Landslide Area Research Articles

Assessment of factors causing landslides using the Analytical Hierarchy Process (AHP) method

Landslides are Indonesia's second most common disaster in the last ten years. Landslides cause losses, reaching hundreds of billions and threatening human safety. For this reason, it is necessary to take action to reduce the negative impact of landslides. Physical and non-physical mitigation can occur before, during, and after a disaster. The most essential thing in disaster mitigation is knowing the major factors that cause landslides. This research aims to analyze the major and minor factors that cause landslides using the Analytical Hierarchy Process (AHP) and the Likert scale. Respondents in this research are experts in disasters, especially landslides—respondents from universities in Indonesia, practitioners, and people involved in disaster mitigation. Validity and reliability tests were carried out on each question used in the questionnaire. The research results show that the landslide disaster was caused by a disruption in balance that occurred due to internal and external disturbance factors. The major external factors that cause slope failures are the cutting of hills and changes in land use to built-up areas. In contrast, the major internal factors that trigger landslides are heavy rainfall and steep topographic conditions. The results of this research in the form of weight and scoring values for each factor causing landslides can be used as a reference for mapping landslide areas to identify areas with the potential for landslides.

Identification of sliding surface using electrical-resistivity tomography for landslide mitigation: A case study of the Cibitung Landslide

Landslide mitigation efforts require a knowledge of the geometry and depth of the sliding surface present in a landslide body. Electrical resistivity tomography is the most common geophysical method used in landslide investigation. This paper presents the results of a series of electrical resistivity tomography surveys performed using a dipole-dipole array configuration to identify the sliding surfaces within a landslide body located in the Cibitung landslide area. The ERT images parallel the landslide body suggest that the sliding surface located below the crown is characterized by a bedrock layer with very low resistivity values. This bedrock layer continues down-slope at a maximum depth of 9 m below the ground surface. In contrast, the landslide body is characterized by a higher resistivity value. Based on the interpretation of the ERT images, the landslide involved a non-circular deep sliding surface. The results of this study have been used, in combination with the geotechnical drilling data, to construct the landslide cross-section necessary to analyze landslide stability and subsequently to recommend a landslide stabilization measure.

Research on characteristics and geological genesis of large-scale deep-seated landslide in tuff formation

In engineering practice, engineers generally treated tuff as a lumpy material with a poorly defined laminated structure and a rock group that was not susceptible to slide failure. Most studies of tuff landslides had focused on small clastic landslides in shallow strata with weathering boundaries and lithologic interfaces as slip surfaces. This paper takes a large-scale, deep-seated tuff landslide on the southeast coast of China as the research project. We used borehole TV imaging and exploration tunnels to confirm the material composition and structural characteristics of the tuff stratum and used exploration tunnels to expose the slip soil directly. Microscopic identification, mineralogical composition analysis, zircon U-Pb isotope dating, and Hf isotope analysis of slip soils collected from the exploration tunnels elucidated the geologic background and genesis of the large-scale deep-seated landslides in the tuff stratum. It was found that the formation of a tuff stratum in the landslide area was caused by multi-volcanic orogeny and multi-phase tectonics. The timing of the melting of the original magma from these volcanic events also differs. During these intervals between eruptions, deposition occurred, and this sedimentary material formed the slip soil.

Identifikasi Penyebaran Bencana Longsor Di Kecamatan Sentani Kota, Kabupaten Jayapura

Landslides are natural disasters that can result in loss of life and property. Therefore, it is necessary to carry out inventory research on areas prone to landslides. The model applied to determine the point of distribution of landslide disasters and areas of potential distribution of landslide disasters is a qualitative descriptive spatial method. Several factors that cause landslides are geology, rock properties, stratigraphy, geological structure, level of weathering and seismicity, climate, rainfall, thick soil, solum. , slope topography, vegetation density and human land use. The results of the analysis show that in Jayaura Regency, Sentani District, there are 3 classes of landslide hazard levels, namely not vulnerable, somewhat vulnerable, quite vulnerable, and vulnerable. In general, Jayapura Regency, Sentani sub-district, is quite prone to the spread of landslides, but there are three sub-districts that are vulnerable, namely Hinekombe sub-district, Sentani village, Bart, Sentani sub-district, Sereh village in the middle and Sentani sub-district, Tollan village, 
 
