Large scale simulation of watershed mass transport – a case study of Tsengwen reservoir watershed

The Tenth International Symposium on Mitigation of Geo-disasters in Asia Matsue Symposium Place: Shimane Civil Center, Matsue Date: 8 October 2012We present the large scale simulation of watershed mass transport, including landslide, debris-flow and sediment transport. A case study of Tsengwen reservoir watershed under the extreme rainfall triggered by typhoon Morakot is simulated for verification. This approach starts with volume-area relationship formula with inventory method to predict temporal and regional landslide volume production and distribution. Then, debris flow model, Debris-2D, is used to simulate the mass transport of debris-flow from hillslope to fluvial channel. Finally a sediment transport model, NETSTARS, is used for hydraulic and sediment routing in river and reservoir. The integrated simulation for the whole watershed gives a very good agreement with the temporal variation of sediment concentration recorded at the very downstream location

Landslides in the Mailuu-Suu Valley, Kyrgyzstan—Hazards and Impacts

Mailuu-Suu is a former uranium mining area in Kyrgyzstan (Central Asia) at the northern border of the Fergana Basin. This region is particularly prone to landslide hazards and, during the last 50 years, has experienced severe landslide disasters in the vicinity of numerous nuclear waste tailing dams. Due to its critical situation, the Mailuu-Suu region was and still is the target area for several risk assessment projects. This paper provides a brief review of previous studies, past landslide events and a discussion on possible future risk scenarios. Various aspects of landslide hazard and related impacts in the Mailuu-Suu Valley are analyzed in detail: landslide susceptibility, historical evolution of landslide activity, size-frequency relationship, river damming and flooding as well as impacts on inhabited areas and nuclear waste storage zones. The study was carried out with standard remote sensing tools for the processing of satellite imagery and the construction of digital elevation models (DEMs). The processed inputs were combined on a GIS platform with digital landslide distribution maps of 1962, 1977, and 2003, digitized geological and geographic maps, and information from landslide monitoring and geophysical investigation. As a result, various types of landslide susceptibility maps based on conditional analysis (CA) are presented as well as predictions of future landslide activity and related damming potential and their possible impact on the population. For some risk scenarios, remediation and prevention measures are suggeste

Probabilistic analysis and mapping of seismically induced landslide deformation in Oregon

Landslides are ubiquitous within the state of Oregon, imposing an annual estimated cost of more than $10 million. Weak, saturated soils at steep slopes combined with persistent rainfall throughout most of the year provide a dangerous environment for this natural disaster, particularly in western Oregon. This grim situation is intensified by the presence of the Cascadia Subduction Zone, which is capable of generating large and powerful earthquakes. This thesis presents a fully probabilistic method for regional seismically-induced landslide hazard analysis and mapping, which considers the most current predictions for strong ground motions and seismic sources through deaggregation of the USGS next generation attenuation (NGA) seismic hazard curves in conjunction with topographic, geologic, and other geospatial information. The landslide triggering analysis is integrated into the probability chain and performed using Newmark's sliding block method. In order to estimate strength parameters for each lithological unit, which are difficult to obtain in detail for such a large area, estimated friction angle histograms were derived for each unit based on the terrain slope at locations of previously mapped landslides within the unit. Next, predictive displacement regression models suitable for regional assessment were integrated into the probability chain to calculate the probability of exceedance for specific displacement thresholds (0.1, 0.3, 1.0, 10, 100 m) relevant to engineering and planning purposes. The landslide triggering probability map was validated by previously reported landslides (The Statewide Landslide Inventory Database of Oregon, SLIDO), where more than 99.8% of these landslides fall in "very high" category of hazard level on the landslide triggering map. The created maps are suitable for regional resilience and planning studies by various agencies as well as integration with other hazard maps for risk assessment. The maps can also be used to guide geotechnical investigation, but they should not be used in place of a site-specific analysis

The SLIP model: A major step towards the application in real time civil protection integrated platforms for landslide prevention.

