Geological Disasters Research Articles

Research Trends and ‘Space-Sky-Ground-Underground’ Monitoring Technology Analysis of Landslide Hazard

Landslide is a typical geological disaster distributed in most countries worldwide. Due to long-term natural weathering and human engineering disturbances, the instability of landslides is prone to occur. Once monitoring and disposal methods are implemented inappropriately, they can lead to landslide hazards, seriously threatening the safety of people’s lives and property. For a long time, extensive research on landslide monitoring has been conducted from various countries, providing crucial technical support for reducing the incidence and severity of landslide hazards. However, considering the complex geological conditions of actual landslides and the direct impact of internal and external factors such as rainfall, storms, and earthquakes, the early warning accuracy of landslide hazards is still relatively low. Therefore, based on advanced research achievements, it is significant to carry out research on the current status and development trends of landslide monitoring technology. Based on the Web of Science core database, this study quantitatively analyzes the advanced research achievements in global landslide monitoring in the past decade using bibliometric analysis. A systematic analysis of landslide monitoring technology development is conducted according to each study’s publication time, keywords, and countries. On this basis, a multi-dimensional monitoring system for landslides was proposed, which utilizes the complementary advantages of multi-dimensional monitoring technology to achieve all-round, high-precision, and real-time monitoring of landslides. Finally, taking the Xinpu landslide in the Three Gorges Region of China as an example, a multi-source and multi-field-monitoring experiment was conducted. The application of landslide multi-field-monitoring technology provides an essential reference for monitoring, early warning, as well as the scientific prevention and control of landslide hazard.

Research on the Joint Evaluation of Geological Disaster Susceptibility Based on Fractal Theory and Hierarchical Analysis Method

Research on the Joint Evaluation of Geological Disaster Susceptibility Based on Fractal Theory and Hierarchical Analysis Method

Landslide Distribution and Development Characteristics in the Beiluo River Basin

The Beiluo River Basin, situated in the central region of the Loess Plateau, frequently experiences landslide geological disasters, posing a severe threat to local lives and property. Thus, establishing a detailed database of historical landslides and analyzing and revealing their development characteristics are of paramount importance for providing a foundation for geological hazard risk assessment. First, in this study, landslides in the Beiluo River Basin are interpreted using Google Earth and ZY-3 high-resolution satellite imagery. Combined with a historical landslide inventory and field investigations, a landslide database for the Beiluo River Basin is compiled, containing a total of 1781 landslides. Based on this, the geometric and spatial characteristics of the landslides are analyzed, and the relationships between the different types of landslides and landslide scale, stream order, and geomorphological types are further explored. The results show that 50.05% of the landslides have a slope aspect between 225° and 360°, 68.78% have a slope gradient of 16–25°, and 38.97% are primarily linear in profile morphology. Areas with a high landslide density within a 10 km radius are mainly concentrated in the loess ridge and hillock landform region between Wuqi and Zhidan Counties and in the loess tableland region between Fu and Luochuan Counties, with a significant clustering effect observed in the Fu County area. Loess–bedrock interface landslides are relatively numerous in the northern loess ridge and hillock landform region due to riverbed incision and the smaller thickness of loess in this area. Intra-loess landslides are primarily found in the southern loess tableland region due to headward erosion and the greater thickness of loess in this area. Loess–clay interface landslides, influenced by riverbed incision and the limited exposure of red clay, are mainly distributed in the northern part of the southern loess tableland region and on both sides of the Beiluo River Valley in Ganquan County. These results will aid in further understanding the development and spatial distribution of landslides in the Beiluo River Basin and provide crucial support for subsequent landslide susceptibility mapping and geological hazard assessment in the region.

Dynamic changes and improvement paths of China's emergency logistics response capabilities under public emergencies-research based on the entropy weight TOPSIS method.

