GRAVITY CALIBRATION: A SIGNATURE ACCOMPLISHMENT

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1 GRAVITY CALIBRATION: A SIGNATURE ACCOMPLISHMENT Phil Hubbard, P.E., HRSD Paul Wilson, P.E., Brown and Caldwell* Mark Harber, P.E., Brown and Caldwell *301 Bendix Road, Suite 400 ABSTRACT Virginia Beach, Virginia, Brown and Caldwell greatly improved the hydraulic model calibration of significant gravity interceptors, ranging in diameter from 18-inches to 54-inches, for the Hampton Roads Sanitation District (HRSD) by reevaluating the typical use of velocity versus depth scattergraphs. The scattergraphs were evaluated to detect distinctive hydraulic responses across a range of dry and wet weather flow conditions. This approach deviates from the classic approach of using time-series hydrographs to calibrate model response only to specific wet weather events. Instead, the hydraulic signature approach employed used meter data from multiple wet weather events across a five-year time period in different locations along the gravity reaches studied. The calibration effort achieved more realistic simulation of capacity constrictions in the gravity reaches and improved accuracy in predicting surcharge and overflow locations. The analysis assessed the calibration of three separate gravity reaches. One of the reaches terminates at a treatment plant influent and the other two at regional pump stations. All are fed directly by gravity sewer connections and by pump stations connected to the upstream interceptor system. Meter data was evaluated to discern the presence and extent of backwater effects. Review of cleaning records provided locations and volume of grit removed, thereby indicating the locations where sedimentation should be considered for simulation. Improved calibration was iteratively achieved by changing friction factors, adding simulated sediment and revising key hydraulic elements, namely siphon chambers. Calibration improvement was performed by comparing velocity versus depth scattergraphs of measured data, regardless of timeframe, versus model output. Given the structural similarity of the actual and simulated pipes, the analysis demonstrated a hydraulic signature, a unique plotted distribution of velocity versus depth, for each gravity reach representing its response to a variety of flow conditions. This procedure is well suited to fine tuning hydraulic models to simulate observed SSOs. Detecting the hydraulic signature of the gravity reaches in response to significant wet weather events allowed for enhanced evaluation of continuous time series data by focusing on the best rainfall events where capacity limitations were observed in the field. This methodology provides a robust, efficient method for gravity sewer model calibration and can be applied to any gravity sewer system requiring more accurate representation of its hydraulic depth and velocity response to flow. It also provides a more solid basis on which to evaluate necessary capital or operational improvements that will provide required capacity under the RWWMP. Introduction During recent efforts by the Hampton Roads Sanitation District (HRSD) to fulfill their EPA Regional Wet Weather Management Plan (RWWMP) consent decree (CD) requirement, Brown and Caldwell (BC) was

2 requested to provide improvements to the calibration of the HRSD Regional Hydraulic Model (RHM). For this effort, BC was asked to improve the simulation of observed capacity deficiencies in significant gravity reaches and provide a more accurate modeling tool to identify necessary improvements in the HRSD system. An innovative approach for calibration was needed to meet these goals and reduce the associated risk with eliminating wet weather overflows in the regional planning process. The calibration approach selected by BC leveraged the use of time-independent scattergraphs as part of a hydraulic signature approach. This approach provided a method that 1) allowed the integrated use of reliable gravity flow monitoring data from different wet weather events with multiple flow monitors and 2) identified the hydraulic response of the monitored gravity reaches in a manner that was effective for comparison with model results. The calibration approach chosen by BC provided greater flexibility to improve simulation quality by re-purposing available flow monitoring data without spending time or funds on additional gravity flow monitoring campaigns. The overall analysis and approach were essential to improve the simulation of more realistic levels of surcharge and sanitary sewer overflow conditions. This method is well suited for evaluating improvements to hydraulic models (storm, sanitary or combined) where field observations have included sewer overflows. Our methodology, which paired the hydraulic signature from scattergraphs of the gravity reaches with significant wet weather events, allowed for the enhanced evaluation of continuous time-series data by focusing on the long term hydraulic behavior and response observed during significant flow events in the field. This methodology was also able to provide a cost-effective means to improve the gravity portions of the HRSD regional hydraulic model for a more realistic representation of the system that will reduce the risk in the development of capital projects as part of the HRSD RWWMP. This approach could be applied to other gravity sewer systems that have known issues with surcharging and SSOs where the models do not properly represent observed field conditions, as well as systems where effective solutions are needed to control existing and long-term capacity challenges. Methodology: The methodology used a combination of available gravity flow monitoring data. The data was collected in different points throughout the system over a five-year period. Depth-velocity scattergrapths from the RHM model simulations were compared to monitoring data to create a time independent view of the system. This resulted in a clear hydraulic signature at different points of the system that were used to implement the necessary adjustments in the hydraulic model for improved representation of observed flow conditions. Flow Monitoring: Gravity flow monitoring is a practice used by utilities through a network of flow meters to measure the flow rates, velocities and water levels in their sewer conveyance system. Flow is calculated by measuring the velocity and depth measurements of the flow over a known area. Using this information utilities are able to record how their system reacts to dry and wet weather conditions to plan for future needs in the system. More importantly, when this data is used to calibrate, validate and test hydrologic and hydraulic models, this information provides strategic insight for estimating system capacity and identifying areas that have capacity limitations (Hampton Roads Sanitation District, 2008). A common approach for using flow monitoring data is to compare the simulated and measured values in a time-series format. The area of interest in this study, the Jefferson Avenue gravity reach, had a total of seven flow metering locations: Jefferson 01, 02, 03, 04, 05, Copeland Park Pump Station and Newmarket Creek Pump Station. Three meters were located directly on the main Jefferson Avenue gravity line; two were located

