Download PDF Summer Bridge Issue on Engineering for Disaster Resilience July 1, 2019 Volume 49 Issue 2 The articles in this issue present examples of engineering innovation to develop resilient infrastructure. Climate-Resilient Infrastructure: Engineering and Policy Perspectives Monday, July 1, 2019 Author: Bilal M. Ayyub and Alice C. Hill Each year, governments and the private sector invest trillions of dollars in infrastructure that may not withstand future risks from climate change (Oxford Economics 2017). Most of the world’s new infrastructure will be built in developing countries, which face the dual challenges of disaster response and urbanization (Oxford Economics 2017), but responding to -natural disasters is also a major challenge in developed countries. -Damage from Hurricanes Harvey, Maria, and Irma totaled approximately $265 billion, making 2017 the most expensive hurricane season in US history (Drye 2017; Heathcote 2017; NOAA 2018). Long-lived infrastructure must be resilient to weather extremes, the effects of climate change, and other hazards. Background Infrastructure development requires a broad range of actors, including policymakers, planners, funders, engineers, researchers, and communities. Together they shape the physical structures and services intended to provide critical support to the public for decades. Some of these actors have attempted to integrate consideration of future climate risk into infrastructure decisions. For example, the American Society of Civil Engineers (ASCE) developed a top-down approach for adaptive risk management that starts with the climate scenario and projections shown in figure 1. But despite these promising efforts, innovative ideas and strategies for addressing climate risks are not yet common practice. Figure 1 How can resilience be designed, funded, and incorporated in public infrastructure investments? This question puts engineers and other professionals in a race against a changing climate to enhance planning and design practices. Climate and weather are exhibiting intensifying extremes, but infrastructure systems traditionally have been designed, constructed, operated, and maintained according to assumed stationary climate and weather conditions in stochastic terms, without taking account of future climate change and associated uncertainties that increase and intensify hazards. Adaptation technologies, adaptive designs, and appropriate new policies (e.g., addressing risk management) are necessary to reduce climate impacts and risks. A Changing Climate and National Impacts In 2014 the Intergovernmental Panel on Climate Change (IPCC) concluded that warming of the climate system is unequivocal and that it is extremely likely that the dominant cause of the observed warming since the mid-20th century is human influence. Graphs from the congressionally mandated Fourth National Climate Assessment (NCA4; USGCRP 2018) depict these trends in figures 2 and 3. Since the 1950s, anthropo-genic greenhouse gas (GHG) emissions have driven many of the observed changes, which are unprecedented over decades and even millennia (IPCC 2014). Future GHG emissions are uncertain and depend on many factors, including policy, population growth, globalization, economic activity, and human behavior, all of which require the use of projections to define emissions pathways (European Commission 2015; Hausfather 2018). Figure 2 Figure 3 According to the NCA4, the global annually averaged surface air temperature increased by about 1.8°F (1.0°C) from 1901 to 2016. This 115-year period is now the warmest in the history of modern civilization, and the last few years have also seen record-breaking climate-related weather extremes. Researchers have documented changes in surface, atmospheric, and oceanic temperatures; melting glaciers; diminishing snow cover; shrinking sea ice; rising sea levels; ocean acidification; and increasing atmospheric water vapor. Without major emission reductions from policy, behavioral, or technological change, annual average global temperature relative to preindustrial times could increase by 9°F (5°C) or more by 2100. With significant reductions, it could be limited to 3.6°F (2°C) or less, which would still be associated with serious climate impacts. In light of the uncertainties surrounding how much climate will change, climate scientists and engineers struggle to accurately characterize future climate and weather extremes even in probabilistic terms, requiring projections based on numerous assumptions about GHG pathways. Improving Engineering Design for a Changing Climate While the evidence that climate is changing is very strong, the engineering community has found it difficult to incorporate consideration of climate change at temporal and spatial scales relevant to engineering practice. Development of adaptation and mitigation technologies and strategies has proved elusive based on current practices. As an example, relative sea level rise (SLR) is a locally observable phenomenon that reflects changes in the eustatic sea level, the subsidence or uplift of the sea floor, and the accumulation, erosion, or compaction of sediment along the coast. Sediment accumulation and erosion are greatly affected by subsidence and uplift, so these processes are often mutually reinforcing (ASCE 2018). The tectonic setting of continental margins plays a primary role in determining whether a section of coastline experiences uplift or subsidence due to large landmasses breaking up with geological interactions. In addition, glacial loading contributes through (a) glaciation depression, with associated isostatic adjustments during periods of widespread continental glacial coverage, or (b) rebounding due to glacial retreat, creating uplift at rates slower than that of the