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Suction stress is critical for understanding the hydrological and mechanical behavior of unsaturated soils in construction and engineering. Many soils encountered in these fields exhibit layering due to geological sedimentation or artificial reinforcement. This study establishes the vertical distributions of matric suction and degree of saturation for layered soils under one-dimensional (1D) steady-state seepage, using the Darcy law and constitutive relationships of unsaturated soils. A closed-form suction stress is derived for an arbitrary number of layers and soil types. Hypothetical layered soils with varying hydraulic properties at four infiltration rates are assessed. Results show that soil stratification affects the suction stress profiles, with the impact depending on infiltration rates, soil configuration, and layer thickness. Abrupt variations in suction stress occur at most layered interfaces due to differences in permeability between adjacent layers. The suction stress profiles can be used to evaluate the earth pressure and stability of layered slopes under seepage conditions. Several case studies of multi-layered slope failures in Southern Italy are presented to demonstrate the suitability of the proposed framework for evaluating the stability of layered slopes under rainfall conditions. [ABSTRACT FROM AUTHOR]

The Mediterranean region is increasingly experiencing intense and short-term rainfall, whose effects on the ground trigger widespread and quickly evolving phenomena including debris flows and shallow landslides which cause damage to buildings and infrastructure and occasionally even loss of life. In this research, we focus on the central Mediterranean in an area exposed to high-intensity rainfall that impacts small catchments which have been intensively anthropogenically modified through the years. The Portofino Promontory is characterized by a high cultural and landscape value where nature and historical anthropogenic landforms and signs coexist. The Promontory attracts tourists from all over the world, but it is exposed to a high number of hazards related to debris–mud flow processes that may impact cultural heritage, tourism facilities and infrastructure. In addition, the ancient man-made terraces that are widespread along the Promontory's slopes may play the role of being a source for shallow landslides, as this similarly happens in many Mediterranean regions. In 2011, heavy rainfall impacted the similar landscape of the Cinque Terre, triggering hundreds of small mud–debris flows whose combined effect was devastating. To this end, a ground effects simulation was developed as part of the H2020 project RECONECT which aims to contribute to a European reference framework on nature-based solutions, based on the high-detail and -precision remote sensing data acquired within the project. The data allowed us to assess the triggering areas, the transport channel, the observed deposition zones and the interaction with the exposed elements before building a possible risk scenario. The simulation and the entire approach may be upscaled to many similar areas where shallow landslide hazards originating from man-made terraces threatens buildings, cultural heritage, tourism facilities and infrastructure. [ABSTRACT FROM AUTHOR]

An extreme rainstorm hit Fuyang District, Zhejiang Province, China, on 22 July 2023. A record-breaking 320 mm of rain fell in less than 48 h. In the early evening of 22 July, more than 145 shallow landslides emerged in a 20 km2 hilly area of Fuyang amid turbulent flash flooding and claimed five lives. Post-event field investigations and laboratory experiments were urgently carried out, targeting two geologically typical shallow landslides, to decipher the initiation mechanism and distributing features of the regionally distributed landslides. The main findings are summarized as follows: (1) The week-long rainfall preceding the event and the intense storm on 22 July are presumably primary triggers for the landslides. Besides rainfall, convergent topography of hollows may be another important factor influencing the initiation of landslides. (2) The dominant moso bamboo has an extensive and interconnected root system, which could significantly stabilize slopes by enhancing soil strength and restricting cracks. (3) The sedimentary Heshangzhen Group area is more susceptible to landslides than the igneous Shuangxiwu Group area. Bedrock lithologies affect landslide distribution through controlling soil structures and properties to shape the hillslope hydrology and also through influencing landscape morphology. This study offers new evidence and insights into the lithological control on landslide initiation and distribution. [ABSTRACT FROM AUTHOR]

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]

Rainfall-triggered landslides pose a significant threat to both infrastructure and human lives, making it crucial to comprehend the factors that contribute to their occurrence. Specifically, understanding the relationship between these factors and the amount of rain that is necessary for triggering such events is essential for effective prediction and mitigation strategies. To address this issue, our study proposes a statistical modelling approach using machine learning, specifically the Random Forest algorithm, to investigate the connection between landslide predisposing factors and the daily rainfall intensity threshold necessary for the initiation of shallow landslides in Portugal. By leveraging a comprehensive dataset comprising historical landslide events, associated critical rainfall, and ten distinct landslide predisposing factors, we developed several models and used cross-validation technique to evaluate their performance. Our findings demonstrate that the Random Forest model effectively captures a relationship among landslide predisposing factors, critical daily rainfall intensity, and landslide occurrences. The models exhibit a satisfactory accuracy in assessing the spatial variation of critical daily rainfall intensity based on the predisposing factors, with a mean absolute percentage error (MAPE) of around 17%. Furthermore, the models provide valuable insights into the relative importance of various predisposing factors in landslide triggering, highlighting the significance of each factor. It was found that it takes higher rainfall intensity to trigger shallow landslides in the north region of Portugal when considering critical rainfall events of 3 and 13 days. Slope aspect, slope angle, and clay content in the soil are among the main predisposing factors used for defining the spatial variation of the daily rainfall intensity threshold. [ABSTRACT FROM AUTHOR]

To investigate the influence of tree roots on the triggering mechanism of shallow landslides, this study focused on a typical vegetation-covered cluster landslide in the Wuping area of China. A tree root profile investigation and a double-ring infiltration test were conducted. The undisturbed soil samples were collected for laboratory tests to measure the influence of tree vegetation on soil physical and hydraulic properties. The root reinforcement effect is limited by the depth of root distribution, with over 90% of the roots situated above the slip surface. The presence of roots increases the resistance of the soil to disintegration. The soil disintegration in the 0–80 cm layer was less than 25% after 24 h of water immersion and the soil undergoes complete disintegration at a depth of 180–200 cm within 120 s. Tree roots facilitate the infiltration of soil, and Ks at 0 m was 11.21 times than that at 2 m, and the interface between soils with roots and soils without roots may become a sliding surface. Under extreme rainfall conditions, the root system promotes water infiltration, accelerates the softening and disintegration of the soil on the sliding surface, which adversely affects the stability of landslides.

