A. James Clark School of Engineering
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The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
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Item NATURAL LANGUAGE PROCESSING, SOCIAL MEDIA, AND EPIDEMIC MODEL-ING FOR WILDFIRE RESPONSE AND RE-SILIENCE ENHANCEMENT(2024) Ma, Zihui; Baecher, Gregory B; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Effective disaster response is critical for communities to remain resilient and advance the development of smart cities. Responders and decision-makers benefit from reliable, timely measures of the issues impacting their communities during a disaster, and social media offers a potentially rich data source. Social media can reflect public concerns and behaviors during a disaster, offering valuable insights for decision-makers to understand evolving situations and optimize resource allocation. A comprehensive literature review of natural language processing (NLP) of social media data in disaster management, covering 324 articles published between 2011 and 2022, revealed a gap in applying NLP techniques to wildfire scenarios. Meanwhile, the increasing frequency of wildfires highlights the need for advanced management tools. To address this, we integrated the BERTopic and SIR models to capture public responses on Twitter during the 2020 western U.S. wildfire season, analyzing both the magnitude and velocity of topic diffusion. The results displayed a clear relationship between topic trends and wildfire propagation patterns. The parameters estimated from the SIR model for selected cities revealed that residents expressed various levels of concern or demand during wildfires. The study also demonstrated a practical framework for utilizing social media data to aid wildfire evacuations. Through social network analysis, we clarified the roles of key information disseminators and provided guidelines for extracting high-priority information. Although biases in social media and model limitations exist, the study offers qualitative and quantitative approaches to investigate wildfire response and sup-port community resilience enhancement.Item ANALYZING REDISTRIBUTION OF FEDERAL DISASTER AID THROUGH MACHINE LEARNING(2023) Bryant, Adriana Yanmei; Reilly, Allison; Niemeier, Deb; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Natural disasters are on the rise and will be costly for both the United States government and its citizens. The record-breaking year of 2020 left $1 billion worth of damages in the wake of twenty-two different events (FEMA, 2023). As costs due to disasters increase in the coming decades, the livelihoods of all citizens, especially those most vulnerable are at risk. It is known that natural disasters exacerbate current standing social vulnerabilities and inequities. Federal disaster aid programs in place are intended to assist those who cannot solely finance their own recovery efforts. This study looks to analyze FEMA’s Public Assistance (PA) program, Individual Assistance (IA) program, and Hazard Mitigation Assistance (HMA) program. It is important that these systems put in place are distributing federal resources as intended because they are funded via people’s taxpayer dollars. This study looks to explore the relationship between disaster aid that is awarded at the county level with respect to the federal income taxes residents of that county pay to the federal government. This is expressed through the creation of the donor-donee ratio. This study also contributes to the literature a new metric of burden, the ratio of expected annual disaster losses of a county and its gross domestic product, which can beutilized as a proxy for coping capacity. The burden metric provides additional useful insight as it is tabulated by FEMA directly and published in their National Risk Index (NRI) at the county level. Over the last decade, this research examines the donor-donee ratio and burden metric over the years 2010 to 2019. Results of mapping the donor-donee ratio and burden metric indicate there is spatial heterogeneity between counties in the United States. The redistribution of federal aid is not only heterogeneous but there are distinct regional patterns where further research could investigate their causality. To investigate the relationship between the redistribution of aid and coping capacity by proxy, this study utilized supervised machine learning to characterize counties. Significant outcomes of the machine learning indicate that most counties across the country received moderate funding and were evaluated as having a moderate burden as well. This does suggest that to some level the redistribution of aid is working as intended. Although upon further digging, it was found that counties that experience high-cost, less frequent events, contain over 50% of the country’s population and lie in metropolitan areas. Upon the application of a logistic regression model, it was found that these counties while associated with higher income, are also associated with higher mobile homes residence. As the risk of these higher costs events increases over the years, it is imperative that vulnerable communities are receiving adequate funding to increase their resilience to future hazards. This study highlights the flows of federal disaster dollars and where these programs allocate funding.Item ACCESSIBILITY BASED EVALUATION OF COASTAL RURAL COMMUNITIES’ VULNERABILITY TO COASTAL FLOODING AND THEIR ADAPTATION OPTIONS(2022) Yahyazadeh Jasour, Zeinab; Reilly, Allison C; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Global climate change and sea-level rise will cause significant risks to coastal communities. To make inclusive and cost-effective adaptation planning decisions, we need to understand who may be impacted and when. Currently, planning literature generally focuses on housing impacts; when will a house be inundated, and what adaptation strategies are useful to keep a house habitable? Housing, though, is only one of many types of infrastructures people need to reside in an area. Reliable roads are another. This dissertation conducts an analysis of parcel-level impacts of SLR on local residents’ ability to reach key amenities such as emergency services, grocery stores, and schools. Furthermore, it strategically evaluates where road protection should be implemented so that access is maintained in an equitable manner. Next, I use the accessibility analysis to identify the important roads for gathering high-resolution flood data to improve the accuracy of the analysis. I use Dorchester County, Maryland, U.S., as a case study. It is an extremely low-lying rural county and is expected to shrink in half by the end of the century due to SLR. The results from the case study indicate that some parcels are not expected to be inundated by SLR but are expected to experience accessibility impacts. Road protection appears to be a temporary strategy that can buy time for long-term adaptation strategies such as relocation. However, the protection strategies should be cautiously selected based on decision-makers priorities. The insight obtained by this dissertation highlights that when policy and decision-makers are deciding among adaptation strategies, they need to reach some level of consensus about assumptions for which a possible future is planned, and also the trade-off between increasing accessibility levels and balancing the distribution of accessibility among different demographic groups.Item Urban Heat Projections and Adaptations in a Changing Climate, Washington D.C. as a Case Study(2019) Zhang, Yating; Ayyub, Bilal M; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Carbon emission from human activities has changed the Earth’s overall climate and intensified extreme weather and climate events. Climate risks are regionally uneven due to different vulnerability levels of populations, infrastructures, and natural resources. Assessing local-scale risk is important in supporting climate preparation, adaptation planning, and policy development for cities to overcome climate change. This dissertation developed the Asynchronous Regional Regression Model (ARRM) that statistically downscales data of Coupled Model Intercomparison Project Phase Five (CIMP5) into locations of observing stations, employed the Weather Research and Forecasting (WRF) model that dynamically downscales data of Community Earth System Model version one (CESM1) into fine-grid results, and proposed a framework to assess adaptation strategies for vulnerable infrastructure systems incorporating the probabilistic risk approach. Based on those models and methods, this dissertation projected the trend and level of the urban heat island (UHI) effect and heat waves in the rest of the 21st century for Washington D.C. and its surrounding areas, evaluated mitigation options for heat waves, and assessed adaptation strategies for electrical power systems in such area. Projections based on the higher greenhouse gas (GHG) concentration scenario, Representative Concentration Pathway (RCP) 8.5, indicate a growing trend of heat waves at Washington D.C. in the rest of the century. The amplitude of heat waves may grow by 5.7°C, and frequency and duration may increase by more than twofold by the end of the century. The UHI effect may increase in summer and decrease in winter. The lower scenario, RCP 2.6, leads to slight decay of heat waves after a half-century of increase, and a minor change in the UHI effect. Five heat wave mitigation strategies based on cool roofs, green roofs, and reflective pavements were evaluated in three future time periods. Results indicated that applying cool roofs and green roofs in the city scale can effectively reduce heat wave amplitude and duration, whereas the effectiveness of reflective pavements is negligible. However, reflective pavements can be more cost-effective than green roofs because of their low initial and maintenance costs. Electrical power systems are particularly vulnerable to extreme heat. Results indicated that power outage risk caused by temperature rise may increase seventyfold in the Washington metro area by the end of the century. If summer peak load on the electrical grid is cut by three quarters, there would be a twentyfold increase instead. This reduction is achievable by installing solar panels on building roofs, which can add an average generation capacity of 13.02 GW to the existing power system. Increasing the use of rooftop photovoltaics (PV) can increase the level of benefits.Item WATER-ENERGY-CLIMATE NEXUS: INTERDEPENDANCIES AND TRADEOFFS, AND IMPLICATIONS FOR STRATEGIC RESOURCE PLANNING(2017) Liu, Lu; Forman, Barton; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The water-energy nexus has been an active area of research in recent decades and has been explored in many different directions pertaining to its core. It is imperative to manage water and energy in a holistic approach as there are critical interconnections between the two systems. Climate change is an intrinsic environmental variable that has vital implications for the study of water-energy nexus, and hence, the term water-energy-climate nexus is used throughout the dissertation in reference to the interdependencies and tradeoffs between these systems. This dissertation is composed of three research studies under the domain of the water-energy-climate nexus, and they are interconnected through the intrinsic linkages among the three systems. The first study deals with the vulnerability of U.S. thermoelectric power plants to climate change. Findings suggest that the impact of climate change is lower than in previous