Landslide Activity Research Articles

Elevation dependence of landslide activity induced by climate change in the eastern Pamirs

Elevation dependence of landslide activity induced by climate change in the eastern Pamirs

InSAR Displacement with High-Resolution Optical Remote Sensing for the Early Detection and Deformation Analysis of Active Landslides in the Upper Yellow River

Frequent landslides and other geological disasters pose a serious threat to human life and infrastructure in the Upper Yellow River. Detecting active landslides and ascertaining their impact necessitate the determination of deformation characteristics. In this study, we developed an integrated method combining interferometric synthetic aperture radar and high-resolution optical satellite remote sensing to detect active landslides in the Upper Yellow River region from Longyang Gorge to Lijia Gorge. Sentinel-1 satellite data from January 2019 to April 2021 with ascending and descending orbits were adopted to obtain deformation using the STACKING and interferometric point target analysis techniques. A 97.08% overlap rate in the detected results from the two InSAR technologies confirmed the suitability of both approaches. The missing detection rates (6.79% & 8.73%) from single line-of-sight (LOS) InSAR results indicate the necessity of different orbit direction data. Slight deformation rate changes (<4 mm/month) before and after rainy seasons of the Lijia Gorge landslide group indicate that precipitation exerted little impact on slope activity. This study supports the feasibility of integrated methods for the detection and analysis of active landslides in the Upper Yellow River and other regions.

Automatic detection and update of landslide inventory before and after impoundments at the Lianghekou reservoir using Sentinel-1 InSAR

There is an urgent demand for continuous detection and monitoring of active slopes in wide reservoir areas, as reservoir impoundments may activate unstable slopes. Although satellite time-series InSAR has been widely used in mapping active landslides, the tedious artificial interpretation of InSAR results limits the efficiency and reliability of landslides detection. We propose a set of procedures for deformation monitoring and continuous automatic landslide identification in wide reservoir areas. The local time window estimation can extract the nonlinear deformation in the time series InSAR signal, thus enhancing the deformation field. Spatial adaptive clustering enables the effective extraction of unstable slopes. The abnormal deformation trends of landslides can be updated through the continuous identification of new results and comparison with historical results. The procedure is used to continuously detect unstable slopes in the Lianghekou reservoir area before and after the impoundment. Combining the ascending and descending SAR data of Sentinel-1, 109 historically active landslides were found and 18 new landslides were activated within one year after the first water storage. The distribution and types of unstable slopes were analyzed, followed by two case studies. The first case shows the different effects of the two-stage water storage on slope deformations, indicating rising water levels' critical role in landslide activation. The second case shows the consolidation settlement of the embankment dam and the influence of water storage on slope deformation monitoring. The results demonstrate the effectiveness of the InSAR automatic landslide identification and this study provides a technical reference for similar reservoir area.

A GIS-Based Kinematic Analysis for Jointed Rock Slope Stability: An Application to Himalayan Slopes

GIS-based kinematic stability analysis in rock slopes is a rare practice in geological engineering despite its immense potential to delineate unstable zones in a mountainous region. In this article, we have used a GIS-based modified technique to assess the efficiency of kinematic analysis in predicting shallow landslides in the rock slopes of the Himalayan mountains on a regional scale. The limited use of this technique is primarily due to the complexities involved in its practical application. To make this technique more effective and convenient usability, we present modified methods and a new application, ‘GISMR’, that works with the aid of GIS software for the determination of kinematic susceptibility. A modified kinematic analysis method was implemented to define the stability in terms of failure susceptibility on a scale of 0 to 100 rather than a conservative result, such as failure or non-failure. We also present another functionality of the GISMR that provides optimised slope angles over a region. This functionality could aid the decision-making process when selecting a suitable location for a road path or other engineering constructions that are impacted by unstable mountain slopes. The applicability of this new method was demonstrated in a rock failure-prone region in the mountains of the Indian Himalayas. The outcomes delineate the unstable slopes in the region, which are intersected by a strategic National Highway 05 and have a long history of landslide-related hazards. It was found that 9.61% of the area is susceptible to failure. However, 2.28% is classified as a low susceptible region, and 2.58% of the area is very-low susceptible. The regions with moderately high, high, and very-high susceptibility cover 2.78%, 1.49%, and 0.46% of the whole area, respectively. The results were evaluated by receiver operating characteristic curve and a frequency ratio method to represent the association between kinematic susceptibility and the mass movement inventory in the area. It is concluded that kinematic susceptibility has a strong relationship with landslide activity in the rock slopes of the Himalayan region.