retreat. Besides long-term changes on geologic time scales, relative SLR is affected by fluid withdrawal, diversion or elimination of sediment sources, and other human activities. High-resolution SLR projections are important for the development of durable engineering designs. They are useful tools to support coastal hazard mitigation design criteria and communicate projected changes to stakeholders. However, engineering works must also consider the significant unknowns in future SLR, including those resulting from possible GHG pathways and those based on the behavior of ice sheets, which remain uncertain. Dealing with Uncertainty in Engineering Design: Observational Method Civil engineers have dealt with uncertainty in geotechnical engineering practice by employing the observational method (OM), originally proposed by Karl Terzaghi (Nicholson et al. 1999; Peck 1969; Terzaghi and Peck 1948). The specific steps in a climate change OM (modified after Terzaghi and Peck 1948) are as -follows (also see Ayyub and Wright 2016): Project design is based on the most probable weather or climate condition(s) rather than the most unfavorable. The most credible unfavorable deviations from the most probable conditions are identified. A course of action or design modification is devised (in advance) for every foreseeable unfavorable weather or climate deviation from the most probable condition(s). The performance of the project is observed over time (using preselected quantities) and the response of the project to observed changes is assessed. Design and construction modifications (-previously identified) can be implemented in response to observed changes. Figure 4 provides an example and ASCE (2018) includes additional examples. Figure 4 Uncertainties and Design Philosophies The uncertainty associated with future climate is not completely quantifiable, and therefore accounting for it in engineering practice requires understanding and treatment of uncertainty as well as engineering judgment. Uncertainty can be broadly classified as follows for convenience (Ayyub and Klir 2006): recognized and well characterized (e.g., materials properties); recognized but moderately characterized (e.g., future precipitation, hurricanes, wind speed); recognized but poorly characterized (e.g., future -energy use by populations worldwide); recognized but not characterizable (e.g., global governance and cooperation); and of unknown existence or nature (e.g., physical laws or behaviors not yet discovered or undiscoverable based on current methods and research pursuits). Climate projections entail similar types of -uncertainty (Stainforth et al. 2007), although they are expressed differently for the purpose of communication to the public; however, these five classes offer a basis for engineering and planning guides and standards. It is common practice in engineering to classify uncertainties as (a) aleatory and (b) epistemic. The former is considered inherent to the situation and irreducible with data collection, although its characterization can be enhanced. The latter is reducible with data collection or investigation, although the economic cost of investigating the data might not justify the reduction. Planning for a changing climate entails planning not only for climatic uncertainty but also for uncertainty about regulatory, environmental, economic, social, and other conditions affecting an engineering project. Risk Assessment Risk methods provide practical means for managing uncertainty (Ayyub 2014). Risk is commonly measured in simple terms as the probability of occurrence of an event or scenario and the outcomes or consequences associated with the occurrence. Risk assessment is primarily concerned with answering three questions (Kaplan and Garrick 1981): What could happen? How likely is it to happen? If it does happen, what are the consequences? Risk assessment is thus a systematic process to identify potential, uncertain events, including hazards, to estimate occurrence likelihood and determine the consequences of events. Engineers should develop a new paradigm for engineering practice as climate change, population growth, and development patterns alter the risk profiles of projects, communities, and even nations. The effects of climate change may be difficult to estimate with a high degree of certainty in many instances, but clear indications are available of some effects, such as SLR, more frequent extreme heat events, and an increase in the number of extreme events in areas where they have rarely been encountered. These suggest a changing footprint of risk, regardless of the magnitudes of the events on regional or national scales. Accounting for Uncertainty in Engineering Design Engineers design infrastructure by accounting for uncertainties to achieve acceptable safety levels and appropriate physical and economic efficiencies. Uncertainty is thus foundational in developing a design philosophy. Engineering design evolves based on an enhanced understanding of uncertainty. The five types of uncertainty noted above drive engineers toward practice enhancements. When -uncertainty is recognized and well characterized, engineers use tradi-tional factors of safety, followed by -reliability-based design in building codes. For cases 2 and 3, where uncertainty is recognized but moderately or poorly characterized, engineers use reliability-based or risk-informed designs. When dealing with climate change, it is important to recognize that it is not possible to define a hazard with probability distributions a priori. Scenario modeling, which can be used to perform sensitivity analysis and address variability, incorporates conditional probabilistic information such as uncertainties owing to spatial variability of seismic demand, random phasing of ground