Rainfall-induced rapid and long-runout catastrophic landslide on July 23, 2019 in Shuicheng, Guizhou, China

Fan, Xiang; Tang, Junjie; Tian, Shujun; Jiang, Yuanjun

doi:10.1007/s10346-020-01454-y

Cited by 42 publications

(23 citation statements)

References 22 publications

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“…Therefore, geological disasters such as landslides and debris flows during rainy seasons occur more frequently in SWC than most of other regions of China, resulting in huge losses in both human lives and economy in SWC (Y. Li, Qu et al., 2013; Tao et al., 2009). A recent example is that the continuous heavy precipitation during July 2019 over Shuicheng, Guizhou Province (in SWC), caused a catastrophic landslide, resulting in 42 fatalities, 9 missing people, and substantial economic costs (Fan et al., 2020). Most of the geo‐hazards are related to precipitation, especially extreme precipitation (C. Zhou & Li, 2009).…”

Section: Introductionmentioning

confidence: 99%

Synoptic‐Scale Circulation Precursors of Extreme Precipitation Events Over Southwest China During the Rainy Season

Nie

Sun

2021

JGR Atmospheres

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This study analyzes the synoptic‐scale circulation patterns favorable for regional extreme precipitation events over southwest China (SWC) from 1979 to 2018 occurring during the rainy seasons. The whole SWC is regionalized into two subregions, western SWC and eastern SWC, according to the spatial distribution of two extreme precipitation indices. Furthermore, the atmospheric patterns associated with the independent regional extreme precipitation events (REPEs) that occurred over the two subregions are categorized into two types using k‐means clustering. For type 1, a Rossby wave train originating from the Northeast Atlantic almost a week before REPEs leads to an anomalous low over the eastern Tibetan Plateau (TP), inducing upper‐troposphere divergence and ascending motion over SWC. Moreover, anomalous convective activities over India and the Bay of Bengal (the enhanced and westward‐extended western Pacific subtropical high) are critical precursors of REPEs over western (eastern) SWC. For type 2, an anomalous high is developed over the Ural Mountains at least a week prior to REPEs. The subsequent anomalous low over Lake Baikal and eastward‐shifted South Asian high are conducive to forming updrafts over SWC. An anomalous anticyclone at the middle‐to‐lower troposphere south of the TP is the main moisture contributor. Discrepancies in the zonal location of the Lake Baikal low and the strength of the Ural Mountain high, as well as the intensity of atmospheric circulation anomalies at low latitudes, are the major differences between the type 2 events occurring in western and eastern SWC.

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Section: Introductionmentioning

confidence: 99%

Synoptic‐Scale Circulation Precursors of Extreme Precipitation Events Over Southwest China During the Rainy Season

Nie

Sun

2021

JGR Atmospheres

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“…e Shuicheng landslide occurred in the Emeishan basalt in the Middle Permian. Due to the columnar joints in the basalt of the Shuicheng landslide and the influence of weathering and tectonic effects, the basalt is relatively broken, and unstable structural surfaces develop inside it, which is easy to cause geological disasters [39]. e joints and fractures in basalt are also natural seepage channels [40].…”

Section: Geological Conditionsmentioning

confidence: 99%

“…Rainstorms often cause the phreatic line to rise which in turn induces seepage damage [43], and the concentrated mountains and rainfall are the causes of landslides [44]. e accumulated rainfall from July 18 to July 22 was 189 mm (Figure 4) [39]. Continuous rainfall will increase the pore water pressure inside the rock and soil of the slope, reducing the effective stress.…”

Section: Climate and Rainfallmentioning

confidence: 99%

Dynamic Analysis of the High‐Speed and Long‐Runout Landslide Movement Process Based on the Discrete Element Method: A Case Study of the Shuicheng Landslide in Guizhou, China

