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Among all the factors affecting the destructiveness of debris flow, the mean velocity is one of the most important characteristics. In this paper, we aim to apply a particle swarm optimization (PSO) based on the relevance vector machine (RVM) to predict the mean velocity. The PSO is used to optimize kernel parameters inside the RVM, whereas the RVM is responsible for completing the prediction task. Through sample training, a nonlinear relationship can be obtained, enabling a rapid prediction of the mean velocity for new samples. The debris flow dataset of Jiangjia Gully is used to evaluate the performance of PSO‐RVM in this study. Besides, we further compare the prediction results of PSO‐RVM with other prominent approaches, for example, the support vector machine (SVM), BP neural network (BP), and the RVM. The results show that the mean relative error (MRE) of PSO‐RVM is only 0.69%. In addition, BP yields the highest MRE (27.61%), and the MRE (2.75%) corresponding to the RVM is lower than that (5.98%) yielded by the SVM. For the root mean square error (RMSE) and Theil's inequality coefficient (TIC), the PSO‐RVM method still generates much lower RMSE (6.48%) and TIC (0.179%) values than the other three methods. Overall, compared with current debris flow prediction models, the PSO‐RVM achieves high prediction accuracy, fewer optimization parameters, and low computational complexity. Finally, a sensitivity analysis is conducted to explore the dominative factors of debris flow. [ABSTRACT FROM AUTHOR]

Susceptibility mapping has been an effective approach to manage the threat of debris flows. However, the sample heterogeneity problem has rarely been considered in previous studies. This paper is to explore the effect of sample heterogeneity on susceptibility mapping and propose corresponding solutions. Two unsupervised clustering approaches including K-means clustering and fuzzy C-means clustering were introduced to divide the study area into several homogeneous regions, each region was processed independently to solve the sample heterogeneity problem. The information gain ratio method was used to evaluate the predictive ability of the conditioning factors in the total dataset before clustering and the homogeneous datasets after clustering. Then the total dataset and the homogeneous datasets were involved in the random forest modeling. The receiver operating characteristic curves and related statistical results were employed to evaluate the model performance. The results showed that there was a significant sample heterogeneity problem for the study area, and the fuzzy C-means algorithm can play an important role in solving this problem. By dividing the study area into several homogeneous regions to process independently, conditioning factors with better predictive ability, models with better performance and debris flow susceptibility maps with higher quality could be obtained. [ABSTRACT FROM AUTHOR]

The rapid movement and extensive displacement of gravel-silty clay landslides result in significant property damage and loss. Following the destabilization of the Shaziba landslide in Enshi City, it transformed into a debris flow, ultimately obstructing the Qingjiang River and creating a barrier dam. This study delves into the failure mechanism, leap dynamics, and motion processes of this specific landslide by employing a blend of ring shear testing and the discrete element method. Initially, the residual shear strength of the sliding soil was assessed through ring shear tests conducted under various coaxial stresses and shear rates within the sliding region, using field surveys and aerial imagery. Building upon this foundation, the entire progression of the landslide-from sliding to settlement-was replicated using PFC3D, allowing for an examination of the landslide's movement characteristics such as speed, displacement, and trajectory. The findings indicate that the shear displacement and residual friction coefficients are higher at elevated shear rates compared to lower rates. The landslide commences with an initial acceleration phase, with the silty clay material's movement lasting approximately 757 s, reaching a maximum velocity of 32.5 m/s and a displacement exceeding 1000 m. The simulated settlement volume of the landslide (9.31 × 105m3) closely aligns with the results obtained from field investigations (1.5 × 106m3). This research offers comprehensive insights into recent Shaziba landslides, serving as a valuable resource for enhancing our understanding of the dynamics involved and mitigating the potential risks associated with such events. [ABSTRACT FROM AUTHOR]

Early identification of debris-flow-prone watersheds and determination of the initiation location of debris flows are prerequisites for debris flow monitoring and early warning. The high altitude, steep slope, dense vegetation, and influence of numerous factors triggering debris flows (FTDFs) in Danba, China, pose great difficulties in identifying debris-flow-prone watersheds and locating the possible initiation position of debris flows in this area. We propose a watershed-oriented and multifactor-integrated (WOMI) method for identifying debris-flow-prone watersheds in Danba. This method integrates various FTDFs, uses the watershed as an analysis unit, and detects the debris-flow-prone watersheds with a random forest (RF) algorithm. Moreover, we propose a statistical similarity metric to evaluate the rationality of identification results and introduce the extenics theory to evaluate the debris-flow hazard of the identified debris-flow-prone watersheds and their tributaries, thereby locating the possible initiation positions of debris flow in the identified debris-flow-prone watersheds. Based on 26 FTDFs derived from multi-source data between 2015 and 2019 in Danba, 36 new debris-flow-prone watersheds between 2015 and 2019 were discovered in this study. Nine debris-flow-prone watersheds and their 17 tributaries have very high hazard. "6.17" Meilong Valley debris flow just erupted in one of the identified debris-flow-prone watersheds in 2020. The statistical analysis and occurrence status of debris flows validated the proposed methodology and the identified debris-flow-prone watersheds in Danba. The research results of this article assisted in the investigation, early warning, and prevention of debris flows in Danba. [ABSTRACT FROM AUTHOR]

In large-scale debris flow susceptibility assessments, there is often excessive manual intervention, low efficiency, and inadequate model accuracy. To address these issues, this paper integrates multiple data sources and proposes a Multi-channel and Multi-scale Residual Network (MMRNet) for automatic extraction of gully features. Firstly, MMRNet employs a multi-scale feature fusion module to capture both local and global features of gullies, enhancing the model's feature representation capabilities. It then uses an improved residual structure to fuse shallow features, compress features, and improve assessment efficiency. Additionally, channel rearrangement techniques are used to enhance feature flow. Finally, susceptibility prediction is made based on the similarity between the gully under evaluation and gullies where debris flows have occurred. The natural breakpoint method is used to classify susceptibility results into five levels. Experimental results show that the very high susceptibility zones for debris flows are mainly concentrated in areas with abundant river systems along the Nujiang River, covering 61.68% of the entire study area, with a debris flow proportion of 98.78%. The MMRNet model achieves an accuracy (ACC) of 81.6% and an area under the curve (AUC) of 0.8320, indicating that this model is a high-performance method for debris flow susceptibility assessment. [ABSTRACT FROM AUTHOR]

Infrasound generated during the formation and movement of debris flows exhibits long propagation distance and slow energy attenuation, rendering it ideal for remote monitoring of debris flows. However, accurately identifying the infrasound signals of debris flows is challenging because of the complexity of background noise interference and variations in signal characteristics linked to the event's specific characteristics. In this study, the infrasound signal is preprocessed using high and low-pass filters, wavelet soft threshold denoising to mitigate noise interference, and then time-frequency transformed into a two-dimensional image, which is then input into a deep learning model fused with ResNet18 and Vision Transformer for training. The fusion model offers a potent feature extraction capability and the ability to generalize models, which leads to a better understanding of the details of the infrasound signals from debris flows. The experimental results show that the recognition accuracy of the proposed method is up to 88.60%, which is able to effectively predict and warn about the upcoming debris flow events. [ABSTRACT FROM AUTHOR]

To address the issue of debris flow high-tide often lagging behind earthquakes by 1–2 years in a region, this study uses the case of the Xifan Gully debris flow, which occurred on June 25, 2018, in the Jiuzhaigou area. The research was conducted as follows: First, the amount of new material sources in Xifan Gully was determined by comparing drone images taken before and after the earthquake. Second, regional daily rainfall data from meteorological stations were used to calculate the runoff and infiltration in the gully. Third, indoor shear tests were conducted on soil samples collected on-site to determine the relationship between cohesion (C) and internal friction angle (φ) with changes in moisture content. Finally, numerical simulations were used to calculate how the factor of safety (FS) of the soil in Xifan Gully changes with rainfall. Results show that the peak acceleration brought by the Jiuzhaigou County earthquake to Xifan gully was 164.3 Gal. The materials of Xifan gully and newly added landslide and channel materials occupied 78.81 × 104 and 16.07 × 104 m3, respectively. Although the rainfall in September 2017 was the highest in the last decade, the loose material did not reach saturation. The peak rainfall before debris flow eruption in the Xifan Gully (June 21, 2018) was 21.8 mm, and the effective rainfall reached 68.5 mm until the occurrence of debris flow (June 21–25). At this time, the loose source reached saturation and debris flow started. The results demonstrated that High-tide hysteresis of post-earthquake debris flows is due toe the earthquake not only amplifying the amount of loose material but also increasing the amount of rainfall required to saturate the soil, thereby extending the time needed for the soil to reach saturation. Overall, our results are beneficial for monitoring and early warning of debris flow disasters in mountainous areas. [ABSTRACT FROM AUTHOR]