This study aims to obtain valuable insights into forest management that can reduce the risk of shallow landslides. We developed shallow landslide susceptibility maps (SLSMs) incorporating tree height and the relative spacing index as indicators of forest management for Cryptomeria japonica and Chamaecyparis obtusa plantations, focusing on the shallow landslides that occurred during the July 2012 Northern Kyushu heavy rain in the Aso region of Kumamoto Prefecture. We created SLSMs by developing a Random Forest model. The explanatory variables included tree height and relative spacing index, topography, geology, rainfall, and other factors totaling eleven factors. The area under the curve for the model was 0.94, indicating very high accuracy. The importance of the relative spacing index was comparatively low. The impact of forest management on shallow landslides was quantitatively assessed via a partial dependence plot for the relative spacing index. The results indicated that the relative spacing index that minimized the landslide probability was 23.7, below the cut-off value that distinguishes between landslide and non-landslide. In addition, the SLSMs indicated that implementing forest management with a uniform relative spacing index of 23.7 could reduce the ‘Very High' susceptibility area by 77.76 ha compared to the case without forest management. The threshold of the relative spacing index obtained in this study are crucial for future plantation forest management practices aimed at reducing the risk of shallow landslides.

Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and extensive blackouts. In this work, an application of the reworked version of the model proposed by Borga et al. and Tarolli et al. for rainfall-induced shallow landslide hazard assessment is presented. The revised model is called SLEM (Shallow Landslide Express Model) and is designed to merge in a closed-from equation the infinite slope stability with a simplified hydrogeological model. SLEM was written in Python language to automatise the parameter calculations, and a new strategy for evaluating the Dynamic Contributing Area (DCA) and its dependence on the initial soil moisture condition was included. The model was tested for the case study basin of Trebbia River, in the Emilia-Romagna region (Italy) which in the recent past experienced severe episodes of geo-hydrological hazards. The critical rainfall ratio (rcrit) able to trigger slope instability prediction was validated against the available local rainfall threshold curves, showing good performance skills. The rainfall return time (TR) was calculated from rcrit identifying the most hazardous area across the Trebbia basin with respect to the position of powerlines. TR was interpreted as an index of the magnitude of the geo-hydrological events considering the hypothesis of iso-frequency with precipitation. Thanks to its fast computing, the critical rainfall conditions, the temporal recurrence and the location of the most vulnerable powerlines are identified by the model. SLEM is designed to carry out risk analysis useful for defining infrastructure resilience plans and for implementing mitigation strategies against geo-hazards. [ABSTRACT FROM AUTHOR]

This study assessed root reinforcement on slopes influenced by various herbaceous species. The study examined the distribution, structural traits of these species, and their root systems, as well as their biomass. We established a quantitative model for evaluating root reinforcement at the soil interface influenced by different herbaceous colonizers. The focus was on a mining environment, specifically measuring root reinforcement at a dumpsite slope. The results showed that the herbaceous plants in the dumpsite included Candian fleabane (Conyza canadensis), Annual bluegrass (Poa annua), and Suaeda (Suaeda glauca), and the weights of the three herbaceous plants in descending order were Annual bluegrass, Candian fleabane, and Suaeda. Notably, the tensile strength of annual bluegrass roots peaked when diameters were less than 0.4 mm. Statistical analysis revealed significant variations in root tensile strength (p

Climate change brings with it phenomena such as large amounts of rainfall in short periods. Infiltration of rainwater into clayey soils is a common trigger for shallow landslides on slopes. In this way, numerous shallow landslides occur in the area of northern Croatia, and a characteristic example is the landslide “Orehovčak”. To stop the sliding of the destabilized slope, it was necessary to solve the drainage of water that infiltrates the landslide body. For this purpose, detailed geotechnical investigations and monitoring were conducted. Many data were collected at the investigation site, especially soil characteristics and groundwater fluctuations. The surface soil on the slope consists of highly plastic clay, and the sliding surface was created in contact with the solid subsoil of marl, the depth of which varies positionally. The analyses confirmed that water is a slip trigger. To solve the problem, excavations and installation of deep drains were performed. The slope safety factor confirms landslide stabilization, whose calculated value after rehabilitation was Fs = 1.645. Inclinometer readings carried out after remediation show that slope slippage stopped. This confirms that the presented remediation method is very applicable to shallow landslides in northern Croatia and similar landslides around the world.

The Mediterranean region is increasingly experiencing intense and short-term rainfall, whose effects on the ground trigger widespread and quickly evolving phenomena including debris flows and shallow landslides which cause damage to buildings and infrastructure and occasionally even loss of life. In this research, we focus on the central Mediterranean in an area exposed to high-intensity rainfall that impacts small catchments which have been intensively anthropogenically modified through the years. The Portofino Promontory is characterized by a high cultural and landscape value where nature and historical anthropogenic landforms and signs coexist. The Promontory attracts tourists from all over the world, but it is exposed to a high number of hazards related to debris–mud flow processes that may impact cultural heritage, tourism facilities and infrastructure. In addition, the ancient man-made terraces that are widespread along the Promontory’s slopes may play the role of being a source for shallow landslides, as this similarly happens in many Mediterranean regions. In 2011, heavy rainfall impacted the similar landscape of the Cinque Terre, triggering hundreds of small mud–debris flows whose combined effect was devastating. To this end, a ground effects simulation was developed as part of the H2020 project RECONECT which aims to contribute to a European reference framework on nature-based solutions, based on the high-detail and -precision remote sensing data acquired within the project. The data allowed us to assess the triggering areas, the transport channel, the observed deposition zones and the interaction with the exposed elements before building a possible risk scenario. The simulation and the entire approach may be upscaled to many similar areas where shallow landslide hazards originating from man-made terraces threatens buildings, cultural heritage, tourism facilities and infrastructure.

In this study, we analyzed the effect of forest damage caused by forest fires or shallow landslides on the rainfall thresholds needed to initiate bedload transport in mountain watersheds. Two bedload monitoring systems were used: a slot sampler and a hydrophone. These were installed in a forest fire-damaged site, a shallow landslide-damaged site, and a control site. A total of 199 effective rainfall-bedload data were collected from 2014 to 2016. Total rainfall amount (TR) and peak rainfall intensity (PRI) were found to be the most effective rainfall indices to predict bedload transport initiation. We also used linear functions to estimate percent threshold lines of the rainfall indices and used performance evaluations to select a representative threshold line for each site. As a result, the forest fire-damaged and shallow landslide-damaged sites had lower TR and PRI reference values than the control site, indicating that lower TR and PRI values can initiate bedload transport in damaged mountain forest areas. Although our study results may be limited by different characteristics between the study sites and insufficient data collection, it still indicates that forest damage caused by forest fires and shallow landslides affects bedload transport. Future studies are needed to further confirm these findings. [ABSTRACT FROM AUTHOR]

