Slow-moving Landslides Research Articles

River channel width controls blocking by slow-moving landslides in California's Franciscan mélange

Abstract. To explore the sensitivity of rivers to blocking from landslide debris, we exploit two similar geomorphic settings in California's Franciscan mélange where slow-moving landslides, often referred to as earthflows, impinge on river channels with drainage areas that differ by a factor of 30. Analysis of valley widths and river long profiles over ∼19 km of Alameda Creek (185 km2 drainage area) and Arroyo Hondo (200 km2 drainage area) in central California shows a very consistent picture in which earthflows that intersect these channels force tens of meters of gravel aggradation for kilometers upstream, leading to apparently long-lived sediment storage and channel burial at these sites. In contrast, over a ∼30 km section of the Eel River (5547 km2 drainage area), there are no knickpoints or aggradation upstream of locations where earthflows impinge on its channel. Hydraulic and hydrologic data from United States Geological Survey (USGS) gages on Arroyo Hondo and the Eel River, combined with measured size distributions of boulders input by landslides for both locations, suggest that landslide derived boulders are not mobile at either site during the largest floods (>2-year recurrence) with field-measured flow depths. We therefore argue that boulder transport capacity is an unlikely explanation for the observed difference in sensitivity to landslide inputs. At the same time, we find that earthflow fluxes per unit channel width are nearly identical for Oak Ridge earthflow on Arroyo Hondo, where evidence for blocking is clear, and for the Boulder Creek earthflow on the Eel River, where evidence for blocking is absent. These observations suggest that boulder supply is also an unlikely explanation for the observed morphological differences along the two rivers. Instead, we argue that the dramatically different sensitivity of the two locations to landslide blocking is related to differences in channel width relative to typical seasonal displacements of earthflows. A synthesis of seasonal earthflow displacements in the Franciscan mélange shows that the channel width of the Eel River is ∼5 times larger than the largest annual seasonal displacement. In contrast, during wet winters, earthflows are capable of crossing the entire channel width of Arroyo Hondo and Alameda Creek. In support of this interpretation, satellite imagery shows that immobile earthflow-derived boulders are generally confined to the edges of the channel on the Eel River. By contrast, immobile earthflow-derived boulders jam the entire channel on Arroyo Hondo. Our results imply that lower drainage area reaches of earthflow-dominated catchments may be particularly prone to blocking. By inhibiting the upstream propagation of base-level signals, valley-blocking earthflows may therefore promote the formation of so-called “relict topography”.

Assessment of building behavior in slow-moving landslide-affected areas through DInSAR data and structural analysis

Slow-moving landslides are a natural hazard which affects wide areas in the world and often are cause of significant damage to structures and infrastructures. Analysis of landslide evolution and of their interaction with existing man-made structures plays a key role in risk prevention and mitigation activities. To this purpose, a considerable interest towards innovative approaches has grown among the scientific community and land management institutions. In this work, Synthetic Aperture Radar data acquired by C-band and X-band sensors, combined with numerical analyses, have been successfully applied as a tool to detect spatial and temporal landslide-induced effects, in terms of deformations and structural behavior of a building affected by ground instability. Such approach has been applied to Moio della Civitella urban settlement (Salerno province, Italy), whose whole territory is interested by several slow-moving landslides. In detail, performance of a masonry building aggregate and the efficacy of restoration works have been investigated through an integrated assessment of displacement time-series pre- and post-repair intervention, and structural analysis performed with numerical code.Historical DInSAR data have permitted firstly the interpretation of building displacement time-series corresponding to pre- and post-works configurations; subsequently, the analysis of interpolated interferometric products has allowed to define gradient maps of vertical and horizontal displacements and to identify part of aggregate which can suffer a greater susceptibility to damage as a consequence of deformation gradients. Finally, the comparison of satellite and numerical data showed a substantial agreement with local failures and damage surveyed, thus confirming the capability of DInSAR technique to investigate building performance where no in situ displacement measurements were available.

