• Title/Summary/Keyword: karst collapse

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Risk assessment of karst collapse using an integrated fuzzy analytic hierarchy process and grey relational analysis model

  • Ding, Hanghang;Wu, Qiang;Zhao, Dekang;Mu, Wenping;Yu, Shuai
    • Geomechanics and Engineering
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    • v.18 no.5
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    • pp.515-525
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    • 2019
  • A karst collapse, as a natural hazard, is totally different to a normal collapse. In recent years, karst collapses have caused substantial economic losses and even threatened human safety. A risk assessment model for karst collapse was developed based on the fuzzy analytic hierarchy process (FAHP) and grey relational analysis (GRA), which is a simple and effective mathematical algorithm. An evaluation index played an important role in the process of completing the risk assessment model. In this study, the proposed model was applied to Jiaobai village in southwest China. First, the main controlling factors were summarized as an evaluation index of the model based on an investigation and statistical analysis of the natural formation law of karst collapse. Second, the FAHP was used to determine the relative weights and GRA was used to calculate the grey relational coefficient among the indices. Finally, the relational sequence of evaluation objects was established by calculating the grey weighted relational degree. According to the maximum relational rule, the greater the relational degree the better the relational degree with the hierarchy set. The results showed that the model accurately simulated the field condition. It is also demonstrated the contribution of various control factors to the process of karst collapse and the degree of collapse in the study area.

Prediction of karst sinkhole collapse using a decision-tree (DT) classifier

  • