Continuous Modeling of Wet Weather Strategies Annual Water ... · Continuous Modeling of Wet Weather Strategies Annual Water Quality Results Support a Municipality’s Decision-Making

Continuous Modeling of Wet Weather Strategies Annual Water Quality Results Support a Municipality’s Decision-Making Process

Kathleen Smith* and Jon Hothem

Malcolm Pirnie, Inc. 1900 Polaris Parkway, Suite 200

Columbus, Ohio 43240 ABSTRACT An extensive water quality modeling effort for the City of Columbus Long Term Control Plan (LTCP) was performed in order to evaluate future scenarios to abate combined sewer overflows. This modeling effort was supported by a massive data collection program and employed three different models to analyze the receiving streams. Once the models were selected and calibrated, continuous annual simulations were run to evaluate and compare the alternatives for final selection by the City. The models projected future bacteria concentrations in the receiving streams and also predicted the dissolved oxygen levels in the stream. The modeling tools supported the City’s selection of a LTCP alternative by providing projections of environmental benefits. KEY WORDS Wet Weather Modeling, Long Term Control Plan, Dissolved Oxygen, Bacteria PROJECT BACKGROUND The City of Columbus, Ohio developed a Wet Weather Management Plan (WWMP), which addressed both Combined Sewer Overflow Long Term Control Plan (CSO LTCP) and System Evaluation and Capacity Assurance Plan (SECAP) requirements. Because both plans were being developed at the same time, potential changes in the separate system could also be accounted for in the evaluation and analysis of the combined system. This integration of the plans is important, because despite separate regulatory programs, the City’s combined sewers and sanitary sewers function as integrated components of the overall wastewater collection and treatment system. One of the CSO LTCP focuses was receiving water modeling, which was complemented by a large characterization effort. This effort spanned over two years and resulted in the collection of over 14,000,000 data points. Of particular importance to the modeling program is the collection of continuous in-situ dissolved oxygen concentrations (DO) at 34 locations spanning across the study area (FIGURE 1). This data was integral in the calibration of the dissolved oxygen water quality model. In addition, numerous dry and wet weather discrete samples were collected from the receiving streams, wastewater treatment plants, combined sewer overflows, storm sewers, and designed sanitary relief points. These data assisted in the determination of the parameters of interest for water quality modeling purposes, and were necessary in the calibration of the models.

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Copyright 2006 Water Environment Foundation. All Rights Reserved©

FIGURE 1: Receiving Stream Continuous Monitoring Locations

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The parameters that were of interest for further study and modeling were dissolved oxygen and bacteria. The data revealed that there were no metals issues to be concerned about in the receiving streams; most of the samples collected were under detection limit, and certainly met water quality standards. In addition, it was also determined that nutrient loadings on the rivers were not significantly affected by the sewer system. The sampling also revealed that in general, the DO levels in the receiving streams were met applicable standards. There were exceptions to this observance, but most exceptions occurred during unique dry weather conditions that were not directly related to wet weather activity. However, when projecting future loads on the receiving waters, it is important to simulate a dissolved oxygen response in the streams; for this reason dissolved oxygen was carried into the modeling analysis. Therefore, as is often the case with a CSO LTCP, the main parameters of concern were dissolved oxygen and bacteria. These were the two parameters that were carried through the calibration process. The modeling program consisted of three main models: a hydrologic model for generating the flows in the receiving streams, a receiving streams hydrodynamic model, and a receiving streams water quality model. In combination, these models provided the tools necessary to determine the affects that various changes in the sewer system would have on the receiving streams. The models were all run to evaluate the system response to a typical year of rainfall. With these models the City hoped to determine the potential impact that each alternative might have in the future with respect to the parameters of concern: dissolved oxygen and bacteria. The CSO LTCP was broken into two main areas of analysis: the local combined collection system and a transport and treat system. As seen in FIGURE 2 all of the combined collection system drains to a single point, at the Whittier Street Storm Tanks (WSST). In the current system, approximately 85 percent of the annual system-wide CSO discharge occurs at the single WSST CSO. Therefore, in any abatement scenario, the majority of the CSO discharge will have to be addressed at the WSST through some combination of transport, treatment, or storage. For this reason the two components of the combined sewer system were analyzed separately, the local combined sewer system, and the transport and treatment component. During the modeling effort one collection system model was used to evaluate the impact of all of the combined and separate sewer system upgrades. The output from this model was fed into the water quality model to assess the impact of all of the WWMP improvements (both CSO LTCP and SECAP) on the receiving streams. MODELING EFFORT OVERVIEW SELECTION AND DEVELOPMENT OF HYDROLOGIC MODEL The hydrologic model for generating the flows for the receiving streams consisted of two distinct components: a model for flows generated within the City’s CSS area and a model

