An updated method for estimating landslide‐event magnitude

Summary statistics derived from the frequency–area distribution (FAD) of inventories of triggered landslides allows for direct comparison of landslides triggered by one event (e.g. earthquake, rainstorm) with another. Such comparisons are vital to understand links between the landslide‐event and the environmental characteristics of the area affected. This could lead to methods for rapid estimation of landslide‐event magnitude, which in turn could lead to estimates of the total triggered landslide area. Previous studies proposed that the FAD of landslides follows an inverse power‐law, which provides the basis to model the size distribution of landslides and to estimate landslide‐event magnitude (mLS), which quantifies the severity of the event. In this study, we use a much larger collection of earthquake‐induced landslide (EQIL) inventories (n=45) than previous studies to show that size distributions are much more variable than previously assumed. We present an updated model and propose a method for estimating mLS and its uncertainty that better fits the observations and is more reproducible, robust, and consistent than existing methods. We validate our model by computing mLS for all of the inventories in our dataset and comparing that with the total landslide areas of the inventories. We show that our method is able to estimate the total landslide area of the events in this larger inventory dataset more successfully than the existing methods. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.     

Analysis of historical landslide time series in the Emilia‐Romagna region,northern Italy

A catalogue of historical landslides, 1951–2002, for three provinces in the Emilia‐Romagna region of northern Italy is presented and its statistical properties studied. The catalogue consists of 2255 reported landslides and is based on historical archives and chronicles. We use two measures for the intensity of landsliding over time: (i) the number of reported landslides in a day (D_L) and (ii) the number of reported landslides in an event (S_event), where an event is one or more consecutive days with landsliding. From 1951–2002 in our study area there were 1057 days with 1 ≤ D_L ≤?45 landslides per day, and 596 events with 1 ≤ S_event ≤ 129 landslides per event. In the first set of analyses, we find that the probability density of landslide intensities in the time series are power‐law distributed over at least two‐orders of magnitude, with exponent of about ?2·0. Although our data is a proxy for landsliding built from newspaper reports, it is the first tentative evidence that the frequency‐size of triggered landslide events over time (not just the landslides in a given triggered event), like earthquakes, scale as a power‐law or other heavy‐tailed distributions. If confirmed, this could have important implications for risk assessment and erosion modelling in a given area. In our second set of analyses, we find that for short antecedent rainfall periods, the minimum amount of rainfall necessary to trigger landslides varies considerably with the intensity of the landsliding (D_L and S_event); whereas for long antecedent periods the magnitude is largely independent of the cumulative amount of rainfall, and the largest values of landslide intensity are always preceded by abundant rainfall. Further, the analysis of the rainfall trend suggests that the trigger of landslides in the study area is related to seasonal rainfall. Copyright © 2010 John Wiley & Sons, Ltd.     

Use of LIDAR‐derived images for mapping old landslides under forest

Large, deep‐seated landslides are common features in the Flemish Ardennes (Belgium). As most of these old (>100 years) landslides are located under forest in this hilly region, aerial photograph interpretation is not an appropriate landslide mapping method. This study tested the potential of LIDAR (Light Detection and Ranging) images for mapping old landslides under forest. Landslide inventory maps were created for a 125 km² area by applying the expert knowledge of seven geomorphologists to LIDAR‐derived hillshade, slope and contour line maps in a GIS environment. Each of the seven LIDAR‐based landslide inventories was compared (i) with the other six, (ii) with a detailed field survey‐based inventory, and (iii) with a comparable study in which topographic data were extracted from a topographical map. The combination of the percentage of field landslides indicated by an expert and the percentage of positional discrepancies (expressed in terms of positional mismatch) were used to evaluate the quality of the LIDAR‐based inventory maps. High‐quality LIDAR‐derived landslide inventory maps contain more than 70 per cent of the landslides mapped during the field survey, and have positional discrepancies smaller than 70 per cent when compared with the field survey‐based inventory map. Four experts and the combination map of all experts satisfied these criteria. Together the seven experts indicated all landslides mapped in the field. Importantly, LIDAR enabled the experts to find ten new landslides and to correct the boundaries of eleven (of the 77) landslides mapped during the field survey. Hence, this study showed that large‐scale LIDAR‐derived maps analysed by experienced geomorphologists can significantly improve field survey‐based inventories of landslides with a subdued morphology in hilly regions. Copyright © 2006 John Wiley & Sons, Ltd.     

Empirical prediction of coseismic landslide dam formation

In this study we develop an empirical method to estimate the volume threshold for predicting coseismic landslide dam formation using landscape parameters obtained from digital elevation models (DEMs). We hypothesize that the potential runout and volume of landslides, together with river features, determine the likelihood of the formation of a landslide dam. To develop this method, a database was created by randomly selecting 140 damming and 200 non‐damming landslides from 501 landslide dams and > 60 000 landslides induced by the M_w 7.9 2008 Wenchuan earthquake in China. We used this database to parameterize empirical runout models by stepwise multivariate regression. We find that factors controlling landslide runout are landslide initiation volume, landslide type, internal relief (H) and the H/L ratio (between H and landslide horizontal distance to river, L). In order to obtain a first volume threshold for a landslide to reach a river, the runout regression equations were converted into inverse volume equations by taking the runout to be the distance to river. A second volume threshold above which a landslide is predicted to block a river was determined by the correlation between river width and landslide volume of the known damming landslides. The larger of these two thresholds was taken as the final damming threshold. This method was applied to several landslide types over a fine geographic grid of assumed initiation points in a selected catchment. The overall prediction accuracy was 97.4% and 86.0% for non‐damming and damming landslides, respectively. The model was further tested by predicting the damming landslides over the whole region, with promising results. We conclude that our method is robust and reliable for the Wenchuan event. In combination with pre‐event landslide susceptibility and frequency–size assessments, it can be used to predict likely damming locations of future coseismic landslides, thereby helping to plan emergency response. Copyright © 2014 John Wiley & Sons, Ltd.     

Factors controlling landslide frequency–area distributions

A power-law relation for the frequency–area distribution (FAD) of medium and large landslides (e.g. tens to millions of square meters) has been observed by numerous authors. But the FAD of small landslides diverges from the power-law distribution, with a rollover point below which frequencies decrease for smaller landslides. Some studies conclude that this divergence is an artifact of unmapped small landslides due to lack of spatial or temporal resolution; others posit that it is caused by the change in the underlying failure process. An explanation for this dilemma is essential both to evaluate the factors controlling FADs of landslides and power-law scaling, which is a crucial factor regarding both landscape evolution and landslide hazard assessment. This study examines the FADs of 45 earthquake-induced landslide inventories from around the world in the context of the proposed explanations. We show that each inventory probably involves some combination of the proposed explanations, though not all explanations contribute to each case. We propose an alternative explanation to understand the reason for the divergence from a power-law. We suggest that the geometry of a landslide at the time of mapping reflects not just one single movement but many, including the propagation of numerous smaller landslides before and after the main failure. Because only the resulting combination of these landslides can be observed due to a lack of temporal resolution, many smaller landslides are not taken into account in the inventory. This reveals that the divergence from the power-law is not necessarily attributed to the incompleteness of an inventory. This conceptual model will need to be validated by ongoing observation and analysis. Also, we show that because of the subjectivity of mapping procedures, the total number of landslides and total landslide areas in inventories differ significantly, and therefore the shapes of FADs also differ considerably. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.     

Landslide susceptibility analysis based on citizen reports

Landslide susceptibility estimates are essential for reducing the risk posed by landslides to social and economic well-being. However, estimates of landslide susceptibility depend on reliable landslide inventories whose production requires extensive field or remote sensing efforts. Further, most inventories are not updated through time and thus may not capture the influence of changes in climate and/or land use. Inventories based on citizen reports of landslide occurrence, have the potential to overcome these limitations. Such an inventory can be produced from citizen reports to a 311-phone and online system, a nationwide database that updates real-time and records reported landslides location and timing. Whereas this landslide inventory is promising, it has not used for landslide susceptibility analyses and may be associated with spatial uncertainties and reporting biases. In this study we explore the use of 311-based landslide inventory for landslide susceptibility estimates in Pittsburgh, PA, USA, where landslide risk is among the highest in the nation. We compare the 311-based inventory to field-validated inventories through a multi-pronged approach that combines field validation of 311-reported landslides, probabilistic analysis of the association between landslides and the underlying topographic and geologic factors, and spatial filtering. Our results show that: (a) approximately 70% of the 311-reported landslides are associated with an identifiable landslide in the field; (b) the spatial uncertainty of the 311-reported landslides is 104 ± 25 m; (c) 311-reported landslides differ from other inventories in that they are primarily associated with proximity to roads, however, field-correction of 311-reported landslide locations rectifies this anomaly; (d) a simple spatial filter, scaled by the uncertainty in location as determined from a subset of the 311-data, can increase the consistency between the 311-reported inventory and field-validated inventories. These results suggest that 311-based landslide inventories can improve susceptibility estimates at a relatively low cost and high temporal resolution.     

Landslide incidence zonation in the Rio Mendoza valley,Mendoza Province,Argentina

This paper presents a landslide incidence zonation map showing the percentage of underlying material involved in mass‐movement processes in the Rio Mendoza valley, Argentina. The landslide incidence zonation map was derived from an inventory map of landslides and reveals that many areas of the Rio Mendoza valley are implicated in this kind of process. A correlation has been found between the occurrence of landslides, earthquakes, and rainfall. The relation between lithology and landslides is clear: areas covered by friable sedimentary and volcanic rocks of the Choiyoi Group are prone to debris ?ows and complex landslides. The slope map has been ranked and a general relation between slope and type of event is shown. Falls commonly develop in high‐angle slopes. Copyright © 2004 John Wiley & Sons, Ltd.     

The Spatial Distribution and Attribute Parameter Statistics of Landslides Triggered by the May 12th, 2008, MW7.9 Wenchuan Earthquake

A complete landslide inventory and attribute database is the importantly fundamental for the study of the earthquake-induced landslide. Substantial landslides were triggered by the M_W7.9 Wenchuan earthquake on May 12^th, 2008. Google Earth images of pre- and post-earthquakes show that 52 194 co-seismic landslides were recognized and mapped, with a total landslides area of 1 021 km².Based on the statistics,we assigned all landslide parameters and established the co-seismic landslides database, which includes area, length, and width of landslides, elevation of the scarp top and foot edge, and the top and bottom elevations of each located slope. Finally, the spatial distribution and the above attribute parameters of landslides were analyzed. The results show that the spatial distribution of the co-seismic landslides is extremely uneven. The landslides that mainly occur in a rectangular area (a width of 30 km of the hanging wall of the Yingxiu-Beichuan fault and a length of 120 km between Yingxiu and Beichuan) are obviously controlled by surface rupture, terrain, and peak ground acceleration. Meanwhile, a large number of small landslides (individual landslide area less than 10 000 m²)contribute less to the total landslides area. The number of landslides larger than 10 000 m² accounts for 38.7% of the total number of co-seismic landslides, while the area of those landslides account for 88% of the total landslides area. The 52 194 co-seismic landslides are caused by bedrock collapse that usually consists of three parts:source area, transport area, and accumulation area. However, based on the area-volume power-law relationship, the resulting regional landslide volume may be much larger than the true landslide volume if the landslide volume is calculated using the influenced area from each landslide.     

An open-accessed inventory of landslides triggered by the MS 6.8 Luding earthquake,China on September 5, 2022

This study constructs a preliminary inventory of landslides triggered by the M_S 6.8 Luding earthquake based on field investigation and human-computer interaction visual interpretation on optical satellite images. The results show that this earthquake triggered at least 5 007 landslides, with a total landslide area of 17.36 ?km², of which the smallest landslide area is 65 ?m² and the largest landslide area reaches 120 747 ?m², with an average landslide area of about 3 500 ?m². The obtained landslides are concentrated in the IX intensity zone and the northeast side of the seismogenic fault, and the area density and point density of landslides are 13.8%, and 35.73 ?km^?2 peaks with 2 ?km as the search radius. It should be noted that the number of landslides obtained in this paper will be lower than the actual situation because some areas are covered by clouds and there are no available post-earthquake remote sensing images. Based on the available post-earthquake remote sensing images, the number of landslides triggered by this earthquake is roughly estimated to be up to 10 000. This study can be used to support further research on the distribution pattern and risk evaluation of the coseismic landslides in the region, and the prevention and control of landslide hazards in the seismic area.     

Application of a multi‐temporal,LiDAR‐derived,digital terrain model in a landslide‐volume estimation

Sediments produced by landslides are crucial in the sediment yield of a catchment, debris flow forecasting, and related hazard assessment. On a regional scale, however, it is difficult and time consuming to measure the volumes of such sediment. This paper uses a LiDAR‐derived digital terrain model (DTM) taken in 2005 and 2010 (at 2 m resolution) to accurately obtain landslide‐induced sediment volumes that resulted from a single catastrophic typhoon event in a heavily forested mountainous area of Taiwan. The landslides induced by Typhoon Morakot are mapped by comparison of 25 cm resolution aerial photographs taken before and after the typhoon in an 83.6 km² study area. Each landslide volume is calculated by subtraction of the 2005 DTM from the 2010 DTM, and the scaling relationship between landslide area and its volume are further regressed. The relationship between volume and area are also determined for all the disturbed areas (V_L = 0.452A_L^1.242) and for the crown areas of the landslides (V_L = 2.510A_L^1.206). The uncertainty in estimated volume caused by use of the LiDAR DTMs is discussed, and the error in absolute volume estimation for landslides with an area >10⁵ m² is within 20%. The volume–area relationship obtained in this study is also validated in 11 small to medium‐sized catchments located outside the study area, and there is good agreement between the calculation from DTMs and the regression formula. By comparison of debris volumes estimated in this study with previous work, it is found that a wider volume variation exists that is directly proportional to the landslide area, especially under a higher scaling exponent. Copyright © 2013 John Wiley & Sons, Ltd.     

Terrain attributes of earthquake‐ and rainstorm‐induced landslides in orogenic mountain Belt,Taiwan

Landsliding induced by earthquakes and rainstorms in montane regions is not only a sculptor for shaping the landscape, but also a driver for delivering sediments and above‐ground biomass downstream. However, the terrain attributes of earthquake‐ and rainstorm‐induced landslides are less discussed comprehensively in Taiwan. As part of an island‐wide inventory, we here compare and contrast the landslide terrain attributes resulting from two catastrophic events: the Chi‐Chi earthquake (M _w = 7.6, September 1999) and typhoon Morakot (rainfall >2500 mm, August 2009). Results show that the earthquake‐induced landslides are relatively small, round‐shaped and prone to occur primarily in middle and toe of slopes. In contrast, the rainstorm‐induced landslides are larger, horseshoe‐shaped and preferentially occurring in slope toes. Also, earthquake‐induced landslides, particularly large landslides, are usually found at steeper gradients, whereas rainstorm‐induced landslides aggregate at gradients between 25° and 40°. Lithologic control plays a secondary role in landsliding. From an island‐wide perspective, high landslide density locates in the region of earthquake intensity ≥ VI or one‐day rainfall ≥600 mm day^?1. Through the landslide patterns and their terrain attributes, our retrospective approach sheds light on accessing the historical and remote events for close geophysical investigations. Finally, we should bear in mind that the landslide location, size, and terrain attributes varying with triggers may affect the landscape evaluation or biogeochemical processes in landslide‐dominated regions. Copyright © 2017 John Wiley & Sons, Ltd.     

Controls of preferential orientation of earthquake- and rainfall-triggered landslides in Taiwan's orogenic mountain belt

Landsliding usually occurs on specific hillslope aspect, which may reflect the control of specific geo-environmental factors, triggering factors, or their interaction. To explore this notion, this study used island-wide landslide inventories of the Chi-Chi earthquake in 1999 (M_W = 7.6) and Typhoon Morakot in 2009 in Taiwan to investigate the preferential orientation of landslides and the controls of landslide triggers and geological settings. The results showed two patterns. The orientations of earthquake-triggered landslides were toward the aspect facing away from the epicenter in areas with peak ground acceleration (PGA) ≥ 0.6 g and landslide ratio ≥ 1%, suggesting that the orientations were controlled by seismic wave propagation. Rainfall-triggered landslides tended to occur on dip slopes, instead of the windward slopes, suggesting that geological settings were a more effective control of the mass wasting processes on hillslope scale than the rainfall condition. This study highlights the importance of the endogenic processes, namely seismic wave and geological settings, on the predesigned orientation of landslides triggered by either earthquake or rainfall, which can in turn improve our knowledge of landscape evolution and landslide prediction. © 2019 John Wiley & Sons, Ltd.     

Geomorphic imprint of landslides on alpine river systems,southwest New Zealand

An inventory of 846 mass movements, mainly landslides, in two alpine regions of southwest New Zealand was created to explore the geomorphic impacts of slope‐failure processes on river channels and valley floors. In total, 213 (i.e. 27 per cent) of the slope failures descended to valley floors, affecting the geomorphology of trunk channels (catchment area A_C > 10 km²) and valley floors in recurring patterns. A nominal classification system is introduced for characterizing (a) the physical contact nature between landslides and river channels, and (b) the resulting geomorphic consequences for drainage. Although landslide area A is useful for estimating the length of channel directly impacted by debris, it does not necessarily predict the direction of fluvial response or type of impact. Dominant persistent geomorphic imprints of bedrock landslides include channel occlusions and landslide dams in South Westland and Fiordland, respectively. Differences in size distribution and geomorphic effects on river systems between the two study regions are attributed to bedrock geology, tectonics and sediment flux. Although South Westland rivers are more frequently affected by landslides, disrupting long‐term effects such as blockage are more persistent in Fiordland. Copyright © 2005 John Wiley & Sons, Ltd.     

Prediction of rainfall‐induced shallow landslides in the Loess Plateau,Yan'an,China, using the TRIGRS model

In this work, a transient rainfall infiltration and grid‐based regional slope‐stability model (TRIGRS) was implemented in a case study of Yan'an City, Northwest China. In this area, widespread shallow landslides were triggered by the 12 July 2013 exceptional rainstorm event. A high‐resolution DEM, soil parameters from in‐situ and laboratory measurements, water table depths, the maximum depth of precipitation infiltration and rain‐gauge‐corrected precipitation of the event, were used as inputs in the TRIGRS model. Shallow landslides triggered on the same day were used to evaluate the modeling results. The summarized results are as follows: (i) The characteristics and distribution of thirty‐five shallow landslides triggered by the 12 July 2013 rainfall event were identified in the study area and all were classified as shallow landslides with the maximum depth, area and volume less than 3 m, 200 m² and 1000 m³, respectively, (ii) Four intermediate factor of safety (F_S) maps were generated using the TRIGRS model to represent the scenarios 6, 12, 18 and 24 hours after the storm event. The area with F_S < 1 increased with the rainfall duration. The percentage of the area with F_S < 1 was 0.2%, 3.3%, 3.8% and 5.1% for the four stages, respectively. Twenty‐four hours after the rainstorm, TRIGRS predicted that 1255 grid cells failed, which is consistent with the field data. (iii) TRIGRS generated more satisfactory results at a given precipitation threshold than SINMAP, which is ideal for landslide hazard zoning for land‐use planning at the regional scale. Comparison results showed that TRIGRS is more useful for landslide prediction for a certain precipitation threshold, also in the regional scale. (iv) Analysis of the responses of loess slope prone to slope failure after different precipitation scenarios revealed that loess slopes are particularly sensitive to extended periods of heavy precipitation. Copyright © 2016 John Wiley & Sons, Ltd.     

Testing a model for predicting the timing and location of shallow landslide initiation in soil‐mantled landscapes

The growing availability of digital topographic data and the increased reliability of precipitation forecasts invite modelling efforts to predict the timing and location of shallow landslides in hilly and mountainous areas in order to reduce risk to an ever‐expanding human population. Here, we exploit a rare data set to develop and test such a model. In a 1·7 km² catchment a near‐annual aerial photographic coverage records just three single storm events over a 45 year period that produced multiple landslides. Such data enable us to test model performance by running the entire rainfall time series and determine whether just those three storms are correctly detected. To do this, we link a dynamic and spatially distributed shallow subsurface runoff model (similar to TOPMODEL) to an in?nite slope model to predict the spatial distribution of shallow landsliding. The spatial distribution of soil depth, a strong control on local landsliding, is predicted from a process‐based model. Because of its common availability, daily rainfall data were used to drive the model. Topographic data were derived from digitized 1 : 24 000 US Geological Survey contour maps. Analysis of the landslides shows that 97 occurred in 1955, 37 in 1982 and ?ve in 1998, although the heaviest rainfall was in 1982. Furthermore, intensity–duration analysis of available daily and hourly rainfall from the closest raingauges does not discriminate those three storms from others that did not generate failures. We explore the question of whether a mechanistic modelling approach is better able to identify landslide‐producing storms. Landslide and soil production parameters were ?xed from studies elsewhere. Four hydrologic parameters characterizing the saturated hydraulic conductivity of the soil and underlying bedrock and its decline with depth were ?rst calibrated on the 1955 landslide record. Success was characterized as the most number of actual landslides predicted with the least amount of total area predicted to be unstable. Because landslide area was consistently overpredicted, a threshold catchment area of predicted slope instability was used to de?ne whether a rainstorm was a signi?cant landslide producer. Many combinations of the four hydrological parameters performed equally well for the 1955 event, but only one combination successfully identi?ed the 1982 storm as the only landslide‐producing storm during the period 1980–86. Application of this parameter combination to the entire 45 year record successfully identi?ed the three events, but also predicted that two other landslide‐producing events should have occurred. This performance is signi?cantly better than the empirical intensity–duration threshold approach, but requires considerable calibration effort. Overprediction of instability, both for storms that produced landslides and for non‐producing storms, appears to arise from at least four causes: (1) coarse rainfall data time scale and inability to document short rainfall bursts and predict pressure wave response; (2) absence of local rainfall data; (3) legacy effect of previous landslides; and (4) inaccurate topographic and soil property data. Greater resolution of spatial and rainfall data, as well as topographic data, coupled with systematic documentation of landslides to create time series to test models, should lead to signi?cant improvements in shallow landslides forecasting. Copyright © 2003 John Wiley & Sons, Ltd.     

基于高分卫星遥感影像的地震应急滑坡编目与分布特征探讨——以2017年8月8日九寨沟7.0级地震为例

地震应急是减轻地震灾害的重要途径之一。地震应急工作具有时间紧迫、事关重大的特点。2017年8月8日四川九寨沟M_S7.0级地震发生后,为快速、准确地提供地震引发的滑坡灾害分布,本研究基于震后第一天获取到的高分辨率遥感影像（高分二号卫星影像、北京二号卫星影像）,通过人工目视解译的方法初步建立了四川九寨沟地震滑坡编目。结果表明,该地震至少触发了622处同震滑坡,分布在沿使用影像边界框定的面积为3919km2的区域内。本研究还利用这个地震滑坡编目,统计了九寨沟地震滑坡数量和滑坡点密度（LND）与地形（坡度、坡向）、地震（地震烈度、震中距）等因素的关系。结果表明九寨沟地震滑坡多发生在坡度为20°—50°的区域内,滑坡的易发性随着坡度的增加而增加。受地震波传播方向的影响,E、SE向是地震滑坡较易发生的坡向。滑坡的易发程度和地震烈度呈正相关,即随着烈度的增大,滑坡易发性增大。滑坡易发性还随着震中距增加而降低,这是由于地震波能量随震中距的增加而衰减导致的。     

Temporal correlations and clustering of landslides

This paper examines temporal correlations and temporal clustering of a proxy historical landslide time series, 2255 reported landslides 1951–2002, for an area in the Emilia‐Romagna Region, Italy. Landslide intensity is measured by the number of reported landslides in a day (D_L) and in an ‘event’ (S_event) of consecutive days with landsliding. The non‐zero values in both time series D_L and S_event are unequally spaced in time, and have heavy‐tailed frequency‐size distributions. To examine temporal correlations, we use power‐spectral analysis (Lomb periodogram) and surrogate data analysis, confronting our original D_L and S_event time series with 1000 shuffled (uncorrelated) versions. We conclude that the landslide intensity series D_L has strong temporal correlations and S_event has likely temporal correlations. To examine temporal clustering in D_L and S_event, we consider extremes over different landslide intensity thresholds. We first examine the statistical distribution of interextreme occurrence times, τ, and find Weibull distributions with parameter γ << 1·0 [D_L] and γ < 1·0 [S_event]; thus D_L and S_event each have temporal correlations, but S_event to a lesser degree. We next examine correlations between successive interextreme occurrence times, τ. Using autocorrelation analysis applied to τ, combined with surrogate data analysis, we find for D_L linear correlations in τ, but for S_event inconclusive results. However, using Kendall's rank correlation analysis we find for both D_L and S_event the series of τ are strongly correlated. Finally, we apply Fano Factor analysis, finding for both D_L and S_event the timings of extremes over a given threshold exhibit a fractal structure and are clustered in time. In this paper, we provide a framework for examining time series where the non‐zero values are strongly unequally spaced and heavy‐tailed, particularly important in the Earth Sciences due to their common occurrence, and find that landslide intensity time series exhibit temporal correlations and clustering. Many landslide models currently are designed under the assumption that landslides are uncorrelated in time, which we show is false. Copyright © 2010 John Wiley & Sons, Ltd.     

Quantifying rainfall controls on catchment‐scale landslide erosion in Taiwan

Landslide erosion is a dominant hillslope process and the main source of stream sediment in tropical, tectonically active mountain belts. In this study, we quantified landslide erosion triggered by 24 rainfall events from 2001 to 2009 in three mountainous watersheds in Taiwan and investigated relationships between landslide erosion and rainfall variables. The results show positive power‐law relations between landslide erosion and rainfall intensity and cumulative rainfall, with scaling exponents ranging from 2·94 to 5·03. Additionally, landslide erosion caused by Typhoon Morakot is of comparable magnitude to landslide erosion caused by the Chi‐Chi Earthquake (M_W = 7·6) or 22–24 years of basin‐averaged erosion. Comparison of the three watersheds indicates that deeper landslides that mobilize soil and bedrock are triggered by long‐duration rainfall, whereas shallow landslides are triggered by short‐duration rainfall. These results suggest that rainfall intensity and watershed characteristics are important controls on rainfall‐triggered landslide erosion and that severe typhoons, like high‐magnitude earthquakes, can generate high rates of landslide erosion in Taiwan. Copyright © 2012 John Wiley & Sons, Ltd.