This work has focused on validating, on a large scale, the physically based model, named SLIP (Shallow Landslide Instability Prediction) for its future application in real time civil protection integrated platforms, after almost 15 years from its first formulation. Many works have been carried out by our research group using this model to back analyze occurred events and with the correct calibration of its input data the model always gave good results. In this thesis a further validation on various aspects of the model have been carried out from the prediction of instability of simulated landslides in laboratory flume tests to a real scale analysis. Particularly SLIP has been used to model two case studies, namely the landslide event that hit the Parma Apennines in April 2013 and the event of Giampilieri (ME) occurred the 1st October of 2009. In the first study case a large gathering of information was carried out from both in situ measurements and laboratory tests on the landslides and its soil. Thanks to an already known background for this type of soil, studied in previous works of our research group, the modeling gave good predictive capability. A new technique that extracted spatial land cover classes from pre-event flight images was consequently used. There was a clear improvement in the overall accuracy of the model between the cases in which this differentiation was used and not showing how a better spatial variation of parameters can improve the model predictive capacity. From a temporal stand point both the parameter sets give excellent results remarking the instability pattern that witnesses and local news provided. The results highlight a good prediction although there is a high over prediction ratio in the first set, and some false alerts in the second set. These problems can be related to an incomplete landslide database and spatial errors due to the absence of post event images. The calibration of the input parameters of the Giampilieri event was made by laboratory geotechnical characterization, numerical models for hydraulic parameters and by simulating in a small scale flume the triggering of landslides. Flume tests can be used for multiple purposes, such as to evaluate in back-analysis the initial soil conditions of a reference landslide event, but also to define several input parameters of SLIP model, as well as to analyze in detail the triggering mechanisms of the material potentially susceptible to shallow landslides. Furthermore, the apparatus used in this study is not complex or expensive. With the correct expedients, such as insertion of macro channels, the flume can be used to simulate the real case and to model hypothetical scenarios before they occur in real slopes. The outcome of flume tests underlines the influence of initial soil conditions on times and modalities of slope failure, as well as indicating how a variable rainfall input produces an increase of water infiltration compared to a constant one of same cumulative depth. The output of two models, SLIP and TRIGRS, a well established model, are shown. The results indicate that the models reconstruct quite well the event, both in terms of temporal evolution and spatial distribution of slope instability, and identify substantially the same areas mostly affected by shallow landslides. The comparison confirms the good predictive capability of the SLIP physically-based model, considering that the two maps converge to the same solution in large part of the study area, although SLIP overestimates spatially the instability while TRIGRS underestimates the landslide occurrence and slightly overestimates temporally the duration of the landslide event. SLIP is a more simple model than TRIGRS requiring less input parameters. The results of a two-year daily analysis are shown only using the SLIP model because a yearly analysis with TRIGRS would require elevated computational time. The results show haw the model well predicts instability capturing both the reported events of this time span and producing only one false alert. SLIP model returns the results in a few minutes for large areas. This means that updated triggering scenario maps can be obtained substantially in real-time. This feature is obviously essential considering a possible integration of the approach with an early warning system. Furthermore, if SLIP model was used in this way, it would operate with rainfall inputs forecasted for the next hours, then much more reliable than those estimated with a statistical analysis of historical rainfall data which, furthermore, are not always available for a specific area. Overall, if coupled with forecasted rainfall maps the model could be used as a preliminary early warning system for landslides and could be used to simulate landslide susceptibility over large areas with different rainfall scenarios

Probabilistic Geospatial Analyses, Uncertainty Modeling, and Mapping of Seismically-induced Ground Failures