Uncertainties related to runout distances in shallow landslide analyses may not only affect lives but may also result in economic losses. Owing to the increase in shallow landslides, which are especially triggered by heavy rainfall, runout distances have been investigated to decipher whether applications of a functional runout distance are feasible. This paper aims to give insights into the modeling of the shallow landslide runout probability in Eocene flysch facies in the Western Black Sea region of Türkiye. There are two main stages in this study—which are dominated by empirical models, the detection of initiation points, and propagation—which help us to understand and visualize the possible runout distances in the study area. Shallow landslide initiation point determination using machine learning has a critical role in the ordered tasks in this study. Modified Holmgren and simplified friction-limited model (SFLM) parameters were applied to provide a good approximation of runout distances during the propagation stage using Flow-R software. The empirical model parameters suggested for debris flows and shallow landslides were investigated comparatively. The runout distance models had approximately the same performance depending on the debris flow and shallow landslide parameters. While the impacted total runout areas for the debris flow parameters were predicted to amount to approximately 146 km2, the impacted total runout areas for the shallow landslide parameters were estimated to be about 101 km2. Considering the inclusion of the RCP 4.5 and RCP 8.5 precipitation scenarios in the analyses, this also shows that the shallow landslide and debris flow runout distance impact areas will decrease. The investigation of runout distance analyses and the inclusion of the RCP scenarios in the runout analyses are highly intriguing for landslide researchers. [ABSTRACT FROM AUTHOR]

The southern Apuan Alps (Italy) are prone to rainfall-induced landslides. A first attempt to calculate rainfall thresholds was made in 2006 using non-statistical and repeatable methods for the 1975–2002 period. This research aims to update, validate, and compare the results of that attempt through different statistical approaches. Furthermore, a new dataset of rainfall and landslides from 2008 to 2016 was collected and analyzed by reconstructing the rainfall events via an automatic procedure. To obtain the rainfall thresholds in terms of the duration–intensity relationship, we applied three different statistical methods for the first time in this area: logistic regression (LR), quantile regression (QR), and least-squares linear fit (LSQ). The updated rainfall thresholds, obtained through statistical methods and related to the 1975–2002 dataset, resulted in little difference from the ones obtained with non-statistical methods and have similar efficiency values among themselves. The best one is provided by the LR, with a landslide probability of 0.55 (efficiency of 89.8%). The new rainfall thresholds, calculated by applying the three statistical methods on the dataset from 2008–2016, are similar to the 1975–2002 ones, except for the LR threshold, which exhibits a higher slope. This result confirms the validity of the thresholds obtained with the old database. [ABSTRACT FROM AUTHOR]

Climate change brings with it phenomena such as large amounts of rainfall in short periods. Infiltration of rainwater into clayey soils is a common trigger for shallow landslides on slopes. In this way, numerous shallow landslides occur in the area of northern Croatia, and a characteristic example is the landslide "Orehovčak". To stop the sliding of the destabilized slope, it was necessary to solve the drainage of water that infiltrates the landslide body. For this purpose, detailed geotechnical investigations and monitoring were conducted. Many data were collected at the investigation site, especially soil characteristics and groundwater fluctuations. The surface soil on the slope consists of highly plastic clay, and the sliding surface was created in contact with the solid subsoil of marl, the depth of which varies positionally. The analyses confirmed that water is a slip trigger. To solve the problem, excavations and installation of deep drains were performed. The slope safety factor confirms landslide stabilization, whose calculated value after rehabilitation was Fs = 1.645. Inclinometer readings carried out after remediation show that slope slippage stopped. This confirms that the presented remediation method is very applicable to shallow landslides in northern Croatia and similar landslides around the world. [ABSTRACT FROM AUTHOR]

Extreme rainfall events pose a severe challenge to soil and water conservation, even in areas with high vegetation cover on the Loess Plateau. In this study, the artificial extreme rainfalls with cumulative rainfall of 270 mm and intensity of 60 mm · hr−1 were conducted on in‐situ experimental plots (20 × 2.5 m) on a loess gully–slope with gradients of 35°–40° that were treated with different grass coverage: (0%, 30%–40%, 70%–80%, >90%). The ephemeral gully/rill and shallow landslide occurred in plots were analyzed. Revegetation changed the erosion type on gully–slope, reducing gully erosion but promoting shallow landslide due to the change from infiltration–excess runoff to saturation–excess runoff. Under grass coverage of >90%, over 95% of rainfall seeped into the soil, and subsurface flow was generated due to the lower saturated hydraulic conductivity of underlying soil, which increased the possibility of landslides. The average erosion rate (0.36–3.29 g · m−2 min−1; no obvious erosion) in plots with 70%–80% coverage was 95.5% lower than that in bare land plots (27.8–47.5 g · m−2 min−1; ephemeral gully erosion), while due to landslides the average erosion rate in plots with >90% coverage (135.1–184.3 g · m−2 min−1) was 86.5 times higher than that in plots with 70%–80%. For grass, a coverage of 70%–80% was most effective in preventing soil erosion, controlling gully erosion and preventing landslides under extreme rainfall. These results deepen the understanding of the complex relationship between vegetation, gully erosion, and landslides in ecologically sensitive areas. Key Points: Vegetation changed the erosion type on slope from water erosion to gravity erosionHigh‐coverage vegetation promoted shallow landslides under extreme rainfallFor grass cover, a coverage of 70%–80% was most effective in preventing soil erosion [ABSTRACT FROM AUTHOR]

Widespread shallow landslides typically result in the loss of productive soils and grasslands. Deposits of landslide tails have received much attention, while the severity of rill erosion on the landslide scar is generally neglected or underestimated. Thirty‐five rainfall‐induced shallow landslides were selected on Lishi (finer texture) and Malan loess (coarser texture) on the hilly and gully Loess Plateau, China. The rill erosion intensity and rill morphological parameters of these landslide scars were measured by on‐site investigation 3 years after the landslides. Landslide characteristics were investigated by unmanned aerial vehicle photogrammetry, and soil properties were also evaluated. We found that landslide scars suffered rill erosion for more than 8 years after landslides. Rill erosion intensities of the Lishi (22.91 × 103 t km−2) and Malan landslides (16.90 × 103 t km−2) in 3 years occupied 11.43% of the landslide deposit amounts. The structural equation model demonstrated that catchment area, soil bulk density, soil organic matter, water stable aggregate content (WSA), and sand content explained 87% of the variance in rill intensity through paths of rill depth, width, and distribution. Additionally, the negative effect of rill distribution on rill depth led to the unusual result that coarse soils with low WSA had low rill erosion intensities. In summary, the rill erosion of shallow landslide scars reached a non‐negligible value. The effect of initial rill distribution masked the effect of soil properties on rill intensity. Therefore, this study casts fresh insight into the sediment source of landslides, increasing theoretical support for landslide control strategies. [ABSTRACT FROM AUTHOR]

