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Article

Extreme Rainfall Events Triggered Loess Collapses and Landslides in Chencang District, Shanxi, China, during June–October 2021

1
School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China
2
Badong National Observation and Research Station of Geohazards, China University of Geosciences, Wuhan 430074, China
3
Hunan Water Planning and Design Institute Co., Ltd., Changsha 410008, China
4
Xinjiang Bureau of Geology and Mineral Resources Exploration and Development, The Second Hydrological Engineering Geological Brigade, Changji 831100, China
5
Shaanxi Geological and Mineral Third Team, Baoji 721300, China
6
The Seventh Geological Brigade of Hubei Geological Bureau, Yichang 443000, China
*
Authors to whom correspondence should be addressed.
Water 2024, 16(16), 2279; https://doi.org/10.3390/w16162279
Submission received: 9 July 2024 / Revised: 1 August 2024 / Accepted: 8 August 2024 / Published: 13 August 2024

Abstract

:
In recent years, the increasing frequency of extreme weather events has exacerbated the severity of geological disasters. Therefore, it is important to understand the mechanisms of geological disasters under extreme rainfall conditions. From June to October 2021, Baoji City, Shanxi Province, China, experienced some extreme and continuous heavy rainfalls, which triggered more than 30 geological disasters. Those geo-disasters threatened the lives of 831 people and the safety of 195 houses. The field investigations found that most of these geological disasters were devastating collapses that occurred in the loess layer, primarily due to the cave dwelling construction. The shear strength, montmorillonite content, disintegration degree, and plasticity index of two typical loesses, namely the Sanmen Formation stiff clay and the Hipparion red clay, were analyzed, and their water sensitivities were evaluated. The failure mechanisms of the landslides, ground fissures, and collapses were analyzed and most of them were controlled by the cave dwelling construction and the strong water sensitivity of the loess. This study provides data for understanding shallow geological disasters induced by extreme rainfall in the loess area, which are more threatening than large geological disasters. We proposed an intensity–duration (I–D) rainfall threshold as I = 90 D−0.92, which relates the rainfall intensity (I) to the rainfall event duration (D). The empirical threshold provides some useful information for the early warning of collapses or landslides in similar geological settings in the loess area.

1. Introduction

Extreme rainfall events have significantly increased the annual precipitation in China [1]. According to the China Meteorological Administration reports, the annual precipitation from 1951 to 2020 increased rapidly by 5.1 mm/10 years, especially in the Qinghai-Tibet Plateau, Xinjiang Province, and the West of China. Rainfall-induced geological disasters are generally the most frequent and widespread [2,3]. For example, in Shanxi Province, more than 3255 geological disasters occurred and killed 560 people from 2010 to 2018 [4], especially under extreme rainfall conditions. In 2021, there were 42 extreme rainfall occurrences in China, causing serious disasters in Henan, Shanxi, Shaanxi, Hubei, and other places. As a result, the economic losses amounted to CNY 3.2 billion, and 4772 geological disasters occurred, including 2335 landslides (https://www.mem.gov.cn/gk/tjsj/ (accessed on 23 January 2022)).
The loess soil has obvious water sensitivity, disintegration, developing pores, and vertical joints [5,6], which caused the many geo-disasters that developed in the loess plateau, such as landslides, collapses, and mudflows [7,8,9]. Recently, as human engineering activities intensify, more and more geological disasters have occurred and caused many economic loess, especially under the conditions of a frequent extreme climate [10,11,12]. Continuous intensive rainfalls occurred in Shanxi Province from June to October 2021, and numerous geological disasters, such as landslides and collapses, occurred. The field investigations found that over 30 geological disasters occurred in Chencang District, Baoji City, which seriously threatened the lives of 831 people and the safety of 195 buildings (more details are shown in Table 1). Most of these geological disasters are collapses, developing in the loess layer because of the construction of the cave dwelling. Therefore, the properties of the loess were analyzed. The failure mechanisms of these geological disasters were analyzed. The results could help to understand the failure mechanism of shallow loess landslides caused by extreme rainfall.

2. Chencang District Description

2.1. Topography and Geology

Chencang District is situated in Baoji City, Shanxi Province, China. It is 119.49 km long from east to west, 67.78 km wide from north to south, and its area is 2517 km2 (Figure 1). The maximum elevation difference in the study area is 1732 m. Weihe River flows through the Chencang District. Four tributary streams form a complex surface runoff network. The western and southeastern parts of the district are mountainous, with elevations ranging from 150 to 450 m. The northwestern region features loess hills, including Xiangong and Xinjie Towns. The northeastern area consists of loess terraces and plains, which are densely populated and encompass the towns of Qiao, Jiacun, Qianhe, Guo, Panxi, Tianwang, Yangping, Diaowei, Zhouyuan, and Muyi. An overall step-like morphology is formed by multilevel fluvial terraces, which resulted from the combination of repeated tectonic uplift stages and river erosion.
The main geologic units of the study area are loess, interbedded sandstone and mudstone, carbonatite and metamorphic rock series, and granite series (Figure 2). The depth of loess in the study area is 0–100 m [12], which is widely distributed in the middle and east of the Chencang District area. The interbedded sandstone and mudstone represent the easy sliding stratum in Shanxi Province, which is located in the north of the area. The granite and metamorphic rock series are widely distributed in the mountain area.

