Review of the Founding Issue of P-LRT: Progress in Landslide Research and Technology

Abstract

This article presents an overview and a concise review of the founding issue of Progress in Landslide Research and Technology (P-LRT). The Vol. 1, No. 1 issue of P-LRT was comprised of a total of twenty-four articles from twenty-five countries/regions worldwide. The inaugural issue embodies recent progress in landslide research and technology for practical applications and the benefit for the society contributing to the Kyoto Landslide Commitment 2020 for a global promotion of understanding and reducing landslide disaster risk.

1 Introduction

The founding issue of P-LRT: Progress in Landslide Research and Technology was composed of the contributions of twenty-four relevant articles from twenty-five countries/regions worldwide. The articles represented a total of eleven original articles, one review article, a total of ten articles on the projects of the International Programme on Landslides (IPL) and the World Centres of Excellence on Landslide Risk Reduction (WCoEs), and Kyoto Landslide Commitment, one teaching tool, and one technical note from a total of one-hundred and fifteen researchers/practitioners. The themes were diverse and ranged from landslide-induced tsunamis to natural-hazard-related web observatories, port-fire erosion rates mapping, mechanisms and early warning of rainfall-induced landslides, design of protection structures against flow-like landslides, landslide warning systems, translational landslides, spectral element method in slope instability analysis, climate change-induced landslide susceptibility and exposure assessment, using experimental models to calibrate numerical models for slope stability/deformation analysis, sustainability of geosynthetics-based landslide stabilization, establishment of the disaster risk reduction unit in UNESCO, real-time high-resolution prediction of orographic rainfall, landslide monitoring best practices and advanced technology, International Organization for Standardization (ISO), rockslide inventory, global database of giant landslides on volcanic islands, 2018 Easter Iburi landslide disasters, empirical-statistical modeling of landslide travel distances, landslide hazard resilience and geometry for restoration, teaching tool/manual of the integrated landslide simulation model LS-RAPID, and rainfall thresholds for landslide early warning systems.

2 Review of the Founding Issue of P-LRT

The founding issue of Progress in Landslide Research and Technology featured a total of 24 articles that represented original articles (11), review article (1), IPL/WCoEs/Kyoto Commitment activities articles (10), teaching tool (1) and technical note (1), which will be reviewed in order as below.

Sassa et al. presented the outcome of the panel discussion (Fig. 1) organized across America, Europe, and Asia and the review of the World Tsunami Awareness Day Special Event of the Fifth World Landslide Forum. The article presented some recent advances, the current state and challenges in understanding and reducing the disaster risk of landslide-induced tsunamis.

Fig. 1

The framework, essential content and a short summary of the panel discussion in the World Tsunami Awareness Day Special Event of the Fifth World Landslide Forum (Sassa et al. 2022a) (Fig. 22 in Sassa et al. 2022b)

Mikoš et al. presented a natural-hazard-related web observatory on landsides as a sustainable development tool. The information gathered on the internet (e.g. Fig. 2) is structured, and shown using geolocators for different regions and/or countries to be used by different stakeholders when implementing global climate adaptation policies and relevant European Union strategies.

Fig. 2

Exploring a timeline of worldwide news on landslide events throughout 927,847 articles in eight years of collected data (Fig. 9 in Mikoš et al. 2022)

Vacha et al. mapped post-fire monthly erosion rates at the catchment scale on GIS in the north-western Italian Alps. They highlighted the marked increase (more than 20 times) in erosion rates, quantified by expressing both the EI (erodibility index), the A (monthly soil loss) and the SL (monthly sediment loss) rise (Table 1) in the post-fire scenario than the pre-fire one.

Table 1 Spatially averaged mean soil loss (A) and averaged monthly sediment loss (SL) comparison for the burned and unburned situation (Table 7 in Vacha et al. 2022)

Gratchev et al. presented the mechanisms of rainfall-induced shallow landslides in Australia (Fig. 3). The major factors causing the landslide mass such as geology, weathering, and rainfall patterns were discussed based on the field and laboratory investigations, showing the role of the formation of wetting (moisture) front, increases in water content, and the excess pore water pressure generation.