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. This paper presents an empirical model 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 images 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 landslides (or hill slope debris flows) 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]

Shrub species Caragana korshinskii Kom. dominates slope protection and soil and water conservation in the loess area of the northeastern Qinghai–Tibet Plateau. However, the root anchoring mechanism and the effects of soil consolidation and slope protection of this shrub species remain unclear. This study aimed to elucidate the anchoring mechanism of roots of the C. korshinskii roots and establish a calculation model to evaluate their contribution to the stability of shallow loess slopes. C. korshinskii plants with an 11-year growth period were selected as the study subject. The anchoring force of C. korshinskii roots was determined through in-situ excavation tests, in-situ root pullout tests, and theoretical analysis, along with their impact on the stability of shallow loess soil slopes. The results showed that, due to the absence of a “bolt head” structure on the root surface, it was reasonable to consider the anchoring force provided by the roots as the minimum value between the maximum pullout resistance of the roots below the sliding surface and the anchoring reaction force of the roots above the sliding surface, based on the geometric characteristics of the sliding surface. When the roots of an 11-year-old C. korshinskii roots were anchored on different sliding blocks of a shallow landslide with a maximum thickness of 2 meters, the stability coefficient of the potential sliding surface increased by 0.020% to 0.408%. When the roots of a single plant were anchored in the middle and upper parts of the potential sliding surface, the stability coefficient of the potential sliding surface was relatively higher than when the plant roots were anchored at the top and bottom positions. Moreover, when four C. korshinskii roots were anchored to the shallow landslide with a row spacing of two sliding blocks (approximately 3 m), the stability coefficient of the potential sliding surface increased by 1.035% to 1.111%, which was significantly higher than when a single C. korshinskii root was anchored (P

Abstract This study aimed to develop a physical-based approach for predicting the spatial likelihood of shallow landslides at the regional scale in a transition zone with extreme topography. Shallow landslide susceptibility study in an area with diverse vegetation types as well as distinctive geographic factors (such as steep terrain, fractured rocks, and joints) that dominate the occurrence of shallow landslides is challenging. This article presents a novel methodology for comprehensively assessing shallow landslide susceptibility, taking into account both the positive and negative impacts of plants. This includes considering the positive effects of vegetation canopy interception and plant root reinforcement, as well as the negative effects of plant gravity loading and preferential flow of root systems. This approach was applied to simulate the regional-scale shallow landslide susceptibility in the Dadu River Basin, a transition zone with rapidly changing terrain, uplifting from the Sichuan Plain to the Qinghai–Tibet Plateau. The research findings suggest that: (1) The proposed methodology is effective and capable of assessing shallow landslide susceptibility in the study area; (2) the proposed model performs better than the traditional pseudo-static analysis method (TPSA) model, with 9.93% higher accuracy and 5.59% higher area under the curve; and (3) when the ratio of vegetation weight loads to unstable soil mass weight is high, an increase in vegetation biomass tends to be advantageous for slope stability. The study also mapped the spatial distribution of shallow landslide susceptibility in the study area, which can be used in disaster prevention, mitigation, and risk management.

Land cover changes in mountainous regions are potential precursors to landslide disasters. However, the effects of past long-term land cover changes on the characteristics of recent landslides remains underexplored. We studied land cover evolution over a 56-year period on Omishima Island in western Japan to examine the spatial relations of landslides in the July 2018 storm event based on rainfall, land cover trajectories, and topography. We generated land cover maps for 1962, 1981, and 2018 by aerial photo interpretation. We also identified 512 new landslides. Based on 47-year precipitation records, we estimated the return periods of 1- to 264-h rainfalls during the storm using the generalised extreme value (GEV) distributions. Return periods showed wide variation when the derived GEV distributions were applied to 1-km grid rainfall distributions. Despite such pronounced spatial variations in rainfall, we did not observe a clear correlation between rainfall intensity and landslide distribution. In contrast, land cover trajectories had a pronounced effect on landslide occurrence. Landslides were more concentrated on slopes that experienced land cover changes after 1962. A comparison of slopes on farmland developed between 1962 and 1981 (mainly citrus orchards) indicated that landslide density and area ratio were significantly lower on slopes that had reverted to forests than on those remaining as farmland. However, the values of the reforested slopes exceeded those of forests and farmlands that remained since before 1962. Our geospatial analysis revealed that even if the field had shifted to forests, the effects of reduced slope stability due to orchard development had remained for at least 37 years. This suggested that the impacts of converting forests to orchards last longer than harvesting in managed plantation forests. [ABSTRACT FROM AUTHOR]

The purpose of this study is to experimentally estimate the criteria for shallow landslide occurrence using hydrological indicators such as matric suction and volumetric water content for representative soils with the different geological conditions in which landslides frequently occur in South Korea. To investigate the detection criteria for shallow landslides, a series of landslide model tests are conducted using weathered soils obtained from regions of granite, gneiss, and mudstone where landslides occur. A landslide model test device, which includes a rainfall simulator, a slope model flume, and a measurement system with sensors, is developed to simulate shallow landslides that generally occur on natural slopes during rainfall. Based on the results of the model test, an infinite slope stability analysis considering the suction stress of unsaturated soil is applied to analyze changes in the safety factor of the slopes according to rainfall. Using the domestic standard of slope design used in South Korea, landslide detection criteria based on the safety factor of slopes are recommended as 1.3 for attention-level alerts and 1.0 for warning-level alerts. The matric suction corresponding to the attention and warning levels is defined as the critical matric suction, and the volumetric water content corresponding to the critical matric suction on the soil‒water characteristic curve (SWCC) is defined as the critical volumetric water content. The proposed critical matric suctions and critical volumetric water contents can potentially be used as basic data to detect the time of shallow landslide occurrence and issue a landslide early warning. [ABSTRACT FROM AUTHOR]

