Conference Papers

Purpose: The purpose of this presentation is to walk the audience through the process of increasing the capacity of a wet weather collection system and how this affects the sustainability of the system. The presentation will present the concepts of sustainability as defined in the ASCE MOP 151 Sustainable Design of Pipelines. Benefits of Presentation: There are several benefits to the industry that this presentation will provide. This presentation will provide a real-world project where the San Antonio Water System had to work through the process of increasing the capacity of a major interceptor through the historic and congested downtown area. This presentation will describe the options available and the deciding factors used for the ultimate solution. When faced with the requirement to increase capacity of a centralized gravity wastewater collection system, utilities have numerous options that can span the full range of costs, schedule, impacts to resources, customers, the environment, and to the public. The recently issued ASCE MOP 151 Sustainable Design of Pipelines publication provides an abundance of ideas for engineers and utilities to consider when designing and constructing a pipeline project to increase its sustainability and minimize its adverse impacts. As the San Antonio Water System (SAWS) Broadway Corridor Interceptor Improvement Project was recently placed into service, this provides an opportunity to compare the project to the precepts presented in ASCE MOP 151. There are multiple solutions available for designing an interceptor to handle both dry flows and wet weather flows. These solutions include inline and offline storage, upsizing, pumping, and parallel pipes (typically with one being the relief sewer). Each of these have their own unique hydraulic properties and requirements and influence the final design. This presentation will review the hydraulic characteristic of each solution and how this can affect the ultimate sustainability of the project. The hydraulics of a gravity sanitary sewer are of utmost importance to ensuring the proper operation of the system and long-term longevity and unimpeded service to the public. However, it is imperative that proper hydraulics is not the only or even the top-ranked factor used in determining the final solution. Status of Completion: Completed, operational since 2020 Conclusion: Many projects use a matrix to help consider other influences that could steer the decision-makers toward one solution or another. This is exactly the approach that SAWS and the design team used in determining the final solution for the Broadway Corridor Interceptor. ASCE MOP 151 provides a well-documented and step-by-step guide for scoring those influences that affect the sustainability and resiliency of pipeline projects. As laid out in the MOP, the areas that should be considered include pipeline materials, owner best practices, planning and design best practices, construction, operations and maintenance, and life-cycle analysis. This presentation will evaluate each of these areas and how the Broadway Corridor project measures up against each of these sustainability goals. With the updated Broadway Corridor Interceptor operational since 2020, this presentation will provide the audience with a real-world example of how projects can be designed more sustainably by applying the principles of MOP 151 during the planning and design phase and how important it is to continue the application of those principles through construction and operation to benefit the owner and community.

INTRODUCTION Sustainability is increasingly more important for the operation of wastewater treatment plants. To meet sustainability goals and better energy recovery, the current business as usual approach to anerobic digester operation is not ideal. Improving digester operation is crucial for effective energy recovery. Having a reactive approach to digester foaming prevents optimal digester performance and causes other problems like digester failure, poor biogas recovery, uncontrolled release of contaminated waste to the environment and odour. Figure 1 shows some of these impacts. The best way to mitigate digester foaming is through robust design, but if this is not possible there are several operating conditions that can be improved to control foaming. Sydney Water Corporation (SWC) recognised the importance of preventing anaerobic digester foaming. Digester foaming at SWC plants has been caused by multiple different issues and foam management can therefore be largely reactive. There are operational methods and digester design features in place at some plants that aim to reduce the occurrence of the impacts of foam events, however this is not widespread or consistent. Investigation into 5 plants was undertaken to determine the likely causes of digester foaming and gas entrainment and the most effective ways to manage this and where possible through design changes as upgrades occur. For plants where design changes are not possible in the near future, key operating conditions were reviewed, early warning signs for digester foaming events determined and management practices recommended to mitigate digester foaming. METHODOLOGY Digester foaming was investigated at 5 SWC Water Resource Recovery Plants (WRRP), including Cronulla, Malabar, Warriewood, West Hornsby and Hornsby Heights. Digester operation data was analysed to determine the likely causes of digester foaming issues and recommendations on proactive and reactive measures for foam management including how to prevent or mitigate foaming at these plants and across broader SWC plants were established and operator training provided. Digester operation parameters and recommended monitoring were also outlined. Best practice digester design to minimise foaming and maximise energy production was investigated, drawing on international experience. These design components were presented to SWC designers, along with recommended implementation methodologies. RESULTS The main issues causing digester foaming at the SWC plants investigated were seasonal foaming related to activated sludge processes, lack of effective redundancy or contingency measures associated with the digester process, and illegal industrial discharges to the incoming sewer. There are other fundamental operating issues that cause digester foaming, such as running with one digester offline for extended periods (for example, at 2 plants digesters were offline due to issues with digester lids, which resulted in excessive volatile solids load in remaining digester/s particularly when food waste was accepted), turning off mixing, high volatile solids loading rates in digesters, poor temperature control, unstable feed to the digesters, and large step changes in temperature and feed. Figure 2 shows the volatile solids (VS) loading rate and specific volatile solids loading rate (SVSLR) in the primary digester at one of the plants where primary and secondary digesters are currently operated in series. At this plant, there is inadequate solids retention time (SRT) in the digesters, as well as a high VS loading to the primary digester. The average VS load to the primary digester was 3.74 kgVS/m3.d and a peak loading rate of 4.5 kgVS/m3.d, where the recommended range is 1.6-3.2 kgVS/m3.d . Therefore, the anaerobic digesters are operated beyond the typical recommended VS loading rates. The high VS loading rate is also exacerbated by the unloading/loading sequence of flow, which results in intermittent VS loading, rather than constant loading across the day. The high VS load impacts the stability of the sludge and increases risk of foaming in the digesters. The SVSLR is a variation of VS loading rate that considers the VS in the digester as a function of active