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Finding the optimal solution to address problems in sewer management systems has always challenged asset managers. An understanding of deterioration mechanisms in sewers can help asset managers in developing prediction models for estimating whether or not sewer collapse is likely. The effective use of deterioration prediction models along with the development and use of life cycle cost analysis (LCCA) can contribute to the goals of reducing construction, operation and maintenance costs in sewer systems. When sewer system maintenance/rehabilitation options are viewed as investment alternatives, it is important, and in some cases, imperative, to make decisions based on life cycle costs instead of relying totally on initial construction costs. The objective of this paper is to discuss the application of deterioration modelling and life cycle cost principles in sewer system management, and to explore the role of the Markov chain model in decision making regarding sewer rehabilitation. A test case is used to demonstrate the application of the Markov chain decision model for sewer system management. The analysis includes evaluation of this concept using dynamic programming and the policy improvement algorithm.

This paper proposes a decision‐making framework to assist asset managers in decision making regarding sewer maintenance/rehabilitation (M&R) plans under constraints of limited access to sewer condition data. It discusses the application of probabilistic dynamic programming in conjunction with a Markov chain model to analyze the life cycle cost of combined sewer systems. M&R issues have traditionally been addressed with a crisis‐based approach, but this study contributes to sewer infrastructure management efforts in developing a management system based on life cycle cost analysis. The framework includes the optimal M&R techniques for sewer projects and the optimal times of application. The role of simulation is also explored to obtain the variability of the total cost. By knowing the expected costs and their variabilities, a deeper understanding of life cycle costs of sewer infrastructure can be obtained. The model’s capability is enhanced further by testing its sensivitity to varying discount and inflation rates.

The chapter explores the perils of the unbridled growth of tourism and offers some approaches to optimise the benefits of tourism for the stakeholders. It also discusses the catalysing role of the COVID-19 pandemic in reorienting consumer preferences and thereby government policies towards a more responsible paradigm. India's fast-growing economy and rapid build-up of infrastructure would unleash a commensurate growth in its tourism sector and hence call for a need to approach it from the perspective of responsible tourism. It assesses the model of the Responsible Tourism initiative of Kerala based on the three pillars of environmental, economic and social responsibility. The chapter also proposes pilot initiatives at select destinations across the nation with primacy placed upon carrying capacity. It calls for reorienting the approach to the destination level instead of state-level and preparing a framework of administrative structures and financing. It also proposes a responsible tourism classification for tourism enterprises to which incentives and subsidies could be aligned to encourage onboarding.

Residents of South Florida have been living with the effects of climate change in the form of flooding due, in part, to sea level rise, for more than a decade. However, previous research has characterized news coverage of climate change impacts as concerning distant events in terms of time and place. In this study, we look at coverage of climate change at The Miami Herald from 2011-2015, a time period significant in terms of increased temperatures and flooding levels on city streets. Through a content analysis of 167 articles, this study argues that news coverage of climate change in The Miami Herald was largely pragmatic, linked to a news peg, locally focused and presented via opinion pieces rather than news articles. Furthermore, Miami Herald coverage links distant hypotheses of climate change with local realities, invokes a network of editorial responses, and emphasizes local impacts, particularly in more affluent areas. Findings from this study contribute to understanding how news coverage of climate change as a local story may provide a useful model for engaging the public in adapting to and mitigating against the impact of climate change, and creating social acceptance of climate change policy.

This paper is about best practice in managing legacy drainage assets to support sustainable urban regeneration. The purpose of this paper is to describe best practice sewer asset management (AM) and to adjust the current reactive maintenance approach for sewers, to one that accommodates long-term operational and town planning needs. The development of an improved sewer deterioration model (DM) provided an important tool for this.

This research adopts a mixture of qualitative and quantitative approaches to analyse a total network length of 24,252 km which represents 703,156 records of historic sewer structural condition inspection data. This was used to build an improved DM. These models were used as inputs into a proactive AM approach that improves upon recommendations in the Sewerage Rehabilitation Manual developed by Water Research Centre.

This is a paradigm shift and goes beyond the current culture of OFWAT (Water Services Regulation Authority) supervision, five-year asset management period and occasional environmental penalties. A new legislative model may be needed; especially because a report by UKWIR (Water Industry Research) in 2015 identified that nationally the rate of sewer network deterioration is outpacing available investment and significant health problems may arise in addition to those from developmental pressures.

The authors have researched and managed old sewer networks and present a review of the new issues raised by intensive development, particularly for the London region, but applicable elsewhere, and how these must lead to a modified risk, and novel incentive-based approach to AM, if the system is not to fail.

Large, legacy databases of several decades of sewer network performance records have been combined and analysed as stratified, heterogeneous sets with Gaussian distributions; thereby improving on previous assumptions of homogeneous data. The resulting rigorous DMs are the foundation of new approaches to sustainable risk management of large urban networks.

