The presented methodology results in an optimal portfolio of resilience‐oriented resource allocation under weather‐related risks. The pre‐event mitigations improve the capacity of the transportation system to absorb shocks from future natural hazards, contributing to risk reduction. The post‐event recovery planning results in enhancing the system's ability to bounce back rapidly, promoting network resilience. Considering the complex nature of the problem due to uncertainty of hazards, and the impact of the pre‐event decisions on post‐event planning, this study formulates a nonlinear two‐stage stochastic programming (NTSSP) model, with the objective of minimizing the direct construction investment and indirect costs in both pre‐event mitigation and post‐event recovery stages. In the model, the first stage prioritizes a bridge group that will be retrofitted or repaired to improve the system's robustness and redundancy. The second stage elaborates the uncertain occurrence of a type of natural hazard with any potential intensity at any possible network location. The damaged state of the network is dependent on decisions made on first‐stage mitigation efforts. While there has been research addressing the optimization of pre‐event or post‐event efforts, the number of studies addressing two stages in the same framework is limited. Even such studies are limited in their application due to the consideration of small networks with a limited number of assets. The NTSSP model addresses this gap and builds a large‐scale data‐driven simulation environment. To effectively solve the NTSSP model, a hybrid heuristic method of evolution strategy with high‐performance parallel computing is applied, through which the evolutionary process is accelerated, and the computing time is reduced as a result. The NTSSP model is implemented in a test‐bed transportation network in Iowa under flood hazards. The results show that the NTSSP model balances the economy and efficiency on risk mitigation within the budgetary investment while constantly providing a resilient system during the full two‐stage course.
Towards an AI-driven framework for multi-scale urban flood resilience planning and design
Abstract Climate vulnerability is higher in coastal regions. Communities can largely reduce their hazard vulnerabilities and increase their social resilience through design and planning, which could put cities on a trajectory for long-term stability. However, the silos within the design and planning communities and the gap between research and practice have made it difficult to achieve the goal for a flood resilient environment. Therefore, this paper suggests an AI (Artificial Intelligence)-driven platform to facilitate the flood resilience design and planning. This platform, with the active engagement of local residents, experts, policy makers, and practitioners, will break the aforementioned silos and close the knowledge gaps, which ultimately increases public awareness, improves collaboration effectiveness, and achieves the best design and planning outcomes. We suggest a holistic and integrated approach, bringing multiple disciplines (architectural design, landscape architecture, urban planning, geography, and computer science), and examining the pressing resilient issues at the macro, meso, and micro scales.
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- NSF-PAR ID:
- 10295179
- Date Published:
- Journal Name:
- Computational Urban Science
- Volume:
- 1
- Issue:
- 1
- ISSN:
- 2730-6852
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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ABSTRACT -
Abstract The impact of climate extremes upon human settlements is expected to accelerate. There are distinct global trends for a continued rise in urban dwellers and associated infrastructure. This growth is occurring amidst the increasing risk of extreme heat, rainfall, and flooding. Therefore, it is critical that the urban development and architectural communities recognize climate impacts are expected to be experienced globally, but the cities and urban regions they help create are far more vulnerable to these extremes than nonurban regions. Designing resilient human settlements responding to climate change needs an integrated framework. The critical elements at play are climate extremes, economic growth, human mobility, and livability. Heightened public awareness of extreme weather crises and demands for a more moral climate landscape has promoted the discussion of urban climate change ethics. With the growing urgency for considering environmental justice, we need to consider a transparent, data-driven geospatial design approach that strives to balance environmental justice, climate, and economic development needs. Communities can greatly manage their vulnerabilities under climate extremes and enhance their resilience through appropriate design and planning towards long-term stability. A holistic picture of urban climate science is thus needed to be adopted by urban designers and planners as a principle to guide urban development strategy and environmental regulation in the context of a growingly interdependent world.more » « less