biomass. However, SVSLT may not account for the feedstock other than the wastewater sludge such as high strength organic matter. The maximum recommended SVSLR for mesophilic digestion without any pre-treatment is 0.16 kg VS/kg VS in digester day. As shown in Figure 1, along with the VS loading rate, the SVSLR for the primary digester is consistently above the recommended limit, making it vulnerable to the digester foaming and failure with fluctuation in digester loading rate. Best practice digester design to avoid foaming issues and maximise energy recovery include the use of standpipes for surface overflow (see Figure 2) and emergency withdrawal via p-traps (see Figure 3), minimisation of the top water surface area, installation of fixed covers and external gas storage, the use of pumped mixing to reduce short-circuiting and having adequate redundancy to ensure that there is no single point of failure. Digesters should have a conical shape to facilitate grit removal and more efficient mixing. Wasting foam from the surface in secondary activated sludge processes will also minimise the amount of trapped foam, improving conditions in the downstream digesters. Rolling out design changes in a systematic way as digesters are taken offline for planned maintenance is an effective way to facilitate continuous removal of foaming issues from upgraded digesters. In addition to benefits of maximising energy generation, achieving maximum hydraulic capacity within existing digesters by having external gas holders and running digesters full may allow capital upgrades of digesters to be delayed for a number of years if not decades, further improving sustainability of WRRPs. Where design changes cannot be implemented, there are operational improvements that can be made to manage digester foaming and increase energy production. Generally, if there are filamentous bacteria in the activated sludge bioreactor at a plant, there is a high likelihood of foaming in the digester. These foaming incidents are manageable through adjusting the operating parameters in the activated sludge plant. Digesters should be brought online slowly with small step increases in feed and temperature over time. A common misconception is that digester mixing should be turned off to control a foam event, however mixing should be turned down. Digesters should be operated with a top water level high into the lid, with sprays used to suppress foam and move foam to wasting points. Digested sludge should be withdrawn from the top and bottom of the digester, and consideration given to alkalinity correction when the pH in the digester starts to drop. Running the digesters without any safety factor and running some process equipment at loading rates higher than designed for will increase the risk of process upsets that could also contribute to foaming. Allowing a safety factor in terms of solids retention time and volatile solids loading provides plants with the ability to cope with under upset conditions and avoids the need to detune the digesters and the plant to minimise the risk of foaming. CONCLUSION By successfully managing digester foaming and operating digesters in a manner than maximises power generation, WRRPs can achieve more effective energy recovery and meeting energy sustainability and neutrality goals. Some fundamental issues that generally arose to cause digester foaming were: -Running with one digester offline for long periods resulting in much higher loadings and shorter SRT than originally designed -High VS loading rates in the digesters -Reduced effective SRT due to mixing being turned off and accumulation of grit and screening -Mixing generally not designed for current solids loading due to intensification -Poor temperature control for the digesters -Unstable feed to the digesters -Large step changes in temperature or feed due to heater failure or storm conditions Foaming subsequently resulted in lower biogas production, high costs for digester reinstatement, and poor run times on biogas engines due to poor biogas quality. Robust digester design which minimises digester foaming and gas entrainment is the most preferable management mechanism, and changes to digester components can be implemented over time as maintenance is undertaken. Where design changes are not possible, operational improvements can be made to greatly reduce digester foaming. This paper outlines some best practice measures that can save millions of dollars by avoiding catastrophic foaming events and will help maximise biogas production and energy generation.

Introduction: The open channels of Los Angeles County are prone to encroachments such as vegetation, encampments, and other objects that impede water flow. Routine inspections are required to identify and address encroachments. However, the traditional encroachment inspection approach includes an on-site survey conducted by engineers, which is both time intensive and incurs high labor costs. Figure 1 shows an example of a vegetation encroachment. Therefore, a new encroachment identification approach is developed in this paper, based on machine learning and remote sensing technologies. Remote sensing technology collects aerial images of reflectance measurements from different bands of the electromagnetic spectrum. Reflectance from target land cover classifications (e.g., vegetation encroachment, open channel, water, etc.) can be used as training data for a machine learning model. Once the machine learning model is trained, it can then be applied to reflectance measurements across a given area of interest to identify encroachment on a pixel-by-pixel basis. Most machine learning algorithms require robust training data datasets in order to reach satisfactory model performance. In this paper, 10 open channel section aerial photos were collected and labeled by the Stantec project team, resulting in about 20 million total pixels to be used as training points. The model is trained on those 10 open channel section aerial photos, with each photo containing four bands (red, green, blue, and near infrared). The model prediction performance is evaluated by accuracy, F1-score, and encroachment class recall values. The preliminary results indicate that the model can reach an overall 74% prediction accuracy with 0.51 F1-score. Around 73% of the vegetation encroachments in the original photos were correctly captured by model predictions. Methodology: The data used for training the machine learning model includes 10 open-channel section aerial images in Tag Image File Format (TIFF). TIFF files were acquired from the Los Angeles Region Imagery Acquisition Consortium (LARIAC) Program. TIFF images store pixel values (e.g., different reflectance values for each wavelength band measured) and geo-reference information. The pixel size is 0.25 by 0.25 ft. Figure 2 shows an example of the training data, where Figure 2a) shows the original aerial image and Figure 2b) shows the pixels designated as Clean Dry Open Channel pixels. The original aerial data need to be labeled for downstream analysis. Imagery pixels were labeled as one of five potential classifications. The five classifications included: 1) Clean Dry Channel, 2) Clean Wet Channel, 3) Others, 4) Overhead Structure, and 5) Vegetation, as shown in Table 1. Labels were created by visually identifying the five different classifications from imagery and manually drawing polygons around the different classes with a GIS software. Figure 3 is an example showing partial polygons drawn for an aerial image. The TIFF images used in this study contained the reflectance values from four bands of the electromagnetic spectrum: red, green, blue, and near infrared. Band values range from 0 to 255, representing the brightness value for each band. Figure 4 provides an illustrative example of different bands. The four individual reflectance bands will serve as four features in the machine learning model. In addition to using reflectance from each individual band, we also calculated indices from these bands and included them as features in the model as well. The creation of new features, also known as 'feature engineering', is often required in machine learning. Many indices are used in remote sensing to help identify different land cover types based on the unique reflectance patterns they have. In this project, we will use four remote sensing indices: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI), and Normalized Difference Water Index (NDWI). Classification and Regression Trees (CART) is selected as the machine learning model in this project because it is able to explain how a target variable's value (label) can be predicted based on other values (features). Model Results: One training image is chosen to evaluate the model performance on training data. Figure 5 shows the comparison between the true label (a) and the predicted label from the model (b). For all five classes, the predictions closely align with the actual labels. The Vegetation and Overhead structure pixel crowds are well captured. The training metrics are calculated as 81% accuracy, 0.55 F1 score, 0.86 Vegetation recall, and 0.92 Others recall. Although the training metrics cannot be the sole indicators of model performance, they can still illustrate how well the model performs and demonstrates its potential to be powerful on the test dataset. The model is also evaluated on a single test image. The confusion matrix result is shown in Figure 6. The test metrics are calculated as 74% accuracy, 0.51 F1-score, 0.73 vegetation recall, and 0.18 Others recall. In this section, all the test data come from the same TIFF image, we are able to visualize and compare the predictions vs. true labels. Figure 7 shows the test image labeled using the true labels, predicted labels, real TIFF data, and real vegetation class polygons in subfigures a), b), c) and d) respectively. Comparing subfigures a) and b), it is shown that class 1 (Clean Dry Channel) and class 2 (Clean Wet channel) are predicted well, while class 4 (Overhead structure) is partially captured. Since class 5 (Vegetation) is hard to see in the true label plot due to the overlap with class 2 (Clean Wet channel) label, subfigures c) and d) are included. Subfigure d) is based on the true TIFF image c), where polygons of vegetation class are drawn and visible. Most of the true vegetation pixels are in the middle of the channel, which is reflected in the prediction figure subfigure b). The model fails to capture the Others class (class 3) very well, as illustrated in the low recall value. In fact, a high Other recall on training data (0.92) and a low Other recall on test data (0.18) indicates that the model has potential but requires more information on the Others class (such as the type of encroachment). However, the vegetation encroachment can be predicted fairly well. Conclusions: The objective of this paper is to develop a machine learning model to automatically identify vegetation encroachments in open channels in Los Angeles County. The machine learning model developed is based on the CART model, which is a simple white box model that can handle complex data. The model is trained on 10 open channel section aerial images, where each image contains four bands (red, green, blue, and near infrared) in the TIFF file format and has been manually labeled using polygons to categorize each pixel into an encroachment class. The model prediction performance is evaluated using accuracy, F1-score, and encroachment class recall values. The preliminary results indicate that the model can reach an overall 74% prediction accuracy with a 0.51 F1-score. In addition, the Vegetation class recall score means that 73% of the vegetation encroachments in the original photos can be correctly captured by model predictions.

There is an increasing emphasis on the impact of volatile gaseous emissions from area sources such as anaerobic treatment ponds, biosolids treatment processes, feedlot pads, compost windrows, and municipal wastewater sites, due to the concerns related to malodors, greenhouse gases, micropollutants, or bioaerosols. The estimation of emission rates are critical to support the assessment of environmental and social impacts such as nuisance and human health as well as climate change. Emission sampling is an essential stage in determining emission rates, where sampling methods seek to simulate the real emission scenarios. In a previous review (Liu et al. 2022), the benefits and disadvantages of a series of sampling methods (flux chamber, wind tunnel, static chamber, headspace methods) were compiled. The review showed there was lack of the understanding of the role of sampling methods, creating difficulties for industries or users in the analysis and interpretation of the emission data. Flux chambers are a commonly used method, due to the presence of standards, ease of operation and perception as a method that simulates real-world emissions. During method development, flux chambers were extensively tested to assess the impact of operational factors such as flushing rate and placement depth, however, experimental implications of different designs of flux chambers were limited. Based on the finding by Hudson and Ayoko (2008), 19 called flux chamber cylindrical devices were found out of 76 dynamic devices, while only 5 of 19 shared the same design in terms of dimension and operating system (Gholson et al. 1991, Sarwar et al. 2005). Such differences in design, limits the comparison of data and the establishment of an emission model for evaluating emission from area sources such as biosolids storage and application sites. In this research, four different flux chambers were used to measure the volatile emission rate from porous media using typical operating conditions (Table1). The comparison of flux chambers took into account inlet gas distribution system, chamber materials and variations in hood dimensions. The sweep gas flow rate in the chamber was varied from 1 L/min to 5 L/min. The results were interpreted using the relationship between gas velocity, turbulence intensity and the physical design of the device. Chamber II was set up based on the U.S. EPA flux chamber design (Kienbusch 1986) and tested as a benchmark. The emission rate measured using chamber III, which was duplicated from chamber II, showed 20%-60% variations, indicating the necessity of calibrations for each flux chamber before use. Compared to chamber II, variations of sweep air flow rate in chamber IV showed less effect on changes in the emission rate. However, the overall emission rate from chamber IV was higher, e.g. 103% higher at 1L/min flow rate. This difference was attributed to altered sweep gas jet direction which affects the circulation of sweep gas over the area surface and generated turbulence. To verify the hypothesis that sweep gas direction can affect the emission rate, axially vertical jets of sweep gas were used in chamber IV resulting in a higher emission rate compared to chamber II, while the increased number of jets further increased the measured emission rate (chamber I). The study findings emphasised the importance using a standardised flux chamber configuration, while linking the inlet gas distribution setups to recirculation motion in the chamber as well as the effects on emission rates from porous media. This is in agreement with prior studies conducted using CFD on liquid surfaces (Andreao et al. 2019). The outcome of this study will contribute to the more consistent use of flux chamber within which consistent, reproducible conditions could be established.

