Landslide Initiation Research Articles

Assessment of temporal probability for rainfall-induced landslides based on nonstationary extreme value analysis

Climate change may alter the frequency and intensity of rainfall, and thereby significantly affect the frequency and magnitude of shallow landslides. To accurately evaluate the temporal probability of landslide initiation, it is therefore important to consider the effect of climate variation. Although various approaches have been proposed to estimate the temporal probability of landslides to date, most of them were based on the stationary assumption, i.e., that the statistical properties of the historical rainfall data are time-invariant. However, if historical rainfall data show nonstationary characteristics such as a trend or an abrupt change, the stationary assumption is no longer valid and induces a miscalculation. In this study, we propose a new approach that can estimate the temporal probability of future rainfall-induced landslide occurrence while incorporating the nonstationary characteristics of the rainfall data. In assessing such data, a nonstationary generalized extreme value distribution was used to evaluate the temporal probability. Then, by combining the derived nonstationary temporal probability with landslide susceptibility results obtained from the random forest model, probabilities of landslide occurrence were calculated for future periods, from 1 to 50 years, and compared with the results based on a stationary model. The results showed that the stationary model underestimated the landslide probability compared with the nonstationary approach. This is because an increasing trend in local rainfall, taken from a gauge in the study area, was not considered in the stationary analysis. Thus, climate change has ongoing consequences for landslide occurrence. To reflect the impacts of climate change, a nonstationary approach capable of coping with climate variation should therefore be considered in any landslide hazard analysis.

Ultimate lateral pressures exerted on buried pipelines by the initiation of submarine landslides

Submarine slope instabilities are considered one of the major threats for offshore buried pipelines. This paper presents a novel method to evaluate the ultimate pressure acting on a buried pipeline during the liquefaction of an inclined seabed. Small-scale model tests with pipes buried at three different embedment ratios have been conducted at an enhanced centrifugal acceleration condition. A high-speed, high-resolution imaging system was developed to quantify the soil displacement field of the soil body and to visualize the development of the liquefied zone. The measured lateral pressures were compared with the hybrid approach proposed for the landslide–pipeline interaction in clay-rich material by Randolph and White (2012) and Sahdi et al. (2014). The hybrid approach is proved to be able to predict later pressures induced by the movement of (partially) liquefied sand on buried pipelines. It is found that the fluid inertia (fluid dynamics) component plays an important role when the non-Newtonian Reynolds number >~2 or the shear strain rate > 4.5 × 10−2 sec−1.

Ongoing Landslide Deformation in Thawing Permafrost

AbstractThawing permafrost influences landslide initiation, but observation of landslide development in thawing permafrost is limited. To evaluate the impact of landslide age, morphology, and permafrost conditions, we quantified topographic deformation of three shallow‐angle, thaw‐initiated landslides in discontinuous permafrost in Alaska. Two of the landslides initiated <3 years ago and the third initiated 20–50 years ago. The two recent landslides are still mobile, with maximum elevation loss of 0.8 ± 0.04 and 1.0 ± 0.08 m over the study period. At one site, shallow permafrost (<2.3 m) is present at 0.4–1.9 m depth adjacent to the landslide but not within the landslide. The lack of shallow permafrost within the slide indicates that permafrost has thawed faster within the landslide because ground surface disturbance increased heat flux to the subsurface. We propose that a positive feedback between permafrost thaw and landslide development exists. Climate warming will accelerate loss of permafrost in recent landslides.

HydroMet: A New Code for Automated Objective Optimization of Hydrometeorological Thresholds for Landslide Initiation

