Extreme precipitation induced concurrent events trigger prolonged disruptions in regional road networks

Dave, Raviraj; Subramanian, Srikrishnan Siva; Bhatia, Udit

doi:10.1088/1748-9326/ac2d67

Cited by 21 publications

(9 citation statements)

References 104 publications

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“…We also do not explicitly consider flood drivers or specific impacts of flooding (e.g., standing water, road damage, traffic flow, debris and sediment deposition), and instead focus on network disruption based purely on elevation. Future work can incorporate observations on how road networks are impacted by relative contributions of specific drivers from marine sources (Serafin et al., 2017) and others, such as pluvial (Dave et al., 2021; Evans et al., 2020; Kelleher & McPhillips, 2020; Neumann et al., 2021; Pregnolato et al., 2017) or groundwater flooding (Habel et al., 2020, 2017; Plane et al., 2019; Rotzoll & Fletcher, 2013), or the potential importance of variability in flood duration (Arrighi et al., 2021; Darestani et al., 2021; de Bruijn et al., 2019; Najibi & Devineni, 2018; Pezza & White, 2021; Sweet et al., 2014). Adding traffic dynamics either through graph‐based approaches (e.g., Dong et al., 2022), or agent‐based traffic simulations (e.g., Hummel et al., 2020; Papakonstantinou et al., 2019) would also enrich future work, as would further investigation of material and mechanical properties of roadways to understand the event conditions likely to cause permanent damage (e.g., Khan et al., 2014, 2017; Mallick et al., 2017).…”

Section: Discussionmentioning

confidence: 99%

“…In addition to graph‐based methods, recent work has focused on investigating disruption to road networks using techniques from agent‐based traffic simulation paired with hydrodynamic models of flooding, specifically to look at travel time delays (e.g., Hummel et al., 2020; Papakonstantinou et al., 2019). Studies consider road and other transportation networks in urban coastal settings (de Bruijn et al., 2019; Kasmalkar et al., 2020, 2021; Kermanshah & Derrible, 2017; Pezza & White, 2021; Plane et al., 2019; Rotzoll & Fletcher, 2013; Sadler et al., 2017; Suarez et al., 2005; Sweet et al., 2014) and in fluvial floodplains and upland catchments (Abdulla & Birgisson, 2021; Arrighi et al., 2021; Dave et al., 2021; Dong, Esmalian, et al., 2020; Dong et al., 2022; Evans et al., 2020; Hummel et al., 2020; Kelleher & McPhillips, 2020; Papakonstantinou et al., 2019; Pregnolato et al., 2017; Singh et al., 2018; Versini et al., 2010; Wang et al., 2019); others focus on water‐treatment systems in low‐lying coastal regions (Hummel et al., 2018) or multiple layers of infrastructure networks (Douglas et al., 2016; Habel et al., 2020, 2017; Koks et al., 2019; Neumann et al., 2021). To understand and forecast the future dynamics of developed barrier islands, more inquiry is needed to link thresholds in road network functioning to the physical forces that drive coastal change.…”

Section: Introductionmentioning

confidence: 99%

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Thresholds in Road Network Functioning on US Atlantic and Gulf Barrier Islands

2022

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Barrier islands predominate the Atlantic and Gulf coastlines of the USA, where population and infrastructure growth exceed national trends. Forward‐looking models of barrier island dynamics often include feedbacks with real estate markets and management practices aimed at mitigating damage to buildings from natural hazards. However, such models thus far do not account for networks of infrastructure, such as roads, and how the functioning of infrastructure networks might influence management strategies. Understanding infrastructure networks on barrier islands is an essential step toward improved insight into the future dynamics of human‐altered barriers. Here, we examine thresholds in the functioning of 72 US Atlantic and Gulf Coast barrier islands. We use digital elevation models to assign an elevation to each intersection in each road network. From each road network we sequentially remove intersections, starting from the lowest elevation. We use the maxima of the second giant connected component to identify a specific intersection—and corresponding elevation—at which functioning of the network fails, and we match the elevation of each critical intersection to local annual exceedance probabilities for extreme high‐water levels. We find a range of failure thresholds for barrier island road network functioning, and also find that no single metric—absolute elevation, annual exceedance probability, or a quantitative metric of robustness—sufficiently ranks the susceptibility of barrier road networks to failure. Future work can incorporate thresholds for road network into forward‐looking models of barrier island dynamics that include hazard‐mitigation practices for protecting infrastructure.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Thresholds in Road Network Functioning on US Atlantic and Gulf Barrier Islands