The Stormwater Management Program (SMP) is a Johnson County, Kansas program which partners with the 20 cities in the County to manage stormwater and is funded by a 1/10th of one percent, county-wide sales tax. It administers these funds on behalf of the Cities, historically by providing matching funds to Cities for eligible projects, including study, design, and construction projects. In 2016, SMP as part of new strategic asset management program implemented watershed-based approach to fund projects that incorporate flooding, water quality, and system management. Under 'System Management' program, SMP started funding inspection, rehabilitation, and replacement of stormwater asset projects. As part of this program, SMP developed a risk-based tool to prioritize stormwater assets. This tool is used to assign a prioritization score to all eligible assets contained in County-wide asset database. This prioritization score is calculated using Likelihood of Failure (LoF), Consequence of Failure (CoF), and total risk (Business Risk Score, BRE). The two fundamental building blocks for defining total risk (BRE) are LoF and CoF. LoF describes the chance of an asset failure occurring and CoF measures the severity of the impacts if an asset were to fail. Total Risk or BRE = LoF * CoF Currently, SMP employs a linear age-based degradation model and incorporates an adjustment factor for increased salt load in estimating LoF. to prioritize inspection of stormwater assets (hard assets). For rehab/replacement projects, field verified condition score is used. However, existing field verified condition rating systems like the National Association of Sewer Service Companies' (NASSCO) Pipeline Assessment and Certification Program (PACP) and Water Resource Commission (WRC) were initially developed for wastewater systems. These standard ratings do not capture the environment factors and other variables specific to stormwater pipes. Currently, no standardized methods exist for assessing the condition of stormwater pipes and structures in the U.S. Given these challenges, SMP engaged with NEER to utilize its cloud-based Machine Learning (ML) solution to identify the risk condition of the stormwater assets and implement a proactive data driven asset management program. As a part of this project, NEER developed a Machine Learning (ML) Model that is specific to Johnson County SMP to calculate LoF for all the hard assets such as inlets, junction boxes, bridges, culverts, enclosed gravity. All of these assets are represented either as Links or Nodes. During the ML model creation, all the data obtained from AIMS and local municipalities (physical, functional/operational) were standardized. The NEER team developed micro-ML models to populate several missing parameters for few nodes and links. In addition, several environmental parameters were also superimposed to the existing datasets. After the normalization of the datasets, the original datasets (113,124 links and 122,957 nodes) that had field verified conditions were selected for model training and validation. There were 39,814 links (35% of total links) and 44,600 nodes (36% of total nodes) that had field verified conditions. NEER was able to develop a best performing ML model using 80% of the data (field verified conditions data) for model training and the rest of the 20% of the data (field verified conditions data) for model validation. This ML model is able to predict LoF with an accuracy of 90% & 91% respectively for the existing nodes and links. This SMP specific LoF prediction ML model was configured to continuously train and optimize itself to improve accuracy over time. NEER also adopted the same methodology that is currently being used by SMP to calculate the CoF and Business Risk Exposure (BRE)/Total Risk score. This CoF and BRE/Total Risk score calculation was implemented in the NEER Platform, so that SMP can calculate CoF and BRE/Total Risk for each asset in Watershed Organization 1.

There is a need for a framework to mainstream citizen engagement, increase Transparency and boost Communication channels in case of repeated episodes of impact in neighboring communities. When there is a conflict, most crisis communication experts agree that Engagement, Transparency, and Communication (E&T&C) are key to maintaining or regaining the neighbors' trust. The Volkswagen emissions scandal is a recent case demonstrating the negative outcome of not having an Engagement, Transparency, and Communication Policy. To promote a change in the traditional industrial opaque thinking paradigm, we have created the first E&T&C Certification. This Certification is designed to assess the performance of Water Resource Recovery Facilities concerning their relationship with communities nearby, making it the first Certification of its kind. A project's performance is verified through 'third-party' audits by an independent auditor, depending on the degree of depth of analysis. This third-party Certification guarantees independence and impartiality in the process. The ultimate goal is to score the degree of a Water Resource Recovery Facility's Transparency, Communication, and Participation.

