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At 6pm on July 19, 2019, the Yahuokou earthflow (Zhouqu County, Gansu Province, China) was reactivated following a period of intense rainfall. A volume of approximately 3.9 × 106 m3 travelled approximately 1100 m in 27 days, blocking part of the Min River. Multi-temporal InSAR monitoring and interpretation of high-resolution optical images were used to map different phase of mass movements (including rock fall, topple, slide, and flowslide) to characterize the pre-failure deformation of the earthflow. Analysis of displacement patterns indicates that initiation of the earthflow is closely correlated with road construction, intense and long-lasting rainfall (443 mm from April 1, to July 19, 2019), and seismic activity. The potential to forecast the time of failure based on pre-failure deformation patterns observed by InSAR monitoring is demonstrated. Three types of pre-failure deformation are distinguished: steady creep, fluctuating creep, and accelerating creep. The monitoring process enabled identification and characterization of three key stages of the earthflow (initiation, transportation, and accumulation/deposition) providing important lessons learned for improvement of landslide early warning and hazard assessment in similar geological and geomorphological settings.

Debris flows are one of the natural disasters that can occur in the alpine environment, cause large economic damage, and endanger human lives. This study presents an overview of recent research done in relation to the debris flow hazard assessment and conceptual mitigation at the Koroska Bela area in Slovenia. This includes fieldwork, lab experiments, modelling, and a conceptual design of hydro-technical measures to reduce the risk. The results indicate that multiple debris flows occurred in the past in the area but a relatively long period of more than 100 years without an extreme event led to urbanization and development of the area. Magnitudes of the most extreme events as the worst-case scenarios were estimated to be in the range between 100,000 and 400,000 m3, using debris flow modelling and geological information from research trenches. Based on the landslide volumes, such events could also potentially occur in the future in extreme conditions. Additionally, torrential floods could mobilize more than 15,000 m3 of material located along the stream network that can be regarded as potentially unstable. The existing check dam system does not have the capacity to capture this material. Thus, a new check dam and three flexible net barriers could help to reduce the risk due to torrential outbursts or debris flows.

When an active landslide is first identified in an artificial reservoir, a comprehensive study has to be quickly conducted to analyse the possible hazard that it may represent to such a critical infrastructure. This paper presents the case of the El Arrecife Landslide, located in a slope of the Rules Reservoir (Southern Spain), as an example of geological and motion data integration for elaborating a preliminary hazard assessment. For this purpose, a field survey was carried out to define the kinematics of the landslide: translational in favour of a specific foliation set, and rotational at the foot of the landslide. A possible failure surface has been proposed, as well as an estimation of the volume of the landslide: 14.7 million m3. At the same time, remote sensing and geophysical techniques were applied to obtain historical displacement rates. A mean subsidence rate of the landslide around 2 cm/year was obtained by means of synthetic aperture radar interferometry (InSAR) and ground-penetrating radar (GPR) data, during the last 5 and 22 years, respectively. The structure-from-motion (SfM) technique provided a rate up to 26 cm/year during the last 14 years of a slag heap located within the foot of the landslide, due to compaction of the anthropical deposits. All of this collected information will be valuable to optimise the planning of future monitoring surveys (i.e. differential global positioning systems, inclinometers, ground drilling, and InSAR) that should be applied in order to prevent further damage on the reservoir and related infrastructures., This work was mainly supported by the European Regional Devel-opment Fund (ERDF) through the project "RISKCOAST" (SOE3/P4/ E0868) of the Interreg SUDOE Programme. The work of J.P.G., M.M-S., P.R. and J.M.A. was also supported by the "Ramón y Cajal" Programme (RYC-2017–23335) of the Spanish Ministry of Science, the project "MOR-PHOMED"—PID2019-107138RB-I00 / SRA (State Research Agency / https://doi.org/10.13039/501100011033) and the project "RADANDA -LUS" (P18-RT-3632) and B-RNM-305-UGR1818 of the FEDER / Junta de Andalucía-Consejería de Transformación Económica, Industria, Cono-cimiento y Universidades.

Landslides hazard assessment requires the combination of spatial and temporal probabilities. In this work, we combine spatial modelling and regionalization of debris rainfall thresholds for assessing both these probabilities and map debris flows initiation hazard over 15 × 103 km2 of the Emilia-Romagna Apennines (Italy). In this area, debris flows are spatially and temporally less frequent than earth slides and earth flows. However, more than a hundred debris flows occurred in October 2014 and September 2015 during two large rainstorms clusters in Parma in Piacenza provinces; some tens of debris flows are reported to have occurred in the past and few others have occurred recently. Since landslides inventory maps used for land use planning only consider some large debris flows accumulation fans, and substantially no information is given on the slopes along which these phenomena might occur, this study aims to fill this gap by creating a hazard map using the evidences collected after the recent abovementioned multi-occurrence events. Different spatial statistical models (Frequency Ratio [FR], Weight of Evidence [WOE] and Logistic Regression [LR]), set up with various combinations of geo-environmental causal factors, have been trained using 60% of debris flow initiation points mapped after the 2014 and 2015 events. The predictive performances of the models have been compared by success rate curves using the remaining 40% of initiation points of the 2014 and 2015 events. The model with the best predictive capability (area under the curve > 0.96) has been further validated using the spatial distribution of other debris flows occurred in the period 1972–2016, and its outputs have been classified into spatial probability classes. Furthermore, the annual exceedance probability of recently published debris flows 3 h cumulated rainfall triggering thresholds has been calculated for in 185 rain gauges and regionalized by spatial interpolation. Finally, spatial and temporal probability maps ranked in a 0–1 range have been combined into a regional debris flows initiation hazard map that, on the basis of the return periods, is associated to different yearly probability values. The resulting hazard map classifies 0.87% of the area as high hazard, 2.83% as medium hazard, 0.5% as low hazard and the remaining 95.81% as null hazard. The spatial distribution of hazardous zones is quantitatively and qualitatively consistent with the spatial distribution of past debris flows. Furthermore, it is coherent with geomorphological common sense and it has proven sufficiently accurate in discriminating as hazardous the debris flows initiation zones of phenomena occurred after it was produced. On such a basis, despite its limitations, we consider the debris flows hazard map produced sufficiently reliable to integrate existing inventory maps in land-use regulation and emergency planning.