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Coastal Communities are exposed to multiple hazards including hurricanes, storm surges, waves, and riverine flash floods. This paper presents the outcome of a Basin-wide Flood Multi-hazard Risks module that was developed and offered as part of a collaboration between two research projects: the UPRM-DHS Coastal Resilience Center of Excellence (CRC) funded by the Department of Homeland Security and the Resilient Infrastructure and Sustainability Education Undergraduate Program (RISE-UP) funded by the National Science Foundation (NSF). The content was designed to give students an understanding of complex project management in coastal communities. The main learning objective was for students to be able to assess and recognize the actions that can be taken to improve resiliency in coastal communities. Students learned how to manage multi-hazard floods. Through knowledge gained by participating in lectures, discussions, and the development of case studies, students were able to assess flood risk and current mitigation strategies for coastal communities in Puerto Rico. The learning experience provided an overview of the history, needs, and challenges that coastal communities face regarding flood and coastal hazards. Through the case studies, students were able to appreciate and understand the risk exposure on the natural and built infrastructure, and the importance of always taking into consideration the social impact.more » « less
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Low-lying coastal cities across the world are vulnerable to the combined impact of rainfall and storm tide. However, existing approaches lack the ability to model the combined effect of these flood mechanisms, especially under climate change and sea level rise (SLR). Thus, to increase flood resilience of coastal cities, modeling techniques to improve the understanding and prediction of the combined effect of these flood hazards are critical. To address this need, this study presents a modeling system for assessing the combined flood impact on coastal cities under selected future climate scenarios that leverages ocean modeling with land surface modeling capable of resolving urban drainage infrastructure within the city. The modeling approach is demonstrated in quantifying the impact of possible future climate scenarios on transportation infrastructure within Norfolk, Virginia, USA. A series of combined storm events are modeled for current (2020) and projected future (2070) climate scenarios. The results show that pluvial flooding causes a larger interruption to the transportation network compared to tidal flooding under current climate conditions. By 2070, however, tidal flooding will be the dominant flooding mechanism with even nuisance flooding expected to happen daily due to SLR. In 2070, nuisance flooding is expected to cause a 4.6% total link close time (TLC), which is more than two times that of a 50-year storm surge (1.8% TLC) in 2020. The coupled flood model was compared with a widely used but physically simplistic bathtub method to assess the difference resulting from the more complex modeling presented in this study. The results show that the bathtub method overestimated the flooded area near the shoreline by 9.5% and 3.1% for a 10-year storm surge event in 2020 and 2070, respectively, but underestimated the flooded area in the inland region by 9.0% and 4.0% for the same events. The findings demonstrate the benefit of sophisticated modeling methods compared to more simplistic bathtub approaches, in climate adaptive planning and policy in coastal communities.more » « less
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We describe a framework for deploying agent-based models as a tool for decision-making during resilience planning, with an emphasis on flood mitigation. Prior work has demonstrated that agent-based models can be effective tools for modelling evolving community flood resilience and risk perception when they incorporate elements of individual decision-making. We argue for extending this methodology and incorporating it into regional infrastructure and resilience planning in order to 1) create more distributed and robust green infrastructure implementations and performance management systems; 2) provide a critique and alternatives to existing planning and delivery processes based on public sector jurisdictional boundaries; and, 3) validate and improve the modelling process by connecting it directly to stakeholder decision-making processes. This final point will effectively merge these systems-centric modelling approaches with human-centred community organising that employs various co-design methods. In regard to the ABMs, co-design methods can be a useful source of real-world data about individual decision-making that can inform and validate iterations of the models. For stakeholders, they can be a valuable source of information and education about flood risk and climate-related impacts that might not be available through other channels. And finally, hands-on workshops coupled with potential small implementation grants can be effective ways of providing skills and incentives to stakeholders who may wish to undertake projects on their own property, reshaping the way green infrastructure planning and implementation can be accomplished.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1007/s43762-021-00011-0