Landslide hazard assessment is an important component of risk management and land-use planning. This study aims to investigate the application of a physically-based model named after the fast shallow landslide assessment model (FSLAM) to rainfall-triggered landslide hazard assessment. In August 2015, a total of 123 landslides induced by Typhoon Soudelor in Wenzhou City, southeastern China, was taken as an example. Five input raster files (elevation, soil types, vegetation, antecedent rainfall, event rainfall) and two parameter files regarding soil properties and vegetation were determined. Considering the randomness and uncertainty of soil and vegetation parameters on the regional scale, FSLAM model computes the probability of failure (PoF) by using random parameters inputs. Finally, the landslide hazard map was generated for the study area to reflect the landslide risk. The results showed that FSLAM could accurately capture the effect of rainfall on PoF of slopes, and more than 70% of the landslide were identified in very high/high hazard zones. The accuracy of the receiver operating characteristic (ROC) reached 0.720, which was higher than that of the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model (0.620). Regarding the computational time, FSLAM had better efficiency, and the consuming time was 1/25 compared with TRIGRS. [ABSTRACT FROM AUTHOR]

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In this work, we evaluated the influence of root structure on shallow landslide distribution. Root density measurements were acquired in the field and the corresponding root cohesion was estimated. Data were acquired from 150 hillslope deposit trenches dug in areas either devoid or affected by shallow landslides within the Garfagnana Valley (northern Tuscany, Italy). Results highlighted a correlation between the root reinforcement and the location of measurement sites. Namely, lower root density was detected within shallow landslides, with respect to neighboring areas. Root area ratio (RAR) data allowed us to estimate root cohesion by the application of the revised version of the Wu and Waldron Model. Then, we propose a new method for the assimilation of the lateral root reinforcement into the infinite slope model and the limit equilibrium approach by introducing the equivalent root cohesion parameter. The results fall within the range of root cohesion values adopted in most of the physically based shallow landslide susceptibility models known in the literature (mean values ranging between ca. 2 and 3 kPa). Moreover, the results are in line with the scientific literature that has demonstrated the link between root mechanical properties, spatial variability of root reinforcement, and shallow landslide locations. [ABSTRACT FROM AUTHOR]

This study aims to model a probabilistic-based reliability assessment of the gridded rainfall thresholds for shallow landslide occurrence (RA_GRTE_LS) to quantify the effect of the uncertainty of rainfall in time and space on the rainfall thresholds under consideration of local soil properties. The proposed RA_GRTE_LS model is developed by coupling the uncertainty analysis with the logistic regression equation using a significant number of the landslide-derived rainfall thresholds of the specific warning times. The 30 historical gridded hourly rainstorms at 10 study grids in the study area (Jhuokou River watershed) are used in 1,000 simulations of rainfall-induced shallow landslides under an assumption of the soil layer of 310 cm. The results reveal that the shallow landslide in the study area probably occurs at the time step of less than the 36th hour around the bottom of the soil layer (about 275 cm) during a rainstorm; also, using the proposed RA_GRTE_LS model, the resulting rainfall thresholds and quantified reliabilities, especially for the warning time of less than 18 h, exhibit a sizeable varying trend in space due to the variations in rainfall and soil properties; accordingly, the short-term rainfall thresholds for shallow landslide occurrence could be locally determined under acceptable reliability. HIGHLIGHTS This study aims to model a probabilistic-based reliability assessment of the gridded rainfall threshold estimates for shallow landslide occurrence.; The resulting rainfall thresholds and quantified reliabilities exhibit a sizeable varying trend in space due to the spatial variations in rainfall and soil properties.; The short-term thresholds for shallow landslides could be locally determined under acceptable reliability.;

Landscapes disturbed by shallow landslides present several residual risks. For example, residual soils on sliding surfaces may lead to the re-occurrence of shallow landslides, and landslide deposits on valley floors may introduce multiple hazards associated with river blocking or landslide damming. Despite such risks, few studies have investigated the residual risks following shallow landslides, and thus, no methodology has been established for assessing such risks. In this study, we combined portable cone penetration test (PCPT) and electrical resistivity tomography (ERT) to investigate the post-event risks associated with a landslide scar resulting from the 2018 Hokkaido Eastern Iburi earthquake (HEIE) in Japan. The multi-point PCPT identified the interface between a weak volcanic soil layer and underlying weathered sedimentary rocks. This interface exhibited an abrupt spatial change in resistivity, ranging from 20 to 100 Ωm. The thickness of the residual soil layer was 0.3–3.2 m and that of the landslide deposit exceeded 2.0 m. An infinite-slope stability analysis was performed to predict the re-occurrence of shallow landslides due to a lower intensity earthquake than that of HEIE in this region. Considering the area affected by the HEIE and the physical properties of soil layers, our findings imply a widespread risk of re-occurrence of shallow landslides over an area of 20 km × 20 km. Although the areal coverage of the combined ERT/PCPT method needs to be extended, it is effective for assessing the residual risks associated with shallow landslides. [ABSTRACT FROM AUTHOR]

Landslides triggered by heavy rainfall pose significant threats to human settlements and infrastructure in temperate and equatorial climate regions. This study focuses on the development of the Open Landslide Project (OLP), an open source landslide inventory aimed at facilitating geostatistical analyses and landslide risk management. Using a multidisciplinary approach and open source, multisatellite imagery data, more than 3000 landslides triggered by the extreme rainfall of autumn 2019 in northwestern Italy were systematically mapped. The inventory creation process followed well-defined criteria and underwent rigorous validation to ensure accuracy and reliability. The dataset's suitability was confirmed through multivariate correlation and Double Pareto probably density function. The OLP inventory effectiveness in assessing landslide risks was proved by the development of a landslide susceptibility model using binary logistic regression. The analysis of rainfall and lithology revealed that regions with lower rainfall levels experienced a higher occurrence of landslides compared to areas with higher peak rainfall. This was attributed to the response of the lithological composition to rainfalls. The findings of this research contribute to the understanding and management of landslide risks in anthropized climate regions. The OLP has proven to be a valuable resource for future geostatistical analysis. [ABSTRACT FROM AUTHOR]

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Shallow landslide occurrence is most common in rainy season in the form of flow of debris, costs heavy damages to the infrastructure and human lives. Early prediction framework of such disaster can help to mitigate such damages. The present work deals with prediction framework for initiation of debris flow, which is developed and validated with real case study. In order to test reliability of prediction framework, back analysis of very recent landslide debris flow accrued in the study area, Taliye village of Konkan region of Maharashtra, India on 22 July 2021 was carried out. Simulation results of landslide stability were compared with the leaky barrel-based rainfall-water saturation algorithm. Relations of landslide stability with the water saturation were established through physically based approach using Geo-Studio analysis module. Leaky barrel algorithm was used for study location for monitoring effect of rainfall on water saturation. The result confirms the good predictability of landslide occurrence through a developed early prediction framework. The methodological framework was presented in this paper for prediction of shallow landslide occurrence and recommended for real-time monitoring of landslide prone locations. [ABSTRACT FROM AUTHOR]

