Formation Mechanism of Mud Bank Along the Southwest Coast of India

Mud bank formation during the southwest monsoon along the southwest coast of India remains an enigma to the researchers and coastal community in spite of several earlier studies. The present study attempts to unravel the mystery through a high-frequency, season-long time-series observation at Alappuzha, located at the southern part of the west coast of India, a region of frequent occurrence of mud bank. Using 7-month-long weekly time-series observation, we identified strong winds and high waves associated with onset of the southwest monsoon and subsequent three episodic atmospheric low-pressure events (LPEs).With the help of in situ time-series data, we show that the strong winds and high waves associated with southwest monsoon pre-conditions the near shore bottom sediment to bring it into suspension. The high amplitude waves associated with the southwest monsoon, while propagating from the deep water to shallow water region, interact with the bottom initiating bottom-sediment movement and its suspension due to wave refraction and shoaling. The sporadic occurrence of the atmospheric LPEs enhances the process of suspension of bottom sediment in the near shore region leading to the formation of fluid mud. Simulations with a cohesive sediment transport model yielded realistic estimates of sediment transport, in the presence of an onshore current, a pre-requisite for transporting the fluid mud toward the coast. The prevailing onshore upwelling current during the southwest monsoon provides the favorable pre-requisite conditions for transporting the fluid mud through depression channel network towards the coast. Once sufficient quantity and thickness of fluid mud is accumulated in the near shore region, it acts as a wave damper for subsequent high monsoon waves, as indicated by the time-series wave data, leading to the formation of tranquil mud bank region. Depression channel networks extending from the shelf to the coast off Alappuzha, Kochi, Ponnani, Beypore, and Ullal were found in the bathymetric charts, thus explaining why mud banks occur only at few locations in spite of the prevalence of similar monsoon conditions.     

Rainfall thresholds for the triggering of landslides considering previous soil moisture conditions (Asturias,NW Spain)

Given its geological and climatic conditions and its rugged orography, Asturias is one of the most landslide prone areas in the North of Spain. Most of the landslides occur during intense rainfall episodes. Thus, precipitation is considered the main triggering factor in the study area, reaching average annual values of 960 mm. Two main precipitation patterns are frequent: (i) long-lasting periods of moderate rainfall during autumn and winter and (ii) heavy short rainfall episodes during spring and early summer. In the present work, soil moisture conditions in the locations of 84 landslides are analysed during two rainfall episodes, which represent the most common precipitation patterns: October–November 2008 and June 2010. Empirical data allowed the definition of available water capacity percentages of 99–100% as critical soil moisture conditions for the landslide triggering. Intensity-duration rainfall thresholds were calculated for each episode, considering the periods with sustained high soil moisture levels before the occurrence of each analysed landslide event. For this purpose, data from daily water balance models and weather stations were used. An inverse relationship between the duration of the precipitation and its intensity, consistent with published intensity-duration thresholds, was observed, showing relevant seasonal differences.     

An analysis of failure mechanism constraints on pre-failure rock block deformation using TLS and roto-translation methods

Rockfall hazards increase the risk of train derailment along railway corridors in western Canada. In this study, repeated terrestrial laser scanning (TLS) datasets were collected every 2–3 months at three different sites along the Thompson and Fraser River corridors in British Columbia, referred to as the Goldpan, White Canyon, and Mile 109 sites. A total of 207 rockfall events occurring across all three sites between November 11, 2014 and October 18, 2016 were recorded in a database. For each of these rockfalls, pre-failure deformation was measured using a method of three-dimensional roto-translation block tracking. Each rockfall was classified by its deformation behaviour and further categorised based on failure mechanism, volume, lithology, and the roughness condition of the failure plane. Results reveal that detectable levels of deformation were measured in 33% of the total number of rockfall events using the present methods. Rotation deformation was most commonly observed in toppling failures with relatively steep joint orientations. Conversely, planar sliding blocks generally exhibited the least measurable deformation, with the majority not showing any precursory translation or rotation. It is postulated that overhanging rockfall configurations may suppress the expression of deformation in rockfall source blocks, though additional research is required to confirm this.     

A non-hydrostatic model for the numerical study of landslide-generated waves

This paper proposes and demonstrates a two-layer depth-averaged model with non-hydrostatic pressure correction to simulate landslide-generated waves. Landslide (lower layer) and water (upper layer) motions are governed by the general shallow water equations derived from mass and momentum conservation laws. The landslide motion and wave generation/propagation are separately formulated, but they form a coupled system. Our model combines some features of the landslide analysis model DAN3D and the tsunami analysis model COMCOT and adds a non-hydrostatic pressure correction. We use the new model to simulate a 2007 rock avalanche-generated wave event at Chehalis Lake, British Columbia, Canada. The model results match both the observed distribution of the rock avalanche deposit in the lake and the wave run-up trimline along the shoreline. Sensitivity analyses demonstrate the importance of accounting for the non-hydrostatic dynamic pressure at the landslide-water interface, as well as the influence of the internal strength of the landslide on the size of the generated waves. Finally, we compare the numerical results of landslide-generated waves simulated with frictional and Voellmy rheologies. Similar maximum wave run-ups can be obtained using the two different rheologies, but the frictional model better reproduces the known limit of the rock avalanche deposit and is thus considered to yield the best overall results in this particular case.     