The purpose of this paper was exploring and comparing different deterioration models based on statistical and machine learning approaches. These models were chosen from their successful results in other case studies. The deterioration models were developing considering two scenarios: (i) only the age as covariate (Scenario 1); and (ii) the age together with other available sewer characteristics as covariates (Scenario 2). Both were evaluated to achieve two different management objectives related to the prediction of the critical condition of sewers: at the network and the sewer levels.

Six statistical and machine learning methods [logistic regression (LR), random forest (RF), multinomial logistic regression, ordinal logistic regression, linear discriminant analysis and support vector machine] were explored considering two kinds of predictor variables (independent variables in the model). The main propose of these models was predicting the structural condition at network and pipe level evaluated from deviation analysis and performance curve techniques. Further, the deterioration models were exploring for two case studies: the sewer systems of Bogota and Medellin. These case studies were considered because of both counts with their own assessment standards and low inspection rate.

The results indicate that LR models for both case studies show higher prediction capacity under Scenario 1 (considering only the age) for the management objective related to the network, such as annual budget plans; and RF shows the highest success percentage of sewers in critical condition (sewer level) considering Scenario 2 for both case studies.

There is not a deterioration method whose predictions are adaptable for achieving different management objectives; it is important to explore different approaches to find which one could support a sewer asset management objective for a specific case study.

The originality of this paper consists of there is not a paper in which the prediction of several statistical and machine learning-based deterioration models has been compared for case studies with different local assessment standard. The above to find which is adaptable for each one and which model is adaptable for each management objective.

Jefferson County, Alabama undertook a series of risky financial maneuvers in 2003 that included issuing large amounts of variable rate and auction rate securities as well as engaging in numerous interest rate swaps in order to lower the burgeoning costs of repairing its sewer system to comply with federal regulations. These complex financial instruments, intended to lower debt service costs on the countyʼs $3 billion in outstanding sewer warrants, led the county to financial bankruptcy in the wake of the financial markets collapse. This paper explores the choice of securities by analyzing the risk of adjustable rate securities and interest rate swaps, examining the Jefferson County case in detail, and providing some lessons for future financial management within the context of unexpected events such as the current recession.

This paper highlights a crucial public safety issue due to falling objects from tall residential buildings in Singapore. A systematic façade inspection regime and a system of evaluation of severity for the detection and assessment of potential falling objects from tall buildings are presented.

The research uses qualitative case study approach with 450 tall residential buildings sampled for the study. The common materials, elements, components with high risk of falling objects, the nature and type of the falling, the critical factors affecting the falling, the respective level of severity, and the effectiveness of various diagnostic techniques and protocols, are summarised.

Façade for tall residential buildings in Singapore comprises mainly cementitious materials cast in situ or precast, with fixtures and architectural features, all of which have potential of falling. The common anomalies arising from each material and fixture/features are identified, the causes evaluated and their implications to future design, construction and maintenance analysed.

This study provides original and significant information to a crucial public safety issue, setting design and construction criteria that will serve as a benchmark for new and existing facades, applicable to all cities dominated by tall buildings. The paper presents original figures, checklists and guides as a basis for readers' consideration to use according to their respective unique conditions.

Local governments are often forced to purchase expertise for non-recurring analyses, such as rate setting for water and sewer services, because it is not cost-effective for these governments to maintain such expertise in-house or because independent analyses are preferred by watch-dog agencies or mandated by state statutes. However, like many ostensibly value-neutral analytical studies, these studies inevitably entail policy choices of which elected policy makers may not be aware. External analysts may not be aware of idiosyncratic factors, and they apply boilerplate perspectives that may not be responsive to local preferences. These perspectives limit policy options, although they may appear to be value-neutral. Policy makers must take an active role in these analytical studies in order to ensure that local preferences and specific factors are considered. Citizen committees comprised of residents with the necessary expertise, or experts from local colleges and universities may be able to provide the necessary oversight.

Jefferson County was in a financial crisis as the commissioners faced a decision concerning whether the County should file for bankruptcy. The County was under an EPA mandate to update an outdated and overrunning sewer system. Estimates to do the work ranged from $250 million to $1.2 billion. The situation led to graft, corruption, bribery and illegal activities. More than 20 people were prosecuted in association with the illegal activities involved in financing and construction of the sewer system and four of the five commissioners were sentenced for their involvement in the corruption. Five new commissioners were elected and had to determine what to do after the down-grade of the County's bonds and warrants; the reduced revenues; and the corruption had put the County in a situation where funds were not available to continue to operate the County and provide services to its citizens. Should they declare bankruptcy or choose other paths open to them?

Data sources – this case is based on field research and interviews with a commissioner, court documents and from many other public sources. Extent of disguise – the case is not disguised.

The case can be used in graduate or upper division undergraduate courses in accounting, strategy, public administration or finance. There are several topics in the case that could be addressed: governance; economics, government and political issues, ethics, accounting, financial instruments, and strategy.