Author
Listed:
- Weiting Yue
(Southwest Jiaotong University)
- Yunji Gao
(Southwest Jiaotong University)
- Yao Xiao
(Southwest Jiaotong University)
- Ziqun Ye
(Southwest Jiaotong University)
- Qian Zhao
(Southwest Jiaotong University)
- Yuchun Zhang
(Southwest Jiaotong University)
Abstract
Climate change and increased human activity have resulted in an increase in the frequency and intensity of wildfires. Effective wildfire risk assessment is essential for disaster prevention, resource protection, and regional stability. Existing studies often overlook spatial heterogeneity and temporal patterns of wildfires, with limited county-scale quantitative assessments. To address these gaps, multidimensional wildfire risk assessment framework for Sichuan Province was proposed, combining temporal characterization with county-scale spatial modeling. Temporal trends and mutation patterns of wildfires from 2001 to 2023 were analyzed using the Mann–Kendall test. Additionally, county-scale wildfire risk assessment model in Sichuan Province was constructed by combining hazard and vulnerability assessments. Specifically, wildfire hazard was assessed using Multiscale Geographically Weighted Regression (MGWR) model and capturing the spatial heterogeneity of driving factors. Vulnerability was assessed through Multi-Criteria Decision Analysis approach to identify areas of high vulnerability and their factor importance. The results indicated a significant rise in wildfires, particularly during winter and non-fire prevention periods. The MGWR model effectively captured spatial heterogeneity, identifying the highest hazard levels in southwestern Sichuan, particularly in Liangshan Prefecture and Panzhihua City. High vulnerability areas were scattered, mainly across southwestern, southern, and northern Sichuan. The integrated risk assessment revealed that Liangshan Prefecture and its surrounding counties exhibited significantly higher wildfire risk levels than other regions, while the eastern and northeastern regions demonstrated the lowest risk.
Suggested Citation
Weiting Yue & Yunji Gao & Yao Xiao & Ziqun Ye & Qian Zhao & Yuchun Zhang, 2025.
"Study on the temporal pattern and county-scale comprehensive risk assessment of wildfires in Sichuan Province,"
Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 121(13), pages 15201-15238, July.
Handle:
RePEc:spr:nathaz:v:121:y:2025:i:13:d:10.1007_s11069-025-07384-z
DOI: 10.1007/s11069-025-07384-z
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:121:y:2025:i:13:d:10.1007_s11069-025-07384-z. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.