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FIGURE 2: CSO LTCP Combined Sewer System and Transport and Treat System

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for flows generated in areas outside of the City’s CSS area. The boundaries for these two areas are shown in FIGURE 3. For the remaining watershed area, no hydrologic model was developed. Instead, flow data was obtained from four USGS gage stations (FIGURE 4) and used as an input to the upstream boundaries of the receiving stream hydrodynamic model. Flows for the CSS area were generated using the City’s PCSWMM model of its combined sewer system, developed by EMH&T. This model uses the SWMM RUNOFF block to model surface hydrology within the CSS area. For consistency purposes, it was decided that the RUNOFF block of XP-SWMM v.8.29 would be used to model the hydrology of the areas outside of the CSS area. Aerial photographs were used to divide the area into “urban” and “rural” subwatersheds. For the “urban” subwatersheds, the non-linear reservoir method in the RUNOFF block was used to represent the hydrology. For the “rural” subwatersheds, the SCS hydrology method in the RUNOFF block was used to represent the hydrology. Hydrologic parameters for these subwatersheds outside of the CSS area were initially estimated through the use of available digital elevation model (DEM), soil type, and land use GIS coverages. SELECTION AND DEVELOPMENT OF RECEIVING STREAMS HYDRODYNAMIC MODEL The receiving streams hydrodynamic model was developed next. In order to meet the goals of the analysis, the selected model would have to perform dynamic continuous simulations and be able to link to a dynamic water quality model capable of modeling both bacteria and dissolved oxygen. It would also need to be able to adequately model the hydraulics of low-head dams, several of which are present in the model area (FIGURE 5). Four hydrodynamic models were identified as potentially meeting the desired criteria: RIVMOD, SWMM TRANSPORT, EFDC, and EPDRIV1. During the initial screening process, RIVMOD and EFDC were eliminated from consideration because of a lack of widespread application in municipal planning projects and because of an unnecessary level of complexity, respectively. For the remaining two model candidates, a series of pilot test simulations were performed on a portion of the receiving stream to be included in the model. The purposes for the pilot test simulations were as follows:

• To ensure that the models could adequately meet the desired model analysis criteria.

• To provide a framework for further comparing the relative strengths and weaknesses of the models.

• To develop the protocols for flow input, model linkage, etc., that would later be applied during the development of the full receiving streams hydrodynamic model.

During the pilot test simulations, it was found that EPDRIV1 may not be capable of meeting all of the desired criteria. In particular, problems arose in generating the

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FIGURE 3: Hydrologic Model Boundaries

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FIGURE 4: Hydrodynamic and Water Quality Model Boundaries

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FIGURE 5: Low Head Dam Figure