Xia

Liu

et al. 2021

Advances in Civil Engineering

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On July 23, 2019, a high-speed and long-runout landslide occurred in Jichang Town, Shuicheng County, Guizhou Province, China, causing 42 deaths and 9 missing. This paper used the discrete element software MatDEM to construct a three-dimensional discrete element model based on digital elevation data and then simulated and analyzed the movement and accumulation process of the landslide. The maximum average velocity of the source area elements reached 14 m/s when passed through the scraping area; meanwhile, the velocity of the scraping area elements increased rapidly. At 90 s, the maximum displacement of the source area elements reached 1358.5 m. The heat generated during the movement of the landslide was mainly the frictional heat, and the frictional heat increased sharply when the source area elements passed through the scraping area. The change of frictional heat has a certain positive correlation with the velocity of the scraping area elements. Finally, the volume of the scraping area elements was 2.4 times greater than the source area elements in the deposits. The scraping effect increases the volume of the sliding body and expands the impact area of the landslide disaster. Additionally, by setting different compressive and tensile strengths as well as internal friction coefficients to analyze the influences of their value changes on the landslide movement process, the results show that the smaller the strengths and internal friction coefficient of the model, the greater the depth and area of the scraping area, which will result in a thicker accumulation; meanwhile, the average displacement, average velocity, and heat will also increase.

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“…Therefore, the preparation of accurate and up-to-date landslide susceptibility and hazard maps is of great importance for landslide hazard mitigation efforts. Among commonly observed triggering factors for landslides, extreme precipitation and earthquakes can be listed (see, e.g., [18][19][20][21]), which also cause debris slides and flows (e.g., [22]).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Floods and Landslides Triggered by a Meteorological Catastrophe (Ordu, Turkey, August 2018) Using Optical and Radar Data

et al. 2020

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This study explores the potential of photogrammetric datasets and remote sensing methods for the assessment of a meteorological catastrophe that occurred in Ordu, Turkey in August 2018. During the event, flash floods and several landslides caused losses of lives, evacuation of people from their homes, collapses of infrastructure and large constructions, destruction of agricultural fields, and many other economic losses. The meteorological conditions before and during the flood were analyzed here and compared with long-term records. The flood extent and the landslide susceptibility were investigated by using multisensor and multitemporal data. Sentinel-1 SAR (Synthetic Aperture Radar), Sentinel-2 optical data, and aerial photogrammetric datasets were employed for the investigations using machine learning techniques. The changes were assessed both at a local and regional level and evaluated together with available damage reports. The analysis of the rainfall data recorded during the two weeks before the floods and landslides in heavily affected regions shows that the rainfall continued for consecutive hours with an amount of up to 68 mm/hour. The regional level classification results obtained from Sentinel-1 and Sentinel-2 data by using the random forest (RF) method exhibit 97% accuracy for the flood class. The landslide susceptibility prediction performance from aerial photogrammetric datasets was 92% represented by the Area Under Curve (AUC) value provided by the RF method. The results presented here show that considering the occurrence frequency and immense damages after such events, the use of novel remote sensing technologies and spatial analysis methods is unavoidable for disaster mitigation efforts and for the monitoring of environmental effects. Although the increasing number of earth observation satellites complemented with airborne imaging sensors is capable of ensuring data collection requirement with diverse spectral, spatial, and temporal resolutions, further studies are required to automate the data processing, efficient information extraction, and data fusion and also to increase the accuracy of the results.

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Rainfall-induced rapid and long-runout catastrophic landslide on July 23, 2019 in Shuicheng, Guizhou, China

Cited by 42 publications

References 22 publications

Synoptic‐Scale Circulation Precursors of Extreme Precipitation Events Over Southwest China During the Rainy Season

Synoptic‐Scale Circulation Precursors of Extreme Precipitation Events Over Southwest China During the Rainy Season

Dynamic Analysis of the High‐Speed and Long‐Runout Landslide Movement Process Based on the Discrete Element Method: A Case Study of the Shuicheng Landslide in Guizhou, China

Evaluation of Floods and Landslides Triggered by a Meteorological Catastrophe (Ordu, Turkey, August 2018) Using Optical and Radar Data

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