4 to 10% from existing conditions to 2020 Baseline in the estuary, 3% in the outer harbor, 1% at Bradford and McKinley Beaches, and 4 percent at South Shore Beach. Water quality for both the existing conditions and 2020 Baseline in the estuary, outer harbor, and beaches met the TSS guideline at least 98% of the year.

When comparing the Screening Alternatives to 2020 Baseline, only Screening Alternative 2 showed an improvement of 4 to 7% in the mean TSS concentration for the estuary, a 4 to 5% improvement in the outer harbor, and a 2 to 3% improvement at the beaches. Screening Alternatives 1A through 1D showed between a 1% increase to a 1% decrease in mean TSS concentrations in the estuary and showed a 1 to 2% decrease in mean concentrations from the 2020 Baseline alternative in the outer harbor and beaches. Water quality under all Screening Alternatives met the TSS guideline >85% of the year in the estuary, outer harbor, and beaches.

Total Nitrogen The mean concentrations of TN improved 12% at the Menomonee River estuary assessment point RI-11 from existing conditions to 2020 Baseline and improved 4 to 6% at the other estuary points. The mean concentrations either did not change or improved up to 2% in the outer harbor and beach areas.

Except at the upper Milwaukee River estuary assessment point RI-06, mean TN concentrations for all Screening Alternatives showed improvement at all other estuary points, the outer harbor, and the beaches. At assessment point RI-06, mean TN concentrations did not change between Screening Alternatives 1A through 1D over the 2020 Baseline and showed a 1% improvement with Screening Alternative 2. The lower Milwaukee River point RI-08 and the Kinnickinnic and Menomonee River portions of the estuary improved 1 to 8% for all Screening Alternatives. Water quality at the Hoan Bridge (OH-01) improved 14 to 15%, improved 23 to 28% in the outer harbor, and improved 10 to 20% at the beaches. There is no compliance standard or planning guideline to which the mean concentration could be compared.

Total Phosphorus The mean concentrations for TP showed between a 1% increase to a 1% decrease in concentration from existing conditions to 2020 Baseline in the estuary and showed either no change or up to 1% increase in concentration in the outer harbor and beaches. Only water at the Milwaukee River estuary assessment point RI-06 did not meet the TP guideline >85% of the year for both the existing conditions and 2020 Baseline.

When comparing the Screening Alternatives to 2020 Baseline, mean TP concentrations either did not change or improved up to 7% in the estuary, improved between 9 and 13% in the outer harbor, and improved between 4 to 7% at the beaches. With the exception of the Milwaukee River estuary assessment point RI-06, water quality at the other estuary, outer harbor, and beach assessment points met the TP guideline >85% of the year.


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Copper The mean concentrations for copper did not change or improved 3 to 4% from existing conditions to the 2020 Baseline in the estuary except at the Milwaukee River estuary assessment point RI-06, where the mean concentration worsened by 1%. Mean copper concentrations at the outer harbor and beaches either did not changed or improved by 1%.

The mean copper concentrations for the Screening Alternatives did not vary from 2020 Baseline model more than 2%, indicating little difference between these Screening Alternatives in improving water quality. There is no compliance standard or planning guideline to which the mean concentration could be compared.

Summary In summary, water quality in the Lake Michigan Direct Drainage Area under the 2020 Baseline was considered impaired with respect to fecal coliform for the entire year at the Menomonee River portion of the estuary. Water quality at the Milwaukee, Kinnickinnic, and Hoan Bridge portions of the estuary, outer harbor, and beaches were not considered impaired with respect to fecal coliform, DO, and TSS. Only at the Milwaukee River estuary assessment point RI-06 was water quality considered impaired with respect to TP.

Water quality was not considered impaired with respect to fecal coliform during the swimming season, DO, and TSS at the estuary, outer harbor, and beaches when the Screening Alternatives were applied to the model. Only at the Milwaukee River estuary assessment point RI-06 was water quality considered impaired with respect to TP When fecal coliform was evaluated for the entire year, water quality at the Menomonee River estuary assessment point RI-11 was considered impaired, and water quality at the other four estuary points was not considered impaired. Overall, the Screening Alternatives showed improvements in decreasing mean fecal coliform concentrations over the 2020 Baseline, and showed slight improvements when the data was evaluated for the percent of time that the fecal coliform standard was met. The modeled data indicates that Screening Alternatives 1A and 1B were effective in lowering the mean fecal coliform concentration but had little effect on the other parameters. Screening Alternative 2 showed slight improvement for most of the parameters. Screening Alternatives 1C and 1D had a nominal effect on all the parameters.