Compiling an inventory is a fundamental step for carrying out assessments of landslide hazards. However, data in sufficient quantity and quality are not always available. Thus, this study puts forward an approach for drawing up a landslide inventory using textual data from telephone records, and for mapping hazards of landslides in an urban area. Forty thousand seven hundred ninety-two textual records and the naive Bayes algorithm were used to classify them, and these form the landslide inventory. After creating the inventory, the random forest algorithm with 12 conditioning variables was used to map landslide hazards. The text classification model obtained an accuracy of 0.8671 and a Kappa index of 0.8038. The hazard mapping model obtained accuracy of 0.9503 and an AUC (area under the curve)-ROC (receiver operating characteristics) of 0.9870. The results produced by the model were also compared with real landslides reported in news reports and were shown to be close to what had happened, thus demonstrating the ability of the proposed approach to predict landslides. Finally, the proposed approach can be used in simulation environments, thereby supporting strategic decision-making associated with hazard analysis.

Landslide disasters are associated with severe losses on the Loess Plateau of China. Although early warning systems and susceptibility mapping have mitigated this issue to some extent, most methods are qualitative or semi-quantitative in the site-specific range. In this paper, a quantitative spatial distribution model is presented for site-specific loess landslide hazard assessment. Coupled with multi-temporal remote sensing images and high-precision UAV cloud point data, a total of 98 loess landslides that have occurred since 2004 on the Heifangtai terrace were collected to establish a landslide volume-date and retreating distance database. Eleven loess landslides are selected to construct a numerical model for parameter back analysis, and the accuracy of the simulation results is quantitatively evaluated by the centroid distance and overlapping area. Different volumes and receding distance rates of landslides are fitted to determine the relationship between cracks and potential volume, and different volumes and parameters are combined to simulate the spatial distribution of potential loess landslides. The results of this study reveal that landslide volumes mainly range between 1 × 103 and 5 × 105 m3, and the historical occurrence probability reaches 0.551. The optimal parameters are estimated by the maximum likelihood method to obtain a uniform distribution parameter value probability model, and the results show that the error of the estimated length within a range of 0.05 from the optimal parameter does not exceed 15%. In the selected slope slide case, farmland near the toe of the slope primarily includes exposed hazards with probabilities greater than 0.7. This work provides a useful reference for local disaster reduction and a theoretical methodology for hazard assessments.

The landslide complex at Gold Basin, Washington, has been drawing considerable attention after a catastrophic runout of the nearby landslide at Oso, Washington, in 2014. To evaluate potential threats of the Gold Basin landslide to the campground down the slope, remote sensing and numerical modeling were integrated to monitor recent landslide activity and simulate hypothetical runout scenarios. Bare-earth LiDAR DEM (digital elevation model) differencing, InSAR (Interferometric Synthetic Aperture Radar), and offset tracking of SAR images reveal that localized collapses at the headscarps have been the primary type of landslide activity at Gold Basin from 2005 to 2019, and currently no signs indicative of movement of a large centralized block or a deep-seated main body were detected. The maximum horizontal deformation rate is 5 m/year occurring primarily from headscarp recession of the middle lobe, and the annual landsliding volume of the whole landslide complex averages 1.03 × 105 m3. From three-dimensional limit equilibrium analysis of generalized terrace structures, the maximum landslide volume is estimated as 2.0 × 106 m3. Simulations of hypothetical runout scenarios were carried out using the depth-averaged two-phase model D-claw with above-obtained landslide geometry constraints. The simulation results demonstrate that debris flows with volume less than 105 m3 only pose limited threats to the campground, while volumes over 106 m3 could cause severe damages. Consequently, the estimated maximum landslide volume of 2.0 × 106 m3 suggests a potential risk to the campground nearby. Adaption of our methodology could prove useful for evaluating other similar landslides globally for hazards prevention and mitigation.

A bathymetric survey of Harrison Lake in southwest British Columbia revealed deposits of three large landslides on the lake floor. The blocky and flow-like surface morphology of the deposits suggests rapid emplacement from subaerial sources. The multibeam survey, together with a subbottom acoustic survey, allowed us to estimate deposit volumes of 2.4 Mm3, 1.3 Mm3, and 0.2 Mm3 for the Mount Douglas, Mount Breakenridge, and Silver Mountain landslides, respectively. The large volumes and inferred rapid emplacement of the Mount Douglas and Mount Breakenridge landslides suggest they were tsunamigenic. Because people live along the shoreline of Harrison Lake, our discovery and characterization of these landslide deposits and their tsunami-generating potential form an important foundation for further landslide-tsunami hazard analysis in the region.