2.2. Rainfall

Figure 3a shows the annual rainfall of Chencang District from 1974 to 2007. The annual rainfalls of those years are greater than 600 mm in more than half the years, and the maximum value was less than 1000 mm. There are obvious regional differences in atmospheric precipitation in Chencang District (Figure 2). In the loess plateau of northeastern China, annual rainfall averages 600 mm. In the western mountainous regions, this figure increases to 750 mm. The Qinling Mountains experience the highest rainfall, with local amounts reaching up to 900 mm. Rainfall is predominantly concentrated between June and October each year.
Figure 3b,c show the rainfall distribution from June to October 2021. During this period, there were 19 days with daily rainfall exceeding 20 mm, indicating concentrated precipitation. Notably, the cumulative rainfall from 13–17 June was 131.04 mm. Similarly, the cumulative rainfall was 112.31 mm from 15–18 September, and, from 22–28 September, it reached 224.47 mm. The total cumulative rainfall over these five months amounted to 1163.48 mm, which is 2.27 times the average of previous years. Specifically, the monthly rainfall in September 2021 is 3.69 times the historical average, 2.77 times in June, and 1.69 times in August.

2.3. NDVI of Chencang District

The Normalized Difference Vegetation Index (NDVI) is a widely used metric for estimating the health and density of vegetation using sensor data. It is derived from spectrometric data at two specific wavelengths: red and near-infrared. These data are typically obtained from remote sensors (MODIS13A13, NASA, Washington, DC, USA).
NDVI evaluates vegetation by comparing the difference between near-infrared light (which vegetation reflects strongly) and red light (which vegetation absorbs). The formula for NDVI is as follows:
N D V I = N I R R N I R + R
where NIR is the near-infrared value. R is the red value
The Normalized Difference Vegetation Index (NDVI) measures vegetation health and density by comparing the reflectance of near-infrared and red light. NDVI values range from −1 to +1, with negative values typically indicating water, values close to +1 representing dense green leaves, and values near zero indicating urbanized or barren areas. Higher NDVI values signify healthier vegetation, while lower NDVI values indicate sparse or absent vegetation. We collected vegetation data from May to October 2021 and used the maximum synthesis method to generate the NDVI map of the Chencang area. This method selects the highest NDVI value for each pixel from a series of images, effectively removing the effects of clouds, shadows, and atmospheric disturbances. As a result, it produces a more accurate and reliable NDVI map that reflects the actual vegetation conditions of the Chencang area. Figure 4 shows the NDVI of Chencang District. The eastern part of the district has lower NDVI values due to the presence of many rivers. This region is mainly composed of loess, a type of soil that is easily eroded by water. The terrain is also low and flat, facilitating human activities such as agriculture and urbanization. Lower NDVI values indicate less vegetation cover and more bare land. Similarly, Pingtou Town, Xiangquan Town, and the western edge of the Chencang District also have lower NDVI values.

3. Materials and Methodology

3.1. Field Investigations and Remote Sensing Technology

In 2010, field investigations and Remote Sensing Technology detected a total of 382 geological disasters (Figure 1), consisting of 331 landslides, 22 collapses, and 18 mudslides. Among these, there are 5 extra-large landslides (volume > 10 million m3), 13 giant landslides (volume > 3 million m3), and 27 large-scale landslides (volume 0.5–3.0 million m3). Additionally, there are 3 extra-large collapses (1 million m3) and 5 large-scale collapses (100,000 m3). More than 100 geological disasters (37.8%) occurred in the loess layer. Most of these geological disasters were concentrated in the northwest and east of the district, where the topography consists of loess terrace and plain and the stratum is the deposit [13].

3.2. Ethylene Glycol-Diethyl Ether Method and Shear Test

We used the ethylene glycol-diethyl ether method to measure the specific surface area of the soil samples. First, we soaked the soil samples with ethylene glycol-diethyl and then removed the excess liquid by vacuuming. Second, we weighed the samples periodically until their mass was stable. Finally, we calculated the specific surface area of the samples by assuming that the mass of the remaining liquid was ethylene glycol-diethyl ether adsorbed on the surface of a monolayer. We obtained the shear strength of the soil samples by consolidated drain test using the DSJ-2 strain direct shear apparatus produced by Nanjing Soil Instrument Company (220 Xiaowei Street, Xuanwu District, Nanjing, China). The shear rate was 0.02 mm/min, and the vertical stress was 100 kPa, 200 kPa, 300 kPa, or 400 kPa. We repeated the shear test five times for each soil sample. We took the peak of the first shear result as the shear strength of the soil sample. We obtained the physical and mechanical indices of the Sanmen Formation stiff clay and the Hipparion red clay.