9A.5.7 Screening Alternatives Water Quality Summary The implementation of Screening Alternatives that concentrate solely on CSO and SSO elimination produced very little water quality improvement. The Screening Alternative that involves widespread implementation of nonpoint stormwater controls, Screening Alternative 2, shows some promise in terms of water quality improvement although it also falls short of any significant water quality improvement in terms of meeting water quality standards at all times.

9A.6 Evaluation Matrix Analysis To allow for comparison of the Screening Alternatives, an evaluation matrix was created. The matrix was based on a scoring system that awarded points for the number of days an alternative met water quality standards or guidelines. The water quality scoring was based upon “endpoints” that represent achievement of one of the goals and objectives discussed in Chapter 7,


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System Plan Goals and Objectives of this report. The rationale for using the number of days meeting a standard or guideline as an “endpoint” is discussed in detail in Chapter 7 and in Section 9.1 through 9.3 of Chapter 9, Alternative Analysis. This section contains all the details regarding all of the evaluations made in this appendix.

9A.6.1 Explanation of Absolute Scoring The following endpoints were scored using model results (water quality endpoints):

♦ Days Meeting Fecal Coliform not to exceed Standard in the swimming season (May-September)

♦ Days Meeting Fecal Coliform Geometric Mean Standard in the swimming season (May-September)

♦ Days Meeting Fecal Coliform Geometric Mean Standard (Year-Round)

♦ Days Meeting Fecal Coliform Not to Exceed Standard (Year-Round)

♦ Days Meeting TSS Guideline

♦ Days Meeting DO Standard

♦ TN Load relative to Existing Conditions

♦ TP Load relative to Existing Conditions

The endpoints were scored based on the number of days that met the standard or guideline (for all water quality endpoints except for TN and TP). If an alternative reached 100% compliance with water quality standards (fecal coliform and dissolved oxygen) and 100% compliance with planning guidelines (for TSS and TP), the alternative would receive the maximum score of 10 points. Otherwise, it would receive a lower score from 0 to 9 points depending on the percent of days that it reached compliance with the standard or guideline. For example, if an alternative was compliant between 30 and 39% of the time, then it would receive a score of 3 points, and if it was compliant between 50 and 59% of the time, it would receive a score of 5 points. Total load of phosphorous and nitrogen was also evaluated using the same type of scale. The scores were evenly distributed along the range of possible days as shown in Table 9A-17.

The TN and TP loads were scored based on the modeled deviation from modeled existing loads. The existing load in each watershed received a score of 6 points. The remaining scores (1-5 and 7-10) were distributed evenly above and below the existing load, as shown in Table 9A-18.

Each watershed outlet, estuary, and beach location was scored separately for each water quality endpoint. Then, the scores were averaged to arrive at a score for each endpoint and an overall water quality (WQ) score for each alternative.

In a second method used to evaluate Screening Alternatives, subjective endpoints were developed based upon the subjective publicly inspired goals and objectives.


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TABLE 9A-17

EVALUATION MATRIX SCORING SYSTEM OF DAYS MEETING STANDARD OR GUIDELINE

Percent Days Meeting Standard Score

0-9 010-19 120-29 230-39 340-49 450-59 560-69 670-79 780-89 890-99 9100 10

TABLE 9A-18 EVALUATION MATRIX SCORING SYSTEM FOR TOTAL NITROGEN

AND TOTAL PHOSPHORUS LOADS

Percent of Existing Load Score <39 10

40-59 9 60-79 8 80-99 7

100-116 6 117-132 5 133-149 4 150-166 3 167-182 2 183-199 1

200 0

The subjective endpoints were scored separately from the water quality endpoints. The following endpoints were scored using subjective methods:

♦ Percent increase in area of preserved natural areas from existing

♦ Number of miles of rehabilitated channel


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♦ Percent of watershed in preserved tree canopy (more points given if connectivity is addressed)

♦ Increase in miles of preserved riparian buffer

♦ Percent reduction of visible trash and floatables from existing conditions

♦ Environmental Justice

♦ Costs

Each alternative was given a high (10 points), medium (5 points), or low (0 points) based on the degree to which the alternative was assumed to meet the subjective endpoint. For example, if alternative proposed to substantially increase the amount of preserved natural areas, then that alternative would receive a high score (10 points). Table 9A-19 lists the scores and corresponding symbols used for the subjective scoring.