Landslide detection and warning systems are important tools for mitigation of potential hazards in landslide prone areas. Traditionally, warning systems for shallow landslides have been informed by rainfall intensity-duration thresholds. More recent advances have introduced the concept of hydrometeorological thresholds that are informed not only by rainfall, but also by subsurface hydrological measurements. Previously, hydrometeorological thresholds have been shown to improve capabilities for forecasting shallow landslides, and they may ultimately be adapted to more generalized landslide forecasting. We present HydroMet, a code developed in Python by the U.S. Geological Survey, which allows users to guide the automated estimation of hydrometeorological thresholds for a site or area of interest, with the flexibility to select preferred threshold variables for the antecedent hydrologic conditions and the triggering meteorological conditions. Users can import hydrologic time-series data, including rainfall, soil-water content, and pore-water pressure, along with the times of known landslide occurrences, and then conduct objective optimization of warning thresholds using receiver operating characteristics. HydroMet presents many additional options, including selecting the threshold formula, the timescale of possible threshold variables, and the skill statistics used for optimization. Users can develop dual-stage thresholds for watch and warning alerts, with a lower, risk-averse threshold to avoid missed alarms and a less conservative threshold to minimize false alarms. Users may also choose to split their inventory data into calibration and evaluation subsets to independently evaluate the performance of optimized thresholds. We present output and applications of HydroMet using monitoring data from landslide-prone areas in the U.S. to demonstrate its utility and ability to produce thresholds with limited missed and false alarms for informing the next generation of reliable landslide warning systems.

Effects of terrain on the occurrence of debris flows after forest harvesting

ABSTRACT Forest harvesting and subsequent forest regeneration represent widespread changes in land cover in mountain regions. Although impacts of forest harvesting on landslide initiation has been widely reported, the effects of forest harvesting on the occurrence of debris flows remains unclear. We propose that forest harvesting will differentially affect the susceptibility of debris flows amongst catchments with different terrain characteristics. This hypothesis was assessed in the Sanko catchment, Japan, where comprehensive forest harvest records date back to 1913. The frequency of debris flows directly originating from landslides occurred in similar timeframes as the occurrence of landslides. Landslides that reached channels and continued downstream as debris flows were more prevalent in steep channel reaches with small hillslope-channel junction angles. In addition to the increase in the frequency of landslides, especially within 10 years after forest harvesting, debris flows caused by mass movement of channel deposits in steep reaches increased during this period. These relationships between the occurrence of debris flows and channel topography indicate a high susceptibility of debris flow occurrence after forest harvesting in first and zero-order mountain streams. Sediment previously routed into channel networks by landslides is likely a more important factor for in-channel debris flow initiation in the lower channel reaches, while instability of areas proximate to riparian zones, including stream banks and geomorphic hollows, possibly accelerate occurrence of debris flows in upper channel reaches. Consequently, catchment topography should be considered in evaluating debris flow risk after forest harvesting.

Monitoring and Data Analysis in Small-Scale Landslide Physical Model

Physical modeling of landslides using scaled landslide models began in the 1970s in Japan at scaled natural slope physical models. Laboratory experiments of landslide behavior in scaled physical models (also known as flume or flume test) started in the 1980s and 1990s in Canada, Japan, and Australia under 1 g conditions. The main purpose of the landslide physical modeling in the last 25 years was research of initiation, motion, and accumulation of fast flow-like landslides caused by infiltration of water in a slope. In October 2018, at the Faculty of Civil Engineering University of Rijeka, started a four-year research project “Physical modeling of landslide remediation constructions’ behavior under static and seismic actions” funded by the Croatian Science Foundation. This paper presents an overview of the methods and monitoring equipment used in the physical models of a sandy slope exposed to artificial rainfall. Landslide development was monitored by observation of volumetric water content and acceleration as well as by observations of surface displacement by means of high-speed stereo cameras, terrestrial laser scanning, and structure-from-motion photogrammetry. Some of the preliminary results of the initial series of experiments are presented, and advantages and disadvantages of the used equipment are discussed.