The present study aimed to understand the debris flow characteristics in view of frequent extreme rainfall events, expansion of road networks, tourist influx, and population pressure in the NW & Central Himalaya. Notably, majority of the human settlements, roads, bridges, buildings, and even protection measures in the NW & Central Himalaya do not take into consideration such debris flow impact scenario despite a history of debris flow disasters. The Voellmy-Salm rheology dependent dynamic runout simulation method was used to determine the debris flow pressure and velocity regime in 9 debris flow locations belonging to different litho-tectonic conditions. Results revealed that the debris flow pressure and velocity in these 9 studied debris flows might reach up to 3000 kPa and 20 m/s, respectively. The debris flow pressure and velocity of these orders have the potential to damage the protection measures and infrastructures, which have also been observed in other hilly terrains. The sensitivity analysis was carried out at a range of input parameters by considering 729 possible simulations and debris flow pressure and velocity are found to follow relatively better corelation until ~ 250 kPa flow pressure and ~ 15 m/s velocity thresholds. The influence of slope topography on the debris flow characteristics is also observed in the form of amplification of flow pressure and velocity at concave portions. The rapid development of road network in the NW & Central Himalayan region and its subjectivity to potential debris flow risk is also discussed. [ABSTRACT FROM AUTHOR]

Debris flows are rapid downslope, gravity-driven movements of highly viscous, dense and concentrated/hyperconcentrated fluid materials. In Brazil, the most susceptible area to this type of mass movement comprises the oriented foothills of Serra do Mar. Several numerical modeling approaches have been created to measure, identify, predict, and monitor debris-flow processes, for example, RAMMS (Rapid mass movement simulation), a single-phase numerical model that simulates the propagation of debris flow using the Voelmy rheology. In this work, the RAMMS code is applied to model the debris-flow event that occurred in 1967 in Caraguatatuba County (State of Sao Paulo). Induced by heavy rains, this debris-flow event is one of highest magnitude recorded in Brazil, with more than 100 deaths and major socioeconomic and environmental impacts. Studies involving debris-flow modeling are still recent in Brazil, and they are relevant because can be applied to support the delineation of the affected area and the understanding of the dynamics of these phenomena. Thus, back-analysis studies are applied to assist the model setup and the results evaluations. Field observations and the back-analysis studies showed that the debris-flow processes in the Serra do Mar region are strictly granular, which helped the modeling step, and the debris are preferentially deposited in regions with low slopes (< 5°). The model results can be used to support political and engineering actions aimed at mitigating the effects of future events. [ABSTRACT FROM AUTHOR]

Geological disasters in the Emei to Mianning section of the Chengdu–Kunming Railway located in southwestern China occur frequently, and many debris flow gullies are distributed along the line. Debris flows often cause damage to the railway and highway that threatens the safe operation of the original line and the double-track line. Along the railway, the debris flow outbreak risks are analyzed for 53 debris flow gullies using field survey, remote sensing interpretation, and numerical simulation. Their developmental characteristics were judged according to the code. The results are used for numerical simulation of debris flow to further determine the movement characteristics and the accumulation range of debris flow. The results are combined with high-definition satellite images to analyze the form of the railway passing from the mouth of the ditch and the simulation results to determine the impact on the safe operation of the Chengdu–Kunming Railway when the debris flow erupts. Finally, disaster prevention and mitigation projects are proposed, and the prevention and control effects of the proposed works are validated. [ABSTRACT FROM AUTHOR]

An integrated taphonomic analysis was applied to a tank deposit from the Zabelê Palaeontological Site (ZPS) in northeast Brazil. The unique sedimentological evidence documents the origin of the mammal assemblage via debris flow. Optically stimulated luminescence (OSL) dates put the ZPS in the later Marine Isotope Stage (MIS) 3, which was a time when it was colder and there were fewer trees. The study revealed that the Zabelê's periphery accumulation was the result of the short transport of specimens and their entrainment by debris flow. This hydraulic transport caused the preferential orientation of the bioclasts (north–southwest). Comparisons were made with other Pleistocene tank deposits, suggesting the occurrence of common megamammal taxa. Temporal mixing was evidenced by the long time interval recorded by OSL ages and the co‐occurrence of distinct degrees of fragmentation, weathering, and fossil diagenesis. Permineralization and staining of Fe3+ and Mn colour patterns were identified as fossilization processes with preservation of the original bone hydroxyapatite without substitution. The comparison with other tank deposits revealed common signatures (disarticulated and fragmented with moderate abrasion) and signs of reworking. Finally, the savanna‐adapted herbivore megamammals from ZPS, such as Eremotherium, Notiomastodon, Toxodon, and Glyptotherium, are congruent with the forest decline from MIS 3 to the Last Glacial Maximum. [ABSTRACT FROM AUTHOR]

Debris flow disasters frequently occur and pose considerable hazards; thus, it is essential to thoroughly evaluate their risks. This study constructs a database comprising 20 assessment indicators, utilizing comprehensive natural disaster risk assessment theory and incorporating the triggering factors of Huokou Lake in the Changbaishan Mountains. This research employs a hybrid ANP-CRITIC methodology to allocate weights to the assessment indicators efficiently. For hazard assessment, this research utilizes both the Information Quantity and Random Forest models for comparative analysis. The ROC curve was employed to validate the outcomes, ultimately favoring the Random Forest model due to its superior accuracy in assessing debris flow hazards. In this study, the risk of debris flow disasters in Antu County is comparatively assessed under scenarios with and without an outburst event. The findings indicate that areas of high and very high risk are predominantly located within the central regions of economically prosperous and densely populated townships. Additionally, the risk in Erdao Baihe Township escalates significantly when considering the outburst of Huokou Lake. The significance of this study lies in its ability to furnish a robust scientific basis for decision-makers aimed at preventing future debris flow disasters. Furthermore, it serves as a crucial reference for advancing sustainable regional development and facilitates the equilibrium between economic growth and environmental protection within disaster management strategies. [ABSTRACT FROM AUTHOR]

Sediment transported from debris‐flow initiation zones is typically stored in a topographic feature called a debris‐flow fan, the formation process of which governs secondary sediment transport further downstream. Although sediment transport from debris‐flow fans can impact sediment regimes and change landforms, the determinants of progressive fan formation are not well constrained. To identify such determinants, this study monitored debris flows and performed topographic surveys of debris‐flow fans in the Ichino‐sawa torrent (Japan) during 2016–2017. In this period, eight debris flows occurred, two of which eroded the existing fan and formed a new channel with a short recurrence interval (~40 days). Consequently, these two cases induced substantial sediment transport further downstream from the fan. The examined rainfall indices did not provide a threshold for diagnosing the occurrence of such sediment transport. Debris flows with a large flow depth and a long duration led to changes in the runout direction and subsequently formed new channels. Before these processes, the existing channel was backfilled and plugged by previous debris flows, forming a steep fan surface around the fan apex. The results suggest that increasing the magnitude and the duration of debris flows potentially triggers sediment transport from fans coupled with channel plugging. The annual sediment transport from the fan exceeded almost all sediment yields of the world rivers and was found comparable with that linked with volcanic eruptions and their aftermath. Thus, the fan‐formation process can induce substantial sediment transport, independent of volcanic perturbations and extreme climatic events, and is dependent on the sediment supply from repeated occurrence of debris flows in the initiation zones. [ABSTRACT FROM AUTHOR]

Improving our ability to relate postfire debris‐flow volume to rainfall characteristics, terrain attributes, and fire severity is critical for quantifying postfire sediment yields from steep landscapes and predicting changes in debris‐flow hazards following fire. This is especially true in the Southwest United States (US) (Arizona and New Mexico), where fire activity has increased in recent decades. In this study, we present a database of 54 postfire debris‐flow volumes that we collected across the Southwest between 2010 and 2021. We use these data to develop a multiple linear regression model for postfire debris‐flow volume based on peak 30‐min rainfall intensity, watershed area greater than 23°, and a soil burn severity variable. We further propose a model that utilizes only rainfall and terrain variables, as well as a model that requires only terrain attribute and fire‐severity variables. These models are beneficial in scenarios where there are data limitations. We compare these new models with others developed in the western US to explore differences in the factors that control debris‐flow volume across geographic regions. We find that the models introduced here more accurately predict postfire debris‐flow volume in the Southwest relative to existing models. We also find that models that include sub‐hourly rainfall intensity perform better than those that do not, revealing the benefits of high‐resolution rainfall data for constraining postfire debris‐flow volume. Results improve our ability to forecast postfire debris‐flow volume in the Southwest and provide insights into relationships between rainfall intensity, terrain attributes, fire severity, and debris‐flow volume. Plain Language Summary: Postfire debris flows are fast‐moving mixtures of water and sediment that are a common hazard in steep landscapes recently burned by wildfires. Debris flows can result in the loss of life and damage to downstream infrastructure and buildings, underscoring the need for tools that can be used to reduce the impacts of future events. Because the amount of sediment that is transported by a debris flow is directly related to the area that it can impact downstream, tools for predicting postfire debris‐flow volume are especially important. However, a historic lack of postfire debris‐flow volume data has limited the creation of such tools in many fire‐prone regions of the western United States, including the Southwest (Arizona and New Mexico). In this study, we use a new data set of 54 postfire debris‐flow volumes that we collected across Arizona and New Mexico between 2010 and 2021 to develop three new methods for predicting postfire debris‐flow volume in the Southwest. These tools can accurately predict the volume of postfire debris flows given information related to rainfall, watershed topography, and fire severity. They outperform three existing postfire debris‐flow volume models and improve our ability to predict postfire debris‐flow volume in the Southwest. Key Points: We compile a data set of 54 postfire debris‐flow volumes to develop multiple linear regression models for predicting volume in the SouthwestSouthwest‐specific volume models outperform three existing models developed using data from other regions of the western United StatesSub‐hourly rainfall intensity improves predictions of postfire debris‐flow volume in the Southwest [ABSTRACT FROM AUTHOR]

The slope failure and the debris flow at Chandmari and Sichey within the city of Gangtok in Sikkim, India, have been numerically analyzed using the distinct element method. The published data on the failure surface and the extent of the debris flow, which followed a 5-h, 210-mm rainfall event in 1997 at Chandmari, have been used to verify the adopted methodology. The numerical simulations have revealed that the runout distances predicted for the landslide are in agreement with the actual ground observations. After a satisfactory simulation of the Chandmari landslide, the instability and the debris flow at Sichey, located on the backside of the same mountain, were studied. The results indicated that a collapsed building noticed during a 2019 field visit to Sichey is located within the predicted failure surface. The debris flow after the ground saturation originates from two distinct parts of the Sichey slope, located near the toe and the crown of the potential failure surface. The debris flow from the lower slope failure, near the toe of the critical slip surface, has a longer runout distance and higher velocity than the debris flow from the upper slope failure near the crown of the critical slip surface. Due to a broad and relatively flat road bench located at the middle portion of the failure surface, these two distinct debris flows might not get a chance to merge to form a major destructive force entirely, and thus, the locality in the down slope might escape a total inundation. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to obtain a preliminary understanding on the sources of debris flow sediments and the characteristics of organic carbon (OC) transported by debris flow events. Methods: Samples from debris flow and debris flow deposits as well as potential sources in the catchment were collected. For the collected samples, we measured grain size compositions, OC concentrations and properties such as C:N ratio, stable C isotopic composition and OC components derived from nuclear magnetic resonance (NMR) spectroscopy. Results: As inferred from OC concentrations, C:N ratios and δ13C values, we found that OC in debris flow sediments and bare land soils are mainly petrogenic OC, while OC in forest, cropland and grassland soils contained a large fraction of biospheric OC. Fine particles were found to be preferentially transported in debris flow, and the particle selectivity decreased with increasing debris flow erosion intensity. However, no selectivity was observed for OC contained in debris flow, which is different from the widely observed preferential mobilization of OC in sediments by surface erosion. Conclusions: Our results show that sediments in debris flow are mainly sourced from bare lands. The fact that there are no significant differences in the petrogenic OC concentrations in various size fractions of debris flow sediment sources leads to no selectivity of OC in debris flow despite of selectivity of sediment particles. [ABSTRACT FROM AUTHOR]

Background: Climate change-induced geohazards are increasingly posing a critical threat to the sustained functionality and resilience of constructed infrastructures. Among these hazards, debris flows represent significant natural disasters, particularly in mountainous terrains, causing widespread property damage and loss of life globally. These phenomena involve complex interactions between solid and fluid forces, resulting in long run-out distances and high-speed flows. Predicting and monitoring debris flows is challenging due to the intricate interplay of these forces. Objective: The objective of this study is to evaluate the structural damage caused by debris flows and assess the efficacy of rigid barrier structures with passages/apertures. Method: Employing Smoothed Particle Hydrodynamics, a Lagrange-based mesh-free computational technique, the researchers simulated the impact of debris on a stiff structure. The focus was on the Rishiganga river valley in the Indian state of Uttarakhand, a region recently devastated by a debris flow that severely compromised essential infrastructure, including a hydroelectric power station. The research entailed modeling the debris flow in this specific locale and analyzing its effects on an assumed downstream rigid structure. Additionally, the study explored the outcomes of introducing a rigid barrier upstream. Results and Conclusion: Results indicated a substantial reduction in the impact on the downstream structure with the presence of an upstream rigid structure. Moreover, as the number of apertures in the upstream barrier was increased, the impact of flow on the downstream structure further diminished, because of a more streamlined flow pattern. [ABSTRACT FROM AUTHOR]

Landslide, debris flow, and other destructive natural hazards induced by heavy rainfall in mountainous regions are sometimes not independent but combined to form a disaster chain. Based on the integral link between the triggering of the landslide and the subsequent debris flow, we propose an approach that combines the transient rainfall infiltration and grid-based regional slope stability (TRIGRS) model and the AL-A model to achieve hourly hazard prediction. The results indicate that the TRIGRS model performes well in predicting the spatial distribution of the shallow landslides, with a success rate of 57%. Thus, it is reasonable to use it as the initial input for debris flow simulations. The coupled model was found to have a good accuracy of 67.4% in predicting the debris flow. Furthermore, the proposed coupled model can dynamically predict disasters by the hour based on actual rainfall events. Therefore, the results of this study help provide a more complete hazard prediction method for rainfall- induced landslide-debris flow hazards in mountainous regions. [ABSTRACT FROM AUTHOR]

Seismic-induced secondary disasters, such as collapses and landslides, generate loose deposits in gullies. Under the influence of intense rainfalls, these deposits can become destabilized and lead to the initiation of large-scale debris flow. The systematic study of this type of debris flow and the revelation of its initiation mechanism and destruction law can provide certain theoretical references for the debris flow prevention and control project in the southwest region in China, where such events are particularly prevalent. Therefore, based on the current state of domestic and international research, this study focuses on analyzing the factors affecting the stability of gully deposits, categorizes four destabilisation types, distills the initiation mechanism of two types of gully deposits, and summarizes three types of critical initiation models for debris flow triggered by the destabilisation of gully deposits from the perspective of hydrologic debris flows. Finally, due to the complexity of the initiation process of debris flow triggered by the destabilisation of gully deposits, three critical scientific issues involved in this type of debris flow are proposed based on the analysis of the shortcomings of the existing results. [ABSTRACT FROM AUTHOR]

