Landslide-induced Debris Flows Research Articles

Travel distance estimation of landslide-induced debris flows by machine learning method in Nepal Himalaya after the Gorkha earthquake

Debris flows are more likely to be triggered in the earthquake-strike areas with a widespread presence of unstable slopes, causing severe casualties and changing the surrounding natural topography. In such scenario, estimating the travel distance of debris flows becomes crucial to understand the hazardous areas. Therefore, a hybrid machine learning model (GA-XGBoost) was employed to achieve a reliable estimation of debris-flow travel distance. This model was applied to the Nepal Himalayas, the site of the 2015 Gorkha earthquake. We selected four geomorphological factors for travel distance estimation. They are the volume of failure mass (VL), the height difference between the material source center and end point of movement mass (H), the mean gradient of the travel path (J), and the mean curvature of the travel path (C). Furthermore, to eliminate the noise information and enhance stability of input data, a principal component analysis (PCA) was used to generate three principal components (PC1, PC2, and PC3) from the selected factors to serve as input variables of model development. The performance of this model was evaluated using the assessment indexes, resulting in a mean absolute percentage error (MAPE) of 8.71%, a root mean square error (RMSE) of 144.3 m, and a mean absolute error (MAE) of 86.1 m. Four empirical approaches were also introduced for comparison analysis. Our proposed model has proven to be superior and effective, as the estimated results closely match the actual values. All the results affirm the suitability of our developed model for estimating the travel distance of landslide-induced debris flows following a strong earthquake.

Preliminary analysis of the mechanism in the July 16, 2022 Gaojiashan cascading hazard: a landslide-induced debris flow in Southwest China

Preliminary analysis of the mechanism in the July 16, 2022 Gaojiashan cascading hazard: a landslide-induced debris flow in Southwest China

Landslide-induced debris flows and its investigation using r.avaflow: A case study from Kotrupi, India

Landslide-induced debris flows and its investigation using r.avaflow: A case study from Kotrupi, India

Dynamic characteristics and erosion effect of a landslide-induced debris flow which occurred in Pingwu, southwest China

Dynamic characteristics and erosion effect of a landslide-induced debris flow which occurred in Pingwu, southwest China

Formation mechanism and quantitative risk analysis of the landslide-induced hazard chain by an integrated approach for emergency management: A case study in the Bailong River basin, China

The landslide–debris flow–river blockage hazard chain is one of the most common types of geological hazard chain in mountainous areas, seriously threatening human life and property across an extensive geographical area. The development of approaches for the rapid investigation and prediction of multi-hazard chains can play a significant role in reducing the number of casualties and economic losses. Here, taking the Lijie landslide–debris flow–river blockage in the Bailong River basin as a case study, we used remote sensing methods, geophysical technology, numerical simulations and empirical formulas to develop an integrated approach for analyzing the mechanisms, multi-hazard prediction and quantitative risk assessment induced by this geological hazard chain. The reactivation process of the Lijie landslide is composite retrogressive sliding. The steep slopes and highly fractured bedrock with low strength are the principal internal factors, and heavy rainfall in 2020 and spring freeze–thaw effect are the principal triggering factors. The deposited landslide material is eroded and transformed into a channel-type debris flow under high rainfall conditions. The steep terrain and abundant fine-grained material provides favorable conditions for a viscous debris flow with a long runout, which is usually followed by secondary disasters associated with river blockage. Our results indicate that under rainfall conditions with a 100-year return period, the Bailong river will be completely blocked by the landslide-induced debris flow. And there will be an estimated 5.84 million CNY of economic losses caused by the multi-hazard chain, which is 2.6 times the losses directly caused by the landslide. Our integrated approach is practicable in an emergency context and useful for local administrators to rapidly develop strategies for multi-hazard chain prevention and mitigation, based on information about the transformation mechanisms of the multi-hazard chain, potential hazard-affected areas, damaged degree of elements at the risk, and incurred economic losses.

Analyzing landslide-induced debris flow and flow-bridge interaction by using a hybrid model of depth-averaged model and discrete element method

Analyzing landslide-induced debris flow and flow-bridge interaction by using a hybrid model of depth-averaged model and discrete element method

Properties of debris flow deposits in Masamba, South Sulawesi, Indonesia

On 13 July 2020, a huge landslide-induced debris flow struck Masamba city and its vicinity, providing a massive amount of sedimentation materials. The landslide-induced debris flow was triggered by heavy rainfall, causing damages such as life and property losses, traffic disruption. Landslide-induced debris flow is a sudden natural hazard in mountain regions characterized by fast velocity, huge impact area, large scale, and often causes disastrous accidents. This study aims to investigate the properties of the debris flow materials including the soil size distribution, density, shear strength and bearing capacity. The results showed that the sedimentation material at landslide sites containing a large amount of sand which is classified as a poorly graded sand (SP). The engineering properties such as density, cohesion, internal friction angle and the value California Bearing Ratio (CBR) were also discussed.

Discussions on the transformation conditions of Wangcang landslide-induced debris flow

On August 14, 2020, it occurred a landslide-induced debris flow in Wangcang County, Sichuan Province, Southwest China, three people killed, and two houses destroyed. Behaved as a typical geohazard chain, it originated from a rockslide in marlstone, controlled initially by structural planes in rock mass, and evolved into a debris flow through successive geophysical process. This debris flow reached a run-out distance of 2050 m in the horizontal and 628 m in vertical direction. Remote sensing analysis, field survey, and laboratory tests were conducted to investigate its failure mechanism and dynamic characteristics. The results found that the source zone in the gully was 16.32 × 103 m2, with a volume of 317.52 × 103 m3. Interbedded marlstone with dense structural planes was one of controlling factors for the landslide failure. The continuous rainfall up to 315 mm during the previous 24 days and 32 mm at the date before the incident directly motivated rock slope failure. The contributions of topography, rock fragmentation, entrainment, and flow discharge for this process were discussed. It is found that changes in slope from 11° to 40° provided tremendous potential energy for the rock mass sliding with high speed and then disintegrating in traveling. Entrainment in the channel increased the fine content of the moving rocky mixture. In addition, the flow discharge changed the rheological properties of the mixture by adding seepage. These factors significantly affected the transformation process. Notably, the turning relief or confluence site may be accelerating this process. This research may provide references for further research on geohazard chains.

The mechanism of landslide-induced debris flow in geothermal area, Bukit Barisan mountains of Sumatra, Indonesia

Landslides frequently occur in Indonesia, especially in the geothermal areas located on Sumatra's mountainous island. On April 28, 2016, around 04:30 Western Indonesia Time, a landslide-induced debris flow occurred in Lebong District, Bengkulu Province, Indonesia. The source area of the landslide was located at Beriti Hill on the Bukit Barisan Mountain Range. It resulted in 6 fatalities and damage to infrastructures such as geothermal facilities, roads, water pipes, houses, and bridges. Subsequent landslides and debris flows occurred on April 30, May 2, and 3, 2016. Therefore, this study aims to examine the mechanism and to know the most significant contributing factor to the Beriti Hill landslide. Field investigation, soil sampling, XRD analysis, and Lidar analysis were carried out in the research. Beriti Hill is a geothermal area with many manifestations and is composed of volcanic rocks. Alteration processes produced a thick layer of soil from volcanic rocks. The thick soil dominated by clay minerals and steep slopes is the dominant controlling factor of a landslide, triggered by high rainfall intensity. Increasing water saturation in the landslide material due to high rainfall is the most contributing factor to the developing debris flow from the landslide. Debris flows are recurring events based on the Air Kotok river's stratigraphic data downstream of the landslide area. The debris flow material is toxic due to the low pH from the geothermal process. Therefore, the alluvial fan deposit area from Beriti Hill debris flow is a hazard zone and unsuitable for settlement and agriculture. This research shows that a landslide mechanism in a geothermal area was controlled by clay mineral presence due to the alteration process. The future of landslide risk assessment in the geothermal area can be considered by detailing clay type and their characteristic that significantly contributes to debris flow.

Evaluating Factors for Controlling Sediment Connectivity of Landslide Materials: A Flume Experiment

Connectivity of landslide sediment to and within fluvial systems is a key factor affecting the extent of mobilization of hillslope material. In particular, the formation of landslide dams and the transformation into landslide-induced debris flows represent “end members” of landslide sediment mobility. To quantify sediment connectivity, we developed a two-segment flume representing tributary inflow and the main channel. Mobility of sediment was examined by combinations of various topographic factors, such as tributary inflow angle (0 to 90° in 30° increments) and main channel gradient (10° and 15°), as well as water content of sediment (0 to 100% in 20% increments). We also examined differences of mobility among sediments derived from various lithologies (sand and shale, pyroclastic sediment, weathered granite, and weathered sedimentary rock). Mobility of sediment differed, depending on the water content of sediment, particularly less than saturation or greater than saturation. When all types of unsaturated landslide sediments entered the channel at inflow angles of 60° and 90°, substantial deposition occurred, suggesting the formation of landslide dams. At low inflow angles (0° and 30°) in a steep channel (15°), >50% of landslide sediment was transported downstream, indicating the occurrence of a debris flow. The amount of sediment deposited at the junction angle was greater for pyroclastic sediment followed by weathered granite, weathered sedimentary rock, and finally, sand and shale. Our connectivity index suggests that a threshold exists between landslide dam formation and debris flow occurrence associated with topographic conditions, water content, and types of sediment.