A new approach in the development and analysis of the landslide susceptibility map of the hillslopes of Bujumbura, Burundi

As in other hilly and mountainous regions of the world, the hillslopes of Bujumbura are prone to landslides. In this area, landslides impact human lives and infrastructures. Despite the high landslide-induced damages, slope instabilities are less investigated. The aim of this research is to assess the landslide susceptibility using a probabilistic/statistical data modeling approach for predicting the initiation of future landslides. A spatial landslide inventory with their physical characteristics through interpretation of high-resolution optic imageries/aerial photos and intensive fieldwork are carried out. Base on in-depth field knowledge and green literature, let’s select potential landslide conditioning factors. A landslide inventory map with 568 landslides is produced. Out of the total of 568 landslide sites, 50 % of the data taken before the 2000s is used for training and the remaining 50 % (post-2000 events) were used for validation purposes. A landslide susceptibility map with an efficiency of 76 % to predict future slope failures is generated. The main landslides controlling factors in ascendant order are the density of drainage networks, the land use/cover, the lithology, the fault density, the slope angle, the curvature, the elevation, and the slope aspect. The causes of landslides support former regional studies which state that in the region, landslides are related to the geology with the high rapid weathering process in tropical environments, topography, and geodynamics. The susceptibility map will be a powerful decision-making tool for drawing up appropriate development plans in the hillslopes of Bujumbura with high demographic exposure. Such an approach will make it possible to mitigate the socio-economic impacts due to these land instabilities

Coupled 3D numerical model for a landslide-induced impulse water wave: A case study of the Fuquan landslide

Large impulse waves are generated when a highly mobilized landslide impacts a water body along the runout path. On August 27, 2014, a massive landslide occurred in Fuquan, Guizhou, China and induced an impulse wave upon contact with a quarry lake. The landslide and its associated impulse wave were a multiphase and multicomponent mixture that collectively destroyed two villages. The present study provides insights into multiphase dynamic analysis by employing an existing 3D coupled discrete element modeling and computational fluid dynamics approach to model a case study of the Fuquan landslide and its impulse wave. EDEM and Fluent were two-way coupled by an application programming interface, which transferred data between the models to simulate subaerial movement and impulse wave generation. The simulated results indicate a maximum velocity of 31.7 m/s achieved by the subaerial movement and a runout duration of 39 s. The detached mass entered the quarry lake at a velocity of 24.3 m/s, at t = 7.1 s after the landslide initiation. Energy was transferred between the sliding mass and lake water, and the generated water wave rushed toward the opposite slope. The generated wave had a run-up of 28.4 m and traveled approximately 90 m in the lateral direction, with a maximum dynamic pressure of 3.03 MPa. Qualitative validation of the present model was performed using Fritz's experimental setup for wave generation, and the velocity evolution was physically verified. This study provides calibrated parameters for the forward simulation of similar cases of landslide-induced impulse water waves and related hazard zonation.

Hydrological control of soil thickness spatial variability on the initiation of rainfall-induced shallow landslides using a three-dimensional model

Thickness and stratigraphic settings of soils covering slopes potentially control susceptibility to initiation of rainfall-induced shallow landslides due to their local effect on slope hydrological response. Notwithstanding the relevance of the assessment of hazard to shallow landsliding at a distributed scale by approaches based on a coupled modelling of slope hydrological response and slope stability, the spatial variability of soil thickness and stratigraphic settings are factors poorly considered in the literature. Under these premises, this paper advances the well-known case study of rainfall-induced shallow landslides involving ash-fall pyroclastic soils covering the peri-Vesuvian mountains (Campania, southern Italy). In such a unique geomorphological setting, the soil covering is formed by alternating loose ash-fall pyroclastic deposits and paleosols, with high contrasts in hydraulic conductivity and total thickness decreasing as the slope angle increases, thus leading to the establishment of lateral flow and an increase of pore water pressure in localised sectors of the slope where soil horizon thickness is less. In particular, we investigate the effects, on hillslope hydrological regime and slope stability, of irregular bedrock topography, spatial variability of soil thickness and vertical hydraulic heterogeneity of soil horizons, by using a coupled three-dimensional hydrological and a probabilistic infinite slope stability model. The modelling is applied on a sample mountain catchment, located on Sarno Mountains (Campania, southern Italy), and calibrated using physics-based rainfall thresholds derived from the literature. The results obtained under five simulated constant rainfall intensities (2.5, 5, 10, 20 and 40 mm h−1) show an increase of soil pressure head and major failure probability corresponding to stratigraphic and morphological discontinuities, where a soil thickness reduction occurs. The outcomes obtained from modelling match the hypothesis of the formation of lateral throughflow due to the effect of intense rainfall, which leads to the increase of soil water pressure head and water content, up to values of near-saturation, in narrow zones of the slope, such as those of downslope reduction of total soil thickness and pinching out of soil horizons. The approach proposed can be conceived as a further advance in the comprehension of slope hydrological processes at a detailed scale and their effects on slope stability under given rainfall and antecedent soil hydrological conditions, therefore in predicting the most susceptible areas to initiation of rainfall-induced shallow landslides and the related I-D rainfall thresholds. Results obtained demonstrate the occurrence of a slope hydrological response depending on the spatial variability of soil thickness and leading to focus slope instability in specific slope sectors. The approach proposed is conceived to be potentially exportable to other slope environments for which a spatial modelling of soil thickness would be possible.