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hydrodynamic linkage files needed for the water quality model. For this reason, the TRANSPORT block of EPA-SWMM v.4.4gu was chosen as the model for the receiving streams hydrodynamic model. The pilot test model was then expanded to the full model using the protocols developed during the pilot test process. The full hydrodynamic model was created by defining nodes at the following locations: locations where cross-sectional surveys occurred, USGS gages, low-head dams, receiving stream confluences, in-stream monitoring locations, CSO outfalls, major storm sewer outfalls, watershed load point locations, and treatment plant effluent and bypass locations. The extent of the hydrodynamic model is shown in FIGURE 4. SELECTION AND DEVELOPMENT OF RECEIVING STREAMS WATER QUALITY MODEL For wet weather analysis of CSO contributions to receiving waters, a water quality model must meet certain criteria. For the City’s WWMP, the model had to be dynamic, be able to model continuous periods, be applicable to rivers, be able to represent low-head dams, and be able to model both bacteria and dissolved oxygen. Three models were identified that met these criteria: EFDC, EPD RIV1, and USEPA WASP. In the previous screening rounds both EFDC and EPD RIV1 were eliminated. This left WASP, which has been widely used for this type of wet-weather application. The limitations of this model include only having a global CBOD decay value (can not be varied reach-by-reach), and difficulty in representing dissolved oxygen conditions in stratified, non-riverine dam pools. These details are discussed further in the dissolved oxygen calibration section. Once the WASP model was selected the pilot test models were tested for compatibility between all the modeling components – the hydrologic model, the hydrodynamic model, and the WASP water quality model. Once this compatibility was confirmed, the model selection process was complete, and the full model calibration effort and typical year simulations began. CALIBRATION OF HYDROLOGIC AND RECEIVING STREAMS HYDRODYNAMIC MODELS The calibration of the non-CSS area hydrologic model and the receiving streams hydrodynamic model occurred simultaneously (the hydrology model for the CSS area was calibrated separately during the collection system modeling effort). The calibration process consisted of comparing predicted and monitored flow hydrographs at 13 in-stream locations for five wet-weather events. A sixth event was used for validation purposes only. Flow depth was also used as a secondary comparison parameter. The in-stream locations used during the calibration process can be seen on FIGURE 6. Calibration began with the most upstream locations and worked downstream from there. During calibration, the primary adjusted parameters were percent impervious, overland flow width, and soil characteristics for the hydrologic model, and streambed Manning’s n values for the receiving streams hydrodynamic model. Example calibration plots can be

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FIGURE 6: Model Calibration Locations

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seen in FIGURE 7 and FIGURE 8. Once the calibration process was completed, the calibrated receiving streams hydrodynamic model was used to generate the hydrodynamic linkage files needed by the receiving streams water quality model for its calibration process. CALIBRATION OF RECEIVING STREAMS WATER QUALITY MODEL The water quality model calibration process started with the data collection effort. Six wet weather events were sampled in the receiving stream over a 72 hour period to provide the baseline data for the bacteria calibration. For dissolved oxygen, continuous water quality instruments were installed in the streams to provide the necessary calibration information. Also, during the wet weather sampling events discrete dissolved oxygen readings were taken; these readings verified the in-situ dissolved oxygen readings and provided another calibration point for the modeling effort. Calibration of the bacteria model was completed by comparing the model predicted pollutographs to the sampled pollutographs. Of the six sampled wet weather events, four were used for calibration, and two for validation of the model. For the bacteria modeling, the upstream boundary bacteria concentrations were assigned constant dry-weather and wet-weather values, based on sampled data. Instream temperature profiles for the calibration events were also based on sampling data. The bacteria decay constant and the bacteria concentrations of the point sources were adjusted during calibration, with the point source concentrations guided by end-of-pipe concentrations measured during the sampling program. The bacteria model was developed using Event Mean Concentration (EMC) values for the point sources, in order to extrapolate wet weather conditions to future scenarios. FIGURE 9 and FIGURE 10 show examples of the bacteria model calibration results. Dissolved oxygen calibration was performed in the same manner as the bacteria, by comparing collected data against model predicted values. Again, calibration was performed using four wet weather events, with two used for validation. During the dissolved oxygen model calibration the following were held constant:

• Dissolved oxygen concentrations at the upstream boundaries, based on monitoring data

• Ultimate CBOD, Organic Phosphorus, and Orthophospate concentrations at upstream boundaries, based on sampling data

• Algae concentrations at upstream boundaries, based on monitoring data • Temperature profiles, based on monitoring data • Source concentrations for dissolved oxygen were set at saturation because high

turbulence during the wet weather events typically drives dissolved oxygen levels to saturation at the discharge

Parameters adjusted to calibrate the dissolved oxygen model were as follows:

• Source concentrations for CBOD, Organic Phosphorus, and Orthophosphate

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Figure 7Olentangy River at Dodridge Street Flow Calibration

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Figure 8Scioto River at Jackson Pike Flow Calibration

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Figure 9Alum Creek at SR104 Water Quality Validation

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Figure 10Olentangy River at John Herrick Drive Water Quality Calibration