TABLE 9A-19 SUBJECTIVE SCORING CATEGORIES

Level of Success/Feasibility Score

High 10Medium 5Low 0

The above scores were related back to the stakeholder matrix and weighted according to the “committee weights.” (Weighting exercises were conducted with the various stakeholder groups, as explained in Chapter 7, as a means of prioritizing stakeholder interests as part of the public involvement process).

Where the stakeholder matrix specified estuary/beach locations for an endpoint, only the estuary/beach scores were used and vice versa for the river locations. When a location was not specified, the average of river, estuary, and beach scores was applied. The TN and TP scores were averaged to apply to the combined TN and TP endpoint in the stakeholder matrix. The 10-point scores were multiplied by the committee weights and summed to calculate scores for each endpoint in the stakeholder matrix.

These scores were then computed for all of the Screening Alternatives and the results are compared in the tables in this section. First, Table 9A-20 shows the raw scores for water quality.

The raw scores were then normalized on a 10 point basis as shown in Table 9A-21.

The water quality scores of the various Screening Alternatives were very similar. This is due to the outcome basis (endpoint) of the scoring – how many days per year the alternative meets water quality standards or guidelines. The detailed data show that the implementation of the Screening Alternatives does not significantly increase the days of compliance with water quality standards and guidelines.z

z See Appendix 9B, Modeled WQ Data – Screening Alternatives.


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TABLE 9A-20 RAW WATERSHED SCORES – STUDY AREA-WIDE SCORE

Endpoint Existing 2020

Baseline Alt 1A Alt 1B Alt 1C Alt 1D Alt 2

Fecal Coliform Geometric Mean Standard (May-Sept.) 120 123 128 127 125 125 124Fecal Coliform Geometric Mean Standard (Year-Round) 101 103 108 108 104 104 106Fecal Coliform Not to Exceed Standard 120 120 122 122 120 120 121Total Suspended Solids Guideline 44 45 45 45 45 45 45Dissolved Oxygen Guideline 47 47 47 47 47 47 47Total Nitrogen Load 30 37 37 37 37 37 37Total Phosphorus Load 30 36 36 37 36 36 36

TABLE 9A-21 SUMS OF WATERSHED SCORES -- STUDY AREA WIDE SCORE, NORMALIZED TO 10-POINT

SCALE

Endpoint Existing 2020 Baseline

Alt 1A Alt 1B Alt 1C Alt 1D Alt 2

Fecal Coliform Geometric Mean Standard (May-Sept.) 8.0 8.2 8.5 8.5 8.3 8.3 8.3Fecal Coliform Geometric Mean Standard (Year-Round) 6.7 6.9 7.2 7.2 6.9 6.9 7.1Fecal Coliform Not to Exceed Standard 8.0 8.0 8.1 8.1 8.0 8.0 8.1Total Suspended Solids 8.8 9.0 9.0 9.0 9.0 9.0 9.0Dissolved Oxygen 9.4 9.4 9.4 9.4 9.4 9.4 9.4Total Nitrogen Load 6.0 7.4 7.4 7.4 7.4 7.4 7.4Total Phosphorus Load 6.0 7.2 7.2 7.4 7.2 7.2 7.2Water Quality Aggregated Score for Alternative 7.6 8.0 8.1 8.1 8.0 8.0 8.1

9A.6.2 Subjective Goals The matrix evaluation also included an assessment of the subjective endpoints. As shown in Table 9A-22, the Screening Alternatives scored very poorly with respect to the subjective measures except for Screening Alternative 2. This is because the Screening Alternatives were not developed based on the goals and objectives described in Chapter 7 of this report. The rationale for the scoring of the subjective goals can be found in Section 9.1 through 9.3 of


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Chapter 9, Alternative Analysis. This section contains all the details regarding all of the evaluations made in this appendix.

TABLE 9A-22

SCORING OF SUBJECTIVE GOALS

Endpoint Existing2020

Baseline Alt 1A Alt 1B Alt 1C Alt 1D Alt 2 Percent increase in area of preserved natural areas from existing. 0 0 0 0 0 0 10 Number of miles of rehabilitated channel 0 0 0 0 0 0 0 Percent of watershed in preserved tree canopy (give more points if addresses connectivity) 0 0 0 0 0 0 10 Increase in miles of preserved riparian buffer 0 0 0 0 0 0 0 Percent reduction of visible trash and floatables from existing conditions 0 0 0 0 0 0 10 Environmental Justice 10 10 0 10 10 10 10 Cost 10 10 2.5 2.4 5.5 2.0 5.7 Total Score 20 20 2.5 12.4 15.5 12.0 45.7 Total Possible Score 70 70 70 70 70 70 70 Normalized to 10 Point Scale 2.9 2.9 0.4 1.8 2.2 1.7 6.5

9A.6.3 Total Scores

As a final comparative tool, a combined score was developed to address both the water quality and subjective goals as measured by the endpoints as noted in Chapter 7. The combined total of normalized WQ and subjective scores is shown below in Table 9A-23.