Geology and vegetation control landsliding on forest-managed slopes in scarplands

Abstract. Landslides are important agents of sediment transport, cause hazards and are key agents for the evolution of scarplands. Scarplands are characterized by high-strength layers overlying low-inclined landslide-susceptible layers that precondition and prepare landsliding on geological timescales. These landslides can be reactivated, and their role in past hillslope evolution affected geomorphometry and material properties that set the framework for present-day shallow landslide activity. To manage present-day landslide hazards in scarplands, a combined assessment of deep-seated and shallow landsliding is required to quantify the interaction between geological conditions and vegetation that controls landslide activity. For this purpose, we investigated three hillslopes affected by landsliding in the Franconian scarplands. We used geomorphic mapping to identify landforms indicating landslide activity, electrical resistivity to identify shear plane location and a mechanical stability model to assess the stability of deep-seated landslides. Furthermore, we mapped tree distribution and quantified root area ratio and root tensile strength to assess the influence of vegetation on shallow landsliding. Our results show that deep-seated landslides incorporate rotational and translational movement and suggest that sliding occurs along a geologic boundary between permeable Rhätolias sandstone and impermeable Feuerletten clays. Despite low hillslope angles, landslides could be reactivated when high pore pressures develop along low-permeability layers. In contrast, shallow landsliding is controlled by vegetation. Our results show that rooted area is more important than species-dependent root tensile strength and basal root cohesion is limited to the upper 0.5 m of the surface due to geologically controlled unfavourable soil conditions. Due to low slope inclination, root cohesion can stabilize landslide toes or slopes undercut by forest roads, independent of potential soil cohesion, when tree density is sufficient dense to provide lateral root cohesion. In summary, geology preconditions and prepares deep-seated landslides in scarplands, which sets the framework of vegetation-controlled shallow landslide activity.

Multi-hazard performance evaluation of hillside buildings under earthquakes and landslides

Earthquake-induced landslide, a cascading hazard in hilly regions, can substantially increase the damaging effects of an earthquake. This necessitates performance evaluation of buildings situated in hilly regions under the effects of landslide-only and landslides following earthquakes. In this study, the performance of two commonly observed hillside building configurations is assessed—namely, step-back and split foundation—subjected to the above-mentioned multi-hazard scenarios using an uncoupled approach. The uncertainty in the soil properties that influence the landslide-induced forces is considered based on laboratory tests of soil samples collected from active landslide sites and an existing database of landslide events. Three-dimensional hillside buildings are analysed for uphill-side landslide scenarios by performing force-controlled non-linear static analyses. Further, a suite of earthquake ground motions is scaled to a predefined intensity level, and then non-linear time history analyses are performed to obtain the damaged state of the buildings prior to assessing the landslide response. It is observed that the earthquake loading history and its direction of excitation significantly affect the response of hillside buildings to a landslide following an earthquake. Further, the step-back building is observed to be more vulnerable to landslide damage when compared to its split foundation counterpart for a given uphill-side landslide scenario.

