Modelling the impact of wildfire smoke on driving speed

Intini, Paolo; Wahlqvist, Jonathan; Wetterberg, Niklas; Ronchi, Enrico

doi:10.1016/j.ijdrr.2022.103211

Cited by 9 publications

(3 citation statements)

References 35 publications

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“…Any sort of physical asset damage previously described can lead to the cutoff of critical transportation pathways and can strain alternative routes or modes (Mo et al 2023). Similar strains and disruptions can be triggered by smoke or precipitation, both of which can reduce visibility on roadways, contributing to slower travel speeds and increased congestion during fire evacuation, even limiting road use in some cases (Cova and Conger 2004, Biging et al 2012, Cahoon et al 2015, Goldbeck et al 2020, Wetterberg et al 2021, Intini et al 2022. Evacuees displaced to neighboring communities can also increase traffic (Spearing and Faust 2020).…”

Section: Transportationmentioning

confidence: 99%

Cross-boundary risks of hinterland hazards to city infrastructure

Joines,

Horgan,

et al. 2024

Environ. Res.: Infrastruct. Sustain.

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Extreme weather-related events are showing how infrastructure disruptions in hinterlands can affect cities. This paper explores the risks to city infrastructure services including transportation, electricity, communication, fuel supply, water distribution, stormwater drainage, and food supply from hinterland hazards of fire, precipitation, post-fire debris flow (PFDF), smoke, and flooding. There is a large and growing body of research that describes the vulnerabilities of infrastructures to climate hazards, yet this work has not systematically acknowledged the relationships and cross-governance challenges of protecting cities from remote disruptions. An evidence base is developed through a structured literature review that identifies city infrastructure vulnerabilities to hinterland hazards. Findings highlight diverse pathways from the initial hazard to the final impact on an infrastructure, demonstrating that impacts to hinterland infrastructure assets from hazards can cascade to city infrastructure. Beyond the value of describing the impact of hinterland hazards on urban infrastructure, the identified pathways can assist in informing cross-governance mitigation strategies. It may be the case that to protect cities, local governments invest in mitigating hazards in their hinterlands and supply chains.

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Section: Transportationmentioning

confidence: 99%

Cross-boundary risks of hinterland hazards to city infrastructure

Joines,

Horgan,

et al. 2024

Environ. Res.: Infrastruct. Sustain.

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“…Traffic during wildfire evacuation can encounter smoke which can obscure the drivers' views and make it unsafe to drive at the usual speeds for that specific road type. This causes the adopted speeds to decrease with decreasing visibility conditions, in addition to the potential speed reduction already adopted for increasing traffic densities (Wetterberg et al 2021;Intini et al 2022).…”

Section: Test T5: Vehicle Speed Reduction In Reduced Visibility Condi...mentioning

confidence: 99%

The verification of wildland–urban interface fire evacuation models

et al. 2023

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This paper introduces a protocol for the verification of multi-physics wildfire evacuation models, including a set of tests used to ensure that the conceptual modelling representation of each modelling layer is accurately implemented, as well as the interactions between different modelling layers and sub-models (wildfire spread, pedestrian movement, traffic evacuation, and trigger buffers). This work presents a total of 24 verification tests, including (1) 4 tests related to pedestrians, (2) 15 tests for traffic evacuation, (3) 5 tests concerning the interaction between different modelling layers, along with 5 tests for wildfire spread and trigger buffers. The evacuation tests are organized in accordance with different core components related to evacuation modelling, namely Population, Pre-evacuation, Movement, Route/destination selection, Flow constraints, Events, Wildfire spread and Trigger buffers. A reporting template has also been developed to facilitate the application of the verification testing protocol. An example application of the testing protocol has been performed using an open wildfire evacuation modelling platform called WUI-NITY and its associated trigger buffer model k-PERIL. The verification testing protocol is deemed to improve the credibility of wildfire evacuation model results and stimulate future modelling efforts in this domain.

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“…Such a community might be required to evacuate to a place of relative safety in response to the conditions faced. The time for the community to reach safety is crucial as it determines whether residents avoid worsening (and possibly untenable) conditions [ 11 , 32 ]. The time for a community to reach a place of safety is an emergent property of its response, the infrastructure available, the information available, and the fire conditions experienced.…”

Section: Introductionmentioning

confidence: 99%

Roxborough Park Community Wildfire Evacuation Drill: Data Collection and Model Benchmarking

et al. 2023

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Wildfires are increasing in scale, frequency and longevity, and are affecting new locations as environmental conditions change. This paper presents a dataset collected during a community evacuation drill performed in Roxborough Park, Colorado (USA) in 2019. This is a wildland–urban interface community including approximately 900 homes. Data concerning several aspects of community response were collected through observations and surveys: initial population location, pre-evacuation times, route use, and arrival times at the evacuation assembly point. Data were used as inputs to benchmark two evacuation models that adopt different modelling approaches. The WUI-NITY platform and the Evacuation Management System model were applied across a range of scenarios where assumptions regarding pre-evacuation delays and the routes used were varied according to original data collection methods (and interpretation of the data generated). Results are mostly driven by the assumptions adopted for pre-evacuation time inputs. This is expected in communities with a low number of vehicles present on the road and relatively limited traffic congestion. The analysis enabled the sensitivity of the modelling approaches to different datasets to be explored, given the different modelling approaches adopted. The performance of the models were sensitive to the data employed (derived from either observations or self-reporting) and the evacuation phases addressed in them. This indicates the importance of monitoring the impact of including data in a model rather than simply on the data itself, as data affects models in different ways given the modelling methods employed. The dataset is released in open access and is deemed to be useful for future wildfire evacuation modelling calibration and validation efforts.

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Modelling the impact of wildfire smoke on driving speed

Cited by 9 publications

References 35 publications

Cross-boundary risks of hinterland hazards to city infrastructure

Cross-boundary risks of hinterland hazards to city infrastructure

The verification of wildland–urban interface fire evacuation models

Roxborough Park Community Wildfire Evacuation Drill: Data Collection and Model Benchmarking

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