Topographical features of rainfall-triggered landslides in Mon State,Myanmar, August 2019: spatial distribution heterogeneity and uncommon large relative heights

Continuous 5-day (August 4–9, 2019) torrential rainfall in the monsoon season triggered more than 90 landslides on northwest-southeast extended mountain range of Mon State, Myanmar. In this study, remote sensing images, DEM, and limited fieldworks were used to create the landslide inventory. The topography features of these landslides are analyzed via ArcGIS. The largest one occurred on 9 August 2019 and caused 75 deaths and 27 buildings were damaged. This landslide occurred on gentle topography (slope angle, 23°) with long run-out, in which the angle of reach was relatively low (10°). The volume was 111,878 m³ was mainly composed of weathered granite and red soil and the sliding depth was approximately 7.5 m. Topographic characteristics including the relative slope height, angle of reach, and slope angle of source area of 35 landslides with areas?>?4000 m² were analyzed. The spatial distribution characteristics and topographic features of the 35 landslides below are distinguished: (1) the concentration of most of landslides on southwest-facing slopes showing the heterogeneous spatial distribution of landslide; (2) an uncommon landslide distribution in which more than half of landslide originates from upper slope; (3) the range of the angle of the source area (17°–38°) compatible with the internal friction angle of soils in tropical regions (17°–33°); and (4) the tangent of the angle of reach is generally smaller than 0.5 (angle of reach?<?27°) shows a relative high mobility and the relation between landslide mobility and the slope angle of the landslide source area is similar to the one of earthquake-triggered landslides, even though the triggering mechanism, landslide type, and landslide volume are dramatically different.

     

Effects of strong ground motion on the susceptibility of gully type debris flows

Typhoon Herb in 1996 caused widespread debris flows in central Taiwan. The 7.3 Chi-Chi earthquake on September 21, 1999, which also took place in central Taiwan, induced many landslides in the region. These landslides turned into debris flows when Typhoon Toraji struck Taiwan in 2001. This research selects three regions which suffered a ground motion class of 5, 6, and 7 on the Richter scale during the Chi-Chi earthquake as study areas. Air photos from 1997 and 2001 of these regions are used to map the gully-type debris flows that took place after Typhoons Herb and Toraji, respectively. The gullies adjacent to the debris flow, but without a trace of debris flows, are also mapped as the non-debris flow data. The topography, hydrogeology, and rainfall factors – where debris flow occurred and in which there was no occurrence of debris flows in these gullies were retrieved from DTM, geological maps, and iso-countour maps, and of rainfall through GIS processing. These characteristic are introduced into a probabilistic neural network to build a predicting model for the probability of the occurrence of debris flows. Three series of cross analyses are conducted to compare the probability of the occurrence of debris flows of the same dataset predicted by different prediction models. The results reveal that the susceptibility of debris flows was elevated after the Chi-Chi earthquake struck. The upsurge of susceptibility was more obvious for the regions that received a higher class of ground motion.     

The Hungtsaiping landslides: from ancient to recent

A large and deep-seated landslide at Hungtsaiping was triggered by the 1999 Chi-Chi earthquake with the magnitude of 7.3. Extensive site investigations for the landslide were conducted including field reconnaissance, geophysical exploration, borehole logs, and laboratory experiments. Thick colluvium was found around the landslide area and indicated the occurrence of a large ancient landslide. The Hungtsaiping area involves at least two large landslides events, an ancient rockslide and the 1999 colluvium slide. With the consideration of a source collapse mass, the two landslides in sequence are reasonably reproduced by the distinct element modeling. The modeling is calibrated by rock mass strength behavior through a procedure with the Hoek?CBrown failure criterion, statistical experimental design, and optimization techniques. The mechanism of the 1999 landslide that cannot be revealed by the underground exploration data alone is clarified. The proposed procedure enables a rational and efficient way to determine micro-parameters for the distinct element modeling of landslides.     