Characteristics and distribution of geohazards since the middle miocene of the Xisha sea area, South China Sea

Geological hazards can cause significant harm to the construction and maintenance of reef infrastructure projects in the Xisha Sea area. This study uses high-resolution multichannel earthquake data, single-channel seismic profiles, and multi-beam survey data to identify and analyze the geological hazards in the Xisha Sea area since the Miocene. Based on the geophysical data interpretation, the destructive geological disaster factors that are active, such as active faults, shallow gas, diapers, landslides, multistage scarps (steps), scouring troughs, and canyons, as well as the restrictive geological disaster factors without activity ability, such as buried paleochannels, pockmarks, reefs, and undersea volcanoes, are identified and analyzed. This paper discusses the causes and hazards of geological hazards and, for the first time, draws a comprehensive plane layout of the geological hazards. The above analysis demonstrates that the scarps are mainly located around the atolls or platforms, and the slope of the southeast seabed topography is significantly higher than that of the northwest. There are seven medium and large landslides, mainly located around Yongxing Plateau and Yongle Plateau, caused by gravity and faulting. Shallow gas is mainly developed in the southern part of the North Reef and is indicated by diaper structures, faults, and gas chimneys. A series of shallow faults are developed in the study area, mainly steep normal faults. The scouring troughs are primarily distributed near the Yongxing Platform, Zhongjian North Platform, and Huaguang Platform. Submarine canyons are primarily located in the northern and southern parts of the Shidao Platform. Affected by multiple factors such as hydrodynamic conditions, the stability of sedimentary layers, and sediment supply, the scour degree varies, with the general depth ranging from several meters to several hundred meters. Underwater infrastructure in the study area should not be constructed in areas with active and destructive geological hazards. The results of this study can serve as a guide for further exploration in the Xisha area and disaster prevention and mitigation during construction activity in the area.

Insight from a Physical-Based Model for the Triggering Mechanism of Loess Landslides Induced by the 2013 Tianshui Heavy Rainfall Event

Rainfall-induced landslides pose a significant threat to human life, destroy highways and railways, and cause farmland degradation in the Loess Plateau. From 19 June 2013 to 26 July 2013, continuous and heavy rainfall events occurred in the Tianshui area, Gansu Province. This strong rainfall process included four short-term serious rainfall events and long-term intermittent rainfall, triggering many shallow loess landslides. To improve our understanding of this rainfall process as the triggering mechanism of the loess landslides, we conducted the physical-based spatiotemporal prediction of rainfall-induced landslides. By utilizing precipitation data recorded every 12 h from the rain gauge stations and 51 soil samples from within a 50 km radius of the study area, we predicted 1000 physical-based model-calculated pictures of potential landslides, and the slope failure probability (Pf) of the study area was obtained by Monte Carlo simulations. The model was validated by the actual landslide data of the 2013 heavy rainfall event, and the effects of the precipitation process and the trigger mechanism on the landslides were discussed. The results showed that the fourth rainfall event had the best prediction ability, while the third event had the second-best prediction ability. There was a solid linear link between the antecedent precipitation (Pa) and the predicted landslide area (Pls) based on the fitting relationship, indicating that antecedent rainfall may play a significant role in the occurrence of landslides in the region. By comparing the distribution of the predicted results of the four heavy rainfall events with the actual landslide, we observed that the first two rainfall processes may not have been the main reason for slope failure, contributing only to prepare for the landslides in the later period. The superposition of the fourth and third rainfall events finally determined the spatial distribution characteristics of the landslide induced by the 2013 heavy rainfall event.

Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China

There is no doubt that land cover and climate changes have consequences on landslide activity, but it is still an open issue to assess and quantify their impacts. Wanzhou County in southwest China was selected as the test area to study rainfall-induced shallow landslide susceptibility under the future changes of land use and land cover (LULC) and climate. We used a high-resolution meteorological precipitation dataset and frequency distribution model to analyse the present extreme and antecedent rainfall conditions related to landslide activity. The future climate change factors were obtained from a 4-member multi-model ensemble that was derived from statistically downscaled regional climate simulations. The future LULC maps were simulated by the land change modeller (LCM) integrated into IDRISI Selva software. A total of six scenarios were defined by considering the rainfall (antecedent conditions and extreme events) and LULC changes towards two time periods (mid and late XXI century). A physically-based model was used to assess landslide susceptibility under these different scenarios. The results showed that the magnitude of both antecedent effective recharge and event rainfall in the region will evidently increase in the future. Under the scenario with a return period of 100 years, the antecedent rainfall in summer will increase by up to 63% whereas the event rainfall will increase by up to 54% for the late 21st century. The most considerable changes of LULC will be the increase of forest cover and the decrease of farming land. The magnitude of this change can reach + 22.1% (forest) and –9.2% (farmland) from 2010 until 2100, respectively. We found that the negative impact of climate change on landslide susceptibility is greater than the stabilizing effect of LULC change, leading to an over decrease in stability over the study area. This is one of the first studies across Asia to assess and quantify changes of regional landslide susceptibility under scenarios driven by LULC and climate change. Our results aim to guide land use planning and climate change mitigation considerations to reduce landslide risk.

