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Jefferson County, Alabama - Leveraging Data Driven Approaches and Tools to Optimize CIP and Achieve Asset Management GoalsAbstractThe Jefferson County Commission (County) has been under an EPA Consent Decree (Decree) since 1996. One of the four primary objectives of the Decree is eliminating sanitary sewer overflows (SSOs). The Decree applies individually to each of the County's nine water reclamation facilities and their respective collection systems. The County has steadily improved system performance and refined its Capacity, Management, Operations, and Maintenance (CMOM) programs using a strategy based on asset management principles and supported with the best available tools to shape an effective and sustainable Capital Improvement Program. The County maintains a 3,100-mile collection system, and over the last ten years, the County has reduced SSOs from 9.8/100 miles in FY2014 down to 3.8/100. During this last 10-year period, the County has diligently worked to improve the management of the collection systems using condition assessments, risk-based prioritizations, asset deterioration models, hydraulic models, capital planning optimization with advanced algorithm solutions integrated with the hydraulic models, and related financial models. All the tools mentioned above have culminated in an affordable and effective forward-looking ten-year Capital Improvement Plan (CIP) that will continue to reduce SSOs. Root Cause Analyses: Performing a root cause analysis of each SSO event (what failed, where it failed, why and how it failed) has enabled the County to better adapt strategies to address the core problems in a holistic and systemwide manner while identifying and prioritizing corrective actions. Sanitary Sewer Modeling: One of the initial investments that the County made was to develop hydraulic models of all nine (9) sanitary sewer basins which included sewers 12-inches and larger and smaller sewers in areas with known SSOs. The models are all formally updated every five (5) years and are refined yearly based on post flow monitoring data in areas where rehabilitation occurs or other remedial measures are constructed. The existing systems are analyzed using the calibrated models under both dry and wet weather conditions to identify problem areas and evaluate potential solutions to address SSOs. Condition Assessment/Deterioration Model: Condition assessment was another tool that was used by the County to determine the expected remaining life of their assets. Using Markov Chain modeling, the County built a model that predicted the likelihood of PACP score deterioration for a pipe over time as a function of pipe age, material, prior inspection results, length and diameter, and other parameters. The deterioration model can be used to identify assets in need of upgrade or repair prior to failure to help prevent SSOs. The County currently uses the deterioration model to predict the asset renewal rate (now at 1.5% per year) needed to ensure that projects planned at that rate yield a sustainable system that fits within the allocated budget. Using the most recent PACP inspection score for each pipe, the model is used to simulate: -Ongoing pipe deterioration in the future, -Performance of future inspections on pipes whose risk of degradation becomes high, and -Performance of future repairs, rehabilitations, and upgrades (with corresponding score improvements) for those pipes found to have degraded. This approach, while not precisely predicting lifetime and failure of pipes on an individual basis, shows the impact of reinspection and renewal rate assumptions on system condition as a whole as well as the program costs of achieving those conditions. The approach confirmed the original assumption for a suitable asset renewal rate of 1.5% per year. Figure 1: Simulated PACP score distributions in future years resulting from modeled deterioration rates and assumed inspection and renewal rates. Figure 2: Simulated future annual inspection length and backlog under assumptions of maximum annual inspection budget and level of deterioration detected by those inspections. Optimization: Aging collection systems with asset condition and capacity deficiencies typically have a large range of improvement alternatives and planning scenarios available for analysis. Traditional 'trial-and-error' scenario modeling can handle only a relatively small number of scenarios and does not provide a comprehensive and defensible approach to evaluate the vast number of available alternatives. Intelligent algorithm optimization using OptimizerTM (software product of Optimatics) provides a framework for undertaking a comprehensive analysis of master plan alternatives that considers system-wide interactions and life-cycle costs. Optimizer links to the hydraulic model and detailed life-cycle cost data to evaluate many thousands of improvement alternatives. In a single analysis, cloud computing is used to run thousands of solution permutations to identify those solutions that meet the planning and performance criteria at least cost. Moreover, once formulated, the optimization model can be used to efficiently run scenarios and sensitivity analyses to develop alternate solutions with distinctly different characteristics. The RMP optimization framework is illustrated in Figure 3. Figure 3: RMP optimization framework using OptimizerTM Financial Model: Financial Model: The Jefferson County ESD Financial Model is guided by the Department's long-term planning goals and various financial performance targets. The model has been developed to evaluate projected revenues, expenses, debt service, and debt service coverage to determine the financial feasibility of the Department's projected operating expenses and ten-year CIP, including funding of remedial measures projects to address SSOs and needed investments for operational efficiency and reliability. The implementation of this financial model guides long range planning to ensure the County will be able to meet its debt obligations and establish a resilient and sustainable foundation for efficient and effective sewer service delivery throughout the forecast period and beyond. The combined use of these data-driven tools has allowed the County to develop Capital Improvement and O Hazen and Sawyer 2SourceProceedings of the Water Environment FederationDocument typeConference PaperPublisherWater Environment FederationPrint publication date Apr 2024DOI10.2175/193864718825159386Volume / Issue Content sourceCollection Systems and Stormwater ConferenceCopyright2024Word count19
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