Due to global industrialization and urbanization, natural disasters, accidents, and public health emergencies happen frequently. These events cause significant loss of life and property damage to countries worldwide. In the context of frequent public emergencies, enhancing emergency logistics response capabilities is crucial, ensuring rapid supply of rescue materials and support for rescue personnel, thereby saving lives and reducing economic losses. In order to identify the changes and enhancement paths of the emergency logistics response capability of Chinese regions under the shocks of public emergencies, this paper innovatively constructs emergency logistics response capability measurement indicators. This paper uses the entropy weight TOPSIS method and panel quantile regression model to quantify the change and enhancement paths of China's regional emergency logistics response capability under different events. It is found that: (1) The gap in emergency logistics response capability among Chinese regions is widening, with the internal difference in the eastern region higher than that in the west, while the difference in the central region is relatively low. (2) China's emergency management department can effectively transform social logistics into emergency logistics, thereby promoting the improvement of emergency logistics response capabilities. (3) Sudden geological disasters break through the limits of social logistics resources when they cross lower scales, resulting in the failure of emergency logistics response capabilities. This paper expands research on assessing emergency logistics capabilities, addressing issues in existing assessments such as reliance on single indicators and subjective measurement methods. Additionally, it quantifies the dynamic changes in China's regional emergency logistics response capabilities under public emergencies by extending the study of event content, types, and impacts. This enhances discussions on the effects of public emergencies. Finally, from an empirical perspective, the paper explores pathways to enhance regional emergency logistics response capabilities in China. In practice, this paper assists countries worldwide in assessing whether different regions of China can effectively provide emergency support for various resources in direct investments, thus providing a scientific basis for investment decisions.

Experimental and numerical investigations of secondary granular flow

AbstractAmong the geological disasters in the form of granular flow, the secondary slide mass is often neglected, potentially leading to unexpected losses. Results indicate that under conditions of a certain sliding total mass, the secondary granular flow in the deposition area is significantly influenced by pre‐formed deposits when tested in a flow flume. When the initial sliding mass is small and the mass ratio of two slides is less than 12.5%, the secondary sliding mass expands the runout distance, thereby increasing potential harm. To elucidate the interaction between the secondary sliding mass and the previously formed deposition, DEM (the discrete element method) was employed based on experimental tests.. The numerical results show that the previous deposition effectively blocks the secondary granular flow. When the initial sliding mass is small, the front edge of the second slide may overtop the previous deposition, extending the runout distance by impact, extrusion, and pushing. The DEM proves to be a reliable and effective tool for studying the secondary granular flow, revealing complex phenomena and processes that complement experimental research. This study provides valuable references for a more in‐depth understanding of multi‐phase continuous disaster processes.

Multi-hazard direct economic loss risk assessment on the Tibet Plateau

Natural disasters are becoming increasingly regional, frequent, and complex. Semi-quantitative risk assessments based on risk indices or relative risk levels lack quantitative parameters to characterize losses adequately. This study focuses on earthquakes and geological disasters, quantitatively assessing the risk of probable maximum loss (PML) from multi-hazard on the Tibet Plateau (TP) in terms of both absolute and relative values. The results indicate that total PML from multi-hazard on the TP is estimated at 465.5 billion CNY, with a relative value of 5.3%. The total loss value of towns with very high absolute PML is estimated at 254.8 billion CNY, while the relative loss value of towns with very high relative PML is 25.1%. Towns with high absolute value of PML for multi-hazard may have higher fixed asset values, while those with high relative value imply higher vulnerability. Adjusting building structures and reducing the vulnerability of buildings could effectively mitigate the risk of disaster losses caused by multiple hazards.

Experimental study on the dynamic behavior of pile-anchor structures under impact loading of debris flow and rockfall

The pile-anchor structure is widely used in slope/landslide reinforcement, and is also applicable to debris flow and rockfall barriers in mountainous areas. However, the impact behavior of this structure has not been studied. To promote the use of this retaining structure in the prevention of slope geological disasters, this study investigated the dynamic responses and impact behavior of pile-anchor structures through a set of impact experiments, wherein dry granular materials with different particle size and sliding blocks with different masses were adopted to simulate different impact loading scenarios of granular flow and rockfall. The impact pressure on the pile-anchor structure, the seismic signals induced inside the slope during the sliding and impact processes, and the deformation characteristics and failure modes of the piles and anchors were systematically investigated. The results indicate that the peak impact force and intensity of the seismic signal are affected by the particle size of the impact granular materials. As the impact loading of sliding blocks increased, the tensile force of the anchor increased nonlinearly, the distribution pattern of the pile's impact dynamic moment changed, and anchor prestress loss was observed. The preliminary results obtained by this study are expected to provide the theoretical basis for designing relevant barriers in areas prone to debris flow and rockfall, and promote the inclusivity of the impact behavior of slope retaining structures in existing design codes pertaining to retaining structures.

Assessing the strength of deep-sea surface ultrasoft sediments with T-bar penetration: A machine learning approach

With the expansion of marine resource utilization, geological disaster prediction, and ecological protection in deep-sea regions, accurate identification of deep-sea engineering geological environments has become paramount, highlighting the significance of understanding the mechanical characteristics of deep-sea surface ultrasoft sediments (DSUSs). However, DSUSs typically exhibit low strength, high compressibility, and significant fluidity, making sampling for indoor strength testing a challenging task. On-site testing employing a T-bar penetrometer has become increasingly prominent for assessing DSUS strength, but the complexity of influencing parameters limits the application of this valuable method. This study utilizes a validated computational fluid dynamics (CFD) approach to model the complete process of T-bar penetration into a DSUS. The aim is to understand the quantitative effects and corresponding mechanisms of various significant complex parameters, including the undrained shear strength, dimensionless penetration depth, rate effect, and interface contact condition, on the dimensionless penetration resistance coefficient. Additionally, a machine learning model based on the random forest algorithm is introduced to establish a multiparameter evaluation method for the dimensionless penetration resistance coefficient. The findings illuminate the intricate interactions and effective evaluation of these factors when evaluating DSUS strength using a T-bar penetrometer, addressing the above challenges in marine engineering geology and the environment.

DACLnet: A Dual-Attention-Mechanism CNN-LSTM Network for the Accurate Prediction of Nonlinear InSAR Deformation

Nonlinear deformation is a dynamically changing pattern of multiple surface deformations caused by groundwater overexploitation, underground coal mining, landslides, urban construction, etc., which are often accompanied by severe damage to surface structures or lead to major geological disasters; therefore, the high-precision monitoring and prediction of nonlinear surface deformation is significant. Traditional deep learning methods encounter challenges such as long-term dependencies or difficulty capturing complex spatiotemporal patterns when predicting nonlinear deformations. In this study, we developed a dual-attention-mechanism CNN-LSTM network model (DACLnet) to monitor and accurately predict nonlinear surface deformations precisely. Using advanced time series InSAR results as input, the DACLnet integrates the spatial feature extraction capability of a convolutional neural network (CNN), the advantages of the time series learning of a long short-term memory (LSTM) network, and the enhanced focusing effect of the dual-attention mechanism on crucial information, significantly improving the prediction accuracy of nonlinear surface deformations. The groundwater overexploitation area of the Turpan Basin, China, is selected to test the nonlinear deformation prediction effect of the proposed DACLnet. The results demonstrate that the DACLnet accurately captures developmental trends in historical surface deformations and effectively predicts surface deformations for the next two months in the study area. Compared to traditional LSTM and CNN-LSTM methods, the root mean square error (RMSE) of the DACLnet improved by 85.09% and 68.57%, respectively. These research results can provide crucial technical support for the early warning and prevention of geological disasters and can serve as an effective alternative tool for short-term ground subsidence prediction in areas lacking hydrogeological and other related data.

A study of impact of climate change on the U.S. stock market as exemplified by the NASDAQ 100 index constituents

This paper employs an innovative event study methodology to demonstrate the impact of climate change on the NASDAQ index from the unique perspective of extreme weather events. This is achieved through the application of the event study methodology to a total of 526 biological, climatic, geological, hydrological, and meteorological disasters of climate change occurring in the U.S. during the period of 2000–2019. The results of the study demonstrate that: ① it can be generally observed that the five dimensions of climate change have a significant impact on stock returns. ② Empirical evidence indicates that the impact of different climate change dimensions on the return rate of stocks from NASDAQ stocks varies. In contrast, the biological and hydrological dimensions have a significantly negative impact on the return rate of stocks from the NASDAQ index, while the climate dimension has a significantly positive impact on the return rate of stocks from the NASDAQ index. ③ From the perspective of time, the impact of the five dimensions of climate change on the stock yield exhibits certain non-linear characteristics. This can be observed in the phenomenon of shock reversal, which occurs before and after the event.

