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.
Prior work has established that changes in temperature, precipitation, sea level, and coastal storms will increase the vulnerability of infrastructure across the United States (US) (Neumann et al. 2010b; Neumann and Price 2009; Transportation Research Board 2008; Larsen et al. 2008; Wright et al. 2012; Wilbanks et al. 2012; Wilbanks et al. 2007; USGAO 2013). Using four models of the vulnerability, expected impacts, and adaptation options for infrastructure (including consideration of the role infrastructure plays in protecting economic activity and property value), this paper estimates how roads, bridges, coastal properties, and urban drainage infrastructure respond to a range of climate stresses under varying emission scenarios, climate sensitivities, and global climate models. For the first time, impacts on a diverse set of coastal and non-coastal infrastructures are evaluated in a common framework, and, most important, the results demonstrate that reductions in greenhouse gas (GHG) emissions, which in turn lessen the magnitude of the sea-level rise (SLR), temperature, and precipitation stressors on infrastructure, reduce climate change impacts to infrastructure by more than one third. These analyses are part of a multi-sectoral, national-scale climate change impacts and benefits project, described in Waldhoff et al. (Submitted for publication in this issue), that is designed to estimate the benefits of GHG mitigation actions in an integrated and consistent way.
In this paper, we provide insights regarding the potential for adaptation to reduce vulnerabilities in each sector, and, through analysis of alternative emissions scenarios that represent the results of GHG mitigation efforts, discern the effect of mitigation strategies in reducing climate damages. Detailed descriptions of the GHG emissions scenarios, along with projections of global climate change, are provided in Paltsev et al. (2013) of this special issue. In short, three emission scenarios are used: a reference (REF) or ‘business as usual’, and two scenarios representing futures with policies that limit global GHG emissions such that radiative forcing levels in 2100 are stabilized at 4.5 W/m2 (Policy 4.5) or 3.7 W/m2 (Policy 3.7).
The framework used to project future climate, which employs the Community Atmospheric Model linked with the Integrated Global Systems Model (IGSM-CAM), is presented in Monier et al. (Submitted for publication in this issue), along with details on the regional projections of climate change. The IGSM-CAM system also provides an opportunity to examine the impact of alternative climate sensitivity values of 2, 3, 4.5, and 6 °C on impacts –we report results for the 3 °C climate sensitivity alternative as a central result.
Since the IGSM-CAM climate scenario reflects the results of a single general circulation model (GCM), simplified representations of two additional GCM patterns were employed to analyze the structural uncertainties associated with GCM selection, in particular with respect to precipitation projections in the contiguous US. Monier et al. (Submitted for publication in this issue) describes how these GCM patterns were used to produce a range of precipitation futures for the REF and Policy 3.7 scenarios: MIROC representing a dryer pattern, and CCSM a wetter future. Additional details on the IGSM-CAM and IGSM pattern-scaling climate projections are provided in Online Resource 1.
Using this consistent set of emissions and climate scenarios to evaluate impacts and assess adaptation potential for a diverse range of infrastructure types is unique – in addition, nowhere else have mitigation and adaptation as alternative and complementary policies for reducing impacts to infrastructure been jointly assessed. The remainder of the paper describes the methods and results of impact and adaptation modeling for each of the four sectors addressed, and concludes with a brief synthesis and priorities for further research.
2 Coastal effects
Several past efforts have characterized or quantified the effects of SLR on US coastal resources (see CCSP 2009 for a summary), but only a few of the models that have been applied are tractable for economic analyses at a national scale (Neumann et al. 2010a), and only local or global-scale models have considered the role of mitigation policies in reducing effects of SLR (Nicholls et al. 2011; Yohe et al. 2011). We rely on US Environmental Protection Agency’s (USEPA) National Coastal Property Model (NCPM), which comprehensively examines the contiguous US coast at a detailed 150 m × 150 m grid level; incorporates site-specific elevation, land subsidence, and property value data; estimates cost-effective responses to the threat of inundation; and provides economic impact results for three categories of response: shoreline armoring, beach nourishment, and property abandonment (Neumann et al. 2010b – note that inland, riparian flooding effects are addressed in a companion paper in this special issue, see Strzepek et al., Submitted for publication in this issue). Additional methodological details for this application of the NCPM are described in Online Resource 2.