3.3. Two Typical Loess Properties

To determine the properties of the Hipparion red clay and the Sanmen Formation stiff clay, we conducted spot drilling samplings in three locations: Jiacun, Yangping, and Xiangong (Figure 1), collecting thirty soil samples. As shown in Table 2, the clay content (particles < 5 μm) ranged from 40–50%, and an average montmorillonite content was between 15% and 20%. The montmorillonite content increased with the specific surface area (Figure 5a). The average montmorillonite content and specific surface area in the Sanmen Formation stiff clay were 17.68% and 166.2 m2/g, respectively, which were lower than those in the Hipparion red clay (21.70%, 207.7 m2/g). Shear strength decreased with the water content (Figure 5b). As shown in Table 3, both kinds of clay soils with 16% water content exhibited higher cohesion (128.2 kPa and 115.1 kPa), but their cohesion rapidly decreased to 98.5 kPa and 75.6 kPa when saturated (Table 3). Their friction also decreased to 20% and 23%, respectively. The residual cohesion and friction decreased by 60–70% and 35–40%, respectively. Additionally, the loess in the study area exhibited strong disintegration. We dried the soil samples at a constant temperature of 105 °C and then placed the samples with natural water content into a container filled with water, recording the fragmentation process. The soil samples disintegrated completely within 4.5 h (Figure 5c). The plasticity index of the Sanmen Formation stiff clay ranged from 13.70% to 22.94% (average = 18.4%), while the Hipparion red clay ranged from 17.83% to 33.00% (average = 23.30%). We classified these clays into medium and high degrees of potential expansiveness based on the relationship between the plasticity index of the whole sample and the percentage clay fraction [14,15] (Figure 5d).

4. Results

4.1. Field Investigation of Loess

Loess is widely distributed in Baoji City, with thicknesses ranging from 0.2 m to 180.0 m. It exhibits strong water sensitivity and forms some vertical joints [16,17]. The field investigation revealed that the Pliocene clay layers are the weak layers in the loess slope due to their pronounced water sensitivity and swelling–shrinkage characteristics. Numerous joints exist in the Hipparion red clay and the Sanmen Formation stiff clay (Figure 6). These joints include tectonic joint fissures (Figure 6a,b), unloading joints, and swell–shrink fissures (Figure 6c), which are induced by the water absorption, expansion, and shrinkage of the strongly hydrophilic clay minerals (such as montmorillonite). Additionally, these two types of clays exhibit high water sensitivity. Consequently, shear zones are easily generated between these clay layers and other loess layers (Figure 6c). There are also evident brush abrasions in the shear zone between the loess and the Hipparion red clay (Figure 6d).

4.2. Distribution of Geological Disasters Induced by Extreme Continuous Intense Rainfall

In 2021, we conducted field investigations and identified over 30 geological disasters, endangering the lives of 831 people and the safety of 195 buildings (see Table 1 and Figure 1 for more details). These disasters included thirteen landslides, eleven collapses, and two ground fissures. Notably, 77.8% of these geological disasters occurred in cut slopes caused by excavation, and 87.5% (21 incidents) had a failure volume of less than 200 m3. Most of these geological disasters were not within the scope of the investigation in 2010. We classified the slopes into 12 types based on their location and stratum. Slopes No. 1–2 were mainly found in the loess area, especially near the bank. Slopes No. 3–4 were located to the south of Xiangquan and Chisha, and to the west of Tuoshi. Slope No. 5 was situated to the north of Qiao. Slope No. 6 was mostly found in Chisha, Pingtou, and Xinjie. Slopes No. 7–9 were in the loess ridge area, including places like Xiangong and Xinjie. Slope No. 10 was mainly found in Chisha/Pingtou, Xinjie, and Xiangong, with the rock layer composed of mudstone and muddy sandstone. Finally, Slopes No. 11–12 were located to the north of Qiao and Xinjie, with the stratum consisting of clastic rock and loess.

4.3. Deformation Characteristics of Geological Disasters

During our field investigations, we identified two ground fissures on the roads (Figure 7). The first fissure was located in Tuoshi Town and was initially observed on 26 September 2021, with a width of 10–20 mm. By 7 October 2021, it had expanded to a width of 50–60 mm and exhibited a vertical displacement of 100 mm (Figure 7a,b). This fissure extended approximately parallel to the road. The second ground fissure was discovered on 5 October 2021, extending approximately perpendicular to the road (Figure 7c). The ground fissure crossed the road, measuring 30 m in length and 0.3 m in width, with a maximum vertical displacement of 1.2 m (Figure 7d). The main stratum of the road foundation was colluvial soil, characterized by low strength and high porosity.
Collapses are widely developed in Shanxi Province due to its unique humanistic and geological environment. Cave dwellings, traditional constructions on the loess plateau of northern China, are typically built in ravines, gullies, or hills. The construction of these cave dwellings have created many bluff slopes, and numerous new buildings have been constructed in front of these cave dwellings. During this extreme and continuous heavy rainfall, we observed more than a dozen small-scale collapses (Figure 8), which caused varying degrees of damage to the houses, roads, and people.
Figure 9 shows the deformation characteristics of the collapses that occurred on the vertical slope. Most of these collapses took place at the cliffs behind the buildings, potentially damaging the roads (Figure 9a,b) and buildings, causing economic losses and casualties. Some collapses also occurred above the cave dwellings (Figure 9b,c,e,f). Our field investigation revealed that the collapsing mass had a lower water content, with a higher water content only in the shallow soil layer (1–2 m) (Figure 9b,e).
We observed a specific type of landslide that exhibited fluid-like movement of the slope. Our field investigations revealed that this landslide originated from the top of a cave (Figure 10). The landslide body had a high water content, which enabled it to move in a fluid state. In contrast, the stable formation had a significantly lower water content. Figure 10b–d show that the landslide underwent complete fluidization.
Figure 11 shows the deformation characteristics of the landslides. We did not observe any obvious deformation in the large landslides during our field investigation, but we did observe some shallow landslides. We classified the landslides into three types based on their deformation characteristics. (1) Tension cracks and sliding: Continuous rainfall generated tension cracks, causing the landslide to slide along the sliding zone. For example, Figure 11a,b shows a highway slope after excavation, with a height of 10 m and a depth of 5 m. Sliding occurred in the shallow landslide (Figure 11a), and a tension crack was found in the shoulder of the slope, extending along the water furrow. The crack measured 6–7 m in length and had a maximum width of 50 mm (Figure 11b). Rainfall infiltrated into the deep landslide through those tension cracks, rapidly decreasing the shear strength of the sliding zone soil, resulting in landslide movement (Figure 11c,d). (2) Flow liquefaction failure: The sliding mass had high water content and experienced flow liquefaction failure (Figure 11e,g). Groundwater was observed seeping from the toe of the landslides. The high water sensitivity and liquefaction of the loess were the key factors contributing to the landslide movement. (3) Interface-controlled sliding: The landslide was controlled by the interface between the surficial deposit and the bedrock (Figure 11h). Although no obvious deformation was observed in the large landslides, local landslides occurred, potentially decreasing the overall stability of the landslides (Figure 11h,i).