2022

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“…Each polygonal tessellation has a natural dual graph representation, which inherits the connectivity of the generating polygons. We note that also functional components such as transport infrastructure can, in most cases, be functionally represented by spatial graphs, i.e., a set of vertices connected by edges (Dave et al, 2021). Since such graph structures can be remarkably complex, they can therefore be conveniently simplified by projecting and aggregating them onto the dual graph of the tessellation.…”

Section: Methodsmentioning

confidence: 99%

“…The range of impacting mechanisms, especially for intense hydrometeorological events includes very often direct (physical) damages to assets, as well as indirect effects based on the functional impairment of the underlying systems. For instance, the interruption of a road caused by a landslide or a bridge collapse due to extreme river runoff can severely affect the emergency reaction capabilities and ultimately threaten the exposed communities (Dalziell and Nicholson, 2001;Dave et al, 2021). This is particularly evident in rural and mountainous areas where the road network has little redundance and is more exposed to natural hazards (Argyroudis et al, 2019;Dalziell and Nicholson, 2001).…”

Section: Introductionmentioning

confidence: 99%

Cross-border multi-functional, multi-hazard exposure modelling in Alpine regions

Pittore

Campalani

Renner

et al. 2022

Preprint

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Extreme hydrometeorological events such as the 2018 Vaia storm increasingly threaten alpine regions with multiple hazards often compounded and with cascading effects. Currently available risk assessment and prevention tools may therefore prove inadequate, particularly for transborder and vulnerable mountain areas, calling for comprehensive multi-hazard and transdisciplinary approaches. In particular, the exposed assets should not anymore be considered a sheer collection of static items, but the models should also reflect functional features. Extreme hydrometeorological events such as the 2018 Vaia storm increasingly threaten alpine regions with multiple hazards often compounded and with cascading effects. Currently available risk assessment and prevention tools may therefore prove inadequate, particularly for transborder and vulnerable mountain areas, calling for comprehensive multi-hazard and transdisciplinary approaches. In particular, the exposed assets should not anymore be considered a sheer collection of static items, but the models should also reflect functional features. In this paper we propose an integrated approach to multi-hazard exposure modelling including both static and functional components. The model is based on a homogeneous planar tessellation composed of hexagonal cells, and a graph-like structure which describes the functional connections among the cells. To exemplify the methodology a combination of static (buildings, protective forests), dynamic (population) and functional (road-based transport system) components have been considered together, targeting a ca. 10’000 km² region across Italy and Austria. A cell-based aggregation at 250m resolution and an innovative graph-based simplification allow for a good trade-off between the complexity of the model and its computational efficiency for risk-related applications. Furthermore, aggregation ensures protection of sensitive data at a scale still useful for civil protection. The resulting model can be used for different applications including scenario-based risk analysis and numeric simulation, probabilistic risk assessment, impact forecasting and early warning.

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“…As one of the most hazardous extreme phenomena, extreme rainfall events bring considerable manuscript submitted to replace this text with name of AGU journal damage, resulting in secondary disasters including landslides and flash floods (Dave et al, 2021;Meyer et al, 2021;Ning et al, 2021). Extreme rainfall has a severe impact on human life, ecosystems, and the social economy of agriculture, causing colossal socioeconomic losses.…”

Section: Introductionmentioning

confidence: 99%

Trends and Spatio-Temporal Variability of Summer Mean and Extreme Precipitation Events across South Korea for 1973-2022

Kim

Moon

Yun

et al. 2022

Preprint

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Climate change has altered the frequency, intensity, and timing of mean and extreme precipitation events. Extreme precipitation has caused tremendous socio-economic losses and displays strong regional variability. Although many previous studies have addressed daily extreme precipitation, hourly extreme rainfall still needs to be thoroughly investigated. In this study, we investigated the trends, spatio-temporal variability, and long-term variations in mean and extreme precipitation over South Korea using daily and hourly observational data. During the past 50 years (1973–2022), there has been a notable escalation in maximum hourly precipitation, although the boreal summer mean precipitation has increased only marginally. Regionally, an increase in mean and extreme rainfall occurred in the northern part of the central region. Moreover, increased intensity and frequency of extreme precipitation have contributed more to the total summer precipitation in recent years. Our findings provide scientific insights into the progression of extreme summer precipitation events in South Korea.

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Extreme precipitation induced concurrent events trigger prolonged disruptions in regional road networks

Cited by 21 publications

References 104 publications

Thresholds in Road Network Functioning on US Atlantic and Gulf Barrier Islands

Thresholds in Road Network Functioning on US Atlantic and Gulf Barrier Islands

Cross-border multi-functional, multi-hazard exposure modelling in Alpine regions

Trends and Spatio-Temporal Variability of Summer Mean and Extreme Precipitation Events across South Korea for 1973-2022

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