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Maximizing Affortable Housing with Minimal Water Environment Impacts--Innovative Pilot for ChristChurch, New ZealandAbstractPURPOSE This paper presents an innovative, first-of-its kind in Australia and New Zealand, application of intelligent algorithm optimization to evaluate urban development alternatives and identify specific regions within the city that can accommodate growth with minimal impact to the performance of the wastewater network. The existing wastewater network has wet weather overflows that exceed consent targets. Interim to completion of capital projects to resolve existing capacity constraints, Christchurch City Council and Kainga Ora (supporting affordable homes and community well-being) undertook the development opportunity optimization to identify opportunities for development potential without increasing environmental impacts. BENEFITS WCS brings to the market a novel AI-driven framework to urban planning that promises sustainable, strategic, and environmentally conscious decision-making platform, adaptable to any utility, regardless of system size and hydraulic complexity. Unlike traditional modeling and planning methodologies, WCS' AI-powered workflow allows the utility and engineers to spend their time where it's most efficient — understanding the problem, formulating the problem, and making informed decisions. This project displays an innovative roadmap, including the construction of an intuitive Business Intelligence decision-making platform to aid in urban growth to ultimately enhance urban living standards and accommodate growing populations more effectively. INTRODUCTION Christchurch City Council (CCC) has a large and complex wastewater network serving approximately 373,000 people with a single wastewater treatment plant capable of treating approximately 160 megaliters/day. The city has two main river systems: the Avon River and the Heathcote River, which both flow into the Avon-Heathcote Estuary which then flows into the Pacific Ocean. CCC holds a resource consent (permit) for the overflows to waterways. The resource consent allows an overflow frequency to each of these receiving environments which decreases over time to a 2-year recurrence interval, based on continuous simulation of 15 years rainfall data. In addition, no overflow site may overflow more than every six months on average, based on the same long time series modeling. While CCC is tracking well against progress targets for wet weather overflow abatement, it is reluctant to permit development in regions that could significantly exacerbate existing overflows or create new overflows. The current city population is forecast to increase from the current population of approximately 370,000 to a 2054 population of over 450,000; however, the maximum potential population if all land parcels are developed to their maximum land use density is over 2,000,000. There are many considerations when determining the effect of growth on a city. To assess water and wastewater network capacity impacts associated with proposed development, it is common for manual hydraulic modeling to be completed for each development application. Not only is this approach time consuming and repetitive, but it is also difficult to establish any significant impact associated with an individual development. By applying intelligent algorithm optimization using cloud computing to simulate thousands of urban growth alternatives, the complex hydraulic interdependencies and cumulative impact of growth were synergistically considered in a holistic, effective planning analysis. DETAILS The existing system performance (baseline) was assessed based on 15-year continuous simulation of historic rainfall to assess wet weather overflow frequencies, volumes and peak discharge rates. The results were then used to construct a composite rainfall event from various historic events that correspond to a 2-year return period specific to each catchment. The 'representative 2-year design storm' was used to prepare an optimized master plan based on a life-cycle cost evaluation of conveyance, storage and inflow and infiltration (I/I) reduction alternatives. The master plan was then prioritized to determine the sequence of project implementation that maximizes return on investment with respect to reducing wet weather overflows (weighted by customer and environmental impact) as cost-efficiently as possible. Interim to scheduled capital improvements, the impact of development can result in deteriorating performance if not managed appropriately. Maximum population growth alternatives to be considered for each wastewater subcatchment were determined based on consideration of the CCC 2068 growth model and the maximum density yield based on land-use. Each alternative was formulated in Optimizer-ICMTM such that the optimization algorithm would trial combinations of growth intensities and assess hydraulic performance for each trial scenario. Hydraulic performance was assessed relative to the baseline existing system performance (total overflow volume and available freeboard in the representative 2-year design storm). Individual manhole changes in overflow volume or freeboard reduction were quantified as a percentage relative of their existing values. Each of the thousands of population growth trial solutions evaluated in the optimization analysis was retained in a data portal and post-processed using Power BI to demonstrate the relationship between optimized growth and system performance impacts (Figure 1). Spatial probability algorithms were scripted in Power BI to identify subcatchments and regions with the maximum potential for growth with minimal impact (Figure 2). ArcGIS was used to communicate the optimization results based on high-resolution grouped subcatchments (Figure 3) and macro-scale suburb (Figure 4) growth potential weightings. COMPLETION The benefit of the optimization approach has already been demonstrated. In a first for Aotearoa, a housing optimization project was successfully carried out on Council's wastewater network in 2023. Thousands of intensification scenarios were evaluated using the AI framework. The project identified the Council's wastewater subcatchments and suburbs with the greatest capacity for growth, with results showing that housing for up to 35,000 additional people could be accommodated with virtually no increase in wastewater overflows (see Figures 3 and 4).This paper was presented at the WEF Collection Systems and Stormwater Conference, April 9-12, 2024.SpeakerWilson, JoelPresentation time11:15:0011:45:00Session time10:45:0011:45:00SessionSmart Systems - StormwaterSession number18Session locationConnecticut Convention Center, Hartford, ConnecticutTopicArtificial Intelligence, Combined Sewer Overflow, Combined Sewer System, Continuous Monitoring and Adaptive Control, Optimization, Stormwater Case Study/Application, Sustainability And Social Responsibility, Utility ManagementTopicArtificial Intelligence, Combined Sewer Overflow, Combined Sewer System, Continuous Monitoring and Adaptive Control, Optimization, Stormwater Case Study/Application, Sustainability And Social Responsibility, Utility ManagementAuthor(s)Wilson, JoelAuthor(s)J. Wilson1, B. O'Brien2, M. McDonald3, G. Hughes4Author affiliation(s)WCS Engineering 1; WSP 2; Christchurch City Council 3; Kainga Ora 4SourceProceedings of the Water Environment FederationDocument typeConference PaperPublisherWater Environment FederationPrint publication date Apr 2024DOI10.2175/193864718825159392Volume / Issue Content sourceCollection Systems and Stormwater ConferenceCopyright2024Word count14
Wilson et al. (Thu,) studied this question.