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1
Crosta, G. B., and P. Frattini. "Distributed modelling of shallow landslides triggered by intense rainfall." Natural Hazards and Earth System Sciences 3, no. 1/2 (April 30, 2003): 81–93. http://dx.doi.org/10.5194/nhess-3-81-2003.
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Abstract. Hazard assessment of shallow landslides represents an important aspect of land management in mountainous areas. Among all the methods proposed in the literature, physically based methods are the only ones that explicitly includes the dynamic factors that control landslide triggering (rainfall pattern, land-use). For this reason, they allow forecasting both the temporal and the spatial distribution of shallow landslides. Physically based methods for shallow landslides are based on the coupling of the infinite slope stability analysis with hydrological models. Three different grid-based distributed hydrological models are presented in this paper: a steady state model, a transient "piston-flow" wetting front model, and a transient diffusive model. A comparative test of these models was performed to simulate landslide occurred during a rainfall event (27–28 June 1997) that triggered hundreds of shallow landslides within Lecco province (central Southern Alps, Italy). In order to test the potential for a completely distributed model for rainfall-triggered landslides, radar detected rainfall intensity has been used. A new procedure for quantitative evaluation of distributed model performance is presented and used in this paper. The diffusive model results in the best model for the simulation of shallow landslide triggering after a rainfall event like the one that we have analysed. Finally, radar data available for the June 1997 event permitted greatly improving the simulation. In particular, radar data allowed to explain the non-uniform distribution of landslides within the study area.
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Yu, Teng-To, Ting-Shiuan Wang, and Youg-Sin Cheng. "Analysis of Factors Triggering Shallow Failure and Deep-Seated Landslides Induced by Single Rainfall Events." Journal of Disaster Research 10, no. 5 (October 1, 2015): 966–72. http://dx.doi.org/10.20965/jdr.2015.p0966.
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Earthquakes, rainfall, or a combination of both can trigger landslides, which can be classified into shallow and deep-seated types according to scale. Landslide risk potential can be charted according to the spatiotemporal characteristics of a combination of triggering factors that can be collated for similar historical events by various methods. The geographic information system (GIS) and the instability index method are two approaches commonly used to perform such a task; however, the nature of the event and the quality of imported data affect the degree of bias of model predictions against real-time values. To identify the differences between shallow and deep-seated landslides, 324 cases of landslides triggered by single rainfall events in Taiwan are analyzed in this study. It is determined that the principal factor governing shallow failure for rainfall-induced landslides is slope and that deep-seated failure is controlled by the amount of accumulated rainfall. By arranging the weighting, these factors could predict 93% and 75% of the occurrences of shallow and deep-seated landslides, respectively, based on a pre-event digital terrain model.
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Roccati, Anna, Francesco Faccini, Fabio Luino, Laura Turconi, and Fausto Guzzetti. "Rainfall events with shallow landslides in the Entella catchment, Liguria, northern Italy." Natural Hazards and Earth System Sciences 18, no. 9 (September 13, 2018): 2367–86. http://dx.doi.org/10.5194/nhess-18-2367-2018.
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Abstract. In recent decades, the Entella River basin, in the Liguria Apennines, northern Italy, was hit by numerous intense rainfall events that triggered shallow landslides and earth flows, causing casualties and extensive damage. We analyzed landslide information obtained from different sources and rainfall data recorded in the period 2002–2016 by rain gauges scattered throughout the catchment, to identify the event rainfall duration, D (in h), and rainfall intensity, I (in mm h−1), that presumably caused the landslide events. Rainfall-induced landslides affected the whole catchment area, but were most frequent and abundant in the central part, where the three most severe events hit on 23–24 November 2002, 21–22 October 2013 and 10–11 November 2014. Examining the timing and location of the slope failures, we found that the rainfall-induced landslides occurred primarily at the same time or within 6 h from the maximum peak rainfall intensity, and at or near the geographical location where the rainfall intensity was largest. Failures involved mainly forested and natural surfaces, and secondarily cultivated and terraced slopes, with different levels of maintenance. Man-made structures frequently characterize the landslide source areas. Adopting a frequentist approach, we define the event rainfall intensity–event duration (ID) threshold for the possible initiation of shallow landslides and hyper-concentrated flows in the Entella River basin. The threshold is lower than most of the curves proposed in the literature for similar mountain catchments, local areas and single regions in Italy. The result suggests a high susceptibility to rainfall-induced shallow landslides of the Entella catchment due to its high-relief topography, geological and geomorphological settings, meteorological and rainfall conditions, and human interference. Analysis of the antecedent rainfall conditions for different periods, from 3 to 15 days, revealed that the antecedent rainfall did not play a significant role in the initiation of landslides in the Entella catchment. We expect that our findings will be useful in regional to local landslides early warning systems, and for land planning aimed at reducing landslide risk in the study area.
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Kieffer, D. Scott, Randy Jibson, Ellen M. Rathje, and Keith Kelson. "Landslides Triggered by the 2004 Niigata Ken Chuetsu, Japan, Earthquake." Earthquake Spectra 22, no. 1_suppl (March 2006): 47–73. http://dx.doi.org/10.1193/1.2173021.
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The Niigata Ken Chuetsu earthquake triggered a vast number of landslides in the epicentral region. Landslide concentrations were among the highest ever measured after an earthquake, and most of the triggered landslides were relatively shallow failures parallel to the steep slope faces. The dense concentration of landslides can be attributed to steep local topography in relatively weak geologic units, adverse hydrologic conditions caused by significant antecedent rainfall, and very strong shaking. Many of the landslides could be discerned from high-resolution satellite imagery acquired immediately after the earthquake.
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Vessia, G., M. Parise, M. T. Brunetti, S. Peruccacci, M. Rossi, C. Vennari, and F. Guzzetti. "Automated reconstruction of rainfall events responsible for shallow landslides." Natural Hazards and Earth System Sciences 14, no. 9 (September 10, 2014): 2399–408. http://dx.doi.org/10.5194/nhess-14-2399-2014.
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Abstract. Over the last 40 years, many contributions have identified empirical rainfall thresholds (e.g. rainfall intensity (I) vs. rainfall duration (D), cumulated rainfall vs. rainfall duration (ED), cumulated rainfall vs. rainfall intensity (EI)) for the possible initiation of shallow landslides, based on local and global inventories. Although different methods to trace the threshold curves have been proposed and discussed in literature, a systematic study to develop an automated procedure to select the rainfall event responsible for the landslide occurrence has only rarely been addressed. Objective criteria for estimating the rainfall responsible for the landslide occurrence play a prominent role on the threshold values. In this paper, two criteria for the identification of the effective rainfall events are presented. The first criterion is based on the analysis of the time series of rainfall mean intensity values over 1 month preceding the landslide occurrence. The second criterion is based on the analysis of the trend in the time function of the cumulated mean intensity series calculated from the rainfall records measured through rain gauges. The two criteria have been implemented in an automated procedure that is written in the R language. A sample of 100 shallow landslides collected in Italy from 2002 to 2012 was used to calibrate the procedure. The cumulated event rainfall (E) and duration (D) of rainfall events that triggered the documented landslides are calculated through the new procedure and are fitted with power law in the D, E diagram. The results are discussed by comparing the D, E pairs calculated by the automated procedure and the ones by the expert method.
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Lainas, Spyridon, Nikolaos Depountis, and Nikolaos Sabatakakis. "Preliminary Forecasting of Rainfall-Induced Shallow Landslides in the Wildfire Burned Areas of Western Greece." Land 10, no. 8 (August 20, 2021): 877. http://dx.doi.org/10.3390/land10080877.
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A new methodology for shallow landslide forecasting in wildfire burned areas is proposed by estimating the annual probability of rainfall threshold exceedance. For this purpose, extensive geological fieldwork was carried out in 122 landslides, which have been periodically activated in Western Greece, after the devastating wildfires that occurred in August 2007 and burned large areas in several parts of Western Greece. In addition, daily rainfall data covering more than 40 years has been collected and statistically processed to estimate the exceedance probability of the rainfall threshold above which these landslides are activated. The objectives of this study are to quantify the magnitude and duration of rainfall above which landslides in burned areas are activated, as well as to introduce a novel methodology on rainfall-induced landslide forecasting. It has been concluded that rainfall-induced landslide annual exceedance probability in the burned areas is higher when cumulative rainfall duration ranges from 6 to 9 days with local differences due to the prevailing geological conditions and landscape characteristics. The proposed methodology can be used as a basis for landslide forecasting in wildfire-affected areas, especially when triggered by rainfall, and can be further developed as a tool for preliminary landslide hazard assessment.
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Jordanova, Galena, Stefano Luigi Gariano, Massimo Melillo, Silvia Peruccacci, Maria Teresa Brunetti, and Mateja Jemec Auflič. "Determination of Empirical Rainfall Thresholds for Shallow Landslides in Slovenia Using an Automatic Tool." Water 12, no. 5 (May 19, 2020): 1449. http://dx.doi.org/10.3390/w12051449.
