A new global landslide dam database (RAGLAD) and analysis utilizing auxiliary global fluvial datasets

To address the current data and understanding knowledge gap in landslide dam inventories related to geomorphological parameters, a new global-scale landslide dam dataset named River Augmented Global Landslide Dams (RAGLAD) was created. RAGLAD is a collection of landslide dam records from multiple data sources published in various languages and many of these records we have been able to precisely geolocate. In total, 779 landslide dam records were compiled from 34 countries/regions. The spatial distribution, time trend, triggers, and geomorphological characteristic of the landslides and catchments where landslide dams formed are summarized. The relationships between geomorphological characteristics for landslides that form river dams are discussed and compared with those of landslides more generally. Additionally, a potential threshold for landslide dam formation is proposed, based on the relationship of landslide volume to river width. Our findings from our analysis of the value of the use of additional fluvial datasets to augment the database parameters indicate that they can be applied as a reliable supplemental data source, when the landslide dam records were accurately and precisely geolocated, although location precision in smaller river catchment areas can result in some uncertainty at this scale. This newly collected and supplemented dataset will allow the analysis and development of new relationships between landslides located near rivers and their actual propensity to block those particular rivers based on their geomorphology.

Landslide Hazard Assessment and Runout Simulation by Utilizing Remote Sensing, Geophysical, and Geological Techniques

Landslide events in Karakorum ranges are frequent and have already damaged local infrastructures and roads. In the hilly regions, landslide characterization and predicting its deposition pattern are essential for accurate engineering hazard assessment. To this end, numerical simulation models are commonly used tools. However, appropriate model parameters are often not available to predict and generate real landslide scenarios. This work describes the use of multidisciplinary techniques to estimate the model parameters for a slope prone to landslide and simulate the hazard level. The first important parameter, landslide boundary, and dynamics were estimated from temporal satellite images by identifying the areas with prominent deformations using the Interferometric Synthetic Aperture Radar (InSAR) technique. The susceptible subsurface strata volume and the possible landslide initiation depth were determined with the electrical resistivity method. In addition, voxel 3D electrical resistivity models were created to present the depth of the existing rupture and the nature of subsurface strata. The soil mechanical parameters were calculated during field visits and laboratory tests. The parameters adopted from different techniques helped simulate the susceptible landslide volume and initiation depth. These parameters are a critical factor in developing an accurate high-speed landslide model through numerical simulation. The applied methodology is vital to understand the dynamics of a particular slope and perform accurate engineering hazard assessment with numerical simulation. The results are essential to predict the potential deposition areas of the landslide event accurately, minimize the risk level, and take proactive mitigation measures.

Detection of earthflow dynamics using medium-resolution digital terrain models: Diachronic perspective of the Jovac earthflow, Southern Serbia

The paper presents and discusses the landslide research procedure related to the topography before and after its occurrence, using the comparative analysis of two medium-resolution digital terrain models. The case study is the Jovac mega-landslide—the largest landslide to occur in Serbia in the last 100 years, active for three days in February 1977. The indicators used to determine the volume and movement mechanism were the spatial distribution of elevation differences within the two digital terrain models (DTM), and the analysis of geomorphological features before the landslide. The obtained elevation differences allowed the definition of the approximate landslide volume: 11.6 × 106 m3. All the data obtained indicate that the movement mechanism falls into the category of earthflow.

GIS-BASED LANDSLIDE VOLUME ESTIMATION USING DIGITAL TERRAIN MODELS DERIVED FROM LIDAR AND RADAR SYSTEMS: CASE OF PIDIGAN, ABRA

Southwest Monsoon (Habagat) and Typhoon Luis caused a deep-seated landslide that struck Sitio Kayang, Brgy. Immuli, Pidigan, Abra on August 15, 2018. Rainfall-induced deep-seated landslides displace partially at a time which necessitates the determination of remaining landslide volume along the slope. In this study, the potential landslide volume and mass transport were estimated using several remote sensing products, including SAR (Synthetic Aperture Radar) data and LiDAR-DTM (Light Detection and Ranging-Digital Terrain Model). The post-landslide DTM was generated using Sentinel-1 SAR data. The potential landslide volume and landslide failure surfaces were ascertained through the stability analysis using Scoops3D, while the mass transport volume was obtained from the pre- and post-landslide DTM. Results showed that the estimated total volume in all the landslide areas was 135,962 m3. Meanwhile, the remaining landslide volume (i.e., difference between potential volume from pre-landslide event and volume of transported mass) yielded illogical values due to the derived large mass transport values. This blunder may be attributed to the generalization of the transported volume (due to Sentinel-1 DTM coarse resolution), and decorrelation due to vegetation cover. Overall, the LiDAR-DTM data delivered a high-resolution estimation of the potential landslide volume and proved to be useful for landslide application studies. Future studies may incorporate field data (e.g., geotechnical parameters, groundwater, landslide actual measurements) for more accurate performance of stability analysis and may best to utilize LiDAR-DTM in post-landslide volume computation for a more reliable estimation of mass transport and potentially remaining landslide volume.

A new empirical equation for predicting the maximum initial amplitude of submarine landslide-generated waves

The accurate prediction of landslide tsunami amplitudes has been a challenging task given large uncertainties associated with landslide parameters and often the lack of enough information of geological and rheological characteristics. In this context, physical modelling and empirical equations have been instrumental in developing landslide tsunami science and engineering. This study is focused on developing a new empirical equation for estimating the maximum initial landslide tsunami amplitude for solid-block submarine mass movements. We are motivated by the fact that the predictions made by existing equations were divided by a few orders of magnitude (10−1–104 m). Here, we restrict ourselves to three main landslide parameters while deriving the new predictive equation: initial submergence depth, landslide volume and slope angle. Both laboratory and field data are used to derive the new empirical equation. As existing laboratory data was not comprehensive, we conduct laboratory experiments to produce new data. By applying the genetic algorithm approach and considering non-dimensional parameters, we develop and examine 14 empirical equations for the non-dimensional form of the maximum initial tsunami amplitude. The normalized root mean square error (NRMSE) index between observations and calculations is used to choose the best equation. Our proposed empirical equation successfully reproduces both laboratory and field data. This equation can be used to provide a preliminary and rapid estimate of the potential hazards associated with submarine landslides using limited landslide parameters.

A numerical study of submarine–landslide–generated tsunami and its propagation in Majene, West Sulawesi

On 14th January 2021, there was a devastating earthquake (Mw 6.2) hit Mamuju and Majene, West Sulawesi, Indonesia at 18.28 UTC. According to National Disaster Management Authority, this event causes 84 casualties and 279 houses were damaged. The Sulawesi Island is situated in a very complex tectonic region, there are several thrusts and faults along the area such as Majene Thrust, Palu-Karo Thrust, Matano Fault, and Tolo Thrust that can lead to tectonic activities. One of the largest earthquakes was a 7.9 Mw in 1997 generated from North Sulawesi Megathrust that caused a catastrophic tsunami. Moreover, there were 9 tsunami events in the Makassar Strait from the year 1800 to 1999. In this research, three different scenarios of the tsunami in Majene were applied to obtain the tsunami elevation. Makassar Strait could be potentially generated tsunami wave from submarine landslides due to its steep bathymetry that will impact the coastline at Sulawesi and Kalimantan, so it is necessary to model the tsunami propagation using submarine landslide as the tsunami generation. The volume of submarine landslide had been used in tsunami submarine landslide modelling as an input. Those are included the height, width and length of the submarine landslide volume. Furthermore, the domain bathymetry was obtained from National Bathymetry (BatNas) with spacing grid of 300 m × 300 m. The submarine landslide coordinate is also needed as a source of tsunami at 2.98°S and 118.94°E. The slide angle and slope angle are also inputted in this modelling with three experimental volumes, namely 1 km3, 0.8 km3, and 0.5 km3. This submarine landslide tsunami modelling used the Non-Hydrostatic WAVE Model (NHWAVE) method to obtain tsunami wave generation. The result from NHWAVE model will be used for initial elevation of tsunami wave propagation using the Fully Nonlinear Boussinesq wave model - Total Variation Diminishing (FUNWAVE - TVD) method. The highest initial tsunami elevation value at each observation point obtained from the NHWAVE model occurred at point 18 (the closest location to the earthquake source), which is around 0.4 –1.2 m. The FUNWAVE simulation result is the tsunami wave propagation for 180 minutes later. In the 180th minute, the tsunami wave was still propagating towards the north of Sulawesi Island to the east of Kalimantan Island.

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.

Analysis of Landslide and Land Subsident Using Geophysical Method in the East Java Province, Indonesia

East Java Province, which is geologically very complex, often occurs natural disasters, especially landslide and land subsidence. The area of East Java is divided into 3 parts, namely the southern part which is the result of volcanic lahar, and also the uplift from the southern sea. Those two kinds of sediment, geologically is quarter and tertiary volcanic deposits age, and limestone. The Middle part, is a cluster of active volcanoes that are quarter old, which provide quarter-aged sediments and these area is rich in geothermal. The Northern part, which is a sediment from the Java Sea and the Madura Strait, with several limestone mountains, is an area rich in hydrocarbons. The area to be studied is the Southern area, namely the quarter sediment from volcanic lava and the lifting of limestone which has the potential to occur landslides and land subsident. The landslide and land subsident symptoms will be analyzed using the geophysical method, to predict the landslide volume and also the dangerous areas with regard to the land subsident.

Supplemental Material: Extreme event-driven sediment aggradation and erosional buffering along a tectonic gradient in southern Taiwan

Methods for landslide volume estimation, channel aggradation mapping, sediment transport modeling, and recurrence estimate.<br>

Supplemental Material: Extreme event-driven sediment aggradation and erosional buffering along a tectonic gradient in southern Taiwan

Methods for landslide volume estimation, channel aggradation mapping, sediment transport modeling, and recurrence estimate.<br>