Viscous Elastoplastic SPH Model for Long-Distance High-Speed Landslide

In the landslide-induced debris flow problem, the soil slope experiences three stages: slope instability, debris flow and deposition. This study develops a three-dimensional smoothed particle hydrodynamics model which adopts elastoplastic viscous constitutive relation to simulate this complex process. The Drucker–Prager model with nonassociated plastic flow rule is implemented for slope instability and deposition and constant viscosity is used for propagation stage. The model is validated with laboratory dry-granular dam-break experiments. Good agreements are found between the simulated results and the laboratory data on both the shape evolution and the velocity field. Then, we use the model to study the Yigong avalanche after detailed discussion of model parameters, the time of duration, deposited scope and estimated velocity essentially agree with site survey. Thus, the model is able to simulate instability and flow of dense granular materials at both experimental and field scale, and it could be a powerful tool for the landslide-induced debris flow study.

Correction to: The March 24 and 29, 2016 landslide-induced debris flow at Clapar, Banjarnegara, Central Java

The published version of this article, unfortunately, contained error. Below have the items from the original paper to be corrected.

The March 25 and 29, 2016 landslide-induced debris flow at Clapar, Banjarnegara, Central Java

The Clapar landslide induced debris flow consisted of the Clapar landslide occurred on 24 March 2017 and the Clapar debris flow occurred on 29 March 2017. The first investigation of the Clapar landslide induced debris flow was carried out two months after the disaster. It was followed by UAV mapping, extensive interviews, newspaper compilation, visual observation and field measurements, and video analysis in order to understand chronology and triggering mechanism of the landslide induced debris flow in Clapar. The 24 March 2016 landslide occurred after 5 hours of consecutive rainfall (11,2 mm) and was affected by combination of fishponds leak and infiltration of antecedent rain. After five days of the Clapar landslide, landslide partially mobilized to form debris flow where the head scarp of debris flow was located at the foot of the 24 March 2016 landslide. The Clapar debris flow occurred when there was no rainfall. It was not generated by rainstorm or the surface erosion of the river bed, but rather by water infiltration through the crack formed on the toe of the 24 March 2016 landslide. Supply of water to the marine clay deposit might have increased pore water pressure and mobilized the soil layer above. The amount of water accumulated in the temporary pond at the main body of the 24 March 2016 landslide might have also triggered the Clapar debris flow. The area of Clapar landslide still shows the possibility of further retrogression of the landslide body which may induce another debris flow. Understanding precursory factors triggering landslides and debris flows in Banjarnegara based on data from monitoring systems and laboratory experiments is essential to minimize the risk of future landslide.

The formation of the Wulipo landslide and the resulting debris flow in Dujiangyan City, China

The Wulipo landslide, triggered by heavy rainfall on July 10, 2013, transformed into debris flow, resulted in the destruction of 12 houses, 44 deaths, and 117 missing. Our systematic investigation has led to the following results and to a new understanding about the formation and evolution process of this hazard. The fundamental factors of the formation of the landslide are a high-steep free surface at the front of the slide mass and the sandstone-mudstone mixed stratum structure of the slope. The inducing factor of the landslide is hydrostatic and hydrodynamic pressure change caused by heavy continuous rainfall. The geological mechanical model of the landslide can be summarized as “instability - translational slide - tension fracture - collapse” and the formation mechanism as “translational landslide induced by heavy rainfall”. The total volume of the landslide is 124.6×104 m3, and 16.3% of the sliding mass was dropped down from the cliff and transformed into debris flow during the sliding process, which enlarged 46.7% of the original sliding deposit area. The final accumulation area is found to be 9.2×104 m2. The hazard is a typical example of a disaster chain involving landslide and its induced debris flow. The concealment and disaster chain effect is the main reason for the heavy damage. In future risk assessment, it is suggested to enhance the research on potential landslide identification for weakly intercalated slopes. By considering the influence of the behaviors of landslide-induced debris flow, the disaster area could be determined more reasonably.

