Cargando…
A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon
The intensity and scale of wildfires has increased throughout the Pacific Northwest in recent decades, especially within the last decade, destroying vast amounts of valuable resources and assets. This trend is predicted to remain or even magnify due climate change, growing population, increased hous...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8903305/ https://www.ncbi.nlm.nih.gov/pubmed/35259177 http://dx.doi.org/10.1371/journal.pone.0264826 |
_version_ | 1784664734496194560 |
---|---|
author | Schmidt, Andres Leavell, Daniel Punches, John Rocha Ibarra, Marco A. Kagan, James S. Creutzburg, Megan McCune, Myrica Salwasser, Janine Walter, Cara Berger, Carrie |
author_facet | Schmidt, Andres Leavell, Daniel Punches, John Rocha Ibarra, Marco A. Kagan, James S. Creutzburg, Megan McCune, Myrica Salwasser, Janine Walter, Cara Berger, Carrie |
author_sort | Schmidt, Andres |
collection | PubMed |
description | The intensity and scale of wildfires has increased throughout the Pacific Northwest in recent decades, especially within the last decade, destroying vast amounts of valuable resources and assets. This trend is predicted to remain or even magnify due climate change, growing population, increased housing density. Furthermore, the associated stress of prolonged droughts and change in land cover/land use puts more population at risk. We present results of a multi-phase Extension Fire Program Initiative combining fire model results based on worst-case meteorological conditions recorded at 50 weather stations across Oregon with spatially distinct valuations of resources and assets based on regional ecological and socio-economic conditions. Our study focuses on six different Fire Service Areas covering the state of Oregon. We used a geostatistical approach to find weather stations that provide worst-case meteorological input data on record for representative sub-domains. The results provide regionally distinct assessments of potential value loss by wildfire and show that, depending on the region, 12% to 52% of the highest relative risk areas are on private land. This underscores the need to unite strategies and efforts on the landscape scale by including different landowners, managers, and stakeholders of public land and private land efficiently address wildfire damage protection and mitigation. Our risk assessments closely agreed with risks identified during landscape-scale ground projects. |
format | Online Article Text |
id | pubmed-8903305 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-89033052022-03-09 A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon Schmidt, Andres Leavell, Daniel Punches, John Rocha Ibarra, Marco A. Kagan, James S. Creutzburg, Megan McCune, Myrica Salwasser, Janine Walter, Cara Berger, Carrie PLoS One Research Article The intensity and scale of wildfires has increased throughout the Pacific Northwest in recent decades, especially within the last decade, destroying vast amounts of valuable resources and assets. This trend is predicted to remain or even magnify due climate change, growing population, increased housing density. Furthermore, the associated stress of prolonged droughts and change in land cover/land use puts more population at risk. We present results of a multi-phase Extension Fire Program Initiative combining fire model results based on worst-case meteorological conditions recorded at 50 weather stations across Oregon with spatially distinct valuations of resources and assets based on regional ecological and socio-economic conditions. Our study focuses on six different Fire Service Areas covering the state of Oregon. We used a geostatistical approach to find weather stations that provide worst-case meteorological input data on record for representative sub-domains. The results provide regionally distinct assessments of potential value loss by wildfire and show that, depending on the region, 12% to 52% of the highest relative risk areas are on private land. This underscores the need to unite strategies and efforts on the landscape scale by including different landowners, managers, and stakeholders of public land and private land efficiently address wildfire damage protection and mitigation. Our risk assessments closely agreed with risks identified during landscape-scale ground projects. Public Library of Science 2022-03-08 /pmc/articles/PMC8903305/ /pubmed/35259177 http://dx.doi.org/10.1371/journal.pone.0264826 Text en © 2022 Schmidt et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Schmidt, Andres Leavell, Daniel Punches, John Rocha Ibarra, Marco A. Kagan, James S. Creutzburg, Megan McCune, Myrica Salwasser, Janine Walter, Cara Berger, Carrie A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon |
title | A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon |
title_full | A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon |
title_fullStr | A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon |
title_full_unstemmed | A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon |
title_short | A quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—A case study in Oregon |
title_sort | quantitative wildfire risk assessment using a modular approach of geostatistical clustering and regionally distinct valuations of assets—a case study in oregon |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8903305/ https://www.ncbi.nlm.nih.gov/pubmed/35259177 http://dx.doi.org/10.1371/journal.pone.0264826 |
work_keys_str_mv | AT schmidtandres aquantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT leavelldaniel aquantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT punchesjohn aquantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT rochaibarramarcoa aquantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT kaganjamess aquantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT creutzburgmegan aquantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT mccunemyrica aquantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT salwasserjanine aquantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT waltercara aquantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT bergercarrie aquantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT schmidtandres quantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT leavelldaniel quantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT punchesjohn quantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT rochaibarramarcoa quantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT kaganjamess quantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT creutzburgmegan quantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT mccunemyrica quantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT salwasserjanine quantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT waltercara quantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon AT bergercarrie quantitativewildfireriskassessmentusingamodularapproachofgeostatisticalclusteringandregionallydistinctvaluationsofassetsacasestudyinoregon |