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

Gwynne, Steve M.V. LU ; Ronchi, Enrico LU orcid ; Wahlqvist, Jonathan LU ; Cuesta, Arturo ; Gonzalez Villa, Javier ; Kuligowski, Erica D. ; Kimball, Amanda ; Rein, Guillermo ; Kinateder, Max and Benichou, Noureddine , et al. (2023) In Fire Technology 59(2). p.879-901
Abstract

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... (More)

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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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Drill, Egress, Evacuation, Fire safety, Wildfire, WUI
in
Fire Technology
volume
59
issue
2
pages
879 - 901
publisher
Springer
external identifiers
  • pmid:36873577
  • scopus:85147666811
ISSN
0015-2684
DOI
10.1007/s10694-023-01371-1
language
English
LU publication?
yes
id
f4bea0a6-49b9-4c5b-8110-bdfeee0d6703
date added to LUP
2023-02-21 09:39:28
date last changed
2024-06-13 17:13:07
@article{f4bea0a6-49b9-4c5b-8110-bdfeee0d6703,
  abstract     = {{<p>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.</p>}},
  author       = {{Gwynne, Steve M.V. and Ronchi, Enrico and Wahlqvist, Jonathan and Cuesta, Arturo and Gonzalez Villa, Javier and Kuligowski, Erica D. and Kimball, Amanda and Rein, Guillermo and Kinateder, Max and Benichou, Noureddine and Xie, Hui}},
  issn         = {{0015-2684}},
  keywords     = {{Drill; Egress; Evacuation; Fire safety; Wildfire; WUI}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{879--901}},
  publisher    = {{Springer}},
  series       = {{Fire Technology}},
  title        = {{Roxborough Park Community Wildfire Evacuation Drill : Data Collection and Model Benchmarking}},
  url          = {{http://dx.doi.org/10.1007/s10694-023-01371-1}},
  doi          = {{10.1007/s10694-023-01371-1}},
  volume       = {{59}},
  year         = {{2023}},
}