Landslides triggered by the 2016 Mj 7.3 Kumamoto,Japan, earthquake

The aim of this study is to establish a detailed and complete inventory of the landslides triggered by the Mj 7.3 (Mw 7.0) Kumamoto, Japan, earthquake sequence of 15 April 2016 (16 April in JST). Based on high-resolution (0.5–2 m) optical satellite images, we delineated 3,467 individual landslides triggered by the earthquake, occupying an area of about 6.9 km². Then they were validated by aerial photographs with very high-resolution (better than 0.5 m) and oblique field photos. Of them, 3,460 landslides are distributed in an elliptical area about 6000 km², with a NE-SW directed 120-km-long long axis and a 60-km-long NW-SE trending short axis. Most of the landslides are shallow, disrupted falls and slides, with a few flow-type slides and rock and soil avalanches. The analysis of correlation between the landslides and several control factors shows the areas of elevation 1000–1200 m, stratum of Q₃-Hvf, seismic intensity VIII and VIII+, and peak ground acceleration (PGA) 0.4–0.6 g register the highest landslide abundance. This study also discussed the relationship between the spatial pattern of the landslides and the seismotectonic structure featured by a strike-slip fault with a normal component and the volcanism in the study area.     

2018 International Summer School on rockslides and related phenomena in the Kokomeren River valley (Kyrgyzstan)

Information about the next Kokomeren Summer School that will take place on August 15–30, 2018, is provided.     

Were merely storm-landslides driven by the 2015-2016 Niño in the Mendoza River valley?

Since Holocene time, above-mean precipitations recorded during the El Niño warm ENSO phase have been linked to the occurrence of severe debris flows in the arid Central Andes. The 2015–2016 El Niño, for its unusual strength, began driving huge and dangerous landslides in the Central Andes (32°) in the recent South Hemisphere summer. The resulting damages negatively impacted the regional economy. Despite this, causes of these dangerous events were ambiguously reported. For this reason, a multidisciplinary study was carried out in the Mendoza River valley. Firstly, a geomorphological analysis of affected basins was conducted, estimating morphometric parameters of recorded events such as velocity, stream flow, and volume. Atmospheric conditions during such events were analyzed, considering precipitations, snow cover, temperature range, and the elevation of the zero isotherm. Based on our findings, the role of El Niño on the slope instability in the Central Andes is more complex in the climate change scenario. Even though some events were effectively triggered by intense summer rainstorm following expectations, the most dangerous events were caused by the progressive uplifting of the zero isotherm in smaller basins where headwaters are occupied by debris rock glaciers. Our research findings give light to the dynamic coupled system ENSO–climate change–landslides (ECCL) at least in this particular case study of the Mendoza River valley. Landslide activity in this Andean region is driven by wetter conditions linked to the ENSO warm phase, but also to progressive warming since the twentieth century in the region. This fact emphasizes the future impact of the natural hazards on Andean mountain communities.     

Precursory slope distress prior to the 2010 Mount Meager landslide,British Columbia

In 2010, the south flank of Mount Meager failed catastrophically, generating the largest (53 ± 3.8 × 10⁶ m³) landslide in Canadian history. We document the slow deformation of the edifice prior to failure using archival historic aerial photographs spanning the period 1948–2006. All photos were processed using Structure from Motion (SfM) photogrammetry. We used the SfM products to produce pre-and post-failure geomorphic maps that document changes in the volcanic edifice and Capricorn Glacier at its base. The photographic dataset shows that the Capricorn Glacier re-advanced from a retracted position in the 1980s then rapidly retreated in the lead-up to the 2010 failure. The dataset also documents 60 years of progressive development of faults, toe bulging, and precursory failures in 1998 and 2009. The 2010 collapse was conditioned by glacial retreat and triggered by hot summer weather that caused ice and snow to melt. Meltwater increased pore water pressures in colluvium and fractured rocks at the base of the slope, causing those materials to mobilize, which in turn triggered several secondary failures structurally controlled by lithology and faults. The landslide retrogressed from the base of the slope to near the peak of Mount Meager involving basement rock and the overlying volcanic sequence. Elsewhere on the flanks of Mount Meager, large fractures have developed in recently deglaciated areas, conditioning these slopes for future collapse. Potential failures in these areas have larger volumes than the 2010 landslide. Anticipated atmospheric warming over the next several decades will cause further loss of snow and glacier ice, likely producing additional slope instability. Satellite- and ground-based monitoring of these slopes can provide advanced warning of future landslides to help reduce risk in populated regions downstream.     

Sensitivity analysis of automatic landslide mapping: numerical experiments towards the best solution

The automatic detection of landslides after major events is a crucial issue for public agencies to support disaster response. Pixel-based approaches (PBAs) are widely used in the literature for various applications. However, the accuracy of PBAs in the case of automatic landslide mapping (ALM) is affected by several issues. In this study, we investigated the sensitivity of ALM using PBA through digital terrain models (DTMs). The analysis, carried out in a study area of Poland, consisted of the following steps: (1) testing the influence of selected DTM resolutions for ALM, (2) assessing the relevance of diverse landslide morphological indicators for ALM, and (3) assessing the sensitivity to landslide features for a selected size of moving window (kernel) calculations for ALM. Ultimately, we assessed the performance of three classification methods: maximum likelihood (ML), feed-forward neural network (FFNN), and support vector machine (SVM). This broad analysis, as combination of grid cell resolution, surface derivatives calculation, and performance classification methods, is the challenging aspect of the research. The results of almost 500 experimental tests provide valuable guidelines for experts performing ALM. The most important findings indicate that feature sensitivity in the case of kernel size increases with coarser DTM resolution; however, the peak of the optimal feature performance for the selected study area and landslide type was demonstrated for a resolution of 20 m. Another finding indicated that in combining a set of topographic variables, the optimal performance was acquired for a DTM resolution of 30 m and the support vector machine classification. Moreover, the best performance of the identification is represented for SVM classification.