Many New England communities are undergoing flow restoration efforts to improve the health of impaired waterbodies. One such waterbody is Englesby Brook, which drains an area of approximately 605 acres in Vermont's Burlington Bay watershed before flowing into Lake Champlain. Englesby Brook was designated as a stormwater-impaired watershed on the 2006 Vermont 303(d) list due to multiple impacts associated with excess stormwater runoff [1]. A Total Maximum Daily Load (TMDL) target was subsequently released, requiring an 11.2% increase in stream flows during low flow conditions and a 34.4% reduction in flows during the 1 year 24 hour storm event. To improve stream health in Englesby Brook, the City of Burlington Department of Public Works planned a number of stormwater projects. One such project was the retrofit of a stormwater basin called '08 Pond', a wet detention pond collecting runoff from 131.5 acres (21.7% of the Englesby Brook watershed). The proposed retrofit would have included expanding the existing pond footprint, excavating below the pond bottom, and creating additional storage above the existing permanent pool at an estimated 2015 cost of $400,000. This proposed project was estimated to reduce peak discharge from the pond by 63.4% for the 1 year storm [1]. However, recent advances in communications and control technology provided an alternative to this traditional expansion retrofit. To optimize flow through the 08 Pond, the City of Burlington decided to enhance the basin with continuous monitoring and adaptive control (CMAC) technology. CMAC systems leverage real-time site data, the weather forecast, cloud-based software, and flow controls (e.g., actuated valves) to predictively control the timing and rate of flow through stormwater facilities [2]. At 08 Pond, CMAC automatically draws down the pond below the normal pool in advance of storms, allows the pond to fill up targeting zero discharge during events, and performs a post-storm release. Model results show an up-to 80% reduction in peak discharge during the 1-year storm is possible through the use of CMAC at 08 Pond. Anticipated CMAC costs in early 2020 totaled $98,000. Following the retrofit completion in May, 2022 the City will have invested $105,000 to facilitate the installation of this innovative CMAC system. Data from a set of storms totaling 1.63 inches of rainfall in seven days at 08 Pond is shown in Figure 2. Englesby Brook 08 Pond is the second CMAC system in the City of Burlington. The first was the enhancement of an underground detention vault at the Greater Burlington YMCA in 2020. During an analysis period of 3/1/2020 through 11/1/2020, this project retained 70.2% of the stormwater volume during critical wet weather periods, compared to only 16.8% stormwater capture simulated for an identical passive detention system. This presentation will discuss how Burlington is working towards stormwater impaired waters flow restoration and parallel water quality requirements, the background for the Englesby Brook 08 Pond project and highlight aspects of the design, construction, and software configuration. Performance results will be shared for both the 08 Pond and YMCA CMAC projects.

Water and Wastewater Utilities operate in a constantly changing environment. Regulations, funding availability, utility workforce, and environmental conditions are all constantly changing and impact the needs and capabilities of utilities. However, despite the changing conditions, it is important to stay focused on long term utilities goals and objectives. By setting strategic goals, and employing a continuous improvement approach, (Plan-Do-Check-Act) organizations can become more resilient in pursing long-term goals and gain the ability to pivot when their operating environment changes. Winston-Salem/Forsyth County (WSFC) Utilities has made a long-term commitment to reducing SSOs and optimizing their collection system operations. In 2014 the US EPA issued a Letter of Violation citing poor collection system performance. In response to that, the Collection System Improvement Program (CSIP) was developed to improve operational and regulatory performance of the collection system. The PLAN Phase: Utility leadership established six high level objectives to guide utility actions in improving collection system performance. A detailed roadmap of specific actions was developed to make initial steps toward these goals. The DO Phase: The Utility completed initial studies, tool developments, and implemented the steps in the long-term road map to make first steps toward these goals. The CSIP program resulted in the dismissal of the pending EPA case, but that was not the end of WSFC Utilities commitment to improving collection system performance and focusing on those original long-term goals. The CHECK Phase: The environment had changed along the way. The Utility has experienced hiring freezes, staff shortages, and pandemic conditions. In addition to these phenomenon, the recent weather patterns have resulted in never-before seen levels of Inflow and Infiltration (I&I) of the collection system. The associated flows were now beginning to stress WWTP operations. The ACT Phase: The utility has decided to implement a comprehensive flow monitoring approach to address the high levels of I&I. In response to other changes in the operating environment the utility has also undertaken an extensive maturity and gap assessment to revisit the long-term goals and operational objectives of the collection system program. The result is a new set of initiatives (or roadmap) to establish a sustainable and long-term approach for the future of the collection system operations. This will include the specific tactics needed to continue to make progress towards the latest strategic goals for the program. Following this continuous improvement cycle has allowed for WSFC Utilities to realize over a 40% reduction in SSO events since the start of the CSIP. This has translated to the dismissal of the open EPA case against the utility without regulatory action in 2019. These results represent a significant milestone for the CSIP, but not an endpoint. New regulatory drivers we're surfacing including high peak flows at WWTPs because of I/I within the collection system. Using the continuous improvement framework, the CSIP was able to adapt to this change. Existing programs and activities we're able to be modified to address this new program driver and provide continued value to the utility without the formation of a new or different program. WSFC Utilities was able to use exiting condition assessment data, maintence observations, and flow information to model and understand I/I risk within the wastewater collection system. This information was then used to reprioritize further inspection and rehabilitation work to address this new concern. By adapting program activities to address new and emerging risks, WSFC Utilities has increased the resiliency of their operation. This has allowed the progress and accomplishments of the past to be leveraged to address the problems of the future. By implementing a cycle of continuous improvement, WSFC Utilities has been able to achieve short term goals while continuing to pursue a long-term mission and vision. Other organizations can learn from this example how to adapt to a changing operating environment in ways that deliver value to their staff, ratepayers, and communities.

