Poster session for Special Task Force on Climate Change and Energy.
Integration of ENSO Hazards Risk Assessment into Transportation Systems Planning
Karl Kim, University of HawaiiShow Abstract View Presentation
Rashed Chowdhury, University of Hawaii
Pradip Pant, Hawaii Department of Transportation
Eric Yamashita, University of Hawaii
Following description of ENSO (El Niño-Southern Oscillation) climate patterns and resulting hazards (hurricane, rainfall, flooding, drought, wildfires, high winds, and storm surge), the implications for transportation systems (road, rail, transit, auto, pedestrian, bicycle) are summarized. Based on strong El Niño years, the impacts on California, Hawaii, and the Pacific Islands are described to demonstrate the diversity of effects and investigate responses and requirements for emergency managers, transportation system operators, and planners concerned with mitigation and adaptation. While the focus is on the Pacific, the implications for other regions are also described. With climate change, ENSO effects are expected to increase and efforts to understand and manage impacts on transportation are needed. In addition to more research on ENSO's impacts on transportation, there is need for training and education as part of efforts to increase transportation system resilience. ENSO applications provide a needed middle-ground pathway towards connecting discrete, localized weather events to larger, longer-term changes in climate and resilience capabilities.
Designing a Climate-Ready Coastal Road
Jo Sias, University of New HampshireShow Abstract View Presentation
Jayne Knott, JFK Environmental Services LLC
Jennifer Jacobs, University of New Hampshire
Paul Kirshen, University of Massachusetts, Boston
Eshan Dave, University of New Hampshire
Greenhouse gas emissions have caused global temperatures to rise since the mid-20th century accompanied by sea-level rise (SLR). Temperature increases and SLR-induced groundwater rise have been shown to cause premature pavement failure in many roadway structures. Hybrid bottom-up/top-down (hybrid) adaptation approaches have shown promise by initially investigating an asset’s response to incremental environmental change and then identifying the timing of critical effects for budgetary planning. This improves practitioners’ understanding of the asset’s climate resiliency and informs adaptation-plan development to minimize both cost and risk. In this study, a hybrid approach to pavement adaptation with climate-change-induced temperature and groundwater rise is demonstrated at a case-study site in coastal New Hampshire. The hot-mix-asphalt (HMA) thickness that achieves a minimum of 85% reliability is calculated for 70 combinations of incremental temperature and groundwater rise. Increasing the base-layer thickness improves resiliency against rising temperatures, but rising groundwater diminishes this improvement demonstrating that both HMA and base-layer thickness increases are needed. Thirteen adaptation pathways are evaluated for pavement performance, life-cycle costs, and road-surface inundation over a 60-year pavement management period. A stepwise and flexible adaptation plan is developed that includes HMA overlays with prescribed thickness and application timing, base-layer rehabilitation options, and re-evaluation opportunities.
Performance Evaluation of Public Transit Systems Under Extreme Weather Events: Does Organizational Adaptive Capacity Matter?
Fengxiu Zhang, George Mason UniversityShow Abstract
The study examines the effects of extreme weather events on the technical efficiency of public transit agencies. In response to the growing call for adaptive capacity development in face of a changing climate, it pays special attention to the role of adaptive capacity in modulating weather impacts. Three components of an organization’s adaptive capacity are examined: formal institution, organizational slack and contracting out (the inverse of adaptive capacity). Using a sample of 108 U.S. motorbus transit system in the Northeast and Midwest from 2008 to 2017, the analysis applies the panel data stochastic frontier model (SFA) proposed by Battese and Colelli (1995). A general model is estimated to incorporate the heterogeneity in both the level and efficiency of output. The results point to the negative impacts of extreme weather on technical efficiency of transit systems, and confirm the positive role of adaptive capacity to reduce those impacts. The conclusion ends with a discussion on the theoretical and practical implications of this study.