Landslides sliding rapidly into water bodies may trigger tsunamis, which can threaten not only elements at risk on the slopes but also ships and piers on the water bodies. Management of both direct risks from landslides and indirect risks from landslide-triggered tsunamis along navigation channels is thus highly challenging. In this study, a framework, including hazard and risk identification, hazard analysis, consequence analysis, and risk estimation, is proposed for risk analysis of a landslide-triggered hazard chain, through a case study of the Liangshuijing landslide in the Three Gorges Reservoir area, China. Detailed monitoring data of the landslide indicates a significant influence of the reservoir level fluctuation on the landslide stability. Then, the hazards of both the landslide and its triggered tsunami are predicted by landslide stability calculation, run-out analysis, and tsunami propagation simulation according to defined scenarios. The vulnerability of identified static and dynamic elements at risk is quantified based on hazard intensity and their resistance to the hazard. The total risk, estimated by the sum of the direct risk and the indirect risk from the hazard chain, increases during the drawdown period of the reservoir level. Risk maps are designed to present the dynamic indirect risk along the Yangtze River. Systematic risk analysis emphasizes that the indirect risk from the potential tsunami is much higher than the direct risk, which supports the practical mitigation strategy of the landslide. The framework proposed in this study can be helpful to mitigate reservoir landslide risks, and provides a reference through which entire landslide hazard chains can be analyzed.

This paper shows the results of a study aimed at quantitatively estimating—in terms of direct (repair) costs, at large scale (1:5000)—the slow-moving landslide risk to a road network assumed as undamaged as well as the consequences to the same network in damaged conditions. The newly conceived methodological approaches address some challenging tasks concerning (i) the hazard analysis, which is expressed in terms of probability of occurrence of slow-moving landslides with a given intensity level that, in turn, is established based on empirical fragility curves, and (ii) the consequence analysis, which brings to the generation of time-dependent vulnerability curves. Their applicability is successfully tested in a case study in the Campania region (southern Italy) for which both very high-resolution DInSAR data and information gathered from in situ surveys on the severity of damage sustained by the selected road sections are available. Benefits associated with the use of the obtained results in informed decision-making processes are finally discussed.

Rainfall infiltration in unsaturated slopes alters the effective stress through pore water pressure changes, thus causing ground deformation. Although important to assess the timescale over which the margin of safety of a slope decreases, such coupled processes are rarely accounted in the context of spatially distributed hazard assessment procedures. In this paper, a physically based, spatially distributed model accounting for full hydro-mechanical coupling is discussed. The model relies on a vectorized finite element (FE) solver to calculate the stability of deformable unsaturated infinite slopes subjected to transient flow. First, the FE solver is used to study the response of individual slopes to a prolonged rainfall for three scenarios (i.e., rigid, swelling, and collapsible soil). Then, the model is used in the context of spatially distributed computations to assess spatiotemporal variations of factor of safety over a large area. For this purpose, a series of shallow landslides occurred in a mountainous landscape covered by collapsible loess deposits in northwestern China was used as test site. The analyses show that hydro-mechanical couplings affect the performance of the model in terms of computed failure time and areal extent of the unstable zones. Specifically, volume collapse due to suction decrease is found to reduce the time of failure compared with uncoupled computations obtained for a rigid soil scenario. The most substantial advantages of using coupled analyses have been reported with reference to gentle slopes, for which the higher rate of suction reduction driven by volume change was crucial to capture landslide source areas that would otherwise be overlooked by uncoupled analyses. The proposed methodology offers a complete tool for landslide hazard assessment, in that it incorporates sources of coupling between hydrology and mechanics that are crucial to replicate the physics of landslide initiation.

After a recent forest fire, a weathered granite rock slope located in the northwest of Spain may become increasingly susceptible to rockfalls. This study presents a multi-approach assessment of rockfall hazard, with some features deserving particular attention. First, the geomorphological context represented by a weathered rock mass with multiple dispersed blocks presenting various potential instability mechanisms. Secondly, the presence of a hillfort behind the slope and a small village at its toe, limiting the available solutions for rockfall protection. Finally, the combination of different remote sensing techniques (unmanned aircraft system topography and light detection and ranging) with a semi-automatic geostructural analysis has been successfully applied to obtain both a 3D point cloud of the wide area under study in addition to an estimation of mean block volume for rockfall simulations. Additionally, the design and implementation of a protective measure (rock dynamic barrier) have been addressed.

An accurate and timely inventory for major landslides triggered by seismic events is essential for hazard assessment and risk governance. Sentinel-2 MultiSpectral Instrument (MSI) data have been increasingly used for co-seismic landslide mapping in recent years. However, there have been few studies exploring the full use of Sentinel-2 near infrared (NIR) narrow, red-edge, and short-wave infrared (SWIR) bands for landslide mapping. In this study, Sentinel-2 10-m fused NIR narrow, red-edge-1, SWIR-1, and SWIR-2 bands were incorporated into the change detection-based Markov random field (CDMRF) that considers the spectral, spatial, and contextual information of landslides. The effectiveness of the developed method was proved in mapping co-seismic landslides triggered by two major earthquakes in the Yarlung Tsangpo Grand Canyon, China, in 2017 and Hokkaido, Japan, in 2018. The results demonstrated that the mapping performances with the fused Sentinel-2 bands were significantly improved for both seismic events. Such improvement is mainly attributed to the more abundant spectral information provided by the fused Sentinel-2 red-edge, NIR narrow, and SWIR bands. The novelties of this study are (1) the preliminary attempt to use the Sentinel-2 10-m fused bands for landslide mapping, and (2) the synergy of Sentinel-2 red-edge, NIR narrow, and SWIR bands for more reliable landslide mapping.

