气候变化领域集成服务门户(CCPortal): Rainfall-Induced Landslides forecast using local precipitation and global climate indexes

CCPortal

DOI	10.1007/s11069-020-03913-0
	Rainfall-Induced Landslides forecast using local precipitation and global climate indexes
	Fustos I.; Abarca-del-Rio R.; Moreno-Yaeger P.; Somos-Valenzuela M.
发表日期	2020
ISSN	0921030X
起始页码	115
结束页码	131
卷号	102 期号:1
英文摘要	We analyse RIL events between 1950 and 2002 to investigate the role played by climate variability, using the “El Niño-Southern Oscillation” (ENSO), the Antarctic Oscillation (AAO) and local precipitation as predictors, through logistic and probabilistic (Logit and Probit) modelling. From the probabilistic regression analysis, it is clear that rain plays a major role, since its weight in the regression is almost 50%. However, we show that integrating South Pacific climate variability represented by ENSO/AAO significantly increases predictability, reaching over 87%. Moreover, sensitivity and specificity analyses confirm that although local rainfall is the main triggering factor, adding the two macroclimate variables increases the ability to predict true positive and negative occurrences by almost 80%. This confirms the need to integrate macroclimatic variables to make assertive local predictions. Surprisingly, and contrary to what might have been expected considering ENSO's recognized role in regional climate variability, the integration of AAO variability significantly improves RIL prediction capacity, while on average ENSO can be considered a second-order predictor. These results, obtained through a simple logistic regression methodology (Logit and/or Probit), can contribute to better risk management in the middle-latitude zones of Chile. The methodology can be extended to other areas of the world that do not have high-density hydrometeorological information to support preventive decision-making through logistic RIL forecasting. © 2020, Springer Nature B.V.
关键词	ENSO-AAO variability logistic regression Rainfall-Induced Landslides
英文关键词	air-sea interaction; climate effect; El Nino-Southern Oscillation; forecasting method; global climate; landslide; precipitation (climatology); rainfall; regional climate; regression analysis; Chile; Pacific Ocean; Pacific Ocean (South)
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/205698
作者单位	Departamento de Ingeniería en Obras Civiles, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Francisco Salazar 01145, Temuco, 4780000, Chile; Departamento de Geofísica, Facultad de Ciencias Físicas y Matemáticas, Universidad de Concepción, Concepción, Chile; Departamento de Ingeniería en Obras Civiles y Geología, Universidad Católica de Temuco, Temuco, Chile; Department of Geoscience, University of Wisconsin-Madison, 1215 West Dayton Street, Madison, WI 53706, United States; Department of Forest Sciences, Faculty of Agriculture and Forest Sciences, Universidad de La Frontera, Av. Francisco Salazar 01145, Temuco, 4780000, Chile; Butamallin Research Center for Global Change, Universidad de La Frontera, Av. Francisco Salazar 01145, Temuco, 4780000, Chile
推荐引用方式 GB/T 7714	Fustos I.,Abarca-del-Rio R.,Moreno-Yaeger P.,et al. Rainfall-Induced Landslides forecast using local precipitation and global climate indexes[J],2020,102(1).
APA	Fustos I.,Abarca-del-Rio R.,Moreno-Yaeger P.,&Somos-Valenzuela M..(2020).Rainfall-Induced Landslides forecast using local precipitation and global climate indexes.Natural Hazards,102(1).
MLA	Fustos I.,et al."Rainfall-Induced Landslides forecast using local precipitation and global climate indexes".Natural Hazards 102.1(2020).