Shallow landslide triggering in unsaturated vegetated slopes: Efficient computation of susceptibility maps

A modelling platform is developed to study the coupled hydromechanical processes occurring in shallow unsaturated slopes prone to landslide hazards. It is supplemented with a Graphical User-Interface (GUI) and relies on a finite element solver here referred to as cLiNUs (Computational Landslide Initiation through Numerical Simulations), which discretizes and solves the partial differential equations governing momentum and water mass balance for stratified deposits. cLiNUs allows the versatile simulation of hydrologic processes causing infiltration, surface runoff, moisture increase, deformation, and failure in shallow slopes. In addition, it is coupled with a novel vectorization strategy that enables the mapping of model computations on digital elevation models (DEM) to generate landslide susceptibility maps throughout the duration of storm events. The GUI includes routines for simple parameter initialization, selection of hydro-mechanical constitutive laws, determination of boundary conditions, and results’ visualization. The program also enables a straightforward use of data about stratigraphy (i.e., multiple soil layers within a slope profile), vegetation cover, swelling/shrinkage response of unsaturated soil deposits and water runoff, thus ensuring a variety of analyses for educational and scientific purposes. The capabilities of the new computational platform are illustrated with reference to multiple examples showcasing its ability for landslide susceptibility assessment at the scale of individual slopes. Furthermore, selected examples of regional scale performance are discussed, including spatiotemporal predictions of landslide triggering for a well-documented series of debris flows and runoff simulations taking into account the role of vegetation. The proposed framework opens new possibilities in landslide hazard zonation studies by enabling the incorporation of important datasets that otherwise would remain neglected (i.e., vegetation/land cover and its role on surface/subsurface flow, deformability/hydraulic properties of soil deposits, complex layering sequences of stratified slopes, transient rainfall, among others) while at the same time, relying on a user-friendly interface.

Landslide susceptibility zonation mapping using statistical index and landslide susceptibility analysis methods: A case study from Gindeberet district, Oromia Regional State, Central Ethiopia

The present study was carried out in Gindeberet district, central Ethiopia and covers a total of 128 km2. The geology of the area is comprised of sandstone, mudstone, limestone and basalt. The general objective was to evaluate the factors influencing the landslide initiation and to prepare a landslide susceptibility zonation map. One hundred thirty landslides were identified through field investigation and Google Earth image interpretation. Statistical Index Model (SIM) and Landslide Susceptibility Analysis (LSA) were used for the preparation of landslide susceptibility map. Lithology, slope steepness, aspect, land−use/land cover, and distance from drainage are the causative factors selected, whereas rainfall and human activities are considered as the triggering factors. The relations of landslides and causative factors were determined in terms of weighted value (Wij). From the lithology limestone, mudstone and weathered basalt have strong relationship with the landslides. Moreover, the result shows that weighted values (Wij) are high for N and W orientation class of slope aspect; greater than 45° slope steepness; agricultural land and moderately vegetated land−use/land cover class and 0−100 m and 100−200 m distance from drainage class. Landslide susceptibility zonation (LSZ) map was prepared and classified into very low, low, high, and very high susceptible zones. For LSZ map prepared by SIM model out of 130 landslides inventory data, 2 (1.54%) of the landslides fall in very low susceptible zone, 11 (8.46%) in low susceptible zone, 12 (9.23%) in moderate susceptible zone, 16 (12.31%) falls in high susceptible zone and 89 (68.46%) in very high susceptible zone, whereas LSZ map prepared by LSA model shows that out of 130 landslides inventory data, 11 (8.5%) of the landslides fall in very low susceptible zone, 12 (9.2%) in low susceptible zone, 15 (11.5%) in moderate susceptible zone, 25 (19.3%) in high susceptible zone and 67 (51.5%) in very high susceptible zone. The percent of existing landslide determined from LSZ maps prepared by SIM and LSA falls in high and very high susceptible zones were 81% and 71% respectively. The result of verification shows that areal distributions and occurrences of landslides were relatively comparable in both methods.