A debris flow, with terraced fields as the source area, broke out on June 25th, 2018 in the Xiaotuga area of Yunnan Province, China, and this kind of debris flow is rarely recorded. Two purposes in this study: (1) the influence of flow drag force on slope stability; (2) back-analyze the movement process of debris flow. First, the geological background and movement of this debris flow were described based on a field investigation. Then, drag force, calculated by the laminar flow theory, is added to the slope stability calculation model, which elaborates the initiation process of this disaster. Moreover, dynamic simulation software (DAN3D) was used to simulate the kinematic process of the debris flow with a variety of combination models. The study shows that the terrace area can quickly produce surface runoff and create a drag force under rainfall conditions, which is the essential reason for the initiation of debris flow. In addition, the use of the FVV (Frictional-Voellmy-Voellmy) model is found to provide the best performance in simulating this type of debris flow, which reveals that it lasts approximately 200 s and that the maximum velocity is 12 m/s. [ABSTRACT FROM AUTHOR]

Landslides are common geohazards worldwide, resulting in significant losses to economies and human lives. Data-driven approaches, especially machine learning (ML) models, have been widely used recently for landslide susceptibility mapping (LSM) by extracting features from geospatial variables based on their contribution to landslide occurrences using known distributions of landslides as the training dataset. However, challenges remain in applying ML models for LSM models due to the scarcity and uneven spatial distribution of landslide data coupled with the spatial heterogeneity of hillslope conditions. Moreover, ML models developed with limited data often exhibit unexpected behaviors, resulting in poor interpretability and predictions that deviate from intuitive expectations and established domain knowledge. To overcome these challenges, this study proposes a physics-guided machine learning (PGML) framework that integrates landslide domain knowledge into ML models for LSM. The PGML framework was developed and assessed using a detailed debris flow inventory from a storm event in the Colorado Front Range. Based on the infinite slope model, the factor of safety for the study area was first determined and was subsequently used to constrain the prediction of ML models through a modified loss function and measure the physics consistency of model predictions. To evaluate the robustness and generalizability of the models, this study uses geographical sample selections for model performance evaluation, where ML models are trained and tested across heterogeneous ecoregions. The results of this study demonstrated the efficacy of both physics-based and data-driven methods in determining landslide susceptibility in the study area; however, pure data-driven ML models produced physically unrealistic results and poor generalization performance in new ecoregions. With the incorporation of physical constraints, the PGML model demonstrated notable enhancements in physics consistency and generalization capability, along with reduced model uncertainties across various ecoregions, surpassing the performance of benchmark ML models. [ABSTRACT FROM AUTHOR]

Debris flows are considered one of the most hazardous types of mass movement. China has a long history of monitoring debris flows, which has enhanced the understanding of debris flows and the development of strategies for their prevention. This study reviewed case studies and outputs related to debris flow monitoring in China. The monitoring systems are set in seven catchments, with area between 2 and 40 km2, covering various types of debris flows in different climate conditions. This review also introduced the definitions and classifications adopted for debris flows in China for comparison with those used in Western literatures. A comprehensive analysis was conducted of debris flow parameters, including the grain size distribution, density, Froude number, velocity–depth relationship, volume–peak discharge relationship, volume–drainage area relationship, and velocity and peak discharge calculation methods. Additionally, the rainfall intensity–duration thresholds were compared. Accurate identification of such information is fundamental for enhancing comprehension of debris flow characteristics, facilitating monitoring, and the implementation of early warning and alarm systems. [ABSTRACT FROM AUTHOR]

Flow-type landslides are not typical in this region of the Balkans. However, after the Tamara cyclone event in 2014, numerous such occurrences have been observed in Serbia. This paper presents the initial results of a detailed investigation into debris flows in Serbia, comparing findings from two programs: RAMMS DBF and Geoflow SPH. Located in Western Serbia, the Selanac debris flow is a complex event characterized by significant depths in the initial block and entrainment zone. Previous field investigations utilized ERT surveys, supplemented by laboratory tests, to characterize material behavior. Approximately 450,000 m3 of material began to flow following an extreme precipitation period, ultimately traveling 1.2 km to the deposition zone. For validation purposes, ERT profiles from both the deposition zone and the source area were utilized, with particular attention given to areas where entrainment was substantial, as this had a significant impact on the final models. The first objective of this research is to conduct a detailed investigation of debris flow using field investigations: geophysical (ERT) and aerial photogrammetry. The second objective is to evaluate the capacity of two debris flow propagation models to simulate the reality of these phenomena. The GeoFlow-SPH code overestimated the maximum propagation thickness in comparison to the RAMMS model. The numerical results regarding final depths closely align, especially when considering the estimated average depth in the deposition zone. The results confirm the necessity of using multiple simulation codes to more accurately predict specific events. [ABSTRACT FROM AUTHOR]

Debris flows continuously erode the channel downward and sideways during formation and development, which changes channel topography, enlarges debris flow extent, and increases the potential for downstream damage. Previous studies have focused on debris flow channel bed erosion, with relatively little research on lateral erosion, which greatly limits understanding of flow generation mechanisms and compromises calibration of engineering parameters for prevention and control. Sidewall resistance and sidewall shear stress are key to the study of lateral erosion, and the distribution of the flow field directly reflects sidewall resistance characteristics. Therefore, this study has focused on three aspects: flow field distribution, sidewall resistance, and sidewall shear stress. First, the flow velocity distribution and sidewall resistance were characterized using laboratory debris flow experiments, then a debris flow velocity distribution model was established, and a method for calculating sidewall resistance was developed based on models of flow velocity distribution and rheology. A calculation method for the sidewall shear stress of debris flow was then developed using the quantitative relationship between sidewall shear stress and sidewall resistance. Finally, the experiment was validated and supplemented through numerical simulations, enhancing the reliability and scientific validity of the research results. The study provides a theoretical basis for the calculation of the lateral erosion rate of debris flows. [ABSTRACT FROM AUTHOR]

Debris flows, highly destructive and rapidly moving mixtures of water, sediment, and rock, pose significant threats to human settlements and infrastructure in mountainous regions. Predicting the deposition patterns of debris flows is crucial for hazard assessment and mitigation. Smoothed Particle Hydrodynamics (SPH) has emerged as a valuable numerical simulation technique for modeling debris flow deposition due to its ability to capture complex fluid-solid interactions and particle dynamics. This study focuses on employing SPH simulation to investigate debris flow deposition patterns and assess their accuracy through Particle Image Velocimetry (PIV) validation. The methodology encompasses the discretization of fluid and solid phases into particles, governed by hydrodynamic and constitutive equations, respectively. The coupling of fluid and solid interactions enables the representation of entrainment, transport, and settling of particles, yielding insights into deposition patterns. Twelve case studies are discussed to validate the accuracy and applicability of SPH simulations in reproducing deposition patterns. Additionally, challenges such as numerical stability, parameter sensitivity, and computational efficiency are addressed, along with potential enhancements in modeling techniques. Notably, it was observed that around three specific numerical instances demonstrated an extraordinary level of similarity (2.98%, 7.51% & 9.83%) to the deposition pattern that was observed during the experimental phase. As SPH continues to advance, it holds promise as a reliable tool for assessing debris flow hazards and guiding land-use planning and disaster management efforts in vulnerable regions. [ABSTRACT FROM AUTHOR]

In November 1815, the deadliest "natural" disaster in Balinese history was caused by the exceptional combination of multiple natural hazards that occurred simultaneously and cascaded in the present-day province of Buleleng. This major disaster, which is thought to have claimed more than 10,000 lives, has never been scientifically analyzed. The study conducts an in-depth analysis of this cascading disaster, from the root causes and chronology of natural hazards to their environmental and societal effects, by thoroughly examining all available written sources about this event, whether colonial or Indonesian. Seven months after the Tambora eruption, a magnitude 7.3 earthquake, which occurred in the Bali Sea off the northern coast of the island, triggered a very large landslide on the northern flank of the Buyan-Bratan caldera. The initial mass movement evolved into a cohesive debris flow that reached the sea after traveling up to twenty kilometers through Banyumala River Valley and Singaraja City downstream. According to historical accounts, fifteen villages were buried or devastated by the debris flow. The large volume of sediment entering the sea triggered a local tsunami along Buleleng's coast. This geohistorical approach offers a comprehensive overview of various sources describing Singaraja's situation before the crisis, the hazard succession, the cascading hazard intensities, and the short- to long-term impacts on Buleleng. Based on the written sources, Bali took around fifteen years to recover from the 1815 disasters. [ABSTRACT FROM AUTHOR]