5. Discussion

5.1. Failure Mechanism of Geological Disasters under Rainfalls

The loess beneath the colluvial layer exhibits strong water sensitivity [5,18] due to its medium to high potential expansiveness (Figure 5d) [19]. This characteristic causes the soil to periodically expand and shrink during moisture absorption and dehumidification (Figure 5b,c) [20,21,22]. During extreme heavy rainfall, rain infiltrated into the road foundation, increasing the soil’s water content [21]. Consequently, the volume of the colluvial and loess soil changed, the shear strength decreased, and the structure gradually failed (Figure 5b,c) [23,24]. This led to the uneven settlement of the road foundation. Additionally, the road colors in Figure 7c varied where the cracks occurred, and the cracks were approximately parallel to the boundary, suggesting that the construction technology also influenced the deformation of the road [10].
Loess is characterized by the presence of vertical joints (Figure 6 and Figure 12a), which are more pronounced in steep cliffs due to the excavation unloading effect (Figure 12b,c). These joints widened and deepened over time, allowing more water to infiltrate the soil and increase the water content of the loess [25]. This reduced the shear strength of the loess, making it more prone to collapse. Furthermore, tension cracks that develop along the joints (Figure 12a,b) can propagate through the slope (Figure 12d), facilitating further rain infiltration. Figure 12b shows that the depth of the wetting front along the joints is greater than in the other parts of the slope. Some vegetation growing on the top of the cliff, with the roots penetrating into the tension cracks (Figure 9c), exacerbates this issue. There were 11 periods of rainfall from June to October (Figure 3), creating periodic saturated conditions in the soil. Under these conditions, the interaction between the roots and the shallow soil layer weakens, and the tension cracks gradually expand (Figure 12c). This suggests that the root system can have a dual effect on the slope stability: it could reinforce the shallow soil layer but also enhance the water infiltration and slope instability due to the root splitting effect [26,27,28]. Based on these observations, we propose two possible failure modes for the collapse: vertical collapse along the joints (Figure 9e,f) and mudslide along the arc-shaped sliding surface (Figure 10a,b,f). These two modes have distinct characteristics. The first mode has a low moisture content in the sliding mass (11%), with the wetting front reaching only a shallow depth (10–20 cm). The sliding surface mainly follows the vertical cracks, indicating that this mode is controlled by joint development. Root growth and rainfall infiltration could exacerbate the deformation and failure of this mode. The second mode has a high moisture content in the sliding mass (over 40%), with the wetting front exceeding the liquid limit index. The sliding mass is fluid-plastic, and the sliding surface is arc-shaped. This mode is controlled by the water-sensitive characteristics of loess, which cause the soil structure to disintegrate rapidly upon encountering water, resulting in a loss of strength and failure. The horizontal displacement of the landslide is notably greater than its vertical displacement. Although the destructive power of this type of landslide is less than that of the previously mentioned collapse disasters, its extensive movement distance could significantly impact the residents’ lives. Furthermore, the fluidization of the loess body could lead to the destruction of the roadbeds and building foundations.
The residents constructed cave dwellings by cutting the original slope into a nearly vertical steep slope for aesthetic purposes and planted cypress trees on the top of the slope (Figure 13). Over time, tensile cracks developed in the upper part of the slope and spread downward, creating unstable rock masses. With the social and economic development and improved living standards, the residents abandoned the traditional cave dwellings and built brick-concrete structures in front of them (Figure 8). As a result, the cave dwelling decayed, the internal support structure was damaged, and the necessary maintenance of the overlying soil layer was ignored. This neglect contributed to the occurrence of the loess landslide/collapse [29].
Based on the analysis above, we can deduce the deformation process of the collapse (Figure 14) [29]. After excavation, unloading cracks and tension cracks formed at the top of the collapse (Figure 12b and Figure 14b). The joints, along with the root system, provided channels for rainfall infiltration, accelerating the propagation of the tension cracks (Figure 14c). Eventually, the unstable clay mass collapsed rapidly. We identified two failure modes. The collapses in Figure 10 and Figure 11 occurred along a polyline-shaped sliding surface (Figure 14c). In contrast, the collapses in Figure 9 occurred along a vertical sliding surface (Figure 14d) due to the deep vertical depth of the crack. For example, in Figure 12b, several noticeable vertical cracks with depths of 3–6 m can be observed on the left side of the collapse zone, causing the loess to fail along the vertical sliding surface.
Most of the landslides that occurred during this extreme rainfall were shallow slides along a curved sliding surface (Figure 11a,b,e). The sliding mass was saturated and moved in a fluid state, resembling a mudslide (Figure 11c,d). This failure mechanism was completely different from previous models. Rainfall infiltrated the shallow layer in large quantities through micro-, fine, and macroscopic dominant channels, causing shallow collapse and sliding disasters [30]. According to the Mohr–Coulomb criterion, cohesion is the main component of the shear strength of shallow loess, while friction is the main component of deep loess [31]. Figure 5c shows that the cohesion of loess has strong water sensitivity due to the dissolution and lubrication effect of water on cementation, whereas friction has low water sensitivity. Therefore, shallow loess is easy to slide. Additionally, water-saturated loess soil is highly susceptible to flow liquefaction failure [16,17,26,32]. The failure mode of the shallow slide in Figure 11b is shown in Figure 15a. We collected a soil sample from the sliding zone and observed clear scratches (Figure 15b). We examined the micro-structures of the sliding zone before and after sliding using scanning electron microscopy (SEM). We found that the sliding zone had a flocculent structure before sliding (Figure 15c), which changed to a laminated structure with scratches and a mirror surface (Figure 15d). Therefore, the extreme rainfall infiltration increased the underground water level, which increased the excess pore water pressure and decreased the effective stress. As a result, the water-saturated loess collapsed due to flow liquefaction failure after continuous intense rainfall [33,34].