 

Reducing the dynamic impact of a landslide on buildings and transport structures in the village of Toktogul, Uzgen district of the Kyrgyz Republic

In the Kyrgyz Republic, there is a significant increase in landslide activity against the backdrop of ongoing climate change, especially in the southern mountainous regions of the country. The volume of soil during a landslide in this region can reach tens and hundreds of thousands of cubic meters, and in some cases more. The rate of landslide displacement ranges from several meters per year to several meters per second. The purpose of this study is to unload the landslide area to protect the population, roads and other structures of the village of Toktogul, Uzgen district of the Kyrgyz Republic. This landslide area was studied on the basis of field research on the ground and the results of desk work. The sliding of soil masses in the area can cause destruction and debris of residential and administrative buildings, roads and power lines, as well as injury and death. Considering the equilibrium of the system of forces acting on the subsidence soil mass of the slope section and analyzing them, measures for unloading the landslide body in this section are proposed. The proposed longitudinal profiles of drainage channels to reduce the moisture content of subsidence soil and transverse profiles of developed soil to reduce the weight of subsidence soil are presented. Based on the results of processing research data and analysis, it is recommended to reduce the weight of unstable (subsidence) soil by stepwise development along the slope of the site and transporting it up to 5 km for subsequent brick production. It is also recommended to protect subsidence soil from waterlogging by installing drainage channels. Based on the results of the research, a real project was developed to protect the site from landslides near the village of Toktogul. The proposed measures make it possible to reduce the risk of a landslide in the area under consideration using methods and technical means that are inexpensive and accessible to government agencies and local administrations.

Hybrid Integration of Bagging and Decision Tree Algorithms for Landslide Susceptibility Mapping

Landslides represent a significant global natural hazard, threatening human settlements and the natural environment. The primary objective of the study was to develop a landslide susceptibility modeling approach that enhances prediction accuracy and informs land-use planning decisions. The study utilized a hybrid ensemble-based methodology to improve prediction accuracy and effectively capture the complexity of landslide susceptibility patterns. This approach harnessed the power of ensemble models, employing a bagging algorithm with base learners, including the reduced error pruning decision tree (REPTree) and functional tree (FT) models. Ensemble models are particularly valuable because they combine the strengths of multiple models, enhancing the overall performance and robustness of the landslide susceptibility prediction. The study focused on Yanchuan County, situated within the hilly and gully region of China’s Loess Plateau, known for its susceptibility to landslides, using sixteen critical landslide conditioning factors, encompassing topographic, environmental, and geospatial variables, namely elevation, slope, aspect, proximity to rivers and roads, rainfall, the normalized difference vegetation index, soil composition, land use, and more. Model performances were evaluated and verified using a range of metrics, including receiver operating characteristic (ROC) curves, trade-off statistical metrics, and chi-square analysis. The results demonstrated the superiority of the integrated models, particularly the bagging FT (BFT) model, in accurately predicting landslide susceptibility, as evidenced by its high area under the curve area (AUC) value (0.895), compared to the other models. The model excelled in both positive predictive rate (0.847) and negative predictive rate (0.886), indicating its efficacy in identifying landslide and non-landslide areas and also in the F-score metric with a value of 0.869. The study contributes to the field of landslide risk assessment, offering a significant investigation tool for managing and mitigating landslide hazards in Yanchuan County and similar regions worldwide.

