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A DATA-DRIVEN STRATEGIC INVESTMENT DECISION FRAMEWORK THAT INTEGRATES THE LATENT THREATS TO AND PROLONGED RISKS OF WATER INFRASTRUCTURE

<p>Water infrastructure forms a critical sector of our social system and provides goods and services for public health, the natural environment, economic safety, various businesses, and government operations. In the United States (US), drinking water is supplied nationally through one million miles of pipes, most of which were installed in the early to mid-20th century with a life span of 75 to 100 years. Along with this fact, water bills which are rising faster than inflation, result in communities grappling with aging water systems, fewer water resources, and extreme weather. The federal government’s share of capital investment for water infrastructure has fallen from 31% in 1977 to 4% in 2017. Regional and state expenditure has accounted for a much larger share as federal aid for water infrastructure capital needs has declined. This has led to water rates rising to cover the costs of replacing and upgrading water infrastructure in many communities across the country. They are struggling to meet such costs through local rates and fees.</p><p>Over the next 20 years, more than 56 million new users are expected to connect to centralized treatment systems, and $271 billion is needed to meet current and future demands. However, the investment in critical water infrastructure is currently only meeting a fraction of the funding need. In 2019, the total capital spending on water infrastructure at all levels was $48 billion, while investment needs totaled $129 billion, creating an $81 billion gap. As such, the most recent American Society of Civil Engineers’ Infrastructure Report Card assigned a D to the drinking water infrastructure and a D+ to the nation’s wastewater infrastructure. Ineffectual and wasteful investment in the water sector has caused an adverse effect on grades in the infrastructure report card for water infrastructures. Moreover, this may negatively impact water-reliant sectors and water-related infrastructures due to the economic ripple effect.</p><p>This research has developed a data-driven strategic investment decision support system to close the existing water infrastructure investment gap and reduce the vulnerability of aging water infrastructure. The first phase of this study was to determine the causes affecting the grades in the infrastructure report card for drinking water and wastewater infrastructure and contributing to any latent threats and prolonged risks. It uses data-driven approaches based on analysis of existing ineffective improvement methods and recommendations. It attempts to leverage a data-driven supervised statistical learning method to capture the complex relationships between new challenges and the growing demand for water infrastructure needs. The ultimate outcome of this phase is a research approach to minimize water and wastewater vulnerability and close the investment gap to help create a paradigm shift in the current state of practice. Furthermore, improving the resiliency of and increasing investments in the water and wastewater infrastructure will lead to a resilient, efficient, and reliable water future and protect the public health of future generations.</p><p>The second phase of this study was to predict the economic benefits of additional federal support in water infrastructure among interdependent sectors within an economic system to facilitate the federal government’s share of capital investment. It conducts ripple effects analysis, which predicts the effectiveness of water infrastructure capital investment using historical economic data. It explores how federal capital investment in water infrastructure spreads economic benefits within an interdependent system. This phase was conducted at the federal level using the interindustry-macro model that analyzes macroeconomic data, including over 400 sectors. Investments that are coordinated at the federal, state, and local level will help control and stabilize rising water rates across the US.</p><p>The third phase of this study was to conduct a cost-benefit assessment in terms of private, financial, economic, and efficiency considerations using nominal and real terms to maximize the benefit of investing in the water sector and reduce the vulnerability of water infrastructures. In order to measure the costs and benefits of a strategy to maximize the efficiency of limited budgets and resources, this phase conducts a cost-benefit analysis due to the investment costs for rehabilitating and improving water infrastructures using historical economic and financial data. The long-term financial framework, including considerations of deep uncertainties so that decision-makers can understand the benefit of investing assets for an optimal level versus the cost of doing nothing and allowing the asset to run to failure is developed using the cost-benefit assessment.</p><p>Finally, a data-driven strategic investment decision support system that helps governments make water infrastructure development plans and infrastructure investment decisions in the water sector is presented. It can help governments with designing a novel system or modifying existing ineffective assessment methods and recommendations aimed at minimizing the mismatch in the water infrastructure investment gap between current spending levels and funding needs. Furthermore, minimizing the risks of ineffectual and wasteful water sector investment through rehabilitating and improving water infrastructures in a rational manner will lead to improved grades in the infrastructure report card and the resiliency of interrelated infrastructures and sectors.</p>

  1. 10.25394/pgs.23721225.v1
Identiferoai:union.ndltd.org:purdue.edu/oai:figshare.com:article/23721225
Date07 August 2023
CreatorsKwangHyuk Im (7036595)
Source SetsPurdue University
Detected LanguageEnglish
TypeText, Thesis
RightsCC BY 4.0
Relationhttps://figshare.com/articles/thesis/A_DATA-DRIVEN_STRATEGIC_INVESTMENT_DECISION_FRAMEWORK_THAT_INTEGRATES_THE_LATENT_THREATS_TO_AND_PROLONGED_RISKS_OF_WATER_INFRASTRUCTURE/23721225

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