Fig. 3

Examples of rainfall-induced landslides from Australia: a failure in rock mass of the Neranleigh–Fernvale Beds formation. The bedding planes of sandstone and argillite are steeply inclined, producing an adverse effect on rock mass stability; b landslide in heavily weathered volcanic deposits; c shallow slide of heavily weathered material caused by the Cyclone Debbie in 2017; d shallow landslide in weathered material (Fig. 2 in Gratchev et al. 2022)

Cuomo et al. presented the analysis of LSI (Landslide-Structure-Interaction) for flow-like landslides against protection barriers for their design, on the basis of a general conceptual scheme (Fig. 4) and empirical, analytical and numerical approaches including the estimate of the amount of landslide volume overtopping the barrier. Different tools and options to design a protection barrier have been provided.

Fig. 4

General conceptual scheme for Landslide Structure Interaction (LSI) (Fig. 1 in Cuomo et al. 2022)

Alcántara-Ayala and Garnica-Peña presented the systematic literature analysis of Landslide Early Warning Systems (LEWS) in low- and lower-middle-income countries. The demand for effective regional and international collaborations (Fig. 5) with the scientific community for the disaster risk reduction (DRR) in terms of LEWSs advancement was highlighted.

Fig. 5

Regional and international collaborations among LICs and MICs and other countries (Fig. 10 in Alcántara-Ayala and Garnica-Peña 2022)

Abe et al. presented the role of translational landslides (Fig. 6) in the evolution of cuesta topography based on the field surveys in Japan, Taiwan, Switzerland, and Nepal. The results indicate that the translational bedrock landslides occurring on the cuesta’s back slopes have repeatedly denuded intact sliding surfaces over the long term while maintaining the cuesta landscape.

Fig. 6

Schematic models of the landslide history induced by the development of cracks and streams (Fig. 11 in Abe et al. 2022)

Tiwari and Bhandary presented the application of spectral element method (SEM) in slope instability analysis (e.g. Fig. 7). The SEM procedure has three major benefits over the existing FEM procedures: (1) geometrical flexibility, (2) high computational efficiency, and (3) reliable spectral accuracy (i.e., exponential reduction of errors with increasing degree of polynomials).

Fig. 7

3D model of Jure Sindhupalchowk landslide with Meshing (27°46′1.55″ N latitude and 85°52′17.10″ E longitude) (Fig. 14 in Tiwari and Bhandary 2022)

Wijaya et al. presented the climate change-induced regional landslide hazard and exposure assessment (Fig. 8) in mountainous regions under extreme rainfalls in Nepal. They developed high-resolution landslide hazard models based on the Frequency Ratio (FR) and Analytical Hierarchical Process (AHP) methods, which may aid climate resilient road infrastructure planning.

Fig. 8

Landslide hazard and exposure maps for a baseline period (1976–2005), b time horizon 2030s for RCP4.5, c time horizon 2030s with RCP8.5, d time horizon 2050s for RCP4.5, e time horizon 2050s for RCP8.5, f time horizon 2080s for RCP4.5 and g time horizon 2080s for RCP8.5. RCP denotes representative concentration pathways (Fig. 7 in Wijaya et al. 2022)

Tiwari and Tran described the use of experimental models to calibrate numerical models (Fig. 9) for slope stability and deformation analysis. They showed how various soil and ground parameters influence the stability of slopes and how numerical models can be calibrated with the experimental modeling results to apply the calibrated numerical models for field slopes/landslides.

Fig. 9

Weakest plane obtained from numerical and experimental analyses—Sigma/W for model 6 (Fig. 19 in Tiwari and Tran 2022)

Damians et al. identified sustainability factors to consider when applying geosynthetics (Fig. 10) for mitigating landslide risks. They showed how a value integrated model for sustainable evaluations (MIVES) methodology can be applied to evaluate and compare alternative methods for remediation of landslides and recommended further studies using this tool.

Fig. 10

Scheme of a geosynthetic reinforced soil slope (from IGS leaflet “Geosynthetics in Slopes over Stable Foundations”) (Fig. 1 in Damians et al. 2022)

Delgado et al. reported the establishment of the disaster risk reduction (DRR) unit in UNESCO and UNESCO’s contribution to global resilience. UNESCO’s DRR unit will continue to support the development of global, regional and national multi-hazard early warning systems, the improvement of the scientific basis for developing technologies and tools for landslide multi-risk identification and management (Delgado et al. 2022).

