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PCSWMM/EPA SWMM5 MODEL REPORT

JULY 2011

WAUKEGAN RIVER, ILLINOIS

SECTION 516(e) WRDA 1996

GREAT LAKES TRIBUTARY MODELING

SWMM MODEL REPORT

U.S Army Corps of Engineers i Section 516(e) Waukegan River Chicago District SWMM Model Report

SWMM Model Report

Waukegan River Section 516(e)

July 2011

TABLE OF CONTENTS 1.0 INTRODUCTION ........................................................................................................... 1

2.0 PROJECT DESCRIPTION ................................................................................................ 1

3.0 MODEL DEVELOPMENT ................................................................................................. 2

3.1 Models and Software Used ......................................................................................... 2

3.2 Precipitation and Climatological Data .......................................................................... 2

3.3 Lake Michigan Stage .................................................................................................. 4

3.4 Geometric Data ......................................................................................................... 4

3.5 Subcatchment Delineation.......................................................................................... 5

3.6 Soil and Infiltration Parameters .................................................................................. 6

3.7 Other Subcatchment Characteristics ............................................................................ 6

3.8 Water Quality and Land Use ....................................................................................... 7

3.9 Routing Methodology ................................................................................................. 7

4.0 MODEL CALIBRATION AND VERIFICATION ..................................................................... 7

4.1 Calibration Data ........................................................................................................ 8

4.2 Baseflow .................................................................................................................. 8

4.3 Rainfall Derived Inflow and Infiltration (RDII) .............................................................. 8

4.4 Parameter Calibration ................................................................................................ 8

4.5 Calibration Results..................................................................................................... 9

4.6 Model Verification .....................................................................................................10

4.7 Water Quality Runoff Calibration................................................................................12

5.0 LOW IMPACT DEVELOPMENT (LID) SCENARIO ..............................................................13

6.0 MODEL CAPABILITES AND LIMITATIONS ......................................................................14

7.0 REFERENCES ..............................................................................................................16

U.S Army Corps of Engineers ii Section 516(e) Waukegan River Chicago District SWMM Model Report

List of Tables

Table 1. Event Mean Concentrations .................................................................................... 7

Table 2. Unit Hydrographs for RDII ..................................................................................... 8

Table 3. 2008 Calibration Results .......................................................................................10

Table 4. 2009 Verification Results .......................................................................................11

Table 5. TSS Results .........................................................................................................12

List of Figures

Figure 1. Waukegan River Watershed .................................................................................. 3

Figure 2. 2008 Thiessen Precipitation Record ........................................................................ 4

Figure 3. Flow Measurements for 2008 LID Scenario ............................................................13

Figure 4. TSS Measurements for 2008 LID Scenario .............................................................13

List of Plates

Plates 1-4. 2008 Model Results and Measured Gage Data at QC-04 Gage Location




Plates 17-20. 2008 Model Results and Measured Gage Data at QCA-01 Gage Location





Plates 33-35. 2009 Model Results and Measured Gage Data at QCA-01 Gage Location

U.S Army Corps of Engineers 1 Section 516(e) Waukegan River Chicago District SWMM Model Report

1.0 INTRODUCTION

This report documents the development of an EPA SWMM5 Model for the Waukegan River watershed. The U.S. Army Corps of Engineers (USACE) developed the Waukegan River Scoping Report in November 2008 that presented the intent to develop a SWMM model to study sediment delivery and transport in the Waukegan River. Section 516(e) of the Water Resources Development Act of 1996 gives authority to USACE to develop sediment transport models for tributaries to the Great Lakes that discharge to Federal navigation channels or Areas of Concern (AOCs). Waukegan Harbor is located 1,000 feet north of the mouth of the river at Lake Michigan and sediment from the Waukegan River affects this Federal navigation channel and harbor. Waukegan Harbor is also a designated AOC and exhibits five of the 14 beneficial use impairments [http://www.epa.gov/glnpo/aoc/waukegan.html]. The goal of the development of this model is to provide the local community a tool they can use to help reduce soil erosion, sedimentation, and pollutant loadings to the Great Lakes resulting in reduced costs of navigation maintenance and the need for sediment remediation. Included in this report is an explanation of model development, calibration, and capabilities and limitations. Further information including technical references, scoping report, and contact information to obtain modeling files can be found at the project website [http://glc.org/tributary/models/waukegan.html]