Landslides in Kerala, India, have been shown to be preceded not only by critical rainfall over a short period but also a much longer period of elevated pore pressure. Such rainfall-triggered landslides are difficult to monitor due to a lack of adequate data on the locations of failures and precipitation. Here, a method is presented using Transient Rainfall Infiltration and Grid-based Regional Slope stability (TRIGRS) as a tool to model the relationship between critical rainfall and antecedent pore pressure as they relate to slope stability, which can be useful for hazard assessment in sparse data regions. This is demonstrated by parameterizing the model with a combination of regional data sources, remote sensing, and temporal back-analysis based on two known failure events (June 2004 and July 2007). Ranges of possible geotechnical and hydraulic parameters were obtained from various local and regional sources, and soil thickness was modeled as a function of slope angle. Rainfall was estimated using satellite microwave radiometry data. For back-analysis, combinations of cohesion, friction angle, and water table depth were then tested in TRIGRS using trial and error until the predicted and observed failure times coincided for the two failure events. While the spatial prediction accuracy of the model is low and multiple solution sets are expected to exist, the results confirm that information regarding the critical pre-failure conditions and stability changes over time can be derived despite data-poor circumstances. Future studies can be undertaken extending this method to characterize many parameter combinations and incorporate more failure cases to develop probabilistic early-warning thresholds.

Extreme heavy rainfall due to Typhoon Talas on September 2–4, 2011 in the Kii Peninsula, Japan, triggered numerous floods and landslides. This study investigates the mechanism and the entire process of rainfall-induced deep-seated landslides forming two massive dams in the Kuridaira and Akatani valleys, respectively. The mechanism of the rapid deep-seated landslides is examined through a series of laboratory experiments on samples from sliding surfaces by using undrained high-stress dynamic-loading ring-shear apparatus. The test results indicate that the failure of samples is triggered by excess pore water pressure generation under a shear displacement from 2 to 7 mm with a pore pressure ratio ranging from 0.33 to 0.37. The rapid movement of landslides is mainly attributed to high mobility due to the liquefaction behavior of both sandstone-rich and shale samples. Geomorphic settings and landslide mobility are major contributing factors to the dam formation. Additionally, shear displacement control tests show that a certain amount of shear displacement between 2 and 7 mm along the sliding surfaces of the gravitationally deformed slopes might have led to the failures. Importantly, computer simulation with LS-RAPID software using input parameters obtained from physical experiments is employed to interpret the entire formation process of the abovementioned two landslide dams. The simulation results are examined in accordance with the observed on-site geomorphic features and recorded data to explain the possibility of sliding processes. The results further point out that local failures are initiated from the lower middle part of the landslide bodies where the geological boundary exists. This condition most probably influences the landslide initiation in the two case studies. This research is therefore helpful for hazard assessment of slopes that are susceptible to deep-seated landslides and other sequential processes in areas with geology and geomorphology similar to that of the Kii Peninsula.

A rainfall-induced compound disaster happened in Mocoa in the pre-dawn hours of 1 April 2017. More than 300 people were killed, and a large number of houses and roads were destroyed in the worst catastrophe in the history of Mocoa. To investigate this disaster, a detailed interpretation was carried out using high-resolution images. Analysis of disaster characteristics based on satellite image revealed that the disaster could be identified as a consequence of compound mountain hazards including landslides, debris flows, and mountain torrents. The mountain hazards converged in the mountain watershed, which amplified the disaster’s effects. Analysis considers that this disaster is the result of heavy rainfalls. Moreover, in-depth interpretation of rainfall data and satellite images spanning over 16 years reveals that the previous El Nino event (2014–2016) also played an important role, which caused reduced rainfall and vegetation coverage. The long period of drought brought by El Nino affected the growth of vegetation and reduced the ability of vegetation to cope with heavy rainfalls. The results reveal that both antecedent rainfalls and climate impact need to be taken into consideration for mountain hazard analysis.

At 5:38 am on the 24th June, 2017, a catastrophic rock avalanche destroyed the whole village of Xinmo, in Maoxian County, Sichuan Province, China. About 4.3 million m3 of rock detached from the crest of the mountain, gained momentum along a steep hillslope, entrained a large amount of pre-existing deposits, and hit the village at a velocity of 250 km/h. The impact produced a seismic shaking of ML = 2.3 magnitude. The sliding mass dammed the Songping gully with an accumulation body of 13 million m3. The avalanche buried 64 houses; 10 people were killed and 73 were reported missing. The event raised great concerns both in China and worldwide. Extensive field investigation, satellite remote sensing, UAV aerial photography, and seismic analysis allowed to identify the main kinematic features, the dynamic process, and the triggering mechanism of the event. With the aid of ground-based synthetic aperture radar monitoring, the hazard deriving from potential further instabilities in the source area has been assessed. The preliminary results suggest that the landslide was triggered by the failure of a rock mass, which had been already weakened by the Ms 7.5 Diexi earthquake in 1933. Several major earthquakes since then, and the long-term effect of gravity and rainfall, contributed to the mass failure. The high elevation, slope angle, and vegetation cover in the source area hinder geological field investigation and make hazard assessment difficult. Nonetheless, monitoring and prevention of similar collapses in mountainous areas must be carried out to protect human lives and infrastructures. To this aim, the integrated use of modern high-precision observation technologies is strongly encouraged.

The present paper aims at characterising Alpine anomalous basin-fan systems, in order to develop a method for hazard assessment for such fans. The review of previous studies revealed that anomalous basin-fan systems are often associated with deep-seated slope failure and present-day hazard is associated to debris flow occurrence. Taking into account these peculiarities, a modelling approach to assess the present day hazard in anomalous fans has been developed and applied to the Sernio fan (Valtellina, northern Italy). Debris flow inundation areas have been simulated by means of a numerical model (RApid Mass MovementS (RAMMS) debris flow), which includes a routine for the sediment entrainment. The range of the model parameters was defined based on previous studies, enabling a sensitivity analysis on the debris flow runout, as well as the flow height and velocity. Numerical results point out the paramount importance of entrainment phenomena on debris flow dynamic in anomalous systems, especially with reference to the bulking factor and debris yield rate that reach very high values, typical of basins with unlimited solid supply.

The Longxi river basin with the city of Dujiangyan, in the Sichuan province of South West China, belongs to the seismic area of the May 12, 2008 Wenchuan earthquake. Lots of loose co-seismic materials were present on the slopes, which in later years served as source material for rainfall-induced debris flows. A total of 12 debris flows, were triggered by heavy rainfall on August 13, 2010 in the study area. The FLO-2D numerical analysis software was adopted to simulate debris flows intensity, including movement velocities and maximum flow depths. A comparison of the measured fan spreading with the simulation results, the evaluation parameter Ω was used to verify accuracy of simulation, the results show Ω values ranging between 1.37 and 1.65 indicating relative good simulation results. This study also estimated the flood hydrograph for various recurrence intervals (20, 100, and 200 years, respectively) to perform scenario simulations of debris flows, and followed Swiss and Austrian standards to establish a debris flow hazard classification model on the basis of a combination of the debris flow intensity and the recurrence period. This study distinguishes three hazard classes: low, medium, and high. This proposed approach generated a debris flow hazard distribution map that could be used for disaster prevention in the Wenchuan earthquake-stricken area, South West China.

Landslide hazard, vulnerability, and risk-zoning maps are considered in the decision-making process that involves land use/land cover (LULC) planning in disaster-prone areas. The accuracy of these analyses is directly related to the quality of spatial data needed and methods employed to obtain such data. In this study, we produced a landslide inventory map that depicts 164 landslide locations using high-resolution airborne laser scanning data. The landslide inventory data were randomly divided into a training dataset: 70 % for training the models and 30 % for validation. In the initial step, a susceptibility map was developed using logistic regression approach in which weights were assigned to every conditioning factor. A high-resolution airborne laser scanning data (LiDAR) was used to derive the landslide conditioning factors for the spatial prediction of landslide hazard areas. The resultant susceptibility was validated using the area under the curve method. The validation result showed 86.22 and 84.87 % success and prediction rates, respectively. In the second stage, a landslide hazard map was produced using precipitation data for 15 years. The precipitation maps were subsequently prepared and show two main categories (two temporal probabilities) for the study area (the average for any day in a year and abnormal intensity recorded in any day for 15 years) and three return periods (15-, 10-, and 5-year periods). Hazard assessment was performed for the entire study area. In the third step, an element at risk map was prepared using LULC, which was considered in the vulnerability assessment. A vulnerability map was derived according to the following criteria: cost, time required for reconstruction, relative risk of landslide, risk to population, and general effect to certain damage. These criteria were applied only on the LULC of the study area because of lack of data on the population and building footprint and types. Finally, risk maps were produced using the derived vulnerability and hazard information. Thereafter, a risk analysis was conducted. The LULC map was cross-matched with the results of the hazard maps for the return period, and the losses were aggregated for the LULC. Then, the losses were calculated for the three return periods. The map of the risk areas may assist planners in overall landslide hazard management.

The town of Santa Teresa (Cusco Region, Peru) has been affected by several large debris-flow events in the recent past, which destroyed parts of the town and resulted in a resettlement of the municipality. Here, we present a risk analysis and a risk management strategy for debris-flows and glacier lake outbursts in the Sacsara catchment. Data scarcity and limited understanding of both physical and social processes impede a full quantitative risk assessment. Therefore, a bottom-up approach is chosen in order to establish an integrated risk management strategy that is robust against uncertainties in the risk analysis. With the Rapid Mass Movement Simulation (RAMMS) model, a reconstruction of a major event from 1998 in the Sacsara catchment is calculated, including a sensitivity analysis for various model parameters. Based on the simulation results, potential future debris-flows scenarios of different magnitudes, including outbursts of two glacier lakes, are modeled for assessing the hazard. For the local communities in the catchment, the hazard assessment is complemented by the analysis of high-resolution satellite imagery and fieldwork. Physical, social, economic, and institutional vulnerability are considered for the vulnerability assessment, and risk is eventually evaluated by crossing the local hazard maps with the vulnerability. Based on this risk analysis, a risk management strategy is developed, consisting of three complementing elements: (i) standardized risk sheets for the communities; (ii) activities with the local population and authorities to increase social and institutional preparedness; and (iii) a simple Early Warning System. By combining scientific, technical, and social aspects, this work is an example of a framework for an integrated risk management strategy in a data scarce, remote mountain catchment in a developing country.

In this paper, a study aimed to assess the rockfall hazard along a portion of the SS18 coastal road, located in the coastal area of Maratea (Basilicata Region, Southern Italy), is presented. The relevance of this study derives from the location of the study area, because the SS18 is a strategic roads in a touristic area, and, since the hazard assessment was performed in 2004 within a project financed by the Viability Regional Department of Autonomous National Company of Roads (ANAS), from the possibility to validate the results by using real rockfall events occurred after 2004. The procedure for assessing the rockfall hazard was composed of four sequential analyses: (i) geomechanical and kinematic characterization of rock mass, (ii) implementation of Romana’s (1985) Slope Mass Rating (SMR) method for identifying the potential boulder release areas (rockfall initiation areas), (iii) determination of rockfall trajectories by using a 3D numerical model (ROTOMAP), (iv) calculation and mapping of the hazard index by combining three factors, i.e., (a) lithological features of outcropping materials on rock faces, (b) kinematic compatibility defined by simulating the rockfall trajectories, and (c) spatial distribution of occurred rockfall events. Finally, the proposed methodology was validated by combining the distribution of the hazard levels along the road with the location on the SS18 of the rockfall events occurred from 2004 to 2014.