Deriving landslide dam geometry from remote sensing images for the rapid assessment of critical parameters related to dam-breach hazards

Dam-breaches that cause outburst floods may induce downstream hazards. Because landslide dams can breach soon after they are formed, it is critical to assess the stability quickly to enable prompt action. However, dam geometry, an essential component of hazard evaluation, is not available in most cases. Our research proposes a procedure that utilizes post-landslide orthorectified remote sensing images and the pre-landslide Digital Terrain Model in the Geographic Information System to estimate the geometry of a particular dam. The procedure includes the following three modules: (1) the selection of the reference points on the dam and lake boundaries, (2) the interpolation of the dam-crest elevation, and (3) the estimation of dam-geometry parameters (i.e., the height, length, and width), the catchment area, the volumes of barrier lake and landslides dam. This procedure is demonstrated through a case study of the Namasha Landslide Dam in Taiwan. It was shown the dam-surface elevation estimated from the proposed procedure can approximate the elevation derived from profile leveling after the formation of the landslide dam. Thus, it is feasible to assess the critical parameters required for the landslide dam hazard assessment rapidly once the ortho-photo data are available. The proposed procedure is useful for quick and efficient decision making regarding hazard mitigation.     

Statistical approach to earthquake-induced landslide susceptibility

Susceptibility analysis for predicting earthquake-induced landslides has most frequently been done using deterministic methods; multivariate statistical methods have not previously been applied. In this study, however, we introduce a statistical methodology that uses the intensity of earthquake shaking as a landslide triggering factor. This methodology is applied in a study of shallow earthquake-induced landslides in central western Taiwan. The results show that we can accurately interpret landslide distribution in the study area and predict the occurrence of landslides in neighboring regions. This susceptibility model is capable of predicting shallow landslides induced during an earthquake scenario with similar range of ground shaking, without requiring the use of geotechnical, groundwater or failure depth data.     

A systematic approach for the assessment of flooding hazard and risk associated with a landslide dam

Inundation caused by landslide dams may occur in the upstream and downstream of the dams. A proper flooding hazard assessment is required for reaction planning and decision-making to mitigate possible flooding hazards caused by landslide dams. Both quick and detailed procedures can be used to evaluate inundation hazards, depending on the available time and information. This paper presents a systematic approach for the assessment of inundation hazards and risks caused by landslide dam formation and breaches. The approach includes the evaluation of dam-breach probability, assessment of upstream inundation hazard, assessment of downstream inundation hazard, and the classification of flooding risk. The proposed assessment of upstream inundation estimates the potential region of inundation and predicts the overtopping time. The risk level of downstream flooding is evaluated using a joint consideration of the breach probability of a landslide dam and the level of flooding hazard, which is classified using a flooding hazard index that indicates the risk of potential inundation. This paper proposes both quick and detailed procedures for the assessments of inundation in both the upstream and downstream of a landslide dam. An example of a landslide dam case study in southern Taiwan was used to demonstrate the applicability of the systematic approach.     

Logistic regression model for predicting the failure probability of a landslide dam