Predicting and Visualizing Flood Risk in Subway Tunnels
Dmitrijs Obolevics, Arup USAShow Abstract View Presentation
Dominic Herkes, Arup USA
Camille Tigner, Arup USA
The destruction and damage caused by Hurricane Sandy to the New York City subway system in 2012 demonstrated that the subway infrastructure is particularly vulnerable to major surge flooding events. New York City Transit (NYCT) appointed Arup to undertake a hydraulic modeling study as part of their Sandy Recovery and Resiliency program. This study is focused on development of hydraulic models representing subway tunnels that potentially can be inundated during a major storm surge event. Hydraulic models were developed based on the data provided by NYCT, such as subway tunnel data, locations of vulnerabilities and their existing and/or planned flood mitigation measures. Model simulations were setup and run for a variety of scenarios, including different operational status of pumps and effectiveness of flood protection measures under three storm surge events: SLOSH Category 1 and 2 and Nor’easter. An interactive dashboard web viewer was developed displaying the outputs of hydraulic model simulation runs. The dashboard provides NYCT users with a valuable tool that can be used to assist in operational strategies, and to develop and prioritize capital investment to improve resiliency of subway system relative to flood protection measures.
Transportation Infrastructure Resilience Overview in Coastal Areas Due to Sea-Level Rise and Climate Change: Impacts, Challenges, and Proactive Solutions
Joshua Burroughs, University of Hawai'i, ManoaShow Abstract View Presentation
Guohui Zhang, University of Hawai'i, Manoa
David Ma, University of Hawai'i, Manoa
Sea-level rise has generated significant impacts in coastal regions and become more prominent on the effects of climate change. With the increase in sea-level, further impacts are deteriorating the surface that it consumes slowly, yet rapidly over the years. Regions such as Hawai’i, Rhode Island, Florida and various other states are introduced to the reoccurrence of surges due to storms/hurricanes and mass floods. What exactly causes these drastic results and how do we prevent it from repeatedly occurring in the future? Do these instances occur naturally or does human contact and development accelerate its appearance? Thus, the importance of this paper aims to provide a comprehensive literature review on transportation infrastructure resilience quantification in coastal areas. Sea-level rise and climate change impacts, coastal transportation vulnerability, proactive adaptation measures for enhanced infrastructure resilience and solution implementation and smart decision-makings are examined during this paper in order to gain a better understanding, not just for major corporations, but also communities that are affected during these catastrophic events.
Evaluation and Prediction of Transportation Resilience Under Extreme Weather Events: A Novel Sequence to Sequence Deep-Learning Approach
Hong-Wei Wang, Shanghai Jiao Tong UniversityShow Abstract
Zhong-Ren Peng, University of Florida
Yuan Meng, DiDi Smart Transportation
Tianlong Wu, DiDi Smart Transportation
Weili Sun, DiDi Smart Transportation
Qing-Chang Lu, Chang'an University
Resilience offers a broad social-technical framework to deal with breakdown, response and recovery of transportation networks adapting to various disruptions. Although current research works model and simulate transportation resilience from different perspectives, the real-world resilience of urban road networks is still unclear. In this paper, a novel sequence to sequence network extended model with attention mechanism and a resilience dynamic-capturing algorithm were proposed to estimate and predict the spatiotemporal patterns of transportation resilience under extreme weather events. The presented model fully considers the spatiotemporal features of urban road network and evaluates transportation resilience based on real-world big data, including on-demand ride services data provided by DiDi Chuxing and grid meteorological data. Results show that aggregate data could be used for transportation resilience analysis if historical disaster data are limited under extreme weather events. In terms of observed transportation resilience, transportation network demonstrates different characteristics between sparse network and dense network, as well as general precipitation events and extreme weather events. The response time is double or triple the recovery time, and an elastic limit exists in the recovery progress of network resilience. In terms of resilience prediction, the proposed model outperforms traditional models with higher accuracy and has better predictions of the system performance degradation than other resilience indices. The above results could assist researchers and policy makers clearly understand the real-world resilience of urban road networks in theory and practice, so as to take effective responses under emergent disruptive events.