Rapid debris flows are among the most destructive natural hazards in steep mountainous terrains. Prediction of their path and impact hinges on knowledge of initiation location and the size and constitution of the released mass. To better link mass release initiation with debris flow paths and runout lengths, we propose to capitalize on a newly developed model for rainfall-induced landslide initiation (“Catchment-scale Hydro-mechanical Landslide Triggering” CHLT model, von Ruette et al. 2013) and couple it with simple estimates of debris flow runout distances and pathways. Landslide locations and volumes provided by the CHLT model are used as inputs to simulate debris flow runout distances with two empirical- and two physically-based models. The debris flow runout models were calibrated using two landslide inventories in the Swiss Alps obtained following a large rainfall event in 2005. We first fitted and tested the models for the “Prattigau” inventory, where detailed information on runout path was available, and then applied the models to landslides inventoried from a different catchment (“Napf”). The predicted debris flow runout distances (emanating from CHLT simulated landslide positions) were well in the range of observed values for the physically-based approaches. The empirical approaches tend to overestimate runout distances relative to observations. These preliminary results demonstrate the added value of linking shallow landslide triggering models with predictions of debris flow runout pathways for a range of soil states and triggering events, thus providing a more complete hazard assessment picture for debris flow exposure at the catchment scale.

On 4 July 2013, three catastrophic debris flows occurred in the Hougou, Majingzi, and Xiongjia gullies in Shimian county and produced debris dams and river blockages, resulting in serious casualties and huge economic loss. Though debris flows have been identified prior to the catastrophic events, their magnitudes and destructive power were far beyond early recognition and hazard assessment. Our primary objective for this study was to explore the formation mechanism and typical characteristics and to summarize the lessons learned from these disastrous events in order to avoid the repeat of such disasters in the future. Based on field investigation and imagery interpretation of remote sensing carried out following the catastrophic events, four conclusions were drawn: (1) The catastrophic debris flows were initiated from surface-water runoff, and the triggering factor was attributed to the local intensive rainfall with an hourly intensity of more than 46.7 mm. (2) Entrainment was the most important sediment-supplying method for the debris flow occurrence, and the source materials transported by debris flows from the three gullies were estimated to be about 97 × 104 m3 in volume altogether. (3) As surface-water runoff eroded and entrained hillslope and channel materials persistently, debris flows were characterized by intensive incision at upper or middle reaches and significant magnification effect in flow discharge and volume downstream. Corresponding peak discharge surveyed at the outlets of the Hougou, Majingzi, and Xiongjia gullies was estimated up to 751.0 m3/s, 870.1 m3/s, and 758.7 m3/s, respectively. (4) Debris flows that occurred from the three gullies all belonged to viscous ones and the bulk densities were calculated more than 1.80 g/cm3, indicating a huge carrying capacity and destructive impacting power. In addition, the lessons learned from the catastrophic events were summarized, including recognition and assessment on debris flow hazard and utilization of deposition fan. In this paper, prevention suggestions on debris flow prone valleys with high-vegetation coverage and low occurrence frequency were also put forward. The results of this study contribute to a better understanding on the initiation mechanism, dynamic characteristics, and disaster mitigation of debris flows initiated from intense rainfall and surface-water runoff in mountainous areas.

A debris-flow hazard assessment was conducted for the Medano Creek drainage basin, at Great Sand Dunes National Park and Preserve, following the 2,400 ha Medano Fire in 2010. Debris-flow probability and volume predictions were made using empirical regression models. Model parameters include burn severity, rainfall intensity, topographic characteristics, and soil properties. Model results provided park resource managers with information on potential sub-basin-specific hazards to park visitors, roads, and campsites. Monitoring of the first significant rainfall events following the fire and the resulting debris-flow responses provided means for model validation. Of the three probability models utilized, two predicted high probability of debris-flow occurrence for all sub-basins that produced debris flows, with numerous false positives, while the third failed to predict high probability in any of the sub-basins. The volume model predicted volumes within approximately one order of magnitude higher than those measured.

This article summarises activities and preliminary results of the International Programme on Landslides Project no. 179 “Database of glacial lake outburst floods (GLOFs)”. This project is planned for 3 years (2013–2015); the main objectives of the first year are (1) to create an online database and (2) to select collaborating partners. A survey of existing and relevant documents, information and organisations has been initiated along with the creation of a website (www.glofs-database.org) and the establishment of international collaboration. The first preliminary results show regional differences in various attributes of GLOF events (e.g. triggers, chronological distribution). These differences should be taken into consideration in regionally focused methods of hazard assessment, mitigation and consequently risk management.

International audience; Consequence analysis is, together with hazard evalua-tion, one of the major steps of landslide risk assessment. However, a significant discrepancy exists between the number of published landslide hazard and landslide consequence studies. While various methodologies for regional-scale hazard assessment have been developed during the last decade, studies for estimating and visualising possible landslide consequences are still limited, and those existing are often difficult to apply in practice mainly be-cause of the lack of data on the historical damage or on landslide damage functions. In this paper, an indicator-based GIS-aided methodology is proposed with an application to regional-scale consequence analysis. The index, called Potential Damage Index, allows describing, quantifying, valuing, totalizing and visualising different types of consequences. The method allows estimating the possible damage caused by landslides by combining weighted indicators reflecting the exposure of the elements at risk. Direct (physical injury, and structural and functional damage) and indi-rect (socio-economic impacts) consequences are individually analysed and subsequently combined to obtain a map of total consequences due to landsliding. Geographic visualisation of the index allows the delineation of the areas exposed to any type of possible impacts that could be combined with a corresponding map displaying landslide probability of occurrence. The method has been successfully applied to analyse the present consequences in the Barcelonnette Basin (South French Alps). These maps con-tribute to development of adequate land use and evacuation plans, and thus are important tools for local authorities and insurance companies.