Reliability-based prediction of landslide using efficient Monte Carlo Simulation

Several studies have attempted to develop thresholds for prediction of landslide initiation due to antecedent rainfall by using the physical-based approach. The approach offers a better understanding of the underlying process of the landslide mechanism. In the previous studies, however, determinate values of hydro-mechanical soil parameters are commonly considered, neglecting the uncertainties of the variables. Thus, this study aims to propose a relatively computationally, inexpensive reliability approach to address the uncertainties of the multivariate. The application of the proposed model is demonstrated by taking a case study from Sabah, Malaysia. The Latin Hypercube Sampling was adopted for efficient sampling, while the dependencies of the multivariate were modelled using a higher-order copula. The infiltration process and slope stability were assessed based on a fully-coupled seepage-deformation and shear strength reduction technique, respectively in a finite element programme. The probabilities of failure for various antecedent rainfall condition were computed by using Monte Carlo Simulation. In order to reduce the computational cost of the simulation, the Multilayer Perceptron regressor was applied to form the non-linear surrogate model for an implicit limit state function.

Clay landslide movement triggered by artificial vibrations: new insights from monitoring data

Slope stability is influenced by a number of factors that modify the resisting/acting force ratio control landslide initiation and movement velocity. Among these, artificial vibrations have been identified as an important degrading factor for soil strength, but it is not fully clear if they can trigger or modulate movements of clay landslides. To contribute to a better understanding of the potential effect of vibrations on landslide movement, also in terms of boundary conditions, we analyzed monitoring data acquired at the toe of the Pietrafitta landslide in southern Italy. This landslide adjoins the SS87 national road that suffered periodic closure due to landslide activity and in April 2016 operates daytime only for risk mitigation purpose. This condition promoted a better identification of a potential cause-effect relation between traffic vibration and landslide movement. Results from data analysis and landslide modeling suggest that in condition of incipient movement, artificial vibrations, also of limited amplitude, are able to directly initiate clay landslide movement that due to the viscous nature of the involved material exhibit a specific displacement pattern that is not consistent with a sliding block model.

A Landslide Monitoring System for Natural Terrain in Korea: Development and Application in Hazard Evaluations.

This study describes the development of a landslide monitoring system for the purpose of reducing damages caused by landslides in natural terrain. The system was developed to analyze the effects of landslide-inducing rainfall and the behavior of slopes through 12 monitoring stations that are distributed across eight national parks in Korea. Several sensors and a data acquisition equipment to monitor landslide were installed in each station. The composition of the system and its operating program were designed to efficiently manage the sizeable amounts of real-time monitoring data that are collected from the various stations. To test the potential of the developed system for reliable landslide hazard evaluations, data measured over a five-year period by the two monitoring stations in Jirisan National Park were analyzed. Subsequently, the suction stress of the soil over the monitoring period was calculated by applying laboratory test result of the geotechnical and unsaturated soil properties in the analysis domain area. The infinite slope stability analysis combined with an effective stress concept based on the suction stress was applied to calculate the factor of safety. This method also enabled the temporal and quantitative evaluation of slope stability in natural terrain. In addition, based on the monitoring and slope stability analysis results, an analysis for the spatial classification of landslide hazards was conducted. The analysis results quantitatively and statistically demonstrated that 98% of historical landslide initiation areas were classified as high hazard levels.

