Long-lived Infrastructure Research Articles

Risk-based hydrologic design under climate change using stochastic weather and watershed modeling

Water resources planning and management requires the estimation of extreme design events. Anticipated climate change is playing an increasingly prominent role in the planning and design of long-lived infrastructure, as changes to climate forcings are expected to alter the distribution of extremes in ways and to extents that are difficult to predict. One approach is to use climate projections to force hydrologic models, but this raises two challenges. First, global climate models generally focus on much larger scales than are relevant to hydrologic design, and regional climate models that better capture small scale dynamics are too computationally expensive for large ensemble analyses. Second, hydrologic models systematically misrepresent the variance and higher moments of streamflow response to climate, resulting in a mischaracterization of the extreme flows of most interest. To address both issues, we propose a new framework for non-stationary risk-based hydrologic design that combines a stochastic weather generator (SWG) that accurately replicates basin-scale weather and a stochastic watershed model (SWM) that accurately represents the distribution of extreme flows. The joint SWG-SWM framework can generate large ensembles of future hydrologic simulations under varying climate conditions, from which design statistics and their uncertainties can be estimated. The SWG-SWM framework is demonstrated for the Squannacook River in the Northeast United States. Standard approaches to design flows, like the T-year flood, are difficult to interpret under non-stationarity, but the SWG-SWM simulations can readily be adapted to risk and reliability metrics which bare the same interpretation under stationary and non-stationary conditions. As an example, we provide an analysis comparing the use of risk and more traditional T-year design events, and conclude that risk-based metrics have the potential to reduce regret of over- and under-design compared to traditional return-period based analyses.

Megaprojects: a meandering journey towards a theory of purpose, value creation and value distribution

This paper departs from a reflection of how my time as a doctoral student in the late nineties with the lean construction group at U.C. Berkeley influenced my (ongoing) research journey. I first recall how those early years led to my core empirical and theoretical interests on the management of ‘megaprojects’ - the project-based, multi-party contexts that are set up by one or more organisational actors with the aim of developing capital-intensive, long-lived infrastructure resources. I also analyse the challenges that I faced in the pursuit of a theoretical perspective with power to predict and explain empirical regularities on megaproject behaviour, and thus capable of illuminating the pervasiveness of major cost and schedule slippages as well as scope creep. As well as this, I discuss how the discovery of Elinor Ostrom’s commons governance theory was a watershed in my research journey. Then, drawing from organisational governance literature, I introduce and illustrate a model of the evolution of the governance structure of a megaproject over the project life cycle. I harness this model to draw inferences on megaproject organisational boundaries, on megaproject behaviour, and on how megaprojects create both economic and social value. Further, after conceptualising a megaproject as a purposeful interorganizational form of organising capital production, I discuss feedback loops and contingency variables that affect the gap between intended and realised project behaviour. I conclude with a discussion on how to leverage an organisational perspective of megaprojects to realise the potential of capital investment in new infrastructure to create value, as well as to engender trust in megaprojects, and thus mend their fractured relationship with society. Each era’s theories and prevailing arguments, in part, reflect the preoccupations of the times and coevolve with them 1

European supply chains for carbon capture, transport and sequestration, with uncertainties in geological storage capacity: Insights from economic optimisation

Carbon capture and storage is widely recognised as a promising technology for decarbonising the energy and industrial sector. An integrated assessment of technological options is required for effective deployment of large-scale infrastructures between the nodes of production and sequestration of CO2. Additionally, design challenges due to uncertainties in the effective storage availability of sequestration basins must be tackled for the optimal planning of long-lived infrastructure. The objective of this study is to quantify the financial risks arising from geological uncertainties in European supply chain networks, whilst also providing a tool for minimising storage risk exposure. For this purpose, a methodological approach utilising mixed integer linear optimisation is developed and subsequent analysis demonstrates that risks arising from geological volumes are negligible compared to the overall network costs (always <1% of total cost) although they may be significant locally. The model shows that a slight increase in transport (+11%) and sequestration (+5%) costs is required to obtain a resilient supply chain, but the overall investment is substantially unchanged (max. +0.2%) with respect to a risk-neutral network. It is shown that risks in storage capacities can be minimised via careful design of the network, through distributing the investment for storage across Europe, and incorporating operational flexibility.

How does climate change affect electricity system planning and optimal allocation of variable renewable energy?