Severe fire on steep slopes increases stormwater runoff and the occurrence of runoff‐initiated debris flows. Predicting locations of debris flows and their downstream effects on trunk streams requires watershed‐scale high‐resolution topographic data. Intense precipitation in July and September 2013 following the June 2011 Las Conchas Fire in the Jemez Mountains, New Mexico, led to widespread debris flows in the watershed of Rito de los Frijoles. We differenced lidar Digital Elevation Models (DEMs) collected in 2010 and 2016 to map subwatersheds experiencing debris flows and changes in elevation of the trunk stream. Debris flow occurrence was well predicted by previous assessments of debris‐flow hazard; debris flows occurred in 7 of 9 sub‐basins where the debris‐flow hazard was above 60% for the 25‐year rainfall event, and in 0 of 21 basins where debris flow hazard was less than 60%. Debris flows resulted in fan deposition at the confluence with the trunk stream followed by transport during three documented floods. The bed of the 22 km trunk stream increased in elevation by a mean of 0.29 m, but the local change in thalweg elevation was controlled by inputs of water and sediment and longitudinal variation in gradient. Downstream of the mouths of tributaries with debris flows, the thalweg of the trunk stream rose as much as 2 m. Downstream of the mouths of tributaries without debris flows the thalweg of the main stem degraded by as much as 2 m, mobilizing sediment that was then deposited further downstream where the gradient of the trunk stream decreases. In conclusion, the transport of sediment generated by debris flows was predictably related to spatial variation in sediment supply, discharge and gradient. [ABSTRACT FROM AUTHOR]

The LJ9 segment of Jiumian Expressway frequently experiences gully-type debris flow disasters, posing threats to nearby villages and infrastructure. Considering the unique characteristics and importance of the highway and G247 national road, this study investigates the material source characteristics and scale of six debris flow gullies with debris flow outbreak traces along the LJ9 section of Jiumian Expressway. The debris flows in this area are classified as low-frequency gully flash flood types. The bulk density of the debris flows ranges from 1.647 to 1.843 g/cm³, with velocities between 3.45 and 6.54 m/s, and flow rate ranging from 29.47 to 253.45 m³/s. The total volume of the debris flow ranges from 0.99 x 104 to 8.28 x 104 m³. This paper compares the differences in the scale characteristics of the "8•16" debris flow on the Jiumian Expressway, and analyze the relationship between the volume of material source and the bulk density and scale of debris flow, establishing relevant calculation formulas. The results show that: (1) The fluid properties of debris flow in the study area are classified as low-frequency gully flash flood types, closely related to the volume of material source, with a positive correlation between unit area material source volume and debris flow bulk density. When unit area material source volume exceeds 1.65 x 105 m³/km² or falls below 1.13 x 105 m³/km², debris flow exhibit viscous or diluted characteristics, respectively. (2) Under similar geological conditions, there is a linear correlation between material source volume and debris flow scale, with total debris flow volume decreasing as unit area material source volume decreases. (3) Debris flow damage potential is controlled by material source volume. Gullies with material source volumes exceeding 800 000 m³ are more likely to produce viscous debris flows, which has greater destructive power and form larger debris flow fans at their mouths. These findings provide insights for the design and construction of the Jiumian Expressway and serve as a scientific basis for the safe operation of infrastructure in mountainous regions and the construction work of geological hazard prevention projects. [ABSTRACT FROM AUTHOR]

Lanping County, located in the northwestern part of Yunnan Province, is characterized by unfavorable geological conditions. In recent years, debris flow disasters have frequently occurred in this area due to the influence of rainfall, yet there is a lack of accurate disaster risk evaluations. To enhance early warning preparedness for debris flow disasters in the region, the FLO-2D model was employed to perform an inverse analysis of a historical debris flow event in Lajing Village, Lanping County. Based on the parameters obtained from this analysis, predictions of the dynamic characteristics and risk assessments were conducted for another debris flow-prone gully under three rainfall recurrence period conditions: 20, 50 and 100 years. The results indicate that in Gully No. 2 of Lajing Village, the siltation depth and maximum flow velocity of debris flow increase with the intensification of rainfall. Under extreme rainfall conditions, the siltation depth at the trench bottom is expected to exceed 2.5 m, and the maximum flow velocity in the transportation zone may exceed 5 m/s, leading to the accumulation of more loose materials in the deposition area and creating significant safety hazards. The high-risk zones in gully No. 2 are primarily located in areas with high flow velocity and mud depth, around densely populated residential areas near the gully, and within the debris flow accumulation zone. The findings of this study provide valuable references for disaster prevention and mitigation engineering, as well as for early warning systems in the region. [ABSTRACT FROM AUTHOR]

On August 17, 2020, debris flows successively occurred in four ravines along the main stream of Yazhezaozu Village, Pingwu County, Sichuan Province. This event resulted in multiple collapses and interruptions along the G247 national highway, and extensive damage to the Jiumian expressway project site and laborer residences, among other areas. A significant volume of driftwood carried by the debris flow converged into the main stream, leading to the blockage of downstream road bridges and culverts, causing backflow and village flooding, thereby exacerbating the disaster risk. To prevent similar disasters in the future, post-disaster investigations using field surveys and remote sensing interpretations explored the characteristics of this debris flow disaster's risk. A primary focus was placed on analyzing the risk amplification effect caused by blockages in main stream road bridges and culverts due to debris flow. The results indicated: (1) The '8.17' debris flow in Yazhezaozu Village was a low-frequency, large-scale, rare, and extensive group occurrence, with an eruption frequency of approximately once every 50 years. The debris flows in Azu Gully and Zapai Gully were extremely large-scale, while Mashizha No. 3 Gully and Duobu River No. 5 Gully were large-scale, with an affected debris fan area of about 16.66 x 104 square meters. (2) Improper layout of main stream road bridges and culverts resulted in the blockages of driftwood carried by the debris flow, forming dammed bodies, increasing the affected area by 16.78 x 104 square meters, and enlarging the risk range by about 1-fold. (3) In well-vegetated, moist mountainous areas, when constructing main stream road bridges and culverts, it is advisable to appropriately increase the axial spacing between bridge piers, allowing for a certain width and operational space in the river channel. This will prevent the amplification of debris flow disaster risks caused by driftwood blockages. This study aims to provide guidance for the reasonable planning of main stream road bridges and culverts in similar mountainous areas and relevant prevention and early warning of debris flows. [ABSTRACT FROM AUTHOR]

Deqin County in Yunnan Province is among the most severely affected regions in China by debris flow disasters. The Yizhong River in Deqin County has witnessed numerous large-scale debris flow disasters, causing significant damage and substantial economic losses to residential areas and the G214 national road. To elucidate the range of hazard zones and initiation mechanisms of debris flow disaster triggered by potential sources in the upstream Yizhong River under conditions of heavy rainfall and earthquakes, this study conducted field investigations and causal analyses. High-precision Digital Elevation Model (DEM) data derived from close-range UAV aerial photography were utilized as topographic data. The RAMMS software simulated a debris flow of 16.05 x 104 m³ under heavy rain and earthquake conditions. Two hazardous zones within the Yizhong River Basin were delineated, and the disaster initiation mode of debris flow in Yizhong River was expounded. The results show that the debris flow in Yizhong River belongs to the gully-type viscous debris flow typical of plateau mountainous regions, characterized by large scale, high frequency, and severe impact. Its disaster mechanism is summarized as a gully and valley disaster chain involving high-altitude landslide, debris flow, dammed lake, and flood breach. Risk zone I is located in the area from G214 national road to Dewei Road, while risk zone II is in the gully mouth area prone to accumulation and blockage, presenting high risk. During debris flow movement, the maximum flow velocity reached 23.93 m/s, maximum impact force was 1 000 kPa, maximum accumulation depth was 9.33 m, and the maximum single outburst volume of debris flow was approximately 80 000 m³, with a danger area of about 0.31 km². The research results provide a scientific basis for debris flow control projects in Yizhong River and are of practical significance for improving the comprehensive prevention and control of geological hazards in Deqin County. [ABSTRACT FROM AUTHOR]

Abstract Background Climate change-induced geohazards are increasingly posing a critical threat to the sustained functionality and resilience of constructed infrastructures. Among these hazards, debris flows represent significant natural disasters, particularly in mountainous terrains, causing widespread property damage and loss of life globally. These phenomena involve complex interactions between solid and fluid forces, resulting in long run-out distances and high-speed flows. Predicting and monitoring debris flows is challenging due to the intricate interplay of these forces. Objective The objective of this study is to evaluate the structural damage caused by debris flows and assess the efficacy of rigid barrier structures with passages/apertures. Method Employing Smoothed Particle Hydrodynamics, a Lagrange-based mesh-free computational technique, the researchers simulated the impact of debris on a stiff structure. The focus was on the Rishiganga river valley in the Indian state of Uttarakhand, a region recently devastated by a debris flow that severely compromised essential infrastructure, including a hydroelectric power station. The research entailed modeling the debris flow in this specific locale and analyzing its effects on an assumed downstream rigid structure. Additionally, the study explored the outcomes of introducing a rigid barrier upstream. Results and Conclusion Results indicated a substantial reduction in the impact on the downstream structure with the presence of an upstream rigid structure. Moreover, as the number of apertures in the upstream barrier was increased, the impact of flow on the downstream structure further diminished, because of a more streamlined flow pattern.

