Annual Landslide Research Articles

A research on the relationship between landslide area changes and environmental factors in the southern Tibetan plateau

Introduction: Landslides are known to be one of the most frequent types of geological disasters. However, there is not an established method for large-scale, rapid, and high-precision landslide extraction. The quantitative impact of environmental changes on landslide development is also not well understood, which hinders accurate assessments and decision-making in environmental and disaster response. The polar regions, including the Antarctic, the Arctic, and the Tibetan plateau (TP), sensitive to global environmental changes, are significantly affected by global warming. This leads to extensive landslide development, particularly in the southern TP. This research focuses on new landslides in the southern TP, exploring extraction methods and the relationship between landslides and environmental factors.Methods: Utilizing the Google Earth Engine (GEE) and an improved Otsu threshold segmentation algorithm, we processed remote sensing images with 10 m resolution to identify landslide areas. The proposed Normalized Landslide Bare-soil Separation Index (NDLBSI) achieved an 87% pre-extraction accuracy in extracting landslides from Sentinel-2 images from 2019 to 2023. For the pre-extraction results, manual interpretation and correction were carried out, and a model correlating annual landslide changes with environmental factors was established based on least squares multivariate statistical methods.Results: Results show that a significant increase in landslide areas in the southern TP over the past 5 years, correlating with the watershed-wide increase in annual average temperature and vegetation cover, along with a decrease in snow cover area.Discussion: These changes could affect soil and rock moisture, influencing soil stability and landslide occurrence. The study provides valuable insights for large-scale landslide detection and understanding the environmental factors influencing landslides, which is of some significance for landslide hazards early warning.

Geodetic Evidence for Cascading Landslide Motion Triggered by Extreme Rain Events at Joshimath, NW Himalaya

AbstractSlope instability due to tectonic, hydrological and anthropogenic activities cause severe landslides in Himalaya. Joshimath, a densely populated Himalayan town witnessed a catastrophic landslide event during December 2022 and January 2023 causing damages to ∼700 buildings. We use Interferometric synthetic aperture radar, Global Positioning System and rainfall measurements to probe the kinematics of the Joshimath landslide. We separate the seasonal and episodic deformation components using singular spectrum analysis. While the low amplitude annual landslide motions are modulated by seasonal precipitation, acceleration phases are triggered by extreme rain events. Our analysis revealed episodes of cascading motions triggered by extreme rain events resulting an overall increase in landslide velocity from −22 mm/yr during 2004–2010 to −325 mm/yr during 2022–2023. We estimate the landslide depth (∼30 m) and hydraulic diffusivity (∼3 × 10−5 m2/s) using a 1‐D pore‐water pressure diffusion model. Our study reveals the importance of systematic monitoring of ground deformation and weather parameters for landslide hazard mitigation.

Assessment of Landslide Risk Near Mountain Power Generation Facilities in Korea

Rising greenhouse gases fuel global warming, triggering disasters like droughts, floods, and landslides. Efforts to reduce emissions and combat climate change focus on renewable energy (wind, wave, hydrogen, and solar). However, rapid expansion of solar facilities in mountainous regions, coupled with unchecked logging, intensifies landslides and environmental pollution. Therefore, in this study, the risk of installed solar power generation facilities was evaluated based on the precipitation in a year and rainy season only, and topographical characteristics. The annual cumulative precipitation and rainy season were calculated for 2020, and the risk of landslides caused by rainfall was evaluated through correlation with the annual landslide area. As of 2020, more than 50% of landslides occurred in the areas having a slope range of 30 - 60% and the landslide damage area was also highly correlated with the precipitation during the rainy season (R2 = 0.74). Prior to the installation of solar power generation facilities in the steep mountainous area, more strict and appropriate verification must be done. Additionally, a systematic management plan of solar power generation facilities should be investigated in a permission process.Landslide risk of mountainous solar power generation facilities versus precipitation.