Identifying recurrent and persistent landslides using satellite imagery and deep learning: A 30-year analysis of the Himalaya

This paper presents a remote sensing-based method to efficiently generate multi-temporal landslide inventories and identify recurrent and persistent landslides. We used free data from Landsat, nighttime lights, digital elevation models, and a convolutional neural network model to develop the first multi-decadal inventory of landslides across the Himalaya, spanning from 1992 to 2021. The model successfully delineated >265,000 landslides, accurately identifying 83 % of manually mapped landslide areas and 94 % of reported landslide events in the region. Surprisingly, only 14 % of landslide areas each year were first occurrences, 55–83 % of landslide areas were persistent and 3–24 % had reactivated. On average, a landslide-affected pixel persisted for 4.7 years before recovery, a duration shorter than findings from small-scale studies following a major earthquake event. Among the recovered areas, 50 % of them experienced recurrent landslides after an average of five years. In fact, 22 % of landslide areas in the Himalaya experienced at least three episodes of landslides within 30 years. Disparities in landslide persistence across the Himalaya were pronounced, with an average recovery time of 6 years for Western India and Nepal, compared to 3 years for Bhutan and Eastern India. Slope and elevation emerged as significant controls of persistent and recurrent landslides. Road construction, afforestation policies, and seismic and monsoon activities were related to changes in landslide patterns in the Himalaya.

Stability Analysis of a Rocky Slope with a Weak Interbedded Layer under Rainfall Infiltration Conditions

Landslides not only cause great economic and human life losses but also seriously affect the safe operation of infrastructure such as highways. Rainfall is an important condition for inducing landslides, especially when a fault and weak interlayer exist on the slope, which can easily transform into a landslide and cause instability under the action of rainfall. To explore the effects of a soft interlayer, a fault, and extreme rainfall on slope stability, this paper takes the landslide on the right side of the G104 Jinglan Line in Shengzhou City, Shaoxing City, Zhejiang Province, China, as an example. The cause, failure mechanism, and characteristics of the landslide are analyzed through field investigation and borehole exploration in the landslide area. The slope is simulated by numerical analysis, and the stability of the landslide under natural conditions and extreme rainstorm conditions is calculated using the strength reduction method. The stability of the slope before and after treatment is compared, and the effectiveness of the treatment measures is verified by combining the field monitoring data. At the same time, the complex geological structure and rainfall are considered to have been the main factors leading to the G104 landslide. Near the fault, the weak interlayer of the landslide was easily disturbed, the deformation trend of the deep displacement was consistent with rainfall, and the axial force of the anti-slide piles at the weak interlayer was correspondingly large. For a wedge rock slope, “excavation unloading” and “prestressed anchor + prestressed anchor cable + anti-slide pile” are effective treatments. This paper reveals the effects of a weak interlayer, a fault, and strong rainfall on a rocky high slope, providing predictions of instability modes and time evolution patterns for similar complex geological slopes under rainfall infiltration conditions and providing references for their treatment measures.

Exploring the Potential of Geotourism with a Focus on Kahagolla Landslides Area in Sri Lanka


 
 
 
 Geotourism is a new type of tourism based on geological features. As such, the primary goal of this research is to identify the possibility of converting protected natural hazard areas into profitable Geotourism sites. A geologic hazard visible in the geological environment is a natural event that occurs within the earth's crust which poses a threat to life and property. One such example is landslides. The Kahagolle landslide area is 3.5 ha in size and landslide prevention and mitigation activities have been conducted here as part of a Japan International Cooperation Agency (JICA) project costing millions of rupees. The attractiveness and profitability of this location lie in the availability of different landslide mitigation methods within a single area. Located along the Beragala-Hali Ela highway (A16) in close proximity to Haputale and Bandarawela, the site has the potential to attract many domestic as well as international tourists who visit the central hills of Sri Lanka. This was an inductive study using field observations as primary data, and content analysis of published papers and NBRO documents that have been used as secondary, qualitative data. The main conclusion drawn based on the results is that there certainly is a possibility of improving this area as a Geotourism site aimed at foreign and local tourists mainly for educational purposes. The recommendation is to build an information center with the capacity to raise awareness and enhance knowledge about the history of this landslide, the geological quality of the area along with details of the mitigation project. As such, tickets could be issued, and the site arranged into zones from top to bottom while the methods used could be shared with visitors.
 Keywords: Geotourism, Landslides as tourist sites, Mitigation activities
 
