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The reactivation of ancient landslides, a persistent issue that hinders urban development and threatens human safety, is the central focus of this paper. Specifically, this paper offers a detailed description and analysis of an ancient landslide that reactivated on February 26, 2021, in Guoye town, Zhouqu County, Gansu Province, China, and has remained slow-moving since then. With a volume of approximately 21.2 million m3 of rock and soil masses involved, this landslide poses a significant risk to the safety of 1119 individuals from 282 households in Moli village and Guoye village. A combination of field investigations, remote sensing interpretation, in situ monitoring, and interferometric synthetic aperture radar (InSAR) was used to investigate the landslide characteristics and reactivation mechanisms. The results revealed that the presence of sliding-prone rock formations and tectonic movement were the primary contributors to the formation of the Moli landslide. Furthermore, the accumulation of bedrock blocks in the quarry and collapsed rock masses caused by fault activity at the rear parts, along with the additional load from buildings on the middle and rear sections, increased the sliding force. Simultaneously, the erosion of the Dashuiba River resulted in a reduction in the anti-slip force, thereby directly facilitating landslide reactivation. The notable increase in annual rainfall in recent years has played a crucial role in ancient landslide reactivation by elevating the groundwater level and softening the shear strength of the sliding zone soil. The findings of this study contribute to an enhanced understanding of the reactivation mechanisms in giant, ancient landslides situated within areas characterized by highly complex geological conditions. [ABSTRACT FROM AUTHOR]

Due to their practicability, simple and data-driven empirical models have been extensively developed and applied in practical engineering to predict the run-out distance of landslides. However, the definition of the most appropriate empirical model for specific landslide data is rarely discussed. Moreover, the empirical model is subjected to the high variability of landslide data, which should be quantified into the model to provide more reliable predictions. As such, we propose in this paper, a simple, practical, and probabilistic run-out distance prediction method based on an empirical model and Bayesian method. This method was implemented with a regional landslide inventory compiled from 34 loess landslides in Heifangtai Terrace, Gansu Province, China. In this method, we performed a Bayesian model selection to determine the most appropriate empirical model for the compiled database among the possible candidate models adapted from previous literature. Considering the high variability of data, unknown parameters of the empirical model are regarded as random variables, and their posterior distributions are obtained by Bayesian updating with the compiled database. Then, we developed the probabilistic run-out prediction model to evaluate the run-out distance exceedance probability of landslides based on the most appropriate model and its associated posterior random variable information. We utilized data from two recent landslides that occurred in Heifangtai Terrace to validate the performance of the proposed model. In addition, we produced a run-out distance exceedance probability curve using the proposed method for a potential landslide in Heifangtai Terrace, in which the sliding volume interval is estimated using the sloping local base level (SLBL) method. In general, this study presents a practical method for landslide run-out distance analyses within a probabilistic framework, aiming to provide support for risk-based decisions. [ABSTRACT FROM AUTHOR]

Due to the huge losses caused by landslides, landslide deformation monitoring has become essential. The change of the tilting angle of the slope surface can reflect the instability process of the landslide. However, there are few studies on the relationship between the instability process of landslides and the tilting angle of the slope surface on the time scale. Therefore, there are even fewer cases in using the inclination angle of the landslide as an early warning method in practice. On August 24, 2018, a wireless tilt sensor network was deployed in the Heifangtai area of Gansu Province in China, to monitor the inclination state of loess landslides to study the relationship between the tilting angle of the slope surface and the landslide instability process. At 4 o'clock on October 5, 2019, the wireless tilt sensor network mentioned above detected a new loess fall landslide. Through the analysis of the monitoring data from the tilting sensor nodes named T3 and T4, we found that the tilting angle of the landslide surface in the pre-sliding stage has significant change compared with the stable stage, which directly verifies that the inclination data can be used for landslide warning. At the same time, we inputted the monitored inclination data into the inclination warning model proposed by Xie et al. (Landslides 17:301–312, 2020) for verification and found that the trend of inclination changes matches the model well. However, the forecast time error is large. Therefore, this paper optimizes the inclination early warning model proposed by Xie. Using the optimized early warning model, the predicted landslide occurrence time based on the data of the T3 node was 0.517 days, which was about 8 h later than the actual landslide that occurred on October 4, 2019, which is an improvement of forecasting. This case serves as an on-site direct evidence to further verify the feasibility of using the landslide body inclination state as a landslide monitoring and early warning parameter which can be promoted and used in practice. [ABSTRACT FROM AUTHOR]

Loess landslides pose significant physical and environmental threats to communities of the Heifangtai Terrace in Gansu Province, China. Estimating potentially affected areas using dynamic numerical simulations provides a foundation for risk assessment and management. However, current studies often use rheological input parameters derived from the back analysis of an individual historical landslide, which requires that the potential landslide is quite similar to the historical landslide to guarantee the accuracy of predictions. We collected data from 20 loess flowslides that occurred from 2015 to 2019 in the Heifangtai Terrace. A friction model embedded in MassFlow was used to simulate run-out behavior. Accumulation depths at multiple control points were used as observation information. A multi-objective optimization back analysis was used to calibrate optimal rheological parameters for each flowslide, yielding a region-specific database of 20 datasets for statistical analyses. Finally, two flowslides that occurred in 2019 were employed as potential landslides to conduct probabilistic run-out predictions based on the database. These predictions agreed well with the observed accumulation areas in both cases, thus validating our method. This database will be useful for future landslide run-out predictions in this area. [ABSTRACT FROM AUTHOR]

On February 26, 2021, the ancient Moli landslide in Guoye town, Zhouqu County, Gansu Province, China, was reactivated. The volume of the reactivated landslide was approximately 2120 × 104 m3, which was classified as a remote accumulation layer landslide in a deep superlarge fault fracture zone. No casualties occurred due to timely warnings. The deformation characteristics and failure mechanisms of the landslide were systematically studied by means of field investigations and engineering mapping, field exploration, deep displacement monitoring, and high-density electrical methods. We found that the geological structure and landform of Zhouqu County are extremely complex. The sliding mass of this landslide was mainly gravelly soil with poor soil mechanical properties. The gravelly clay and phyllite clastic layers were prone to sliding. The landslide as a whole presented the comprehensive characteristics of front edge erosion traction and rear load displacement and was associated with multiple secondary landslides. The Heisongping–Sanjiaoping fault zone of the Bailong River passes through the rear edge of the landslide, and a variety of inducing factors worked together to make the landslide failure mechanism particularly complex. The monitoring and comprehensive control of this kind of landslide should be strengthened. [ABSTRACT FROM AUTHOR]

At 18:00 on July 19, 2019, the ancient Yahuokou flow-like landslide in Dongshan Town, Zhouqu County, Gansu Province, China, was revived. The landslide mass of about 3.92 × 106 m3 was revived step by step, slid down the slope, and finally slipped into the Minjiang river, causing the Minjiang river to become a semi-blocked state, the water level of the river rose, and the riverside road was interrupted. The landslide is 1920 m long, with a height difference of 550 m and an apparent friction coefficient of 0.286. It is a typical push-type large-scale long-striped fault-fractured zone accumulation landslide, which is controlled by the Pingding-Huama fault zone. Under the action of long-term rainfall, the trailing edge of the upper section of the landslide first undergoes slow creep deformation, which eventually leads to the overall instability and decline of the upper section of the landslide, and then loads the upper part of the middle section of the sliding mass, which promotes the instability and decline of the middle section of the sliding mass. Finally, the sliding mass in the middle section exerts a load on the upper part of the sliding mass in the lower section, which revives the sliding mass in the lower section and gradually slides into the Minjiang river. Through field investigation, remote sensing interpretation, and borehole investigation, the basic characteristics and information of landslide deformation and movement are obtained. The limit equilibrium method is used to analyze the revival mechanism and the spring model is proposed to analyze the movement mechanism of the landslide. With the help of DNA-W numerical simulation software, the sliding process of the upper sliding mass is simulated by a frictional rheological model to verify the spring model. The analysis of the dynamic mechanism of the Yahuokou flow-like landslide will help provide a reference for the research on the instability and movement mechanism of the landslide in the Pingding-Huama fault zone, and provide the necessary scientific basis for the prevention and mitigation of landslide disasters. [ABSTRACT FROM AUTHOR]

The Jiangdingya (JDY) ancient landslide is a large-scale landslide located in the Bailongjiang River fault zone, Zhouqu County, Gansu Province. Affected by fault activities, rainfall, river erosion, and human engineering activities, the JDY landslide has been repeatedly reactivated and blocked the Bailongjiang River, causing great disasters. To study the reactivation mechanism of the JDY ancient landslide, based on field geological survey, the centrifuge simulation tests of the landslide body under 10%, 15%, and 20% water content conditions are carried out. The tests show that when the water content is 10%, only a few cracks are generated in the middle and rear parts of the slope by the end of the test, but the landslide is still in a stable state overall. However, when the water content is 15% and 20%, the landslide body is damaged, and the centrifugal acceleration required for slope instability is 100 g and 50 g, respectively. The test analysis shows that the JDY ancient landslide demonstrates composite retrogressive sliding. The deformation starts from the middle and rear parts of the slope, and cracks are generated. Then, the cracks gradually expand to the front edge. Under the river erosion influence of the slope toe, the cracks finally penetrate and cause landslide damage. The deformation process of the landslide body is mainly divided into four stages: ① consolidation; ② deformation initiation (crack formation stage); ③ deformation acceleration (crack acceleration development stage); and ④ instability. The centrifugal simulation tests suggest that the factors for JDY ancient landslide reactivation are mainly affected by rainfall and pore water pressure, as well as the coupling of sliding caused by the erosion of the river front with the movement of the middle and rear parts of the landslide caused by rainfall. At present, the JDY ancient landslide is still in a state of creeping deformation. It is necessary to pay close attention to the development of the cracks at the rear edge of the landslide and strengthen the prevention measures for landslide deformation instability and river blocking disasters. [ABSTRACT FROM AUTHOR]

On October 5, 2021, a small-scale catastrophic loess landslide occurred in Niangniangba town, Tianshui City, Gansu Province in China. The landslide with a volume of approximately 15,360 m3 buried 2 houses and damaged another 2 houses. On the basis of field investigation, unmanned aerial vehicle photography, and numerical simulation, the characteristics and dynamic processes of the Zhongzhai landslide are analyzed, and the potential destructive zone of the unstable loess mass is preliminarily assessed. The Zhongzhai landslide is a typical rainfall–reactivated flow-type loess landslide, and its failure mode is creep-tensile type. The upper sliding mass is the typical retrogressive failure, and the lower sliding mass shows thrust load caused failure. The runout simulation results show that the entire sliding process of Zhongzhai landslide lasted for approximately 35 s, with a maximum velocity of 12 m/s. The maximum travel distance of the sliding mass is 130 m. In addition, the presence of masonry buildings has a great influence on the sliding distance. Simulation results of potential destructive zone of the unstable loess mass show that the travel distance of the unstable loess mass is approximately 250–295 m, the thickness of the deposited mass is approximately 2.7–3.3 m in the potential destructive zone, and the maximum velocity is 28 m/s. This work contributes to improving the understanding of evolution law, dynamic processes, and risk prevention of this kind of landslide in loess plateau areas. [ABSTRACT FROM AUTHOR]

On January 27, 2021, a small-scale loess landslide occurred in Dangchuan Village, Yongjing County, Gansu Province, China. Timely monitoring and warning helped to prevent any casualties. The sliding mass of the Dangchuan landslide fell in two stages with an interval of 24 s and lasted for a total of 31 s. Eventually, the Dangchuan landslide had a descent height of approximately 120 m and a sliding portion stretching approximately 350 m. The landslide volume was approximately 3 × 104 m3. Based on the investigation of different stages of the Dangchuan landslide and the characteristics of the deposition area, the induction of this landslide was attributed to the effect of frozen stagnant water. Following field investigation of the landslide source and crack areas, a potential sliding mass model with a volume of 5 × 104 m3 was obtained via calculation. To predict the disaster scope of potential landslides, we first used DAN3D software to invert this Dangchuan landslide. Then, based on the numerical model parameters obtained from the inversion, the sliding accumulation process of the potential slide mass was simulated. The results showed that the maximum disaster scope of the potential slide mass would be larger than that of the Dangchuan landslide. The new deposit would cover an area of approximately 3.5 × 104 m2, with a thickness in the range of 0–6 m. The new deposition area would expand by approximately 50 m in the long-axis direction compared to the Dangchuan landslide, impacting the houses and roads. The DAN3D prediction results of the disaster scope will help residents in the potential danger zone evacuate in advance, reducing unnecessary damage. [ABSTRACT FROM AUTHOR]

On 27 January 2021, at 21:00 (UTC + 8), a shallow loess landslide occurred in Heifangtai, Yongjing County, Gansu Province, northwest of the Chinese Loess Plateau. Fortunately, the independently developed global navigation satellite system predicted the landslide 7 h in advance. Although farmland and channels were buried and destroyed, no damage has been done to the lives and houses of residents. In order to explore the triggering factors and movement process of the landslide, based on the field investigation, we collected the precipitation and temperature data more than 1 year before the landslide and comprehensively used UAV photogrammetry, numerical simulation, and laboratory test for comprehensive research. It was found that as the temperature rose and freeze–thaw cycles, changes in mechanical properties of loess and unique stratum structure were the main factors triggering the landslide. The rise in temperature led to an increase in groundwater levels, and the strength of soil decreased gradually until shear liquefaction occurred. This landslide caused a substantial topographic change, which provided conditions for slope instability in the future. The process of landslide movement can be divided into three stages: start-up stage, severe sliding stage, and deceleration stage. Simulation results show that the maximum velocity was 22 m/s, and the maximum sliding distance was 393 m. The main movement period was 40 s, and the apparent friction angle was 5°. Finally, this study provides a reliable basis for studying the dynamic process and failure mechanism of loess landslides. [ABSTRACT FROM AUTHOR]