Using the Spatiotemporal Hot Spot Analysis and Multi-Annual Landslide Inventories to Analyze the Evolution and Characteristic of Rainfall-Induced Landslide at the Subwatershed Scale in Taiwan

This study used rainfall and annual landslide data for the 2003–2017 period in Taiwan to determine the long-term evolution of landslides and conducted a spatiotemporal analysis of landslides at the subwatershed scale. The historically severe landslide induced by Typhoon Morakot in 2009 was mainly distributed in the central mountainous region and southern Taiwan. The Mann–Kendall trend test revealed that in 2003–2017, 13.2% of subwatersheds in Taiwan exhibited an upward trend of landslide evolution. Local outlier analysis results revealed that the landslide high–high cluster was concentrated in the central mountainous region and southern Taiwan. Moreover, the spatiotemporal analysis indicated 24.2% of subwatersheds in Taiwan in 2003–2017 as spatiotemporal landslide hot spots. The main patterns of spatiotemporal landslide hot spots in 2003–2017 were consecutive, intensifying, persistent, oscillating, and sporadic hot spots. The recovery rate in the first two years after the extreme rainfall-induced landslide event in Taiwan was 22.2%, and that in the third to eighth years was 31.6%. The recovery rate after extreme rainfall-induced landslides in Taiwan was higher than that after major earthquake-induced landslides in the world, and the new landslides were easily induced in the area of rivers and large landslide cases after Typhoon Morakot in 2009.

Evaluating the Landslide Stability and Vegetation Recovery: Case Studies in the Tsengwen Reservoir Watershed in Taiwan

The sediment yield from numerous landslides triggered in Taiwan’s mountainous regions by 2009 Typhoon Morakot have had substantial long-term impacts on the evolution of rivers. This study evaluated the long-term evolution of landslides induced by 2001 Typhoon Nari and 2009 Typhoon Morakot in the Tsengwen Reservoir Watershed by using multiannual landslide inventories and rainfall records for the 2001–2017 period. The landslide activity, vegetation recovery time, and the landslide spatiotemporal hotspot analyses were used in the study. Severe landslides most commonly occurred on 35–45° slopes at elevations of 1400–2000 m located within 500 m of the rivers. The average vegetation recovery time was 2.29 years, and landslides with vegetation recovery times exceeding 10 years were most frequently retrogressive landslide, riverbank landslides in sinuous reaches, and the core area of large landslides. The annual landslide area decline ratios after 2009 Typhoon Morakot in Southern Taiwan was 4.75% to 7.45%, and the time of landslide recovery in the Tsengwen reservoir watershed was predicted to be 28.48 years. Oscillating hotspots and coldspots occupied 95.8% of spatiotemporal patterns in the watershed area. The results indicate that landslides moved from hillslopes to rivers in the 2001–2017 period because the enormous amount of sediment deposited in rivers resulted in the change of river geomorphology and the riverbank landslides.

Spatiotemporal Hotspots and Decadal Evolution of Extreme Rainfall-Induced Landslides: Case Studies in Southern Taiwan

The 2009 Typhoon Morakot triggered numerous landslides in southern Taiwan, and the landslide ratios in the Ailiao and Tamali river watershed were 7.6% and 10.7%, respectively. The sediment yields from the numerous landslides that were deposited in the gullies and narrow reaches upstream of Ailiao and Tamali river watersheds dominated the landslide recovery and evolution from 2010 to 2015. Rainfall records and annual landslide inventories from 2005 to 2015 were used to analyze the landslide evolution and identify the landslide hotspots. The landslide recovery time in the Ailiao and Tamali river watershed after 2009 Typhoon Morakot was estimated as 5 years after 2009 Typhoon Morakot. The landslide was easily induced, enlarged, or difficult to recover during the oscillating period, particularly in the sub-watersheds, with a landslide ratio > 4.4%. The return period threshold of rainfall-induced landslides during the landslide recovery period was <2 years, and the landslide types of the new or enlarged landslide were the bank-erosion landslide, headwater landslide, and the reoccurrence of old landslide. The landslide hotspot areas in the Ailiao and Tamali river watershed were 2.67–2.88 times larger after the 2009 Typhoon Morakot using the emerging hot spot analysis, and most of the new or enlarged landslide cases were identified into the oscillating or sporadic or consecutive landslide hotspots. The results can contribute to developing strategies of watershed management in watersheds with a dense landslide.

Landslide Susceptibility Based on Extreme Rainfall-Induced Landslide Inventories and the Following Landslide Evolution

Landslide susceptibility assessment is crucial for mitigating and preventing landslide disasters. Most landslide susceptibility studies have focused on creating landslide susceptibility models for specific rainfall or earthquake events, but landslide susceptibility in the years after specific events are also valuable for further discussion, especially after extreme rainfall events. This research provides a new method to draw an annual landslide susceptibility map in the 5 years after Typhoon Morakot (2009) in the Chishan River watershed in Taiwan. This research establishes four landslide susceptibility models by using four methods and 12 landslide-related factors and selects the model with the optimum performance. This research analyzes landslide evolution in the 5 years after Typhoon Morakot and estimates the average landslide area different ratio (LAD) in upstream, midstream, and downstream of the Chishan River watershed. We combine landslide susceptibility with the model with the highest performance and average annual LAD to draw an annual landslide susceptibility map, and its mean correct ratio ranges from 62.5% to 73.8%.

Spatiotemporal Distribution of Nonseismic Landslides during the Last 22 Years in Shaanxi Province, China

The spatiotemporal distribution of landslides provides valuable insight for the understanding of disastrous processes and landslide risk assessment. In this work, we compiled a catalog of landslides from 1996 to 2017 based on existing records, yearbooks, archives, and fieldwork in Shaanxi Province, China. The statistical analyses demonstrated that the cumulative frequency distribution of the annual landslide number was empirically described by a power-law regression. Most landslides occurred from July to October. The relationship between landslide time interval and their cumulative frequency could be fitted using an exponential regression. The cumulative frequency of the landslide number could be approximated using the power-law function. Moreover, many landslides caused fatalities, and the number of fatalities was related to the number of landslides each month. Moreover, the cumulative frequency was significantly correlated with the number of fatalities and exhibited a power-law relationship. Furthermore, obvious differences were observed in the type and density of landslides between the Loess Plateau and the Qinba Mountains. Most landslides were close to stream channels and faults, and were concentrated in cropland at elevations from 600–900 m and on slope gradients from 30–40°. In addition, the landslide frequency increased as the annual rainfall levels increased over a large spatial scale, and the monthly distribution of landslides presented a significant association with the precipitation level. This study provides a powerful method for understanding the spatiotemporal distribution of landslides via a rare landslide catalog, which is important for engineering design and planning and risk management.

Urban landslide monitoring by combined use of multiple methodologies - a case study on Sv. Anton town, Slovakia

ABSTRACTWe employed integrated methods to assess the landslide movement in Sv. Anton town in the Western Carpathians Neogene Volcanic Field (Central Slovakia). The integrated diagnostics required study of the landslide kinematic activity by a combination of Global Navigation Satellite Systems (GNSS) and Electrical Resistivity Tomography (ERT) imaging from November 2013 to March 2015. A topographic model with 2-cm accuracy was constructed from Unmanned Aerial Vehicles (UAV) photogrammetry. Continuous spatial datasets of movement and displacement field vectors were interpolated from the measured movements over the entire study period. Although deformation studies in Slovakia have a long-term tradition, complex interdisciplinary studies in urbanized areas are still lacking. This inspired our main objectives: to identify landslide kinematics and to reconstruct and define the rates of annual landslide movement obtained from geodetic measurement at the monitoring points. Our results demonstrate how landslide integrated diagnostics contribute to the detection of slope instability, with a maximum velocity of 60.82 mm/yr during the summer period. The precipitation effects are consistent with the Sv. Anton landslide displacement acceleration, and the following increases in total monthly precipitations are staggering compared to long-term monthly averages: July precipitation increased by 175.3%, August by 203.3%, and September by 198.1%.

Instability Index Derived from a Landslide Inventory for Watershed Stability Assessment and Mapping

Watersheds represent natural units of social–ecological systems and affect crop productivity. Extreme weather events accelerate the natural erosion process by triggering more landslides in watersheds. To achieve the land degradation neutrality set up by the UN’s Sustainable Development Goals, it is necessary to assess and map spatiotemporal landslides in watersheds. This paper proposes an innovative approach to calculating the instability index by preparing an annual landslide inventory, determining the optimum sub-watershed, compensating for shadow effects on the time series of the landslide area ratio, and classifying the standard deviations to different levels of instability. Taking the Qingquan watershed as an example, the instability index calculated for 22 sub-watersheds makes it possible to identify hot spots that are prone to collapse. This new index can also be used to evaluate the effectiveness of watershed management before and after completion of a specific engineering project, as well as to update the latest upriver situation to evaluate current management practices and develop strategies for future planning. Based on this new approach, the Soil and Water Conservation Bureau of Taiwan assesses the stability of 28 watersheds, and the results are made available on the Big Geospatial Information System.

Evaluation of cost and benefit of sediment based on landslide and erosion models

Sediment hazard mapping is a fundamental tool for disaster management and mitigation activities in Thailand. Several countries are at risk of suffering landslide damages, but few studies have focused on the quantitative estimate of damages at a large scale. Most studies have considered the effects of landslide and soil erosion events from the perspective of their economic drawbacks, and there is no consensus on the quantitative assessment of the positive economic impacts of these events. Therefore, this study aimed to support the future assessment of landslides and other soil erosion events on sediment resources from positive economic perspectives. The results showed that the expected annual landslide damage cost in Thailand is approximately 204,000 USD per square kilometer. The cost for dredging sediment in Thailand is 108 USD per square kilometer. However, the benefit of sediment to private sectors is cost more than an average of 2040 USD per square kilometer, and the benefit values increased to approximately 15,000 USD per square kilometer in areas upstream of dams. In addition, there is an average benefit of 16,627 USD per year to the public sectors in each subdistrict of Thailand.

From landslide susceptibility to landslide frequency: A territory-wide study in Hong Kong

Rain-induced shallow landslide is the major type of landslide that happens on natural terrain in Hong Kong due to its high seasonal rainfall and deep weathering soil profile. The Geotechnical Engineering Office has been in a leading role to steer the risk management of natural terrain landslides in Hong Kong. Recently, the territory-wide rainfall-based landslide susceptibility model (in terms of landslide density per year) has been developed to predict the number of natural terrain landslides that may occur in an anticipated rainfall event. Subsequently, the storm-based landslide density has been transformed to the annual landslide frequency to compile the territory-wide landslide frequency map by incorporating the mean annual frequency of occurrence of different probable rainfall scenarios. The annual rainfall frequency of a particular rainfall scenario is derived from its return period, determined based on the abundant real-time rainfall data at a five-minute interval from 110 automatic raingauges across Hong Kong at an average density of 10 km2/gauge. The transformation is discussed in this paper, together with the evaluation of the performance of the landslide frequency map. In addition, the potential applications of the map in Hong Kong and the pitfalls of the common evaluation methods, including the receiver operating characteristic curve and the success-rate curve, are highlighted.

A hydroclimatological approach to predicting regional landslide probability using Landlab

Abstract. We develop a hydroclimatological approach to the modeling of regional shallow landslide initiation that integrates spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km2. The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at mid-elevations (1400 to 2400 m), and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.

An integrated approach to earthquake-induced landslide hazard zoning based on probabilistic seismic scenario for Phlegrean Islands (Ischia, Procida and Vivara), Italy

In this study we present an integrated approach to assess earthquake-induced landslide hazard at the source area of the slope instability process. The method has been applied to the case study of Ischia, Procida and Vivara islands that represent an integral part of the Campi Flegrei, a densely populated, active volcanic area, located at the NW margin of the Naples Bay, Italy.The proposed method follows a stepwise procedure including: 1) Probabilistic Seismic Hazard Analysis (PSHA); 2) assessment of site and topographic effects; 3) input of the PSHA outputs into a classic sliding rigid-block analysis for slope instability (Newmark's approach); 4) construction of landslide frequency - magnitude curves for the estimate of the slope failure probability as a function of defined Newmark's threshold values under different probabilistic seismic scenarios; 5) construction of earthquake-induced landslide hazard maps at the source area, based on the integration of the probabilistic approach and the geological, morphological and geotechnical database available for the study area.The Probabilistic Seismic Hazard Analysis (PSHA) is aimed at the definition of the seismic input with different annual exceedance frequency. PSHA results, expressed in terms of Peak Ground Acceleration (PGA) at the bedrock, are calculated for 14 return periods (T) ranging from 10 to 2000yr. PGA values have been corrected for the site effect associated with geological and morphologic conditions for each selected return period.Secondly, the corrected PGA values have been used as an input for the classic sliding rigid-block Newmark's approach, implemented in a Geographic Information System (GIS) to assess the relative potential for slope failure (landslide susceptibility) both in static (Factor of Safety, FS) and dynamic (Critical acceleration, ac) conditions. The combination of T-dependent, site-corrected PGA with the critical acceleration allowed for the calculation of the expected Newmark's displacements (DN) under different probability of exceeding or return periods (probabilistic seismic scenarios).As a further step, in order to estimate the earthquake-induced landslide hazard, we defined three DN threshold values that have considered capable to trigger shallow seismic-induced landslides in the regional context, and mapped the sectors with DN values exceeding such thresholds. On this basis, we constructed frequency-magnitude curves to estimate the probability of slope failures at the source areas, as a function of DN, by correlating the annual probability of landslide occurrence with the number of terrain cells associated with DN values greater than the selected threshold.Finally, based on the estimated annual landslide frequency of the seismic triggering event for each terrain cell, we implemented a 1:5000 scale map of Earthquake-induced Landslide Hazard for Ischia, Procida and Vivara Islands. The map reports the zoning and ranking of study area into sub-zones, on a pixel basis, according to the degree of the potential hazard from landslides derived by the frequency of the triggering event.

Storm-triggered landslides in the Peruvian Andes and implications for topography, carbon cycles, and biodiversity

Abstract. In this study, we assess the geomorphic role of a rare, large-magnitude landslide-triggering event and consider its effect on mountain forest ecosystems and the erosion of organic carbon in an Andean river catchment. Proximal triggers such as large rain storms are known to cause large numbers of landslides, but the relative effects of such low-frequency, high-magnitude events are not well known in the context of more regular, smaller events. We develop a 25-year duration, annual-resolution landslide inventory by mapping landslide occurrence in the Kosñipata Valley, Peru, from 1988 to 2012 using Landsat, QuickBird, and WorldView satellite images. Catchment-wide landslide rates were high, averaging 0.076 % yr−1 by area. As a result, landslides on average completely turn over hillslopes every ∼ 1320 years, although our data suggest that landslide occurrence varies spatially and temporally, such that turnover times are likely to be non-uniform. In total, landslides stripped 26 ± 4 tC km−2 yr−1 of organic carbon from soil (80 %) and vegetation (20 %) during the study period. A single rain storm in March 2010 accounted for 27 % of all landslide area observed during the 25-year study and accounted for 26 % of the landslide-associated organic carbon flux. An approximately linear magnitude–frequency relationship for annual landslide areas suggests that large storms contribute an equivalent landslide failure area to the sum of lower-frequency landslide events occurring over the same period. However, the spatial distribution of landslides associated with the 2010 storm is distinct. On the basis of precipitation statistics and landscape morphology, we hypothesise that focusing of storm-triggered landslide erosion at lower elevations in the Kosñipata catchment may be characteristic of longer-term patterns. These patterns may have implications for the source and composition of sediments and organic material supplied to river systems of the Amazon Basin, and, through focusing of regular ecological disturbance, for the species composition of forested ecosystems in the region.

Annual landslide risk and effectiveness of risk reduction measures in Shihmen watershed, Taiwan

Landslide risk analysis procedures in this study could evaluate annual landslide risk, and assess the effectiveness of measures. Risk analysis encompassing landslide hazard, vulnerability, and resilience capacity was used to evaluate annual landslide risk. First, landslide spatial, temporal, and area probabilities were joined to estimate annual probability of landslides with an area exceeding a certain threshold in each slope unit. Second, different elements were assigned corresponding values and vulnerabilities to calculate the expected property and life losses. Third, the resilience capacities of communities were calculated based on the scores obtained through community checklists and the weights of items, including “the participation experience of disaster prevention drill,” “real-time monitoring mechanism of community,” “autonomous monitoring of residents,” and “disaster prevention volunteer.” Finally, the annual landslide probabilities, expected losses, and resilience capacities were combined to evaluate annual landslide risk in Shihmen watershed. In addition, annual risks before and after the implementation of measures were compared to determine the benefits of measures, and subsequently benefit–cost analysis was performed. Communities with high benefit–cost ratios included Hualing, Yisheng, Siouluan, and Gaoyi. The watershed as a whole had a benefit–cost ratio far greater than 1, indicating the effectiveness of measures was greater than the investment cost. The results of factor sensitivity analysis revealed changes in vulnerabilities and mortality rates would increase the uncertainty of risk, and that raise in annual interest rates or reduction in life cycle of measures would decrease the benefit–cost ratio. However, these changes did not reverse the cost-effective inference.

Landslide risk assessment in a densely populated hilly area

Landslide risk assessments provide essential information to develop loss reduction strategies. However, only very few studies produce risk maps. Lack of temporal data on landslides is one of the reasons. This paper develops a methodology to assess the economic risk of landslides when limited landslide hazard information is available. It provides spatially explicit estimates of future landslide risks in a densely populated low-relief area and applies different spatial probability scenarios. In the study area (710 km2), residential buildings cover 7 % of the area with elements at risk, but are responsible for about 86 % of the total risk. Roads cover 8 % of the area with elements at risk but are responsible for about 14 % of the total risk. The annual landslide risk is approximately 50 million to 80 million euros 2011 values depending on the spatial probability scenario considered. This indicates that landslide mitigation efforts would create considerable benefits. Landslide risk would reduce significantly if better land use zoning would be applied to sterilize landslide-prone terrain as particularly the residential buildings and access roads determine the total risk.

Kinematic behaviour of a large earthflow defined by surface displacement monitoring, DEM differencing, and ERT imaging

Large earthflow-type landslides are destructive mass movement phenomena with highly unpredictable behaviour. Knowledge of earthflow kinematics is essential for understanding the mechanisms that control its movements. The present paper characterises the kinematic behaviour of a large earthflow near the village of Ľubietová in Central Slovakia over a period of 35years following its most recent reactivation in 1977. For this purpose, multi-temporal spatial data acquired by point-based in-situ monitoring and optical remote sensing methods have been used. Quantitative data analyses including strain modelling and DEM differencing techniques have enabled us to: (i) calculate the annual landslide movement rates; (ii) detect the trend of surface displacements; (iii) characterise spatial variability of movement rates; (iv) measure changes in the surface topography on a decadal scale; and (v) define areas with distinct kinematic behaviour. The results also integrate the qualitative characteristics of surface topography, in particular the distribution of surface structures as defined by a high-resolution DEM, and the landslide subsurface structure, as revealed by 2D resistivity imaging. Then, the ground surface kinematics of the landslide is evaluated with respect to the specific conditions encountered in the study area including slope morphology, landslide subsurface structure, and local geological and hydrometeorological conditions. Finally, the broader implications of the presented research are discussed with particular focus on the role that strain-related structures play in landslide kinematic behaviour.

Integrating spatial, temporal, and size probabilities for the annual landslide hazard maps in the Shihmen watershed, Taiwan

Abstract. Landslide spatial, temporal, and size probabilities were used to perform a landslide hazard assessment in this study. Eleven intrinsic geomorphological, and two extrinsic rainfall factors were evaluated as landslide susceptibility related factors as they related to the success rate curves, landslide ratio plots, frequency distributions of landslide and non-landslide groups, as well as probability–probability plots. Data on landslides caused by Typhoon Aere in the Shihmen watershed were selected to train the susceptibility model. The landslide area probability, based on the power law relationship between the landslide area and a noncumulative number, was analyzed using the Pearson type 5 probability density function. The exceedance probabilities of rainfall with various recurrence intervals, including 2, 5, 10, 20, 50, 100 and 200 yr, were used to determine the temporal probabilities of the events. The study was conducted in the Shihmen watershed, which has an area of 760 km2 and is one of the main water sources for northern Taiwan. The validation result of Typhoon Krosa demonstrated that this landslide hazard model could be used to predict the landslide probabilities. The results suggested that integration of spatial, area, and exceedance probabilities to estimate the annual probability of each slope unit is feasible. The advantage of this annual landslide probability model lies in its ability to estimate the annual landslide risk, instead of a scenario-based risk.

Global patterns of loss of life from landslides

Global loss of life from landslides is poorly quantifi ed. A global data set of fatalities from nonseismically triggered landslides that resulted in loss of life between A.D. 2004 and 2010 permits for the fi rst time proper quantifi cation of impacts and spatial distributions. In total, 2620 fatal landslides were recorded worldwide during the 7 yr period of the study, causing a total of 32,322 recorded fatalities. These total numbers of landslides and victims are an order of magnitude greater than other data sets have indicated, but analysis of the data suggests that it may still slightly underestimate the true human costs. The majority of human losses occur in Asia, especially along the Himalayan Arc and in China. This geographical concentration dominates the annual landslide cycle, which peaks in the Northern Hemisphere summer months. Finally, numbers of fatalities per event show a fat-tailed power law distribution, with the density of landslides being moderately correlated with the population density on a national basis.