 
 

Validation of Unmanned Aerial Vehicle Photogrammetry for Landslide Mapping

Unmanned Aerial Vehicle (UAV) photogrammetry offers quick and effective landslide monitoring. UAV named Polines 01-GD has been developed for photogrammetry. The UAV is designed flexibly in its gimbal to change the camera accordingly. However, UAV validation is needed to evaluate the quality of the device. This study aims to validate the performance of UAV Polines 01-GD for photogrammetry from quantitative and qualitative analysis. The quantitative analysis was performed by RMSE and area accuracy in m2 with the reference DJI Phantom 4 Pro. Meanwhile, the qualitative analysis was done using the DEM (Digital Elevation Model) result. 3D Ground Control Points (GCPs) size 2 m x 2 m were used and placed in the landslide area, UNNES park, Semarang. The camera assembled for an experiment in Polines 01-GD is GoPro Hero 3. The results show that the RMSE of Polines 01-GD is 0,0000234193, and the area accuracy to the real measurement of GCP is 97,8%. The results of landslide indicated by the data was taken in March 2022 compared to the first flight on August 2021, showing landslides in 79.4 m and 60.3 m. Even so, the DEM of DJI Phantom 4 Pro result is clearer than Polines 01-GD. In conclusion, UAV Polines 01-GD can be used for photogrammetry. However, the flight time can be a challenge for future research as Polines 01-GD can only fly in 15 minutes, which is half of DJI Phantom 4 Pro.

Mapping Landslide Vulnerability using Machine Learning Approach along the Taba Penanjung-Kepahiang Road, Bengkulu Province

Landslides occur when masses of rock, debris or soil move due to various factors and processes that cause land movement. The Taba Penanjung-Kepahiang route is one of the areas in Bengkulu Province that is highly prone to landslides. This causeway is the only fastest land route connecting the Bengkulu-Kepahiang area. In recent years, the road area has often been cut off due to landslides and fallen trees, which have caused road access to be cut off and obstructed and claimed lives. This study uses a Machine Learning (ML) and GIS approach with Variable Frequency Ratio using 16 independent factors obtained from the spatial database and DEM, which correlate with landslide events. This research aims to gain an in-depth understanding of the factors that cause landslides. In addition, the research focus is the development of a Disaster Mitigation Model to design and implement effective strategies to reduce the risk and impact of landslide disasters through in-depth analysis The dependent factor is the location of the landslide from the historical landslide area for the last five years, with a distribution of 70/30%. Furthermore, frequency ratio is used to analyze the correlation between conditioning factors and historical landslides. Then, the independent and dependent factors were normalized to create a landslide susceptibility map. Frequency Ratio (FR) indicates the likelihood of an event occurring, with drainage density (FR= 0.69), shear wave velocity (Vs30) (FR= 0.66), slope (FR= 0.60), and rainfall (FR= 0.55). The output of the processed data is in the table below.

A novel landslide susceptibility prediction framework based on contrastive loss

ABSTRACT Recently, the positive unlabeled (PU) learning algorithms have proven highly effective in generating accurate landslide susceptibility maps. The algorithms categorize samples exclusively into positive samples (landslides) and unlabeled samples for training, eliminating random or subjective selection of non-landslide samples. However, existing PU learning algorithms face limitations in capturing correct negative samples in multi-genesis landslide areas, leading to lower prediction accuracy. To address this issue, the PU-pullbaggingDT algorithm was proposed in this study. This integrated method combines the strengths of two techniques: the superior ranking performance of the PU-baggingDT algorithm and the low bias of the contrastive learning approach. The contrastive learning introduces a new contrastive loss of PU learning (PUpull loss), which pulls the distance of similar landslide samples in the projection space closer based on the validation accuracy threshold, without the need for data augmentation and class probability. The PUpull loss relaxes the tightness toward unlabeled samples, reducing the impact of incorrectly defined non-landslide samples on prediction results in multi-genesis landslide areas. The proposed algorithm outperforms existing PU-learning and machine learning methods (support vector machine, decision tree, logistic regression, AdaBoost, and XGBoost) with random selection of negative samples for predicting landslide susceptibility in China’s Zigui County, as demonstrated by comprehensive evaluation metrics. The landslide susceptibility mapping utilizes equal interval division and ranking, achieving approximately a 90% landslide percentage in areas with very high and high susceptibility in Zigui County. This demonstrates the capability of the proposed algorithm to effectively predict landslide susceptibility in complex geological settings.