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• CBOD decay • Dam reaeration variables, with reaeration calculated using standard reaeration

formulas. • Algae growth rate • Time varying solar radiation

Examples of the results of the dissolved oxygen calibration can be seen in FIGURE 11 and FIGURE 12. The bacteria water quality model calibration was challenging in terms of trying to define EMCs that were within sampled limits, but could also be applied to all CSOs in the system. This required significant iteration and investigation of local conditions to reconcile the point source concentrations with the wide range of bacteria concentrations observed in the river. In the end, the bacteria model calibrated very well in terms of timing and magnitude. The only exception to strong bacteria calibration was on the Big Walnut Creek where sampled concentrations were higher than expected and could not be replicated by the modeling effort (FIGURE 13). Investigation into possible bacteria sources during the calibration produced no explanation for the elevated in-stream levels observed in the sampling program. Ultimately, the calibration team decided that the sampled concentrations were not representative, and the high peaks were disregarded. Following the calibration effort, it was found that a sewer main had been damaged in the area (it has since been repaired) and was contributing flow to a storm sewer. This example demonstrated the model’s functionality as a diagnostic tool. The dissolved oxygen calibration was challenging due to WASP’s inability to apply reach specific CBOD decay constants to the model. WASP only allows the user to apply the CBOD decay constant to the entire system. Moreover, in one-dimensional applications, WASP averages the water quality parameters in the dam pools over the large stored volume; this dampened diurnal variations in the pools, but the diurnal swings returned once the flow left the pool. The model did an excellent job of predicting dissolved oxygen concentration just downstream of the WSST (the largest CSO in the system), and at the State Route 665 Bridge. The lowest dissolved oxygen concentrations in the lower Scioto River were observed at State Route 665, making it the critical location for dissolved oxygen modeling. In the end, despite the dissolved oxygen model calibration challenges, the model consistently matched concentrations at key model locations including State Route 665 and just downstream of the WSST. ANNUAL SIMULATIONS FOR FUTURE SCENARIOS The key application of the calibrated water quality model was to perform annual simulations for the typical year. This required many important pieces of information including the typical year of rainfall and representation of the collection system abatement scenarios under consideration. The typical year of rainfall for the City of

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Figure 11Scioto River at SR665 Water Quality Calibration

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Figure 12Scioto River at Main Street Water Quality Calibration

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Figure 13Big Walnut Creek at Reese Road Water Quality Calibration


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Columbus was developed based on approximately 60 years of local rainfall data, focusing on both annual and monthly measured including total depth, number of events, distribution of event sizes, and peak intensities. The typical year contained no storms with a return period greater than one year. A wide range of system control technologies and abatement scenarios were evaluated throughout the project. Initially, the existing system was modeled to determine the current typical year impact on the receiving streams. Then, projected scenarios were modeled to estimate future conditions. The results for future conditions were then compared to the existing system to evaluate the alternative in relation to the current conditions. The final group of four short-listed improvement alternatives included a range of abatement technologies. Some of the technologies included were complete separation (construct new sewers), inflow redirection (construct new storm sewers), offline storage, tunnels (for storage), and large interceptors for transport. For each alternative, a range of levels of control from 1-month (twelve overflows in a typical year) to full control (no overflows in a typical year) were investigated. The four short-listed alternatives selected for detailed analysis consisted of:

Tunnel centered alternative – optimized in terms of tunnel technology Inflow Redirection alternative – optimized in terms of the City’s current

infrastructure philosophies OSIS centered alternative – optimized the use of a transport and treatment

alternative for the CSO flow Lowest cost alternative – optimized in terms of cost

For each alternative, the collection system model was run to determine the overflow hydrographs from each point source discharge location. This model output was then used as input into the receiving stream hydrodynamic file. The hydrodynamic file also received input from the hydrologic model, which provided routed storm runoff to the river. From these inputs the hydrodynamic model generated the hydrodynamic input file for the water quality model. This input file was for the typical year, broken in to four quarters (three months each), containing continuous flow for the rivers, and the point sources to the river. Finally, the hydrodynamic input file was combined with concentrations for each of the point sources to drive the water quality model. This is the same general process as used for the calibration. However, these simulations were not for single events, but rather for an entire annual period. All four short-listed alternatives were run in the calibrated bacteria and dissolved oxygen water quality models. The results from the scenarios were analyzed and figures displaying time-varying dissolved oxygen levels and tabular bacteria results were created. The dissolved oxygen model runs exhibited the same trend as the data, with the lowest sag due to combined sewer system loading occurring at the State Route 665 Bridge. The quarter with the lowest dissolved oxygen concentrations was the third quarter (July,