Utilities around the world have navigated the challenges of the global pandemic by working collaboratively and taking new approaches to delivering on their organizational mission. Some are seeking ways to shift from near-term agility to long-term resiliency and sustainability. Washington Suburban Sanitary Commission's (WSSC Water) Strategy and Innovation Office (SIO) worked with their cross-departmental New Normal Taskforce (Taskforce) to think beyond the current challenges to examine emerging challenges and opportunities. Using scenario planning and virtual forums, the SIO and Taskforce identified six key business opportunity areas for investment that build from pandemic-driven insights and will position WSSC Water for success across a variety of potential futures. This effort demonstrated WSSC Water's ability to leverage crisis-based momentum and internal partnerships to move beyond near-term shocks to build resiliency for the future. WSSC Water is currently among the largest water and wastewater utilities in the nation, with a network of nearly 6,000 miles of water pipeline and over 5,600 miles of sewer pipeline. Their service areas span nearly 1,000 square miles in Maryland's Prince George's and Montgomery counties. They serve 1.8 million residents through approximately 475,000 customer accounts. Guided by their vision to be the world-class water utility 'where excellent products and services are always on tap' and commitment to ethical, sustainable, and financially responsible service led WSSC Water to form the Strategy and Innovation Office (SIO). The SIO is charged with accelerating organizational performance through strategic planning and execution, knowledge management, and organizational effectiveness. The SIO is made up of the Office of Innovation and Research, Strategic Performance Office, and Enterprise Risk Team. The Office of Innovation and Research is responsible for finding and accelerating new technologies and processes that reduce operating expenses, increase safe work practices, improve sustainability and create new revenue opportunities. The Strategic Performance Office leads strategic business planning, data analysis and process improvements. Enterprise Risk spearheads business risk assessments and mitigation planning to minimize challenges to implementation of WSSC Water's strategic business plan. The New Normal Taskforce was formed as a cross-departmental team to identify and address challenges associated with the global pandemic and operational challenges. The Taskforce included the SIO as well as representatives from human resources, asset management, diversity and inclusion, police and homeland security, finance, production and utility services departments. Throughout the pandemic, the Taskforce reviewed working conditions, business practices, and technologies to identify concepts to permanently adopt into post-pandemic operations. Arcadis was retained to facilitate a series of virtual sessions to engage the SIO and Taskforce in examining the emerging opportunities and challenges post-pandemic recovery plus ten years. This longer view was used to move beyond the current context and challenges of the pandemic to identify and to better position WSSC Water for long-term success. A key tactic in this exercise was scenario planning. Scenario planning is a method of using uncertainty in plan development and decision making. By using this tactic, leaders can make decisions or adopt strategies that play out well across several possible futures resulting in more resilient business plans. The WSSC Water-Arcadis team held a series of virtual workshops built on the key steps to scenario planning. First, the team developed framing questions that identified the most pressing challenges or questions facing WSSC Water. These questions included complex long-term topics (e.g., digital transformation, affordability, workforce development, community understanding) that do not have established or discrete solutions. The framing questions were used throughout the workshops to keep discussion anchored in the practical challenges of the utility. Second, the team developed and evaluated key national and regional trends that are outside the control of the organization but impact their decision-making. This analysis involved deep dives into nine trend areas including advanced asset management, alternative energy technologies, climate change, policy and governance, contaminants of emerging concern, customer expectations, intelligent water, revenue and pricing, as well as workforce development and upskilling. From these trends, the team selected two key themes to develop a scenario compass and four alternative future scenarios for use in the idea development sessions. Using a world café format and collaborative virtual platform, the team examined each alternative future scenario and generated ideas that leveraged existing resources to address each of the framing questions. Discussions included approaches to improve infrastructure management, operational efficiency, business continuity, workforce development, customer experience, and digital transformation. From these discussions, idea themes were identified and consolidated into potential innovation investment areas. Over 600 individual ideas were contributed through the virtual sessions which were consolidated into 19 primary idea themes. These themes were later grouped into six research and innovation investment areas including customer experience, infrastructure, stakeholders, operations, sustainability, and data & digital. Within each of these areas, the specific ideas were sequenced across three priority horizons: H1 — enhancing existing core functions, H2 — adopting new functions from partner or adjacent industry, and H3 — novel function or future aspirations. These horizon maps provide a roadmap for general exploration by the SIO. Lastly, using the six investment areas, the team developed tailored roadmaps for innovation investments regarding each framing question. The SIO will use the roadmaps to develop a strategy to assist WSSC Water leadership with investment in near-term innovation with long-term impact and reduction of risk posed by uncertainty. They will use the investment areas to assess and prioritize new ideas and technologies as well as guide decisions regarding resource allocations. The horizons within each investment area help set a cadence for needs assessments and functional requirements for external partnerships. Further, the collaboratively developed focus areas identify cross-departmental support and resources needed to implement these strategies. Lastly, the exercise provides SIO with a number of tactics that will support review of trends and alternative futures. As trends change, the updated roadmaps will provide a framework to guide revisions to investment areas or sequencing to improve organizational resiliency. In this presentation, our team will walk through WSSC Water's experience and outcomes. Participants will learn the fundamentals for applying planning tactics to leverage uncertainty and lessons learned during the pandemic to identify investment areas that will support long-term organizational resiliency.