2.0 PROJECT DESCRIPTION

The Waukegan River watershed is located in the Northeastern portion of Lake County, Illinois approximately 35 miles north of Chicago along Lake Michigan. It drains almost 12 square miles of land that include much of the City of Waukegan and portions of the Village of Beach Park, City of North Chicago and unincorporated Lake County (Figure 1). The Waukegan River watershed empties into Lake Michigan within the City of Waukegan, just south of the Waukegan Harbor. The watershed area was developed from the historical marshes, ravines, and forests that used to cover the region to the industrialized and urbanized city seen today. The area’s urban history has left an indelible mark on the watershed. For instance, previous data indicates many portions of the Waukegan River have sediments contaminated from previous industry. Urbanization and its increases in impervious areas have changed the natural flow regime. Runoff drains quicker from the landscape making the watershed a flashy system that continues to deliver pollutants to the receiving waters. Dumping and intended or unintended illicit discharges continue to occur and pollute the river. The Waukegan River and the South Branch Waukegan River are included on the IEPA’s 2008 303(d) list of impaired waters and does not meet state water quality standards. The Section 516(e) Great Lakes Tributary Modeling Scoping Report for the Waukegan River watershed (USACE 2008) evaluated various modeling solutions for the Waukegan River watershed and selected EPA SWMM5 and HEC-RAS as appropriate models to simulate the hydrologic response and sediment delivery to the Waukegan River. EPA SWMM5 combines hydrologic and hydraulic capabilities into a single model that is capable of continuously simulating hydrologic runoff. EPA SWMM5 has particularly strong capabilities at modeling complex sewer networks so it is useful for urban areas that use storm sewers like those found in the Waukegan River watershed. EPA SWMM5 can model diverse hydraulic networks that

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include closed conduits and open channels as well as sediment runoff from overland flow so it is a useful comprehensive model for this study. The scoping report identified HEC-RAS 4.0 as a model to study sediment deposition and transport in the Waukegan River. This model was not completed as a part of this study because adequate data was not available, particularly detailed grain size of the banks, bed, and overflows.

3.0 MODEL DEVELOPMENT

This section documents the development of the EPA SWMM5 model using PCSWMM. All data and methods employed to develop the models are discussed here.

3.1 Models and Software Used The EPA SWMM5 model was developed using PCSWMM 2011 Standard which is a proprietary platform developed by Computational Hydraulics, Inc. (CHI) in Guelph, Ontario. PCSWMM is a GIS interface for EPA SWMM5. It has features to import ESRI format GIS shapefiles and adds capabilities for reviewing and analyzing model output, however it does not offer any additional technical capabilities beyond the capabilities of EPA SWMM5. PCSWMM uses the EPA SWMM 5.0 engine and has the ability to run the model using various versions of the SWMM 5.0 engine. The latest SWMM version, version 5.21, was used for all modeling scenarios performed as a part of this study. The hydrology in EPA SWMM5 is similar to other hydrologic models. The watershed is divided into smaller subcatchments and the runoff potential for each subcatchment is characterized by various parameters including percent impervious, various infiltration methodologies, land uses, etc. The hydraulic network is specified using a system of nodes and conduits. Elevations are specified in the nodes and dimensions are specified in the conduits.

3.2 Precipitation and Climatological Data The EPA SWMM5 climatology editor uses temperature, monthly wind speed, snow melt, and areal depletion data to support runoff computation. Climatological data was taken from the weather station maintained by the FAA at the Waukegan Airport located at the northern end of the Waukegan River basin. Precipitation data used for model calibration and verification was taken from three gages that were maintained during the model calibration and verification periods. One gage is the aforementioned gage at the Waukegan airport; the other two are gages maintained by the Lake County Stormwater Management Commission (SMC) and a temporary gage maintained by the Lake County Health Department at the lakefront (Figure 1). The precipitation records were analyzed and compared and the Thiessen polygon method was used to weigh the gages and develop a single hourly gage record for use with the model (Figure 2). For the mid-May 2008 through mid-October 2008 period of record used for calibration the total precipitation for the gages was 11.65 inches (Lakefront), 10.52 inches (SMC), and 11.39 inches (FAA). The Thiessen method produced a total precipitation of 10.95 inches.


Figure 1. Waukegan River Watershed show ing subcatchments (red), flow gages (yellow ), and precipitation gages (green)


Figure 2. 2008 Precipitation record computed using Thiessen polygon method.

3.3 Lake Michigan Stage The downstream boundary condition used for the model was the Lake Michigan stage. Hourly data was taken from the NOAA gages at Milwaukee and Calumet Harbors, which was obtained from the online National Climatic Data Center maintained by NOAA. Waukegan lies approximately equidistant from the gage at Milwaukee Harbor and Calumet Harbor so the hourly records of these two gages were averaged and this was used as the downstream boundary condition for the model