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Rainfall-triggered shallow landslides represent a major threat to people and infrastructure worldwide. Predicting the possibility of a landslide occurrence accurately means understanding the trigger mechanisms adequately. Rainfall is the main cause of slope failures in Slovenia, and rainfall thresholds are among the most-used tools to predict the possible occurrence of rainfall-triggered landslides. The recent validation of the prototype landslide early system in Slovenia highlighted the need to define new reliable rainfall thresholds. In this study, several empirical thresholds are determined using an automatic tool. The thresholds are represented by a power law curve that links the cumulated event rainfall (E, in mm) with the duration of the rainfall event (D, in h). By eliminating all subjective criteria thanks to the automated calculation, thresholds at diverse non-exceedance probabilities are defined and validated, and the uncertainties associated with their parameters are estimated. Additional thresholds are also calculated for two different environmental classifications. The first classification is based on mean annual rainfall (MAR) with the national territory divided into three classes. The area with the highest MAR has the highest thresholds, which indicates a likely adaptation of the landscape to higher amounts of rainfall. The second classification is based on four lithological units. Two-thirds of the considered landslides occur in the unit of any type of clastic sedimentary rocks, which proves an influence of the lithology on the occurrence of shallow landslides. Sedimentary rocks that are prone to weathering have the lowest thresholds, while magmatic and metamorphic rocks have the highest thresholds. Thresholds obtained for both classifications are far less reliable due to the low number of empirical points and can only be used as indicators of rainfall conditions for each of the classes. Finally, the new national thresholds for Slovenia are also compared with other regional, national, and global thresholds. The thresholds can be used to define probabilistic schemes aiming at the operative prediction of rainfall-induced shallow landslides in Slovenia, in the framework of the Slovenian prototype early warning system.
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Vessia, G., M. Parise, M. T. Brunetti, S. Peruccacci, M. Rossi, C. Vennari, and F. Guzzetti. "Automated reconstruction of rainfall events responsible for shallow landslides." Natural Hazards and Earth System Sciences Discussions 2, no. 4 (April 25, 2014): 2869–90. http://dx.doi.org/10.5194/nhessd-2-2869-2014.
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Abstract. Over the last 40 years, many contributions have been devoted to identifying the empirical rainfall thresholds (e.g. intensity vs. duration ID, cumulated rainfall vs. duration ED, cumulated rainfall vs. intensity EI) for the initiation of shallow landslides, based on local as well as worldwide inventories. Although different methods to trace the threshold curves have been proposed and discussed in literature, a systematic study to develop an automated procedure to select the rainfall event responsible for the landslide occurrence has rarely been addressed. Nonetheless, objective criteria for estimating the rainfall responsible for the landslide occurrence (effective rainfall) play a prominent role on the threshold values. In this paper, two criteria for the identification of the effective rainfall events are presented: (1) the first is based on the analysis of the time series of rainfall mean intensity values over one month preceding the landslide occurrence, and (2) the second on the analysis of the trend in the time function of the cumulated mean intensity series calculated from the rainfall records measured through rain gauges. The two criteria have been implemented in an automated procedure written in R language. A sample of 100 shallow landslides collected in Italy by the CNR-IRPI research group from 2002 to 2012 has been used to calibrate the proposed procedure. The cumulated rainfall E and duration D of rainfall events that triggered the documented landslides are calculated through the new procedure and are fitted with power law in the (D,E) diagram. The results are discussed by comparing the (D,E) pairs calculated by the automated procedure and the ones by the expert method.
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Giannecchini, R. "Relationship between rainfall and shallow landslides in the southern Apuan Alps (Italy)." Natural Hazards and Earth System Sciences 6, no. 3 (May 11, 2006): 357–64. http://dx.doi.org/10.5194/nhess-6-357-2006.
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Abstract. The Apuan Alps region is one of the rainiest areas in Italy (more than 3000 mm/year), in which frequently heavy and concentrated rainfall occurs. This is particularly due to its geographical position and conformation: the Apuan chain is located along the northern Tuscan coast, close to the Ligurian Sea, and the main peaks reach almost 2000 m. In several cases, the storms that hit the area have triggered many shallow landslides (soil slip-debris flows), which exposed the population to serious risks (during the 19 June 1996 rainstorm about 1000 landslides were triggered and 14 people died). The assessment of the rainfall thresholds is very important in order to prepare efficient alarm systems in a region particularly dedicated to tourism and marble activities. With the aim of contributing to the landslide hazard evaluation of the southern Apuan Alps territory (upper Versilia area), a detailed analysis of the main pluviometric events was carried out. The data recorded at the main rain gauge of the area from 1975 to 2002 were analysed and compared with the occurrence of soil slips, in order to examine the relationship between soil slip initiation and rainfall. The most important rainstorms which triggered shallow landslides occurred in 1984, 1992, 1994, 1996, 1998 and 2000. Many attempts were made to obtain a possible correlation between rainfall parameters and the occurrence of soil slip phenomena and to identify the local rainfall threshold for triggering shallow landslides. A threshold for soil slip activity in terms of mean intensity, duration and mean annual precipitation (MAP) was defined for the study area. The thresholds obtained for the southern Apuan Alps were also compared with those proposed by other authors for several regions in the world. This emphasized the high value of the rain threshold for shallow landslide activity in the Apuan area. The high threshold is probably also linked to the high mean annual precipitation and to the high frequency of rainstorms.
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Gordo, Cristina, José Luís Zêzere, and Rui Marques. "Landslide Susceptibility Assessment at the Basin Scale for Rainfall- and Earthquake-Triggered Shallow Slides." Geosciences 9, no. 6 (June 20, 2019): 268. http://dx.doi.org/10.3390/geosciences9060268.
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The hydrographic basin of Ribeira Grande (S. Miguel Island, Azores) has a set of characteristics that enhance the occurrence of shallow slides that have been triggered by rainfall and earthquakes. Two landslide inventories were built according to the landslide triggers: Landslide Inventory 2 (LI 2), which includes 174 earthquake-triggered shallow slides occurred in 2005; and Landslide Inventory 1 (LI 1), which includes 442 shallow slides triggered by rainfall in several periods from 2005 to 2016. Both landslide inventories were characterized and compared from the morphometric point of view and were used individually to produce susceptibility models to failure using a simple bivariate state-of-the-art statistical method (the Information Value). The landslide susceptibility Models were validated using success rates, prediction rates, and Kappa statistics. The results show that shallow slides triggered by rainfall and earthquakes in the study area have different morphometric characteristics. It was verified that models produced with LI 1 are very effective in predicting the spatial location of LI 2, but the same does not happen in the inverse situation. Finally, landslide susceptibility models developed with LI 1 and LI 2 for the upper sector of the hydrographic basin (where most landslides occurred), and latter applied to the complete watershed, present more modest predictive results but are more reliable to characterize the landslide susceptibility in the study area.
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Guo, Bin, Xiangjun Pei, Min Xu, and Tiantao Li. "Analyzing Rainfall Threshold for Shallow Landslides Using Physically Based Modeling in Rasuwa District, Nepal." Water 14, no. 24 (December 13, 2022): 4074. http://dx.doi.org/10.3390/w14244074.
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On 25 April 2015, an M7.8 large earthquake happened in Nepal, and 4312 landslides were triggered during or after the earthquake. The 2015 earthquake happened years ago, but the risk of rainfall-induced landslides is still high. Rainfall-induced shallow landslides threaten both human lives and economy development, especially in the Rasuwa area. Due to financial conditions and data availability, a regional-scale rainfall threshold can be an effective method to reduce the risk of shallow landslides. A physically based model was used with limited data. The dynamic hydrological model provides the soil moisture and groundwater change, and the infinite slope stability model produces the factor of safety. Remote sensing data, field investigation, soil sample tests, and literature review were used in the model parameterization. The landslide stability condition of 2016 was simulated. In addition, intensity-antecedent rainfall thresholds were defined based on the physically based modelling output. Sixty groups of data were used for validation, and the 15-day intensity-antecedent rainfall threshold has the best performance with an accuracy of 88.33%.
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Luino, Fabio, Jerome De Graff, Marcella Biddoccu, Francesco Faccini, Michele Freppaz, Anna Roccati, Fabrizio Ungaro, Michele D’Amico, and Laura Turconi. "The Role of Soil Type in Triggering Shallow Landslides in the Alps (Lombardy, Northern Italy)." Land 11, no. 8 (July 22, 2022): 1125. http://dx.doi.org/10.3390/land11081125.
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Shallow landslides due to the soil saturation induced by intense rainfall events are very common in northern Italy, particularly in the Alps and Prealps. They are usually triggered during heavy rainstorms, causing severe damage to property, and sometimes causing casualties. A historical study and analysis of shallow landslides and mud-debris flows triggered by rainfall events in Lombardy was carried out for the period of 1911–2010, over an area of 14,019 km2. In this study, intensity–duration rainfall thresholds have been defined using the frequentist approach, considering some pedological characteristics available in regional soil-related databases, such as the soil region, the textural class, and the dominant soil typological units (STU). The soil-based empirical rainfall thresholds obtained considering the soil regions of the study area were significantly different, with a lower threshold for landslide occurrence in the soil region M1 (Alps), where soils developed over siliceous parent material, with respect to the whole study area and the soil region M2 (Prealps), where soils developed over calcareous bedrocks. Furthermore, by considering textural classes, the curves were differentiated, with coarse-textured soils found more likely to triggerlandslides than fine soils. Finally, considering both texture and main soil groups, given the same rainfall duration, the rainfall amount and intensity needed to initiate a landslide increased in the following order: “coarse-skeletal” Cambisols < Umbrisols < Podzols < “fine” Cambisols. The results of this study highlighted the relevant role of pedological conditioning factors in differentiating the activation of rainfall-induced shallow landslides in a definite region. The information on soils can be used to define more precise rainfall–pedological thresholds than empirical thresholds based solely on meteorological conditions, even when they are locally defined. This knowledge is crucial for forecasting and preventing geo-hydrological processes and in developing better warning strategies to mitigate risks and to reduce socio-economic damage.