Pembuatan Peta Resiko Bencana di Desa Kubang Tangah Kota Sawahlunto dengan Metode Arc Toolbox

Landslide movement is the activity of a balance disturbance process that causes the movement of masses of soil and/or rock from higher to lower areas. The cause of landslides is that the driving force on the slope is greater than the resisting force. Several factors cause landslides such as rainfall, steep slopes, soil density, rock type, land use and vibration. Sawahlunto City is one of 19 cities/regencies in West Sumatra Province that has a high level of vulnerability to landslides. Areas prone to landslides can be identified by utilizing remote sensing data and geographic information systems. This service is carried out by making maps of areas prone to landslides using parameters that cause landslides, including rainfall, soil type, height, slope and land use. These parameters will be processed and analyzed with the help of the ArcToolbox method, where ArcToolbox can be used to detect landslide areas in Kubang Tangah Village. The analysis process is carried out by using the spatial analysis tools feature found in ArcGIS software. Community service produces a slope map that can illustrate the vulnerability of landslides. Obtain results in the form of a landslide vulnerability level map which has 4 vulnerability classes, including non-prone vulnerability class, low vulnerability class, medium vulnerability class, and high vulnerability class.

Characterization of the Ngouache Landslide by Geotechnical Survey (Bafoussam, Cameroon)

The heavy rainfall during the night of October 28-29, 2019, caused a landslide in the Ngouache 4 neighborhood in Bafoussam in the West Cameroon region. This landslide caused 43 deaths, several missing persons and the destruction of several houses and plantations. The present investigation attempts to find the causesof this landslide. First, the landslide area was identified and heavy dynamic penetrometer surveys were conducted. Next, intact and reworked samples were taken and, finally, slopes were measured on the slide area to determine the soil parameters. The results of the heavy dynamic penetrometer showed the presence of altered clay layers which, when saturated, exert hydrostatic pressure and unbalance the soil. The granulometric analysis noted a soil with more than 50% of grains of ϕ>80µm with liquidity limits between (50-65.3%), a consistency index between (1.01-1.24), a low cohesion between (0.22-0.30 bars) for a high internal friction angle (20.72°-23.86°), slopes between 48° and 56° and a degree of saturation Sr between (80.5° and 139.9°). These characteristics associated with the large water columns of the night of October 28 to 29, 2019 demonstrated that the water had exerted a hydrostatic pressure having made the clay material reach the limit of plasticity to the creep and raised the level of the water table. Thistherefore promoted the saturation of the substrate yet the increase in the water content reduces the cohesion of the materials and that triggered the saturation at the origin of this deadly slide. The results of the present research may help the public authorities in the decision making regarding the characterization and the securing of risk zones.

Vegetation Effects on Phosphorus Runoff from Headwater Catchments in a Cool-Temperate Region with Landslides, Northern Japan

Forest vegetation and soils in headwaters can control runoff and surface erosion. However, it remains unclear how vegetation affects nutrient exports from cool-temperate forest headwaters during intense rain events that transport sediment-associated nutrients, such as phosphorus (P). To clarify this, we targeted an upstream landslide area and analyzed P contents in surface soils and total P (TP) in stream water of the undisturbed (UF) and landslide-bearing forest (LB) catchments. The soil P content was higher in the UF catchment than in the LB catchment, but differences in the average TP concentration and load during low flows between these catchments were not significant. Conversely, the overall runoff and the TP load were three and ten times higher in the LB catchment than in the UF catchment, respectively, during a rain event with daily precipitation of 49 mm, despite the soil P content being much lower in the LB catchment. Particulate P (PP) accounted for more than 90% of the TP load during the rain event in the LB catchment, whereas dissolved P accounted for more than 80% of the TP load in the UF catchment. Therefore, soil surface mobility strongly affected P transport in the forest catchments. Our study suggests that vegetation not only reduces PP loads by controlling runoff, but also influences stream P forms in cool-temperate forests.