Vegetation-landslide nexus and topographic changes post the 2004 Mw 6.6 Chuetsu earthquake

Ground shaking on steep slopes often triggers numerous landslides, which dramatically modify the landscape and have long-term effects on vegetation dynamics. However, we still have a limited understanding of the quantitative topographic evolution and the duration of post-seismic impacts on the landscapes due to the lack of long-term consistent observation, especially in low-elevation mountain regions. To address this issue, we used high-resolution pre-and post-earthquake DEMs to investigate topographic changes, as well as multi-period and multi-scale remote sensing images to analyze the post-seismic landslides and vegetation recovery in the sites affected by the Mw 6.6 2004 Chuetsu earthquake, Japan. Using a vegetation recovery rate (VRR) time series from 2004 to 2021, we examined the decaying tendency of post-seismic landslide activities and predicted the vegetation recovery rate. Our findings indicate that the Chuetsu earthquake mostly steepens and roughens the terrain in low-elevation areas. The changes to slope aspects are associated with coseismic lateral displacement. The vegetation damage area accounted for 87.98 % of the entire area after the earthquake, and the VRR reaches 85.55 % by June 2021. The number of active landslides decreased to 14.45 % after 15 years. Meanwhile, we predict that vegetation recovery areas will be restored to pre-earthquake levels in 2024, and the landslide activity rate will decrease by less than 1 % in 2026, indicating a stable hillslope devoid of debris flows in the future.

The largest rock avalanches in Patagonia: Timing and relation to Patagonian Ice Sheet retreat

One of the largest concentrations of giant landslides (≥108 m3) in Patagonia is in the eastern part of Lago Cochrane/Pueyrredón (LP) valley in Argentina. In addition to minor earthflows and rock slides, this landslide cluster is dominated by rock and debris avalanches that affect the northern slope of Meseta Belgrano, the largest of which have volumes >1 km3 and a runout of >10 km. To determine the chronology of these large landslides and their relationship to the geological setting and the glacial history related to the Last Glacial Maximum (LGM) ∼20–18 ka ago, we combined geomorphological mapping with absolute dating (luminescence and radiocarbon dating) and numerical modelling of slope stability. Dating and cross-cutting relationships with glaciolacustrine deposits suggest that some of the largest rock avalanches collapsed directly into a glacial lake between ∼17 and ∼12 ka, soon after deglaciation, but some were pre-glacial and landslide activity continued until today, posing a potential hazard to the area. In agreement with these data, numerical modelling suggests that slope stability was only marginally affected by ice retreat and glacial lake drainage, and landslides were most likely favoured by relatively low rock strength, related glacially-conditioned topography, and, possibly, seismic activity. A newly identified active fault at the base of the Meseta Belgrano, whose activity was likely enhanced by postglacial rebound, was probably the key factor that concentrated postglacial rock avalanches into the LP valley. We conclude that exceptionally large (km-scale) landslides can occur on slopes made of relatively weak rocks in a glacially-conditioned topographic setting even without a strong direct triggering effect of deglaciation, while fatigue due to long-term seismicity may promote collapse.