Analysis of Various Kinds Characteristics on Slow-moving Landslide in Pohang-si Area

Analysis of Various Kinds Characteristics on Slow-moving Landslide in Pohang-si Area

A-DInSAR Performance for Updating Landslide Inventory in Mountain Areas: An Example from Lombardy Region (Italy)

This work focuses on the capabilities and limitations of the Advanced Satellite SAR (Synthetic Aperture Radar) Interferometry (A-DInSAR) in wooded and mountainous regions, with the aim to get insights on the performances for studying slow-moving landslides. The considered critical issues are related to the SAR acquisition geometries (angle of incidence of the satellite line of sight, ascending and descending geometries) and to the physical and morphological features of the slopes (land use, aspect and slope angles), which influence the measuring points coverage. 26 areas in Lombardy Region (Italy), affected by known slope instability phenomena, have been analyzed through A-DInSAR technique, using COSMO-SkyMed images. The results allowed to outline general considerations about the effectiveness of A-DInSAR analysis of a single dataset (descending or ascending dataset), selected accordingly to the aspect of the slopes. Moreover, we aimed to quantitatively describe the capability to update the state of activity of several previously mapped landslides using satellite SAR Interferometry results. Although in a wooded and mountainous region, where the chances of retrieving radar targets for satellite SAR analysis are generally low, the A-DInSAR results have allowed to detect landslides’ reactivations or new landslides and to update the inventory for about 70% of the investigated areas.

Rainfall Kick-Starts Slow-Moving Landslides

A census of hundreds of slow-moving landslides in Northern California reveals an uptick in the number and speed of landslides in 2017, the second-wettest year on record.

Landslides detection through optimized hot spot analysis on persistent scatterers and distributed scatterers

Long-term InSAR techniques, such as Persistent Scatterer Interferometry and Distributed Scatterer Interferometry, are effective approaches able to detect slow-moving landslides with millimeter precision. This study presents a novel approach of optimized hot spot analysis (OHSA) on persistent scatterers (PS) and distributed scatterers (DS), and evaluates its performance on detection of landslides across the Volterra area in central Tuscany region of Italy. 1625 ascending and 2536 descending PS processed from eight years (2003–2010) of ENVISAT images were produced by the PS-InSAR technique. In addition, 16,493 ascending and 9746 descending PS/DS measurement points (MP) processed from four years (2011–2014 for ascending orbits and 2010–2013 for descending orbits) of COSMO-SkyMed images were collected by the SqueeSAR approach. The OHSA approach was then implemented on the derived PS and DS through the analysis of incremental spatial autocorrelation and the Getis-Ord Gi* statistics. As a result of OHSA, PS and DS MP that are statistically significant with velocity >|±2| mm/year, p-value < 0.01 and z-score >|±2.58| were recognized as hot spots (HS). Meanwhile, a landslide inventory covering the Volterra area was manually prepared as the reference data for accuracy assessment of landslide detection. The results indicate that, in terms of OHSA-derived ENVISAT HS, the detection accuracy can be improved from 23.3% to 25.3% and from 50.7% to 66.4%, with decreased redundancy from 5.3% to 3.7% and from 5.3% to 2.4%, for ascending and descending orbits, respectively. In addition, for OHSA-derived Cosmo-SkyMed HS, the detection accuracy can be improved from 57.7% to 70.3% and from 73.8% to 81.5%, with decreased redundancy from 3.1% to 1.7% and from 3.4% to 2.1%, for ascending and descending orbits, respectively. Compared to traditional HS analysis such as Persistent Scatterers Interferometry Hot Spot and Cluster Analysis (PSI-HCA), OHSA has the significant advantage that the scale distance used for the Getis-Ord Gi* statistics can be automatically determined by the analysis of incremental spatial autocorrelation and accordingly no manual intervention or additional digital terrain model (DTM) is further needed. The proposed method is very succinct and can be easily implemented in diverse geographic information system (GIS) platforms. To the best of our knowledge, this is the first time that OHSA has been applied to PS and DS.