5.2. Local Intensity–Duration (I–D) Threshold

The intensity–duration (I–D) threshold equation is an empirical model for predicting rainfall thresholds that trigger landslides [35,36]. The general form of the equation is I = α D−β, where α and β are empirical parameters. Figure 16 shows a log–log plot of duration and intensity, with the diameter of the circle indicating the number of geological disaster events. The minimum and maximum duration are 1 day and 16 days, respectively. Although only 30 geological disasters were analyzed, the threshold equation obtained is as follows:
I = 90 D−0.92
According to this threshold equation, no collapse or landslide will occur if the daily rainfall is less than 90 mm. However, rainfall of 12 mm/day for 16 consecutive days could also trigger collapses or landslides. The collapse and landslide events occurred more frequently towards the upper right of the graph, especially when the rainfall was 28.07 mm for 8 days and 12.01 mm for 16 days. Therefore, it could be inferred that the main causes of the collapses and landslides in the loess area are lower-intensity rainfall but with longer durations.

6. Conclusions

Continuous heavy rainfall events triggered over 30 natural disasters, endangering the lives of 831 people and damaging 195 houses in Chencang District, Baoji City, Shanxi Province, China. Most of these geological disasters were collapses occurring in the loess layer. Compared to the over 300 geological disasters detected by field investigation and Remote Sensing Technology, these events were characterized by small volume (<20 m³), shallow sliding, and great damage. We analyzed the properties of the Sanmen Formation stiff clay and the Hipparion red clay. The montmorillonite content increased with specific surface area, and the shear strength of the loess rapidly decreased with increasing water content, leading to complete disintegration within several hours. Moreover, the excavation of the cave dwellings has created numerous steep slopes, leading to the formation of unloading fissures. The root systems of the plants at the top of the slopes further exacerbate the expansion of these fissures. During extreme rainfall events, water infiltrates extensively along those unloading fissures, causing a rapid increase in the moisture content of the superficial loess layer. Meanwhile, groundwater cannot infiltrate deeper into the sliding mass in a timely manner, resulting in a rapid decrease in the strength of the superficial loess and a clear boundary between the high moisture content of the superficial sliding mass and the low moisture content of the mid-deep sliding mass. Therefore, the superficial sliding mass is prone to sliding. We classified the geological hazard bodies into three categories: (1) collapse bodies controlled by vertical joints that are highly destructive; (2) mudslides controlled by water sensitivity and the excavation of the loess, with deformation and failure accelerated by rainfall, root splitting, and cave kiln; (3) shallow landslides controlled by the water sensitivity of the loess and the rise in the groundwater level caused by heavy rainfall. In addition, we proposed a regional threshold for the loess area (I = 90 D−0.92), which could be used in a real-time landslide- or collapse early-warning system for the loess area.