Ongoing climate change affects complex and long-lived infrastructures like electricity systems. Particularly for decarbonized electricity systems based on variable renewable energies, there is a variety of impact mechanisms working differently in size and direction. Main impacts for Europe include changes in wind and solar resources, hydro power, cooling water availability for thermoelectric generation and electricity demand. Hence, it is not only important to understand the total effects, i.e., how much welfare may be gained when accounting for climate change impacts in all dimensions, but also to disentangle various effects in terms of their marginal contribution to the potential welfare loss. This paper applies a two-stage modeling framework to assess very strong climate change impacts on a cost-optimally decarbonized, highly renewables-based European electricity system. Thereby, the performance of two electricity system design strategies – one based on no anticipation of climate change and one anticipating impacts of climate change – is studied under a variety of climate change impacts. Impacts on wind and solar resources are found to cause the largest system effects in 2100. Combined climate change impacts increase system costs of a system designed without climate change anticipation due to increased fuel and carbon permit costs. Applying a system design strategy with climate change anticipation increases the cost-optimal share of variable renewable energy based on additional wind offshore capacity in 2100, at a reduction in nuclear, wind onshore and solar photovoltaics capacity. Compared to a no anticipation strategy, total system costs are reduced.

Investments under non-stationarity: economic evaluation of adaptation pathways

Investment decisions about capital-intensive, long-lived infrastructure are challenging due to uncertainty about their future performance, particularly if the performance is sensitive to climate change. Such investments, like those made for water infrastructure, are rarely evaluated over their total operational lifetime, during which socio-economic and environmental changes can cause potential lock-ins and reduced options for future choices that lead to high costs to transfer to other options. We propose an economic evaluation framework to explore adaptation pathways, or sequences of strategic investments options, that can be implemented if needed due to changing conditions. A novel feature is the inclusion of “transfer costs” associated with a switch to alternative pathways to allow adaptive decision-making and to minimize the cost of adjustment over time. Implementing a pathway-driven approach represents a break with most institutional decision-making processes and can significantly improve decision-making under uncertainty compared to the conventional single-investment perspective. We present a case study on flood risk management in the Netherlands to show the long-term socio-economic consequences of short-term decisions by going beyond the project cycle horizon.

Sustainability cost curves for urban infrastructure planning

Global urban infrastructure spending is expected to triple by 2050 as cities try to keep up with growing populations and retrofit ageing civil works. However, long-lived infrastructure needs to be developed within local and global limits and aspirational targets such as the United Nations sustainable development goals. This paper presents an approach to measure and prioritise urban infrastructure as it relates to sustainability boundaries and targets. It provides a simple yet powerful tool for public policy and urban infrastructure planning. As an example, the method is applied to nine real transportation projects in Toronto, Canada, and these are compared with urban transport projects in Brazil, China, India and Senegal.

Simulated climate adaptation in storm-water systems: Evaluating the efficiency of within-system flexibility

Changes in regional temperature and precipitation patterns resulting from global climate change may adversely affect the performance of long-lived infrastructure. Adaptation may be necessary to ensure that infrastructure offers consistent service and remains cost effective. But long service times and deep uncertainty associated with future climate projections make adaptation decisions especially challenging for managers. Incorporating flexibility into systems can increase their effectiveness across different climate futures but can also add significant costs. In this paper we review existing work on flexibility in climate change adaptation of infrastructure, such as robust decision-making and dynamic adaptive pathways, apply a basic typology of flexibility, and test alternative strategies for flexibility in distributed infrastructure systems comprised of multiple emplacements of a common, long-lived element: roadway culverts. Rather than treating a system of dispersed infrastructure elements as monolithic, we simulate “options flexibility” in which inherent differences in individual elements is incorporated into adaptation decisions. We use a virtual testbed of highway drainage crossing structures to examine the performance under different climate scenarios of policies that allow for multiple adaptation strategies with varying timing based on individual emplacement characteristics. Results indicate that a strategy with options flexibility informed by crossing characteristics offers a more efficient method of adaptation than do monolithic policies. In some cases this results in more cost-effective adaptation for agencies building long-lived, climate-sensitive infrastructure, even where detailed system data and analytical capacity is limited.