The scenarios used here reflect the IGSM results for global SLR through 2100 (see Paltsev et al. 2013), but also incorporate adjustments to account for the omitted effect of dynamic ice-sheet melting, a potentially important factor for SLR projections (Meier et al. 2007). Dynamic ice-sheet melting scenarios incorporate estimates from the empirical model of Vermeer and Rahmstorf (2009), and use as inputs the decadal trajectory of global average air temperature results from the IGSM results. The results of this adjustment are shown in Fig. 2 of Online Resource 2 – the adjustment increases SLR results that derive directly from the IGSM model by as much as a factor of 2.5 in 2100, yielding SLR estimates of about 1.4 m by 2100, but the effect of incorporating estimates of dynamic ice-sheet melting is much stronger at the end of the 21st century than in the early and mid-21st-century periods.
The cumulative undiscounted results of NCPM economic modeling over the 21st century for the scenarios that incorporate dynamic ice sheet melting are presented in Table 1 of Online Resource 2. Dynamic ice sheet melting scenario economic impact results are roughly 70 to 80 % higher than results that do not incorporate dynamic ice sheet melting. Discounting at 3 % the annual trajectory of results reduces all estimates by a factor of approximately 3 to 4 – discounting has a substantial effect because of the upward sloping trajectory of SLR scenarios, with impacts evident throughout the century but growing larger at the end of the century.
As expected, higher climate sensitivities, on the left side of Fig. 1, yield higher impact estimates. Mitigation Policy 3.7 reduces damages in both the 3 and 2 °C climate sensitivity runs by $68 billion ($6.2 billion discounted at 3 %), but with climate sensitivity of 6 °C the benefits of this policy increase to $87 billion ($8.1 billion at 3 %). Results for the 3˚C climate sensitivity runs show that most of the benefits of mitigation policy $57 billion ($5.3 billion at 3 %) compared to $68 billion ($6.2 billion at 3 %) can be realized through Policy 4.5.
These results reflect the existing NCPM’s capability to analyze threats of gradual inundation from SLR. A growing body of literature suggests, however, that the combined effect of SLR and storm surge on coastal properties may be critically important (Tebaldi et al. 2012, Lin et al. 2012). The effects of climate change on storm surge are two-fold: 1) changing storm frequency and severity in a given location; and 2) SLR providing a higher “launch point” for surge even if storm frequency and severity remain constant. Both effects have been demonstrated in prior work for non-US sites (see Neumann et al. 2012 for application in Vietnam), applying a cyclone simulation model (Emanuel et al. 2008), a storm surge estimation model (NOAA’s SLOSH model) and local elevation and property value data. The international applications, however, often suffer from poor elevation and property value data, limiting the usefulness of the approach to estimate economic impacts. These data limitations are greatly reduced at US sites.
Preliminary results of combining the cyclone simulation model used in Neumann et al. (2012) with the elevation and property value estimates in the NCPM are available for two US sites: Tampa, Florida and New York City. Incorporating storm surge also requires modifying the NCPM in three ways: 1) Estimating a cumulative distribution function for location-specific storm surge; 2) Estimating a cumulative distribution function for economic damages (similar to the approach applied in Kirshen et al. 2012); and 3) Adding another response option (property elevation) that represents a cost-effective alternative in areas subject to episodic flooding but which are not permanently inundated.
A parallel effort within the CIRA program examined the effects of SLR on socially vulnerable populations in the US (Martinich et al. 2012). The result is that areas which the NCPM anticipates to be abandoned have a higher percentage of socially vulnerable populations than areas likely to be protected. Further, moving from that study’s high scenario (similar to the REF scenario) to that study’s mid scenario (similar to Policy 3.7) substantially reduces the risk of SLR to the socially vulnerable population, and reduces areas likely to be abandoned. This work suggests that mitigation policies, such as those considered here, also have potential to enhance environmental justice objectives.