Public water agencies throughout the United States face many challenges with extending the reliable service life of their aging buried infrastructure. The San Jose/Santa Clara Regional Wastewater Facility (RWF) has the capacity to treat approximately 200mgd, with ongoing projects expanding this number. It is located in the City of San Jose (City) and has approximately 67,000 linear feet (LF) of buried wastewater process pipes, many of which were installed in the '50s and '60s and thus have exceeded their design life. Because of the potential terminal condition for some RWF piping, the City is using this Project to increase operational reliability and mitigate the likelihood of failure of their existing buried linear assets. If selected, the purpose of this presentation would be to share BV and the City of San Jose's approach to a large-scale piping condition assessment and rehabilitation effort. The presentation would include a description of the risk tool that BV developed exclusively for this project, condition assessment methods that were implemented, and rehabilitation methods that were selected. Fortunately for these agencies, many viable pipe rehabilitation methods have been invented to date, and there are often large pools of contractors vying for the job. Unfortunately for these agencies, there is rarely a platform available to share feedback or lessons learned from prior projects, even between neighboring cities. Furthermore, it is rare for an agency to embark on such a large, comprehensive project. Therefore, the largest benefit of this presentation would be the ability to share BV and the City's approach to delivering an on-time/under budget project, which started with developing a piping inspection prioritization tool and ended with rehabilitating pipes to provide an additional 50-year service life. In 2018, the City retained Black & Veatch (BV) for the Yard Piping Improvements Project (Project) to systematically assess all buried process pipes 8 inches to 144 inches at the RWF, which equates to approximately 60,000 LF of piping. Pipes at the RWF are comprised of many materials, but are primarily made of either reinforced concrete, ductile iron, or welded steel. The focus of the multi-year Project is to repair, rehabilitate, or replace (R/R/R) pipes, or portions of pipes, that are highest priority by virtue of their criticality and/or observed physical condition. In 2015, as part of a separate project, BV developed a condition assessment plan that provided a prioritized list of critical pipes for inspection, inspection protocol recommendations, and end of life estimates. The plan used weighted risk factors to determine the LOF (likelihood of failure) and COF (consequence of failure) for each assessed pipe. Depending upon identified pipe risk, inspection protocols and desired levels of inspection detail were determined for each pipeline. The final report produced in 2015 has served as the technical basis for the current Yard Piping Improvements Project, and the recommendations provided in that initial report have largely been followed. To date, approximately 36,000 LF of primary and secondary treatment piping has been inspected. Following each inspection, BV reviews the resultant condition data and makes R/R/R recommendations based on the findings. The Project follows an annual cyclical schedule whereby pipes are inspected during the regional dry-weather season, design work based upon these inspections occurs during the wet weather season, and R/R/R construction proceeds in the next dry-weather season. There is a separate service order for each year's pipe rehabilitation design, and a design-bid-build (DBB) project model is followed for each service order. Approximately 2,200 LF of the 36,000 LF inspected to date was identified to have severe deficiencies requiring R/R/R, and these pipe segments have since been rehabilitated. The scope for the first pipe rehabilitation service order contained primary effluent 96-inch reinforced concrete pipe (RCP) and an elliptical 87x136-inchpipeline. Beginning in the '50s, the RWF has slowly expanded to add more effective treatment processes and to increase the overall plant capacity. As a result of this expansion, there are many buried crossing utilities that preclude the feasibility of applying many traditional rehabilitation methods, resulting in a trenchless method focus. Ultimately, the 96' pipeline was rehabilitated with CIPP, and the 87'x136' was rehabilitated using a combination of concrete crown restoration with geopolymer material with an epoxy top coating. The second pipe rehabilitation service order, which is currently in the design phase, contains more primary effluent RCP including 78-inch, 96-inch, and 84-inch pipeline. CIPP was selected as a rehabilitation method for both the 78-inch and 96-inch pipelines, and concrete crown repair with a with an epoxy top coating selected for the 84-inch pipeline. The overall project is scheduled to be completed in 2026, with phases completed each year. The presentation of the Project, which has never been presented at a WEF Collections Conference to date, will focus on condition and risk assessment, selection of inspection methods and applications, the criteria against which rehabilitation alternatives are compared, planning and successfully executing pipeline rehabilitation.

INTRODUCTION The Saddle Creek Retention Treatment Basin (RTB) is a significant project as part of the City of Omaha's water quality program 'Clean Solutions for Omaha' to address compliance with their Long Term Control Plan to address combined sewer overflows. Prior to the construction of the facility, over 65 times per year, untreated combined sewage overflowed into the Little Papillion Creek (LPC) from the City's CSO 205 outfall structure. With the new facility in place, combined sewage will be diverted to the RTB to receive grit and screenings removal, disinfection, solids settling, and dechlorination before being discharged back to LPC. The Saddle Creek RTB project began planning and design activities in April of 2011. Construction commenced in Spring 2019 and is anticipated to start operations in the summer of 2023. This facility will provide storage and equivalent to primary treatment of combined sewage flows up to the permitted design flow rate of 160 million gallons per day (MGD) with the ability to screen, remove grit, and disinfect flows up to 320 MGD. Lower volume flows will be captured within the basin and will be pumped into the Little Papillion Creek Interceptor (LPCI) and conveyed to the Papillion Creek Water Resource Reclamation Facility (PCWRRF) for full secondary treatment. Larger volume flows will receive grit and screenings removal, disinfection, solids settling, and dechlorination before being discharged to the LPC. The facility will result in a significant reduction in the volume of untreated CSO, total suspended solids (TSS), and E coli bacteria entering the LPC. This presentation will describe how the Saddle Creek RTB will effectively and reliably capture and treat untreated combined sewage in compliance with regulatory requirements. FACILITY OVERVIEW The Saddle Creek RTB facility consists of a 3.3 million gallon (MG) underground concrete storage basin, with grit removal, mechanical screening, chemical disinfection, gravity effluent discharge, a dewatering pump station, as well as Headworks, Operations, and Chemical Buildings. The