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An extreme rainstorm hit Fuyang District, Zhejiang Province, China, on 22 July 2023. A record-breaking 320 mm of rain fell in less than 48 h. In the early evening of 22 July, more than 145 shallow landslides emerged in a 20 km2 hilly area of Fuyang amid turbulent flash flooding and claimed five lives. Post-event field investigations and laboratory experiments were urgently carried out, targeting two geologically typical shallow landslides, to decipher the initiation mechanism and distributing features of the regionally distributed landslides. The main findings are summarized as follows: (1) The week-long rainfall preceding the event and the intense storm on 22 July are presumably primary triggers for the landslides. Besides rainfall, convergent topography of hollows may be another important factor influencing the initiation of landslides. (2) The dominant moso bamboo has an extensive and interconnected root system, which could significantly stabilize slopes by enhancing soil strength and restricting cracks. (3) The sedimentary Heshangzhen Group area is more susceptible to landslides than the igneous Shuangxiwu Group area. Bedrock lithologies affect landslide distribution through controlling soil structures and properties to shape the hillslope hydrology and also through influencing landscape morphology. This study offers new evidence and insights into the lithological control on landslide initiation and distribution. [ABSTRACT FROM AUTHOR]

Rainfall-triggered landslides pose a significant threat to both infrastructure and human lives, making it crucial to comprehend the factors that contribute to their occurrence. Specifically, understanding the relationship between these factors and the amount of rain that is necessary for triggering such events is essential for effective prediction and mitigation strategies. To address this issue, our study proposes a statistical modelling approach using machine learning, specifically the Random Forest algorithm, to investigate the connection between landslide predisposing factors and the daily rainfall intensity threshold necessary for the initiation of shallow landslides in Portugal. By leveraging a comprehensive dataset comprising historical landslide events, associated critical rainfall, and ten distinct landslide predisposing factors, we developed several models and used cross-validation technique to evaluate their performance. Our findings demonstrate that the Random Forest model effectively captures a relationship among landslide predisposing factors, critical daily rainfall intensity, and landslide occurrences. The models exhibit a satisfactory accuracy in assessing the spatial variation of critical daily rainfall intensity based on the predisposing factors, with a mean absolute percentage error (MAPE) of around 17%. Furthermore, the models provide valuable insights into the relative importance of various predisposing factors in landslide triggering, highlighting the significance of each factor. It was found that it takes higher rainfall intensity to trigger shallow landslides in the north region of Portugal when considering critical rainfall events of 3 and 13 days. Slope aspect, slope angle, and clay content in the soil are among the main predisposing factors used for defining the spatial variation of the daily rainfall intensity threshold. [ABSTRACT FROM AUTHOR]

Landscapes disturbed by shallow landslides present several residual risks. For example, residual soils on sliding surfaces may lead to the re-occurrence of shallow landslides, and landslide deposits on valley floors may introduce multiple hazards associated with river blocking or landslide damming. Despite such risks, few studies have investigated the residual risks following shallow landslides, and thus, no methodology has been established for assessing such risks. In this study, we combined portable cone penetration test (PCPT) and electrical resistivity tomography (ERT) to investigate the post-event risks associated with a landslide scar resulting from the 2018 Hokkaido Eastern Iburi earthquake (HEIE) in Japan. The multi-point PCPT identified the interface between a weak volcanic soil layer and underlying weathered sedimentary rocks. This interface exhibited an abrupt spatial change in resistivity, ranging from 20 to 100 Ωm. The thickness of the residual soil layer was 0.3–3.2 m and that of the landslide deposit exceeded 2.0 m. An infinite-slope stability analysis was performed to predict the re-occurrence of shallow landslides due to a lower intensity earthquake than that of HEIE in this region. Considering the area affected by the HEIE and the physical properties of soil layers, our findings imply a widespread risk of re-occurrence of shallow landslides over an area of 20 km × 20 km. Although the areal coverage of the combined ERT/PCPT method needs to be extended, it is effective for assessing the residual risks associated with shallow landslides. [ABSTRACT FROM AUTHOR]

Climate change and rapid urban expansion can foster landslide disasters and cause severe damage in areas that are traditionally considered relatively safe from such hazards. In this regard, a recent event in Daoshi Town, China, is a good example that showcases the combined effect of extreme rainfall and urbanization in generating a first-time landslide disaster for a developing community. On 10 August 2019, Typhoon Lekima made its landing in Zhejiang Province, China. It generated a rainstorm close to Daoshi Town, inducing severe and unexpected damage from shallow landslides and debris flows (7 deaths, 25,560 affected and a direct economic loss of 1.5 hundred million dollars). In this region, similar rainfall has never been experienced before, and landslides have seldom been reported in the past. Field investigations and measurements were conducted to identify the landslide distributions, size characteristics, and mobility. A landslide inventory map, including 251 shallow landslides and 82 debris flows, was compiled to study the geological and topographical factors related to widespread failure. The results showed that shallow landslides and debris flows mainly occurred in the north-central part of the study area, in which the base was mainly composed of strongly weathered limestone. The elevation, mean slope, and slope aspect also contributed to the occurrence of landslides. In addition, 32.4% of the disasters were located close to buildings and roads, highlighting a relevant predisposing role played by human activity. This typhoon-bound rainstorm gave rise to a higher triggering condition than the normally required rainfall threshold in the study area. Under this circumstance, landslides were easily triggered and were able to transition into debris flows due to liquefaction. Field observations demonstrate that the erosion of slope toes caused by debris flows also facilitated the occurrence of other shallow landslides. A changing climatic setting is a never-before-experienced phenomenon for the study area. This research improves the understanding of landslide development in the area and prepares basic data and information for further studies and mitigation strategies. [ABSTRACT FROM AUTHOR]

Optical fibre–based sensors have now established their place in the field of geohazard monitoring due to their sensitivity to strain and temperature changes. Progressive development in the technology leads to the availability of novel, accurate and durable sensors at a relatively limited cost. This creates room for original monitoring applications that have been, so far, impeded by the shortcomings of conventional monitoring tools. In this work, we explore the applicability of an interferometric optical fibre sensor as a vibration sensing tool at laboratory scale. We tested the ability of the sensor to identify precursors of instability in a downscaled model of a rainfall-induced landslide composed of granular material. We carried out four experimental tests which involved different sensor deployments and soil mixtures. The recorded signals were processed by means of a time–frequency analysis and we identified two frequency-domain parameters—the spectral centroid and band power—that could provide information on the development of instability. Their ratio yielded a unique parameter through which a precursory stage could be outlined by defining a threshold value based on the data collected at the beginning of the experiment. In our lab tests, precursors of instability were detected 2–3 min before a crack was observed at the surface. This may upscale to a lead time of about 20–30 min or more in the field, classifying our monitoring approach in between an alarm and a warning system. The work presented here can be considered a first promising step towards an innovative monitoring system and shows the potential of optical fibre sensing as a shallow landslide monitoring technique, encouraging further testing, especially in real-case studies. [ABSTRACT FROM AUTHOR]

By utilizing the Green-Ampt infiltration equation and the infinite slope stability model, a method for analyzing shallow slope failures caused by rainfall is developed. With rainfall intensity, soil characteristics, and topography, the modified Green-Ampt infiltration equation is used to estimate the rainfall infiltration capacity and depth of infiltration in a given slope. Assigning the calculated depth of infiltration as the depth of slip surface, the factor of safety of the slope is obtained through the infinite slope stability model. A time-series visualization map of the space-time varying factor of safety is generated when the method is implemented with the aid of Geographic Information System (GIS) software. The model is applied and validated with the landslides that occurred during the October 2019 Typhoon Hagibis in Marumori, Japan. The model results show good agreement with the reported time and depths of failure, and the analysis of the spatial distribution of predicted failures yielded receiver operating characteristic-area under the curve (ROC-AUC) value of 0.90. The applicability of the model can be extended for post-analysis, real-time, or projected assessment of slope stability, depending on the nature of input rainfall data (e.g., historical, real-time, forecast, hypothetical). [ABSTRACT FROM AUTHOR]

Slopes covered with unsaturated shallow pyroclastic deposits, lying upon fractured limestone bedrock, are widespread in the mountains around Naples (southern Italy). Rainfall infiltration, reducing soil suction, eventually triggers shallow landslides. While drastic reduction of suction is unanimously recognized as the triggering mechanism, there is still debate about the hydrological processes controlling slope drainage and causing the establishment of landslide predisposing conditions. Field observations at the slope of Cervinara suggested that temporary storage of water in a perched aquifer, in the upper part of the fractured bedrock, may affect the leakage through the soil-bedrock interface. Hence, a physically based model, coupling flows in the unsaturated soil cover and in the perched aquifer, has been applied to three large rainfall events which occurred in December 1999 (when a landslide was triggered), January 2009, and November 2012. The results highlight that the different responses of soil and aquifer to precipitations, related not only to rainfall event characteristics (i.e., duration and mean intensity) but also to the initial conditions of the slope, determined by antecedent precipitations, can play a prominent role in the triggering of landslides. In fact, further simulations with synthetic rainfall events and different initial conditions provide a possible interpretation of the triggering of the landslide of December 1999, indicating that a soil profile with dry conditions at the base and a low level in the perched aquifer, typical of late autumn, can impede the drainage of infiltrating water through the soil-bedrock interface, thus favoring the build-up of pore pressure within the soil cover. [ABSTRACT FROM AUTHOR]

Empirical thresholds indicating the meteorological conditions leading to shallow landslide triggering are one of the most important components of landslide early warning systems (LEWS). Thresholds have been determined for many parts of the globe and present significant margins of improvement, especially for the high number of false alarms they produce. The use of soil moisture information to define hydro-meteorological thresholds is a potential way of improvement. Such information is becoming increasingly available from remote sensing and sensor networks, but to date, there is a lack of studies that quantify the possible improvement of the performance of LEWS. In this study, we investigate this issue by modelling the response of slopes to precipitations, introducing also the possible influence of uncertainty in soil moisture provided by either field sensors or remote sensing, and investigating various soil depths at which the information may be available. Results show that soil moisture information introduced within hydro-meteorological thresholds can significantly reduce the false alarm ratio of LEWS, while keeping at least unvaried the number of missed alarms. The degree of improvement is particularly significant in the case of soils with small water storage capacity. [ABSTRACT FROM AUTHOR]

Shallow landslides have posed significant threats to humans around the world. In order to reduce landslide disaster risk, the effectiveness of early warning systems and hazard zonation work needs to be improved. This research attempted to couple a landslide simulation model (LS-RAPID model) and a hydrological model (Rainfall-Runoff-Inundation (RRI) model) to exploit the advantages of each model for simulating and predicting landslide hazard (location and timing). The pilot area is a small catchment where a shallow landslide happened in July 2015 after 2 days of heavy rain. The landslide buried 3 houses and killed 8 people in Cao Thang Ward, Halong City, Vietnam. A soil sample was collected from the sliding surface and tested using an undrained ring-shear apparatus ICL-2 in the undrained condition. A thickness map of the potential sliding material was interpolated from the relationship between the depth of sandy soil layer and slope (based on 12 soil drill locations) and updated through field surveys in the study area. Different pore water pressure ratio scenarios were applied in the LS-RAPID model to simulate in 3D the initiation and motion of the rapid shallow landslide to create different hazard maps. The subsurface water level was monitored at two locations on the top of the shallow landslide. Based on the observed subsurface water and rainfall data, the RRI model was calibrated and then integrated with the LS-RAPID scenarios to generate Risk Index maps. The simulation results from the newly proposed coupled hydrological-geotechnical framework were compared with those from the observed landslide hazard and showed the reliability to predict the spatial and temporal occurrence of landslide hazard. This could be very useful for supporting decision-makers in rainfall-induced landslide hazard early warning and land use planning. [ABSTRACT FROM AUTHOR]

On 2 September 2018, an intense rainstorm swept Mengdong Town in Yunnan Province of China, inducing a serious landslide and debris flow disaster with 10 deaths and 11 missing. Image interpretation, field survey, and slope stability analysis were used to examine the characteristics and initiation mechanism of this hazard. A total of 1774 landslide scars were identified, the area of which occupied 8.26% of the study region. Due to the spatial inhomogeneity of precipitation, these scars mainly concentrated along valleys in the lower part of the study area. Besides, well-forested hillslopes were more prone to landslides, indicating the limited role of trees in stabilizing slopes in extreme rainfall events. The initiation of landslides is mainly attributed to the week cohesion of the saturated clayey sand beneath the root zone, where the tensile resistance of roots was absent, and the increase of positive pore water pressure. Additionally, 288 landslide scars were situated adjacent to roads, demonstrating that the road construction activity had intensified the landslide disaster. Owing to the relatively low mobility of landslides, a considerable portion of landslide debris deposited on the valley floor in smaller watersheds (< 6.03 hm2), while the remaining portion entered high-order channels. In these channels, where stream power was relatively large, the woody debris and soil carried by landslides were entrained by streamflow, and debris flows were formed. Moreover, the magnitude of debris flow was amplified by the vertical and lateral erosion of the stream channel. [ABSTRACT FROM AUTHOR]

Rainfall-induced diffuse shallow landslides are one of the most critical natural hazards as they often evolve into highly destructive flow slides and debris flows. Vegetation is recognised to play a key role in landslide occurrence and is frequently invoked as a potential remedial measure for slope stabilisation at the catchment scale. The beneficial action of vegetation is generally associated with mechanical (root anchoring) and hydrological (suction generated by root water uptake) effects. There is indeed a third effect that has thus far been little explored. The rhizosphere, the portion of soil directly affected by plant roots, is characterised by hydraulic conductivity higher than the underlying soil horizons. This significantly affects hillslope hydrology by promoting lateral diversion of rainwater. This paper presents a case study in Scotland where the rhizosphere is demonstrated to play a major role in controlling shallow landslides. Field investigation and laboratory testing were carried out to characterise the hydraulic conductivity of the rhizosphere and deeper horizons. In turn, this formed the basis for the development of a physically based model for the slope. The model was first validated against its capability to simulate failure of two historical landslides and then exploited to demonstrate the beneficial effect of the rhizosphere. The lesson learned from this study is that shallow landslide hazard can be mitigated by enhancing the capacity of the rhizosphere to act as a natural lateral drainage. This implies that plants with root-system architecture that enhances lateral subsurface flow should be privileged when designing vegetation-based remedial measures. [ABSTRACT FROM AUTHOR]

The 2018 Hokkaido Eastern Iburi Earthquake struck the eastern Iburi region (epicenter: 42.691°N, 142.007°E, depth: 37.0 km) of Hokkaido, Japan, at 3:07.59 JST, September 6, 2018 (18:07.59, September 5, 2018 UTC). Many shallow landslides were triggered by this Mw 6.6 (Mj 6.7) earthquake. The basement complex in the affected area (sedimentary rocks) is covered with thick pyroclastic fall deposits derived from the Tarumae Volcano, etc., and the strong seismic shocks triggered shallow landsliding of them. Shallow landslides moving along valley type topography traveled greater distances than those moving along planar slope topography. Some shallow landslides occurred on relatively gentle slopes (< 30°). The earthquake also induced several large-scale deep-seated landslides, including one that has formed a landslide dam in the Hidaka-horonai River. Landslides were densely distributed over hilly regions (elevation: 200–400 m) within an area of approximately 400 km2 in Atsuma (landslides caused 36 deaths), Abira, and Mukawa, and the number of landslides and the total area of the landslides were the largest in Japan ever since the Meiji Era (1868–1912). The catchments where shallow landslides were concentrated were severely devastated. [ABSTRACT FROM AUTHOR]