Landslide Mapping and Causes of Landslides in the China–Nepal Transportation Corridor Based on Remote Sensing Technology

The China–Nepal Transportation Corridor is vital to the country’s efforts to build a land trade route in South Asia and promote the Ring-Himalayan Economic Cooperation Belt. Due to the complex geological structure and topographical environment of the Qinghai–Tibet Plateau, coupled with the impact of climate change, the frequent occurrence of geological disasters has increased the operational difficulty of the China–Nepal Highway and the construction difficulty of the China–Nepal Railway. However, to date, there has been no systematic study of the spatial distribution of landslides along the entire route within the area, the factors influencing landslides at different scales, or the causes of landslides under different topographic backgrounds. There is an even greater lack of research on areas threatened by potential landslides. This study comprehensively applies remote sensing, mathematical statistics, and machine learning methods to map landslides along the China–Nepal transportation corridor, explore the influencing factors and causes of different types of landslides, and investigate the distribution characteristics of potential landslides. A total of 609 historic landslides have been interpreted in the study area and were found to be distributed along faults and locally concentrated. The strata from which landslides develop are relatively weak and are mainly distributed within 2 km of a fault with a slope between 20° and 30°. The direction of slope for the majority of landslides is south to south-west, and their elevation is between 4000 and 5000 m. In addition, we discovered a power law relationship between landslide area and volume (VL = 2.722 × AL1.134) and determined that there were 47 super-large landslides, 213 large landslides, and 349 small and medium-sized landslides in the area, respectively. Slope is the most significant influencing factor for the development of landslides in the area. Apart from slope, faults and strata significantly influence the development of large and medium-small landslides, respectively. We have identified 223 potential landslides in the region, 15 of which directly threaten major transport routes, mainly in the Renbu Gorge section of the China–Nepal Highway and the proposed China–Nepal Railway section from Peikucuo to Gyirong County. In addition, we also discussed the causes of landslides within three geomorphic units in the region. First, the combined effects of faulting, elevation, and relatively weak strata contribute to the development of super-large and large landslides in the Gyirong basin and gorge. Second, the relatively weak strata and the cumulative damaging effects of earthquakes promote the development of small and medium-sized landslides in the Xainza-Dinggye rift basin. Third, under the combined effect of the hanging wall effect of thrust faults and the relatively weak material composition, landslides of various types have developed in the Nagarzê mountain. It is worth noting that potential landslides have developed in all three geomorphic units mentioned above. This study provides data and theory to assist in the accurate mitigation and control of landslide hazards in the corridor.

Analysis of the effectiveness of landslide stabilization in a near-dam reservoir area

The geological conditions of the landslide area in a near-dam reservoir area of a water conservancy hub project are complicated, and the stability problem of the landslide body is prominent, which is not only directly related to the safety of the adjacent office building and highway, but also poses a threat to the normal operation of the water conservancy hub. According to the latest geological data of the landslide area, the results of the stability calculation of the landslide body are analyzed, and the reinforcement design scheme of circular chair type anti-slide piles & prestressed anchor cables is proposed for the landslide body to solve the problem of anti-slide stability of the landslide body. Numerical analysis results show that: the safety factor under each working condition after reinforcement is within the permissible range and meets the relevant normative requirements, the landslide body has good control effect on deformation after reinforcement, and the reinforcement measures can provide certain reference value for the design and construction of similar projects.