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August, and September). This is expected due to the warmer stream temperatures and lower baseflows that typically exist in the late summer period. One interesting characteristic of the dissolved oxygen model was its ability to simulate the diurnal algae patterns observed in the stream. As can be seen in FIGURE 14, the model also accounted for the buildup of algae during dry weather and the washout of algae populations during wet weather. This model capability is important, as the algae concentrations directly impact the dissolved oxygen concentrations through photosynthesis and respiration. The impact of storm events can be seen as the DO diurnal is disrupted as algae are washed out during times of wet weather, and how the diurnal recovers during dry weather conditions (FIGURE 15). The bacteria model results were generated and summarized differently than the dissolved oxygen results. All of the time series concentrations from the model were imported into EXCEL spreadsheets, where the bacteria concentrations were converted into the number of hours in each month exceeding the maximum bacteria water quality standard (for both fecal coliform and E. coli). This was done because of the statistically based nature of the Ohio bacteria water quality standard. The bacteria standard is only in effect during the bathing season, from May through October, so the total hours of exceedance were developed for those months. TABLE 1 shows the results from the bacteria water quality model simulation for the final recommended alternative in comparison with the existing system.

In summary, the results of the modeling show that there are no dissolved oxygen violations in the typical year under either existing conditions or with any of the alternatives. At the critical location for dissolved oxygen, the concentrations are consistently above the water quality standard in every simulation. This is also the case for segments upstream, not as heavily influenced by the CBOD from the CSO sources. The bacteria model results show that each of the alternatives reduce the hours of violation in relation to the existing system conditions. In comparison with the other alternatives, the OSIS centered alternative proved most beneficial based on a number of factors important to the City, and so was ultimately selected as the recommended alternative. The water quality modeling tools helped to validate this selection for City decision-makers. SIGNIFICANCE This extensive water quality modeling effort was able to assist the City in determining the abatement alternative which best met their goals. The water quality model, in conjunction with the hydrodynamic model, was able to analyze the receiving stream water quality impacts due to combined sewer overflows in terms of dissolved oxygen and bacteria. These results provided meaningful, credible support to the City’s selection of the preferred alternative. In the end, the City was able to select an alternative with a high degree of confidence that dissolved oxygen water quality standards will be met, and that the bacteria load to the stream will be reduced by 93%, upon completion of the recommended program.

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Figure 14

Predicted Phytoplankton Levels for the Third Quarter at SR665 Reach

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Figure 15Predicted DO Levels for the

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Table 1Annual Hours Exceeding Maximum Criterion for Bacteria WQS

ES 2005 and Final Recommended Alternative

System A39 - Greenlawn 44 - SR 104 53 - I 270 59 - SR 665

E.coli Fecals E.coli Fecals E.coli Fecals E.coli FecalsJanuary 232 51 313 157 411 307 401 296February 312 189 317 206 546 218 532 207March 167 49 188 89 220 106 219 101April 276 77 296 107 290 162 292 155May 440 158 441 156 439 175 430 157June 333 120 338 135 345 179 339 174July 192 91 210 115 223 167 222 173August 123 37 146 68 126 82 137 93September 144 40 150 54 149 50 142 38October 103 17 123 44 123 54 131 63November 168 48 176 83 175 108 176 105December 251 60 280 161 452 259 445 253Bathing SeasonTotal Hours: 1335 463 1408 573 1406 708 1401 700

January 213 42 232 60 228 96 222 90February 305 179 312 177 315 161 315 148March 151 38 157 45 151 51 144 44April 254 64 265 64 249 72 245 74May 434 143 438 132 434 100 425 101June 329 105 333 111 321 107 316 125July 179 50 184 81 162 72 170 88August 94 17 108 31 83 35 79 49September 143 34 143 37 132 25 127 8October 75 0 95 9 57 13 56 12November 148 41 160 43 149 52 148 52December 237 46 253 67 254 93 250 86Bathing SeasonTotal Hours: 1253 348 1300 400 1189 353 1173 384

Notes:(1) Based on annual water quality model simulations for the LTCP typical year(2) Shaded monthes represent Recreational Season

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Continuous Modeling of Wet Weather Strategies Annual Water ... · Continuous Modeling of Wet Weather Strategies Annual Water Quality Results Support a Municipality’s Decision-Making