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Hadmoko, Danang Sri, Franck Lavigne, Junun Sartohadi, Christopher Gomez, and D. Daryono. "Spatio-Temporal Distribution of Landslides in Java and the Triggering Factors." Forum Geografi 31, no. 1 (July 1, 2017): 1–15. http://dx.doi.org/10.23917/forgeo.v31i1.3790.
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Java Island, the most populated island of Indonesia, is prone to landslide disasters. Their occurrence and impact have increased mainly as the result of natural factors, aggravated by human imprint. This paper is intended to analyse: (1) the spatio-temporal variation of landslides in Java during short term and long-term periods, and (2) their causative factors such as rainfall, topography, geology, earthquakes, and land-use. The evaluation spatially and temporally of historical landslides and consequences were based on the landslide database covering the period of 1981 – 2007 in the GIS environment. Database showed that landslides distributed unevenly between West Java (67 %), Central Java (29 %) and East Java (4 %). Slope failures were most abundant on the very intensively weathered zone of old volcanic materials on slope angles of 30O – 40O. Rainfall threshold analysis showed that shallow landslides and deep-seated landslides were triggered by rainfall events of 300 – 600 mm and > 600 mm respectively of antecedent rainfall during 30 consecutive days, and many cases showed that the landslides were not always initiated by intense rainfall during the landslide day. Human interference plays an important role in landslide occurrence through land conversion from natural forest to dryland agriculture which was the host of most of landslides in Java. These results and methods can be used as valuable information on the spatio-temporal characteristics of landslides in Java and their relationship with causative factors, thereby providing a sound basis for landslide investigation in more detail.
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Ma, Siyuan, Xiaoyi Shao, and Chong Xu. "Characterizing the Distribution Pattern and a Physically Based Susceptibility Assessment of Shallow Landslides Triggered by the 2019 Heavy Rainfall Event in Longchuan County, Guangdong Province, China." Remote Sensing 14, no. 17 (August 29, 2022): 4257. http://dx.doi.org/10.3390/rs14174257.
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Rainfall-induced landslides pose a significant threat to the lives and property of residents in the southeast mountainous and hilly area; hence, characterizing the distribution pattern and effective susceptibility mapping for rainfall-induced landslides are regarded as important and necessary measures to remediate the damage and loss resulting from landslides. From 10 June 2019 to 13 June 2019, continuous heavy rainfall occurred in Longchuan County, Guangdong Province; this event triggered extensive landslide disasters in the villages of Longchuan County. Based on high-resolution satellite images, a landslide inventory of the affected area was compiled, comprising a total of 667 rainfall-induced landslides over an area of 108 km2. These landslides consisted of a large number of shallow landslides with a few flowslides, rockfalls, and debris flows, and the majority of them occurred in Mibei and Yanhua villages. The inventory was used to analyze the distribution pattern of the landslides and their relationship with topographical, geological, and hydrological factors. The results showed that landslide abundance was closely related to slope angle, TWI, and road density. The landslide area density (LAD) increased with the increase in the above three influencing factors and was described by an exponential or linear relationship. In addition, southeast and south aspect hillslopes were more prone to collapse than the northwest–north aspect ones because of the influence of the summer southeast monsoon. A new open-source tool named MAT.TRIGRS(V1.0) was adopted to establish the landslide susceptibility map in landslide abundance areas and to back-analyze the response of the rainfall process to the change in landslide stability. The prediction results were roughly consistent with the actual landslide distribution, and most areas with high susceptibility were located on both sides of the river valley; that is, the areas with relatively steep slopes. The slope stability changes in different periods revealed that the onset of heavy rain on 10 June 2019 was the main triggering factor of these group‑occurring landslides, and the subsequent rainfall with low intensity had little impact on slope stability.
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Schmidt, J., G. Turek, M. P. Clark, M. Uddstrom, and J. R. Dymond. "Probabilistic forecasting of shallow, rainfall-triggered landslides using real-time numerical weather predictions." Natural Hazards and Earth System Sciences 8, no. 2 (April 14, 2008): 349–57. http://dx.doi.org/10.5194/nhess-8-349-2008.
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Abstract. A project established at the National Institute of Water and Atmospheric Research (NIWA) in New Zealand is aimed at developing a prototype of a real-time landslide forecasting system. The objective is to predict temporal changes in landslide probability for shallow, rainfall-triggered landslides, based on quantitative weather forecasts from numerical weather prediction models. Global weather forecasts from the United Kingdom Met Office (MO) Numerical Weather Prediction model (NWP) are coupled with a regional data assimilating NWP model (New Zealand Limited Area Model, NZLAM) to forecast atmospheric variables such as precipitation and temperature up to 48 h ahead for all of New Zealand. The weather forecasts are fed into a hydrologic model to predict development of soil moisture and groundwater levels. The forecasted catchment-scale patterns in soil moisture and soil saturation are then downscaled using topographic indices to predict soil moisture status at the local scale, and an infinite slope stability model is applied to determine the triggering soil water threshold at a local scale. The model uses uncertainty of soil parameters to produce probabilistic forecasts of spatio-temporal landslide occurrence 48~h ahead. The system was evaluated for a damaging landslide event in New Zealand. Comparison with landslide densities estimated from satellite imagery resulted in hit rates of 70–90%.
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Nicolet, P., L. Foresti, O. Caspar, and M. Jaboyedoff. "Shallow landslide's stochastic risk modelling based on the precipitation event of August 2005 in Switzerland: results and implications." Natural Hazards and Earth System Sciences 13, no. 12 (December 9, 2013): 3169–84. http://dx.doi.org/10.5194/nhess-13-3169-2013.
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Abstract. Due to their relatively unpredictable characteristics, shallow landslides represent a risk for human infrastructures. Multiple shallow landslides can be triggered by widespread intense precipitation events. The event of August 2005 in Switzerland is used in order to propose a risk model to predict the expected number of landslides based on the precipitation amounts and lithological units. The spatial distribution of rainfall is characterized by merging data coming from operational weather radars and a dense network of rain gauges with an artificial neural network. Lithologies are grouped into four main units, with similar characteristics. Then, from a landslide inventory containing more than 5000 landslides, a probabilistic relation linking the precipitation amount and the lithology to the number of landslides in a 1 km2 cell, is derived. In a next step, this relation is used to randomly redistribute the landslides using Monte Carlo simulations. The probability for a landslide to reach a building is assessed using stochastic geometry and the damage cost is assessed from the estimated mean damage cost using an exponential distribution to account for the variability. Although the model reproduces well the number of landslides, the number of affected buildings is underestimated. This seems to result from the human influence on landslide occurrence. Such a model might be useful to characterize the risk resulting from shallow landslides and its variability.
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Nicolet, P., L. Foresti, O. Caspar, and M. Jaboyedoff. "Shallow landslides stochastic risk modelling based on the precipitation event of August 2005 in Switzerland: results and implications." Natural Hazards and Earth System Sciences Discussions 1, no. 2 (March 28, 2013): 747–91. http://dx.doi.org/10.5194/nhessd-1-747-2013.
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Abstract. Due to their relatively unpredictable characteristics, shallow-landslides represent a risk for human infrastructures. Multiple shallow-landslides can be triggered by large spread precipitation events. The event of August 2005 in Switzerland is used in order to propose a risk model to predict the expected number of landslides based on the precipitation amounts and lithological units. The spatial distribution of rainfall is characterized by blending data coming from operational weather radars and a dense network of rain gauges with an artificial neural network. Lithologies are grouped into four main units, with similar characteristics. Then, from a landslide inventory containing more than 5000 landslides, a probabilistic relation linking the precipitation amount and the lithology to the number of landslides in a 1 km2 cell, is obtained. In a next step, this relation is used to randomly redistribute the landslides using Monte-Carlo simulations. The probability for a landslide to reach a building is assessed using stochastic geometry and the damage cost is assessed from the estimated mean damage cost using an exponential distribution to account for the variability. Although the outputs reproduce well the number of landslides, the number of affected buildings is not reproduced by the model. This seems to results from the human influence on landslide occurrence. Such a model might be useful to characterize the risk resulting from shallow-landslides and its variability.
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Cullen, Cheila Avalon, Rafea Al Suhili, and Edier Aristizabal. "A Landslide Numerical Factor Derived from CHIRPS for Shallow Rainfall Triggered Landslides in Colombia." Remote Sensing 14, no. 9 (May 7, 2022): 2239. http://dx.doi.org/10.3390/rs14092239.
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Despite great advances in remote sensing technologies, accurate satellite information is sometimes challenged in tropical regions where dense vegetation prevents the instruments from retrieving reliable readings. In this work, we introduce a satellite-based landslide rainfall threshold for the country of Colombia by studying 4 years of rainfall measurements from The Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) for 346 rainfall-triggered landslide events (the dataset). We isolate the two successive rainy/dry periods leading to each landslide to create variables that simulate the dynamics of antecedent wetness and dryness. We test the performance of the derived variables (Rainfall Period 1 (PR1), Rainfall Sum 1 (RS1), Rainfall Period 2 (PR2), Rainfall Sum 2 (RS2), and Dry Period (DT)) in a logistic regression that includes three (3) static parameters (Soil Type (ST), Landcover (LC), and Slope angle). Results from the logistic model describe the influence of each variable in landslide occurrence with an accuracy of 73%. Subsequently, we use these dynamic variables to model a landslide threshold that, in the absence of satellite antecedent soil moisture data, helps describe the interactions between the dynamic variables and the slope angle. We name it the Landslide Triggering Factor—LTF. Subsequently, with a training dataset (65%) and one for testing (35%) we evaluate the LTF threshold performance and compare it to the well-known event duration (E-D) threshold. Results demonstrate that The LTF performs better than the E-D threshold for the training and testing datasets at 71% and 81% respectively.
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Thomas, Juby, Manika Gupta, Prashant K. Srivastava, and George P. Petropoulos. "Assessment of a Dynamic Physically Based Slope Stability Model to Evaluate Timing and Distribution of Rainfall-Induced Shallow Landslides." ISPRS International Journal of Geo-Information 12, no. 3 (March 2, 2023): 105. http://dx.doi.org/10.3390/ijgi12030105.
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Shallow landslides due to hydro-meteorological factors are one of the most common destructive geological processes, which have become more frequent in recent years due to changes in rainfall frequency and intensity. The present study assessed a dynamic, physically based slope stability model, Transient Rainfall Infiltration and Grid-Based Slope Stability Model (TRIGRS), in Idukki district, Kerala, Western Ghats. The study compared the impact of hydrogeomechanical parameters derived from two different data sets, FAO soil texture and regionally available soil texture, on the simulation of the distribution and timing of shallow landslides. For assessing the landslide distribution, 1913 landslides were compared and true positive rates (TPRs) of 68% and 60% were obtained with a nine-day rainfall period for the FAO- and regional-based data sets, respectively. However, a false positive rate (FPR) of 36% and 31% was also seen, respectively. The timing of occurrence of nine landslide events was assessed, which were triggered in the second week of June 2018. Even though the distribution of eight landslides was accurately simulated, the timing of only three events was found to be accurate. The study concludes that the model simulations using parameters derived from either of the soil texture data sets are able to identify the location of the event. However, there is a need for including a high-spatial-resolution hydrogeomechanical parameter data set to improve the timing of landslide event modeling.
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Sarun, S., P. Vineetha, Rajesh Reghunath, A. M. Sheela, and R. Anil Kumar. "Post landslide Investigation of Shallow Landslide: A case study from the Southern Western Ghats, India." Disaster Advances 14, no. 7 (June 25, 2021): 52–59. http://dx.doi.org/10.25303/147da5221.
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Many mountainous regions in the tropics witnessed extreme orographic rainfall episodes in the recent past. The portions of the Western Ghats that fall on the Kerala state also experienced extreme climatic conditions in floods and landslides in 2018 and 2019. More than a thousand small and large landslides occurred during that period in the State's Western Ghats regions. The landslide at Kavalapara in the Malappuram district in 2019 is at the top in the state regarding the causalities, financial loss, and spatial spread. This study is based on a comprehensive field investigation at the Kavalappara landslide site and we developed a detailed landslide susceptibility map with the local community's involvement. The massive landslide covers 0.34 Sq.km (34 hectares) triggered by the unprecedented monsoon rainfall coupled with unsustainable agricultural practices. The area's risk zones have been identified and spatially mapped with the help of a detailed field investigation using Geographic Information System (GIS) and remote sensing technology. The output of the study can be used for the policymakers and planners working in landslide-prone areas.
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Waswa, G. W., and S. A. Lorentz. "A model of landslide triggering by transient pressure waves." Hydrology and Earth System Sciences Discussions 11, no. 2 (February 26, 2014): 2355–90. http://dx.doi.org/10.5194/hessd-11-2355-2014.
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Abstract. Previous studies indicate that most rainfall-triggered shallow landslides are initiated by a spike in rainfall intensity, which does not usually occur at the beginning of a critical storm, within which the slide is triggered, but after several minutes (or hours) of the storm. The critical storm is also usually not positioned at the beginning of a rainfall season, but after several days of antecedent period. Rainfall triggers landslides via rapid increase in pore water pressure, commonly associated with the change in water content. Consequently, many hydrologic pressure wave models assume that rapid pore water pressure responses are as a result of rapid infiltration of rainwater. On the contrary, this paper argues that, based on the above timings of landslide occurrences and the knowledge that infiltration rate decays with the soil wetness, the rapid increase in pore water pressure that triggers shallow landslides is as a result of rapid introduction of additional energy into the tension saturated (or nearly saturated) zone by the intense rainfall at the ground surface, without infiltration. Antecedent and critical precipitations are significant in creating a tension saturated zone, necessary for rapid transmission of the introduced energy from the ground surface to the lower soil horizons during the critical storm. These arguments are supported by a newly proposed one-dimensional diffusion mathematical model, which, when solved for the appropriate boundary conditions, can yield pore water pressure at any time and depth of a tension-saturated soil profile, without infiltration. The newly proposed diffusion model is mathematically similar to Iverson's model (Iverson, 2000), except that the hydraulic diffusivity parameter in the latter is substituted with a newly proposed energy diffusivity coefficient in the former. A combination of the new diffusion model and the infinite slope model can predict the stability of a shallow slope as a result of transient pore water pressure.
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Kuradusenge, Martin, Santhi Kumaran, Marco Zennaro, and Albert Niyonzima. "Experimental Study of Site-Specific Soil Water Content and Rainfall Inducing Shallow Landslides: Case of Gakenke District, Rwanda." Geofluids 2021 (September 8, 2021): 1–18. http://dx.doi.org/10.1155/2021/7194988.
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Shallow landslides are among the natural threats causing death and damage. They are mostly triggered by rainfall in mountainous areas where precipitation used to be abundant. The amount of rainfall inducing this natural threat differs from one site to another based on the geographical characteristics of that area. In addition to the rainfall depth, the determination of soil water content in a specific zone has a major contribution to the landslide prediction and early warning systems. Rwanda being a country with hilly terrains, some areas are susceptible to both rainfall and soil water content inducing landslides. But an analytical study of the physical threshold determination of both rainfall and soil water content inducing landslides is lacking. Therefore, this experimental study is conducted to determine the rainfall and soil water content threshold that can be fed in to the landslide early warning system (LEWS) for alert messages using the Internet of Things (IoT) technology. Various experiments have been conducted for the real-time monitoring of slope failure using the toolset composed of a rain gauge, soil moisture sensors, and a rainfall simulating tool. The results obtained show that the threshold for landslide occurrence does not solely correlate with the total rainfall amount (or intensity) or soil moisture, but also influenced by internal (geological, morphological) and environmental factors. Among the sampled sites, the sites covered by forest indicated no sign of slope failure, whereas sites with crops could slip. The experiments revealed that for a specific site, the minimum duration to induce slope failure was 8 hours, 41 minutes with the rainfall intensity of 8 mm/hour, and the soil moisture was above 90% for deeper sensors. These values are used as thresholds for LEWS for that specific site to improve predictions.
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Zêzere, J. L., R. M. Trigo, M. Fragoso, S. C. Oliveira, and R. A. C. Garcia. "Rainfall-triggered landslides in the Lisbon region over 2006 and relationships with the North Atlantic Oscillation." Natural Hazards and Earth System Sciences 8, no. 3 (May 15, 2008): 483–99. http://dx.doi.org/10.5194/nhess-8-483-2008.
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Abstract. Landslides occurred in the Lisbon area during the last 50 years were almost always induced by rainfall and have been used to establish rainfall thresholds for regional landslide activity. In 2006, three new rainfall-triggered landslide events occurred in the study area, namely on the 20 March, the 25–27 October, and the 28 November. Landslide events occurred in March and October 2006 include shallow translational slides and few debris flows, and the corresponding absolute antecedent rainfall was found to be above the threshold for durations ranging from 4 to 10 days. These events also fit the combined threshold of daily precipitation and 5 days calibrated antecedent rainfall values. Likewise the landslide event that took place in late November 2006 includes some slope movements with deeper slip surfaces, when compared with landslides dating from March and October. Moreover, the corresponding absolute antecedent rainfall was also found to be above the 40-day period rainfall threshold. Here we characterize in detail the short and long-term atmospheric circulation conditions that were responsible for the intense rainfall episodes that have triggered the corresponding landslide events. It is shown that the three rainfall episodes correspond to considerably different synoptic atmospheric patterns, with the March episode being associated to an intense cut-off low system while the October and November episodes appear to be related to more typical Atlantic low pressure systems (and associated fronts) travelling eastwards. Finally, we analyse the role played by the North Atlantic Oscillation (NAO) during those months marked by landslide activity. It is shown that the NAO index was consistently negative (usually associated with above average precipitation) for the months prior to the landslide events, i.e. between October 2005 and March 2006, and again between August and October 2006.