Effect of topography and soil parameterisation representing soil thicknesses on shallow landslide modelling

Hillslope hydrology studies have shown that bedrock surface topography maybe the most important factor affecting subsurface flow, and that soil thickness and soil properties related to topography are important factors in shallow landslide prediction. In this study, the physically based H-slider (hillslope-scale shallow landslide-induced debris flow risk evaluation) model was used to evaluate the effects of topography and soil parameterisation reflecting soil depth on shallow landslide prediction accuracy. Two digital elevation models (DEMs; i.e. ground surface and bedrock surface) and three soil thicknesses (average soil thickness, soil thickness to weathered rock and soil thickness to bedrock) and physical soil parameters (cohesion and internal friction angle) at a small hillslope site in Jinbu, Kangwon Prefecture, eastern part of the Korean Peninsula, were considered. Each prediction result simulated with the H-slider model was evaluated by receiver operating characteristic (ROC) analysis for modelling accuracy. The results of the ROC analysis for shallow landslide prediction using the ground surface DEM (GSTO) and the bedrock surface DEM (BSTO) indicated that the prediction accuracy was higher using the GSTO compared to the BSTO. Moreover, the prediction accuracy based on soil parameterisation reflecting soil thickness was highest in all cases. These results imply that the effect of soil parameters on shallow landslide prediction could be larger than the effects of topography and soil thickness. Therefore, we suggest that using soil properties representing the effect of soil thickness can improve the accuracy of shallow landslide prediction, which should contribute to more accurately predicting shallow landsides.

Discharge of landslide-induced debris flows: case studies of Typhoon Morakot in southern Taiwan

Abstract. Three debris-flow gullies, the Hong-Shui-Xian (HSX), Sha-Xin-Kai (SXK), and Xin-Kai-Dafo (XKD) gullies, located in the Shinfa area of southern Taiwan, were selected as case studies on the discharge of landslide-induced debris flows caused by Typhoon Morakot in 2009. The inundation characteristics of the three debris flows, such as the debris-flow volume V, deposition area Ad, and maximum flow depth, were collected by field investigations and simulated using the numerical modeling software FLO-2D. The discharge coefficient cb, defined as the ratio of the debris-flow discharge Qdp to the water-flow discharge Qwp, was proposed to determine Qdp, and Qwp was estimated by a rational equation. Then, cb was calibrated by a comparison between the field investigation and the numerical simulation of the inundation characteristics of debris flows. Our results showed that the values of cb range from 6 to 18, and their values are affected by the landslide ratio RL. Empirical relationships for cb versus RL, Qdp versus Qwp, Qdp versus V, and Ad versus V are also presented.

Analysis of landslide inventories for accurate prediction of debris-flow source areas

For the generation of susceptibility maps on medium scales (1:25,000 to 1:50,000) using statistical techniques, a reliable landslide inventory is needed, together with factor maps used as inputs. This paper compares landslide susceptibility maps obtained with the same methodology but using different landslide inventories: the official Italian landslide inventory GeoIFFI for the Lombardy Region and a recently mapped inventory (DF2001). The analysis included four main steps: (i) preparation of debris flow inventories using both random and spatial partitions and factor maps as explanatory variables; (ii) calculation of accountability and reliability indices for a preliminary susceptibility analysis and selection of an appropriate combination of the factor maps for detailed analysis; (iii) evaluation and validation of the obtained susceptibility maps; and (iv) comparison of the results and selection of the final map. The study area is located in the Valtellina Valley in the Central Italian Alps. The analysis identified highly susceptible areas of shallow landslides that may generate debris flows. It was demonstrated that more precisely delimited source areas for landslide-induced debris flows produce better susceptibility maps. However, the improvement of these maps was relatively limited when the inventories were randomly subdivided. Higher improvements were observed after the subdivision of the inventories into three geographical parts with different geomorphological characteristics. Although the modelling showed very similar results if evaluation is made using standard techniques, the spatial pattern of the susceptibility maps was highly variable and dependent on the combination of the factor maps used.

A rational method for estimating maximum discharge of a landslide-induced debris flow: A case study from southwestern China

This paper presents a rational method for estimating the maximum discharge of a landslide-induced debris flow. The method has five basic principles or steps: (a) to identify and measure representative bends and straight zones along a channel through which a debris flow went down; (b) to evaluate peak debris flow velocity in the bends; (c) to assess peak debris flow velocity in the straight channel zones; (d) to use the peak velocities to estimate the distribution of peak discharge along the entire channel; and (e) to find the maximum velocity and discharge of the debris flow. The method is illustrated with a case study of a landslide-induced debris flow at a mountainous region near Chengdu, southwestern China. The results show that the peak debris velocity was between 2.4 and 4.7 m s − 1 and the peak debris discharge was between 6.7 and 35.7 m 3 s − 1 . The peak discharge initially increased at the upper portion of the channel, then decreased at the lower portion, indicating that the upper channel experienced erosion but the lower channel experienced deposition. The location with the maximum debris flow discharge corresponds to the point where the volume of the debris flow started to decrease. The method presented in this paper can help to prevent or mitigate debris flow hazards.

Shear failure of large clay blocks of landslide-induced debris flow

Shear failure of large clay blocks of landslide-induced debris flow