3.4 Geometric Data Geometric data from multiple sources was used to develop the EPA SWMM5 geometry. Data that constitutes the geometric data includes the locations, dimensions, and elevations of sewer lines; cross sections of open channels; storage area depths and dimensions; and locations and dimensions of weirs and other hydraulic structures. The geometric data in the model is all in the NAVD88 datum. The City of Waukegan maintains a database of plans and GIS data that was used as a basis for the SWMM model geometry. This database includes maps of their storm sewer network, which has details of the dimensions, elevations, and location of all conduits and manholes. The City also has records of some culvert dimensions and details on the areas of storage ponds (though not the inverts). The database maintained by the City was adequate to develop a first phase of the model however there were data gaps that made developing a fully detailed model

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impossible. Elevation data was not available for the main channel and there was some confusion regarding the datum used for the sewer network plans. To rectify this situation the USACE contracted to develop a detailed survey and fill in the data gaps. The most important missing data were surveyed cross sections of the main channel. Also collected were elevations of key sewer arteries; invert elevations of outfalls; and measurements and dimensions of key culverts and hydraulic control structures (such as the weirs that control flow through the Bonnie Brook golf course). This survey was completed in the Spring of 2010. A detailed survey of portions of the Waukegan River North Branch between Jackson and Washington Streets was completed by the City of Waukegan in 2005. This work was performed for an erosion control project and the Contractor for the work as indicated on the drawings was Biotechnical Erosion Control, Ltd. This data was used to develop EPA SWMM 5 model cross sections for this portion of the Waukegan River. Surveys of the Waukegan River main channel were also completed by the City of Waukegan and documented in plans developed by McClure Engineering Associates, Inc in 2008. This survey data was incorporated into a HEC-RAS model by Arcadis. PCSWMM has the capability to import HEC-RAS geometry into the EPA SWMM5 environment. PCSWMM was able to import the channel cross sections and elevations; conduit dimensions, length, and elevations; and road overpass elevations. Both of these regions of the Waukegan River that were surveyed by the City of Waukegan were not part of the survey contracted by USACE, Chicago District. A wealth of data was available for model development, however some assumptions were still necessary to complete the model geometry. Inverts of the storage areas were not available so these values had to be assumed. These storage areas generated considerable instability in the model on initial runs so they were removed and replaced with cross sections. Because inverts of the storage areas were not available the inverts of the cross section had to be assumed. Storage areas were assumed to range in depth from 4-7 feet based on past experience with suburban stormwater basins. For the sewer network, a conversion factor was necessary to convert the inverts in the City’s database to NAVD88. The USACE survey was used to correlate to the City’s database and develop a conversion factor. There were some inconsistencies that were observed when making this comparison but a single value was arrived at that appeared to be the most reasonable. A value of 580.2 feet was established as a factor to add to the City’s sewer data base to convert these inverts to NAVD88. Even with this conversion factor established there were a number of nodes both in the main channel and the sewer network where invert data was not available. For these nodes it was necessary to linear interpolate between the known points.

3.5 Subcatchment Delineation Sewersheds or subcatchments for the Waukegan River watershed were originally developed by Kabbes and Geosyntec Engineering and documented in their watershed management plan (Kabbes 2008). These subcatchment boundaries were re-evaluated and subdivided into smaller units using the GIS database of the storm sewer system assembled by the city; a digital elevation model created from 10 foot LIDAR data; and the new survey data collected by the USACE. The model attempted to capture and model most conduits greater than 15 inches in diameter. This required further discretization of the original Waukegan River subbasin. The final adjustment of the subbasins resulted in 252 subbasins with an average size of 27.3 acres


(basins ranged in size from 1 to 289 acres). Generally basins were larger in areas that were not drained by the storm sewer system and smaller in the urban and dense residential areas that were drained by storm sewer. The target basin size for urban areas was 45 acres, which was a rule of thumb based on other studies of similar sized drainage areas.

3.6 Soil and Infiltration Parameters Soil data was obtained from the NRCS and was used to develop Green-Ampt infiltration parameters. The Green-Ampt methodology uses physically based parameters and is designed for continuous simulations. Green-Ampt methodology requires the specification of three parameters for each subcatchment: initial moisture deficit (IMD), suction head (Su), and the saturated hydraulic conductivity of the soil (Ks). Guidance for development of these parameters was taken from the User’s Guide to SWMM (CHI 2008) and the PCSWMM User’s Guide (CHI 2011). The hydraulic conductivity value was based on the SCS hydrologic soil group of soil (i.e. A, B, C, D); the moisture deficit and suction head were based on the soil type (e.g. silt, loam, clay, sand loam, etc.). The CHI manual usually reported a range of values and the average value was typically used. Some discretion was necessary to develop appropriate values based on the description of the soil. Area weighted average values for each of these parameters was computed for each of the subcatchments. In SWMM methodology these parameters apply only to the pervious surfaces.

