A Risk-Based Long-Term Capital Planning Program

Ganjidoost, Amin; Daly, Craig; Baird, Gregory M.

doi:10.1061/9780784483602.001

Cited by 4 publications

(5 citation statements)

References 3 publications

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“…As a result, the utility needs to plan yearly budgets for the metallic mains in risk tiers 2, 3, and 4. Table 3 summarizes the unit cost of metallic mains assessment in each tier based on historical projects conducted by some water utilities in the US (Ganjidoost, Daly, et al, 2021; Ganjidoost, Knight, et al, 2021). It should be noted that all numeric values and planning horizon length obtained or assumed for in this study can be updated based on the utility's desire to test the impact of changing inputs on the modeling outcomes.…”

Section: Risk‐based Capital Planningmentioning

confidence: 99%

“…However, none of these studies considered the risk of asset failure in their models when planning for operational and capital works. Ganjidoost, Daly et al (2021) proposed a DSS using SD to demonstrate the value of investing in water main assessment programs when planning for CIPs. Using data from a mid‐sized US water utility, they showed the long‐term value of investing in assessment programs.…”

Section: Risk‐based Decision‐system System Using Sdmentioning

confidence: 99%

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Leveraging risk and data analytics for sustainable management of buried water infrastructure

Ganjidoost¹,

Vladeanu

Daly

2022

AWWA Water Science

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A proactive and sustainable asset management program is vital for utilities to maintain their capital assets at the required level of service, while ensuring that adequate funds are available for intervening when needed on their riskiest assets. One of the most popular methods for building such programs is by prioritizing capital investments based on the asset's risk of failure, which evaluates its likelihood or probability of failure and impact, or consequence of failure. This paper presents the application of a financial planning analysis using system dynamics to provide insights into quantifying more practical risk avoidance. This is exemplified through a 5-year budgetary planning scenario analysis for a large-sized US water utility to help the utility best plan for short and long-term capital operations and show the value of a data-driven and riskbased decision-making.

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Section: Risk‐based Capital Planningmentioning

confidence: 99%

Section: Risk‐based Decision‐system System Using Sdmentioning

confidence: 99%

Leveraging risk and data analytics for sustainable management of buried water infrastructure

Ganjidoost¹,

Vladeanu

Daly

2022

AWWA Water Science

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“…Decision-making models have been developed to assess the consequence and risk of sewer pipe failure using risk matrix and a weighted sum multi-criteria decision-matrix (Baah et al, 2015) or artificial intelligence-based techniques (Mashford et al, 2010), and evaluate data-driven and risk-based decisions to prioritize inspection, rehabilitation, or replacement of the sewer pipe (Tran et al, 2010;Syachrani et al, 2011;Elsawah et al, 2016;Ganjidoost et al, 2021b). Rehan et al (2011Rehan et al ( , 2014, Ganjidoost et al (2015Ganjidoost et al ( , 2018Ganjidoost et al ( , 2021a and Mohammadifardi et al (2019) developed sustainable management strategies models for the wastewater collection infrastructure using system dynamics to help the water utility find out "Where do we want to go?"…”