Improved correction of seasonal tropospheric delay in InSAR observations for landslide deformation monitoring

Synthetic Aperture Radar Interferometry (InSAR) provides an effective tool to study slow-moving landslides. However, InSAR observations are often contaminated by tropospheric artefacts due to spatial and temporal variations of atmospheric refractivity. Particularly, the topography-dependent stratified delays may introduce seasonal oscillation biases into InSAR-measured deformation time series under steep terrains, which cannot be removed by conventional spatial and temporal filtering. In this study we proposed two complementary approaches to correct the stratified tropospheric delays for time series InSAR analysis when studying single landslides. One is the Iterative Linear Model (ILM) as an improved version of the traditional Linear Model (LM). The other is to fuse tropospheric delays predicted by several global weather models (FDWM) with different temporal intervals and spatial resolutions. Both methods are integrated into the standard Small BAseline Subset (SBAS) time series analysis procedure. We evaluated the proposed methods in three landslide-prone areas in southwest China using Sentinel-1 datasets. The experimental results demonstrated that the ILM method removed the seasonal stratified delays mixed in deformation time series, unaffected by the deforming points. The FDWM method achieved an optimal combination of tropospheric delay predictions by four weather models, i.e. ERA-Interim, ERA5, HRES ECMWF, and MERRA-2. Validations using in-situ GPS measurements suggested that the original Root Mean Squared (RMS) values of interferometric phases declined by more than 35% after both ILM and FDWM corrections. The ILM had better performances than the FDWM to correct stratified delay for single landslides, whereas the FDWM can be an effective alternative when the ILM is inapplicable in case of limited coherent points.

Modeling of Landslide–Tunnel Interaction: the Varco d’Izzo Case Study

This paper reports a case study of the interaction between a slow-moving landslide in clay soil and a railway tunnel protected by sheet pile walls, that crosses the landslide accumulation. The earthflow, that develops in the Southern Apennines, Italy, has been long studied and monitored by different organizations, such as the national railway company and the University of Basilicata. Since the investigated landslide and construction typologies are quite diffused in mountainous areas, the case study can be considered representative of a large number of other similar cases. Differently from other approaches proposed in the literature, the role of the landslide slip surface depth, changing in the directions longitudinal and transversal to the tunnel, and of structural connections, affecting the pile–tunnel system response, are accounted for in detail. Several numerical models are used to simulate the interaction between the sliding soil and tunnel. Different 2D and 3D geotechnical and structural models are adopted to reproduce stress–strain scenarios compatible with the experimental evidence. The modeling results indicate that the interaction varies considerably along the tunnel length because of the 3D geometry of the landslide, and is conditioned by the residual shear strength available on the slip surface. The expansion joints in the tunnel lining only marginally influence the stress in the structure because of the presence of the adjacent sheet pile walls, which enable considerable collaboration between the tunnel sectors.

Displacement mechanisms of slow-moving landslides in response to changes in porewater pressure and dynamic stress

Abstract. Although slow-moving landslides represent a substantial hazard, their detailed mechanisms are still comparatively poorly understood. We have conducted a suite of innovative laboratory experiments using novel equipment to simulate a range of porewater pressure and dynamic stress scenarios on samples collected from a slow-moving landslide complex in New Zealand. We have sought to understand how changes in porewater pressure and ground acceleration during earthquakes influence the movement patterns of slow-moving landslides. Our experiments show that during periods of elevated porewater pressure, displacement rates are influenced by two components: first an absolute stress state component (normal effective stress state) and second a transient stress state component (the rate of change of normal effective stress). During dynamic shear cycles, displacement rates are controlled by the extent to which the forces operating at the shear surface exceed the stress state at the yield acceleration point. The results indicate that during strong earthquake accelerations, strain will increase rapidly with relatively minor increases in the out-of-balance forces. Similar behaviour is seen for the generation of movement through increased porewater pressures. Our results show how the mechanisms of shear zone deformation control the movement patterns of large slow-moving translational landslides, and how they may be mobilised by strong earthquakes and significant rain events.