3.7 Other Subcatchment Characteristics Other subcatchment characteristics that are specified in EPA SWMM5 include the subcatchment width (based on the travel length), percent imperviousness, percent zero imperviousness, slope, depression storage depths, and manning’s n values for pervious and impervious surfaces. Land use data was used to develop the percent imperviousness. The land use percentages that are included in the model are strictly tied to computing water quality run off for contaminants (see Section 3.8). The basis for determining the percent imperviousness for the watershed was taken from the 2008 Kabbes/Geosyntec report. Based on an analysis of the basin the document reports that 16.81% of the Waukegan River basin is paved roadway; the building rooftop areas is 11.11% of the watershed (or 821.9 acres total); and there was another 1.1 to 1.2 acres of impervious area including sidewalks, driveways, and parking lots for every acre of building roof area. Using this data a slightly different algorithm was developed that tied the building rooftop area to subcatchments that actually contained buildings. This was necessary because some subcatchments did not contain buildings so applying 11.11% to the entire watershed would overestimate the impervious area for some of the subcatchments. The new algorithm determined that for subcatchments that contain rooftops 13.27% of the area is impervious area due to rooftops. The subcatchment width is computed by dividing the subcatchment area by the travel length. This is an abstract basin parameter and is commonly used as a “tuning parameter” for model calibration because of its inherent uncertainty. Increasing the travel length decreases the subcatchment width which creates a more attenuated response to precipitation events. There are many techniques for developing the travel length and all can be valid so long as the method is consistent among subcatchments (CHI 2011). One technique is to omit the portions of the subcatchment travel length that would have more concentrated flow such as in pipes or gutters for instance. The velocity is much higher along these pathways than along the pervious surface pathways so these overland flow pathways dominate the response time, which is what the


travel length represents. This approach was not employed in this model because the concentrated flow travel length in some subcatchments was significant. To account for this the flow length used for each subcatchment was computed as a composite of the impervious and pervious surface travel lengths, with the impervious travel length multiplied by ⅓. This de-emphasizes the “fast moving” part of the travel length while not omitting it entirely. The one third value is based on average flows over impervious and pervious surfaces for conditions that would be expected in the Waukegan watershed. It is recognized that this method cannot be representative of all hydraulic conditions though the method is valid so long as it is consistent among all subcatchments. Default EPA SWMM5 values were used for most of the other hydrologic parameters including percent zero imperviousness, which is the percent of impervious area with no depression storage; D store, the depression storage depth; and manning’s n for pervious and impervious surfaces.

3.8 Water Quality and Land Use Event mean concentrations are flow weighted average constituent concentrations over the duration of a runoff event. The Northern Illinois Planning Commission (currently the Chicago Area Planning Commission—CMAP) developed Event Mean Concentrations specific to Lake County, Illinois for different land use types (NIPC 1993). In EPA SWMM5 event mean concentrations can be tied to the specific land use type to compute contaminant runoff in the model. The residential value used in the model (Table 1) was computed based on a revised methodology developed by Conservation Design Forum for the Lake County Stormwater management Commission (CDF 2007). Table 1 Event Mean Concentrations for Lake County Watersheds in lbs/acre/year

Residential Commercial Institutional Multi-Family Industrial Vacant Open Transportation Water 285 206 391 391 230 60 60 395 0

3.9 Routing Methodology SWMM offers three routing methods: steady flow, kinematic wave, and dynamic wave. Each offers advantages and disadvantages and each is particularly suited to certain types of applications. The method used for this analysis was dynamic wave, which is the most theoretically accurate. It routes non-steady flows and has ability to model backwater effects, flow reversals, pressurized flows, and entrance/exit energy losses. It is also the most data intensive and computationally time consuming. The model used a 1-second time step, which was necessary to stabilize the model and reduce continuity errors.

4.0 MODEL CALIBRATION AND VERIFICATION

Before the EPA SWMM5 model could be used the model results had to be compared to measured flow monitoring data to determine if the model was accurately predicting flow rates. Flow and water quality data collected by the Lake County Health Department (Lake County 2009) was used for calibration and verification of the EPA SWMM5 models.


4.1 Calibration Data The Lake County Health Department conducted a flow monitoring and sampling program in 2008 and 2009 that was used for model calibration and verification. Continuous flow was monitored at four locations on the Waukegan River (Figure 1), on the north branch, south branch, and in the main channel. The gages measured depth however this could not be easily correlated to an elevation reference so the depth data was not used explicitly for model calibration. This data was reviewed and compared to the model results but it was not used for calibration. Event based water quality samples were also collected for several large storm events at two different gages.

4.2 Baseflow Baseflow for the model was based on the measured baseflow observed in the 2008 flow data. A small flow of 0.006 cfs was added to every node in the model and produced an appropriate calibration for the four gages used in the model calibration.