Spatial Differentiation Characteristics, Driving Mechanisms, and Governance Strategies of Rural Poverty in Eastern Tibet

Rural areas in Tibet, with its complex terrain, fragile ecology, and poor facilities, are subject to a combination of social–ecological system elements, facing the typical risks of recurrent, marginal, and potential poverty. At present, the spatial differentiation and driving mechanism of rural spatial poverty risk in Tibet are not clear, which adversely affects the formulation of differentiated and precise governance strategies. Thus, based on the social–ecological system perspective, 967 poor rural villages in eastern Tibet were taken as an example, using intelligent techniques such as random forest, geographic detector, and multi-scale geographically weighted regression to identify the spatial differentiation characteristics and the driving mechanism of poverty. The results indicated that (1) the high poverty incidence of rural areas in eastern Tibet showed a scattered block distribution, of which approximately 37% of the villages presented a spatial distribution characterised by a high degree of clustering of the high poverty incidence. (2) Topography and the level of public facilities were key factors influencing the poverty levels of rural areas in eastern Tibet, in which the coupling explanatory power between the construction land slope index (CLSI) and several poverty-causing factors was high. (3) Geological disaster, land surface temperature, CLSI, traffic accessibility, livestock resources, cropland per capita, and tourism resources differentially drove the poverty incidence of rural areas in eastern Tibet, forming spatial partitions dominated by the risks of potential, marginal, and recurrent poverty. For different partitions, differentiated governance strategies of upgrading ecological environments, optimising geographical locations, and revitalising social resources were proposed to provide references for solving the problem of relative poverty in the new period.

Urban land subsidence monitoring and risk assessment using the point target based SBAS-InSAR method: a case study of Changsha City

ABSTRACT Changsha City is the political, economic and cultural centre of Hunan Province. In recent years, because of large-scale urban construction and special geological structure, land subsidence has become one of the main geological disasters in Changsha City, which seriously threatens the health of buildings and infrastructure. To solve this problem, this paper monitored the land subsidence in Changsha City from 2015 to 2021 using the Point Target (PT) based Small Baseline Subset InSAR (SBAS-InSAR), revealed the spatial distribution characteristics of land subsidence in the study area, studied the causes of subsidence, and carried out geological disaster risk assessment. The results show that the overall stability of Changsha City is dominated by uneven subsidence. The subsidence areas are mainly distributed in the north of Kaifu District, Moon Island, Malan Mountain Chuangzhi Park and the periphery of the main urban area. The maximum settlement rate is about 87 mm/year, and the cumulative settlement reaches 250 mm. The settlement monitoring results are basically consistent with the actual situation at the same time, which is mainly caused by engineering construction.

A Preliminary Study of Past Geological Disasters in the Trowulan Majapahit Cultural Heritage Area, Mojokerto Regency, East Java

Abstract Numerous sites found buried in the Trowulan Cultural Heritage Area makes the area suspected of being the capital of the Majapahit Kingdom (13-15th century). The condition of the buried site raises an assumption of a past catastrophic event that hit and buried part of Trowulan area, causing the downfall of the Majapahit Kingdom. This assumption is supported by the existence of several books and inscriptions from the Majapahit Kingdom period that record events interpreted as geological disasters. Although there is a lot of evidence, however, what kind of geological disaster that hit the Trowulan area is not known for certain. This study aims to identify what kind geological disasters that buried the Trowulan Capital area based on previous studies and GIS analysis. The results inferred that flash floods and volcanic eruptions contributed to the burial of Trowulan Capital Region, which is supported by the geographical conditions of the capital city of Trowulan where the northern part is a flood plain and the southern part is part of the Jatirejo alluvial fan. Stratigraphic data collection needs to be carried out in the future as supporting evidence to know the detailed sequence of disaster events and the direction of the disaster flow.

The Identification Of Geological Disaster Based On Stratigraphic And Granulometric Data Of Burial Deposit At Majapahit Sites In The Trowulan Area, Mojokerto, East Java

Abstract The abundance of archaeological findings found in damaged and buried conditions in the Trowulan area raises suspicions about the role of geological disasters in the downfall of the Majapahit civilization in the city of Trowulan in the past. This study aims to identify the types and processes of past geological disasters in the Trowulan area based on literature study, stratigraphic data, and granulometry of burial materials at Kumitir Site, Kedaton Site, and Minakjinggo Site. Based on the stratigraphy and granulometry of disaster sediments, there are two types of past geological disasters that struck the Trowulan area, namely earthquake-liquefaction and flash floods. Earthquake-liquefaction disasters are characterized by layers with grain-supported and the presence of collapsed and contorted building structures. On the other hand, flash flood disasters are identified based on layers with matrix-supported compacted material, channeling and fragment imbrication structures, poorly sorting, and subangular-subrounded grain shapes. Based on stratigraphic facies and written records, the disasters that struck Trowulan are identified to have occurred in two periods. The first period includes the Palindu earthquake and Guntur Banyu Pindah flash flood in 1334 AD, while the second period includes the Palindu earthquake in 1450 AD and the Guntur Pawatugunung flash flood in 1481 AD.