Slow-moving landslides interacting with the road network: Analysis of damage using ancillary data, in situ surveys and multi-source monitoring data

Slow-moving landslides are widespread natural hazards that can affect both social and economic activities causing damage to structures and infrastructure networks. This paper aims at providing an innovative simplified procedure to analyse road damage induced by slow-moving landslides based on the joint use of landslide inventory maps, a road damage database (collecting both the results of in-situ surveys and Google Street View images) and ground displacement measurements derived from the interferometric processing of satellite SAR images (DInSAR data). The procedure was applied to the case study of the Calabria region (southern Italy) following a two-scale approach. First, a regional-scale analysis was carried out to gather information on the level of road exposure (namely, Index of Exposed Roads) to slow-moving landslides in order to identify the most representative case studies. Then at local scale, relationships between road damage severity level and a selected parameter (i.e. differential settlement computed in two different ways) of slow-moving landslide intensity were derived for two road stretches that differ in geo-lithological and topographic conditions. The results underline the importance of the availability of both reliable landslide inventories and rich road damage databases as well as the potential of high-resolution DInSAR data for obtaining quantitative information on movement rates of roads useful to carry out in-depth studies pursing vulnerability analyses of the infrastructure.

Monitoring Ground Instabilities Using SAR Satellite Data: A Practical Approach

Satellite interferometric data are widely exploited for ground motion monitoring thanks to their wide area coverage, cost efficiency and non-invasiveness. The launch of the Sentinel-1 constellation opened new horizons for interferometric applications, allowing the scientists to rethink the way in which these data are delivered, passing from a static view of the territory to a continuous streaming of ground motion measurements from space. Tuscany Region is the first worldwide example of a regional scale monitoring system based on satellite interferometric data. The processing chain here exploited combines a multi-interferometric approach with a time-series data mining algorithm aimed at recognizing benchmarks with significant trend variations. The system is capable of detecting the temporal changes of a wide variety of phenomena such as slow-moving landslides and subsidence, producing a high amount of data to be interpreted in a short time. Bulletins and reports are derived to the hydrogeological risk management actors at regional scale. The final output of the project is a list of potentially hazardous and accelerating phenomena that are verified on site by field campaign by completing a sheet survey in order to qualitatively estimate the risk and to suggest short-term actions to be taken by local entities. Two case studies, one related to landslides and one to subsidence, are proposed to highlight the potential of the monitoring system to early detect anomalous ground changes. Both examples represent a successful implementation of satellite interferometric data as monitoring and risk management tools, raising the awareness of local and regional authorities to geohazards.

A multi-scale methodological approach for slow-moving landslide risk mitigation in urban areas, southern Italy

Several urban areas in Euro-Mediterranean countries are affected by slow-moving landslides that, even if rarely associated with the loss of human life, can cause damage to structures and infrastructure. In such contexts, the progressive decay of the built environment can bring along a generalized increase of the physical vulnerability and, as a result, slow-moving landslide risk increases over the time. Under these conditions, as long as suitable risk mitigation measures are lacking, the level of risk (also related to earthquakes) could turn out to be no longer acceptable within an a priori unknown time interval. This problem has a relevant social-economic impact, thus requiring the adoption of risk mitigation strategies that need to be effective and, at the same time, sustainable for the involved stakeholders. In this regard, this paper proposes a multi-scale methodological approach—based on the joint use of satellite-derived displacement monitoring data and the results of building damage surveys—whose applicability is tested with reference to urban areas affected by slow-moving landslides in Calabria region (southern Italy).