4.3 Rainfall Derived Inflow and Infiltration (RDII) The initial modeling runs revealed that the model was significantly under-predicting the falling arm of the event hydrographs. This was evidence that the model was not capturing rainfall derived groundwater that was flowing into the streams after the precipitation events. EPA SWMM5 has capabilities to correct for this using unit hydrographs that represent RDII. This EPA SWMM5 feature creates RDII inflow at specific nodes which is correlated to the size of the storm. RDII unit hydrographs were added at the collection nodes for each subcatchment (Table 2). The model over-predicted runoff in the northern most upstream subcatchments in the watershed as evidenced by comparisons of the model results to the most upstream gage, QC-10. For this reason the quantity of RDII for these 18 upstream subcatchments was reduced from 25% of rainfall to 7% of rainfall to improve the calibration. The reason for lower contributions from RDII may be due to different hydrogeological characteristics of the Northern reaches of the basin however this cannot be ascertained without detailed investigations. Table 2 Unit hydrographs used for RDII. R represents fraction of rainfall that

becomes I&I; T is time to hydrograph peak (hours); K is falling limb duration/rising limb duration

234 Downstream Subcatchments

R T K 18 Upstream Subcatchments

R T K

Short Term Event 0.25 2 12 Short Term Event 0.07 2 12 Medium Term Event 0.25 3 12 Medium Term

Event 0.07 3 12

Long Term Event 0.25 4 12 Long Term Event 0.07 4 12

4.4 Parameter Calibration The model calibration improved with addition of the RDII however there were some additional adjustments that were necessary to finalize the calibration. Adjustments were made to imperviousness and the travel length which are common “tuning” parameters for SWMM hydrologic models. This is partially based on the uncertainty that is inherent to development of


these parameters. The following adjustments were made to the model to improve the calibration:

• Increased the travel length by 10% for all basins. This decreased the subcatchment width and served to attenuate the response times for all storms. Travel length is a common tuning parameter.

• Increased the zero imperviousness for nine downtown subcatchments to 35% from 25%. This was done to improve the calibration with gage QC-04.

• Increased imperviousness for nine downtown subcatchments by 30%. This was done to

improve the calibration with gage QC-04.

• Decreased imperviousness for 18 upstream subcatchments by 25%. This was done to improve the calibration with gage QC-10.

4.5 Calibration Results The results of the final calibration are provided in Table 3 and Plates 1-20. The climatological record runs for the entire year however measured data was only available from May through October so the model was only run for this period. There were gaps in the flow record and periods when the gages produced inaccurate measurements, particularly for gages QC-03, QC-10, and QCA-01. Gages QC-02 and QC-04 were more consistent. During analysis most of these errors were corrected for however some of these can still be observed in hydrographs. Reviewing the detailed hydrographs (Plates 1-20) there are some events that were consistently under-predicted for all of the gages (e.g. August 23rd, June 23rd); some events that were over-predicted for all of the gages (e.g. September 5th); and some events that were not captured by the model (e.g. August 18th). Consistency of this type that is observed at multiple locations suggests a lack of correlation between the precipitation record in the model and the actual precipitation during the event. The precipitation reported at the gages could be inaccurate or the gages may not have captured the spatial variability in the rainfall. Some events were very well correlated at all gages, particularly four significant events that occurred in July, with the exception of QC-10, which slightly over-predicted most events. QC-10 over predicted most events however the magnitude of flow at the gage location is relatively small. As described in Section 4.3, adjustments were made to the RDDI for the basins contributing to this gage, which made a better calibration of the average (Table 3) however many of the peak flows remain over predicted. Useful information regarding the calibration was gleaned by analyzing the monthly average flows. Gage QC-02 is located approximately 2100 feet upstream of QC-03 and the average difference between the model results at the two locations for the 2008 period of record is 0.5 cfs; the average difference in the measured data is 7.4 cfs. The model collects flow at the most downstream node in the subcatchment, which is typical for hydrologic flow routing in a model. The reason for this significant difference is likely that the model is routing a portion of flow just downstream of the gage location. This flow in reality may enter the stream upstream of this location which is why it may be picked up at the gage but not in the model. This may be why the model under predicts flow at QC-03 under most cases.


The average September flow for gage QC-04 is significantly larger than the modeled flow. Reviewing the hydrograph for this period (Plate 4) this difference can mostly be attributed to an event on September 15th, which follows a larger event on the 13th. The measured data shows the peak flow reaching approximately 600 cfs, which is significantly higher than the model. Looking at the two gages that best capture flow on the North and South branch before they enter the main branch, gages QC-03 and QCA-01 respectively, the sum of flow from these two gages is in the neighborhood of 450 cfs. Though gage QCA-01 is not operable during this period (the model flow reaches approximately 150 cfs) a flow of 600 cfs appears high and if it is accurate then the model does not currently have a mechanism to capture it. QC-04 is the most downstream gage in the model, without this one particular storm the calibration would be much more accurate. It is possible that the measured data is accurate and the soil was saturated by the previous event and the model is not accurately modeling the saturated soil conditions from this very large event. Evaluation and calibration of the model results considered both the peak flows during large events and the average flows over longer periods of time. A balance was made between both of these objectives because this model may serve a wide variety of uses.