Rock fall hazard zoning is a challenging yet necessary task to be accomplished for planning an appropriate land use in mountainous areas. Methodologies currently adopted for elaborating zoning maps do not provide satisfactory results though, due to uncertainties and related assumptions characterising hazard assessment. The new Cadanav methodology, presented in this paper, aims at improving quantitative hazard assessment and zoning at the local scale, by reducing uncertainties mainly related to the technique for combining rock fall intensity and frequency of occurrence. Starting from available information on rock fall failure frequency and trajectory simulation results, the procedure merges in a strict way temporal frequency, probability of reach and energy data and evaluates the hazard degree by means of “hazard curves”. These curves are described at each point of the slope by a series of energy–return period couples representing the hazardous conditions which may possibly affect that location. The new Cadanav methodology is here detailed and compared to its original version. Hazard zoning results are illustrated along two different 2D slope profiles, for linear homogeneous cliff configurations, and according to the Swiss intensity–frequency diagram for rock fall hazard zoning. However, the procedure can be easily used with any other intensity–frequency diagram prescribed in national guidelines and, additionally, extended to problems involving 3D topographies.

The Groapa Vântului (Wind’s Dip) landslide, situated in the Buzau Carpathians, on the right-hand slope of the Siriu Reservoir, occurred in April 2006, after the first local movements were signaled in September–October 2005. It represents a reactivation of an older, apparently relict (and well covered by a secular beech forest) landslide, which blocked Siriu Reservoir for several weeks and caused a major change in the sedimentation regime downstream of it. The volume of the displaced material reached almost 2.5 million m3, affecting a surface of more than 250,000 m2 and reducing the reservoir’s volume by almost 2 million m3. The landslide developed on a lithological contact of Paleogene flysch formations and features steep (40–50°) and high (up to 30 m) scarps, as well as complex inner sectors, of rotational, translational, and compresional movement. The assessment of landslide’s morphodynamic behavior is based on repeated geomorphological field mapping and measurements, differential Global Positioning System, and total station profiles, and mobile and fixed landmarks. This preliminary assessment contributes to the understanding of the behavior of old, peri-glacial landslide reactivations and also represents progress towards a better hazard assessment.

Dam-breaches that cause outburst floods may induce downstream hazards. Because landslide dams can breach soon after they are formed, it is critical to assess the stability quickly to enable prompt action. However, dam geometry, an essential component of hazard evaluation, is not available in most cases. Our research proposes a procedure that utilizes post-landslide orthorectified remote sensing images and the pre-landslide Digital Terrain Model in the Geographic Information System to estimate the geometry of a particular dam. The procedure includes the following three modules: (1) the selection of the reference points on the dam and lake boundaries, (2) the interpolation of the dam-crest elevation, and (3) the estimation of dam-geometry parameters (i.e., the height, length, and width), the catchment area, the volumes of barrier lake and landslides dam. This procedure is demonstrated through a case study of the Namasha Landslide Dam in Taiwan. It was shown the dam-surface elevation estimated from the proposed procedure can approximate the elevation derived from profile leveling after the formation of the landslide dam. Thus, it is feasible to assess the critical parameters required for the landslide dam hazard assessment rapidly once the ortho-photo data are available. The proposed procedure is useful for quick and efficient decision making regarding hazard mitigation.

Flow-like landslides have caused significant damage and casualties worldwide. However, studying such phenomena with traditional simulation methods is made difficult by their complex fluidization characteristics. In this paper, we use smoothed-particle hydrodynamics (SPH) for the run-out analysis of flow-like landslides. Compared with conventional methods, the proposed SPH modeling technique is the combination of a Bingham flow model and Navier–Stokes equations in the framework of computational fluid dynamics. At first, two benchmark problems of dam break and granular flow are simulated and verified to evaluate the accuracy of the SPH model. Then, run-out analyses are performed for flow-like landslides triggered by the Ms 8.0 Wenchuan earthquake that occurred on 12 May 2008 in Sichuan Province, China. Run-out analyses of the Tangjiashan, Wangjiayan, and Donghekou landslides are conducted by the application of SPH models to real flow-like landslides. All simulations show good agreement with characteristics of flow-like landslides observed in the field. We have found that numerical modeling can capture the fundamental dynamic behavior of these flow-like landslides and produce preliminary results for hazard assessment and site selection for reconstruction in earthquake-prone areas.

The Niumiangou Creek rock avalanche was triggered by an Ms 8.0 earthquake that happened on 12 May 2008 in the Sichuan Province, China. The rock avalanche traveled a horizontal distance of 3.0 km over a vertical elevation difference of 0.89 km, equivalent to a coefficient of friction of only 0.29. The travel path of the rock avalanche can be divided into three segments: (1) failing and disintegrating, (2) flying, (3) flowing. In the failing and disintegrating segment, the rock slope failed because of the coupled action of horizontal and vertical force of the earthquake, then smashed into the opposite mountain and disintegrated. In the flying segment, the disintegrating rock mass changed direction and flew into the Lianhuaxin Creek, which was different from the previous research results that concluded rock debris flowed in Lianhuaxin Creek. A great amount of air trapped and compressed under the rock debris acted as air cushion and supported the rock debris to fly a further distance. In the flowing segment, the rock debris flowed on the ground surface in Niumiangou Creek. The flowing velocity has been estimated from the maximum elevation and runup according to the damaged trimlines of the debris. The saturated fine material in Niumiangou Creek entrained by the failed debris mass is thought to have contributed to the long runout of the debris. The Niumiangou Creek rock avalanche is one of the three longest rock avalanches triggered by Wenchuan earthquake. The conclusions of the paper have implications for hazard assessment of potential rock avalanches in the earthquake area and the other similar mountainous area in west China.