Experimental Study on Fracture Toughness of Shale Based on Three-Point Bending Semi-Circular Disk Samples

A large number of construction practice projects have found that there are many joints and microcracks in rock, concrete, and other structures, which cause the complexity of rock mechanical properties and are the main cause of geological or engineering disasters such as earthquakes, landslides, and rock bursts. To establish a rock fracture toughness evaluation method and understand the distribution range of fracture toughness of Longmaxi Formation shale, this study prepared three-point bending semi-circular disk shale samples of Longmaxi Formation with different crack inclination angles. The dimensionless fracture parameters of the samples, including the dimensionless stress intensity factors of type I, type II, and T-stress, were calibrated using the finite element method. Then, the peak load of the samples was tested using quasi-static loading, and the load–displacement curve characteristics of Longmaxi Formation shale and the variation in fracture toughness with crack inclination angle were analyzed. The study concluded that the specimens exhibited significant brittle failure characteristics and that the stress intensity factor is not the sole parameter controlling crack propagation in rock materials. With an increase in crack inclination angle, the prefabricated crack propagation gradually transitions from being dominated by type I fracture to type II fracture, and the T-stress changes from negative to positive, gradually increasing its influence on the fracture. An excessively large relative crack length increases the error in fracture toughness test results. Therefore, this paper suggests that the relative crack length a/R should be between 0.2 and 0.6. The fracture load distribution range of shale samples with different crack angles is 3.27 kN to 10.92 kN. As the crack inclination angle increases, the maximum load that the semi-circular disk shale samples can bear gradually increases. The pure type I fracture toughness of Longmaxi Formation shale is 1.13–1.38 MPa·m1/2, the pure type II fracture toughness is 0.55–0.62 MPa·m1/2, and the T-stress variation range of shale samples with different inclination angles is −0.49–9.48 MPa.

Experimental study on the road performance of molybdenum tailings sand stabilized with cement and fly ash

The large accumulation of molybdenum tailings (MoT) has resulted in a series of hazards, including environmental pollution, damage to water resources, and increased risk of geological disasters. This study employs ordinary Portland cement (OPC) and fly ash (FA) stabilization of MoT sand and seeks the optimal mix ratio through experimentation. The strength properties of MoT sand stabilized with different proportions of OPC and FA are studied and analyzed through unconfined compressive strength tests, splitting tensile strength tests, and splitting rebound modulus tests. Additionally, the microstructure of MoT sand stabilized with OPC and FA is analyzed using scanning electron microscopy (SEM). The results indicate that with an increase in OPC content, the compressive strength, splitting tensile strength, and splitting rebound modulus all increase. With an increase in FA content, the compressive strength gradually increases, while the splitting tensile strength and splitting rebound modulus show a trend of initially increasing and then decreasing. The results show that the optimal mix proportion for OPC and FA-stabilized MoT sand is 7 % OPC content and 15 % FA content. This mixture is suitable for a heavy traffic base of expressways and class I highways, as well as for an extra heavy traffic base of class II and below highways. The research results can provide reference for using OPC and FA stabilized MoT sand as roadbed material.

A dataset of drilling site object detection in underground coal mines

Drilling in underground coal mine is an important measure for dealing with gas, water and hidden geological disasters, which can significantly enhance the effectiveness of disaster prevention and control in coal mining operations. In order to monitor the drilling process in real time and improve drilling efficiency, it is necessary to carry out object detection to identify and locate key targets at the drilling site. Compared with traditional object detection method, deep learning-based object detection method can improve accuracy, timeliness and stability of object detection, but it requires high-quality datasets to perform well. At present, research on object detection in underground coal mine drilling sites mainly relies on small-scale private datasets, which are insufficient for providing necessary or reliable data for deep neural network model training. In this study, we constructed a dataset of drilling site object detection using photos taken by intrinsic safety law enforcement recorders. This dataset is developed through several steps, including data cleaning, data labeling, and expert sampling verification. The mainstream YOLO series object detection model is used for data quality assessment. This dataset comprises 70,948 images from drilling sites under different environmental conditions, covering five categories of objects: gripper, chuck, coal miner, mine safety helmet, and drill pipe. It provides annotated files in PASCAL VOC format. This dataset can provide strong data support for object detection research in underground coal mine drilling sites, and plays an important role in promoting intelligent underground coal mine monitoring and early warning.