Abstract The occurrence of frequent debris flow catastrophes in the mountainous regions of southwest China has necessitated the inclusion of debris flow disaster analysis and prevention as an essential component in the planning and construction of mountainous roadways. Daxilada watershed is located in the south of Mabian Yi Zuzizhixian, Leshan City, Sichuan Province, and the proposed Leshan-Xichang Expressway (Lexi Expressway) will pass through the upper reaches of Daxilada watershed. It is essential to consider that the presence of debris flows within the Daxilada watershed could have detrimental effects on the construction and functionality of the proposed Luoshanxi Bridge. This study examined the Daxilada watershed as a case study and analyzed the factors contributing to debris flow formation in the area. This analysis was based on field investigations, remote sensing interpretation, and experimental analysis. Additionally, the study utilized the Massflow software to simulate debris flow movement. It integrated the simulation results to determine the potential hazards the Daxilada Gully debris flow posed to the line project. This study found that Daxilada Gully meets debris flow formation conditions. The simulation results demonstrated that during the debris flow activity, there would be a maximum deposition depth of 2.1 m in the proposed Engineering Agency, which may lead to siltation and blocking disaster of the line project. Concerning the parameters related to the debris flow with a frequency of one in a hundred years, in conjunction with the outcomes obtained from numerical simulation, it would provide the design basis of the cross-flow cross-section of the proposed bridge. In a quantitative analysis of the blockage situation in the gully, debris flow deposits have the potential to cause damage to the line project. Debris flow deposits block the gully, but the risk of blockage is small. The study results have specific reference values for the debris flow prevention and control project of Lexi Expressway and offer valuable insights for the prevention and mitigation of similar disasters in relative projects.

Abstract Debris flow hazards are often interpreted through back-calculated simulation analysis or empirical methods. The mobility of a debris flow is greatly influenced by mechanical and hydrological parameters. The strength parameters play important roles in the debris flow initiation and flow stages. In particular, the rheological parameters of yield strength and plastic viscosity directly affect the debris flow runout distance and velocity. One of the most important parameters to consider when evaluating debris flow hazards is the shear strength. This strength is called the residual shear strength in the failure stage and the yield strength in the post-failure stage. The residual shear strength obtained from ring shear tests can be related to the initiation of mass movements; the yield strength obtained from rheological tests can be related to the mobilization of debris flows. The residual shear stresses obtained from ring shear tests of weathered soils typically range between 10 and 100 kPa and strongly depend on the normal stress and shear velocity. When progressive slope failure (i.e., strain-softening behavior) occurs at a relatively shallow slope depth (e.g.,

The Grand bend of the Yarlung Zangbo River, located at the boundary between the middle and lower reaches of the basin, is one of the most developed areas for debris flow activities in China. This study focuses on the Paiba gully and Qulu Valley on the south bank of the entrance section of the Yarlung Zangbo River’s grand bend. We collected and sorted out the historical optical satellite image data of the region in the past 50 years. By combining multi-period remote sensing image comparative interpretation and field investigation, we carried out the research on the characteristics of the development and distribution of debris flow sources, the characteristics of sediment transport, and the historical evolution of debris flow activities. The results show that from 1980 to 2023, the annual average sediment volume of the Paiba gully entering the main river was about 1900 m3. Before the construction of a retaining dam in 2016, the annual average sediment volume of the Qulu Valley entering the main river channel was about 700 m3. Both Paiba gully and Qulu Valley experienced large-scale debris flow around 1980. Over the next 40 years, Paiba gully was mainly characterized by floods and small-scale debris flow, while Qulu Valley experienced multiple debris flow events of varying scales. In recent years, the number and area of material sources in Paiba gully have increased relatively slowly, and the susceptibility of debris flows is moderate. In contract, Qulu Valley has seen significant increases in the quantity and area of channel and slope material sources, leading to high debris flow susceptibility. Sources developed in the Qulu Valley, and the quantity and area of these material sources have increased significantly in recent years. The susceptibility of debris flows is high, and the previously built control projects are functioning well and can effectively reduce the risk of debris flows.

In response to the challenges posed by frequent, widespread, long-lasting, large-scale, severe, and difficult-to-control debris flows in strong earthquake areas, this study, based on the results of the National Key R&D Program, investigates dozens of typical mega debris flow gullies in these regions. Through test verification and demonstration engineering application, the characteristics of typical debris flow ditches and their prevention and control engineering effects were studied, leading to the construction of a comprehensive technical system for the prevention and control of mega debris flows in strong earthquake areas. A key technical system for exploration, design, prevention, and control of mega debris flows in strong earthquake areas was formed. The exploration and design system introduced new technologies for identifying earthquake-induced fracturing sources and novel approaches for determining blocking coefficients based on existing exploration technologies. According to the morphology of debris flow valleys in seismic areas, debris flows are classified as narrow and steep or wide and gentle. The key technology system for prevention and control was established to comprehensively discuss and practice key technologies for preventing and controlling debris flows in different valley morphologies. Considering the characteristics of debris flow valleys in the upper, middle, and lower reaches of both narrow and steep or wide and gentle debris flow valleys, a combination of various comprehensive prevention and control measures was proposed. This led to the establishment of a hierarchical control system for major debris flows in seismic areas, from controlling the source to the process and ultimately mitigating disasters. This system not only provides technical support for comprehensive prevention and control of debris flows in seismic areas but also serves as a reference for comprehensive prevention and control of debris flows in non-seismic areas.

Abstract In this work, intelligent numerical models for the prediction of debris flow susceptibility using slope stability failure factor of safety (FOS) machine learning predictions have been developed. These machine learning techniques were trained using novel metaheuristic methods. The application of these training mechanisms was necessitated by the need to enhance the robustness and performance of the three main machine learning methods. It was necessary to develop intelligent models for the prediction of the FOS of debris flow down a slope with measured geometry due to the sophisticated equipment required for regular field studies on slopes prone to debris flow and the associated high project budgets and contingencies. With the development of smart models, the design and monitoring of the behavior of the slopes can be achieved at a reduced cost and time. Furthermore, multiple performance evaluation indices were utilized to ensure the model’s accuracy was maintained. The adaptive neuro-fuzzy inference system, combined with the particle swarm optimization algorithm, outperformed other techniques. It achieved an FOS of debris flow down a slope performance of over 85%, consistently surpassing other methods.