3 on tributary branch lines and two represented telemetry data from large pump stations, as indicated in Figure 1. The time period used for all seven locations occurred between 2008 and However, for each location, there was either a difference in coverage or there were significant gaps in the stated time period. Data quality varied widely in time and between locations due to debris accumulation, ragging, equipment failure or other common problems associated with gravity flow monitoring equipment. Therefore, it was important to identify and remove inaccurate flow data so the remaining data could be used to generate a clear and accurate hydraulic response signature. Figure 1: Meter Locations in Jefferson Avenue Gravity Study Area In order to select the best data points for characterizing the system a time-series graphing approach was used. All the data points that were available were assembled using the time-series associated with the data. Using this graphical display approach allowed for quick diagnosis of the common trends found in the datasets. Additionally, a comparison of each meter along the main trunk line to the downstream treatment plant meter was done. This visual point of reference was used to locate irregularities in the data and discard data points that were outliers. Outliers were any data points that didn t follow the normal diurnal pattern or points that showed a high level of variance from previous points in short periods of time when little or no rainfall occurred. An example of the analysis can be seen in Figure 2. The use of these visual techniques ensured that the highest quality data points were used in the subsequent evaluations and gave more realistic flow loading, as well.

4 Figure 2: Example of Comparison of a Flow Meter Site to the downstream Treatment plant Gravity flow monitoring data was similarly used to provide flow inputs and boundary conditions to the hydraulic model. Whenever possible, measured flow hydrographs were used in place of simulated flows. This particular technique allowed for the removal of complicated pump station hydraulics from the upstream input points. By using hydrographs, the introduction of error was lessened and the model was focused on the hydraulic behavior of the gravity reaches. Furthermore, downstream boundary conditions were simulated by employing the flow depth time series from the most downstream gravity flow monitor. A tail water time series captured by the downstream meter also accounts for any backwater effects and hydraulic issues related to our study area. Scattergraphs: Wastewater flow monitoring data can be viewed as a time series or as a scattergraph, but for this study scattergraphs were chosen. Scattergraphs provide a means for displaying two independent variables: depth of flow and velocity (Environmental Protection Agency, 2006). This style of graph displays the behavior of the gravity sewer flow as it passes through the conveyance system, independent of time. Scattergraphs can also be used to provide insight into other factors like: sedimentation, debris accumulation, grease blocks, excess I/I, backwater effects, etc... For this analysis, these graphs are used to calibrate, test and validate a hydraulic model of a sanitary sewer system. Figure 3 shows four examples of scattergraph plots. These plots exhibit the effects of debris passing the meter site, surcharge, overflow, and backwater conditions.

5 Figure 3: Scattergraph Examples (Debris, Surcharge, Overflow and Backwater) Each of the flow metered locations used in the analysis had data that started or stopped at different times and in some cases had large gaps (maintenance, operation issues, etc ) during the monitoring period. In order to make full use of the available data, disregard for time was necessary. Therefore, by focusing on the relationship between depth and velocity (independent variables), time became less of a consideration. This method assumed that the hydraulic behavior of the flow was consistent and repeatable over time. The scattergraphs generated from model simulation outputs were superimposed over the observed data from the corresponding flow monitored locations. These graphs allowed for the evaluation of the data provided with the additional benefit of describing and identifying different types of hydraulic behavior in the gravity reach associated with the flow monitoring like hydraulic restrictions, upstream/downstream overflows, backwater effects, sediment deposits, sensor malfunctions, and pump station operation. This technique was used to compare the flow characterization of the model output and the observed field conditions. The scattergraphs also include reference line to assist in the interpretation of the monitoring data. There are three groups of reference lines: Lines of steady state flow (based on Manning s normal flow equation) Lines of constant flow rate, called iso-qs (based on the continuity equation) Lines of wave speed to distinguish sub and super critical flow (based on the Froude number) These reference lines delivered an ability to quickly diagnose and recognize the hydraulic state of the flow. They also help identify measured values that are physically unrealistic based on fundamental