Incorporating Climate Change Considerations into a State Transportation Agency: The Caltrans Experience
Reza Navai, California Department of Transportation (CALTRANS)Show Abstract
Tracey Frost, California Department of Transportation (CALTRANS)
Michael Flood, WSP
Michael Meyer, WSP
This paper describes a self-assessment process Caltrans used to identify where climate change adaptation considerations could be integrated into agency decision making. The background of the State’s interest in climate change is described as is the rationale for the proposed assessment framework. The recommendations for eight functional areas (e.g., planning, engineering, operations, etc.) that resulted from this assessment are presented. The paper concludes that the self-assessment process was very useful to agency managers for defining where climate change adaptation could be considered more effectively within the agency.
Understanding Thermal Impact of Roads on Permafrost Using Normalized Spectral Entropy
Chi Zhang, Chang'an UniversityShow Abstract
Hong Zhang, Chang'an University
Permafrost is characterized by low temperature, whose thermal stability is key to geohydrological cycles, energy exchange, and climate regulation. Nonetheless, increasing engineering activities, road construction and operation, are affecting the thermal stability in permafrost regions and has already led to the degradation of permafrost and related environmental problems. To understand the spatiotemporal influence of human engineering activities on the thermal dynamics in permafrost regions, we placed the study in Ela Mountain Pass with multiple roads intersected on Qinghai-Tibet Plateau and calculated the thermal dynamics from 2000 to 2017 using a powerful index – normalized spectral entropy (measuring the disorderliness of time series data). Our results indicate road level is a significant affecting factor, where high-level roads (i.e., expressway) exhibit stronger thermal impacts than low-level roads (i.e., province-level road and county-level road). Our results also indicate that operation duration is the most significant factor that determines the thermal impacts of roads on permafrost: the thermal impacts of the newly paved expressway is positively related to elevation, while the thermal impacts of the old expressway are positively related to less vegetated area. The study provides an excellent method to understand the spatiotemporal impacts of engineering activities on the temperature dynamics in permafrost regions, thereby helping policymakers in China and many other countries to better plan their infrastructure project, so as to avoid environmentally vulnerable regions. The study also calls for advanced technique in road maintenance, which can reduce the accumulated disturbance of road operation on permafrost regions.
Hurricane Wind and Storm Surge Effects on Coastal Bridges Under a Changing Climate
Reda Snaiki, University at Buffalo, SUNYShow Abstract View Presentation
Teng Wu, University at Buffalo, SUNY
Andrew Whittaker, University at Buffalo, SUNY
Joseph Atkinson, University at Buffalo, SUNY
Hurricanes and their cascading hazards are often responsible for widespread damage to life and property, and are the largest contributor to insured annual losses in U.S. coastal areas. Such losses are expected to increase due to the changing climate and growing coastal population density. An effective methodology to assess hurricane wind and surge hazard risks to coastal bridges under changing climate conditions is proposed. The influence of climate change scenarios on hurricane intensity and frequency is first explored. Then, a framework that couples the hurricane tracking model (consisting of genesis, track and intensity) with a height-resolving analytical wind model and a newly developed machine learning-based surge model is used for risk assessment. The proposed methodology is applied to a coastal bridge to obtain its traffic closure rate resulting from the observed (historic) and future hurricane winds and storm surges, demonstrating the effects of changing climate on the civil infrastructure in hurricane-prone region.