Heavy rainfall induces shallow landslides in the mountainous areas of China. There is a need for regional slope stability prediction to reduce the damage to infrastructure, residents, and the economy. This study attempts to demarcate areas prone to rainfall-induced shallow landslides using the transient rainfall infiltration and grid-based slope stability (TRIGRS) model under different rainfall conditions. After inputting the engineering geological and geotechnical characteristic data of the area in China, the slope stability was simulated and verified by a deformation monitoring landslide. The slope stability gradually declined under the influence of precipitation from 5–8 July 2021. Slope stability gradually decreased under the predicted rainfall intensity of 60 mm/d for 6 days. The percentage of the slope area with a factor of safety (FS) less than 1.0 increased from 0.00% (1 d) to 3.18% (6 d). The study results could be used for hazards mitigation in this region. [ABSTRACT FROM AUTHOR]

The simple-shear condition is closer to reality than the direct-shear condition for simulating the mechanical behavior of vegetated soil slope under shallow failure. However, study on simple-shear characteristics for vegetated slope is still insufficient, and there lacks intuitive comparison of characteristics between these two shear conditions. In this study, large-scale simple-shear and direct-shear experiments were conducted on soil permeated by roots of Amorpha fruticosa to investigate the shear strength and stiffness. The stress-displacement relationship of each sample was obtained and further normalized to unify the influence of root content. The results reveal that the direct-shear condition overestimates the shear strength of root-permeated soils (by 41%) and thus the estimation of slope stability based on the parameters of direct-shear condition is not conservative. Furthermore, the initial stiffness of root-permeated soil under simple-shear condition is 34% lower than that under direct-shear condition. The higher strength and stiffness under direct-shear condition are caused by the following reasons: the shear plane does not have the lowest strength, the shear area is decreasing, and the shear zone is thinner. The significant deformation (lower stiffness) revealed by the simple-shear condition facilitates the application of early warning for vegetated shallow landslides. [ABSTRACT FROM AUTHOR]

This study aimed to develop a physical-based approach for predicting the spatial likelihood of shallow landslides at the regional scale in a transition zone with extreme topography. Shallow landslide susceptibility study in an area with diverse vegetation types as well as distinctive geographic factors (such as steep terrain, fractured rocks, and joints) that dominate the occurrence of shallow landslides is challenging. This article presents a novel methodology for comprehensively assessing shallow landslide susceptibility, taking into account both the positive and negative impacts of plants. This includes considering the positive effects of vegetation canopy interception and plant root reinforcement, as well as the negative effects of plant gravity loading and preferential flow of root systems. This approach was applied to simulate the regional-scale shallow landslide susceptibility in the Dadu River Basin, a transition zone with rapidly changing terrain, uplifting from the Sichuan Plain to the Qinghai–Tibet Plateau. The research findings suggest that: (1) The proposed methodology is effective and capable of assessing shallow landslide susceptibility in the study area; (2) the proposed model performs better than the traditional pseudo-static analysis method (TPSA) model, with 9.93% higher accuracy and 5.59% higher area under the curve; and (3) when the ratio of vegetation weight loads to unstable soil mass weight is high, an increase in vegetation biomass tends to be advantageous for slope stability. The study also mapped the spatial distribution of shallow landslide susceptibility in the study area, which can be used in disaster prevention, mitigation, and risk management. [ABSTRACT FROM AUTHOR]

Key points Relationship between soil electrical resistivity and hydraulic conductivity were examined for assessment of lithology inducing shallow-landslide. Soil electrical resistivity delineated a boundary between two contrasting resistive and conductive lithologies at 4 m depth. Strong correlation ranged between R2 = 0.9153 to 0.9702 were observed between soil resistivity and hydraulic conductivity for the soil samples examined. The conductive lithology with low hydraulic conductivity below 4 m depth was responsible for the occurrences of the shallow-landslides.

Landslides are some of the most destructive and recurrent natural hazards worldwide. Landslides are triggered by natural phenomena such as extreme rainfall and earthquakes, causing human and economic losses. A rapid response to landslide events is necessary to assess damage mitigation and save lives and property. This study developed a landslide detection model using differential spectral indices and amplitude ratio changes with a classification and regression tree (CART), aiming to detect landslide scars after the occurrence of these events in Asian regions for testing different environment condition. The multi-temporal SAR and optical stack images were pre-processed to reduce speckle noise, seasonal noise, and atmospheric noise. This study explored change detection approaches with a minimum threshold of amplitude ratio change (Aratio), using Sentinel−1 images and the relative difference in the normalized difference vegetation index (rdNDVI), differential bare soil index (dBSI), and differential brightness index (dBI) was obtained using Sentinel−2 images. The accuracy of the model was examined by F1-scores. The accuracy of the model for landslide detection was considered moderately good to excellent. As a result of the landslide detection model, amplitude ratio change detection improved the model as revealed by the F1-scores. Moreover, this study found that differential spectral indices could be used to classify the types of landslides (deep-seated and shallow landslides) according to the level of surface changes and texture of the collapsed material after landslide events. [ABSTRACT FROM AUTHOR]

The work proposes a procedure to build an early warning predictive tool to assess the occurrence of rainfall-induced landslides in silty volcanic covers. The procedure combines both an empirically and a physically based tool used sequentially: the former is designed to be calibrated using older, highly sized and coarser rainfall data, and the latter to interpret recent and finer weather data. Both approaches need to be informed by a common experimental reference summarising the rainfall history, the rainfall point, defined as the couple made of antecedent 4-month rainfall cumulative value (C4m) and last-persistent event (CPLE). The empirical approach aims to identify if, in the (C4m–CPLE) plane, the rainfall point falls in a ‘safe’ or ‘potentially unsafe’ zone where the two distinct regions are built by interpreting rainfall data associated or not with landslide events. In the physically based approach, evaporation and runoff are estimated to refine the assessment of ‘effective’ rainfall points. The resulting transformed rainfall point (C′4 m, C′PLE) is turned into a prediction of the suction level at the mid-depth assumed as a ‘reference’ for the entire cover. Such value is compared with a suction threshold empirically defined. Suction levels prediction is developed by computing in the C′4 m–C′PLE plane the iso-suction lines generated by several rainfall scenarios. The accuracy of the developed procedure is comparable with state-of-the-art literature or operational approaches, properly identifying landslide case events and minimising the number of false alarms. Furthermore, it can inform the preparedness stages more effectively, explicitly accounting for the antecedent slope wetness stage and how it could be far from the incipient slope failure conditions. The developed procedure takes into account the effects of evaporation and antecedent rainfalls that, in dry periods, lead to very dry conditions in the subsoil, making even significant rainfall events inconsequential. Conversely, other procedures already operating in LEWS or highly considered literature background overestimate the effects of rainfalls during dry periods. The developed procedure delivers a simple but robust way to derive landslide thresholds based on the interpretation of past rainfall histories. At the same time, literature methods often require sophisticated approaches to retrieve thresholds. [ABSTRACT FROM AUTHOR]