Author Contributions

Conceptualization, C.Z., Z.X., L.M., S.H., J.Y., D.A. and C.X.; Methodology, D.C., L.M., L.L. and H.X.; Software, C.Z.; Validation, Z.X., D.C., S.H., W.H. and C.X.; Formal analysis, C.Z. and H.X.; Investigation, Z.X., D.C. and D.A.; Resources, J.Y. and W.H.; Data curation, L.M. and S.H.; Writing—original draft, C.Z. and C.X.; Writing—review & editing, L.L.; Project administration, J.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This study was financially supported by the National Natural Science Foundation of China (No. U22A20569, 42207169) and the Open Fund of Badong National Observation and Research Station of Geohazards (BNORSG202315).

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

Author Zhao Xia was employed by the company Hunan Water Planning and Design Institute Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Location of Chencang District. Note the black spots (345) are the disasters found by the satellite and field investigation. The red spots are the geological disasters during June–October 2021.
Figure 1. Location of Chencang District. Note the black spots (345) are the disasters found by the satellite and field investigation. The red spots are the geological disasters during June–October 2021.
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Figure 2. Stratum, disasters distribution, and annual rainfall of Chencang District.
Figure 2. Stratum, disasters distribution, and annual rainfall of Chencang District.
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Figure 3. Rainfall of Chencang District: (a) annual rainfall from 1974 to 2006; (b) average monthly rainfall from July to October during 1974–2006 (red histogram) and 2021 (black histogram); (c) daily and accumulation rainfall from June to October 2021.
Figure 3. Rainfall of Chencang District: (a) annual rainfall from 1974 to 2006; (b) average monthly rainfall from July to October during 1974–2006 (red histogram) and 2021 (black histogram); (c) daily and accumulation rainfall from June to October 2021.
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Figure 4. The Normalized Difference Vegetation Index (NDVI) of Chencang District. Data resource: MODIS13A13.
Figure 4. The Normalized Difference Vegetation Index (NDVI) of Chencang District. Data resource: MODIS13A13.
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Figure 5. Property of Sanmen Formation stiff clay and the Hipparion red clay. (a) Montmorillonite content; (b) cohesion of loess under different water content; (c) disintegration and (d) determination of potential expansiveness of soils. “*” represents multiplication sign.
Figure 5. Property of Sanmen Formation stiff clay and the Hipparion red clay. (a) Montmorillonite content; (b) cohesion of loess under different water content; (c) disintegration and (d) determination of potential expansiveness of soils. “*” represents multiplication sign.
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Figure 6. (a,b) Joints and faults in loess and stiff clay; (c) the shear zone between the Hipparion red clay and loess; (d) grazes in the shear zone between loess and the Hipparion red clay. Red dotted lines on the figure represent the cracks in the soil layer.
Figure 6. (a,b) Joints and faults in loess and stiff clay; (c) the shear zone between the Hipparion red clay and loess; (d) grazes in the shear zone between loess and the Hipparion red clay. Red dotted lines on the figure represent the cracks in the soil layer.
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Figure 7. Deformation characteristics of ground fissures. (a) Crack occurred in front of a building with (b) a vertical displacement of 100 mm; (c,d) ground fissure in the road.
Figure 7. Deformation characteristics of ground fissures. (a) Crack occurred in front of a building with (b) a vertical displacement of 100 mm; (c,d) ground fissure in the road.
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Figure 8. Distribution of collapses. Red arrows represent the sliding direction of the collapses or slopes, yellow dotted lines are the rear edge of those geo-disasters.
Figure 8. Distribution of collapses. Red arrows represent the sliding direction of the collapses or slopes, yellow dotted lines are the rear edge of those geo-disasters.
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Figure 9. Collapse damaged roads and builds. (a) A collapse destroyed a road; (b) a collapse occurred in front of a road; (c) a collapse occurred and destroyed a cave dwelling; (d) two tension cracks occurred in front of a building; (e,f) a collapse occurred above the cave dwelling and damaged the buildings. Red arrows represent the sliding direction of the collapses or slopes, yellow dotted lines are the rear edge of those geo-disasters.
Figure 9. Collapse damaged roads and builds. (a) A collapse destroyed a road; (b) a collapse occurred in front of a road; (c) a collapse occurred and destroyed a cave dwelling; (d) two tension cracks occurred in front of a building; (e,f) a collapse occurred above the cave dwelling and damaged the buildings. Red arrows represent the sliding direction of the collapses or slopes, yellow dotted lines are the rear edge of those geo-disasters.