Shallow landslides are unforeseeable phenomena often resulting in critical conditions in terms of people’s safety and damage. The main purpose of this paper is the comparison of different statistical methods used to determine the rainfall thresholds for the shallow landslide occurrence. Rainfall data over a 46-year period were collected for one rain gauge located in a test area of northwest Italy (Riviera Spezzina; RS). In the RS, intense rainfalls often induce shallow landslides causing damage and sometimes casualties. The rainfall events occurred in the 1967-2006 period were classified as events inducing shallow landslides (SLEs1967-2006) and events that did not trigger shallow landslides (NSLEs1967-2006). Thresholds for various percentiles of SLEs1967-2006 were computed by identifying the lower limit above which shallow landslides occurred. Another set of thresholds, corresponding to different probabilities of occurrence, was determined using SLEs1967-2006 and NSLEs1967-2006. The least-squares linear fit (LSF) and the quantile regression (QR) techniques were employed in the former approach, while the logistic regression (LR) was applied in the latter. The thresholds were validated with the same data used for their definition and with the data recorded in the 2008-2014 period. Contingency tables were created and contingencies and skill scores were computed. The 10% probability threshold obtained using the LR method is characterized by the best values of at least two skill scores for both periods considered; therefore, it may be considered the “best” threshold for the RS. The results of this work can help the choice of the best statistical method to determine the shallow landslide rainfall thresholds. [ABSTRACT FROM AUTHOR]

Shallow landslides may be seen as local disturbances that foster the evolution of slope landscapes as part of their self-regulating capacity. Gaining insight into how slope ecosystems function and evolve could make eco-engineering interventions on slopes more successful. The objective of the present study is to detect traits of shallow landslide-triggered ecosystem evolution, self-regulation and biophysical diversity in a small-scale landslide-prone slope in Northeast Scotland. A protocol was defined to explore the emergence of landslide-driven slope habitats. This protocol studied plant diversity, species richness and plant biomass differences and their interactions with certain soil and topographic attributes at three slope strata during two consecutive growing seasons following an assemblage of shallow landslide events. Plant species and soil properties with potential as indicators of the different landslide-driven slope habitats and landscape evolution were also considered. Shallow landslides contributed to biophysical diversity and created distinct slope habitats within the landscape. Habitat differences in terms of species richness and composition were a direct consequence of the slope self-regulation. Certain plant species were found to be valid indicators of landslide-driven biophysical diversity. Soil total nitrogen and resistance to penetration were related to slope habitat and landscape evolution. As expected, plant establishment relied upon light and nitrogen trade-offs, which in turn were influenced by landscape topography. The insights derived from this study will be useful in slope restoration, particularly in harmonising effective actions with the functioning of landslide-prone ecosystems. Further research directions to clarify the observed variability and interactions are highlighted. [ABSTRACT FROM AUTHOR]

A process chain for the definition and the performance assessment of an operational regional warning model for rainfall-induced landslides, based on rainfall thresholds, is proposed and tested in a landslide-prone area in the Campania region, southern Italy. A database of 96 shallow landslides triggered by rainfall in the period 2003-2010 and rainfall data gathered from 58 rain gauges are used. First, a set of rainfall threshold equations are defined applying a well-known frequentist method to all the reconstructed rainfall conditions responsible for the documented landslides in the area of analysis. Several thresholds at different exceedance probabilities (percentiles) are evaluated, and nine different percentile combinations are selected for the activation of three warning levels. Subsequently, for each combination, the issuing of warning levels is computed by comparing, over time, the measured rainfall with the pre-defined warning level thresholds. Finally, the optimal percentile combination to be employed in the regional early warning system, i.e. the one providing the best model performance in terms of success and error indicators, is selected employing the 'event, duration matrix, performance' (EDuMaP) method. [ABSTRACT FROM AUTHOR]

Evaluating the performance of a physically based model for landslide prediction was conducted in this study. The model was developed based on the basis of the infinite slope instability analysis and TOPMODEL for saturated water level estimation, which enabled to predict the location and time of occurrence of shallow landslides. Field data from 2008 to 2013 in two areas vulnerable to landslide in Taiwan were collected to test the applicability of the model for landslide prediction. Three indexes including the probability of detection (POD), false alarm ratio (FAR), and threat score (TS) were adopted to assess the advantages and disadvantages of the model. The results indicated that the POD for the landslide prediction by using the proposed model was 1.00, the FAR was lower than 0.25, and the overall TS value was higher than 0.75. It is promising to apply the proposed model for landslide early warnings to reduce the loss of life and property. [ABSTRACT FROM AUTHOR]

Process-based models are widely used for rainfall-induced shallow landslide forecasting. Previous studies have successfully applied the U.S. Geological Survey's Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) model (Baum et al. 2002) to compute infiltration-driven changes in the hillslopes' factor of safety on small scales (i.e., tens of square kilometers). Soil data input for such models are difficult to obtain across larger regions. This work describes a novel methodology for the application of TRIGRS over broad areas with relatively uniform hydrogeological properties. The study area is a 550-km region in Central Italy covered by post-orogenic Quaternary sediments. Due to the lack of field data, we assigned mechanical and hydrological property values through a statistical analysis based on literature review of soils matching the local lithologies. We calibrated the model using rainfall data from 25 historical rainfall events that triggered landslides. We compared the variation of pressure head and factor of safety with the landslide occurrence to identify the best fitting input conditions. Using calibrated inputs and a soil depth model, we ran TRIGRS for the study area. Receiver operating characteristic (ROC) analysis, comparing the model's output with a shallow landslide inventory, shows that TRIGRS effectively simulated the instability conditions in the post-orogenic complex during historical rainfall scenarios. The implication of this work is that rainfall-induced landslides over large regions may be predicted by a deterministic model, even where data on geotechnical and hydraulic properties as well as temporal changes in topography or subsurface conditions are not available. [ABSTRACT FROM AUTHOR]

Intense rainfall on July 12, 2012, triggered numerous shallow landslides on steep grassy hillslopes of Aso Volcano, Kyushu, Japan. The hillslopes are mantled by several meters thickness of fallout tephra accumulation from Holocene eruptions. The landslides occurred about 1 m deep in surficial tephra deposits. Stratigraphic surveys of three landslides showed that the tephra deposits beneath the ground consist of two layers, an upper blackish and a lower yellow-brown layer, and that the upper layer represents the accumulation of tephra during the last 1000 years. The surveys also demonstrated that the slip surfaces were formed near the boundary of the two layers, resulting in the sliding of the upper layer. We measured the saturated hydraulic conductivities of both the layers. The hydraulic conductivities of the lower layer are 1 to 2 orders of magnitude lower than those of the upper layer, suggesting that the lower layer acts as an aquiclude. Therefore, pore water pressure locally increases near the boundary between the two layers and failure occurs. We also examined the soil hardness, which has a high correlation with soil shear strength parameters, of the tephra layers at the three landslides. The soil hardness of the lower layer is greater than that of the upper layer in two of the landslides, suggesting that the lower layer collapses less readily than the upper layer. Comparison with previous landslides in the study area demonstrates that this type of rainfall-induced landslide event has occurred in the past and will recur in the future. [ABSTRACT FROM AUTHOR]

On October 25, 2011, an extreme rainfall event affected a wide area along the coasts of Cinque Terre (eastern Liguria, northern Italy). Particularly, in the Vernazza catchment, the event triggered hundreds of shallow landslides and a debris flood that caused three casualties. Investigation of the slope stability after the event was carried out aiming at defining the most effective mitigation measures which may be adopted in future land use planning. To this objective, a susceptibility model was produced and a series of scenarios were simulated using probabilistic methods. The susceptibility model has provided information about landslide conditioning factors on which to act for reducing landslide occurrence and therefore the associated risk. The simulations have taken into consideration the following alternative types of mitigation measures: (1) restoration of abandoned terraces, (2) reforestation of abandoned terraces, (3) use of local structural measures over stretches of potentially unstable hillsides and (4) avoidance of any intervention. The advantages and the disadvantages of the proposed mitigation measures for shallow landslide risk are discussed considering the results of the simulations and taking into account their complex interaction with environmental, historical, cultural and socio-economic aspects. The results show that the most effective mitigation strategy for reducing landslide risk at short term consists of applying structural measures over potentially unstable slopes. However, a long-term programme promoting the development of agricultural or forestry practices on terraced slopes is necessary. In fact, the simulations indicate that if no measures are applied to avoid the degradation of the terraced areas, landslide areal frequency would inevitably increase. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to develop a new hazard evaluation technique considering the current limitations, particularly for shallow landslides. For this purpose, the Buyukkoy catchment area, located in the East Black Sea Region in the east of Rize province and the south of Cayeli district, was selected as the study area. The investigations were executed in four different stages. These were (1) preparation of a temporal shallow landslide inventory of the study area, (2) assessment of conditioning factors in the catchment, (3) susceptibility analyses and (4) hazard evaluations and mapping. A total of 251 shallow landslides in the period of 1955-2007 were recognised using different data sources. A 'Sampling Circle' approach was proposed to define shallow landslide initiation in the mapping units in susceptibility evaluations. To accomplish the susceptibility analyses, the method of artificial neural networks was implemented. According to the performance analyses conducted using the training and testing datasets, the prediction and generalisation capacities of the models were found to be very high. To transform the susceptibility values into hazard rates, a new approach with a new equation was developed, taking into account the behaviour of the responsible triggering factor over time in the study area. In the proposed equation, the threshold value of the triggering factor and the recurrence interval are the independent variables. This unique property of the suggested equation allows the execution of more flexible and more dynamic hazard assessments. Finally, using the proposed technique, shallow landslide initiation hazard maps of the Buyukkoy catchment area for the return periods of 1, 2, 5, 10, 50 and 100 years were produced. [ABSTRACT FROM AUTHOR]

Statistical and deterministic methods are widely used in geographic information system based landslide susceptibility mapping. This paper compares the predictive capability of three different models, namely the Weight of Evidence, the Fuzzy Logic and SHALSTAB, for producing shallow earth slide susceptibility maps, to be included as informative layers in land use planning at a local level. The test site is an area of about 450 km in the northern Apennines of Italy where, in April 2004, rainfall combined with snowmelt triggered hundreds of shallow earth slides that damaged roads and other infrastructure. An inventory of the landslides triggered by the event was obtained from interpretation of aerial photos dating back to May 2004. The pre-existence of mapped landslides was then checked using earlier aerial photo coverage. All the predictive models were run on the same set of geo-environmental causal factors: soil type, soil thickness, land cover, possibility of deep drainage through the bedrock, slope angle, and upslope contributing area. Model performance was assessed using a threshold-independent approach (the ROC plot). Results show that global accuracy is as high as 0.77 for both statistical models, while it is only 0.56 for SHALSTAB. Besides the limited quality of input data over large areas, the relatively poorer performance of the deterministic model maybe also due to the simplified assumptions behind the hydrological component (steady-state slope parallel flow), which can be considered unsuitable for describing the hydrologic behavior of clay slopes, that are widespread in the study area. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The paper presents the results of some experimental tests reproducing the triggering mechanism of a special kind of shallow landslides induced by rainfalls (soil slip) in a physical 1-g model. The experimental data have been employed to verify the capability of a simplified stability model to describe the phenomenon and to back-analyse its occurrence in a case history (Pizzo d’Alvano, Campania Region 1998). The method enables a direct correlation between the safety factor of a slope and rainfall intensity, as well as antecedent rainfalls. [ABSTRACT FROM AUTHOR]