Geohazards in the three Gorges Reservoir Area, China – Lessons learned from decades of research

Abstract The impoundment of the 660-km long reservoir behind the huge Three Gorges Dam, the world's largest hydropower station, increased regional seismicity and reactivated severe geohazards. Before the reservoir filling was initiated in 2003, the region had approximately two earthquakes per year with magnitudes between 3.0 and 4.9; after the full impoundment in 2008, approximately 14 earthquakes per year occurred with magnitudes between 3.0 and 5.4. In addition, hundreds of landslides were reactivated and are now in a state of intermittent creep. Many landslides exhibit step-like annual pattern of displacement in response to quasi-regular variations in seasonal rainfall and reservoir level. Additional problems include rock avalanches, impulse waves and debris flows. The seriousness of these events motivated numerous studies that resulted in 1) Better insight into the behavior and evolution mechanism of geohazards in the Three Gorges Reservoir Area (TGRA); 2) Implementation of monitoring and early-warning systems of geohazards; and 3) Design and construction of preventive countermeasures including lattice anchors, stabilizing piles, rock bolts, drainage canals and tunnels, and huge revetments. This paper reviews the hydro-geologic setting of TGRA geohazards, examines their occurrence and evolution in the past few decades, offers insight learned from extensive research on TGRA geohazards, and suggests topics for future research to address the remaining challenges

Robust Geotechnical Design – A New Design Perspective

In routine geotechnical engineering practice, the engineer has to work with a small sample of data due to budget constraint. Because of complexity of soil deposits, it is often difficult to determine correctly the statistics of soil parameters that are required for reliability-based design of foundations. Furthermore, the traditional reliability-based design is sensitive to the variation of noise factors such as uncertain soil parameters. To address this dilemma, the authors present a new design methodology, termed robust geotechnical design. This new design methodology aims to make the response of a geotechnical system immune to, or robust against, the variation of noise factors by carefully adjusting the design parameters. This methodology is realized through a multi-objective optimization, in which all the design requirements such as safety, robustness, and cost are explicitly considered. The results of such optimization are often expressed as a Pareto Front, which defines a trade-off relationship between cost and robustness, whereas safety is guaranteed. This enables the engineer to make an informed design decision according to a target cost or robustness. The significance of new design methodology is illustrated with an example of shallow foundation design

Geohazards and human settlements: Lessons learned from multiple relocation events in Badong, China – Engineering geologist's perspective

Abstract Mountainous regions are inherently susceptible to geohazards, such as landslides and debris flows, with the threat of natural disasters compounded by human activities (mainly settlements). Lessons learned from past events that involved the interactions between human activities and geohazards are helpful for future site selections of human settlements in mountainous regions. To this end, the events associated with county seat relocations in Badong, a typical county in the Three Gorges Reservoir region, China, are studied from an engineering geologist's perspective. Over its history, the county seat was relocated multiple times, with the first relocation traced back to the Song dynasty (960–1279 CE) and the last two relocations linked to the Three Gorges Dam project. By studying geohazards and their interactions with human activities in these county-seat relocations, and through the reconstruction of these events, we secure insights into decision-making for these events. As part of the reconstruction of these relocation events, we analyze a giant pre-historic landslide, whose discovery ultimately prompted the third relocation. Using the case history of this landslide, we also discuss and emphasize the importance of proactive monitoring of geohazards for disaster resilience enhancement, recognizing that our knowledge of nature is vastly incomplete

Soil Liquefaction and Ground Settlement in Chi-Chi Taiwan, Earthquake

This paper presents an investigation of soil liquefaction and ground settlement in the 1999 Chi-Chi, Taiwan, earthquake. The quake killed more than 2400 people and caused a great destruction to buildings, bridges, dams, highways and railways. One of the causes for heavy damages to the structures is soil liquefaction and ground settlement during the earthquake. Six sites that were observed to experience liquefaction are investigated through cone penetration testing (CPT), and the liquefaction potential of each site and the settlement of the liquefied soil strata are analyzed