Data Predictive Approach to Estimate Nuisance Flooding Impacts on Roadway Networks: A Case Study of Norfolk, Virginia
Shraddha Praharaj, University of VirginiaShow Abstract View Presentation
T. Donna Chen, University of Virginia
Madhur Behl, University of Virginia
Climate change and sea level rise have increased the frequency and severity of nuisance flooding, leading to cascading impacts on roadway networks in coastal cities. This paper’s study area, Norfolk, Virginia, is a low elevation coastal city where road users frequently experience excessive delays or are unable to travel due to localized nuisance flooding. Due to the lack of spatially and temporally disaggregate transportation and hydrology agency data, nuisance flooding impacts is less well-studied compared to major disasters. This study combines various agency and crowdsourced data for transportation and hydrology to formulate a data-predictive model to estimate link-by-link traffic flow in the Norfolk roadway network for a 20-month period containing 10 days with reported roadway flooding. The model estimates a citywide 3% reduction in vehicle-hours of travel (VHT) on days with reported flooding compared to days without reported flooding. Similarly, a 12% reduction in traffic volume and 6% reduction in travel speed is observed in the spatially limited ground truth data. While the number of days with reported flooding is a small sample, there exists a correlation between reduced VHT and increased rainfall intensity. This study provides a data predictive modelling framework for expanding spatially or temporally limited agency data, using crowdsourced data to supplement ground truth data. For this specific application, study results also suggest the need for even more spatially and temporally disaggregate data to fully capture the localized effects of nuisance flooding.
Application of Dynamic Adaptive Planning and Risk-Adjusted Decision Trees to Capture the Value of Flexibility in Resilience and Transportation Planning
Prerna Singh, Georgia Institute of Technology (Georgia Tech)Show Abstract View Presentation
Baabak Ashuri, Georgia Institute of Technology (Georgia Tech)
Adjo Amekudzi-Kennedy, Georgia Institute of Technology (Georgia Tech)
Transportation infrastructure around the world is under stress to perform with ever-changing climate scenarios, unpredictable disasters, and stress on resources stemming from rapid urbanization and population growth. Current approaches to developing resilience applied to the transportation system focus primarily on engineering resilience, and do not explicitly deal with deep uncertainties arising from climate change. This paper reviews adaptation, a critical aspect of a resilient system in an uncertain and changing environment, as applied in the transportation resilience literature. It compares and contrasts the status of adaptive resiliency in transportation with that in other fields to highlight gaps and research opportunities. The paper then presents Dynamic Adaptive Planning (DAP) as a method to deal more effectively with deep uncertainty in decision making and offers an approach that combines economic analysis with DAP to enhance decision making under external uncertainties, such as natural disasters, with financial constraints. It presents a case-study of San Francisco-Oakland Bridge to demonstrate the economic benefits of DAP. This paper provides transportation practitioners with guidance on the application of DAP and understanding the economic benefits of such an approach to decision making in various settings including emergency response planning, long range planning, maintenance and renewal planning, and operations planning. The paper also identifies future research combining financial theory with dynamic adaptive planning as important in developing more robust decision-making frameworks for handling deep uncertainty.
Urban Goods Movement and Local Climate Action Plans: Assessing Strategies to Reduce Greenhouse Gas Emissions from Urban Freight Transportation
Andrew Goetz, University of DenverShow Abstract
Serena Alexander, San Jose State University
This paper examines how freight transport/goods movement has been addressed in U.S. city climate action planning. Transportation is a major contributor of greenhouse gas (GHG) emissions, and freight transport represents a growing component of transportation’s share. Almost all climate action plans (CAPs) address transportation generally, but we focus on efforts to reduce GHG emissions from freight transport specifically. We analyzed 27 advanced local CAPs to determine whether freight transport was targeted in goals and strategies to reduce GHG emissions. We found only six CAPs that included direct measures or programs to reduce freight emissions. Many of the CAPs mentioned general transportation objectives such as lowering vehicle miles traveled or reducing emissions from city-owned vehicle fleets, but most did not include strategies or actions that explicitly targeted freight transport. We identified the strategies and actions that cities are taking to address GHG emissions from freight transport, such as promoting anti-idling and encouraging transitions to electric and alternative fuel delivery vehicles. We also analyzed freight transport plans relevant for the same cities, and found that most do not explicitly mention reducing GHG emissions. Most of the freight plans are focused on improving reliability and efficiency of freight movement, which has the ancillary benefit of reducing GHG emissions, but that goal was not explicitly targeted in most of these plans. Based on our findings, we recommend that cities specifically target freight transport goals and strategies in their CAPs and better coordinate with planners developing freight transport plans to identify GHG emission reduction approaches.