3 Effects on roads
Changes in temperature and precipitation patterns associated with climate change may pose both risks and opportunities for the management of the US road network. Depending on the specific changes in climate occurring in a given area, the stress imposed on roads may increase or decrease as the climate evolves over time. Chinowsky et al. (2013) present methods for quantifying these risks and estimating the corresponding adaptation costs for four effects: (1) rutting of paved roads from precipitation, (2) rutting of paved roads caused by freeze-thaw cycles, (3) the cracking of paved roads during periods of high temperatures, and (4) erosion of unpaved roads from precipitation. For each of these effects, Chinowsky et al. (2013) show how changes in climate affect road maintenance practices and road design and present an approach for estimating costs. Their approach assumes that adaptation measures will be implemented to maintain the current level of service for roads such that residual impacts (once adaptation measures are implemented) are zero. These adaptation measures include more frequent resealing to avoid rutting (effects 1 and 2 above), use of different pavement binders to avoid pavement cracking (effect 3 above), and more frequent re-grading of unpaved roads to minimize erosion impacts (effect 4 above). Depending on the nature of the changes in climate, the analysis may suggest that climate change results in a net cost or a net cost savings.
To gauge the sensitivity of the results generated by the Chinowsky et al. (2013) approach to the selection of GCMs, the IGSM pattern-scaled results were analyzed. Figure 3 shows the trajectory of adaptation costs under both pattern-scaled scenarios, which can be compared with the IGSM-CAM results. The results show that estimated adaptation costs for the US road network are about 50 % higher for 2025 and 2050, and about one third higher in 2075 and 2100, when comparing the “dry” GCM (MIROC) to the “wet” GCM (CCSM) ($4.7 billion for CCSM versus $3.6 billion for MIROC in the reference scenario). This holds under both the REF and policy cases, and largely reflects the impact of precipitation on unpaved roads. As shown in Figure 1 of Online Resource 3, adaptation costs related to pavement binders and resealing for paved roads are similar with both sets of IGSM pattern-scaled GCMs, but adaptation costs for unpaved roads differ significantly. With the wet GCM (CCSM), the analysis suggests an increase in costs for unpaved roads associated with more frequent re-grading. Results for the dry GCM (MIROC), however, indicate climate change may lead to a cost savings for unpaved roads.
The results can also be used to estimate mitigation benefits – the REF and policy scenarios are indistinguishable in the near-term 2025 projection, but the benefits of mitigation policy grow consistently through 2100, with the annual benefits estimated at roughly $6 billion by 2100 (or about $450 million if discounted at 3 %).
4 Effects on bridges
Impacts of climate change on bridge performance associated with flood vulnerability are estimated based on a published model of changes in peak river flow (Wright et al. 2012). The model uses estimates of changes in maximum daily precipitation and results in changes in peak flow rates for the 100-year return period flood. Bridge performance during these events was estimated based on characteristics in the National Bridge Inventory Database. The results include both numbers of bridges affected and the climate change adaptation costs of maintaining the condition and level of service of the bridges at levels consistent with their current state. Although many bridges are currently vulnerable to bridge scour, the method looks only at the incremental costs of climate change to restore bridge condition in response to changes in the risk of flooding. Additional methodological details for this bridge analysis are described in Online Resource 4.
Figure 1 in Online Resource 4 illustrates the vulnerability results for the bridge analysis – the map shows that climate change is estimated to, in some regions, make up to 90 % of bridges vulnerable to bridge scour (in the New Mexico and West Texas region) – these levels of vulnerability are a significant increase over the estimates of currently deficient bridges. Figure 2 in Online Resource 4 shows the percent of bridges vulnerable to increased peak flow in 2100 under the IGSM-pattern scaling climate projections (for the MIROC and CCSM climate models) under the REF scenario. Figure 3 in Online Resource 4 provides an estimate of the incremental number of bridges at risk from increased peak flows for the REF and two policy scenarios – as illustrated, by 2050 the policy scenarios could avoid damage to 20,000 to 40,000 bridges from peak flow, while by 2100, the cumulative effects are greater, with roughly 100,000 bridges subject to lower risks for the 4.5 policy scenario, and well over 100,000 bridges for the 3.7 policy scenario.