6 physical principles of hydraulics. A function also accounts for sediment depth and how that can change the hydraulic characteristics of the flow. Each of these reference points were used to accurately determine any chronic sedimentation problems in the selected gravity reach and limited the number of model runs needed during the calibration adjustment process. Using this particular type of graphical representation allowed each flow behavior observed from the field data and the corresponding hydraulic model representation of the flow at that site to be readily visible and allowed the available data to be used independent of time while using multiple flow events. Hydraulic Signature: Another approach used with the scattergraph was the observation of behaviors or Hydraulic Signature of the conveyance system at each location. This approach is useful if the pattern is repeated event after event to create a consistent pattern for velocity and depth. The combination of all the available data from each flowmeter resulted in the development of a visual pattern based on the gathering and densification of the points captured during the monitoring period. This accumulation of points produced a discernible pattern response that was a reproducible signature in the hydraulic model. For the study outlined in this paper, these signatures were derived from the conveyances systems response to several wet weather events over the life of each of the flow monitors. Using this approach, each site s available data was combined into a single scattergraph in order to produce the necessary graphical representation of the flow behavior observed in the upstream gravity reach. The primary assumption behind this new approach was based on the understanding that the model pipe network was structurally similar to the real pipe network. This assumption was verified by reviewing all available plans and records to validate the flow data used did not occur before any major structural changes happened to any pipes in the study area. This included, but is not limited to diameter changes, collapses of segments, re-laying of the network in new directions and changes in material. The precision of the sewer network data was necessary to the employment of this concept. Once it was established that the pipe network was similarly laid out, the data points gathered could then be directly compared with the flow metered data for the gravity reach. The graphical representation of flow depth versus velocity was used to identify issues upstream and downstream of the monitors. Wet weather events where surcharging or overflows are known to occur were of particular interest. When the simulated hydraulic response of the model did not match the hydraulic signature, adjustments were made in the hydraulic model to properly represent observed flow conditions Likely adjustment needed in the upstream reach included adjustments to the inverts, weir elevations, pipe sizes, material roughness or sediment deposits. Throughout the conveyance network many of these issues were readily identified and then re-verified or adjusted in the model network until both signatures matched. An example of the how the graphs typically looked before the calibration can be seen in Figure 4 which shows the possible presence of debris in the surrounding area of the meter.

7 Figure 4: Base Model (Green) vs. Flow Meter (Blue) for Jefferson 05 Results: The reuse of historical flow monitoring data can effectively supplement more current data through incorporation of the scattergraph approach. This approach overcomes the limitations and potential pitfalls encountered when using only a time-series approach. This has significant implications for the archival, interpretation and reuse of historical data to inform system hydraulic response under varying conditions. Flow monitoring data collected for a specific project may have longer-term system diagnostic value to the organization. After adding each gravity segment back into the larger RHM, the final results showed significant improvement in the ability to simulate realistic flow conditions during significant wet weather events. Figure 5 is a scattergraph of the Jefferson 03 Flow Meter located directly upstream of the 26 th Street Siphon along the Jefferson Avenue gravity trunk line (See Figure 1). The orange data points for all four scattergraphs represent field measurements from the flow meter during the period of January 1, 2013 to February 26, 2013 and included a significant flow event. The blue points in each scattergraph represent model runs from the hydraulic model (Mike Urban 2011). Each graph represents different steps in the effort to calibrate the model and flow from left to right and top to bottom. The model points in the upper left scattergraph represent one of the selected representative flow events simulated in the base RHM model without any alterations made to the model while the model points in the lower right graph represent the final calibrated points from the study, Each graph in Figure 5 shows a major step taken in the calibration effort. The model points in the upper right graph represent the simulation of ten inches of sediment to the upstream pipe segment of the

8 Jefferson 03 flow meter. The model points in the lower left scattergraph represent corrections to the inverts or diameters of several portions of pipe in the Jefferson Avenue gravity sewer based on survey information. It also represents the plugging of one of the barrels in both triple barrel siphons, as well as, changing the sediment deposit depths along the entire gravity reach. The model points in the lower right scattergraph represent the placement of sediment in all three chambers of both siphons and the adjustment of sediment depth in portions of the Jefferson Avenue gravity sewer upstream and downstream of the Jefferson 03 flow meter. Figure 5: Jefferson 03 Flow Meter Location: Model (Blue) vs Field Measured (Orange) Results Figure 6 is a display of the before and after of the maximum simulated water depth at the peak of the wet weather event used in the model. This is represented by the dashed line in the graph. The most notable difference in the water level after calibration is at the most upstream siphon on the line. It is clear that after the addition of sediment to the siphon chamber, the model showed a noticeable increase in the headloss across the siphon. This response produced a more realistic representation of the surcharge conditions present during wet weather events in this gravity reach.