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Schilirò, Luca, José Cepeda, Graziella Devoli, and Luca Piciullo. "Regional Analyses of Rainfall-Induced Landslide Initiation in Upper Gudbrandsdalen (South-Eastern Norway) Using TRIGRS Model." Geosciences 11, no. 1 (January 11, 2021): 35. http://dx.doi.org/10.3390/geosciences11010035.
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In Norway, shallow landslides are generally triggered by intense rainfall and/or snowmelt events. However, the interaction of hydrometeorological processes (e.g., precipitation and snowmelt) acting at different time scales, and the local variations of the terrain conditions (e.g., thickness of the surficial cover) are complex and often unknown. With the aim of better defining the triggering conditions of shallow landslides at a regional scale we used the physically based model TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope stability) in an area located in upper Gudbrandsdalen valley in South-Eastern Norway. We performed numerical simulations to reconstruct two scenarios that triggered many landslides in the study area on 10 June 2011 and 22 May 2013. A large part of the work was dedicated to the parameterization of the numerical model. The initial soil-hydraulic conditions and the spatial variation of the surficial cover thickness have been evaluated applying different methods. To fully evaluate the accuracy of the model, ROC (Receiver Operating Characteristic) curves have been obtained comparing the safety factor maps with the source areas in the two periods of analysis. The results of the numerical simulations show the high susceptibility of the study area to the occurrence of shallow landslides and emphasize the importance of a proper model calibration for improving the reliability.
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Schilirò, Luca, José Cepeda, Graziella Devoli, and Luca Piciullo. "Regional Analyses of Rainfall-Induced Landslide Initiation in Upper Gudbrandsdalen (South-Eastern Norway) Using TRIGRS Model." Geosciences 11, no. 1 (January 11, 2021): 35. http://dx.doi.org/10.3390/geosciences11010035.
Full textAbstract:
In Norway, shallow landslides are generally triggered by intense rainfall and/or snowmelt events. However, the interaction of hydrometeorological processes (e.g., precipitation and snowmelt) acting at different time scales, and the local variations of the terrain conditions (e.g., thickness of the surficial cover) are complex and often unknown. With the aim of better defining the triggering conditions of shallow landslides at a regional scale we used the physically based model TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope stability) in an area located in upper Gudbrandsdalen valley in South-Eastern Norway. We performed numerical simulations to reconstruct two scenarios that triggered many landslides in the study area on 10 June 2011 and 22 May 2013. A large part of the work was dedicated to the parameterization of the numerical model. The initial soil-hydraulic conditions and the spatial variation of the surficial cover thickness have been evaluated applying different methods. To fully evaluate the accuracy of the model, ROC (Receiver Operating Characteristic) curves have been obtained comparing the safety factor maps with the source areas in the two periods of analysis. The results of the numerical simulations show the high susceptibility of the study area to the occurrence of shallow landslides and emphasize the importance of a proper model calibration for improving the reliability.
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Liu, Chia-Nan, and Chia-Chen Wu. "Mapping susceptibility of rainfall-triggered shallow landslides using a probabilistic approach." Environmental Geology 55, no. 4 (October 3, 2007): 907–15. http://dx.doi.org/10.1007/s00254-007-1042-x.
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Lora, M., M. Camporese, P. A. Troch, and P. Salandin. "Rainfall-triggered shallow landslides: infiltration dynamics in a physical hillslope model." Hydrological Processes 30, no. 18 (May 3, 2016): 3239–51. http://dx.doi.org/10.1002/hyp.10829.
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Tsai, Tung-Lin, and Hsin-Fa Chen. "Effects of degree of saturation on shallow landslides triggered by rainfall." Environmental Earth Sciences 59, no. 6 (March 10, 2009): 1285–95. http://dx.doi.org/10.1007/s12665-009-0116-3.
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Comegna, Luca, Emilia Damiano, Roberto Greco, Andrea Guida, Lucio Olivares, and Luciano Picarelli. "Field hydrological monitoring of a sloping shallow pyroclastic deposit." Canadian Geotechnical Journal 53, no. 7 (July 2016): 1125–37. http://dx.doi.org/10.1139/cgj-2015-0344.
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Many mountainous areas in Campania, southern Italy, are characterized by steep slopes covered by unsaturated volcanic deposits. Shallow landslides are frequently triggered by intense and persistent rainfall events, often turning into debris flows that cause huge damage and casualties. Field hydrological monitoring is a useful tool to develop consistent models of slope response to rainfall, in terms of soil suction and moisture, and to define landslide triggering conditions. This is one of the reasons why since 2002 field monitoring is being carried out in Cervinara, around 50 km northeast of Naples. Since October 2009, rainfall height, soil suction and water content at several locations and depths along the slope are automatically being monitored. The data collected help to demonstrate the effectiveness of such a system for better understanding the hydrological processes occurring in similar slopes of Campania, allowing to distinguish between seasonal suction fluctuations, related to long-term meteorological forcing, and short-term response to rainstorms.
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Zieher, Thomas, Martin Rutzinger, Barbara Schneider-Muntau, Frank Perzl, David Leidinger, Herbert Formayer, and Clemens Geitner. "Sensitivity analysis and calibration of a dynamic physically based slope stability model." Natural Hazards and Earth System Sciences 17, no. 6 (June 30, 2017): 971–92. http://dx.doi.org/10.5194/nhess-17-971-2017.
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Abstract. Physically based modelling of slope stability on a catchment scale is still a challenging task. When applying a physically based model on such a scale (1 : 10 000 to 1 : 50 000), parameters with a high impact on the model result should be calibrated to account for (i) the spatial variability of parameter values, (ii) shortcomings of the selected model, (iii) uncertainties of laboratory tests and field measurements or (iv) parameters that cannot be derived experimentally or measured in the field (e.g. calibration constants). While systematic parameter calibration is a common task in hydrological modelling, this is rarely done using physically based slope stability models. In the present study a dynamic, physically based, coupled hydrological–geomechanical slope stability model is calibrated based on a limited number of laboratory tests and a detailed multitemporal shallow landslide inventory covering two landslide-triggering rainfall events in the Laternser valley, Vorarlberg (Austria). Sensitive parameters are identified based on a local one-at-a-time sensitivity analysis. These parameters (hydraulic conductivity, specific storage, angle of internal friction for effective stress, cohesion for effective stress) are systematically sampled and calibrated for a landslide-triggering rainfall event in August 2005. The identified model ensemble, including 25 behavioural model runs with the highest portion of correctly predicted landslides and non-landslides, is then validated with another landslide-triggering rainfall event in May 1999. The identified model ensemble correctly predicts the location and the supposed triggering timing of 73.0 % of the observed landslides triggered in August 2005 and 91.5 % of the observed landslides triggered in May 1999. Results of the model ensemble driven with raised precipitation input reveal a slight increase in areas potentially affected by slope failure. At the same time, the peak run-off increases more markedly, suggesting that precipitation intensities during the investigated landslide-triggering rainfall events were already close to or above the soil's infiltration capacity.
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Giannecchini, R. "Rainfall triggering soil slips in the southern Apuan Alps (Tuscany, Italy)." Advances in Geosciences 2 (February 22, 2005): 21–24. http://dx.doi.org/10.5194/adgeo-2-21-2005.
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Abstract. The Apuan Alps are characterized by frequent heavy rainfall. In several cases this triggered many shallow landslides (soil slips). With the aim of contributing to the landslide hazard evaluation of the southern Apuan Alps (upper Versilian area), a detailed analysis of the main pluviometric events was carried out. Data recorded at the main raingauge of the area from 1975 to 2002 were analysed and compared with the occurrence of soil slips, in order to examine the relationship between soil slip initiation and rainfall. Some thresholds for soil slip-debris flow activity in terms of mean intensity, duration and mean annual precipitation (MAP) were defined for the study area.
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Oakley, N. S., J. T. Lancaster, B. J. Hatchett, J. Stock, F. M. Ralph, S. Roj, and S. Lukashov. "A 22-Year Climatology of Cool Season Hourly Precipitation Thresholds Conducive to Shallow Landslides in California." Earth Interactions 22, no. 14 (July 1, 2018): 1–35. http://dx.doi.org/10.1175/ei-d-17-0029.1.
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Abstract California’s winter storms produce intense rainfall capable of triggering shallow landslides, threatening lives and infrastructure. This study explores where hourly rainfall in the state meets or exceeds published values thought to trigger landslides after crossing a seasonal antecedent precipitation threshold. We answer the following questions: 1) Where in California are overthreshold events most common? 2) How are events distributed within the cool season (October–May) and interannually? 3) Are these events related to atmospheric rivers? To do this, we compile and quality control hourly precipitation data over a 22-yr period for 147 Remote Automated Weather Stations (RAWS). Stations in the Transverse and Coast Ranges and portions of the northwestern Sierra Nevada have the greatest number of rainfall events exceeding thresholds. Atmospheric rivers coincide with 60%–90% of these events. Overthreshold events tend to occur in the climatological wettest month of the year, and they commonly occur multiple times within a storm. These statewide maps depict where to expect intense rainfalls that have historically triggered shallow landslides. They predict that some areas of California are less susceptible to storm-driven landslides solely because high-intensity rainfall is unlikely.
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Ubaidulloev, Akmal, Hu Kaiheng, Manuchekhr Rustamov, and Makhvash Kurbanova. "Landslide Inventory along a National Highway Corridor in the Hissar-Allay Mountains, Central Tajikistan." GeoHazards 2, no. 3 (August 9, 2021): 212–27. http://dx.doi.org/10.3390/geohazards2030012.
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An increasing amount of landslides leading to significant human and economic consequences is a primary concern for the government of Tajikistan and local authorities. Based on the Committee on Emergency Situations data, from 1996 to 2018, there were 3460 emergencies and more than 1000 fatalities because of earthquake-triggered and rainfall-induced landslides in the region. In addition, landslides caused severe damage to houses and infrastructure facilities due to the population’s lack of landslide hazard knowledge. Therefore, current research focuses on developing a regional-scale landslide inventory map in the Hissar–Allay region, central Tajikistan, where the population density is much higher than at other mountainous territories. In recent decades, the enhancements in geographic information systems, the open access to high-resolution remote sensing data, and an extensive field survey allowed us to identify 922 landslides possible along the highway corridor in the Hissar–Allay region. Based on Varnes’s system, these landslides are classified into four categories: debris flows, rockfalls, shallow landslides, and complex (deep-seated) landslides, considering landslides morphology, geology, deformation of slopes, degree and aspect of slopes, and weathered and disintegrated zones on slopes in the study area. The results show that 8.24% of the total study area is affected by landslides. Along the highway corridor in the Hissar–Allay region there are 96 bodies of deep-seated landslides and 216 rockfall catchments, 273 debris flow catchments, and 313 shallow landslides. Thus, shallow landslides are the most frequent type of movement. In addition, landslide frequency-area distribution analysis shows that shallow landslides are frequent with an area of 1.88E+04 m2; most frequent debris flow channels have a place of 5.58E+05 m2; rockfalls, for its part, are rife with an area of 1.50E+05 m2, and frequent complex landslides have an area of 4.70E+06 m2. Furthermore, it was found out that slopes consist of Silurian formation comprise shales, pebbles, sands, loams, and limestones, metamorphic clays are exposed to landslides more than other geological formations because of the layered structure and their broad spatial distribution in the study area. As the first applied research to compile a landslide inventory map in the Hissar–Allay region on the regional scale, our study provides a sound basis for future explorations of landslide susceptibility, hazard, and risk assessment for this region.
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Bessette-Kirton, Erin K., Jeffrey A. Coe, William H. Schulz, Corina Cerovski-Darriau, and Mason M. Einbund. "Mobility characteristics of debris slides and flows triggered by Hurricane Maria in Puerto Rico." Landslides 17, no. 12 (June 30, 2020): 2795–809. http://dx.doi.org/10.1007/s10346-020-01445-z.
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Abstract Mobility is an important element of landslide hazard and risk assessments yet has been seldom studied for shallow landslides and debris flows in tropical environments. In September 2017, Hurricane Maria triggered > 70,000 landslides across Puerto Rico. Using aerial imagery and a lidar digital elevation model (DEM), we mapped and characterized the mobility of debris slides and flows in four different geologic materials: (1) mudstone, siltstone, and sandstone; (2) submarine basalt and chert; (3) marine volcaniclastics; and (4) granodiorite. We used the ratio of landslide-fall height (H) to travel length (L), H/L, to assess the mobility of landslides in each material. Additionally, we differentiated between landslides with single and multiple source areas and landslides that either did or did not enter drainages. Overall, extreme rainfall contributed to the mobility of landslides during Hurricane Maria, and our results showed that the mobility of debris slides and flows in Puerto Rico increased linearly as a function of the number of source areas that coalesced. Additionally, landslides that entered drainages were more mobile than those that did not. We found that landslides in soils developed on marine volcaniclastics were the most mobile and landslides in soils on submarine basalt and chert were the least mobile. While landslides were generally small (< 100 m2) and displayed a wide range of H/L values (0.1–2), coalescence increased the mobility of landslides that transitioned to debris flows. The high but variable mobility of landslides that occurred during Hurricane Maria and the associated hazards highlight the importance of characterizing and understanding the factors influencing landslide mobility in Puerto Rico and other tropical environments.
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Pepe, Mandarino, Raso, Scarpellini, Brandolini, and Cevasco. "Investigation on Farmland Abandonment of Terraced Slopes Using Multitemporal Data Sources Comparison and Its Implication on Hydro-Geomorphological Processes." Water 11, no. 8 (July 26, 2019): 1552. http://dx.doi.org/10.3390/w11081552.
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This paper presents a quantitative multi-temporal analysis performed in a GIS environment and based on different spatial information sources. The research is aimed at investigating the land use transformations that occurred in a small coastal terraced basin of Eastern Liguria from the early 1950s to 2011. The degree of abandonment of cultivated terraced slopes together with its influence on the distribution, abundance, and magnitude of rainfall-induced shallow landslides were accurately analysed. The analysis showed that a large portion of terraced area (77.4%) has been abandoned over approximately sixty years. This land use transformation has played a crucial role in influencing the hydro-geomorphological processes triggered by a very intense rainstorm that occurred in 2011. The outcomes of the analysis revealed that terraces abandoned for a short time showed the highest landslide susceptibility and that slope failures affecting cultivated zones were characterized by a lower magnitude than those which occurred on abandoned terraced slopes. Furthermore, this study highlights the usefulness of cadastral data in understanding the impact of rainfall-induced landslides due to both a high spatial and thematic accuracy. The obtained results represent a solid basis for the investigation of erosion and the shallow landslide susceptibility of terraced slopes by means of a simulation of land use change scenarios.
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Szabó, J. "The relationship between landslide activity and weather: examples from Hungary." Natural Hazards and Earth System Sciences 3, no. 1/2 (April 30, 2003): 43–52. http://dx.doi.org/10.5194/nhess-3-43-2003.
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Abstract. The paper presents the impact of irregular rainfall events triggering landslides in the regional context of landslides in Hungary. The author’s experience, gathered from decades of observations, confirms that landslide processes are strongly correlate with precipitation events in all three landscape types (hill regions of unconsolidated sediments; high bluffs along river banks and lake shores; mountains of Tertiary stratovolcanoes). Case studies for each landscape type underline that new landslides are triggered and old ones are reactivated by extreme winter precipitation events. This assertion is valid mainly for shallow and translational slides. Wet autumns favour landsliding, while the triggering influence of intense summer rainfalls is of a subordinate nature. A recent increasing problem lies in the fact that on previously unstable slopes, stabilised during longer dry intervals, an intensive cultivation starts, thus increasing the damage caused by movements during relatively infrequent wet winters.
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Zêzere, J. L., E. Reis, R. Garcia, S. Oliveira, M. L. Rodrigues, G. Vieira, and A. B. Ferreira. "Integration of spatial and temporal data for the definition of different landslide hazard scenarios in the area north of Lisbon (Portugal)." Natural Hazards and Earth System Sciences 4, no. 1 (March 9, 2004): 133–46. http://dx.doi.org/10.5194/nhess-4-133-2004.
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Abstract. A general methodology for the probabilistic evaluation of landslide hazard is applied, taking in account both the landslide susceptibility and the instability triggering factors, mainly rainfall. The method is applied in the Fanhões-Trancão test site (north of Lisbon, Portugal) where 100 shallow translational slides were mapped and integrated into a GIS database. For the landslide susceptibility assessment it is assumed that future landslides can be predicted by statistical relationships between past landslides and the spatial data set of the predisposing factors (slope angle, slope aspect, transversal slope profile, lithology, superficial deposits, geomorphology, and land use). Susceptibility is evaluated using algorithms based on statistical/probabilistic analysis (Bayesian model) over unique-condition terrain units in a raster basis. The landslide susceptibility map is prepared by sorting all pixels according to the pixel susceptibility value in descending order. In order to validate the results of the susceptibility ana- lysis, the landslide data set is divided in two parts, using a temporal criterion. The first subset is used for obtaining a prediction image and the second subset is compared with the prediction results for validation. The obtained prediction-rate curve is used for the quantitative interpretation of the initial susceptibility map. Landslides in the study area are triggered by rainfall. The integration of triggering information in hazard assessment includes (i) the definition of thresholds of rainfall (quantity-duration) responsible for past landslide events; (ii) the calculation of the relevant return periods; (iii) the assumption that the same rainfall patterns (quantity/duration) which produced slope instability in the past will produce the same effects in the future (i.e. same types of landslides and same total affected area). The landslide hazard is present as the probability of each pixel to be affected by a slope movement, and results from the coupling between the susceptibility map, the prediction-rate curve, and the return periods of critical rainfall events, on a scenario basis. Using this methodology, different hazard scenarios were assessed, corresponding to different rain paths with different return periods.
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Frattini, Paolo, Giovanni Crosta, and Rosanna Sosio. "Approaches for defining thresholds and return periods for rainfall-triggered shallow landslides." Hydrological Processes 23, no. 10 (May 15, 2009): 1444–60. http://dx.doi.org/10.1002/hyp.7269.
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Talebi, A., R. Uijlenhoet, and P. A. Troch. "Application of a probabilistic model of rainfall-induced shallow landslides to complex hollows." Natural Hazards and Earth System Sciences 8, no. 4 (July 23, 2008): 733–44. http://dx.doi.org/10.5194/nhess-8-733-2008.
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Abstract. Recently, D'Odorico and Fagherazzi (2003) proposed "A probabilistic model of rainfall-triggered shallow landslides in hollows" (Water Resour. Res., 39, 2003). Their model describes the long-term evolution of colluvial deposits through a probabilistic soil mass balance at a point. Further building blocks of the model are: an infinite-slope stability analysis; a steady-state kinematic wave model (KW) of hollow groundwater hydrology; and a statistical model relating intensity, duration, and frequency of extreme precipitation. Here we extend the work of D'Odorico and Fagherazzi (2003) by incorporating a more realistic description of hollow hydrology (hillslope storage Boussinesq model, HSB) such that this model can also be applied to more gentle slopes and hollows with different plan shapes. We show that results obtained using the KW and HSB models are significantly different as in the KW model the diffusion term is ignored. We generalize our results by examining the stability of several hollow types with different plan shapes (different convergence degree). For each hollow type, the minimum value of the landslide-triggering saturated depth corresponding to the triggering precipitation (critical recharge rate) is computed for steep and gentle hollows. Long term analysis of shallow landslides by the presented model illustrates that all hollows show a quite different behavior from the stability view point. In hollows with more convergence, landslide occurrence is limited by the supply of deposits (supply limited regime) or rainfall events (event limited regime) while hollows with low convergence degree are unconditionally stable regardless of the soil thickness or rainfall intensity. Overall, our results show that in addition to the effect of slope angle, plan shape (convergence degree) also controls the subsurface flow and this process affects the probability distribution of landslide occurrence in different hollows. Finally, we conclude that incorporating a more realistic description of hollow hydrology (instead of the KW model) in landslide probability models is necessary, especially for hollows with high convergence degree which are more susceptible to landsliding.
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Kubwimana, Désiré, Lahsen Ait Brahim, Pascal Nkurunziza, Antoine Dille, Arthur Depicker, Louis Nahimana, Abdellah Abdelouafi, and Olivier Dewitte. "Characteristics and Distribution of Landslides in the Populated Hillslopes of Bujumbura, Burundi." Geosciences 11, no. 6 (June 17, 2021): 259. http://dx.doi.org/10.3390/geosciences11060259.
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Accurate and detailed multitemporal inventories of landslides and their process characterization are crucial for the evaluation of landslide hazards and the implementation of disaster risk reduction strategies in densely-populated mountainous regions. Such investigations are, however, rare in many regions of the tropical African highlands, where landslide research is often in its infancy and not adapted to the local needs. Here, we have produced a comprehensive multitemporal investigation of the landslide processes in the hillslopes of Bujumbura, situated in the landslide-prone East African Rift. We inventoried more than 1200 landslides by combining careful field investigation and visual analysis of satellite images, very-high-resolution topographic data, and historical aerial photographs. More than 20% of the hillslopes of the city are affected by landslides. Recent landslides (post-1950s) are mostly shallow, triggered by rainfall, and located on the steepest slopes. The presence of roads and river quarrying can also control their occurrence. Deep-seated landslides typically concentrate in landscapes that have been rejuvenated through knickpoint retreat. The difference in size distributions between old and recent deep-seated landslides suggests the long-term influence of potentially changing slope-failure drivers. Of the deep-seated landslides, 66% are currently active, those being mostly earthflows connected to the river system. Gully systems causing landslides are commonly associated with the urbanization of the hillslopes. Our results provide a much more accurate record of landslide processes and their impacts in the region than was previously available. These insights will be useful for land management and disaster risk reduction strategies.
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Deng, Rilang, Huifen Liu, Xianchang Zheng, Qinghua Zhang, Wei Liu, and Lingwei Chen. "Towards Establishing Empirical Rainfall Thresholds for Shallow Landslides in Guangzhou, Guangdong Province, China." Water 14, no. 23 (December 1, 2022): 3914. http://dx.doi.org/10.3390/w14233914.
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Empirical rainfall thresholds for predicting rainfall-triggered shallow landslides are proposed for Guangzhou city, which is prone to widespread geological hazards during the annual flood season due to the subtropical monsoon climate and frequent tropical storms and typhoons. In this study, the cumulated event rainfall (E, in mm), the duration of rainfall event (D, in day) (E–D) thresholds, normalized cumulated event rainfall, and the duration of rainfall event (EMAP–D) thresholds were defined. Thresholds based on five lithological units were obtained at 5%, 20%, and 50% probability levels using quantile regression methods. More than two-thirds of the landslides occurred within units of intrusive rock. The 20-day cumulative rainfall of 97 mm integrating cumulative event rainfall and the duration of rainfall events (CED) is introduced into the three-dimensional spatial threshold. The areas under the receiver operating characteristic curves for the CED threshold and E–D threshold were 0.944 and 0.914, respectively, and the true-positive rate of the CED threshold with the same probability level was slightly lower than that of the E–D threshold, but the CED threshold false-positive rate was much better than the E–D threshold, which can significantly reduce false alarm rate since many non-triggering rainfalls were filtered out.
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D’Ippolito, Antonino, Valeria Lupiano, Valeria Rago, Oreste G. Terranova, and Giulio Iovine. "Triggering of Rain-Induced Landslides, with Applications in Southern Italy." Water 15, no. 2 (January 9, 2023): 277. http://dx.doi.org/10.3390/w15020277.
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Landslides cause fatalities, widespread damages and economic losses. Quite frequently, they are triggered by rainfall. Many studies have investigated the relationships between rainfall characteristics and landslide events. This paper reviews the two main approaches, physical and hydrological, for modelling such relationships. In the physical approach, the influence of rainfall on slope stability is commonly analysed in terms of groundwater infiltration, pore pressure changes and balance between shear stresses and resistances, therefore a considerable amount of hydrogeological, morphological and geotechnical data is required. In the hydrological approach, a statistical-probabilistic study of rainfall series and dates of occurrence of slope movements is instead carried out. Both types of methods are briefly presented, with examples from real applications to study cases in Southern Italy. In particular, the recent reactivations of a large rockslide in Northern Calabria have been modelled by means of physical and hydrological approaches. In addition, shallow landslides in Calabria, Campania and Sicily have been modelled by employing hydrological approaches. Strengths and weaknesses of the adopted methods are discussed, together with the causes that may have hindered better results for the considered cases. For the methods illustrated through real application cases, research perspectives are discussed, as well as their possible use in early warning systems.
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Rickli, Christian, Frank Graf, Peter Bebi, Alexander Bast, Bernard Loup, and Brian McArdell. "Schützt der Wald vor Rutschungen? Hinweise aus der WSL-Rutschungsdatenbank." Schweizerische Zeitschrift fur Forstwesen 170, no. 6 (December 1, 2019): 310–17. http://dx.doi.org/10.3188/szf.2019.0310.
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Does the forest provide protection from landslides? Evidence from the WSL Shallow Landslide Database During strong rainfall events, shallow landslides and debris avalanches (hillslope debris flows, or open-slope debris flows) are triggered and sometimes lead to considerable damage. Analysis of damage-causing events show that there are fewer landslides in forested areas compared to non-forested areas, which indicates the generally positive influence of forest vegetation on slope stability. However, these effects depend on the condition of the forest stand and quantification of the effects is difficult. Event documentation contributes to a better understanding of the relevant processes. The information obtained is not only important for the preparation of hazard maps, but also provides valuable insight for assessing the hazard protection provided by the forest. Data from the landslide database of the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) were used to evaluate the influence of the forest on slope stability. Currently, the database contains information on 734 landslides. Of these, 661 were included in the evaluation – 356 landslides in non-forested areas and 305 in forested areas. In areas with slope angles up to 38°, more landslides per unit area are observed in non-forested areas than in forested areas. In areas with steeper slope angles a stabilizing effect of the forest is no longer recognizable. Statistical analyses show that landslides in forested areas are smaller than in non-forested areas and are more frequent on steeper slopes. In general, the landslides become smaller with increasing slope. Multivariate analyses indicate a positive influence of the forest and also somewhat smaller landslides in well-developed forests. Negative effects are evident in non-forested areas and in areas with overly dense forests. In addition to illustrating the importance of the forest condition for slope stability, the paper also discusses how the forest condition can be described.
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Rault, Claire, Alexandra Robert, Odin Marc, Niels Hovius, and Patrick Meunier. "Seismic and geologic controls on spatial clustering of landslides in three large earthquakes." Earth Surface Dynamics 7, no. 3 (September 2, 2019): 829–39. http://dx.doi.org/10.5194/esurf-7-829-2019.
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Abstract. The large, shallow earthquakes at Northridge, California (1994), Chi-Chi, Taiwan (1999), and Wenchuan, China (2008), each triggered thousands of landslides. We have determined the position of these landslides along hillslopes, normalizing for statistical bias. The landslide patterns have a co-seismic signature, with clustering at ridge crests and slope toes. A cross-check against rainfall-induced landslide inventories seems to confirm that crest clustering is specific to seismic triggering as observed in previous studies. In our three study areas, the seismic ground motion parameters and lithologic and topographic features used do not seem to exert a primary control on the observed patterns of landslide clustering. However, we show that at the scale of the epicentral area, crest and toe clustering occur in areas with specific geological features. Toe clustering of seismically induced landslides tends to occur along regional major faults. Crest clustering is concentrated at sites where the lithology along hillslopes is approximately uniform, or made of alternating soft and hard strata, and without strong overprint of geological structures. Although earthquake-induced landslides locate higher on hillslopes in a statistically significant way, geological features strongly modulate the landslide position along the hillslopes. As a result the observation of landslide clustering on topographic ridges cannot be used as a definite indicator of the topographic amplification of ground shaking.
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Martino, Salvatore, Gian Marco Marmoni, Matteo Fiorucci, Antonio Francesco Ceci, Marco Emanuele Discenza, Javad Rouhi, and Davit Tedoradze. "Role of Antecedent Rainfall in the Earthquake-Triggered Shallow Landslides Involving Unsaturated Slope Covers." Applied Sciences 12, no. 6 (March 12, 2022): 2917. http://dx.doi.org/10.3390/app12062917.
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Different soil cover saturation has a significant effect in influencing slope stability conditions of weathered covers under earthquake-induced shaking. Here we analyze the Montecilfone, Italy (2018), case history, an Mw 5.1 earthquake that revealed an exceptionality in the spatial distribution of the surveyed earthquake-induced shallow landslides. This feature can be justified as intense rainfall occurred in the epicentral area before the seismic event, contributing to increasing the saturation and the weight of the soil covers. To verify the effective influence of antecedent rainfall as a preparatory factor in the earthquake triggering of soil covers, stability conditions for both static and dynamic scenarios were validated by reconstructing different saturation conditions related to a rainfall event that occurred before the earthquake. Soil cover surveying was performed within a 150 km2 area to output its spatial distribution in terms of their compositional features and thickness, whose variability was constrained through empirical models. Based on laboratory test results, 1D infiltration numerical models were performed through the Hydrus-1D free domain software to estimate the saturation degree of the soil cover and the water infiltration depth, taking as a reference the intensity of the rainfall event. Soil cover sequential charts of water content were obtained at different depths and times up to those recorded at the time of earthquake occurrence by the performed numerical modelling. Safety factors (SFs) of the slope covers were quantified assuming an unsaturated condition in the slope stability equation. The outputs reveal that pore pressure spatial distribution in the unsaturated medium infers on the earthquake-induced scenario of shallow landsliding, demonstrating its role as a preparatory factor for earthquake-induced shallow landslides.
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Borrelli, Luigi, Gino Cofone, Roberto Coscarelli, and Giovanni Gullà. "Shallow landslides triggered by consecutive rainfall events at Catanzaro strait (Calabria–Southern Italy)." Journal of Maps 11, no. 5 (August 8, 2014): 730–44. http://dx.doi.org/10.1080/17445647.2014.943814.
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Lee, C. T., C. C. Huang, J. F. Lee, K. L. Pan, M. L. Lin, and J. J. Dong. "Statistical approach to storm event-induced landslides susceptibility." Natural Hazards and Earth System Sciences 8, no. 4 (August 29, 2008): 941–60. http://dx.doi.org/10.5194/nhess-8-941-2008.
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Abstract. For the interpretation of the storm event-induced landslide distribution for an area, deterministic methods are frequently used, while a region's landslide susceptibility is commonly predicted via a statistical approach based upon multi-temporal landslide inventories and environmental factors. In this study we try to use an event-based landslide inventory, a set of environmental variables and a triggering factor to build a susceptibility model for a region which is solved using a multivariate statistical method. Data for shallow landslides triggered by the 2002 typhoon, Toraji, in central western Taiwan, are selected for training the susceptibility model. The maximum rainfall intensity of the storm event is found to be an effective triggering factor affecting the landslide distribution and this is used in the model. The model is built for the Kuohsing region and validated using data from the neighboring Tungshih area and a subsequent storm event – the 2004 typhoon, Mindulle, which affected both the Kuohsing and the Tungshih areas. The results show that we can accurately interpret the landslide distribution in the study area and predict the occurrence of landslides in the neighboring region in a subsequent typhoon event. The advantage of this statistical method is that neither hydrological data, strength data, failure depth, nor a long-period landslide inventory is needed as input.
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Coviello, Velio, Lucia Capra, Gianluca Norini, Norma Dávila, Dolors Ferrés, Víctor Hugo Márquez-Ramírez, and Eduard Pico. "Earthquake-induced debris flows at Popocatépetl Volcano, Mexico." Earth Surface Dynamics 9, no. 3 (May 21, 2021): 393–412. http://dx.doi.org/10.5194/esurf-9-393-2021.
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Abstract. The 2017 Mw 7.1 Puebla–Morelos intraslab earthquake (depth: 57 km) severely hit Popocatépetl Volcano, located ∼ 70 km north of the epicenter. The seismic shaking triggered shallow landslides on the volcanic edifice, mobilizing slope material saturated by the 3 d antecedent rainfall. We produced a landslide map based on a semi-automatic classification of a 50 cm resolution optical image acquired 2 months after the earthquake. We identified hundreds of soil slips and three large debris flows for a total affected area of 3.8 km2. Landslide distribution appears controlled by the joint effect of slope material properties and topographic amplification. In most cases, the sliding surfaces correspond with discontinuities between pumice-fall and massive ash-fall deposits from late Holocene eruptions. The largest landslides occurred on the slopes of aligned ENE–WSW-trending ravines, on opposite sides of the volcano, roughly parallel to the regional maximum horizontal stress and to volcano-tectonic structural features. This suggests transient reactivation of local faults and extensional fractures as one of the mechanisms that weakened the volcanic edifice and promoted the largest slope failures. The material involved in the larger landslides transformed into three large debris flows due to liquefaction. These debris flows mobilized a total volume of about 106 m3 of material also including large wood, were highly viscous, and propagated up to 7.7 km from the initiation areas. We reconstructed this mass wasting cascade by means of field evidence, samples from both landslide scarps and deposits, and analysis of remotely sensed and rainfall data. Although subduction-related earthquakes are known to produce a smaller number of landslides than shallow crustal earthquakes, the processes described here show how an unusual intraslab earthquake can produce an exceptional impact on an active volcano. This scenario, not related to the magmatic activity of the volcano, should be considered in multi-hazard risk assessment at Popocatépetl and other active volcanoes located along volcanic arcs.
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Palacio Cordoba, Johnnatan, Martin Mergili, and Edier Aristizábal. "Probabilistic landslide susceptibility analysis in tropical mountainous terrain using the physically based r.slope.stability model." Natural Hazards and Earth System Sciences 20, no. 3 (March 24, 2020): 815–29. http://dx.doi.org/10.5194/nhess-20-815-2020.
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Abstract. Landslides triggered by rainfall are very common phenomena in complex tropical environments such as the Colombian Andes, one of the regions of South America most affected by landslides every year. Currently in Colombia, physically based methods for landslide hazard mapping are mandatory for land use planning in urban areas. In this work, we perform probabilistic analyses with r.slope.stability, a spatially distributed, physically based model for landslide susceptibility analysis, available as an open-source tool coupled to GRASS GIS. This model considers alternatively the infinite slope stability model or the 2.5-D geometry of shallow planar and deep-seated landslides with ellipsoidal or truncated failure surfaces. We test the model in the La Arenosa catchment, northern Colombian Andes. The results are compared to those yielded with the corresponding deterministic analyses and with other physically based models applied in the same catchment. Finally, the model results are evaluated against a landslide inventory using a confusion matrix and receiver operating characteristic (ROC) analysis. The model performs reasonably well, the infinite slope stability model showing a better performance. The outcomes are, however, rather conservative, pointing to possible challenges with regard to the geotechnical and geo-hydraulic parameterization. The results also highlight the importance to perform probabilistic instead of – or in addition to – deterministic slope stability analyses.
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Bellugi, Dino G., David G. Milledge, Kurt M. Cuffey, William E. Dietrich, and Laurel G. Larsen. "Controls on the size distributions of shallow landslides." Proceedings of the National Academy of Sciences 118, no. 9 (February 26, 2021): e2021855118. http://dx.doi.org/10.1073/pnas.2021855118.
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Rainfall-triggered shallow landslides are destructive hazards and play an important role in landscape processes. A theory explaining the size distributions of such features remains elusive. Prior work connects size distributions to topography, but field-mapped inventories reveal pronounced similarities in the form, mode, and spread of distributions from diverse landscapes. We analyze nearly identical distributions occurring in the Oregon Coast Range and the English Lake District, two regions of strikingly different topography, lithology, and vegetation. Similarity in minimum sizes at these sites is partly explained by theory that accounts for the interplay of mechanical soil strength controls resisting failure. Maximum sizes, however, are not explained by current theory. We develop a generalized framework to account for the entire size distribution by unifying a mechanistic slope stability model with a flexible spatial-statistical description for the variability of hillslope strength. Using hillslope-scale numerical experiments, we find that landslides can occur not only in individual low strength areas but also across multiple smaller patches that coalesce. We show that reproducing observed size distributions requires spatial strength variations to be strongly localized, of large amplitude, and a consequence of multiple interacting factors. Such constraints can act together with the mechanical determinants of landslide initiation to produce size distributions of broadly similar character in widely different landscapes, as found in our examples. We propose that size distributions reflect the systematic scale dependence of the spatially averaged strength. Our results highlight the critical need to constrain the form, amplitude, and wavelength of spatial variability in material strength properties of hillslopes.