5 Effects on urban drainage
Changes in storm intensity associated with climate change have the potential to overburden urban drainage systems across much of the US. In areas where storm intensity increases significantly, increased investment in urban drainage infrastructure may be necessary to prevent the exceeding of system capacity. No studies to date have presented tractable methods for assessing these effects on a national scale, as storm water modeling is typically performed at the local level (e.g., using the Storm Water Management Model (SWMM) developed by the USEPA). To inform the development of such methods, an illustrative analysis was conducted for 19 cities, demonstrating one potential approach for estimating climate change adaptation costs for urban drainage systems across the US. This analysis focuses on adaptation costs associated with changes in the 10-year, 24-h storm event to be consistent with the design criteria for much urban drainage infrastructure. Additional methodological details for urban drainage infrastructure analysis are described in Online Resource 5.
Assuming that the capacity of each city’s system is sufficient to manage runoff from the baseline (without climate change) 10-year, 24-h storm event.
Estimating the change in rainfall associated with the change in the 10-year, 24-h storm event, which is then converted to an estimated change in runoff based on city-specific runoff coefficients. These coefficients are a function of imperviousness based on the approach in Maidment (1993).
Estimating costs for cities to respond to a more severe 10-year, 24-h storm based on cost data from USEPA (1999) for a range of urban stormwater management measures, with upfront capital of approximately $1.52 per cubic foot, and annual O&M cost of $0.08 per cubic foot.
6 Synthesis and conclusions
The results reported here reinforce prior work about the relative role of adaptation and mitigation policy in the coastal sector (Yohe et al. 2011; Nicholls et al. 2011), characterized by high potential impacts and cost-effective adaptation, and extend those findings to non-coastal sectors. The important story, however, is that mitigation policy provides a steady stream of avoided costs for all four of the infrastructure sectors evaluated here. In the non-coastal infrastructure sectors (roads, bridges, drainage), impacts are most sensitive to precipitation forecasts as well as precipitation and runoff variability, and mitigation policies play a clear role in reducing impacts.
Summary of cumulative undiscounted and discounted (3 %) economic impacts through 2100 for reference and policy scenarios based on IGSM-CAM climate projections and 3.0 °C climate sensitivity (billions of 2005$) Undiscounted
Most avoided costs incurred after 2050, excludes storm surge
Discounted (3 %)
Includes effects to paved and unpaved roads
Discounted (3 %)
Most avoided costs incurred before 2050
Discounted (3 %)
Based on generic modeling in 19 US cities
Discounted (3 %)
TOTAL (discounted 3 %)
Nonetheless, the current coverage of infrastructure impacts by these models omits the potentially important rail, public transit (e.g., subways), and energy and communications distribution networks. In addition, the climate impacts modeled do not include change in climate variability, in particular they omit consideration of much more intense extreme events. However, as illustrated by the storm surge modeling, there is a trend to address these effects more systematically.
The top priorities for new research therefore include expanding the sectoral and climatic scope of the models; exploring the likelihood of cascading infrastructure effects, whereby failure in one sector (e.g. flood protection) will lead to failures in other sectors (e.g., roads, bridges, and drainage); integrating the results of these studies in macroeconomic models, to capture the indirect economic effects of diverting GDP-enhancing capital investments toward climate-defensive infrastructure; and considering other indirect effects, such as business and transportation interruption effects associated with infrastructure failure, including from extreme events.
The authors wish to acknowledge the financial support of the US Environmental Protection Agency’s Climate Change Division (Contracts EP-D-09-054 and EP-BPA-12-H-0024). The views expressed in this document are solely those of the authors, and do not necessarily reflect those of EPA.
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