Table 3 Calibration Results for 2008 Period of Record. Average Monthly Calibrated

and Measured Flows in CFS for Each Gage Location.

May 2008

June 2008

July 2008

August 2008

September 2008

October 2008

Average 2008

QC-10 1.3 1.6 0.8 0.2 1.6 - 1.0 Model 1.2 1.7 1.8 0.5 1.7 - 1.6 QC-02 5.0 13.8 9.8 1.5 26.7 6.9 12.3 Model 11.3 16.4 16.2 4.8 29.0 14.6 16.5 QC-03 - 24.8 15.4 6.9 31.6 26.4 19.7 Model - 17.8 14.4 4.9 31.3 30.4 17.0 QC-04 43.3 24.6 28.5 5.8 65.1 25.3 34.8 Model 43.8 28.0 27.9 8.1 50.6 26.6 29.1 QCA-01 - 10.1 5.6 3.2 5.8 11.6 6.6 Model - 10.4 9.6 3.0 9.7 6.7 8.2

4.6 Model Verification The results of the model verification are provided in Table 4 and Plates 21-35. The 2009 data set used for model verification was more limited than the 2008 data set; the flow set only covered April-July. This data set also had more instabilities and gaps than the data set used for calibration. For the model, precipitation, climatological, and Lake Michigan stage data were collected from the same sources described in Section 3. Precipitation records were collected from the same three gages and examined before the analysis was performed. For the April 2009 through July 2009 period of record the total precipitation for the gages was 15.7 inches (Lakefront), 13.1 inches (SMC), and 17.1 inches (FAA). The Thiessen method produced a total precipitation of 14.4 inches. The differences in these totals are more significant than differences observed in the 2008 precipitation record. The maximum difference in the 2008 record was 1.1 inches and the difference for 2009 was 4.24 inches. Errors were found in the SMC record, which contributed to less confidence in that data set. The initial run of the model


using the Thiessen set revealed significant under prediction of the results so the model was rerun using the FAA gage. Some similar results were repeated with the 2009 data set: QC-10 was slightly over predicted; QC-03 under predicted; and QCA-01 slightly over predicted. There were also events that were over predicted at all of the gages (e.g. the three events in July); under predicted at all gages (e.g. April 26th); and well predicted at all of the gage locations (e.g. April 20th and June 17th). This again suggests a lack of correlation with the precipitation record used in the model and the measured gage record. Initial review of the average flow data suggests that the model did not accurately predict flow at the QC-03 and QC-04 gage locations, however closer examination of the data helped to explain these inconsistencies. The largest event recorded during this period of record was the June 20th event. QC-04 recorded over 3300 cfs, which is significantly higher than the modeled peak flow, which was just over 1500 cfs. QC-03, the gage on the North branch just upstream of QC-04 was not operable during this event. QC-02, located 2100 feet further upstream from QC-03 recorded approximately 600 cfs; QCA-01 on the south branch just under 600 cfs. For other storms the QC-04 record did not exceed the QC-02 record by this degree. Also, for other storms the flow at QC-04 was closer to the additive quantity of the flows on the North and South branches, represented by QC-03/QC-02 and QCA-01, respectively. Finally, the large storms in the 2008 period of record did not have this lack of correlation. One possible reason for this difference is the differences in the precipitation record for this event. The FAA gage used in the model recorded 3.95 inches during this storm; the Lakefront gage 4.64 inches; the SMC gage just 3.12 inches. With this large of a storm there may be some inaccuracies in the measurement or there may have been this large degree of variability in the precipitation during the storm. This event is the reason for the lack of correlation between the average modeled and measured flow at QC-04 in June (Table 4). Similar inconsistencies were observed for a large event on April 26th. QC-04 measured over 1000 cfs where the model predicted approximately 300 cfs. QC-02 also measured a much higher flow than the model, almost 500 cfs versus slightly over 100 cfs in the model. Gage QC-03, just downstream of QC-02 however peaked at just 370 cfs, lower than the flow recorded at QC-02. Again, looking at the precipitation record the total precipitation recorded for this storm at the FAA gage is less than the other two gages: 1.65 inches for FAA; 1.91 for the Lakefront; and 1.87 inches for SMC. These inconsistencies could be attributed to inaccurate measurements at the gages or an inconsistent precipitation record. It is not likely possible to make up for these very large volumes of water in the model by adjusting infiltration or runoff parameters.


Table 4 Verification Results for 2009 Period of Record. Average Monthly Calibrated and Measured Flows in CFS for Each Gage Location.