Konagai et al. reported an outline of the joint research project “Development of early warning technology of Rain-induced Rapid and Long-travelling Landslides (Project RRLL)” between the International Consortium on Landslides (ICL) and the National Building Research Organization, Sri Lanka (NBRO). It aims at developing critical technologies for the early warning system against rainfall-induced landslides (e.g. Fig. 11).

Fig. 11

Rendering image of augmented reality dioramas of the predicted rains and locations of rain-induced rapid long-traveling landslides (RRLLs) with a bird’s-eye view of the area as their background on tablet’s screen (Fig. 24 in Konagai et al. 2022)

Onishi et al. described a recent development of reliable high-resolution prediction of orographic rainfall using a next-generation numerical weather prediction model, the Multi-Scale Simulator for the Geoenvironment (MSSG, Fig. 12). The model facilitates reliable predictions of orographic rainfall for realizing early warning of landslides.

Fig. 12

MSSG is designed to be applicable to a global scale, b meso scales and up to c urban scales. The Yin-Yang grid system, which consists of two overlapping latitude–longitude grids indicated in blue and red, is adopted for global simulations (Fig. 1 in Onishi et al. 2022)

Casagli et al. presented Advanced Technologies for LandSlides (ATLaS). They outlined research activities on landslide monitoring and early warning through innovative technologies, exploitation of earth observation data and technology (Fig. 13) to detect, map, monitor and forecast ground deformations, regional forecasting models for landslides risk reduction.

Fig. 13

Satellite-based services at regional scale in Italy: a location of Tuscany, Valle d’Aosta, Veneto Region in Italy; b example of “PS mapping” activity to highlight highest ground motion rates and of “PS monitoring” activity to periodically scan the territory across time; c sketch of systematically updated ground deformation maps based on Sentinel-1 PSI data of Tuscany, Valle d’Aosta, Veneto Region (Fig. 2 in Casagli et al. 2022)

Huntley et al. reported the outcome of the IPL Project 202: Landslide monitoring best practices for climate-resilient railway transportation corridors in southwestern British Columbia, Canada. They proposed a best-practice solution involving three levels of investigation (Fig. 14) to describe the form and function of the wide range of rapid and slow-moving landslides.

Fig. 14

Conceptual model outlining three levels of investigation to classify, determine susceptibility, and identify landslides of concern for monitoring. Inventory maps, geospatial change-detection, and in-situ time-series monitoring define the interactions between landslides of varying sizes, displacement amounts, and timing of activity; and contribute to estimates of infrastructure vulnerability, anticipated damage, and cascade of consequences contributing to landslide risk. Mitigation solutions reduce the risks to railway transportation corridors running through terrain susceptible to landslides (Fig. 7 in Huntley et al. 2022)

Fathani et al. reported the implementation of a new standard for landslide early warning systems to the International Organization for Standardization (ISO). It empowers individuals and communities vulnerable to landslides (Fig. 15) to act in sufficient time and appropriate ways to reduce the possibility of injuries, loss of life, and damage to property and the environment.

Fig. 15

Locations of landslides and floods early warning system implementation in Indonesia (2007–2021) (Fig. 6 in Fathani et al. 2022)

Strom reported the activities of the World Centre of Excellence (WCoE) of JSC “Hydroproject Institute” and of Institute of Seismology of National Academy of Sciences of Kyrgyz Republic. The study for the most disastrous types of landslides in mountainous regions—large-scale rockslides and rock avalanches (Fig. 16) led to the Central Asia Rockslides Inventory.

Fig. 16

Oblique view of the giant Padjvar rockslide in Afghan Badakhshan ca. 6 km³ in volume. The entire ridge about 6 km long collapsed in the adjacent valley of the left tributary of the Pianj River and filled it almost completely with the deposits up to 650–700 m thick that cover 19.72 km², while the total affected area is about 27 km² (Fig. 12 in Strom 2022)

Rowberry et al. described a comprehensive online database of giant landslides on volcanic islands compiled by researchers from the Institute of Rock Structure and Mechanics, Czech Academy of Sciences, in the framework of IPL Project 212. The global distribution of giant landslides on volcanic islands (Fig. 17) was described in depth.