motion, local soil conditions, and performance levels of civil infrastructure (which can be gauged from fragility curves as conditional probabilities for varied hazard levels). Scenario modeling is helpful to design for a changing climate, but may be insufficient. Robust Decision Making Robust decision making (RDM) can address cases where deep uncertainty is recognized but either poorly characterized or incapable of being characterized. It provides an analytic framework to identify strategies that can perform over a wide range of poorly characterized uncertainties. In turn, RDM strategies may provide a basis for a number of scenarios to be analyzed while incorporating probabilistic information. The RDM framework could identify strategies that would be insensitive to vulnerabilities associated with deep uncertainty in future climate projection models. However, it might not produce cost-effective solutions. Adaptive Risk Management When uncertainty is unrecognizable or it is not possible to fully define and estimate the risks and potential costs for a project to reduce the uncertainty in the timeframe in which action should be taken, engineers should use adaptive design or risk management. These are most effective in cases 4 and 5, although they can be used in others. Wilby and Dessai (2010) present a robust framework called adaptive management of climate risks, which involves monitoring of the environment and systematic assessment of the performance of measures installed. The approach calls for inventorying preferred adaptation strategies that are then synthesized into a subset of measures that reduce vulnerability under the current climate regime. The resulting strategies should be able to perform well over a variety of scenarios, regardless of climate change and conditions. The OM, a technique of adaptive risk management, offers the means to enhance projects’ resiliency to future climate and weather extremes. Rather than design approaches at a particular site based on probabilities of extreme events, engineers should seek alternatives that will do well across a variety of possible conditions, including those not yet identified. Such an approach enables the development of cost-effective strategies for making a project more resilient to future climate and weather extremes by including some initial level of enhanced resilience or adaptation rather than retrofitting later. Seismic engineering research uses performance-based design, meaning a system is designed to operate at a set level of performance typically prescribed in standards. The design focuses on ensuring the functionality, durability, and safety of systems at appropriate mean recurrence intervals. Adaptive risk management extends the concept of performance-based design to account for projected increasing risks from climate change impacts. As the characterization of hazards improves, for example with updated sea level projections, climate risks will be -reexamined and managed for a project using built-in features that act as enablers to system changes in cost-effective terms. Policy Options for Building Resilient Infrastructure It is not just engineers who struggle with how to make sound decisions in the face of climate and other uncertainties. It is also policy- and decision makers in both the government and the private sector. There are at least three ways to ensure that policies guiding infrastructure keep pace with the escalating risks from climate change: planning for future risk, thinking systemically, and mainstreaming green infrastructure. Planning for Future Risk To mitigate future risks from a changing climate, it is necessary to start planning for them. Two ways to advance planning practices are to screen projects for climate resilience and/or require that they comply with resilient building standards and practices. Congress could require that, before any federal funds are invested in an infrastructure project, the project be screened by the funding agency to determine its resilience to climate impacts reasonably expected over the life of the project, including those that may affect operation and maintenance. If the screening reveals that the project will not withstand anticipated risks, the federal government should require alterations in design to ensure resilience or deny funding. Similarly, restricting funding for development in areas at known risk for climate impacts—as Executive Order 11988, signed by President Carter in 1977, does for investments in floodplains—could increase resiliency.[1] To ensure that infrastructure design and construction adequately account for future climate conditions, the federal government could also require that certain standards be met. The Federal Flood Risk Management Standard (FFRMS), established by President Obama (White House 2015) but rescinded by President Trump, is instructive. The directive required that when federal monies funded construction or substantial renovation of a structure in or near a floodplain, the structure had to be elevated 2–3 feet (or to a level consistent with the latest climate science). To encourage federal investment in infrastructure that can withstand future climate extremes, the government could provide incentives for the incorporation of flexible design elements, as in the LOSSAN rail corridor (figure 4). If the project’s design adequately accounts for future impacts, additional federal funds could be provided to cover the potential added cost of building resiliently, by, for example, expanding the size of culverts to handle increased precipitation projected in the foreseeable future. Thinking Systemically Thinking systemically about how to build infra-structure that is resilient to multiple sources of risk can help government policy reduce risks from climate change. For