Timber harvesting and related management practices associated with industrial timberlands have changed dramatically in the last two decades. Industrial timberlands are now more carefully assessed and mitigated. Recent studies of mass wasting in northern California included a review of historical aerial photographs from the early 1940s through 2016 and field measurements of nearly 3,000 shallow landslides on industrially managed timberlands. Significant improvements have been seen in management practices over time that include but are not limited to reduced harvest unit sizes, increased streamside tree retention, reduced road density, and improved road-building practices. These improvements are a result of a variety of sources such as evolving state regulations, voluntary conservation plans, and increased professional oversight. Subsequently, significant decreases in management-related erosion are being observed across the area included in this study. Observations show that improvements in management practices have positively affected regional mass wasting. In this investigation, significant changes have been noted in both causal mechanisms and landslide erosion rates. The study data shows that before the year 2000, nearly 85 percent of landslide-related erosion was determined to be the result of historical logging, either by harvesting or from roads (generally poor design and/or location). Shallow landslide erosion rates have varied over the duration of time reviewed for this study, peaking in the 1970s. Since 2000, erosion rates across the study area have decreased to 20 m3/km2/yr, which is a 92 percent reduction compared with the historical rate. [ABSTRACT FROM AUTHOR]

Uncertainties related to runout distances in shallow landslide analyses may not only affect lives but may also result in economic losses. Owing to the increase in shallow landslides, which are especially triggered by heavy rainfall, runout distances have been investigated to decipher whether applications of a functional runout distance are feasible. This paper aims to give insights into the modeling of the shallow landslide runout probability in Eocene flysch facies in the Western Black Sea region of Türkiye. There are two main stages in this study—which are dominated by empirical models, the detection of initiation points, and propagation—which help us to understand and visualize the possible runout distances in the study area. Shallow landslide initiation point determination using machine learning has a critical role in the ordered tasks in this study. Modified Holmgren and simplified friction-limited model (SFLM) parameters were applied to provide a good approximation of runout distances during the propagation stage using Flow-R software. The empirical model parameters suggested for debris flows and shallow landslides were investigated comparatively. The runout distance models had approximately the same performance depending on the debris flow and shallow landslide parameters. While the impacted total runout areas for the debris flow parameters were predicted to amount to approximately 146 km2, the impacted total runout areas for the shallow landslide parameters were estimated to be about 101 km2. Considering the inclusion of the RCP 4.5 and RCP 8.5 precipitation scenarios in the analyses, this also shows that the shallow landslide and debris flow runout distance impact areas will decrease. The investigation of runout distance analyses and the inclusion of the RCP scenarios in the runout analyses are highly intriguing for landslide researchers.

Abstract A 6.6-Mw earthquake struck the Iburi region of Hokkaido, Japan, in 2018, triggering massive landslides. Most of these landslides were shallow and occurred mostly in the Atsuma and Abira towns. Ta-c and Ta-d tephra layers have been found in the Towa landslide at Atsuma from the Tarumai volcano, while Ta-d, En-a, and Spfa-1 tephra layers have been found in the Mizuho landslide at Abira from the Tarumai and Eniwa volcanos, as well as the Shikotsu caldera. Field observations from previous studies revealed that the sliding layers were located in the Ta-d and En-a layers at the Towa and Mizuho landslides, respectively. Unlike previous research on earthquake-induced landslides, which were investigated using mechanical properties, this study investigates the characteristics of physical properties, saturated permeability properties, and content of clay minerals on sliding and surrounding tephra layers. Results from this study reveal that the physical properties of sliding layers from two landslides demonstrated the same characteristics: non-plastic soil with a low density of soil particles, void ratio, and dry density; these characteristics could influence earthquake-induced landslides. It also reveals a relationship between the plasticity chart and the age of tephra materials, including the relationship between the weathering process and density of soil particles and the dissimilarity in characteristics of saturated permeability properties in tephra materials.

Slope disasters often include soil erosion and shallow landslides. These types of slope failure can occur in unsaturated soil. In this study, artificial rainfall is applied to a compacted soil slope in a laboratory to investigate the effects of rainfall intensity, initial moisture content and relative compaction on infiltration and failure behavior of an unsaturated soil slope subjected to rainfall infiltration. Soil moisture probes installed in the soil slope were used to monitor soil moisture content during the experiment. Test results show that the soil saturation at the toe of the slope was observed to be higher than other areas of the slope following the onset of rainfall. Gradually, the saturation advanced towards the crest, resulting in the formation of a wetting band along the slope surface. With increasing rainfall duration, the wetting band progressed further downwards along the slope. The failure of the slope began at the crest and junction of the slope, and the primary cause was soil erosion resulting from high-intensity rainfall. The most significant variable affecting infiltration behavior is relative compaction, followed by the initial moisture content of the compacted slope. During the experiment, the low hydraulic conductivity of the saturated soil caused most of the rainfall on the slope to become surface runoff, which minimized the impact of rainfall intensity on infiltration behavior. Specifically, the hydraulic conductivity of soil compacted at optimal moisture content and 90 R.C. is only 7.041 × 10-5 cm/sec or 2.53 mm/h, which is much lower than rainfall intensities of 80 mm/h and 160 mm/h. In addition, soil saturation contours facilitated visualization and quantification of the infiltration behavior of slopes, enabling a more detailed analysis of experimental results. These results help understand the behavior of unsaturated soil slopes under artificial rainfall conditions and aid in designing effective slope stabilization measures to prevent slope failure and minimize the risk of landslides. [ABSTRACT FROM AUTHOR]