The reactivation of landslides has always been a prominent problem that has endangered town construction and people's safety worldwide. At about 8 a.m. on July 12, 2018, on a mountain near the Bailong River in Nanyu Township, Zhouqu County, Gansu Province, China, a landslide collapse event occurred. About 10,000 m3 of sloped material slid into the Bailong River, with the largest stone reaching 3 m3. As a result, a large number of houses were flooded. Highways and bridges were destroyed. Using field investigations, unmanned aerial vehicle (UAV) photography, InSAR traces, historical records, and multiple remote sensing images, we extracted the landslide's geometry and geomorphic parameters to quantify the characteristics of the Jiangdingya landslide. Based on high-resolution topographic data collected before and after the landslide, the change in the geomorphological factors, geomorphologic stability, and detection of the precursory motion before the landslide failure were analyzed to fully investigate the temporal geomorphological changes. Synthesizing the above research, we discuss the causes of landslide reactivation. The Jiangdingya landslide is a typical ancient landslide formed by the coupling of internal and external dynamics. Rainfall, seismic fault zone activity, human activities, and river erosion were the main causes of this reactivation event. [ABSTRACT FROM AUTHOR]

Loess landslides are a severe engineering geological problem on the Loess Plateau of China. This study relies on interferometric synthetic aperture radar (InSAR) and unmanned aerial vehicle (UAV) photogrammetry techniques to characterise a large-scale loess landslide deformation process in Northwest China. First, a total of 85 Sentinel-1 SAR images acquired from March 2015 to March 2019 were used to detect the spatial displacement and characterise the pattern of deformation from presliding to postsliding. Second, three UAV flight surveys were conducted to reconstruct landslide morphology, identify scarps, cracks and fissures; and generate elevation differences. By comparing these two technologies, we found that InSAR has more advantages in the retrieval of creeping deformation, while UAV data is valuable for detecting large sudden slides. Dynamic deformation zonation maps were generated based on comprehensive analysis, and the deformation pattern of the large loess landslide was deduced. The Hongheyan landslide was induced by heavy rainfall and then gradually became suspended owing to the topography effect. Recently, the western part of the slope showed a clear accelerating trend. This evolution provides comprehensive kinematic information for local governments to make further intensive observations or take effective precautions. [ABSTRACT FROM AUTHOR]

A large-scale loess landslide occurred in Xiaozhuang Village, Changjiahe Town, Tongwei County, Gansu, at approximately 11:00 am on September 14, 2019. A volume of 774 × 104 m3 of a historical sliding mass was reactivated by rainfall and slipped down along a weak interface. The sliding mass accumulated in the valley of the Kushui River, blocking the channel for a distance of ~ 1000 m and destroying several roads and the Yangpo Bridge. This landslide is a typical case of rainfall-induced revival of a historical seismic landslide in the loess region of Northwest China. On the basis of site investigation, Google satellite image, unmanned aerial vehicle photography, and numerical simulation, the deformation and failure characteristics of this landslide are described in detail, and the possible inducing factors and failure mechanism are preliminarily assessed. The Tongwei earthquake in 1718 and the Haiyuan earthquake in 1920 caused the slope to slide multiple times in history. Due to continuous rainfall, the existing softened layer (previous sliding surface) was highly saturated due to the perched water on the top of the relatively impervious mudstone and formed the critical weak zone. Therefore, previous sliding mass in the lower and middle slope was reactivated along the softened layer on September 14, 2019. We suggest that the perched water mainly came from the dominant seepage channels such as sinkholes and underground rivers. In addition, sinkholes on the previous sliding body are the key factors controlling the boundary of the landslide. The movement of the landslide lasted for 12 h, and the main landslide lasted for only 60 s, with a runout distance of 60 m and an average velocity of 5 m/h. Study of the formation conditions and failure mechanism of the Changhe landslide is of great significance for the early identification and risk prevention of this kind of landslide in the loess region of Northwest China. [ABSTRACT FROM AUTHOR]