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TABLE 9A-23

WATER QUALITY AND SUBJECTIVE SCORING COMBINED

Endpoint Existing 2020 Baseline

Alt 1A Alt 1B Alt 1C Alt 1D Alt 2

Water Quality Scores Fecal Coliform Geometric Mean Standard (May-Sept.) 8.0 8.2 8.5 8.5 8.3 8.3 8.3Fecal Coliform Geometric Mean Standard (Year-Round) 6.7 6.9 7.2 7.2 6.9 6.9 7.1Fecal Coliform Not to Exceed Standard 8.0 8.0 8.1 8.1 8.0 8.0 8.1Total Suspended Solids 8.8 9.0 9.0 9.0 9.0 9.0 9.0Dissolved Oxygen 9.4 9.4 9.4 9.4 9.4 9.4 9.4Total Nitrogen Load 6.0 7.4 7.4 7.4 7.4 7.4 7.4Total Phosphorus Load 6.0 7.2 7.2 7.4 7.2 7.2 7.2

Subjective Scores Percent increase in area of preserved natural areas from existing. 0.0 0.0 0.0 0.0 0.0 0.0 10.0Number of miles of rehabilitated channel 0.0 0.0 0.0 0.0 0.0 0.0 0.0Percent of watershed in preserved tree canopy 0.0 0.0 0.0 0.0 0.0 0.0 10.0Increase in miles of preserved riparian buffer 0.0 0.0 0.0 0.0 0.0 0.0 0.0Percent reduction of visible trash and floatables from existing conditions 0.0 0.0 0.0 0.0 0.0 0.0 10.0Environmental Justice 10.0 10.0 0.0 10.0 10.0 10.0 10.0Cost Factor 10.0 10.0 2.5 2.4 5.5 2.0 5.7Total Water Quality and Subjective Aggregate Score 5.2 5.4 4.2 5.0 5.1 4.9 7.3

The Screening Alternatives were based on community questions and solutions to the perceived or preconceived solutions to the region’s water quality problems. They were not based on stakeholder input and rational evaluation of which technologies would produce the best results based upon a cost benefit analysis considering both stakeholder input and regulatory constraints. Thus, the next stage of alternative development shifted to the preliminary alternatives as detailed in Chapter 9, Alternative Analysis, Sections 9.4 and 9.5. It is worth noting, however, that Screening Alternative 2 achieved the highest score among the Screening Alternatives.


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9A.6.4 Relative Water Quality Scoring The process developed above did not show much difference between the Screening Alternatives because it relied upon “absolute” measures (how many days does the alternative meet water quality standards). While this is an excellent way to evaluate meeting the goal of attaining water quality standards, it does not offer any information on which Screening Alternatives are more effective at improving water quality. Thus, a “relative” assessment method was developed to show the relative improvement in water quality for each Screening Alternative. The rationale for the relative water quality scoring can be found in Section 9.1 through 9.3 of Chapter 9, Alternative Analysis. This section contains all the details regarding all of the evaluations made in this appendix.

The relative WQ score is shown in Table 9A-24. The normalized and subjective scoring methods did not differentiate between Screening Alternatives very well because compliance for all the Screening Alternatives usually fell within a narrow range of days. For example, all of the Screening Alternatives complied with the TSS standard for more than 292 days, so none received a score lower than 8 points.

To provide more informative scoring, the scoring methods needed to use the entire range from 0 to 10 points. Thus, a second scoring method was developed, which was based on a relative improvement of water quality between the Screening Alternatives. It was based upon the following:

♦ The Screening Alternative with the worst water quality should receive the lowest possible score of 0 points and the Screening Alternative with the best water quality should receive the highest possible score of 10 points.

♦ To provide better differentiation among the scores, the following changes were made to the scoring methods:

1) Use long term arithmetic mean (versus geomean) concentration for all water quality endpoints

2) Use one endpoint for each water quality parameter so that each parameter (fecal coliform, DO, TSS, TN, or TP) is given equal weight

3) Include all modeling locations

4) Score the Screening Alternatives based on the statistical quartiles for each location

This revised scoring method yields the results in Tables 9A-24 and 9A-25.