The Research Centre on Prediction, Prevention and Control of Georisks, "Sapienza Universita di Roma" (CERI) was selected as one of the World Centres of Excellence on Landslide Risk Reduction (WCoE) under the title of “Research and development of advanced technologies for landslide hazard analysis in Italy” in the period 2008–2011. The present paper provides background information on the activities carried out by the CERI, in the frame of the WCoE network. Pre-defined purposes have been achieved by the implementation of integrated monitoring systems and early warning systems for landslides movements. The application of GBInSAR technique for monitoring landslides interacting with infrastructures is discussed, and two case histories are presented. It is shown that this technique is particularly suitable for the displacements monitoring of landslides interacting with infrastructures, thanks to its peculiar features (i.e. areal mapping, operability under every weather and lighting conditions and continuous and completely remote monitoring). Hence, it can be considered a very important tool for the reduction of risks connected to the realisation and activity of large infrastructures.

The Sharm El-Sheikh/Ras-Nasrani area is one of the most attractive tourist resorts in Egypt particularly and in the world in general. The area has been rapidly growing during the last few years. Many construction projects including villages, hotels, beaches, and roads have recently been undertaken. The following study demonstrates the use of high-resolution satellite images, QuickBird imagery, acquired on June 2nd, 2007 (0.61 m spatial resolution), for detailed mapping of the recent developments and the slope instability hazard zones. The results were confirmed by field reconnaissance. Our findings indicate that there are many development areas threatened by unstable zones. The hazard areas have been delineated and classified, and a final slope instability hazard map has been established. Different factors were found to have a crucial impact on the slope instability, some natural and others man-made. These unstable localities need to be remediated and/or monitored to avoid any loss in property and/or lives.

This paper presents a detailed field investigation and hazard assessment for an unstable rock slope above an industrial site in the Riviera valley in the Canton of Ticino in southern Switzerland. An integrated framework was used to counter issues of geological complexity and uncertainty, linking geological mapping and numerical modeling to develop an understanding of the acting instability mechanism to 2-D and 3-D dynamic runout simulations to predict the travel path and reach in the event of a large volume rockslide. The results from the numerical stability analysis provided a means to constrain failure volume estimates, whereas a series of calibration simulations were used to constrain the input parameters required by the rheological model used for the runout analysis. Results from this assessment suggest that current protection measures in place may not be sufficient, helping local authorities to define hazard zones and aid further development plans for the region.

The Yudonghe landslide is located in a upcoming reservoir region of a 233-m-high Shuibuya rockfill dam, 2,300 m away from the dam site. It consists of a massive landslide with upper and lower segments and two secondary slides, i.e. an eastern secondary slide and a western secondary slide. In this paper, values of factor of safety (FS) for various masses were calculated in a scenario of reservoir impounding-induced increase in groundwater levels, using a method of three-dimensional (3D) limit equilibrium. Results showed that the smallest value of FS for the massive landslide is 1.12 computed on the presupposition of reactivating along a bottom slide zone in case of an earthquake. The smallest FS value of the lower slide mass is 1.12 in a possible direction, given earthquake occurrence and a groundwater level of 225 m above the sea level. This FS value shows that the lower slide mass is stable in case of groundwater increasing. In addition, by the calculation of the 3D limit equilibrium method, the FS value of the east secondary slide is approximately 1.0 in different groundwater levels under consideration of earthquake occurrence, which reflects that this mass is prone to reactivate when external factors are taken into effect.

In Emilia-Romagna, over 32,000 landslide bodies cover one-fifth of the hilly and mountainous territory. The majority of them originated as earth-flows after the last glacial maximum and grew during the rainiest periods of the Holocene through the superimposition of new earth-flows. Reactivation of these large landslides is the main problem the geologists of Emilia-Romagna are facing now. Intense and/or prolonged precipitation play a major role as triggering factors in reactivating landslide bodies, but also the importance of snowmelt is suggested by the monthly distribution of landslide events. Almost all the present-day landslide activity is due to the reactivation of pre-existing landslide bodies. Consequently, territorial planning and geo-thematic cartography are fundamental tools for the reduction of risk. The Emilia-Romagna geo-thematic cartography (1:10,000) is legally binding and regulates land use in regional, municipal and basin plans.

Debris flows, debris floods and floods in mountainous areas are responsible for loss of life and damage to infrastructure, making it important to recognize these hazards in the early stage of planning land developments. Detailed terrain information is seldom available and basic watershed morphometrics must be used for hazard identification. An existing model uses watershed area and relief (the Melton ratio) to differentiate watersheds prone to flooding from those subject to debris flows and debris floods. However, the hazards related to debris flows and debris floods are not the same, requiring further differentiation. Here, we demonstrate that a model using watershed length combined with the Melton ratio can be used to differentiate debris-flow and debris-flood prone watersheds. This model was tested on 65 alluvial and colluvial fans in west central British Columbia, Canada, that were examined in the field. The model correctly identified 92% of the debris-flow, 83% of the debris-flood, and 88% of the flood watersheds. With adaptation for different regional conditions, the use of basic watershed morphometrics could assist land managers, scientists, and engineers with the identification of hydrogeomorphic hazards on fans elsewhere.