facility also includes a diversion structure, sewers, odor control, stormwater BMPs, driveways, and other appurtenances. Refer to Figure 1 for a Process Flow Diagram illustrating the various features of the RTB facility below ground. The facility operates during wet weather events. Prior to the completion of the Saddle Creek RTB project, an existing dry weather diversion weir directed dry weather and a portion of wet weather flow, up to 40 million gallons per day (MGD), was sent to the existing Dupont Grit Facility and ultimately to the LPCI. Prior to this project, any excess flow was discharged untreated to the CSO 205 Channel and eventually the LPC. The existing dry weather diversion pipes will be abandoned as part of this project and replaced with a new 60-inch sewer which will pass through a grit pit within the new facility's Headworks Building. The diversion weir will send flows using real time control and smart sewer technology to provide gate control of up to approximately 60 MGD to the LPCI before overflowing into the RTB influent sewer. This new diversion chamber will divert wet weather flow up to the peak treatment design flow of 160 MGD to the RTB. This diversion chamber configuration ensures that flow rates up to the design flow can pass through the RTB and does not increase the risk of upstream flooding during larger events. Captured volume in the tank will be pumped into the LPCI and conveyed to the Papillion Creek Water Resource Recovery Facility (PCWRRF) for full secondary treatment. Flows more than the facility capacity will be routed around the RTB and discharged into the LPC. Dry weather flow and some wet weather flows up to approximately 60 MGD will pass into a new grit pit, the diversion flow grit pit, constructed in the proposed Headworks Building. For flows passing through the RTB, large grit and other heavy materials will drop out via gravity into a second, larger grit pit, the RTB grit pit, prior to entering the screen channels. Downstream of the RTB grit pit, mechanically cleaned screens will provide for the removal of objectionable solids with the intent of protecting downstream equipment and controlling floatables. The facility includes three (3) continuous duty multi-rake screens with a clear opening size of ¾-inch. Disinfection must result in an effluent that meets E. coli and total residual chlorine (TRC) permit limits. Liquid sodium hypochlorite and sodium bisulfite will be used for disinfection and dechlorination. Above ground improvements include a building to house controls, grit and screening equipment, and chemicals. Refer to Figure 2 for a rendering of the finished facility. PROJECT COMPLETION STATUS In December 2018, the City received bids within the budget for the project and in February 2019, a contract valued at approximately $90 million was approved to build the Saddle Creek Retention Treatment Basin facility. Construction began in April 2019. Wade Trim performed design engineering on the project and is currently providing construction management services. The project is scheduled for Substantial Completion in Spring 2023. Refer to Figures 3 and 4 for construction progress photos. CONCLUSIONS The project's innovative use of a 'gravity in, gravity out' design for the RTB facility allowed for a reduction in pumping of significant flows. The use of real time controls and smart sewer technology will allow this facility to operate efficiently and effectively over a wide range of conditions, which have been evaluated through extensive hydraulic modeling and development of process control strategies. The use of instrumentation for flow and level measurement used in process control must incorporate redundancy and be flexible to allow for changes in available technology and must be compatible with other technologies being used at the facility and within the collection and treatment system.

The Stormwater Management Program (SMP) is a Johnson County, Kansas program which partners with the 20 cities in the County to manage stormwater and is funded by a 1/10th of one percent, county-wide sales tax. It administers these funds on behalf of the Cities, historically by providing matching funds to Cities for eligible projects, including study, design, and construction projects. SMP has invested significantly on StormWatch Alert 2 systems (www.stormwatch.com) over the past 30 years to implement real-time early flood warning systems. SMP has funded the installation and maintenance of many of the sites throughout the region and has utilized the data generated from the system for SMP-sponsored studies and projects. SMP also funds a portion of the cost to maintain and improve the website. Johnson County owns 68 of the 108 sites in the system. In addition, City of Overland Park, Kansas Department of Transportation, and City of Kansas City, MO owns several sensors. Currently, SMP with the help of City of Overland Park uses manual process of forecasting flooding conditions and implements emergency management procedures within the county based on existing stream level and National Weather Service's forecasted weather information. However, this process is very tedious, time consuming and not reliable to accurately forecast future flood conditions. Given these challenges, SMP engaged with NEER for the pilot study to utilize its cloud-based Machine Learning (ML) solution to automatically forecast early flood warning system (up to 24 hours) for the Watershed Organization 1 using existing hydraulic models and StormWatch real time datasets. NEER obtained existing HEC-1 and HEC-RAS models from FEMA for Watershed Organization 1. After verifying the integrity of the models, NEER converted existing HEC-1 and HEC-RAS models into EPA-SWMM model. During the conversion process, NEER followed the standard engineering practices to update the existing hydrology (subbasin and storage data) and hydraulic (open channel geometry, culverts, and bridge data) characteristics. After updating all the parameters, the hydraulic model was calibrated using StormWatch gage data collected during 2016 to 2020. There are a variety of statistical measures used to measure the goodness-of-fit between a long term continuous measured and a modeled hydrograph. For this study, statistical measures Integral Square Error (ISE) and Nash'Sutcliffe efficiency (NSE) were used as a single, non-subjective, statistical measure of model calibration (https://www.chijournal.org/C414). Generally, calibration results showed very good to excellent NSE and ISE range for all the gage locations. After the calibration, NEER set up a continuous real time and forecasting stormwater simulation model. In this step, StormWatch gage data (rainfall and stage collected every 5 minute) was obtained and stored in a Time Series Database. In addition, the 24-hour forecasted rainfall data obtained from the National Weather Service was also used in forecasting the stage and water surface elevation along the Brush and Turkey Creek. This real time and forecasting model that is scheduled to run every 6 hours, provides a predicted and forecasted floodplain boundary, depth grid, water surface elevation grid, velocity grid, and flood severity grid. that can be used for operational decisions. The total number of buildings and roads flooded, and operational recommendations (such as closing of roads, and evacuation of buildings) for every 6 hours is stored and displayed in the dashboard.