Fig. 17

Source Global relief model derived from Global Bathymetry and Topography at 15 Arc Sec: SRTM15 + V2.1 (Tozer et al. 2019) (Figs. 4 and 5 in Rowberry et al. 2022)

Distribution of giant landslides on volcanic islands from the Atlantic and Indian Oceans (left) and the Pacific Ocean (right).

Wang and Nam described landslide disasters caused by the 2018 Eastern Iburi Earthquake in Hokkaido Japan. They reported novel findings pertaining to distinctive properties of the widely distributed, weathered Plinian Ta-d tephra deposit (Fig. 18) from Tarumae volcano and their impact on the spatial clustering of the Iburi landslides.

Fig. 18

Isopach map of pyroclastic fall deposits (Ta-a, Ta-b, Ta-c, Ta-d, En-a and Spfa-1) and field investigation on sliding surface (general view: a–d, and soil profiling: e and f) for the 2018 Iburi landslide disasters (Fig. 3 in Wang and Nam 2022)

Moncayo and Ávila presented the analysis of the database of 123 landslides from the Andean region of Colombia. The empirical-statistical modelling showed that the volume of the displaced mass, the slope angle, the maximum landslide height, and geomorphological environment were the predominant factors controlling the landslides travel distances in the area (Fig. 19).

Fig. 19

Relationship between travel distance L and landslide volume V (left) and maximum landslide height H (right) (Figs. 3 and 4 in Moncayo and Ávila 2022)

Dias et al. presented landform geometry pertaining to the restoration of mountain roads and landslide hazard resilience. They showed that the complexity of slope geometries, potential deformities, ground discontinuities, and soil-rock composite nature are compulsory elements to understand and dominant parameters to describe the on-site stability of earth cut slope (e.g. Fig. 20).

Fig. 20

Example of rock formed failures along the road side slope. Wedge failure, translational slides and falling rocks are very much significant along the road sides. High hazard potential zone can be observed due to foliated and jointed rock formations (Fig. 13 in Dias et al. 2022)

Ajmera et al. presented the teaching tool and manual of LS-RAPID, an integrated simulation model capable of capturing the entire landslide process starting from a state of stability to landslide initiation and movement to the mass deposition. Three tutorials were shown illustrating the applications to (1) a rainfall-induced failure, (2) an earthquake-induced failure, and (3) the case study of the Atami debris flow (Fig. 21), as supplemented by the video tutorials.

Fig. 21

Simulation Results of Atami Debris Flow at 58 h 43 m 00 s from the Start of Rainfall (Fig. 4.39(d) in Ajmera et al. 2022)

Gariano et al. described the LANDSLIP project aimed at developing a landslide early warning system (LEWS) to forecast the occurrence of rainfall-induced landslides in two Indian pilot areas: Darjeeling and Nilgiris (Fig. 22). The rainfall thresholds at different non-exceedance probabilities were determined by adopting a frequentist statistical method and an automatic tool.

Fig. 22

Top: annual distribution of monthly rainfall in a Darjeeling (1959–2017) and c Nilgiris (1987–2017). Bottom: monthly distribution of landslides in b Darjeeling and d Nilgiris; lighter bars indicate the total numbers of catalogued landslides in each pilot area; darker bars indicate the landslides used to calculate the thresholds (values in brackets) (Fig. 3 in Gariano et al. 2022)

3 Conclusion

This article has presented an overview and a concise review of the founding issue of P-LRT: Progress in Landslide Research and Technology. The themes for the Vol. 1, No. 1 of P-LRT were diverse as described above, with a total of one-hundred and fifteen researchers/practitioners from twenty-five countries/regions worldwide contributing to the inaugural issue of the ICL Open Access Book Series. It is hoped that P-LRT will serve as a common, long-standing platform for the publication of recent progress in landslide research and technology for practical applications and the benefit for the society contributing to the Kyoto Landslide Commitment 2020 to globally promote understanding and reducing landslide disaster risk.