9 Figure 6: Profile of Mike Urban Results (Base Model vs. Calibrated Model) As is evident by each of the figures, the pattern of the data from the smaller gravity model developed for the evaluation closely matched that of the results taken from the RHM. Each of the gravity segments produced surcharging events where field observations had witnessed similar behavior in the system. In systems that have not significantly changed their main gravity network over time, it is possible to aggregate partial, reliable gravity flow monitoring data from different dates in time to extract the hydraulic signatures used in this analysis. More important, utilities can save money by using a significantly lesser number of flow monitors to cover large sewer networks by rotating and moving them to different critical locations that can enhance the hydraulic understanding of their system for a better and more realistic representation of their sewer system in a hydraulic model. Discussions/ Conclusions: A key consideration for utilities when using flow monitors is cost. In many cases, the necessary amount of flow monitoring needed to calibrate hydraulic models is not an option in the current budgetary climate. This can be especially problematic when trying to obtain reliable data for a sewer model. Many times during gravity flow monitoring, inconsistencies or errors can occur in the data. These inconsistencies can be the result of blockages, debris or improper calibration of the sensors, as well as, meters being taken out of service for regular maintenance or construction activities. These characteristics make large portions of collected flow monitoring data discontinuous in time. Fortunately, the techniques described in this study are able to handle the flow monitoring data independent of time and even allow for older data from previous monitoring efforts to assist in the characterization of the current hydraulic system. Using scattergraphs in this study proved to be an important tool for the examination of flow meter data. Utilizing this exploratory data analysis, or EDA method (Helsel & Hirsch, 2002), provided critical insight

10 about the hydraulic behavior of the conveyance system. As many already know, patterns found in flow monitoring data tended to be non-linear and compiling the information in scattergraphs present the dataset in a visual manner that reveal patterns not easily determined otherwise like those presented in Figure 5. Moreover, scattergraphs allowed for the leveraging of multiple, large datasets that many utilities like HRSD have gathered through decades of flow monitoring programs. These scattergraphs in conjunction with the Hydraulic Signatures provided significant flexibility when assembling the data and allowed for the use of any available, reliable flow monitoring data that was collected during significant rain events to be examined. The use of the Hydraulic Signature produced by the flow monitors in our study area allowed for an enhanced picture of how the conveyance system not only behaved during wet weather scenarios, but also in scenarios with less intense rainfall events. When placed in key locations these signatures can be used to calibrate large sections of gravity sewer and provide a more robust and accurate calibration than other methods. This approach allows for a quick and efficient comparison of the observed hydraulic signatures from specific gravity reaches with model derived result data. After adding each gravity segment back into the larger RHM, the final results showed significant improvement in the models ability to simulate realistic flow conditions during a larger range of flow conditions. When re-deployment of flow meters is not an option to characterize a hydraulic model, especially in areas with multiple meter sites, the use of scattergraphs and hydraulic signatures becomes increasingly important for the successful reuse of any historical flow meter data. With many utilities constantly looking for ways to not only save on regular overhead cost, but also unanticipated costs with constantly evolving permits, BC believes this approach to calibrating a hydraulic model for a RWWMP will result in a sharp reduction in the overall cost. Additionally, the return on investment dramatically goes up for flow monitoring with each additional use of the previously collected data and serves as model for how the life of this data can be extended. Works Cited ADS Environmental Services. (2014). Scattergraph Principles. Retrieved July 27, 2014, from ADS Environmental Services: Environmental Protection Agency. (2006). Graphical Representations. In E. P. Agency, Data Quality Assessment Statistical Methods for Practicioners (pp ). Washington, D.C.: Environmental Protection Agency. EPA. (n.d.). CADDIS Volume 4: Data Analysis. Retrieved July 20, 2014, from Exploratory Data Analysis: Hampton Roads Sanitation District. (2008). Gravity System Flow Monitoring Plan. Virginia Beach: Hampton Roads Sanitaton District. (2002). Graphical Data Analysis. In D. R. Helsel, & R. M. Hirsch, Statistical Methods in Water Resources. USGS. Retrieved July 19, 2014, from United States Geological Society: