Rainfall thresholds for the possible landslide occurrence in Sicily (Southern Italy) based on the automatic reconstruction of rainfall events

Review of the literature on the reconstruction of the rainfall responsible for slope failures reveals that criteria for the identification of rainfall events are lacking or somewhat subjective. To overcome this problem, we developed an algorithm for the objective and reproducible reconstruction of rainfall events and of rainfall conditions responsible for landslides. The algorithm consists of three distinct modules for (i) the reconstruction of distinct rainfall events, in terms of duration (D, in h) and cumulated event rainfall (E, in mm), (ii) the identification of multiple ED rainfall conditions responsible for the documented landslides, and (iii) the definition of critical rainfall thresholds for possible landslide occurrences. The algorithm uses pre-defined parameters to account for different seasonal and climatic settings. We applied the algorithm in Sicily, southern Italy, using rainfall measurements obtained from a network of 169 rain gauges, and information on 229 rainfall-induced landslides occurred between July 2002 and December 2012. The algorithm identified 29,270 rainfall events and reconstructed 472 ED rainfall conditions as possible triggers of the observed landslides. The algorithm exploited the multiple rainfall conditions to define objective and reproducible empirical rainfall thresholds for the possible initiation of landslide in Sicily. The calculated thresholds may be implemented in an operational early warning system for shallow landslide forecasting.     

Rainfall thresholds for prediction of shallow landslides around Chamoli-Joshimath region,Garhwal Himalayas,India

Majority of landslides in the Indian sub-continent are triggered by rainfall. Several attempts in the global scenario have been made to establish rainfall thresholds in terms of intensity-duration and antecedent rainfall models on global, regional and local scales for the occurrence of landslides. However, in the context of the Indian Himalayas, the rainfall thresholds for landslide occurrences are not yet understood fully. Neither on regional scale nor on local scale, establishing such rainfall thresholds for landslide occurrences in Indian Himalayas has yet been attempted. This paper presents an attempt towards deriving local rainfall thresholds for landslides based on daily rainfall data in and around Chamoli-Joshimath region of the Garhwal Himalayas, India. Around 128 landslides taken place in last 4 years from 2009 to 2012 have been studied to derive rainfall thresholds. Out of 128 landslides, however, rainfall events pertaining to 81 landslides were analysed to yield an empirical intensity–duration threshold for landslide occurrences. The rainfall threshold relationship fitted to the lower boundary of the landslide triggering rainfall events is I?=?1.82 D ^?0.23 (I?=?rainfall intensity in millimeters per hour and D?=?duration in hours). It is revealed that for rainfall events of shorter duration (≤24 h) with a rainfall intensity of 0.87 mm/h, the risk of landslide occurrence in this part of the terrain is expected to be high. Also, the role of antecedent rainfall in causing landslides was analysed by considering daily rainfall at failure and different period cumulative rainfall prior to failure considering all 128 landslides. It is observed that a minimum 10-day antecedent rainfall of 55 mm and a 20-day antecedent rainfall of 185 mm are required for the initiation of landslides in this area. These rainfall thresholds presented in this paper may be improved with the hourly rainfall data vis-à-vis landslide occurrences and also data of later years. However, these thresholds may be used in landslide warning systems for this particular region of the Garhwal Himalayas to guide the traffic and provide safety to the tourists travelling along this pilgrim route during monsoon seasons.     

Exploiting historical rainfall and landslide data in a spatial database for the derivation of critical rainfall thresholds

Critical rainfall thresholds for landslides are powerful tools for preventing landslide hazard. The thresholds are commonly estimated empirically starting from rainfall events that triggered landslides in the past. The creation of the appropriate rainfall–landslide database is one of the main efforts in this approach. In fact, an accurate agreement between the landslide and rainfall information, in terms of location and timing, is essential in order to correctly estimate the rainfall–landslide relationships. A further issue is taking into account the average moisture conditions prior the triggering event, which reasonably may be crucial in determining the sufficient amount of precipitation. In this context, the aim of this paper is exploiting historical landslide and rainfall data in a spatial database for the derivation of critical rainfall thresholds for landslide occurrence in Sicily, southern Italy. The hourly rainfall events that caused landslides occurred in the twentieth century were specifically identified and reconstructed. A procedure was proposed to automatically convert rain guages charts recorded on paper tape into digital format and then to provide the cumulative rainfall hyetograph in digital format. This procedure is based on a segmentation followed by signal recognition techniques which allow to digitalize and to recognize the hyetograph automatically. The role of rainfall prior to the landslide events was taken into account by including in the analysis the rainfall occurred 5, 15 and 30 days before each landslide. Finally, cumulated rainfall duration thresholds for different exceedance probability levels were determined. The obtained thresholds resulted in agreement with the regional curves proposed by other authors for the same area; antecedent rainfall turned out to be particularly important in triggering landslides.     

The rainfall intensity–duration control of shallow landslides and debris flows: an update

A global database of 2,626 rainfall events that have resulted in shallow landslides and debris flows was compiled through a thorough literature search. The rainfall and landslide information was used to update the dependency of the minimum level of rainfall duration and intensity likely to result in shallow landslides and debris flows established by Nel Caine in 1980. The rainfall intensity–duration (ID) values were plotted in logarithmic coordinates, and it was established that with increased rainfall duration, the minimum average intensity likely to trigger shallow slope failures decreases linearly, in the range of durations from 10 min to 35 days. The minimum ID for the possible initiation of shallow landslides and debris flows was determined. The threshold curve was obtained from the rainfall data using an objective statistical technique. To cope with differences in the intensity and duration of rainfall likely to result in shallow slope failures in different climatic regions, the rainfall information was normalized to the mean annual precipitation and the rainy-day normal. Climate information was obtained from the global climate dataset compiled by the Climate Research Unit of the East Anglia University. The obtained global ID thresholds are significantly lower than the threshold proposed by Caine (Geogr Ann A 62:23–27, 1980), and lower than other global thresholds proposed in the literature. The new global ID thresholds can be used in a worldwide operational landslide warning system based on global precipitation measurements where local and regional thresholds are not available..     

Rainfall patterns for shallow landsliding in perialpine Slovenia

This paper presents two types of analysis: an antecedent rainfall analysis based on daily rainfall and an intensity-duration analysis of rainfall events based on hourly data in perialpine Slovenia in the ?kofjelo?ko Cerkljansko hills. For this purpose, eight rainfall events that are known to have caused landslides in the period from 1990 to 2010 were studied. Over the observed period, approximately 400 records of landslides were collected. Rainfall data were obtained from three rain gauges. The daily rainfall from the 30 days before landslide events was investigated based on the type of landslides and their geo-environmental setting, the dates of confirmed landslide activity and different consecutive rainfall periods. The analysis revealed that the rainfall events triggering slope failure can be divided into two groups according to the different antecedent periods. The first group of landslides typically occurred after short-duration rainstorms with high intensity, when the daily rainfall exceeded the antecedent rainfall. The second group comprises the rainfall events with a longer antecedent period of at least 7 days. A comparison of the plotted peak and mean intensities indicates that the rainfall patterns that govern slope failure are similar but do not necessarily reflect the rainfall intensity at the time of shallow landslides in the Dav?a or Poljane areas, where the majority of the landslides occurred. Because of several limitations, the suggested threshold cannot be compared and evaluated with other thresholds.     

Early warning system for shallow landslides using rainfall threshold and slope stability analysis

A combined cluster and regression analysis were performed for the first time to identify rainfall threshold that triggers landslide events in Amboori, Kerala, India. Amboori is a tropical area that is highly vulnerable to landslides. The 2, 3, and 5-day antecedent rainfall data versus daily rainfall was clustered to identify a cluster of critical events that could potentially trigger landslides. Further, the cluster of critical events was utilized for regression analysis to develop the threshold equations. The 5-day antecedent (x-variable) vs. daily rainfall (y-variable) provided the best fit to the data with a threshold equation of y = 80.7–0.1981x. The intercept of the equation indicates that if the 5-day antecedent rainfall is zero, the minimum daily rainfall needed to trigger the landslide in the Amboori region would be 80.7 mm. The negative coefficient of the antecedent rainfall indicates that when the cumulative antecedent rainfall increases, the amount of daily rainfall required to trigger monsoon landslide decreases. The coefficient value indicates that the contribution of the 5-day antecedent rainfall is ∼20% to the landslide trigger threshold. The slope stability analysis carried out for the area, using Probabilistic Infinite Slope Analysis Model (PISA-m), was utilized to identify the areas vulnerable to landslide in the region. The locations in the area where past landslides have occurred demonstrate lower Factors of Safety (FS) in the slope stability analysis. Thus, rainfall threshold analysis together with the FS values from slope stability can be suitable for developing a simple, cost-effective, and comprehensive early-warning system for shallow landslides in Amboori and similar regions.     

The determination of statistical and deterministic hydrological landslide-triggering thresholds

 Hydrological landslide-triggering thresholds separate combinations of daily and antecedent rainfall or of rainfall intensity and duration that triggered landslides from those that failed to trigger landslides. They are required for the development of landslide early warning systems. When a large data set on rainfall and landslide occurrence is available, hydrological triggering thresholds are determined in a statistical way. When the data on landslide occurrence is limited, deterministic models have to be used. For shallow landslides directly triggered by percolating rainfall, triggering thresholds can be established by means of one-dimensional hydrological models linked to the infinite slope model. In the case of relatively deep landslides located in topographic hollows and triggered by a slow accumulation of water at the soil-bedrock contact, simple correlations between landslide occurrence and rainfall can no longer be established. Therefore real-time failure probabilities have to be determined using hydrological catchment models in combination with the infinite slope model. Received: 15 October 1997 · Accepted: 25 June 1997     

Assessment of rainfall thresholds and soil moisture modeling for operational hydrogeological risk prevention in the Umbria region (central Italy)

Rainfall thresholds represent the main tool for the Italian Civil Protection System for early warning of the threat of landslides. However, it is well-known that soil moisture conditions at the onset of a storm event also play a critical role in triggering slope failures, especially in the case of shallow landslides. This study attempts to define soil moisture (estimated by using a soil water balance model) and rainfall thresholds that can be employed for hydrogeological risk prevention by the Civil Protection Decentrate Functional Centre (CFD) located in the Umbria Region (central Italy). Two different analyses were carried out by determining rainfall and soil moisture conditions prior to widespread landslide events that occurred in the Umbria Region and that are reported in the AVI (Italian Vulnerable Areas) inventory for the period 1991?C2001. Specifically, a ??local?? analysis that considered the major landslide events of the AVI inventory and an ??areal?? analysis subdividing the Umbria Region in ten sub-areas were carried out. Comparison with rainfall thresholds used by the Umbria Region CFD was also carried out to evaluate the reliability of the current procedures employed for landslide warning. The main result of the analysis is the quantification of the decreasing linear trend between the maximum cumulated rainfall values over 24, 36 and 48?h and the soil moisture conditions prior to landslide events. This trend provides a guideline to dynamically adjust the operational rainfall thresholds used for warning. Moreover, the areal analysis, which was aimed to test the operational use of the combined soil moisture?Crainfall thresholds showed, particularly for low values of rainfall, the key role of soil moisture conditions for the triggering of landslides. On the basis of these results, the Umbria Region CFD is implementing a procedure aimed to the near real-time estimation of soil moisture conditions based on the soil water balance model developed ad hoc for the region. In fact, it was evident that a better assessment of the initial soil moisture conditions would support and improve the hydrogeological risk assessment.     

Assessment of rainfall-induced shallow landslides in Phetchabun and Krabi provinces,Thailand

Shallow landslides are a common type of rainfall-induced landslide, and various methods are currently used to predict their occurrence on a regional scale. Physically based models, such as the shallow landslide instability prediction (SLIP) model, have many advantages because these models can assess the hazards of shallow landslides dynamically, based on physical stability equations that consider rainfall as a triggering factor. The main objective of this research is to test the SLIP model’s potential to predict shallow landslide hazards in Thailand. To achieve this goal, the SLIP model was applied to two massive landslide events in Thailand. The results predicted by the SLIP model for the two study areas are outlined, and the model prediction capabilities were evaluated using the receiver operating characteristic plot. The Phetchabun results showed that the western part of the catchment had the lowest factor of safety (F _S) value, whereas the Krabi results showed that the slopes surrounding the peak of Khao Panom Mountain had the lowest F _S value, explaining the highest potentials for shallow landslides in each area. The SLIP model showed good performance: The global accuracies were 0.828 for the Phetchabun area and 0.824 for the Krabi area. The SLIP model predicted the daily time-varying percentage of unstable areas over the analyzed periods. The SLIP model simulated a negligible percentage of unstable areas over all considered periods, except for expected dates, suggesting that the prediction capability is reasonably accurate.     

浙江地区引发滑坡的降雨强度-历时关系

由于独特的地理位置,复杂的地质、地形和气候背景,浙江成为中国降雨型滑坡（土体和岩体滑动,也包括泥石流和崩塌等）最频发的地区之一。为评价浙江地区的滑坡灾害,本文对该地区1990年至2003年雨量站记录的降雨数据进行了详细分析,确定了引发土体滑坡-泥石流的降雨强度―历时下限。     

Spatially distributed rainfall thresholds for the initiation of shallow landslides

The evaluation of the combined influence of rainfall patterns (in terms of mean intensity and duration) and the geomorphological and mechanical characteristics of hillslopes on their stability conditions is a major goal in the assessment of the shallow landslide triggering processes. Geographic Information Systems (GIS) represent an important tool to develop models that combine hydrological and geomechanical analyses for the evaluation of slope stability, as they allow to combine information concerning rainfall characteristics with topographic and mechanical properties of the slopes over wide areas. In this paper, a GIS-based code is developed to determine physically based intensity/duration rainfall thresholds at the local scale. Given the rainfall duration and the local geometric, hydrological and mechanical characteristics of the slopes, the code evaluates the spatial distribution of the minimum rainfall intensity that triggers shallow landslides and debris flows over a given area. The key feature of the code is the capability of evaluating the time t _p required to reach the peak pore pressure head on the failure surface and computing the corresponding critical intensity/duration thresholds based on post-event peak pore pressures. The reliability of the model is tested using a set of one-dimensional analyses, comparing the physically based thresholds obtained for three different slopes with some empirical rainfall thresholds. In a log–log scale, the thresholds provided by the model decrease linearly with increased rainfall duration and they are bracketed by the empirical thresholds considered. Finally, an example of application to a study area of the Umbria region in central Italy is presented, describing the capability of the model of providing site-specific thresholds for different rainfall scenarios.     

Comparing the performance of TRIGRS and TiVaSS in spatial and temporal prediction of rainfall-induced shallow landslides

This study compares the performance of transient rainfall infiltration and grid-based regional slope stability (TRIGRS) model and time-variant slope stability (TiVaSS) model in the prediction of rainfall-induced shallow landslides. TRIGRS employs one-dimensional (1-D) subsurface flow to simulate the infiltration rate, whereas a three-dimensional (3-D) model is utilized in TiVaSS. The former has been widely used in landslide modeling, while the latter was developed only recently. Both programs are used for the spatiotemporal prediction of shallow landslides caused by rainfall. This study uses the July 2011 landslide event that occurred in Mt. Umyeon, Seoul, Korea, for validation. The performance of the two programs is evaluated by comparison with data of the actual landslides in both location and timing by using a landslide ratio for each factor of safety class (\({\text{LR}}_{\text{class}}\) index), which was developed for addressing point-like landslide locations. Moreover, the influence of surface flow on landslide initiation is assessed. The results show that the shallow landslides predicted by the two models are highly consistent with those of the observed sliding sites, although the performance of TiVaSS is slightly better. Overland flow affects the buildup of the pressure head and reduces the slope stability, although this influence was not significant in this case. A slight increase in the predicted unstable area from 19.30 to 19.93% was recorded when the overland flow was considered. It is concluded that both models are suitable for application in the study area. However, although it is a well-established model requiring less input data and shorter run times, TRIGRS produces less accurate results.     

Three decades of landslide activity in western Nepal: new insights into trends and climate drivers

In recent decades, landslide disasters in the Himalayas, as in other mountain regions, are widely reported to have increased. While some studies have suggested a link to increasing heavy rainfall under a warmer climate, others pointed to anthropogenic influences on slope stability, and increasing exposure of people and assets located in harm’s way. A lack of sufficiently high-resolution regional landslide inventories, both spatially and temporally, has prevented any robust consensus so far. Focusing on Far-Western Nepal, we draw on remote sensing techniques to create a regional inventory of 26,350 single landslide events, of which 8778 date to the period 1992–2018. These events serve as a basis for the analyses of landslide frequency relationships and trends in relation to precipitation and temperature datasets. Results show a strong correlation between the annual number of shallow landslides and the accumulated monsoon precipitation (r = 0.74). Furthermore, warm and dry monsoons followed by especially rainy monsoons produce the highest incidence of shallow landslides (r = 0.77). However, we find strong spatial variability in the strength of these relationships, which is linked to recent demographic development in the region. This highlights the role of anthropogenic drivers, and in particular road cutting and land-use change, in amplifying the seasonal monsoon influence on slope stability. In parallel, the absence of any long-term trends in landslide activity, despite widely reported increase in landslide disasters, points strongly to increasing exposure of people and infrastructure as the main driver of landslide disasters in this region of Nepal. By contrast, no climate change signal is evident from the data.

     

Rainfall thresholds for debris flow initiation in the Wenchuan earthquake-stricken area,southwestern China

The Wenchuan earthquake-stricken area is frequently hit by heavy rainfall, which often triggers sediment-related disasters, such as shallow landslides, debris flows, and related natural events, sometimes causing tremendous damage to lives, property, infrastructure, and environment. The assessment of the rainfall thresholds for debris flow occurrence is very important in order to improve forecasting and for risk management. In the context of the Wenchuan earthquake-stricken area, however, the rainfall thresholds for triggering debris flows are not well understood. With the aim of defining the critical rainfall thresholds for this area, a detailed analysis of the main rainstorm events was carried out. This paper presents 11 rainfall events that induced debris flows which occurred between 2008 and 2012 after the Wenchuan earthquake. The rainfall thresholds were defined in terms of mean rainfall intensity I, rainfall duration D, and normalized using the mean annual precipitation (MAP). An ID threshold and a normalized I _MAP D threshold graph could be set up for the Wenchuan earthquake-stricken area which forms the lower boundary of the domain with debris flow-triggering rainfall events. The rainfall threshold curves obtained for the study area were compared with the local, regional, and global curves proposed by various authors. The results suggest that debris flow initiation in the study area almost requires a higher amount of rainfall and greater intensity than elsewhere. The comparison of rainfall intensity prior to and after the earthquake clearly indicates that the critical rainfall intensity necessary to trigger debris flows decreased after the earthquake. Rainfall thresholds presented in this paper are generalized, so that they can be used in debris flow warning systems in areas with the same geology as the Wenchuan earthquake-stricken area.     

Landslides in the North of Lisbon Region (Portugal): Conditioning and triggering factors

Detailed geomorphological mapping carried out in 5 sample areas in the North of Lisbon Region allowed us to collect a set of geological and geomorphological data and to correlate them with the spatial occurrence of landslide. A total of 597 slope movements were identified in a total area of 61.7 km², which represents about 10 landslides per km².The main landslide conditioning factors are: lithology and geological structure, slope angle and slope morphology, land use, presence of old landslides, and human activity.The highest landslide density occurs in Cretaceous marls and marly limestones, but the largest movements are in Jurassic clays, marls and limestones.The landslide density is higher on slopes with gradients above 20 °, but the largest unstable area is found on slopes of 10 ° to 15 °, thus reflecting the presence of the biggest slope movements. There is a correlation between landslides and topographical concavities, a fact that can be interpreted as reflecting the significance of the hydrological regime in slope instability.Concerning land use, the highest density of landslides is found on slopes covered with shrub and undergrowth vegetation.About 26% of the total number of landslides are reactivation events. The presence of old landslides is particularly important in the occurrence of translational slides and complex and composite slope movements.20% of the landslide events were conditioned by anthropomorphic activity. Human's intervention manifests itself in ill-consolidated fills, cuts in potentially unstable slopes and, in a few cases, in the changing of river channels.Most slope movements in the study area exhibit a clear climatic signal. The analysis of rainfall distribution in periods of recognised slope instability allows the distinction of three situations: 1) moderate intensity rainfall episodes, responsible for minor slope movements on the bank of rivers and shallow translational slides, particularly in artificial trenches; 2) high intensity rainfall episodes, originating flash floods and most landslides triggered by bank erosion; 3) long-lasting rainfall periods, responsible for the rise of the groundwater table and triggering of landslides with deeper slip surfaces.     

Landslides and Rainfall Characteristics Analysis in Taipei City during the Typhoon Nari Event

The severe Typhoon Nari ended on September 15, 2001 with a high-intensity and high-accumulation storm that dumped up to 1249 mm of rain in Taipei City, Taiwan. The high-intensity and high-accumulation event caused flooding and triggered more than 400 soils slips and debris flows and large, complex landslides. Detailed information on 63 events, including rainfall, initiation time, and magnitude of landslides were documented and analyzed to identify the landslides and rainfall characteristic in Taipei City during Typhoon Nari. The result reveals that slump, slide, and debris flow events are associated with the situation of high-intensity or high-accumulation rainfall. The rainfall intensity-duration condition resulted in smaller magnitude and shallow failures. Medium to massive landslide were mainly related to the high-accumulation rainfall. A landslide regionalization process based on rainfall, geomorphologic and geologic characteristics is proposed. Results of the proposed process show good agreement with landslide events observed in the Taipei City during Typhoon Nari.     

Suggestion of a method for landslide early warning using the change in the volumetric water content gradient due to rainfall infiltration

An early warning system can be an effective measure to reduce the damage caused by landslides by facilitating the timely evacuation of residents from a landslide-prone area. Early detection of landslide triggering across a broad range of natural terrain types can be accomplished by monitoring rainfall and the physical property changes of soils in real time or near-real time. This study involved the installation of a real-time monitoring system to observe physical property changes in soils in a valley during rainfall events. This monitoring included the measurement of volumetric water content, which was compared with the results of laboratory flume tests to identify landslide indicators in the soils. The response of volumetric water content to rainfall events is more immediate than that of pore-water pressure, and volumetric water content retains its maximum value for some time before slope failure. Therefore, an alternative method for landslide monitoring can be based on the observation of volumetric water content and its changes over time at shallow soil depths. Although no landslide occurred, the field monitoring results showed a directly proportional relationship between the effective cumulative rainfall and the gradient of volumetric water content per unit time (t/t _max). This preliminary study thus related slope failure to the volumetric water content gradient as a function of rainfall. Laboratory results showed that a high amount of rainfall and a high gradient of volumetric water content could induce slope failure. Based on these results, it is possible to suggest a threshold value of the volumetric water content gradient demarcating the conditions for slope stability and slope failure. This threshold can thus serve as the basis of an early warning system for landslides considering both rainfall and soil properties.     

Modeling landslide recurrence in Seattle, Washington, USA

To manage the hazard associated with shallow landslides, decision makers need an understanding of where and when landslides may occur. A variety of approaches have been used to estimate the hazard from shallow, rainfall-triggered landslides, such as empirical rainfall threshold methods or probabilistic methods based on historical records. The wide availability of Geographic Information Systems (GIS) and digital topographic data has led to the development of analytic methods for landslide hazard estimation that couple steady-state hydrological models with slope stability calculations. Because these methods typically neglect the transient effects of infiltration on slope stability, results cannot be linked with historical or forecasted rainfall sequences. Estimates of the frequency of conditions likely to cause landslides are critical for quantitative risk and hazard assessments. We present results to demonstrate how a transient infiltration model coupled with an infinite slope stability calculation may be used to assess shallow landslide frequency in the City of Seattle, Washington, USA. A module called CRF (Critical RainFall) for estimating deterministic rainfall thresholds has been integrated in the TRIGRS (Transient Rainfall Infiltration and Grid-based Slope-Stability) model that combines a transient, one-dimensional analytic solution for pore-pressure response to rainfall infiltration with an infinite slope stability calculation. Input data for the extended model include topographic slope, colluvial thickness, initial water-table depth, material properties, and rainfall durations. This approach is combined with a statistical treatment of rainfall using a GEV (General Extreme Value) probabilistic distribution to produce maps showing the shallow landslide recurrence induced, on a spatially distributed basis, as a function of rainfall duration and hillslope characteristics.     

Landslides triggered by slipping-fault-generated earthquake on a plateau: an example of the 14 April 2010, Ms 7.1, Yushu, China earthquake

On 14 April 2010 at 07:49 (Beijing time), a catastrophic earthquake with Ms 7.1 struck Yushu County, Qinghai Province, China. A total of 2,036 landslides were interpreted from aerial photographs and satellite images, verified by selected field checking. These landslides cover about a total area of 1.194 km². The characteristics and failure mechanisms of these landslides are presented in this paper. The spatial distribution of the landslides is evidently strongly controlled by the locations of the main co-seismic surface fault ruptures. The landslides commonly occurred close together. Most of the landslides are small; there were only 275 individual landslide (13.5 % of the total number) surface areas larger than 1,000 m². The landslides are of various types. They are mainly shallow, disrupted landslides, but also include rock falls, deep-seated landslides, liquefaction-induced landslides, and compound landslides. Four types of factors are identified as contributing to failure along with the strong ground shaking: natural excavation of the toes of slopes, which mean erosion of the base of the slope, surface water infiltration into slopes, co-seismic fault slipping at landslide sites, and delayed occurrence of landslides due to snow melt or rainfall infiltration at sites where slopes were weakened by the co-seismic ground shaking. To analyze the spatial distribution of the landslides, the landslide area percentage (LAP) and landslide number density (LND) were compared with peak ground acceleration (PGA), distance from co-seismic main surface fault ruptures, elevation, slope gradient, slope aspect, and lithology. The results show landslide occurrence is strongly controlled by proximity to the main surface fault ruptures, with most landslides occurring within 2.5 km of such ruptures. There is no evident correlation between landslide occurrences and PGA. Both LAP and LND have strongly positive correlations with slope gradient, and additionally, sites at elevations between 3,800 and 4,000 m are relatively susceptible to landslide occurrence; as are slopes with northeast, east, and southeast slope aspects. Q₄ al-pl, N, and T₃ kn ¹ have more concentrated landslide activity than others. This paper provides a detailed inventory map of landslides triggered by the 2010 Yushu earthquake for future seismic landslide hazard analysis and also provides a study case of characteristics, failure mechanisms, and spatial distribution of landslides triggered by slipping-fault generated earthquake on a plateau.     

A distributed hydrological–geotechnical model using satellite-derived rainfall estimates for shallow landslide prediction system at a catchment scale

This paper describes the potential applicability of a hydrological–geotechnical modeling system using satellite-based rainfall estimates for a shallow landslide prediction system. The physically based distributed model has been developed by integrating a grid-based distributed kinematic wave rainfall-runoff model with an infinite slope stability approach. The model was forced by the satellite-based near real-time half-hourly CMORPH global rainfall product prepared by NOAA-CPC. The method combines the following two model outputs necessary for identifying where and when shallow landslides may potentially occur in the catchment: (1) the time-invariant spatial distribution of areas susceptible to slope instability map, for which the river catchment is divided into stability classes according to the critical relative soil saturation; this output is designed to portray the effect of quasi-static land surface variables and soil strength properties on slope instability and (2) a produced map linked with spatiotemporally varying hydrologic properties to provide a time-varying estimate of susceptibility to slope movement in response to rainfall. The proposed hydrological model predicts the dynamic of soil saturation in each grid element. The stored water in each grid element is then used for updating the relative soil saturation and analyzing the slope stability. A grid of slope is defined to be unstable when the relative soil saturation becomes higher than the critical level and is the basis for issuing a shallow landslide warning. The method was applied to past landslides in the upper Citarum River catchment (2,310 km²), Indonesia; the resulting time-invariant landslide susceptibility map shows good agreement with the spatial patterns of documented historical landslides (1985–2008). Application of the model to two recent shallow landslides shows that the model can successfully predict the effect of rainfall movement and intensity on the spatiotemporal dynamic of hydrological variables that trigger shallow landslides. Several hours before the landslides, the model predicted unstable conditions in some grids over and near the grids at which the actual shallow landslides occurred. Overall, the results demonstrate the potential applicability of the modeling system for shallow landslide disaster predictions and warnings.