Slope stability evolution of a deep‐seated landslide considering a constantly deforming topography

AbstractSlow‐moving deep‐seated landslides are characterised by continuous deformation, constantly changing topography and sliding‐mass geometry. Deformation rates are predominantly controlled by temporal dynamics of pore pressure. Progressing movements typically cause an over‐steepening of a landslide's foot, making these areas more susceptible to secondary slope failures and piggyback slides that, once they occur, change the geometric boundary conditions of a slope. This study presents an integrated topographic monitoring and geomechanical modelling approach, which is suitable for both model‐based replication of the landslide's hydro‐meteorological drivers and assessment of the long‐term effect of topographic changes on the stability behaviour of a large deep‐seated landslide. Parametrised at the Vögelsberg landslide (Tyrol, Austria) the integrated approach quantified considerable mass relocations between 2007 and 2020 at the landslide's foot and assessed respective effects on slope stability. Additionally, scenarios of past and future topographies were reconstructed and projected. Mass relocations of the order of 25 000 m3 were assessed between multiple airborne laser scanning acquisitions covering a period of 13 years. Based on annual uncrewed aerial vehicle laser scanning campaigns, area‐wide 3D displacements were analysed, exceeding a magnitude of 200 cm a−1 at small parts (2.500 m2) on the steeper foot of the active landslide. The main landslide body (0.28 km2) moves considerably slower with movements of 2–10 cm a−1. Besides spatio‐temporally varying hydrological drivers, topographic changes can have a severe impact on slope stability and therefore modify the spatiotemporal activity of the landslide. It is shown that, besides the hydrometeorological drivers, the varying elevation of the landslide's toe is a key parameter determining the long‐term trend of slope stability. With the presented approach the formation and evolution of the Vögelsberg landslide can be understood and explained.

Tsunami Potential Prediction with Artificial Neural Network

Natural disasters are caused by biological factors such as earthquakes, tsunamis, and landslides. One of the destructive natural disasters that can cause considerable losses in terms of casualties and the economy is the tsunami. A tsunami is a series of tall or long waves in shallow seas. Various tsunami triggers include earthquakes, volcanic activity, and underwater landslides. This study aims to predict tsunamis with an Artificial Neural Network, which is a part of Machine Learning. Artificial Neural Network (ANN) is a model that has the same characteristics as biological neural networks. The process resembles the work of a neural network, which processes incoming information through neurons—using Multi-Layer Perceptron with five input parameters, two hidden layers, and one output. The ANN model can predict a tsunami potential in a country by 81%.

Large landslide of the hyperarid Central Western Andes triggered during a humid period of the Late Pleistocene (ca. 19°S; northern Chile)

AbstractThe western flank of the Central Andes offers a unique geomorphological record of large paleolandslides that are well preserved on long time‐scales (i.e. ≥Pleistocene) due to the long‐lasting aridity of this region. However, the lack of chronological constraints on those landslides limits our understanding of the respective role of tectonics and climate on their triggering. Here, we report new 10Be surface exposure dating obtained on one of those giant slope‐failures: the Limaxina landslide (northern Chile, 19°S). Five tightly grouped exposure‐ages (one outlier discarded) point to a single landslide failure at 80 ± 4 ka. This timing being consistent with others local records of a wet episode in the Atacama Desert, it suggests a primary role of climate‐forcing on landslide activity in this region, calling to further slope failures dating in the arid Central western Andes to explore landscapes responses to Quaternary climate oscillations and extreme events.

Landslide mechanism and stability of an open-pit slope: The Manglai open-pit coal mine

A clear understanding of landslide mechanisms and stability analyses is of great significance for landslide monitoring, prediction, and control. A large-scale end wall landslide occurred and its area reached 47,752 m2 on August 7–20, 2020, in the Manglai open-pit coal mine, China. In this paper, the engineering geological survey, mechanical test, large-deformation finite element numerical method, limit equilibrium method and analytical formula are used to analyze how the groundwater level rise caused this end wall failure and landslide. The engineering geological conditions, hydrogeological conditions, landslide activity signs and physical and mechanical parameter calibration of the sliding mass are investigated in detail and tested. Three-dimensional and two-dimensional numerical models of slopes are established, and an analytical formula calculation method to calculate the factor of safety (FoS) is proposed when sliding cracks are located on the top and toe of a slope. The results indicate that the fault fracture zone, soft strata, continuous heavy rainfall, and groundwater were the main contributors to this landslide. The three-dimensional numerical calculation results are consistent with the deformation and failure process of the slope observed in the field, which shows a retrogressive progressive failure mode. The calculation results of SLOPE/W and the analytical formula are consistent; i.e., when the groundwater level rises to +950, the stability of the end wall reaches the critical stability state. With the passage of time, the creep of the sliding surface accelerates until the entire end wall landslide.