We conduct an estimation of the soil thickness recovery time after the occurrence of shallow landslides, and elucidate landsliding recurrence period in the area underlain chiefly by the Neogene sedimentary rocks, the Tbmiya Hills, north of the Sendai Cit Northeast Japan. On the basis of soil genesis in the landslides occurring in 1986 and 1947-1961, and a power series regression by the least absolute value estimation, the recovery time is inferred to be approximately 100 to 250 years. While, from the rainfall records of the 4 meteorological stations in the vicinity of the investigated area, a wide range of values, from around 100 years to more than 1,000 years, can be calculated for the return period of the maximum 24-hour rainfall of the 1986 event, which triggered about 2,000 landslides or more. The occurrence of heavy rainfall, however, is essentially dominated by stochastic and random processes; thus consequently the recollapse at the same locality on slopes, is more strongly dependent on the soil thickness recovery which can generally be regarded as a time-series phenomenon. It is, therefore, appropriate to understand the recurrence period of shallow landslides based mainly on the recovery time. [ABSTRACT FROM AUTHOR]

Shallow landslides in Souk Ahras region, NE Algeria, occur usually after prolonged rainfall events. Three localities which are Zaarouria, Hammam Tassa, and Mechroha were chosen to study these landslides and the conditions of their occurrences. They have been observed to affect mainly agricultural lands, main supplies, and the road network. This paper aims to find the relationship between the rainfall, the soil engineering properties, the geology, and the geomorphology. A number of field trips were organized to the study areas where landslide masses were described and mapped as well as some field measurement such as natural moisture content and sampling. In the laboratory, we establish gain size distribution, Atterberg limits, density, and effective cohesion and internal friction. Then we established the unsaturated soil property functions such as the soil water characteristic curve (SWCC) and the hydraulic function. The stability computation was undertaken using, GeoStudio software 2020, a coupled analysis where the Seep/W simulates the seepage and the Slope/W for the safety factor. The results show that the sector study containing: silty sand (SM), well graded sand with silt and gravel (SW-SM), and clayey sand with Gravel (SC) while hydraulic conductivity varies between 4.5. 10−6 for 4.10−5 and 10−3 m/s. The factor of safety varies between 0.8, 1.16, and 0.8. In conclusion, our study confirms the field observations as shallow landslides have been numerous in mars 2019 when rainfall reaches 110 mm. Moreover, high permeability soils, in Mechrouha, show a more dramatic decrease in the factor of safety as the 100 = -mm rainfall amount is reached while it decreases gradually for the other two less permeable soils of Zaarouria and Hammam Tassa. [ABSTRACT FROM AUTHOR]

Slope instability occurrences as damaging shallow-landslides in the residual soil around mountains has been widely studied with geophysical, geotechnical and hydrogeological techniques but relating soil electrical resistivity to hydraulic conductivity for characterisation of lithology inducing of these landslides is not common. In this study, we used Electrical Resistivity Tomography (ERT) data and Hydraulic Conductivity (HC) data obtained from soil samples collected within 1–4.5 m depth in the borehole to assess the characteristics of soil that can induce landslide in the study location. The HC data were derived empirically from Beyer, Kozeny-Carman and Slitcher formula which were validated with HC obtained from laboratory experiment. The Empirical Derived Hydraulic Conductivities (EDHC) were correlated with the soil resistivity. The result shows a strong correlation between soil resistivity and HC with regression values of R2 = 0.9702, R2 = 0.9153 and R2 = 0.9232 for Beyer, Kozeny-Carman and Slitcher formula, respectively. The ERT model revealed a possible sliding surface between two contrasting resistive top material and underneath conductive materials at about 4 m depth. The HC assessment result corroborated the ERT model result because high and low-HC values were obtained in the borehole soil samples within 0–4 m and > 4 m depths from EDHC, respectively. The low-HC zone below 4 m depth was responsible for the occurrences of the shallow-landslides in the study. Key points: Relationship between soil electrical resistivity and hydraulic conductivity were examined for assessment of lithology inducing shallow-landslide. Soil electrical resistivity delineated a boundary between two contrasting resistive and conductive lithologies at 4 m depth. Strong correlation ranged between R2 = 0.9153 to 0.9702 were observed between soil resistivity and hydraulic conductivity for the soil samples examined. The conductive lithology with low hydraulic conductivity below 4 m depth was responsible for the occurrences of the shallow-landslides. [ABSTRACT FROM AUTHOR]

Fujian Province is one of the most frequent areas of landslide disasters in China, so the study of landslide susceptibility in this region is of great significance. Based on the mass landslides that occurred in Sanming, Fujian in 2019, the study used DEM data and aerial imagery to sort out the area, elevation, lithology, and road or building proximity of 131 landslides, and calculated the slope, profile curvature, and plan curvature of the landslides after improving the elevation matrix according to the geometry of landslides. Normalized landslide frequency was used to calculate the contribution of each causative factor to landslide disasters, so as to establish logistic regression models of landslide susceptibility on different scales. It was found that the model based on the 500 m * 500 m grid was the most suitable for evaluating landslide susceptibility. However, the logical regression model is deficient, not only the number of samples should reach more than 50, but also the incidence rate should be at least 30–70%, in order to avoid the model being not significant caused of the small number of samples and the sample imbalance, resulting in too many underestimated or overestimated samples. [ABSTRACT FROM AUTHOR]

Abstract Heavy rainfall brought by typhoons has been recognised as a major trigger of landslides in Taiwan. On average, 3.75 typhoons strike the island every year, and cause large amounts of shallow landslides and debris flow in mountainous region. Because landslide occurrence strongly corresponds to the storm dynamics, a reliable typhoon forecast is therefore essential to landslide hazard management in Taiwan. Given early warnings with sufficient lead time, rainfall-induced shallow landslide forecasting can help people prepare disaster prevention measures. To account for inherent weather uncertainties, this study adopted an ensemble forecasting model for executing precipitation forecasts, instead of using a single-model output. A shallow landslide prediction model based on the infinite slope model and TOPMODEL was developed. Considering the detailed topographic characteristics of a catchment, the proposed model can estimate the change in saturated water table during rainstorms and then link with the slope-instability analysis to clarify whether shallow landslides can occur in the catchment. Two areas vulnerable to landslide in Taiwan were collected to test the applicability of the model for landslide prediction. Hydrological data and landslide records derived from 15 typhoons events were used to verify the applicability of the model. Three indices, namely the probability of detection (POD), false alarm ratio (FAR), and threat score (TS), were used to assess the performance of the model. The results indicated that for landslide prediction through the proposed model, the POD was higher than 0.73, FAR was lower than 0.33, and TS was higher than 0.53. The proposed model has potential for application in landslide early warning systems to reduce loss of life and property.