Three-Dimensional Geological Modelling in Earth Science Research: An In-Depth Review and Perspective Analysis

This study examines the development trajectory and current trends of three-dimensional (3D) geological modelling. In recent years, due to the rising global energy demand and the increasing frequency of regional geological disasters, significant progress has been made in this field. The purpose of this study is to clarify the potential complexity of 3D geological modelling, identify persistent challenges, and propose potential avenues for improvement. The main objectives include simplifying the modelling process, improving model accuracy, integrating different data sources, and quantitatively evaluating model parameters. This study integrates global research in this field, focusing on the latest breakthroughs and applications in mineral exploration, engineering geology, geological disaster assessment, and military geosciences. For example, unmanned aerial vehicle (UAV) tilt photography technology, multisource data fusion, 3D geological modelling method based on machine learning, etc. By identifying areas for improvement and making recommendations, this work aims to provide valuable insights to guide the future development of geological modelling toward a more comprehensive and accurate “Transparent Earth”. This review underscores the global applications of 3D geological modelling, highlighting its crucial role across various sectors such as mineral exploration, the oil and gas industry, urban planning, geological hazard assessment, and geoscientific research. The review emphasizes the sector-specific importance of this technology in enhancing modelling accuracy and efficiency, optimizing resource management, driving technological innovation, and improving disaster response capabilities. These insights provide a comprehensive understanding of how 3D geological modelling can significantly impact and benefit multiple industries worldwide.

Deep Learning in Rockburst Intensity Level Prediction: Performance Evaluation and Comparison of the NGO-CNN-BiGRU-Attention Model

Rockburst is an extremely hazardous geological disaster. In order to accurately predict the hazardous degree of rockbursts, this paper proposes eight new classification models for predicting the intensity level of rockbursts based on intelligent optimisation algorithms and deep learning techniques and collects 287 sets of real rockburst data to form a sample database, in which six quantitative indicators are selected as feature parameters. In order to validate the effectiveness of the constructed eight machine learning prediction models, the study selected Accuracy, Precision, Recall and F1 Score to evaluate the prediction performance of each model. The results show that the NGO-CNN-BiGRU-Attention model has the best prediction performance, with an accuracy of 0.98. Subsequently, engineering validation of the model is carried out using eight sets of real rockburst data from Daxiangling Tunnel, and the results show that the model has a strong generalisation ability and can satisfy the relevant engineering applications. In addition, this paper also uses SHAP technology to quantify the impact of different factors on the rockburst intensity level and found that the elastic strain energy index and stress ratio have the greatest impact on the rockburst intensity level.

Effects of grassland vegetation roots on soil infiltration rate in Xiazangtan super large scale landslide distribution area in the upper reaches of the Yellow River, China

In order to study the infiltration characteristics of grassland soil in the super large scale landslides distribution area in the upper reaches of the Yellow River, this study selected the Xiazangtan super large scale distribution area in Jianzha County as the study area. Through experiments and numerical simulations, plant roots characteristics, soil physical properties and infiltration characteristics of naturally grazed grassland and enclosed grassland with different slope directions were compared and analyzed, and the influence of rainfall on seepage field and stability of the two grassland slopes were discussed. The results show that the highest soil moisture infiltration capacity (FIR) is found on the shady slope of the enclosed grassland (2.25), followed by the sunny slope of the enclosed grassland (1.23) and the shady slope of the naturally grazed grassland (−0.87). Correlation analysis show that soil water content, root dry weight density, total soil porosity, number of forks and root length are positively correlated with infiltration rate (P＜0.05), whereas soil dry density is negatively correlated with infiltration rate (P＜0.05). The results of stepwise regression analyses show that soil water content, total soil porosity, root length and number of forks are the main factors affecting soil infiltration capacity. And the ability of roots to increase soil infiltration by improving soil properties is higher than the effect of roots itself. After 60 min of simulated rainfall, the safety factors of the shady slopes of naturally grazed grassland and enclosed grassland are reduced by 29.56% and 19.63%, respectively, comparing to those before rainfall. Therefore, in this study, the roots play a crucial role in regulating soil infiltration and enhance slope stability by increasing soil water content, soil total porosity and shear strength while decreasing soil dry density. The results of this study provide theoretical evidence and practical guidance for the effective prevention and control of secondary geological disasters such as soil erosion and shallow landslide on the slope of river banks in the study area by using plant ecological measures.