Interaction of landslide spatial patterns and river canyon landforms: Insights into the Three Parallel Rivers Area, southeastern Tibetan Plateau

The interaction and mechanism of landslide spatial patterns and river canyon landforms are significant for understanding geomorphic evolution in intensive tectonic alpine environments. This study focuses on the Three Parallel Rivers Area (TPRA) in the southeastern Tibetan Plateau encompassing three parallel rivers (the Nujiang, Lancang, and Jinsha Rivers), to examine the synergistic evolution of geomorphic features and landslides. The analysis revealed a pattern of landslide aggregation in the river valley characterized by the sequence Nujiang > Lancang > Jinsha Rivers. This pattern aligns closely with the distribution of geomorphic indices (local relief, surface erosion index, and threshold slope gradient) in the valleys. As local relief, normalized surface erosion index and normalized threshold slope gradient increase, the mean values of normalized landslide area density (NLAD) rise from around 0.11 to 0.39, 0.16 to 0.48, and 0.10 to 0.21, respectively. Concurrently, the mean values of normalized frequency of landslide dams (NFLD) increase from around 0.05 to 0.24, 0.12 to 0.22, and 0.02 to 0.17, respectively. Additionally, knickpoints could induce upstream suppression and downstream promotion of landslides showcasing the feedback of landslides on the valley landscape. Our findings indicate that the landform formation process in the southeastern Tibetan Plateau orogen is intricately linked to a substantial landsliding response and the observed mass movements vividly mirror the landform formation pattern. These results hold potential implications for understanding the dynamic equilibrium between uplift and surface erosion in the region. This study enhances our understanding of the interaction and mechanisms of landslides and valley landforms.

Copula-Based Probabilistic Hazard Assessment Model for Debris Flow Considering the Uncertainties of Multiple Influencing Factors

This paper proposes a probabilistic hazard assessment model for debris flows considering the uncertainties of multiple influencing factors based on copula approaches. Fifty-nine rainfall-induced debris flows occurred between 2001 and 2009 in Taiwan are taken as an illustrative example to validate the proposed approaches. A copula-based probabilistic model is developed to model the joint probability distribution of debris-flow volume V and its influencing factors (e.g., rainfall intensity, RI and landslide area, AL). The developed model is then used to make probabilistic prediction of debris-flow volume for a specific hazard level, and compared with the empirical approaches. The proposed probabilistic model is also used to develop the exceedance probability charts of quantities for a specific debris-flow basin. Results show that the developed V–RI–AL probabilistic model can provide reasonable estimates of debris-flow volume in Taiwan for a specific probability level of 0.94, and show better predictive performance than the empirical relationships by using an independent debris-flow dataset in Taiwan for validation. The developed multivariate joint probabilistic model can also provide the exceedance probability of debris flows through considering the uncertainties of debris flow and its influencing factors, providing a preliminary reference for hazard assessment of the debris flows.

Landslide development model based on tree-ring data and quantification of the magnitude of landslide movements

Analysis of landslide events by studying anomalies in tree-ring series of disturbed trees provides unique data on past landslide behaviour. However, a comprehensive spatio-temporal model of landslide evolution using dendrogeomorphic data has not yet been constructed. In terms of determining landslide hazard, one of the key issues, besides the frequency of movements, is their magnitude. Thus, this study is aimed at constructing a model of landslide area development including quantification of landslide displacements. Moreover, not only standard macroscopic growth disturbance but also quantitative anatomical parameters of tree rings were used as a basis for these objectives. The research was carried out on a landslide of the Váh river bank (Slovakia) using data from 32 disturbed black locust (Robinia pseudoacacia L.) individuals. Anatomical analysis revealed a reduction in the vessel lumen area in response to landslide movements. The response was associated with tension wood formation or damage to the tree root system. The reconstructed chronology of landslide movements revealed the main phase of landslide in 2017 and its subsequent evolution. Based on the chronological information and the morphology of the landslide body, a spatio-temporal model of the landslide evolution from the initial slope failure to the present was constructed. The model showed the interrelationships between vertical displacement of the main block, compression and tension deformations within the landslide body, and lateral erosion of the landslide toe by the river. Quantification of the magnitude of landslide displacements was realized from exposed roots in tension cracks but also from the ruptured tree trunk. The limitations and advantages of both approaches are discussed.