Increased rainfall volume from future convective storms in the US

Mesoscale convective system (MCS)-organized convective storms with a size of ~100 km have increased in frequency and intensity in the USA over the past 35 years 1 , causing fatalities and economic losses 2 . However, their poor representation in traditional climate models hampers the understanding of their change in the future 3 . Here, a North American-scale convection-permitting model which is able to realistically simulate MSCs 4 is used to investigate their change by the end-of-century under RCP8.5 (ref. 5 ). A storm-tracking algorithm 6 indicates that intense summertime MCS frequency will more than triple in North America. Furthermore, the combined effect of a 15–40% increase in maximum precipitation rates and a significant spreading of regions impacted by heavy precipitation results in up to 80% increases in the total MCS precipitation volume, focussed in a 40 km radius around the storm centre. These typically neglected increases substantially raise future flood risk. Current investments in long-lived infrastructures, such as flood protection and water management systems, need to take these changes into account to improve climate-adaptation practices. Limitations with climate models have previously prevented accurate diagnosis of future changes in mesoscale convective systems (MCSs). A convection-permitting model now indicates that summer MCSs will triple by 2100 in the United States, with a corresponding increase in rainfall rates and areal extent.

Framework for Incorporating Downscaled Climate Output into Existing Engineering Methods: Application to Precipitation Frequency Curves

AbstractTo improve the resiliency of designs, particularly for long-lived infrastructure, current engineering practice must be updated to incorporate a range of future climate conditions that are l...

The United States Energy System Has Become More Volatile and Harder to Predict

Long-term projections of energy consumption, supply, and prices heavily influence decisions regarding long-lived energy infrastructure. Predicting the evolution of these quantities over multiple years to decades is a notoriously difficult task. This work provides the first effort in the literature to estimate volatility and unpredictability over multi-decade time frames for many quantities in the US energy system using historical projections. We determine the distribution over time of the most extreme projection errors (unpredictability) from 1985-2014, and the largest year-over-year changes (volatility) in the quantities themselves from 1949-2014. Critically, we find that both volatility and unpredictability have increased in the past decade, relative to prior decades. We encourage energy decision-makers to consider these findings, emphasizing robustness as they invest in and regulate long-lived energy infrastructure in a deeply uncertain world.

Commercialisation and airport performance: The case of Ireland's DAA

Airport performance has been the subject of an increasing volume of empirical research in recent years. This paper bridges a gap in the existing literature through an in-depth case study analysis of the process of commercialisation in the Dublin Airport Authority (DAA), Ireland's state-owned airport company, and the corresponding impact on performance over the 1994–2014 period. We use a model of commercialisation to examine changes in the DAA's internal and external environments that show evidence of a more commercial focus. The DAA's economic performance is then analysed using total factor productivity (TFP) and labour productivity indicators, as well as basic financial indicators. Our analysis highlights the significant internal and external changes experienced by the DAA over the past two decades that have driven a continuous process of commercialisation. While TFP growth was positive or stable in half of the years that we examined, the overall level of TFP declined over our timeframe of analysis. Much of this decline was due to two considerable programmes of investment in long-lived infrastructure assets where a return in the short-term would not be expected.

NEKI TEHNIČKO-EKONOMSKI ASPEKTI PRUGA ZA VELIKE BRZINE / SOME TECHNICAL-ECONOMIC ASPECTS OF HIGH RAILWAY SPEED

Many countries investment and building high speed rail (HSR) infrastructure becouse produces social benefits and costs. The potential benefits are basically time savings, higher reliability, comfort, safety and the release of capacity in the conventional rail network, enviromental roads and airport infrastructure. The costs are high, and sunk in a significant proportion; therefore, the social profitability of the project requires that HSR users’ and other beneficiaries’ willingness to pay is high enough to compensate the sunk and variable costs of maintaining and operating the line plus any other external cost during construction and project life. Problem for our country, is number of passengers to justify a new high speed line. It is very variable, ranging from 3 millions to 17 millions in the first year of operation under possible assumptions examined, but typically even under favourable conditions at least 9 millions passengers per annum will be needed. The economic evaluation of long-lived infrastructure requires a careful construction of the contrafactual and there are many assumptions that might seriously bias the results. This is the case of transport pricing during the lifespan of the project. Pricing policy needs to be explicitly treated.

Do denser urban areas save on infrastructure? Evidence from New Zealand territorial authorities

How urban planners shape urban form and longlived infrastructure in these coming few years will largely determine whether the world gets locked into a traditional model … or moves onto a better path, with more compact, connected and liveable cities, greater productivity and reduced climate risk.