estimates due to the inclusion of a spatially-disaggregated representation of environmental regulations and provisional variances that temporarily relieve power plants from permit requirements. This study highlights the significance of accounting for legal constructs and underscores the effects of provisional variances along with environmental requirements. The second study demonstrates the adaptation measures taken by the U.S. energy system in the face of constraints on water availability. Results show that water availability constraints may cause substantial capital stock turnover and result in non-negligible economic costs for the western U.S. This work emphasizes the need to integrate water availability constraints into electricity capacity planning and highlights the state-level challenges to facilitate regional strategic resource planning. The last study assesses the potential of surface reservoir expansion for major river basins around the world as an adaption measure to secure a reliable water supply. Results suggest that conservation zones and future human migration will have a substantial, heterogeneous impact on the maximum amount of reservoir storage that can be expanded worldwide. Findings from this study highlight the importance of incorporating human development, land-use activities, and climate change drivers when quantifying available surface water yields and reservoir expansion potential. This dissertation takes an integrated holistic approach to examine water and energy system interrelationships, and assesses the role of climate change in reshaping the interconnectivity. The three studies are tied in to each other by identifying some of the challenges the society is facing in the water-energy-climate nexus (first study) and providing a few possible solutions in both energy supply (second study) and water supply (third study) sector. Novelty of this dissertation includes but not limited to 1) explicit representation of state-level environmental regulations pertaining to power plant operations in the U.S. 2) integrated approach that captures the interactions of energy system with other sectors of the economy; and 3) global assessment of reservoir capacity expansion potential with consideration of multiple constraints. General conclusions, along with further details, provide insights for sustainable resource planning and future research directions.Item THE TROUBLE WITH VOLUNTARY CARBON TRADING FOR BUILDINGS EXPOSED TO HURRICANE RISK(2017) Liu, Xiaoyu; Cui, Qingbin; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Increased climate risks pose challenges of combining climate mitigation and adaptation goals into building designs. These two goals are often misaligned, as adaptation measures use additional materials and equipment that are sources of carbon emissions. This phenomenon causes building design to involve tradeoffs between enhancing structural resilience and reducing emissions. This dissertation addresses the need to identify the optimal investment mechanisms for the design of buildings in hurricane-prone regions. Dynamic decision-making models are developed for individual investors to characterize emission trading and risk mitigation behaviors over a building’s lifecycle. The models enable the following outcomes: (i) evaluation and selection of baseline rules for sectoral emission trading, (ii) ability to reflect resilience goals in the building design, construction and maintenance, and to balance between climate mitigation and adaptation goals for a wide range of building examples, and (iii) policy implications for improving emission trading efficiencies and achieving environmental and economic sustainability at community level. Modeling results indicate that the trouble of voluntary emission trading is mainly attributed to imperfect market information and future climate risks. The uncertainty in predicting emissions and potential baseline manipulation leads to the production of non-additional carbon offsets and an extension of sectoral emission caps. This situation is even bleaker when emission trading are implemented in the areas that exposure to significant risks of catastrophic events such as hurricanes. The results reveal a trend of a transition from long-advocated low-carbon investment to a risk-oriented portfolio for building retrofits in hurricane-prone regions. The risk mitigation efforts should be pursued with discretion on the accuracy of insurance premium discounts. Meanwhile, subsidies for emission abatements are recommended to accommodate existing emission trading schemes and building property values.Item THE IMPACT OF CLIMATE CHANGE ON AGRICULTURAL CRITICAL SOURCE AREAS (CSAS) AND BEST MANAGEMENT PRACTICES (BMPS) IN EASTERN MARYLAND(2015) Renkenberger, Jaison; Brubaker, Kaye; Montas, Hubert; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Chesapeake Bay jurisdictions are required to develop Watershed Implementation Plans (WIPs) to reduce Non-Point Source (NPS) pollution by sediment, nitrogen, and phosphorus, and meet EPA Total Maximum Daily Loads (TMDLs) for water quality. This study quantifies the potential impacts of climate change on Critical Source Areas (CSAs) and Best Management Practice (BMP) efficiencies, two keys to WIP success, in an agricultural watershed in Maryland. The SWAT model was calibrated for the watershed and subjected to climate scenarios SRES B1, A1B and A2, over mid- and end-century time horizons. Simulation results predict that changed precipitation patterns will produce at least a doubling of CSA areas within the watershed and that, with BMPs designed for current climate, TMDLs will be exceeded by a factor of up to 2.4. For WIPs to be robust against climate change, BMPs must be designed for future climate and community-based, participatory implementation strategies are needed.