Section: Introductionmentioning

confidence: 99%

Performance Modeling and Simulation for Wastewater Collection Networks

Ganjidoost

Knight²,

Unger³

et al. 2022

Front. Water

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This study develops a framework for asset management strategy of wastewater collection networks comprised of three interconnected decision-making layers: (1) Visions & Values, (2) Function, and (3) Performance, which are set according to the established concepts of strategic targets, policy levers, sustainability and life cycle. The asset management strategy framework is implemented and validated through demonstration of functionality and value by using the wastewater collection networks of three utilities in Ontario, Canada, to drive management simulations. A borrowing management strategy is used to benchmark the utilities against each other in terms of infrastructure, sociopolitical, and financial performance over a 100-year benchmarking period. It is found that a borrowing management strategy can enable the utility to accelerate their capital works, reduce the volume of inflow and infiltration and their associated expenses and sustainably meet their strategic targets over the life cycle of the assets. Using contour plots, the impact of maximum debt capacity on two infrastructure and financial benchmarking performance indicators is also investigated to explore the “optimal” combination of allowable fee hikes and preferred rehabilitation rates. Furthermore, using a borrowing management strategy, a business case for asset management of wastewater collection networks is developed to explore the “optimal” combination of allowable fee-hike and rehabilitation rates, using a developed inflow and infiltration expenditures (I&IEx) saving ratio contour plots. The results indicate that a borrowing management strategy competes as long as the combinations of allowable fee-hike and preferred rehabilitation rates lead to a positive value of I&IEx saving ratio.

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“…Katko et al (2010) suggested that the concept of integrating the management of water and wastewater infrastructure systems is familiar, but the idea as a whole has not been fully embraced. Many studies, including, but not limited to, Ganjidoost (2016), Ganjidoost et al (2017, 2018), Ganjidoost, Daly, and Baird (2021), Ganjidoost, Haas, et al (2015a, 2015b), Ganjidoost, Knight, et al (2021), Ganjidoost, Knight, et al (2022), Ganjidoost, Vladeanu, and Daly (2022a, 2022b), Ganjidoost, Younis, and Knight (2015), Mohammadifardi, Knight, and Unger (2019), Rehan et al (2011, 2013, 2015), Rehan, Knight, et al (2014), Rehan, Unger, et al (2014) along (Baah et al, 2015; Duchesne et al, 2013; Elsawah et al, 2016; Hawari et al, 2016; Kleiner et al, 1998a, 1998b; Mashford et al, 2010; Mazumder et al, 2021; Park et al, 2015; Roshani & Filion, 2013; Scheidegger et al, 2011; Scholten et al, 2014; Syachrani et al, 2011; Tran et al, 2010) have developed distinct and separate management models for water and wastewater infrastructure systems. The evaluation of these models indicates that the current management models and tools are applied to either water distribution or wastewater collection systems.…”

Section: Introductionmentioning

confidence: 99%

“…Ganjidoost et al (2018) developed three categories of infrastructure, socio‐political, and financial benchmarking performance indicators for water distribution and wastewater collection networks. They used SD to demonstrate how water utilities can utilize the proposed normalized and time‐integrated performance indicators to benchmark and compare their networks' short and long‐term performance against one another and their own strategic targets (Ganjidoost et al, 2018; Ganjidoost, Daly, & Baird, 2021; Ganjidoost, Knight, et al, 2021; Ganjidoost, Knight, et al, 2022; Ganjidoost, Vladeanu, & Daly, 2022a, 2022b).…”

Section: Introductionmentioning

confidence: 99%

Integrated asset management of urban water and wastewater systems

et al. 2022

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This paper presents a decision support system for the integrated management of water distribution and wastewater collection networks. The proposed methodology utilizes system dynamics to integrate water mains and sewers with finance and sociopolitical sectors. It enables user rate-setting and planning of integrated water and wastewater infrastructure operational and capital works over their life-cycle (50+ years). The integrated asset management model is implemented using data from a large-sized utility in Southern Ontario, Canada. The result indicates that the integrated framework enables the utility to accelerate funding for capital and operational works due to the integration of the water and wastewater financial resources and improve the integrated levels of service. In practice, the proposed integrated framework empowers and encourages water utilities to manage and plan their assets in an integrated approach to enhance their water and wastewater assets' infrastructure, financial, and sociopolitical performance relative to managing them in isolation.

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A Risk-Based Long-Term Capital Planning Program

Cited by 4 publications

References 3 publications

Leveraging risk and data analytics for sustainable management of buried water infrastructure

Leveraging risk and data analytics for sustainable management of buried water infrastructure

Performance Modeling and Simulation for Wastewater Collection Networks

Integrated asset management of urban water and wastewater systems

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