The Hejiapingzi landslide in Weining County, Guizhou Province, Southwest China: a recent slow-moving landslide triggered by reservoir drawdown

The Hejiapingzi landslide is a slow-moving landslide along the shore of the reservoir created by the Xiangbiling hydropower dam in Weining County, Guizhou Province, Southwest China. Movement caused cracks in the land surface and residential buildings of Heping village on 20 August 2017 and was triggered after an 8-day continuous drawdown of the reservoir water by 2.2 m. Field investigations and borehole and landslide surface monitoring were carried out to determine the landslide features and deformation characteristics. Based on analysis of the monitoring data, the behavior of the landslide was neither spatially nor temporally uniform. In general, it could not move quickly due to the gentle sliding surface. The possible reasons for landslide occurrence were the drawdown of the reservoir water, the increase in seepage force, and the loss of strength in a soft mudstone layer to form the landslide slip surface. Although mitigation measures, including engineering control or resident relocation to a safe place, have not yet been finally determined, some interim measures including covering landslide cracks, subsurface monitoring, decreasing the reservoir drawdown velocity, and setting velocity thresholds of landslide displacement for warnings are advised to reduce the landslide risk caused by planned reservoir drawdown in 2019.

Sparsity Optimization Method for Slow-Moving Landslides Detection in Satellite Image Time-Series

This paper presents a new method based on recent optimization technique to detect slow-moving landslides (<;150m/year) in time series of displacement field generated by satellite images. Sparse optimization is applied simultaneously on the 3-D data set in space as well as in time. The proposed method takes into account the distinctive signal physical properties in space and time, by enforcing a sparse representation by blocks in space, but a continuing and monotonous representation in time of the landslides. As a result, we show that a mixed ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> ,2-norm is the most suitable norm for this detection problem, compared to pure ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -norm or ℓ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -norm. Moreover, an outlier estimation step is included that sets apart the Gaussian noise from locally sparse processing errors in the data. The performance of this approach is tested by applying it both on synthetic data and on a time series of displacements fields over 16 dates in the Colca Valley, Peru. This detection presents commission and omission errors for landslides of 29% and 14%, respectively, using a medium resolution (10 m) data set of optical satellite images. It detects all important landslides, already known from field investigations. Moreover, it also points out other smaller or unknown landslides, increasing the existing slow-moving landslide inventory by +50%.

Multi-technique Geophysical Investigation of a Very Slow-moving Landslide near Ashcroft, British Columbia, Canada

Landslides in the Thompson River valley, British Columbia have the potential to adversely impact vital national railway infrastructure and operations, the natural environment, cultural heritage features, communities, public safety and the economy. To better manage geohazard risks in the primary national transportation corridor, government agencies, universities and railway industry partners are focusing research efforts on the Ripley Landslide, 7 km south of Ashcroft. The internal composition and structure of this very slow-moving landslide as revealed by geophysical surveys and terrain mapping provides contextual baseline data for interpreting slope stability monitoring results and guiding geohazard mitigation efforts. Terrestrial and waterborne geophysical surveys were undertaken using subsets of the following methods: electrical resistivity tomography, frequency electromagnetic conductivity, ground penetrating radar, primary-wave refraction and multispectral analysis of shear-waves, natural gamma radiation, induction conductivity and magnetic susceptibility. Small and irregular anomalies, areas of complex subsurface geometry and groundwater-rich zones are resolved along all terrestrial geophysical survey lines. Terrain mapping and geophysical surveys indicate a high relief bedrock sub-surface overlain by a 10 m to &gt;30 m thick package of complex fine-grained sediments containing groundwater. Planar sub-surface features revealed in surface exposures, borehole logs and geophysical profiles include tabular bedding and terrain unit contacts. Profiles also show discrete curvilinear features interpreted as rotational-translational failure planes in clay-rich beds in the main body of the slide beneath the rail ballast and retaining wall. Integrating data from surficial geology mapping and an array of geophysical methods provided significantly more information than any one technique on its own.