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Figure 10. (a) Shallow collapse and (b) sliding disasters; (ce) show the details of the sliding disasters. Red arrows represent the sliding direction of the collapses or slopes, the yellow dotted lines are the rear edge of those geo-disasters.
Figure 10. (a) Shallow collapse and (b) sliding disasters; (ce) show the details of the sliding disasters. Red arrows represent the sliding direction of the collapses or slopes, the yellow dotted lines are the rear edge of those geo-disasters.
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Figure 11. Deformation characteristics of landslides. (a) A landslide occurred behind a road; (b) severe cracks occurred and groundwater infiltrated the landslide along those cracks; (c,d) a landslide behind a building; (eg) a landslide moved like flow; (h) a small landslide occurred along the bedrock–cover interface; (i) local sliding in a huge landslide. Red arrows represent the sliding direction of the collapses or slopes, the yellow dotted lines are the rear edge of those geo-disasters.
Figure 11. Deformation characteristics of landslides. (a) A landslide occurred behind a road; (b) severe cracks occurred and groundwater infiltrated the landslide along those cracks; (c,d) a landslide behind a building; (eg) a landslide moved like flow; (h) a small landslide occurred along the bedrock–cover interface; (i) local sliding in a huge landslide. Red arrows represent the sliding direction of the collapses or slopes, the yellow dotted lines are the rear edge of those geo-disasters.
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Figure 12. (a) Joints in the loess layer; (b) unloading joints; (c) shear cracks and tree roots in the shear cracks; (d) profile of collapses. Red arrows represent the sliding direction of the collapses or slopes, the yellow dotted lines are the rear edge of those geo-disasters. Red dotted lines represent the cracks developed in the soil layer.
Figure 12. (a) Joints in the loess layer; (b) unloading joints; (c) shear cracks and tree roots in the shear cracks; (d) profile of collapses. Red arrows represent the sliding direction of the collapses or slopes, the yellow dotted lines are the rear edge of those geo-disasters. Red dotted lines represent the cracks developed in the soil layer.
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Figure 13. Effects of excavation, vegetation, and rainfall on the stability of cave dwellings in loess: (a) vertical cracks above the abandoned cave dwellings; (b,c) collapse above the cave dwellings. Yellow arrows represent the sliding direction of the collapses or slopes, yellow dotted lines are the cracks developed in the soil layer. Red dotted lines are cave dwellings.
Figure 13. Effects of excavation, vegetation, and rainfall on the stability of cave dwellings in loess: (a) vertical cracks above the abandoned cave dwellings; (b,c) collapse above the cave dwellings. Yellow arrows represent the sliding direction of the collapses or slopes, yellow dotted lines are the cracks developed in the soil layer. Red dotted lines are cave dwellings.
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Figure 14. Deformation process of the collapses. (a) Initial model; (b) excavation of cave dwelling; (c) formation of tension cracks and local collapse; (d) complete collapse burying cave dwelling and formation of stable slope.
Figure 14. Deformation process of the collapses. (a) Initial model; (b) excavation of cave dwelling; (c) formation of tension cracks and local collapse; (d) complete collapse burying cave dwelling and formation of stable slope.
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Figure 15. (a) Failure model of the shallow sliding; (b) soil sample of sliding zone; (c) micro-structure of the soil sample before sliding; (d) micro-structure of the soil sample after sliding.
Figure 15. (a) Failure model of the shallow sliding; (b) soil sample of sliding zone; (c) micro-structure of the soil sample before sliding; (d) micro-structure of the soil sample after sliding.
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Figure 16. Rainfall intensity–duration threshold for the rainfall events, which led to landslide and collapse occurrences in Chencang District, Baoji. The diameter of the circle indicates the number of disaster events.
Figure 16. Rainfall intensity–duration threshold for the rainfall events, which led to landslide and collapse occurrences in Chencang District, Baoji. The diameter of the circle indicates the number of disaster events.
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Table 1. Information of nature hazards after the continuous rainfalls.
Table 1. Information of nature hazards after the continuous rainfalls.
TypeLocationDeveloping StrataVolume (m³)ReasonHazardsTime of Occurrence
No. 1LandslideE 107°01′23.59″
N 34°33′21.52″
Quaternary loess60Excavation (house)5 h 8 peoples5 October
No. 2CollapseE 107°01′28.75″
N 34°31′17.28″
Quaternary loess100Excavation (house)5 h, 2 people29 September
No. 3LandslideE 106°59′54.71″
N 34°32′35.26″
Quaternary loess200Excavation (house)15 h, 30 people and 1 road5 October
No. 4LandslideE 107°04′24.09″