Sediment gravity flows (SGFs) cause serious damage in the Alpine regions. In the literature, several methodologies have been elaborated to define the main features of these phenomena, mainly considering the rheological features of the flow processes by laboratory experiments or by flow simulation using 2D or 3D propagation models or considering a single aspect, such as the morphometric parameters of catchments in which SGFs occur. These very targeted approaches are primarily linked to the definition of SGFs’ propagation behavior or to identify the predisposing role played by just one feature of catchments neglecting other complementary aspects regarding phenomena and the environment in which SGFs can occur. Although the research aimed at the quantification of some parameters that drive the behavior of SGFs provides good results in understanding the flow mechanisms, it does not provide an exhaustive understanding of the overall nature of these phenomena, including their trigger conditions and a complete view of predisposing factors that contribute to their generation. This paper presents a research work based on the collection and cross-analysis of lithological, geomechanical, geomorphological and morphometrical characteristics of Alpine catchments compared with sedimentological and morphological features of SGF deposits, also taking in to account the rainfall data correlation with historical SGF events. A multidisciplinary approach was implemented, aiming at quantifying SGF causes and characteristics starting from the catchments’ features where the phenomena originate in a more exhaustive way. The study used 78 well-documented catchments of Susa Valley (Western Italian Alps), having 614 historical flow events reported, that present a great variability in geomorphological and geological features. As the main result, three catchment groups were recognized based on the dominant catchment bedrock’s lithology characteristics that influence the SGFs’ rheology, sedimentological and depositional features, triggering rainfall values, seasonality, occurrence frequency and alluvial fan architecture. The classification method was also compared with the catchments’ morphometry classification, demonstrating that the fundamental role in determining the type of flow process that can most likely occur in a given catchment is played by the bedrock outcropping percentage, regardless of the results provided by the morphometric approach. The analysis of SGF events through the proposed method led to a relative estimate of the hazard degree of these phenomena distinguished by catchment type.

Extended Abstract Background: Debris is one of the important phenomena of slope movements in mountainous areas. Harsh climatic conditions and the availability of tectonic and geological structures in the central Alborz Mountain heights have caused a significant amount of debris to form on the slopes. Studying this process by relying on two opportunity and threat patterns is particularly important. Therefore, the current research tries to analyze the susceptibility of the occurrence of the Haraz Valley debris flow in the range of Plour to Baijan by providing a suitable index to prioritize the factors affecting the formation and expansion of debris to achieve its more accurate zoning. Methods: The effects of six layers of information, including lithology, height, slope, aspect, distance from the fault, vegetation, and land use, were investigated on the occurrence and spread of debris flow. First, the debris location in the area was identified using the geological map of Damavand, with a scale of 1:100,000 and Google Earth images. Then, the distribution map of the debris was prepared after field survey and recording points by a GPS device and transferred to the GIS environment. Maps of independent and influential variables on the spread of debris, including lithology and distance from the fault, were prepared from the Damavand geological map, and the height, slope, and direction of the range were prepared using the ASTER digital elevation model. The vegetation and land use maps were prepared from the national coverage map of Iran by processing Sentinel images on the Google Earth Engine Cloud platform. In the next step, the distribution map of the debris was combined with each map of the affecting factors, and the weight of each class of independent variables was obtained based on the density area model. Then, a zoning map of the susceptibility of the spread of debris was prepared in five classes of very high, high, moderate, low, and very low susceptibility. The average effective weight of the deposit susceptibility index was also calculated to determine the prioritization of affecting factors and prepare a more accurate map for the zoning of the expansion of debris. Results: The analysis of factors affecting the spread of debris in the studied area using the density area model shows that Melafir stone units (weathered basalts) have the most weight among all the stone units and all factors affecting the spread of debris in the region. After that, biogenic limestone, alluvial defenses, and Lar Formation are more important factors. The investigation of the elevation factor shows that the frequency of debris increases from 2100 meters up, and the elevation class of 2400-2700 meters is more sensitive. In terms of the slope factor, most of the debris in the region was observed in the slope between 10 and 40 degrees, and the largest deposit cover is related to the slope layer of 20-30 degrees. The calculation of the area density of the debris in different aspects shows that the northwest and north slopes have the most weight and susceptibility. The process of freezing and melting snow is evident in the destruction of rocks and the creation of most of the debris on these slopes. Examining the distance from the fault also showed that the frequency of debris is significant up to a distance of 1000 meters, and the highest weight of this layer, based on the density area, belongs to the zero-500-m layer of the faults. In addition to transmitting seismic stresses, faults cause the penetration of water caused by melting snow into rocks and are influential in destroying rocks and causing debris. In terms of vegetation and land use, pasture lands are the most susceptible to debris. The results of the statistical analysis of the density area and preparation of the regional zoning map showed that 5, 21.15, 29.78, 29.53, and 14.54% of the area of the region have very high, high, medium, and low susceptibility, respectively, to expand debris. According to the Debris Susceptibility Index (DSI) model, land use, lithology, and slope have the highest priorities with average effective weights of 21.04, 20.12, and 18.72, respectively, and are the main factors controlling the spread of debris in the area. The factors of slope, elevation, aspect, and distance from the fault were the next priorities. Conclusion: In the current research, the distribution of debris in different classes of independent variables was analyzed using the Density Area Model, and the importance of each class of parameters affecting the spread of debris was determined based on the weighting of the layers relative to each other. To evaluate the effic iency of the results of the density area model and verify its performance, a zoning map of the expansion of debris was prepared using the DSI model. The evaluation of the accuracy of the models using the empirical probability (P) shows that the density area and DSI models are suitable for zoning the susceptibility of debris in the area with probabilities of 0.79 and 0.80, respectively. The layers of high susceptibility to very high expansion of the deposit cover about 26% of the area, which is considered an environmental resource from one point of view. Hence, it can be exploited as a sedimentary deposit for use in engineering structures by forming a volume reserve, and from another point of view, it is a potential risk in agricultural fields, residential areas, and hydraulic structures.

Continuous heavy rainfall occurred in Shunchang County, Fujian Province, China, from June 14 to 18,2010, causing many landslide hazards. Among Shunchang County districts, Baozhuang Village is one of the hardest-hit areas and suffered severe losses. A detailed analysis of the relationship between the catchment area and the area of landslides was carried out to explore the relationship between debris flow occurring and the provenance provided by landslides. An empirical model was presented to analyze gully-type debris flows caused by hillslope debris flow everywhere. Forty-three catchments in the Baozhuang Village area were selected and investigated using Google Earth Pro satellite image to estimate the area of landslides in the catchment area. The thresholds for gully-type debris flow caused by shallow landslides were defined in terms of the area of the landslides (A0) and the catchment (A). A0 -A threshold models were constructed for debris flow catchment in Baozhuang Village using the empirical data set of debris flow by shallow landslides. The validation suggests that the proposed models are suitable for analyzing the initiation mechanism of debris flow caused by shallow landslide (or hill slope debris flow) in Fujian Province. The empirical models are simple, and the data necessary for the input are easily measurable catchment and landslide scar areas in a catchment. Owing to its simplicity and low cost-benefit rate, the approach may be applied to analyzing gully-type debris flow caused by shallow landslides in other areas. [ABSTRACT FROM AUTHOR]

Lahars are hazardous mixtures of rock and water that flow rapidly in the form of debris flows or mudflows. The continuous eruptions at Sakurajima supply volcanic ash to form on the surface, reducing the permeability of the ground. As the surface permeability decreases, surface runoff occurs and eventually lahar starts. Therefore, Sakurajima Island suffers from lahars triggered by heavy rains every year. Sheet erosion by surface runoff decreases the thickness of volcanic ash on the ground and subsequently increases hydraulic conductivity. This cycle continues due to the eruptions of the Sakurajima volcano and the lahars formed by heavy rains. Depending on the lahar type and amount of surface runoff, the flow density and block sizes carried in the lahar vary. In this study, the relationship between the volcanic ash thickness and the hydraulic conductivity of the ground was investigated in the Arimura River basin of Sakurajima volcano between 2015 and 2020. Monthly volcanic ash thickness was measured 2 km from the craters. The dynamic change of volcanic ash thickness due to accumulation and erosion was investigated by the Universal Soil Loss Equation and the newly developed Discharge Dependent Erosion methods. Block sizes of the lahars were estimated by vibrographs and CCTV camera. The hydraulic conductivity of the ground was calculated with a Kinematic Wave Model developed specifically for this study. Based on the relationship between volcanic ash thickness and hydraulic conductivity, a risk assessment chart was created considering the block sizes carried by the lahars. [ABSTRACT FROM AUTHOR]