Landslides may obstruct river flow and result in landslide dams; they occur in many regions of the world. The formation and disappearance of natural lakes involve a complex earth–surface process. According to the lessons learned from many historical cases, landslide dams usually break down rapidly soon after the formation of the lake. Regarding hazard mitigation, prompt evaluation of the stability of the landslide dam is crucial. Based on a Japanese dataset, this study utilized the logistic regression method and the jack-knife technique to identify the important geomorphic variables, including peak flow (or catchment area), dam height, width and length in sequence, affecting the stability of landslide dams. The resulting high overall prediction power demonstrates the robustness of the proposed logistic regression models. Accordingly, the failure probability of a landslide dam can also be evaluated based on this approach. Ten landslide dams (formed after the 1999 Chi-Chi Earthquake, the 2008 Wenchuan Earthquake and 2009 Typhoon Morakot) with complete dam geometry records were adopted as examples of evaluating the failure probability. The stable Tsao-Ling landslide dam, which was induced by the Chi-Chi earthquake, has a failure probability of 27.68% using a model incorporating the catchment area and dam geometry. On the contrary, the Tangjiashan landslide dam, which was artificially breached soon after its formation during the Wenchuan earthquake, has a failure probability as high as 99.54%. Typhoon Morakot induced the Siaolin landslide dam, which was breached within one hour after its formation and has a failure probability of 71.09%. Notably, the failure probability of the earthquake induced cases is reduced if the catchment area in the prediction model is replaced by the peak flow of the dammed stream for these cases. In contrast, the predicted failure probability of the heavy rainfall-induced case increases if the high flow rate of the dammed stream is incorporated into the prediction model. Consequently, it is suggested that the prediction model using the peak flow as causative factor should be used to evaluate the stability of a landslide dam if the peak flow is available. Together with an estimation of the impact of an outburst flood from a landslide-dammed lake, the failure probability of the landslide dam predicted by the proposed logistic regression model could be useful for evaluating the related risk.     

Discriminant analysis of the geomorphic characteristics and stability of landslide dams

Landslides can cause the formation of dams, but these dams often fail soon after lake formation. Thus, rapidly evaluating the stability of a landslide dam is crucial for effective hazard mitigation. This study utilizes discriminant analysis based on a Japanese dataset consisting of 43 well documented landslide dams to determine the significant variables, including log-transformed peak flow (or catchment area), and log-transformed dam height, width and length in hierarchical order, which affect the stability of a landslide dam. The high overall prediction power (88.4% of the 43 training cases are correctly classified) and the high cross-validation accuracy (86%) demonstrate the robustness of the proposed discriminant models PHWL (with variables including log-transformed peak flow, and log-transformed dam height, width and length) and AHWL (with variables including log-transformed catchment area, and log-transformed dam height, width and length). Compared to a previously proposed “DBI” index-based graphic approach, the discriminant model AHV – which uses the log-transformed catchment area, dam height, and dam volume as relevant variables – shows better ability to evaluate the stability of landslide dams. Although these discriminant models are established using a Japanese dataset only, the present multivariate statistical approach can be applied for an expanded dataset without any difficulty when more completely documented worldwide landslide-dam data are available.     

Impacts of September 21, 1999 Chi-Chi earthquake on the characteristics of gully-type debris flows in central Taiwan

Debris flows are more frequent in central Taiwan, because of its mountainous geography. For example, many debris flows were induced by Typhoon Herb in 1996. The Chi-Chi earthquake with a magnitude of 7.3, which took place in 1999 in central Taiwan, induced many landslides in this region. Some landslides turned into debris flows when Typhoon Toraji struck Taiwan in 2001. This study investigates the characteristics of the gullies where debris flows have occurred for a comparison. Aerial photos of these regions dated in 1997 (before the earthquake) and 2001 (after the earthquake) are used to identify the occurrence of gully-type debris flows. A Geographic Information System (GIS) is applied to acquire hydrological and geomorphic characteristics: stream gradient, stream length, catchment gradient, catchment area, form factor, and geology unit of these gullies. These characteristics in different study regions are presented in a statistical approach. The study of how strong ground motion affects the debris flows occurrence is conducted. The characteristics of the debris flow gullies triggered by typhoons before and after the Chi-Chi earthquake are quantitatively compared. The analysis results show that a significant transformation in the characteristics was induced by the Chi-Chi earthquake. In general, the transformation points out a lower hydrological and geomorphic threshold to trigger debris flows after the Chi-Chi earthquake. The susceptibility of rock units to strong ground motion is also examined. The analysis of debris flow density and accumulated rainfall in regions of different ground motion also reveal that the rainfall threshold decreases after the Chi-Chi earthquake.