Integrated risk assessment due to slope instabilities in the roadway network of Gipuzkoa, Basque Country

Abstract. Transportation corridors such as roadways are often subjected to both natural instability and cut-slope failures, with substantial physical damage to the road infrastructure and threats to the circulating vehicles and passengers. In the early 2000s, the Gipuzkoa Provincial Council of the Basque Country in Spain noted the need for assessing the risk related to the geotechnical hazards of its road network, in order to assess and monitor their safety for road users. The quantitative risk assessment (QRA) was selected as a tool for comparing the risk of different hazards on an objective basis. Few examples of multi-hazard risk assessment along transportation corridors exist. The methodology presented here consists of the calculation of risk, in terms of probability of failure and its respective consequences, and it was applied to 84 selected points of risk (PoR) over the entire road network managed by the Gipuzkoa Provincial Council. The types of encountered slope instabilities that are examined are rockfalls, retaining-wall failures, and slow-moving landslides. The proposed methodology includes the calculation of the probability of failure for each hazard based on an extensive collection of field data, and its association with the expected consequences. Instrumentation data from load cells and inclinometers were used for the anchored walls and the slow-moving landslides, respectively. The expected road damage was assessed for each hazard level in terms of a fixed unit cost (UC). The results indicate that the risk can be comparable for the different hazards. A total of 21 % of the PoR in the study area were found to be of very high risk.

Application of multi-dimensional electrical resistivity tomography datasets to investigate a very slow-moving landslide near Ashcroft, British Columbia, Canada

Landslides in the Thompson River valley, British Columbia, Canada, have historically impacted vital transportation infrastructure, the environment and natural resources, cultural heritage features, communities, public safety, and the economy. To better understand and manage geohazard risks in Canada’s primary national railway corridor, government agencies, universities, and railway industry partners are focusing research efforts on Ripley Landslide, 7 km south of Ashcroft. Electrical resistivity tomography (ERT) datasets collected in November 2013 (on land) and November 2014 (over water) were successfully combined and inverted into a pseudo-3D model that produced significantly deeper resistivity values than previously available in 2D profiles. The lithology, degree of saturation, porosity, presence of dissolved electrolytes, and temperature all influence electrical resistivity of earth materials in the landslide. Continuous (real-time) ERT monitoring began in November 2017 to characterize the long-term hydrological behavior of geological units in the landslide. Seventy-two electrodes were positioned in two arrays across the slide body and connected to a proactive infrastructure monitoring and evaluation (PRIME) system with internet access. PRIME resistivity results corroborate data from other geophysical techniques and hints at an unusual distribution pattern for surface moisture and groundwater in fractured bedrock and overlying clay-rich sediments containing vertical tension cracks and discrete sub-horizontal planar features interpreted as slide surfaces within pre-sheared zones. A greater understanding of the composition and internal structure of slope failures in the valley is gained at the site from terrain analysis and modeling of multi-dimensional geophysical datasets. This insight helps with the interpretation of multi-year monitoring datasets and will guide future efforts to record landslide activity in the valley, reducing stakeholder risks.

High-Resolution Spaceborne, Airborne and In Situ Landslide Kinematic Measurements of the Slumgullion Landslide in Southwest Colorado

The Slumgullion landslide, located in southwestern Colorado, has been active since the early 1700s and current data suggests that the most active portion of the slide creeps at a rate of ~1.5–2.0 cm/day. Accurate deformation measurement techniques are vital to the understanding of persistent, yet slow-moving landslides like the Slumgullion. The factors that affect slope movements at the Slumgullion are on-time scales that are well suited towards a remotely sensed approach to constrain the 12 different kinematic units that make up the persistent creeping landslide. We derive a time series of motion vectors (magnitude and direction) using subpixel offset techniques from very high resolution TerraSAR-X Staring Spotlight ascending/descending data as well as from a novel high-resolution amalgamation of airborne lidar and unmanned aerial systems (UAS) Structure from Motion (SfM) digital surface model (DSM) hillshades. Deformation rates calculated from the spaceborne and airborne datasets show high agreement (mean difference of ~0.9 mm/day), further highlighting the potential for the monitoring of ongoing mass wasting events utilizing unmanned aircraft systems (UAS) We compare pixel offset results from an 11-day synthetic aperture radar (SAR) pair acquired in July of 2016 with motion vectors from a coincident low-cost L1 only Global Navigation Satellite System (GNSS) field campaign in order to verify the remotely sensed results and to derive the accuracy of the azimuth and range offsets. We find that the average azimuth and range pixel offset accuracies utilizing the methods herein are on the order of 1/18 and 1/20 of their along-track and slant range focused ground pixel spacing values of 16.8 cm and 45.5 cm, respectively. We utilize the SAR offset time series to add a twelfth kinematic unit to the previously established set of eleven unique regions at the site of an established minislide within the main landslide itself. Lastly, we compare the calculated rates and direction from all spaceborne- and airborne-derived motion vectors for each of the established kinematic zones within the active portion of the landslide. These comparisons show an overall increased magnitude and across-track component (i.e., more westerly angles of motion) for the descending SAR data as compared to their ascending counterparts. The processing techniques and subsequent results herein provide for an improved knowledge of the Slumgullion landslide’s kinematics and this increased knowledge has implications for the advancement of measurement techniques and the understanding of globally distributed creeping landslides.