Probability-Based Liquefaction Evaluation Using Shear Wave Velocity Measurements

Three preliminary probability-based models and one artificial neural network model for evaluating soil liquefaction potential using shear wave velocity measurements are presented and compared with the deterministic curves developed by Andrus et al. The probability models are developed using logistic regression and Bayesian techniques applied to the same case history data used to develop the deterministic curves. The case history data consists of in situ shear wave velocity measurements at over 70 sites and field performance data from 26 earthquakes. The artificial neural network model is a high-order function capable of tracking the irregular boundary separating individual liquefaction and no liquefaction case histories. From the logistic regression and Bayesian models, the deterministic curve is characterized with a probability of about 30 %. This finding indicates that the shear wave-based deterministic curve and the SPT-based deterministic curve exhibit similar conservatism. The results provide a method for liquefaction risk analysis

Assessing Probabilistic Methods for Liquefaction Potential Evaluation — An Update

This paper presents an assessment of existing probabilistic methods for liquefaction potential evaluation. Emphasis is placed on comparison of probabilities of liquefaction calculated with four different methods. Two of these methods are based on SPT, and the other two are based on CPT. In both SPT- and CPT-based evaluations, logistic regression and Bayesian techniques are applied to map factor of safety to probability of liquefaction. The present study shows that the Bayesian approach yields more conservative results than does the logistic regression approach, although results from the two approaches are quite comparable. Discussion of the procedure for risk-based liquefaction potential evaluation is also presented

Georisk Special Issue in Honour and Memory of Professor Tien H. Wu

10.1080/17499518.2019.1668591Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards1304237-24

Mitigation of liquefaction hazard by dynamic compaction - a random field perspective

This paper presents the findings of a case study to quantitatively assess the effect of dynamic compaction (DC) on mitigating liquefaction hazards from a random field perspective. DC is known to increase the density and strength of loose sand deposits, leading to a decrease in liquefaction potentials. Thus, by comparing the liquefaction potentials before and after DC at a given site, the effectiveness of DC in mitigating liquefaction hazards can be quantified. In practice, however, a direct one-to-one comparison is challenging due to limited availability of in situ test data and the fact that the number and location of these data before and after DC are typically different. To overcome these challenges, a random field-based approach is proposed in this study to visualize and quantitatively evaluate the effectiveness of DC across the entire project site. This approach is proven effective in assessing the effects of DC and is validated with liquefaction observations from the 1999 Chi-Chi earthquake.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Regional characterization of vs30 with hybrid geotechnical and geological data

Regional characterization of soil properties requires not only geostatistical models considering the spatial variability of soil properties but also methods that account for various sources of heterogeneous information. This paper presents a multi-conditional random field approach to characterize the regional characteristics of the average shear-wave velocity in the top 30 meters of subsoil (vs30) based on hybrid geotechnical and geological data. The workflow for integrating multiple sources of soil properties information in a random field model for regional vs30 mapping is developed. A detailed two-dimensional (2D) synthetic digital soil field is generated to assess and verify this workflow. With the generated synthetic field, parametric studies on the investigation plans, the value of Markov Bayes coefficient B, element size, and a predefined grid of secondary data are performed. Practice on whether to incorporate secondary data for vs30 mapping and the determination of coefficient B are provided

An efficient method to compute the failure probability

This paper presents an efficient method to compute the failure probability of a geotechnical system, which is based upon numerical integration of the cumulative distribution function (CDF) of the performance function. This new method is inspired by the concept of the vertex method often used in conjunction with fuzzy sets theory; however, new approach is taken to account for the probabilistic feature of the uncertain input parameters. In the new method, only the deterministic analysis of the system performance and the evaluation of the joint probability of the uncertain input parameters are required. The proposed new method is a deterministic approach, easy to follow and apply; no Monte Carlo simulation is required. Through an example study of a shallow strip foundation, the effectiveness and the efficiency of the proposed new method, in terms of the accuracy and the computational effort, respectively, are demonstrated.Non UBCUnreviewedThis collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.Facult