Analysis of the relationship of landslide occurrence with rainfall: a case study of Wudu County, China

Bai, Shibiao; Wang, Jian; Thiebes, Benni; Chen, Cheng; Yang, Yongbo

doi:10.1007/s12517-013-0939-9

Cited by 70 publications

(34 citation statements)

References 13 publications

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“…The role of rainfall as one of the main triggers of landslides has been widely demonstrated (e.g., Bai et al, 2014;Giannecchini et al, 2012;Dahal and Hasegawa, 2008). Rainfall is also known to be the most common cause of flash floods (Modricka and Georgakakos, 2015;Archer and Fowler, 2015).…”

Section: Modelling Extreme Rainfall Amountmentioning

confidence: 99%

Statistical modelling of extreme rainfall, return periods and associated hazards in the Bamenda Mountain, NW Cameroon

Afungang

Bateira²

2016

GOT

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Section: Modelling Extreme Rainfall Amountmentioning

confidence: 99%

Statistical modelling of extreme rainfall, return periods and associated hazards in the Bamenda Mountain, NW Cameroon

Afungang

Bateira²

2016

GOT

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“…In the last decade, various researchers have constructed daily versus antecedent rainfall plots to assess the temporal aspect of landslide occurrence (Bai et al 2014;Jaiswal and van Westen 2009) and the coupling with the spatial aspect for the elaboration of hazard maps Nat Hazards (Bui et al 2013;Althuwaynee et al 2014) and risk maps (Erener and Duzgun 2013). As given in Table 1, a common practice is to evaluate several techniques for the same study area in order to determine which one yields the best predictive performance (Chleborad et al 2006;Dahal and Hasegawa 2008;Kanungo and Sharma 2014;Zezêre et al 2015).…”

Section: Considerations For the Construction Of Daily Versus Antecedementioning

confidence: 99%

Establishing rainfall frequency contour lines as thresholds for rainfall-induced landslides in Tegucigalpa, Honduras, 1980–2005

Garcia-Urquia

2016

Nat Hazards

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In this paper, a method to derive rainfall thresholds based on the relationship between daily and the antecedent rainfall up to 6 days prior to landslide occurrence is proposed for the analysis of 134 landslide days in Tegucigalpa, Honduras, during the years 1980-2005. Based on a simple graphical procedure, rainfall frequency contour lines have been drawn in the daily versus antecedent rainfall plots to connect rainfall combinations relatively having the same frequency of occurrence. A two-bound threshold has been established: Below the lower bound, rainfall events are so frequent that any landslide day may only occur due to a significant anthropogenic disturbance, while, above the upper bound, rainfall alone is capable of inducing landslide days. Contour lines originating at the same daily rainfall value in all plots were then grouped together to form a threshold set, for which the number of well-predicted landslide days and false alarms was determined. It has been determined that 16 and 84 landslide days have fallen below the lower bound and above the upper bound, respectively. In addition, this method has been proven effective in the distinction between days with and without landslides, since it has led to a 23 % reduction in the number of false alarms per well-predicted landslide day when compared to a previously established threshold line for Tegucigalpa.

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“…In addition, the ecological environment of Zhouqu is deteriorated by anthropogenic activities such as highway engineering construction. Accordingly, Zhouqu has been suffering from landslide-related geo-hazards for several decades, including the giant debris flow that occurred on 7 August 2010 that caused nearly 1800 deaths [21,22]. Several large landslides such as Suoertou, Nanshanqiaotou and Xieliupo have been found at the both banks of the Pai-lung River, which is the main water source of Zhouqu [23,24].…”

Section: Introductionmentioning

confidence: 99%

Towards Slow-Moving Landslide Monitoring by Integrating Multi-Sensor InSAR Time Series Datasets: The Zhouqu Case Study, China

Sun

Zhang

et al. 2016

Remote Sensing

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Abstract:Although the past few decades have witnessed the great development of Synthetic Aperture Radar Interferometry (InSAR) technology in the monitoring of landslides, such applications are limited by geometric distortions and ambiguity of 1D Line-Of-Sight (LOS) measurements, both of which are the fundamental weakness of InSAR. Integration of multi-sensor InSAR datasets has recently shown its great potential in breaking through the two limits. In this study, 16 ascending images from the Advanced Land Observing Satellite (ALOS) and 18 descending images from the Environmental Satellite (ENVISAT) have been integrated to characterize and to detect the slow-moving landslides in Zhouqu, China between 2008 and 2010. Geometric distortions are first mapped by using the imaging geometric parameters of the used SAR data and public Digital Elevation Model (DEM) data of Zhouqu, which allow the determination of the most appropriate data assembly for a particular slope. Subsequently, deformation rates along respective LOS directions of ALOS ascending and ENVISAT descending tracks are estimated by conducting InSAR time series analysis with a Temporarily Coherent Point (TCP)-InSAR algorithm. As indicated by the geometric distortion results, 3D deformation rates of the Xieliupo slope at the east bank of the Pai-lung River are finally reconstructed by joint exploiting of the LOS deformation rates from cross-heading datasets based on the surface-parallel flow assumption. It is revealed that the synergistic results of ALOS and ENVISAT datasets provide a more comprehensive understanding and monitoring of the slow-moving landslides in Zhouqu.

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Analysis of the relationship of landslide occurrence with rainfall: a case study of Wudu County, China

Cited by 70 publications

References 13 publications

Statistical modelling of extreme rainfall, return periods and associated hazards in the Bamenda Mountain, NW Cameroon

Statistical modelling of extreme rainfall, return periods and associated hazards in the Bamenda Mountain, NW Cameroon

Establishing rainfall frequency contour lines as thresholds for rainfall-induced landslides in Tegucigalpa, Honduras, 1980–2005

Towards Slow-Moving Landslide Monitoring by Integrating Multi-Sensor InSAR Time Series Datasets: The Zhouqu Case Study, China

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