Inclinometer and Improved SBAS Methods with a Random Forest for Monitoring Landslides and Anchor Degradation in Otoyo Town, Japan

Kochi Prefecture is located in an active zone of Japan that is frequently subjected to landslides due to heavy precipitation in typhoon seasons. Slow-moving landslides have been reported by both the local prefectural authorities and the National Government of Japan. We observed landslide movements in Otoyo Town by using ground- and satellite-based tools. Despite the high cost of establishing a borehole inclinometer survey to obtain accurate ground-based measurements, no previous InSAR study has been conducted in Otoyo Town, and the capacity for regional discrimination between active and inactive slow-moving landslides when using these tools remains unclear. We found that the horizontal velocity component was dominant at a rate of 21.4 mm/year across the whole of Otoyo Town. Satellite-based monitoring of ground-anchor efficiency may be possible in combination with ground-based inclinometer surveys. Three types of land cover are present in the study area—urban, field, and forests—and we selected a random forest (RF) model to extract low-coherence pixels by using optical and radar satellite sensors to identify important features and precisely remove pixels causing decorrelation. Long-term monitoring results from ground-based surveys, including inclinometer (boreholes) and anchor tension distribution data, were compared with the results of synthetic radar by using coherence-based small baseline subset (CB-SBAS) measurements. Generally, landslide occurrence was investigated across the whole of Otoyo Town, and we specifically evaluated the reliability of InSAR measurements in the Kawai landslide as a study site scale. The activity of the Kawai landslide channel was evaluated with borehole inclinometer displacement measurements (15.46 mm) and an anchor pressure survey (736 kN) from 2016 to 2019, as well as the steady state of the area (1.7 mm for the borehole inclinometer and 175 kN for the anchor pressure measurements), although a high cumulative precipitation of 3520 mm was reached during 2020 due to the ground anchor efficiency, which showed a consistent tendency with respect to the InSAR displacement measurements (14 mm during 2018 and 2019 and 0.7 mm during 2020). This comparison showed a consistent time-series displacement correlation, which was strengthened after introducing the RF mask into the analysis procedure, as the RF model correction reduced the standard deviation from the line-of-sight (LoS) average velocity estimation by 1.9 mm/year. Our research will help mitigate landslide impacts in Otoyo Town and its surroundings.

Anatomical growth response of Fagus sylvatica L. to landslide movements

Determining the age of landslide events is crucial for determining landslide risk, triggers, and also for predicting future landslide occurrence. Currently, the most accurate method for dating historical landslide events is dendrogeomorphic analysis. Unfortunately, the standard use of macroscopic growth responses of damaged trees for dating landslide activity suffers from many shortcomings. Thus, the aim of this study is to analyze in detail the growth response of trees to landslide movements at the anatomical level, a completely groundbreaking methodological approach. Ten specimens of European beech (Fagus sylvatica L.) were analyzed at two sampling heights, growing in two morphologically contrasting zones of the landslide area. Detailed anatomical analysis was focused on changes in morphometric parameters of the vessels and in the number of radial rays. The period (2008–2012) with the occurrence of the largest landslide movement (2010) recorded by long-term monitoring was analyzed. The results obtained revealed different anatomical responses in trees growing in different morphological zones of landslide. The tree responses on the ridge corresponded to the manifestations of tension wood formation, which corresponded to the stem tilting due to the landslide block movement. In the case of the trees in the trenches, root damage due to the subsidence of the landslide block blocked the flux of phytohormones, and their accumulation caused a significant reduction in the parameters of vessels and an increase in the number of rays. The study also includes recommendations in the future application of anatomical analyses in landslide research resulting from the obtained results. Thus, the obtained findings will improve the acquisition of chronological data for the purpose of landslide risk assessment.