Analysis of Rainfall-induced Landslide Using the Extended DDA by Incorporating Matric Suction

Rainfall-induced landslide is a common natural hazard, and one of the disaster-causing factors is the loss of apparent cohesion that is mainly caused by the dissipation of matric suction. To analyze the rainfall-induced landslide, especially the post-failure behaviors, a matric suction model is proposed and incorporated into the Discontinuous Deformation Analysis (DDA). In this model, the matric suction is simplified as an equivalent line load and updated at each time step. The safety factor of the simple sliding model simulated by the extended DDA (DDA_c) showed a good agreement with the limit equilibrium method. The simulated relationship between runout distance and the degree of saturation of the multi-block sliding model was validated by the experimental results. Finally, a rainfall-induced landslide in Fukuchi-machi was simulated using the extended DDA. The results illustrated that the apparent cohesion loss is an important mechanism for landslide initiation and a crucial reason for the long-runout distance. The presented DDA_c can be served as a qualified tool to analyze shallow slope stability and post-failure behavior involving apparent cohesion.

Airborne Electromagnetics to Improve Landslide Knowledge in Tropical Volcanic Environments

Caribbean areas are particular volcanic territories in tropical environments. These territories juxtapose several landslide-prone areas with different predisposing factors (poorly consolidated volcanic materials, superimposition of healthy materials on highly weathered materials, high heterogeneity of thicknesses, etc.). In these environments, where rapid development of slopes and land use changes are noticeable, it is necessary to better characterize these unstable phenomena that cause damage to infrastructure and people. This characterization has to be carried out on the materials as well as on the initiation conditions of the phenomena and requires complementary investigations. This study, focusing on La Martinique, proposes a landslide analysis methodology that combines new information about landslide-prone materials acquired by an airborne electromagnetics survey with a physical-based model. Once the data are interpreted and compared with field observations and previous data, a geological model is produced and introduced into the physical model to test different instability scenarios. The results show that geophysical investigations (i) improve the knowledge of the internal structure of landslides and surficial formations, (ii) specify the spatial limits of the materials that are sensitive to landslides, and (iii) give a better understanding of landslide initiation conditions, particularly hydrogeological triggering conditions.

Study on the Dynamic Response of Landslide Subjected to Earthquake by the Improved DDA Method

Majiagou landslide, a major ancient landslide in Three Gorges Reservoir region, is located in the high earthquake area of southwest China. The 2013 Badong earthquake caused an obvious deformation of landslide monitored by the sliding inclinometer. A strong earthquake may induce the reactivation of ancient landslide. So, it is necessary to research the seismic dynamic response of Majiagou landslide. For this purpose, discontinuous deformation analysis (DDA), improved by introducing the artificial joint and viscous boundary, is applied in this study. The displacements at monitoring points caused by Badong earthquake are calculated and compared with the field data, verifying the numerical method and model. Further, a strong earthquake with the peak acceleration of 1 g is assumed to act on the landside, the initiation and evolution process of landslide is simulated, and the movement features of landslide are discussed. The dynamic failure of landslide and the local amplification of seismic wave can be embodied, indicating that the improved DDA provides an alternative approach for analyzing the seismic dynamic response of jointed rock.

Chemical weathering and progressing alteration as possible controlling factors for creeping landslides.