April 2009

May 2009

June 2009

July 2009

Average 2009

QC-10 2.3 1.0 1.5 0.8 1.4 Model 1.8 1.5 2.6 1.0 1.7 QC-02 28.7 13.2 22.8 1.8 16.3 Model 19.1 14.7 26.4 8.6 17.1 QC-03 63.3 - 29.1 15.5 33.3 Model 24.8 - 19.9 8.7 16.1 QC-04 52.3 24.7 111.0 3.7 45.1 Model 26.9 26.8 59.9 17.6 31.8 QCA-01 17.2 6.3 14.3 - 9.7 Model 13.7 9.2 17.2 - 11.3

The April 26th event is the reason for the lack of correlation between the average modeled and measured flow at QC-04 in June (Table 4). There are a number of significant gaps in the QC-03 data record which has exaggerated the differences in the averages for this location. This is also why the model average at QC-03 is lower than at QC-02, which isn’t likely because QC-03 is downstream of QC-02. The reason for this is that much of the data was omitted from the computation of this average in order to correlate it to the gage record which had numerous data gaps. Therefore the measured record at QC-03 is not the best quality data for evaluating the model.

4.7 Water Quality Runoff Calibration The Lake County Health Department conducted event based water quality monitoring at two of their stations, QCA-01 and QC-03, for six separate events over 2008 and 2009. Composite samples were collected over the course of the event and the TSS concentration (among other contaminants) was measured for the composite sample. The composite samplers turned on when the flow increased and turned off when the flow decreased. Unfortunately, at the time of development of this report the exact times when the samplers turned on and off during the event could not be ascertained. This is critically important because the average flow computed from the model output can vary considerably depending on when the flow samplers turned on. To analyze and compare the results a range of averages was computed that considered an early turn off time and a later turn off time. This range was compared to the measured sample data (Table 5). Table 5 Average Modeled and Measured TSS for Six Precipitation Events. TSS in mg/L.

July 11, 08 Sept 5, 08

Oct 8, 08 April 20, 09

May 14, 09

June 17, 09

QC-03 141 95.2 121 52.4 521 108 Model 147-73 162-105 135-83 121-87 140-78 131-105 QCA-01 47.2 198 69.9 35.7 14.8 224 Model 148-55 140-84 117-57 122-81 138-60 103-75


The modeled results compared well to the measured data for many of the events. For some measured events the TSS appears either very high or very low, particularly at the QCA-01 gage. The model results have considerably less variability than the measured data, which is because the EMF mechanism that is used to model contaminant runoff relates the contaminant runoff concentration directly to the volume and intensity of the event and the area of the land use. Based on the range of values observed in the measured data there may be some other variable that is affecting the contaminant concentration that is not captured in the model. Or, this variability may simply be a function of when the composite sampler begins and stops sampling. Without details on the times the samplers began and stopped sampling there is not adequate reason to adjust or calibrate the EMC values.

5.0 LOW IMPACT DEVELOPMENT (LID) SCENARIO

With version 5.0.021 EPA SWMM5 added capabilities to model low impact developments (LIDs) such as rain barrels, permeable pavement, rain gardens, bioswales, and infiltration trenches.

Figure 3: Flow results of Low Impact Development scenario (blue) compared to baseline standard (red) for June 2008 event. These particular hydrographs are for the most downstream gage location in the model (QC-04).


Figure 4: TSS results of Low Impact Development scenario (blue) compared to baseline standard (red) for June 2008 event. These particular hydrographs are for the most downstream gage location in the model (QC-04).

Designs for each of the five LIDs available in EPA SWSMM5 were added to the models for future use. These are realistic but generic designs and should be adjusted for a specific design scenario. A fictional scenario was developed to demonstrate the capabilities of this feature and the runoff and contaminant reduction that can be achieved by the addition of LIDs. Using the calibrated 2008 period of record as a baseline LID technologies were added throughout the commercial and residential areas in the watershed. Rain barrels were added to the majority of homes in the City and rain gardens were added to the majority of commercial areas. The model was rerun and the hydrographs and polutographs for the LID scenario were compared to the baseline scenario. The results demonstrate a reduction in runoff that can best be observed at times of peak flow (Figure 3 and Figure 4).

6.0 MODEL CAPABILITES AND LIMITATIONS

The following section summarizes the capabilities and limitations of the SWMM models developed for the Waukegan River watershed.

• The model is developed for continuous simulations. The model currently contains climatological and precipitation data for periods of record from January-December 2008 and April-July 2009. These periods contain many significant events. This is a calibrated model so additional climatological/precipitation data can be added if other time periods need to be analyzed.