Experiential Lock-In: Characterizing Avoidable Maladaptation in Infrastructure Systems

Facing the combined challenges of environmental, social, and technological change, long-lived infrastructure systems run the risk of getting locked into unsustainable, maladapted pathways. This is particularly challenging in the context of climate change, given projected climate impacts are characterized by high degrees of uncertainty (Hallegatte 2009). Lock-in is a concept developed by economic historians to describe how economies get tied into using inefficient technologies, and it is linked to the concept of path dependence (Arthur 1983; David 1985), which refers to the fact that infrastructure systems follow specific trajectories that are difficult and costly to change. As shown in Arthur (1989), these trajectories depend on historical circumstances, timing, and strategy as much as on optimality. In the 1990s, some investigations highlighted the need to approach the analysis of technological changes through coevolutionary approaches that recognize the technological systems influences and are influenced by the social, economic, and cultural setting in which they develop (Rip and Kemp 1998). Liebowitz and Margolis (1994) argued that the role of some elements of the system, such as network externalities, remains contested. Of particular interest is the extent to which favoring incumbent infrastructure systems limits the development capacity of socioeconomic groups such as communities, industries, or countries. While exploring the whole phase space of possible fundamental influences is impractical, the authors argue that it is still possible to avoid some lock-in by effectively utilizing existing anticipatory capacity. The paper elaborates on three ideas, firmly rooted in the scholarly literature and recent studies, which characterize one type of avoidable lock-in: (1) the observed dominance of experiential versus analytical anticipatory capacity of communities, industries, and countries in the governance of sociotechnical systems; (2) the existence of formal approaches to quantify the limits to adaptation in such systems; and (3) limitations of the impact and capacity approach to adaptation. The elements of an avoidable lock-in are then summarized and illustrated by an example. Finally, some conclusions are given on the implications of this type of avoidable lock-in and how it might increasingly affect policy decisions that have long-term implications, such as those related to long-lasting infrastructure systems and spatial planning.

Promoting the Use of Climate Information to Achieve Long-Term Development Objectives In Sub-Saharan Africa

While the impacts of climate change are being felt by people and communities now, many of the most severe impacts will be felt in the decades to come. This presents significant barriers to achieving long-term development objectives – particularly in sub-Saharan Africa, a region with low capacity to adapt to the future impacts of climate change. Factoring medium- to long-term climate information into investments and planning decisions is therefore an important component of climate-resilient development.We know little about how climate information is used in Africa to make decisions with long-term consequences, or how effective it is. We know even less about the barriers to – and opportunities for – using climate information in decision-making. How, then, should governments, businesses and donors strive for climate information to achieve Africa’s long-term development objectives?The Future Climate For Africa (FCFA) programme explores these questions and seeks to challenge many of the assumptions that underlie them. To guide the programme, six case studies investigated how climate information was being used in decisionmaking in sub-Saharan Africa. These comprised four country case studies: Malawi, Rwanda, Zambia and a combined study of Accra, Ghana and Maputo, Mozambique; and two desk-based studies focused on long-lived infrastructure in the ports sector and the large hydropower sector. This report presents the results of the scoping phase.

The (Under) Performance of Mega-Projects: A Meta-Organizational Perspective

This study links evolution in organizational structure to ambiguity in the definition of performance in the context of organizations formed to develop long-lived infrastructure: so-called ‘mega-pro...

Environmental assessments for the greening of public infrastructure in South Africa

South Africa has announced another massive investment plan in infrastructure, amounting to R3.2 billion. This plan takes the guise of a National Infrastructure Plan made up of more than 150 projects clustered into 18 strategic infrastructure projects. Most of these projects consist of long-lived social and economic infrastructures planned to deliver services for many decades. Meanwhile, South Africa is reaching its environmental boundaries and faces a crucial need to reduce the environmental impacts of its development path. Owing to the lump-sum investment the projects represent and the lock-in effects they induce once projects are built, long-lived infrastructure projects have to be part and parcel of the country's decoupling strategy to sustain service delivery over the long term, and thereby support economic growth and service access. This paper seeks to highlight the role that environmental impact assessments and strategic environmental assessments could play in supporting the greening of public infrastructure as a decoupling means for South Africa.

