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City governments incorporate ICTs into government services to improve citizen participation and access to those services. Too much dependence on technology, however, can lead to concerns about creating a digital divide between different groups of citizens. The potential for digital inequality is a critical issue that can be exacerbated by insufficient attention being paid to vulnerabilities across communities. Given that socio-economically vulnerable populations are the ones who need government services the most, especially during disaster events, it is critical to investigate the extent to which digital inequality is an issue for technology-based government services. With this in mind, this paper analyzes the use of different technology-enabled access options for a representative eGovernment service system, the New York City 311 service system, in the early stages of the COVID-19 pandemic. Two sets of socio-economically distinct locations in New York City are compared, using average income as a proxy for vulnerability, to draw conclusions about potential inequalities in such a system during a crisis.

Coastal populations are facing increasing environmental stress from coastal hazards including sea level rise, increasing tidal ranges, and storm surges from hurricanes. The East and Gulf Coasts of the United States (U.S.) are projected to face high rates of sea level rise and include many of the U.S.’s largest urban populations. This study proposes modelling land-use change and coastal change between 1996-2019 to project the impacts of intensifying coastal hazards on the U.S. Gulf and East Coast populations and to estimate how coastal populations are growing or retreating from high-risk areas. The primary objective is to develop a multifaceted spatial-temporal (MuST) framework to model coastal change through land-use projections and thorough analysis of the indicators of coastal urban growth or retreat. While urban growth models exist, one that presents an interdisciplinary evaluation of potential growth and retreat due to geographic factors and coastal hazards has not been released. This study proposes modelling urban growth using geospatial metrics including topographic slope, topographic elevation, distance to existing urban areas, distance to existing roads, and distance to the coast. The model will also use historic hurricane data, including storm track and footprint for named storms between 1996-2019 and the associated flood claims datamore »from Federal Emergency Management Agency (FEMA), to account for existing impacts from coastal storms. Additionally, climate change data including sea level rise projections and future tidal ranges will be incorporated to project the impacts of future coastal hazards on urban expansion over the next 30 years (2020-2050). The basis of the urban growth model compares land-use change between 1996-2019 to complete a geospatial analysis of both the areas shifting from rural (agricultural, forest, wetlands) to urban, indicating growth and population data from 2000-2020, to evaluate coastal retreat or abandonment over the next 30 years.« less

Barrier island models that include marsh and lagoon processes are highly parameterized. To constrain model uncertainty, those desiring to use these models should seek a robust understanding of the parameter sensitivities. In this study, global sensitivity analysis was performed on a long-term barrier island model to yield insights into the modeled barrier-backbarrier system. Given that a variety of global sensitivity analysis methods exist, each one appearing to differ in its implementation, computational burden, and output, three methods (i.e., the Two-Level Full Factorial Method, Morris Method, and Sobol Method) were applied to the model for the purposes of comparison. Key influential parameters (e.g., sea level rise rate, equilibrium/critical barrier width, and reference wind speed) were consistently identified by all three sensitivity analysis methods. Despite the relatively low number of simulations required by the Morris Method, the Two-Level Method computationally outperformed the others, warranting further exploration of the Morris Method’s parallelization structure. These results may be used to help identify parameter constraints and characterize model uncertainty toward more confident predictions and management decisions for coastal barrier systems.

Storm surge flooding caused by tropical cyclones is a devastating threat to coastal regions, and this threat is growing due to sea-level rise (SLR). Therefore, accurate and rapid projection of the storm surge hazard is critical for coastal communities. This study focuses on developing a new framework that can rapidly predict storm surges under SLR scenarios for any random synthetic storms of interest and assign a probability to its likelihood. The framework leverages the Joint Probability Method with Response Surfaces (JPM-RS) for probabilistic hazard characterization, a storm surge machine learning model, and a SLR model. The JPM probabilities are based on historical tropical cyclone track observations. The storm surge machine learning model was trained based on high-fidelity storm surge simulations provided by the U.S. Army Corps of Engineers (USACE). The SLR was considered by adding the product of the normalized nonlinearity, arising from surge-SLR interaction, and the sea-level change from 1992 to the target year, where nonlinearities are based on high-fidelity storm surge simulations and subsequent analysis by USACE. In this study, this framework was applied to the Chesapeake Bay region of the U.S. and used to estimate the SLR-adjusted probabilistic tropical cyclone flood hazard in two areas: One ismore »an urban Virginia site, and the other is a rural Maryland site. This new framework has the potential to aid in reducing future coastal storm risks in coastal communities by providing robust and rapid hazard assessment that accounts for future sea-level rise.« less

This paper will discuss the beginnings of a sensitivity analysis of barrier island breaching. The study area of Mantoloking, New Jersey, USA is used as the barrier island breached significantly during Hurricane Sandy in 2012. The numerical model XBeach is used to conduct this study. The study investigates the affects that back-bay currents, water-level timing, and barrier-island configuration have on barrier island breaching.

Disasters are becoming more frequent as the global climate changes, and recovery efforts require the cooperation and collaboration of experts and community members across disciplines. The DRRM program, funded through the National Science Foundation (NSF) Research Traineeship (NRT), is an interdisciplinary graduate program that brings together faculty and graduate students from across the university to develop new, transdisciplinary ways of solving disaster-related issues. The core team includes faculty from business, engineering, education, science, and urban planning fields. The overall objective of the program is to create a community of practice amongst the graduate students and faculty to improve understanding and support proactive decision-making related to disasters and disaster management. The specific educational objectives of the program are (1) context mastery and community building, (2) transdisciplinary integration and professional development, and (3) transdisciplinary research. The program’s educational research and assessment activities include program development, trainee learning and development, programmatic educational research, and institutional transformation. The program is now in its fourth year of student enrollment. Core courses on interdisciplinary research methods in disaster resilience are in place, engaging students in domain-specific research related to natural hazards, resilience, and recovery, and in methods of interdisciplinary and transdisciplinary collaboration. In addition to courses,more »the program offers a range of professional development opportunities through seminars and workshops. Since the program’s inception, the core team has expanded both the numbers of faculty and students and the range of academic disciplines involved in the program, including individuals from additional science and engineering fields as well as those from natural resources and the social sciences. At the same time, the breadth of disciplines and the constraints of individual academic programs have posed substantial structural challenges in engaging students in the process of building interdisciplinary research identities and in building the infrastructure needed to sustain the program past the end of the grant. Our poster and paper will identify major program accomplishments, but also draw on interviews with students to examine the structural challenges and potential solution paths associated with a program of this breadth. Critical opportunities for sustainability and engagement have emerged through integration with a larger university-level center as well as through increased flexibility in program requirements and additional mechanisms for student and faculty collaboration.« less