The spatial relationship between landslide and land use activities in Langat River Basin: A case study

Landslide is a natural hazard that occurs all over the world and can cause enormous damage to the environment and human life. The developing countries are not spared from dealing with the issue of landslides where land use activities are recognised as one of the most triggering factors of landslide occurrences. In this study, investigation on spatial relationship was performed between landslide occurrences and land use activities at Langat River Basin. Landslide spatial distribution was determined using land use activities for the year 2021. The land use map was generated using supervised classification by Artificial Neural Network (ANN) approach. In addition, the accuracy assessment was applied using Kappa coefficient to validate the land use classification. A total of 70 historical landslide points was used to analyse the spatial relationship between landslide and land use activities. Based on the results, land use category at Langat River Basin was dominated by agriculture with 59.65%. The overall accuracy for land use classification was 90.81% and kappa coefficient was 0.88. Meanwhile, the spatial relationship between landslide occurrence and land use activities was higher in the built-up area with 48.57%. The growing population and economic sector in Langat River Basin were found to be contributing to the increase in built-up areas. Thus, these results are particularly useful in understanding the spatial relationship between landslide occurrence and land use activities where the development area is more vulnerable to facing landslide disasters. These findings will also help the government to achieve the agenda for Sustainable Development Goal (SDG) 2030 as highlighted to mitigate the risk of natural disasters.

Increasing landslide activity in the Taxkorgan River Basin (eastern Pamirs Plateau, China) driven by climate change

Global warming promotes glacier retreat, snow melting, and permafrost thawing, thereby increasing landslide activity in alpine mountain regions. However, our understanding of the effects of climate change on landslides is restricted by the sparse nature of landslide records. In this study, taking the Taxkorgan River basin in the eastern Pamirs as the study area, we assessed the interaction between landslides and climate change over the past 20 years using a reconstructed landslide inventory and a set of downscaled meteorological data, and we projected the future impacts of climate change on landslide activity. From 2000 to 2019, the number of landslides increased exponentially under global warming. Especially in 2000 and 2014, the abrupt increases in temperature and precipitation caused a more significant increase in the number of landslides. Ninety-four percent of the landslides occurred in the warm season (April to October), which is attributed to the diminishing snow cover in the warm season and the increase in the annual snow cover variation. Spatially, the increase in the number of landslides with elevation was due to the increase in the rate of temperature rise, suggesting that the high-elevation region (4500 m above sea level) responds more significantly to climate change and is more susceptible to landslides. The future climate is predicted to exhibit a warming and wetting trend, which will likely induce more frequent landslides for some time. We suggest that in alpine mountain areas, there is an urgent need to improve the comprehensive ground observation network and reveal the underlying relationship between the variable climate and landslides using multiple datasets, which would contribute to the accurate assessment of the risks posed by landslides induced by climate change and the adequate management of this risk under the warming climate in the future.

Landslide monitoring techniques in the Geological Surveys of Europe

Landslide monitoring is a mandatory step in landslide risk assessment. It requires collecting data on landslide conditions (e.g., areal extent, landslide kinematics, surface topography, hydrogeometeorological parameters, and failure surfaces) from different time periods and at different scales, from site-specific to local, regional, and national, to assess landslide activity. In this analysis, we collected information on landslide monitoring techniques from 17 members of the Earth Observation and Geohazards Expert Group (from EuroGeoSurveys) deployed between 2005 and 2021. We examined the types of the 75 recorded landslides, the landslide techniques, spatial resolution, temporal resolution, status of the technique (operational, non-operational), time of using (before the event, during the event, after the event), and the applicability of the technique in early warning systems. The research does not indicate the accuracy of each technique but, rather, the extent to which Geological Surveys conduct landslide monitoring and the predominant techniques used. Among the types of landslides, earth slides predominate and are mostly monitored by geological and engineering geological mapping. The results showed that Geological Surveys mostly utilized more traditional monitoring techniques since they have a broad mandate to collect geological data. In addition, this paper provides new insights into the role of the Geological Surveys on landslide monitoring in Europe and contributes to landslide risk reduction initiatives and commitments (e.g., the Kyoto Landslide Commitment 2020).