As shown in the evaluation in Table 9A-24, Screening Alternative 2 scored the highest of all the Screening Alternatives. The results above can be disaggregated to show differences at specific locations as shown in Table 9A-25.


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TABLE 9A-24

STUDY AREA-WIDE SCORE, NORMALIZED TO 10-POINT SCALE QUARTILES METHOD SCORES BASED ON RIVER, ESTUARY, AND BEACH LOCATIONS

Endpoint Existing 2020


Fecal Coliform 0.5 2.8 6.9 7.1 5.0 5.0 8.5

Total Suspended Solids 0.0 8.3 8.2 8.3 8.3 8.3 10.0

Dissolved Oxygen 9.6 10.0 10.0 10.0 10.0 10.0 10.0

Total Nitrogen 0.0 5.0 5.3 5.4 5.4 5.4 10.0

Total Phosphorus 4.2 6.0 6.5 6.0 6.0 6.0 9.2

WQ Aggregated Score for Alternative 2.9 6.4 7.4 7.4 7.0 7.0 9.5


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TABLE 9A-25

SUMMARY BY WATERSHEDS ACROSS ALL PARAMETERS (NORMALIZED TO 10-POINT SCALE)

Watershed Existing 2020


Oak Creek 2.6 7.1 7.3 7.3 7.3 7.3 10.0

Menomonee River 3.6 6.2 7.0 7.2 6.8 6.8 10.0

Milwaukee River 4.0 4.3 5.2 4.8 4.7 4.7 8.7

Kinnickinnic River 3.0 7.0 9.5 9.5 8.5 8.5 9.3

Root River 2.0 6.9 7.3 7.3 7.3 7.3 10.0

Milwaukee River (Estuary)1 0.0 2.5 7.5 7.5 5.0 5.0 10.0

Kinnickinnic River (Estuary)1 5.0 0.0 10.0 10.0 5.0 5.0 2.5

Hoan Bridge (OH-01)1 0.0 2.5 10.0 10.0 5.0 5.0 7.5

Bradford Beach1 0.0 5.0 10.0 10.0 5.0 5.0 5.0

McKinley Beach1 0.0 5.0 10.0 10.0 5.0 5.0 5.0

South Shore Beach1 0.0 2.5 10.0 10.0 5.0 5.0 7.5

North Harbor (OH-04) 0.0 2.5 10.0 10.0 5.0 5.0 5.0

Middle Harbor (OH-03) 0.0 0.0 10.0 10.0 5.0 5.0 5.0

Main Gap (OH-07) 2.5 0.0 10.0 10.0 5.0 5.0 5.0

South Harbor (OH-11) 0.0 0.0 10.0 10.0 5.0 5.0 5.0

1) Scored by Fecal Coliform endpoint only.

The relative scoring method was better at distinguishing between the Screening Alternatives. As shown in the data, Screening Alterative 2 accomplishes more water quality improvement in the watersheds than any of the other Screening Alternatives. In the Lake/Estuary area, Screening Alternatives 1A and 1B show the most improvement, but it is important to note that many of the areas in the Lake/Estuary are already meeting applicable water quality standards.


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References (1) CH2M Hill, Technology Evaluation and Preliminary Engineering for High-Rate

Treatment of Wet-Weather Flows (Draft Report 2006; Contract Number M03022P01)

(2) Patrick P. Rasmussen and Andrew C. Ziegler, Comparison and Continuous Estimates of Fecal Coliform and Escherichia Coli Bacteria in Selected Kansas Streams, May 1999 Through April 2002 (2002)

(3) D.S. Fisher and A.L. Dillard, Distributions of E. Coli and Enterococci in the Surface Waters of the Upper Oconee Watershed of Georgia (2003) p. 119-123 In: Proceedings of 2nd Conference on Watershed Management to Meet Emerging Environmental Regulations (ASAE, Albuquerque, NM)

(4) Sandra L. McLellan, Sources of E. coli at South Shore Beach Final Research Report (Great Lakes WATER Institute, 2004)

(5) D.S. Fisher and A.L. Dillard, Distributions of E. Coli and Enterococci in the Surface Waters of the Upper Oconee Watershed of Georgia (2003)

appendix 9a screening alternatives · 9a-5 summary of alternative 1 elements and approximate costs...

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