N 34°32′34.01″
Quaternary loess100Excavation (house)21 h, 85 people30 September
No. 5LandslideE 107°04′24.09″
N 34°32′34.01″
Quaternary loess100Excavation (house)25 houses, 90 people, 1 road28 September
No. 6CollapseE 107°08′16.63″
N 34°32′11.56
Quaternary loess20Excavation (house)1 house, 1 people27 September
No. 7CollapseE 107°07′49.34″
N 34°32′03.09″
Quaternary loess20Excavation (house)1 house, 3 peoples28 September
No. 8LandslideE 107°07′49.65″
N 31°30′56.47″
Quaternary loess50Excavation (road)1 house, 3 peoples28 September
No. 9CollapseE 107°07′45.55″
N 31°30′14.06″
Quaternary loess100Excavation (house)1 house, 2 peoples10 October
No. 10CollapseE 107°09′16.84″
N 34°33′34.60″
Quaternary loess20Excavation (house)6 h, 24 people29 September
No. 11CollapseE 107°15′51.18″
N 34°29′10.04″
Quaternary loess40Excavation (house)16 houses, 20 peoples26 September
No. 12CollapseE 107°15′51.18″
N 34°29′10.04″
Quaternary loess20Excavation (house)10 houses, 8 peoples5 October
No. 13CollapseE 107°16′11.60″
N 34°28′51.55″
Quaternary loess40Excavation (house)10 houses, 8 peoples26 September
No. 14CollapseE 107°29′08″
N 34°20′03″
Quaternary loess200Excavation (road)1 road26 September
No. 15CollapseE 106°53′6.46″
N 34°49′31.17″
Quaternary loess400Excavation (house)17 houses, 30 peoples4 October
No. 16CollapseE 106°54′17.30″
N 34°49′26.13″
Quaternary loess200Excavation (house)9 houses, 22 peoples4 October
No. 17Ground fissureE 106°53′48.79″
N 35°02′21.09″
Quaternary loess Excavation (road)1 road5 October
No. 18CollapseE 106°57′57.17″
N 34°21′31.12″
Quaternary loess200Excavation (house)1 house, 2 peoplesFirst: 5 October
Second: 7 October
No. 19LandslideE 106°56′53.88″
N 34°22′28.15″
Quaternary loess400Excavation (house)21 houses, 37 peoples26 September
No. 20LandslideE 106°55′0.88″
N 34°22′28.15″
Quaternary loess400Excavation (house)21 houses, 37 peoples26 September
No. 21LandslideE 106°52′53.13″
N 34°22′28.15″
Quaternary loess400Excavation (house)21 houses, 37 peoples26 September
No. 22LandslideE 106°41′15″
N 34°24′14″
Quaternary residual gravel soil Rainfall2 houses, 8 peoples6 October
No.23LandslideE 106°41′45.47″
N 34°24′43.10″
Quaternary loess500Excavation (house)4 houses, 17 peoples26 September
No.24LandslideE 106°39′34.47″
N 34°23′20.68″
Quaternary loess100Excavation (road)64 houses, 234 peoples6 October
No.25Ground fissureE 106°42′16.06″
N 34°23′17.20″
Quaternary loess Excavation (house)8 houses, 20 peoples6 October
No.26slumpE 106°39′49.49″
N 34°22′59.91″
Quaternary loess700Excavation (house)1 house, 8 peoples26 September
No.27LandslideE 106°32′0.88″
N 34°32′28.15″
Quaternary loess400Excavation (house)21 houses, 37 peoples26 September
No.28LandslideE 106°30′6.84″
N 34°32′2 0.93″
Quaternary loess2000Excavation (road)36 h, 49 people-
No.29LandslideE 106°27′11″
N 34°32′00″
Quaternary loess and gneiss20Excavation (house)40 houses, 200 peoples4 October
No.30LandslideE 106°26′0.88″
N 34°32′28.15″
Quaternary loess Excavation (house)3 houses-
Table 2. Particle size grading of two clays.
Table 2. Particle size grading of two clays.
Soil
Samples
SoilParticle Size Grading (mm %)
>0.0750.075~0.005<0.005<0.002
S1Sanmen Formation stiff clay5.37~13.30
(Average = 9.18)
39.29~58.04
(49.58)
30.20~52.85
(42.24)
21.89~45.25
(33.62)
S23.19~12.80
(7.97)
48.09~54.92
(52.56)
27.31~48.72
(39.47)
24.43~43.56
(33.33)
S31.51~21.21
(9.74)
46.53~68.46
(56.04)
31.12~44.32
(34.23)
21.87~36.75
(28.99)
S3Hipparion Red clay0.08~3.41
(1.54)
45.02~62.71
(55.2)
37.12~54.40
(43.3)
30.24~48.04
(37.1)
Table 3. Shear strength of two clays under saturated and unsaturated states.
Table 3. Shear strength of two clays under saturated and unsaturated states.
Soil SampleUnsaturated State (w = 18%)Saturated State
PeakResidualPeakResidual
C/kPaφ(°)C/kPaφ(°)C/kPaφ(°)C/kPaφ(°)
Sanmen Formation stiff clay128.234.936.122.798.528.132.617.4
Hipparion Red clay115.134.348.921.275.626.429.415.6
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Zhou, C.; Xia, Z.; Chen, D.; Miao, L.; Hu, S.; Yuan, J.; Huang, W.; Liu, L.; Ai, D.; Xu, H.; et al. Extreme Rainfall Events Triggered Loess Collapses and Landslides in Chencang District, Shanxi, China, during June–October 2021. Water 2024, 16, 2279. https://doi.org/10.3390/w16162279

AMA Style

Zhou C, Xia Z, Chen D, Miao L, Hu S, Yuan J, Huang W, Liu L, Ai D, Xu H, et al. Extreme Rainfall Events Triggered Loess Collapses and Landslides in Chencang District, Shanxi, China, during June–October 2021. Water. 2024; 16(16):2279. https://doi.org/10.3390/w16162279

Chicago/Turabian Style

Zhou, Chang, Zhao Xia, Debin Chen, Leqian Miao, Shenghua Hu, Jingjing Yuan, Wei Huang, Li Liu, Dong Ai, Huiyuan Xu, and et al. 2024. "Extreme Rainfall Events Triggered Loess Collapses and Landslides in Chencang District, Shanxi, China, during June–October 2021" Water 16, no. 16: 2279. https://doi.org/10.3390/w16162279

APA Style

Zhou, C., Xia, Z., Chen, D., Miao, L., Hu, S., Yuan, J., Huang, W., Liu, L., Ai, D., Xu, H., & Xiao, C. (2024). Extreme Rainfall Events Triggered Loess Collapses and Landslides in Chencang District, Shanxi, China, during June–October 2021. Water, 16(16), 2279. https://doi.org/10.3390/w16162279

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