气候变化领域集成服务门户(CCPortal): Post-fire debris flow modeling analyses: case study of the post-Thomas Fire event in California

CCPortal

DOI	10.1007/s11069-019-03814-x
	Post-fire debris flow modeling analyses: case study of the post-Thomas Fire event in California
	Addison P.; Oommen T.
发表日期	2020
ISSN	0921030X
起始页码	329
结束页码	343
卷号	100 期号:1
英文摘要	There is an increased risk in post-fire debris flow (DF) occurrences in the western USA with recent increase in wildfire frequencies. DFs are destructive, causing high loss to lives and infrastructure. A lot of effort is going into possible preventive and/or mitigation measures. Recent research efforts in this niche focus on developing statistical models that assist emergency responders in isolating high-hazard locations after fires. There are two general approaches to this statistical modeling: linear and nonlinear. This study has looked into applying a linear-based logistic regression model and a nonlinear-based C5.0 decision tree model to assess the strength of each in predicting the locations within the Thomas Fire boundary that produced DFs. To do this, DF scars were delineated by running a change detection protocol known as delta normalized difference vegetation index (dNDVI), using high spatial resolution data from Planet Labs. These scars were further validated with data gathered by Santa Barbara County officials on affected areas. Results from the two statistical models were then overlain on the delineated DF scars and compared against each other to determine predictive strengths. The results revealed both models to perform well in predicting high probabilities for locations that were shown to produce DFs. The logistic regression model predicted an overall ~ 44,800 ha (49%) more high-hazard coverage compared to the C5.0 tree and therefore showed greater urgency. However, a closer look at the basin predictions with the delineated DF scars showed that most of these high-hazard basins identified by the logistic regression did not to have any discernible scars. It was projected that most of these locations were likely false positives and further fine-tuning of the model was recommended. Further recommendation was made concerning the development of additional models to predict potential DF inundation paths. Combining origination and inundation models will be most beneficial since the greatest associated danger with DFs is not necessarily where they start, but rather further downstream where most communities and infrastructure are situated. © 2019, Springer Nature B.V.
关键词	Debris flow prediction Decision tree dNDVI Hazard assessment Logistic regression Probability modeling
英文关键词	debris flow; hydrological modeling; NDVI; prediction; probability; regression analysis; spatiotemporal analysis; wildfire; California; United States
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/205566
作者单位	Department of Geological and Mining Engineering and Sciences, Michigan Technological University, Houghton, MI 49931, United States
推荐引用方式 GB/T 7714	Addison P.,Oommen T.. Post-fire debris flow modeling analyses: case study of the post-Thomas Fire event in California[J],2020,100(1).
APA	Addison P.,&Oommen T..(2020).Post-fire debris flow modeling analyses: case study of the post-Thomas Fire event in California.Natural Hazards,100(1).
MLA	Addison P.,et al."Post-fire debris flow modeling analyses: case study of the post-Thomas Fire event in California".Natural Hazards 100.1(2020).