Human-centered flood mapping and intelligent routing through augmenting flood gauge data with crowdsourced street photos

Alizadeh, Bahareh; Li, Diya; Hillin, Julia; Meyer, Michelle A.; Thompson, Courtney M.; Zhang, Zhe; Behzadan, Amir H.

doi:10.1016/j.aei.2022.101730

Cited by 20 publications

(4 citation statements)

References 80 publications

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“…Assessing the impacts of flooding on power system operations requires having high-resolution space-time estimates of flooding depth. In this study, we use a purely data-driven approach [44], following a similar assimilative approach to [45,46], integrating different types of data to achieve flooding estimates (as opposed to physical hydrologic models). We start with records of 'high water marks' (maximum flooding depth) that were collected during Hurricane Florence from [47] (see blue dots in figure 3(b)).…”

Section: Flooding Analysismentioning

confidence: 99%

High-resolution, open-source modeling of inland flooding impacts on the North Carolina bulk electric power grid

Prieto-Miranda,

Kern

2024

Environ. Res.: Energy

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Although damages to local distribution systems from wind and fallen trees are typically responsible for the largest fraction of electricity outages during hurricanes, outages caused by flooding of electrical substations pose a unique risk. Electrical substations are a key component of electric power systems, and in some areas, the loss of a single substation can cause widespread power outages. Before repairing damaged substations, utilities must first allow floodwaters to recede, potentially leaving some customers without power for weeks following storms. As economic losses from flooding continue to increase in the U.S., there has been increasing attention paid to the potential impacts of flooding on power systems. Yet, this attention has mostly been limited to geospatial risk assessments that identify what assets are in the path of flooding. Here, we present the first major attempt to understand how flooding from hurricanes and other extreme precipitation events affects the dynamic behavior of power networks, including losses of demand and generation, and altered power flows through transmission lines. We use North Carolina, hit by major hurricanes in three of the past seven years, as a test case. Using open-source data of grid infrastructure, we develop a high-resolution direct current optimal power flow model that simulates electricity production and generators and power flows through a network consisting of 662 nodes and 790 lines. We then simulate grid operations during the historical (2018) storm Hurricane Florence. Time series of flooding depth at a discrete set of “high water” mark points from the storm are used to spatially interpolate flooding depth across the footprint area of the storms on an hourly basis. Outages of substations and solar farms due to flooding are translated to location-specific losses of demand and solar power production throughout the network. We perform sensitivity analysis to explore grid impacts as a function of the height of sensitive equipment at substations. Results shed light on the potential for localized impacts from flooding to have wider impacts throughout the grid (including in areas not affected by flooding), with performance tracked in terms of transmission line flows/congestion, generation outputs, and customer outages.

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Section: Flooding Analysismentioning

confidence: 99%

High-resolution, open-source modeling of inland flooding impacts on the North Carolina bulk electric power grid

Prieto-Miranda,

Kern

2024

Environ. Res.: Energy

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“…These digital exchanges provide an uncensored window into metropolitan populations' collective consciousness, making it possible to assess public opinion, spot new trends, and find unfulfilled requirements. Urban planners and legislators may better understand urban dynamics and design development policies that reflect the goals and values of the communities they serve by using the power of crowdsourced data [21]- [25].…”

Section: The Influence Of User-submitted Datamentioning

confidence: 99%

Crowdsourced Data for Informed Urban Development: A Social Media Crowdsourcing Test

Epifantsev,

Bisht,

Vanam

et al. 2024

BIO Web Conf.

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This data-intensive study examined civic engagement in urban environments, and we found a varied participant sample with ages ranging from 22 to 40 (mean age 31.4), nearly equal gender distribution (52% female, 48% male), and a range of educational backgrounds, including postgraduates (35%), high school graduates (25%), and bachelor's degree holders (40%). A rich tapestry of civic activities was found throughout our inquiry, with 15% making financial contributions, 35% attending, and 45% actively volunteering. Social network research revealed that participants with a wider range of social connections had higher levels of engagement, underscoring the critical function that social networks play in promoting civic participation. Informed urban development and community cohesiveness depend on understanding the complex interactions between demographics, participation roles, and social networks, all of which are shaped by this research.

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“…The economic losses are $35 billion in total in Pakistan, Australia, China, Nigeria, and India. For example, global climate and hydrological forecasts indicate an increase in the area that will be affected by floods in the future [5]. Thus, urbanized regions, transport networks, and basic infrastructure are under increasing threat of destruction due to floods.…”

Section: Introductionmentioning

confidence: 99%

The Problem of Effective Evacuation of the Population from Floodplains under Threat of Flooding: Algorithmic and Software Support with Shortage of Resources

et al. 2023

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Extreme flooding of the floodplains of large lowland rivers poses a danger to the population due to the vastness of the flooded areas. This requires the organization of safe evacuation in conditions of a shortage of temporary and transport resources due to significant differences in the moments of flooding of different spatial parts. We consider the case of a shortage of evacuation vehicles, in which the safe evacuation of the entire population to permanent evacuation points is impossible. Therefore, the evacuation is divided into two stages with the organization of temporary evacuation points on evacuation routes. Our goal is to develop a method for analyzing the minimum resource requirement for the safe evacuation of the population of floodplain territories based on a mathematical model of flood dynamics and minimizing the number of vehicles on a set of safe evacuation schedules. The core of the approach is a numerical hydrodynamic model in shallow water approximation. Modeling the hydrological regime of a real water body requires a multi-layer geoinformation model of the territory with layers of relief, channel structure, and social infrastructure. High-performance computing is performed on GPUs using CUDA. The optimization problem is a variant of the resource investment problem of scheduling theory with deadlines for completing work and is solved on the basis of a heuristic algorithm. We use the results of numerical simulation of floods for the Northern part of the Volga-Akhtuba floodplain to plot the dependence of the minimum number of vehicles that ensure the safe evacuation of the population. The minimum transport resources depend on the water discharge in the Volga river, the start of the evacuation, and the localization of temporary evacuation points. The developed algorithm constructs a set of safe evacuation schedules for the minimum allowable number of vehicles in various flood scenarios. The population evacuation schedules constructed for the Volga-Akhtuba floodplain can be used in practice for various vast river valleys.

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Human-centered flood mapping and intelligent routing through augmenting flood gauge data with crowdsourced street photos

Cited by 20 publications

References 80 publications

High-resolution, open-source modeling of inland flooding impacts on the North Carolina bulk electric power grid

High-resolution, open-source modeling of inland flooding impacts on the North Carolina bulk electric power grid

Crowdsourced Data for Informed Urban Development: A Social Media Crowdsourcing Test

The Problem of Effective Evacuation of the Population from Floodplains under Threat of Flooding: Algorithmic and Software Support with Shortage of Resources

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