Ground failures, in particular landsliding, liquefaction and lateral spreading can be triggered by seismic sources. The frequency, magnitude, and impact of these ground failures are highly dependent on the topography and geology of the site including its slope, depositional environment, and geotechnical properties as well as the proximity of the site to seismic sources. Many available models for estimating these variables have high epistemic uncertainty given the extreme challenge to fully characterize seismic sources and subsurface conditions. Nevertheless, this high uncertainty must be considered when mapping ground failure hazards for a large area using geologic, geotechnical, topographical, and seismic hazard data of limited availability.Many hazard maps do not fully consider uncertainty from the seismic sources, subsurface testing, and empirical models developed for estimating ground failures. Often, previously developed maps are qualitative based on judgment due to the lack of detailed subsurface geotechnical investigations.This research presents new mapping methods to address these challenges, resulting in ground failure hazard maps for evaluation and risk assessment. It explores both deterministic and probabilistic methods of mapping ground failure hazards for large study areas. Available geospatial data are incorporated in this research including digital elevation models (DEMs) acquired from lidar and photogrammetric data, DEM derivatives such as slope, geologic mapping, shear wave velocity tests and other geotechnical subsurface investigations, and seismic hazard curves.First, efficient algorithms were developed to map estimates of the peak ground acceleration, landslide and liquefaction triggering probability, and horizontal displacement as a result of landslides or lateral spreading across the state of Oregon for several earthquake scenarios associated with the Cascadia Subduction Zone (CSZ). These algorithms utilize site classification and site geology maps provided by the Oregon Department of Geology and Mineral Industries (DOGAMI).Second, a performance-based, landslide-induced, displacement hazard mapping technique is proposed and implemented for Western Oregon. This approach computes landslide displacement hazard curves across the regional area. The approach utilizes a detailed landslide inventory database and high-resolution topographical data to estimate the soil strength and associated uncertainty in the general geologic units. Third, in an effort to characterize the uncertainty of the geotechnical properties of geologic units, a geospatial geotechnical database was developed and evaluated. In this evaluation, available geologic maps and geotechnical subsurface databases from three counties in the State of Utah were compiled. Then, several distributions of geotechnical properties for the general geologic units were developed, and these distributions enabled the determination of which geologic units were most susceptible to liquefaction and lateral spreading. A statistical approach was also developed to provide a framework for simplifying geologic units based on soil properties.Lastly, a new and fully probabilistic framework is developed for mapping the liquefaction-induced lateral spread displacement hazard at a regional scale. This framework is demonstrated by producing lateral spread hazard maps for Utah County, Utah. By performing numerous Monte Carlo simulations, the method accounts for uncertainties in the soil properties, seismic loading, and the empirical models for predicting horizontal displacements due to lateral spreading.Keywords: Liquefaction, Ground Failure, Landslide, Lateral Spreading, Earthquake, Hazard Mappin

Slope stability assessments considering material inhomogeneity

This research applies the finite element finite element upper bound and lower bound limit analysis methods to evaluate in-homogeneous soil and rock slope stability problems, which can help improve current slope designs. To make slope safety assessments more direct and accurate

Regional and Site-Specific Vulnerabilities of the Western Power Grid from a M9.3 Cascadia Subduction Zone Earthquake

The likelihood of a Cascadia Subduction Zone (CSZ) earthquake is estimated between 37 to 42% in the next 50 years, leading to strong shaking, liquefaction, landsliding, and other seismic ground failure resulting in major impacts to critical lifelines such as the western power grid. Electrical power is essential for continued functionality of emergency services, economic recovery, and other basic, essential needs such as water and fuel supply, wastewater treatment, and communications. Hence, understanding the extent of damage to the power grid from a CSZ event is critical. The objective of this research, part of a broader study identifying the seismic resilience of the western power grid, is to assess the vulnerabilities of the synthetic western power grid by quantifying the likelihood and magnitude of seismically induced landslide occurrence to determine the effects of those displacements on electrical transmission poles and towers at a regional scale. To this end, this thesis presents a probabilistic method for a regional seismic landslide hazard analysis and map for the Western United States based on the USGS M9.3 Megathrust CSZ scenario earthquake with consideration of topographic, geologic, and other geospatial information. The landslide triggering analysis completed uses several empirical seismic displacement prediction models based on the Newmark sliding block method, which are calibrated using strength parameters for each geological unit based on the terrain slope at locations of previously mapped landslides within the unit. A predictive displacement regression model, LOS21 was developed using a logic tree scheme that weights the individual models based on the suitability of the model to this regional assessment. The LOS21 model was used to calculate the probability of exceedance of specific thresholds (e.g., 5%, 15% and 50%) to evaluate potential impacts to the power grid. Electrical infrastructure located west of the Cascades in Washington, Oregon, and Northern California were determined to be subjected to the highest risk of landslide-induced damage. To provide context to the broader study focusing on non-landslide-induced impacts to the western power grid (e.g., ground shaking and inertial equipment loading), an evaluation site was characterized for a detailed site-specific site response analyses to evaluate the differences in amplification between equivalent linear and nonlinear, total stress analyses using ten ground motions pairs scaled and matched to the USGS seismic scenario hazard. The results of the site-specific site response analysis are used to evaluate the potential impact to the electrical components for the substation at the evaluation site for comparison to the seismic hazard developed using the regional map. The equivalent linear and the nonlinear approach produced PGA amplification results that were lower from the USGS seismic scenario hazard by 6% and 32%, respectively. The maps created are suitable for regional resilience and planning and to guide geotechnical investigations but should not be used in place of site-specific analysis for engineering design purposes