Lifecycle costing sensitivities for zero energy housing in Melbourne, Australia

• Examined assumptions applied to lifecycle costing of zero energy housing scenarios. • Case study of housing in Victoria, Australia. • Changes to key assumptions have a significant impact on lifecycle cost outcomes. • The use of conservative or historical data is problematic for policy development. • Need to review assumptions applied by policy-makers regarding housing performance. Minimum energy efficiency standards for new housing are typically informed by regulatory impact statements, underpinned by lifecycle costing (LCC) analysis. While LCC techniques are empirical and testable, such analysis is informed by considerable assumptions on key parameters. These assumptions are often heavily contested in the literature and by built environment stakeholders, but there is limited exploration of their implications within wider policy developments. This paper addresses this gap by analysing the impact of a number of assumptions and their implications within a LCC analysis of zero energy housing options in Victoria, Australia. The results show that changes to assumptions on key parameters have significant impact on LCC outcomes, with associated policy implications. Analysis shows that there is a requirement for a detailed review and debate of the assumptions applied within LCC analysis which is used to inform the development of minimum energy efficiency standards in Australia and internationally. In particular, as housing is a long-lived infrastructure, the issue regarding the use of assumptions based upon historical data or data based upon future predictions is critical to the development of policy and energy efficiency standards.

Climate change risks to US infrastructure: impacts on roads, bridges, coastal development, and urban drainage

Changes in temperature, precipitation, sea level, and coastal storms will likely increase the vulnerability of infrastructure across the United States. Using four models that analyze vulnerability, impacts, and adaptation, this paper estimates impacts to roads, bridges, coastal properties, and urban drainage infrastructure and investigates sensitivity to varying greenhouse gas emission scenarios, climate sensitivities, and global climate models. The results suggest that the impacts of climate change in this sector could be large, especially in the second half of the 21st century as sea-level rises, temperature increases, and precipitation patterns become more extreme and affect the sustainability of long-lived infrastructure. Further, when considering sea-level rise, scenarios which incorporate dynamic ice sheet melting yield impact model results in coastal areas that are roughly 70 to 80 % higher than results that do not incorporate dynamic ice sheet melting. The potential for substantial economic impacts across all infrastructure sectors modeled, however, can be reduced by cost-effective adaptation measures. Mitigation policies also show potential to reduce impacts in the infrastructure sector – a more aggressive mitigation policy reduces impacts by 25 to 35 %, and a somewhat less aggressive policy reduces impacts by 19 to 30 %. The existing suite of models suitable for estimating these damages nonetheless covers only a small portion of expected infrastructure sector effects from climate change, so much work remains to better understand impacts on electric and telecommunications networks, rail, and air transportation systems. In addition, the effects of climate-induced extreme events are likely to be important, but are incompletely understood and remain an emerging area for research.

Addressing ‘deep’ uncertainty over long-term climate in major infrastructure projects: four innovations of the Thames Estuary 2100 Project

Climate change brings new challenges for traditional environmental risk management, particularly for major infrastructure projects, where the decisions made today can have long-term implications. A major challenge is that projections of future climate are deeply uncertain. If this uncertainty is not managed appropriately, long-lived infrastructure may need to be replaced or expensively retrofitted before the end of the design lifetime. The Thames Estuary 2100 Project (TE2100) was one of the first major infrastructure projects to explicitly recognise and address the issue of the deep uncertainty in climate projections throughout the planning process. In this paper, we discuss the innovations and techniques that were adopted in this case that enabled it to cope with this uncertainty. We classify the overall approach as ‘dynamic robustness’, which aims to build flexible strategies that can be changed over time as more is learnt or as conditions change. The project combined four key innovations: (1) the ‘decision-centric’ process; (2) the combination of numerical models and expert judgement to develop narrative sea level rise scenarios; (3) the adoption of an ‘Adaptation Pathways’ approach to identify the timing and sequencing of possible ‘pathways’ of adaptation measures over time under different scenarios; and (4) the development of a monitoring framework that triggers defined decision points. A secondary focus of this paper is an exploration of how climate information was used in TE2100. We suggest that the techniques employed in TE2100 imply different needs from climate science that may cause them to redefine their research priorities related to adaptation; namely a shift in emphasis away from probabilistic modelling, toward greater investment in observations and monitoring; improved understanding of historical climate variability; and improved understanding of physical Earth system processes and their representation in models to enhance ‘best guess’ models and to better bound future projections using narrative scenarios.