A non-linear damage rheological constitutive model and its application to a giant slow-moving landslide

Generation of a landslide is a typical aging process of rock and soil deformation. Therefore, it is a basic method and also a difficult problem to build constitutive models that reflect the deformation process of landslides and furthermore to use the models for prediction. However, many classical rheological models can only be used to describe the first and second creeping stages and are unable to describe the third accelerated stage. Base on the non-linear and aging characteristics of the slip zone soil during the shear creeping development and the damage theory, this paper attempts to construct a non-linear damage rheological constitutive model by combining a non-linear damage visco-plastic element with the CVISC rheological model built-in FLAC3D, namely the modified CVISC model. For implementing this modified CIVSC model in 3D numerical simulations, its 3D difference equations are developed. The numerical codes for the difference equations are programmed following the roles of the FLAC3D’s user interface program. This model is applied to simulation of the Xieliupo landslide, which is a long-term slow-moving landslide with intermittently intense movement. The results show that the modified CVISC model can disclose accelerated creeping of the landslide, which is roughly consistent with the movement history of the landslide. This gives an indication of the validity of the modified CVISC model based on non-linear damage theory.

Reconstructing movement history of frozen debris lobes in northern Alaska using satellite radar interferometry

Frozen debris lobes (FDLs) are slow-moving landslides along permafrost-affected slopes, and consist of soil, rock, organic debris, and areas of massive infiltration ice. Based on their proximity to the adjacent infrastructure, their size, and their flow dynamics, FDLs represent potential geohazards. Eight FDLs (FDL-A, -B, -C, -D, -4, -5, -7, -11) within the Dalton Highway corridor in the Brooks Range, Alaska, USA are the subject of this paper. We examined temporal and spatial variation of FDL displacement using medium-resolution Synthetic Aperture Radar (SAR) images and differential SAR Interferometry (dInSAR) techniques. European Remote Sensing satellite 1/2 (ERS 1/2) and Phased Array type L-band Synthetic Aperture Radar (PALSAR) acquisitions were used to generate coherent interferograms to study the displacement history of FDLs for 1995–1996 and 2006–2010. We conducted an initial assessment of the capability of satellite InSAR to monitor FDL movement depending on data resolution, season, and vegetation coverage, which also helped us to select useful interferograms. With multi-temporal interferometric displacement maps, we found that seven investigated FDLs (FDL-7 was excluded from this sub-experiment due to limited data coverage) demonstrated strong spatial and seasonal variations in their movement patterns, with maximum displacement rates typically occurring in October and minimum displacement rates during February or March, which is consistent with previously published field study results. Overall, through this study we: (1) delineated the active FDLs during the winter period using a wrapped PALSAR interferogram; (2) analyzed the spatial variation of the deformation field within each FDL body; (3) modeled the seasonal changes of FDL deformation rates through the analysis of multi-temporal ERS tandem interferograms; and (4) integrated InSAR-derived deformation rates with those obtained through historical imagery analysis to determine long-term deformation rates. Results from this study fill the gaps left in the historical imagery analysis and provide important seasonal and spatial deformation data, which are essential in the development of a mitigation plan as these features approach infrastructure. We also summarize our research experience studying these moving features using satellite radar interferometry and believe this can be useful for future studies of similar features.