• The model is not developed for discrete design or synthetic storms. Individual

design storms are useful for flood studies, however the hydrologic parameters in the


model were not developed with these type of events in mind. Hydrological parameters and model calibration should be re-evaluated before single event precipitation data is loaded into the model.

• The model can be used to study the impacts of LIDs on flow and TSS runoff. A

fictional scenario that evaluates the flow and TSS runoff impacts from the addition of rain barrels and raingardens is included in the model. Any other type of LID scenario can be developed on an entire watershed scale or on one particular neighborhood. The impacts on flow or TSS runoff can be analyzed at any node or conduit in the model. When developing LID scenarios the percent imperviousness and subcatchment width should be re-evaluated.

• The model can be used to study the impact of development on TSS runoff.

Contaminant runoff in the model is tied to land use percentages, which are specified for each subcatchment. The land uses percentages can be adjusted to study the impact of development on runoff. Other contaminants or co-pollutants can be added to the model and other features included in EPA SWMM5 can be activated including street sweeping and contaminant buildup.

• The model cannot study sediment deposition or transport in the Waukegan

River main channel. EPA SWMM5 cannot compute sedimentation in the Waukegan River or sediment transport/erosion processes within Waukegan River. The model only computes sediment delivery from overland flow.

• Flood impact studies should be performed w ith care. Additional survey data may

need to be added to the model and portions of the model may need to be re-evaluated before a flood impact study is undertaken.

o Overpass survey data was only available for some of the bridges and conduits on the main channel so many of the bridges and culverts do not contain high cord (road overpass) survey data.

o Calibration has not been performed on any of the sewers because data was not available. The model reports flooding at particular nodes that would need to be verified. The invert elevations for some of these nodes were based on interpolation and the top of rim elevations were taken from a 10 foot digital elevation model so exact elevations would need to be verified. Also, losses within the sewer pipes would need to be evaluated and added to the model.

o Calibration of the model may need to be re-evaluated if a flood study is going to be performed; more emphasis would need to be placed on matching the peak and volumes for large events rather than the overall average flow for particular months.

o Several weirs are overtopped in the model. If the elevated flows here are of particular interest then these results would need to be evaluated further.

• The 2008 and 2009 periods of record can be used as baseline events. Any new

scenario that is developed should use a baseline event so that the new simulation can be compared to a reference.


7.0 REFERENCES

Computational Hydraulics Inc. (CHI). 1996. User’s Guide to SWMM5, Guelph, Ontario, Canada Computational Hydraulics Inc. (CHI). 2011. PCSWMM Users Manual, Guelph, Ontario, Canada Conservation Design Forum. 2007. Memo to Patty Werner, Lake County Stormwater Management Commission from Tom Price regarding Residential Pollutant Loading Rates for Lake County, Illinois. Environmental Protection Agency (EPA). 2010. Storm Water Management Model User’s Manual Version 5.0. Cincinnati, OH Kabbes Engineering, Inc. 2007. Waukegan River Watershed Plan, Barrington, IL. Lake County Health Department. 2009. Water Quality and Flow Monitoring in the Waukegan River, 2008-2009, Section 319 DRAFT Final Report, Waukegan, IL National Resource Conservation Service (NRCS). 2005. Soil Survey of Lake County, Illinois Northern Illinois Planning Commission (NIPC). 1993. Unit Area Pollutant Load Estimates for Lake County, Illinois Lake Michigan Watershed U.S. Army Corps of Engineers (USACE). 2008. Waukegan River, Illinois, section 516(e) WRDA 1996 Great Lakes Tributary Modeling Scoping Report, Chicago, IL

U.S Army Corps of Engineers Section 516(e) Waukegan River Chicago District SWMM Model Report

Plates


Plate 1. 2008 Calibration. Model in red, measured gage data in grey.


Plate 2. 2008 Calibration. Model in red, measured gage data in grey.


Plate 3: 2008 Calibration. Model in red, measured gage data in grey.


Plate 4: 2008 Calibration. Model in red, measured gage data in grey.


Plate 5: 2008 Calibration. Model in blue, measured gage data in grey.


Plate 9: 2008 Calibration. Model in green, measured gage data in grey.


Plate 13: 2008 Calibration. Model in cyan, measured gage data in grey.


Plate 17: 2008 Calibration. Model in magenta, measured gage data in grey.


Plate 21: 2009 Verification. Model in red, measured gage data in grey.


Plate 24: 2009 Verification. Model in blue, measured gage data in grey.


Plate 27: 2009 Verification. Model in green, measured gage data in grey.


Plate 30: 2009 Verification. Model in cyan, measured gage data in grey.


Plate 33: 2009 Verification. Model in magenta, measured gage data in grey.


Plate 34: 2009 Verification. Model in magenta, measured gage data in grey.


Plate 35: 2009 Verification. Model in magenta, measured gage data in grey

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