After the 2008 Wenchuan earthquake (MS 8.0), a large number of debris flow source areas formed and further affected the occurrence of debris flows. Identifying the source area that may participate in debris flow activities requires understanding its dynamically changing conditions of location and probability. Based on this, the Bayesian geomorphology method was used to analyze the variation probability in the sediment supply from coseismic landslide deposits to subsequent debris flows and to undertake a quantitative assessment as well. The segment of the Min River, stretching from the urban area of the Wenchuan County to the Yingxiu town, China, was selected as the study area. Geomorphologic characteristics, including elevation, distance to faults, seismic intensity, land cover, gradient, monthly precipitation, and lithostratigraphy, were determined as assessment factors. The method was applied and verified in three clusters of debris flow events from 2010 to 2019 in 37 debris flow catchments. The results indicate that the method is applicable for identifying the dynamic debris flow source areas in earthquake-affected regions with a high accuracy of over 87% and a refined resolution of 30 m. This study finds that the sediment supply types have changed since 2019, that is, the sediment supply from Wenchuan earthquake-induced landslide deposit zones occupied by the debris flow-prone area has dropped from an average of 95.9% in 2013 to approximately 44.7% in 2019. Still, a large number of coseismic landslide deposits exist in the debris flow basins; the probability of debris flow source areas could thus be used as an important criterion for evaluating the long-term evolution of landslides and subsequent debris flow activities in earthquake-affected regions. [ABSTRACT FROM AUTHOR]

Due to being lightweight, fine-grained sediments easily flow with water and thus amplify the destructive effect of debris flow hazards. In such hazards, water content and shear strength are key inter-controlled factors relating to the stability of fine-grained sediments and thus control the density, scale, and danger of debris flow hazards. Although the correlation between water content and sediment stability has been studied, there are still some issues to be solved: what is the changing trend of shear strength with increasing water content? What is the water content spatial distribution pattern of fine-grained sediments in debris flow? What is the role/impact of this pattern on debris flow hazards prevention? Therefore, the objective of this research is to show the spatial distribution pattern of water content and establish a correlation between the water content and the shear strength of fine-grained sediments to provide a scientific basis for debris flow hazard prevention. Taking the Beichuan debris flow for our study, with a length of 37.6 km, and a 341 km2 study area, the results show that (1) the average water content shows an increasing trend, from 9.9% in the upstream of the river (SP01–SP05) to 21.7% in the downstream of the river (SP13–SP15). (2) When unsaturated, the correlation between the water content and shear strength is determined by combining the cohesion, normal stress, and internal friction angle; when saturated, the water content is negatively correlated with shear strength. (3) Water content and shear strength are the key inter-controlled factors relating to the stability of fine-grained sediments, and the water content distribution pattern of this research indicates the key locations that require attention: locations with high water content in the downstream river or with high curvature, which is of some significance for debris flow hazard prevention. [ABSTRACT FROM AUTHOR]

Debris flow hazards are often interpreted through back-calculated simulation analysis or empirical methods. The mobility of a debris flow is greatly influenced by mechanical and hydrological parameters. The strength parameters play important roles in the debris flow initiation and flow stages. In particular, the rheological parameters of yield strength and plastic viscosity directly affect the debris flow runout distance and velocity. One of the most important parameters to consider when evaluating debris flow hazards is the shear strength. This strength is called the residual shear strength in the failure stage and the yield strength in the post-failure stage. The residual shear strength obtained from ring shear tests can be related to the initiation of mass movements; the yield strength obtained from rheological tests can be related to the mobilization of debris flows. The residual shear stresses obtained from ring shear tests of weathered soils typically range between 10 and 100 kPa and strongly depend on the normal stress and shear velocity. When progressive slope failure (i.e., strain-softening behavior) occurs at a relatively shallow slope depth (e.g., < 1 m), the soil strength ranges from approximately 5–10 kPa. If the liquid limit state (i.e., solid‒liquid transition) is reached, the shear strength of the soil is approximately 2 kPa. Once the soil fails and mixes with ambient water along the slip surface, the yield strength decreases dramatically, resulting in high mobilization. A suggestion on how strength parameters can be applied to estimate debris flow mobility is presented by considering the 2011 Miryang debris flow, which occurred in weathered soil deposits in Miryang city, Republic of Korea. The best approach for debris flow yield strength estimation would be to consider the residual shear strength in the initiation stage, the yield strength in the flow stage, and the reduction in yield strength with the entrainment effect of the flow in the rapid fluidization stage. [ABSTRACT FROM AUTHOR]

Fine-grained sediments in debris flows refer to Quaternary sediments with grain sizes smaller than 2 mm. Their stability is closely related to the initial water threshold that triggers the debris flows and thus controls the density, scale, and damage of the debris flows. Based on this, they play a key "probe" role in early warnings of debris flows. Studies on fine-grained sediment stability are related to the accuracy and efficiency of early warnings of debris flows and thus play an important role in ensuring the safety of people and property. There have been some studies on fine-grained sediment stability in debris flows, but no one has carried out a systematic analysis and summary of this field. Therefore, in response to the urgent need for high-precision early warnings of debris flows, firstly, we review the current research on the aspects of fine-grained sediment stability, initiation, triggering, physical properties, hyperspectral remote sensing, and early warning systems; secondly, we summarize the main problems related to high-precision early warnings of debris flow hazards; and finally, we outline the future directions of research on fine-grained sediment stability in debris flows. [ABSTRACT FROM AUTHOR]

The establishment of a quantitative mudslide susceptibility evaluation method is of great significance for the prevention and control of mudslide disasters. Through the detailed survey and data compilation of 130 mudslide ditches in Hebei Province, the regional characteristics of mudslides in Hebei Province were analyzed and summarized. On this basis, evaluation factors were selected, the weights of evaluation factors were determined by introducing random forest classification method, the quantitative relationship between evaluation factors and mudslide susceptibility level was established by using Gaussian forward cloud model, and finally, the rationality of the new method was proved by engineering examples. The study shows that the mudflow hazard sites in western and northeastern Hebei Province are surrounded by 600 mm and 700 mm annual rainfall contours, respectively, while the mudflow hazard sites in northern areas are mostly located between 400 mm and 500 mm annual rainfall contours. The key factors of debris flow formation in Hebei Province are rainfall intensity, catchment area, loose material storage along the gully, slope of the gully bank, relative height difference of the watershed and specific drop of the gully. The type of debris flow in Hebei Province is mainly small and medium-sized gully storm-water and rock flow. The engineering example analysis shows that the evaluation results of the cloud model evaluation method of debris flow susceptibility based on random forest empowerment are consistent with the actual situation. [ABSTRACT FROM AUTHOR]

In this study, a novel debris flow resisting structure is proposed that incorporates negative Poisson's ratio (NPR) cables to unite a flexible net and a rigid barrier; this structure is referred to as the NPR barrier. The NPR barrier attempts to utilize the mechanical properties of the NPR cable—the constant resistance and large deformation—to convert the impact into particle friction resistance and support force. NPR cables can effectively improve the performance of the resisting barrier. To investigate the mechanical response of an NPR barrier, physical experiments are conducted on a debris flow impacting an NPR barrier at two distances with four volume fractions. The experimental results reveal that the impact model of a debris flow with an NPR barrier is a hybrid model that simultaneously incorporates both runup and pileup mechanisms. During the buffering, run-up, and backflow-depositional stages of the debris flow, the NPR cables correspondingly demonstrate a sharp increase in resistance, slight decrease in resistance, and constant resistance, respectively, effectively transforming the impact into resistance. The relationship between the buffer force and impact force exhibits an inverse correlation as the material volume fraction increases. When the material volume fraction increases from 40 to 70%, the buffer force significantly increases by 73.4%, and the impact force substantially decreases by 35.6%. Finally, the calculation methods for the impact force, NPR cable tension, and buffer force are discussed. This study represents an attempt to generate novel insights into the structural optimization of debris flow control systems. Highlights: A novel debris flow barrier, which incorporates Negative Poisson's ratio (NPR) cables, a flexible net, and a rigid barrier, is proposed and referred to as the NPR-anchored barrier (NPR barrier). The impact model of a debris flow with an NPR barrier is a hybrid model that simultaneously integrates both run-up and pile-up mechanisms. The NPR barrier utilizes the constant resistance and large deformation properties of the NPR cable to achieve a sustained equilibrium of impact load and to enhance the efficiency of dissipating impact energy. The mechanical response properties of the NPR barrier have been validated through physical experiments and mechanical calculation analyses. [ABSTRACT FROM AUTHOR]