example, after Tropical Storm Allison in 2001, the Texas Medical Center (TMC), which lost 25 years of research data, took drastic steps to reduce future risks from storms to its multiacre campus. Among other measures, TMC relocated electrical equipment, lab animals, and experiments to higher floors. Elevating sensitive components of the hospital’s work also reduced the threat of other risks, such as unauthorized tampering and theft. Incorporating systemic thinking in policy can help ensure that infrastructure is resilient to many types of hazards. After a disaster, the government could require certain types of improvements so that structures are “built back better” as a condition of recovery funds used for rebuilding. Mainstreaming Green Infrastructure Mainstreaming green infrastructure in policy can help avoid costly grey infrastructure projects and may offer as much benefit as the latter. When Hurricane Sandy struck the East Coast in 2012, it overwhelmed many infrastructure services, including flood defenses, which proved inadequate to handle the storm surge in several cases. However, coastal wetlands across the northeastern states prevented an estimated $625 million in additional flood damages during the hurricane (Narayan et al. 2016). Areas with wetlands saw on average 10 percent—and in some cases as much as 29 percent—less property damage. Thus ecosystems can provide valuable risk reduction services that perform as well as or better than infrastructure built by humans. Policy should take this into account and capitalize on the benefits of green infrastructure. Conclusion Coordination between policy and engineering practice is necessary to achieve cost-effective solutions such as climate-resilient infrastructure. Such coordination will depend on changes in the current practices of policy-makers, planners, and designers. References ASCE [American Society of Civil Engineers]. 2018. Climate-Resilient Infrastructure: Adaptive Design and Risk Management, ed Ayyub BM. ASCE Manual of Practice 140. Reston VA. Ayyub BM. 2014. Risk Analysis in Engineering and -Economics, 2nd ed. Boca Raton FL: Chapman & Hall/CRC. Ayyub BM, Klir GJ. 2006. Uncertainty Modeling and -Analysis in Engineering and the Sciences. Boca Raton FL: -Chapman & Hall/CRC. Ayyub BM, Wright RN. 2016. Adaptive climate risk control of sustainability and resilience for infrastructure systems. Journal of Geography and Natural Disasters 6(2):e118. Betts RA, Jones CD, Knight JR, Keeling RF, Kennedy JJ. 2016. El Niño and a record CO2 rise. Nature Climate Change 6:806–810. Dial R, Smith B, Rosca G Jr. 2014. Evaluating -sustainability and resilience in infrastructure: Envision, SANDAG, and the LOSSAN rail corridor. Proceedings of the 2014 International Conference on Sustainable Infrastructure, Nov 6–8, Long Beach CA. Drye W. 2017. 2017 hurricane season was the most expensive in US history. National Geographic News, Nov 30. European Commission. 2015. The Paris Protocol: A blueprint for tackling global climate change beyond 2020. Brussels. Hausfather Z. 2018. Analysis: Fossil-fuel emissions in 2018 increasing at fastest rate for seven years. Carbon Brief, Dec 5. Heathcote C. 2017. Forecasting infrastructure investment needs for 50 countries, 7 sectors through 2040. World Bank Group blog, Aug 10. IPCC [Intergovernmental Panel on Climate Change]. 2014. Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Cambridge: Cambridge University Press. Kaplan S, Garrick BJ. 1981. On the quantitative definition of risk. Risk Analysis 1(1):11–27. Narayan S, Beck MW, Wilson P, Thomas C, Guerrero A, Shepard C, Reguero BG, Franco G, Ingram CJ, -Trespalacios D. 2016. Coastal Wetlands and Flood Damage -Reduction: Using Risk Industry-based Models to Assess Natural Defenses in the Northeastern USA. London: Lloyd’s -Tercentenary Research Foundation. Nicholson D, Tse C, Penny C, O’Hana S, Dimmock R. 1999. The Observational Method in Ground Engineering: Principles and Applications, vol 185. London: Construction Industry Research and Information Association. NOAA [National Oceanic and Atmospheric -Administration]. 2018. Costliest US tropical cyclones tables updated, Jan 26. Olivier JGJ, Peters AHW. 2018. Trends in Global CO2 and Total Greenhouse Gas Emissions. The Hague: PBL -Netherlands Environmental Assessment Agency. Oxford Economics. 2017. Global Infrastructure Outlook. -Sydney: Global Infrastructure Hub. Peck RB. 1969. Advantages and limitations of the Observational Method in applied soil mechanics. Geotechnique 19(2):171–187. Stainforth DA, Allen MR, Tredger ER, Smith LA. 2007. Confidence, uncertainty and decision-support relevance in climate predictions. Philosophical Transactions of the Royal Society A 365(1857):2145–2161. Stewart MG, Deng X. 2015. Climate impact risks and climate adaptation engineering for built infrastructure. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A 1(1):04014001. Terzaghi K, Peck RB. 1948. Soil Mechanics in Engineering Practice. Hoboken NJ: Wiley. USGCRP [US Global Change Research Program]. 2018. Vol I: Climate Science Special Report, and Vol II: Impacts, Risks, and Adaptation in the United States. Washington. White House. 2015. Presidential Executive Order – -Establishing a Federal Flood Risk Management Standard and a Process for Further Soliciting and Considering Stakeholder Input, Jan 30. Washington. Wilby RL, Dessai S. 2010. Robust adaptation to climate change. Weather 65(7):180–185. [1] https://www.fema.gov/executive-order-11988-floodplain- -management About the Author:Bilal Ayyub, PE, is a professor and director of the Center for Technology and Systems Management, Department of Civil and Environmental Engineering, University of Maryland at College Park. Alice Hill is a research fellow at the Hoover Institution, Stanford University.