Landslides can behave as dynamic processes, which emerge from the complex interplay of tectonics, erosion, weathering and gravitational influences, triggered by various hydrological, mineralogical, biological and geotechnical factors. Integral studies to assess the mechanisms underlying landslide initiation and progression are mainly focussed on specific cases with high geohazard potential. The landslide near Stadtschlaining (Austria) represents a key study site to elucidate the impacts of pelitic sediment composition, weathering regime, alteration patterns and hydrochemistry on recurrent damage progression in the local infrastructure. Based on field work, soil-mechanical logging (Atterberg limits, undrained strength, friction angles), water chemistry (ICP-OES, IC, hydrochemical modeling), solid-phase characterization (XRD, XRF, SEM) and sorption experiments we establish a conceptual model for initiating and progressing of landslides: Infiltration of low mineralized meteoric water (EC: <200μS/cm) in permeable limonitic gravels triggers chemical weathering of greenschist-derived detritus and promotes its transformation into kaolinite and smectite. The clayey strata (>50wt% of clay minerals) create zones of mechanical and chemical weakness in the underground (~4-6m below ground level), which are characterized by particle disintegration/delamination, slip bedding and deformations, and development of porous layers depicting water flow paths. Subsequent Na+ exchange for bivalent ions in the smectite interlayer delivered by percolating, highly mineralized water (EC: 1600-5100μS/cm) is caused by de-icing salt and fertilizer applications during winter and late summer, and yield in i) decohesion and physical breakdown of the particle aggregates and ii) swelling of the clay matrix in early spring and autumn. These processes reduce the shear strength of the pelitic sediments, resulting in failure and initiation of landslides (deformation: ~500mm within a month) and subsequent steady creeping motion (deformation: ~100mm in 6months). Customized engineered solutions to prevent landslides in this area are presented, which can be conveyed to analogous landslide-affected areas worldwide.

Changing significance of landslide Hazard and risk after the 2015 Mw 7.8 Gorkha, Nepal Earthquake

The 2015 Mw 7.8 Gorkha, Nepal Earthquake triggered in excess of 20,000 landslides across 14 districts of Central and Western Nepal. Whilst the instantaneous impact of these landslides was significant, the ongoing effect of the earthquake on changing the potential for rainfall-triggered landsliding in the months and years that followed has remained poorly understood and challenging to predict. To provide insight into how landsliding has evolved since the earthquake, and how it has impacted those living in the affected area, a detailed time-series landslide mapping campaign was undertaken to monitor the evolution of coseismic landslides and the initiation of new post-seismic landslides. This was supplemented by numerical modelling to simulate the future potential reactivation and runout of landslides as debris flows under monsoon rainfall, identifying locations potentially at risk. This analysis shows that landslide hazard was higher in November 2019 as compared to immediately after the 2015 earthquake, with a considerable portion of the landscape being impacted by landsliding. We show that, while pre-existing landslides continued to pose the majority of hazard in the aftermath of the earthquake, a significant number of landslides also occurred in new locations. We discuss the value of this type of analysis in informing the reconstruction and management of settlements at risk by summarizing how this work was integrated into the project Durable Solutions II, that supported communities at risk from landslides. Finally, we consider how such data could be used in future to inform risk sensitive land-use planning and disaster recovery, and to mitigate the impacts of future landsliding in Nepal and beyond.

Controls on the size distributions of shallow landslides

Rainfall-triggered shallow landslides are destructive hazards and play an important role in landscape processes. A theory explaining the size distributions of such features remains elusive. Prior work connects size distributions to topography, but field-mapped inventories reveal pronounced similarities in the form, mode, and spread of distributions from diverse landscapes. We analyze nearly identical distributions occurring in the Oregon Coast Range and the English Lake District, two regions of strikingly different topography, lithology, and vegetation. Similarity in minimum sizes at these sites is partly explained by theory that accounts for the interplay of mechanical soil strength controls resisting failure. Maximum sizes, however, are not explained by current theory. We develop a generalized framework to account for the entire size distribution by unifying a mechanistic slope stability model with a flexible spatial-statistical description for the variability of hillslope strength. Using hillslope-scale numerical experiments, we find that landslides can occur not only in individual low strength areas but also across multiple smaller patches that coalesce. We show that reproducing observed size distributions requires spatial strength variations to be strongly localized, of large amplitude, and a consequence of multiple interacting factors. Such constraints can act together with the mechanical determinants of landslide initiation to produce size distributions of broadly similar character in widely different landscapes, as found in our examples. We propose that size distributions reflect the systematic scale dependence of the spatially averaged strength. Our results highlight the critical need to constrain the form, amplitude, and wavelength of spatial variability in material strength properties of hillslopes.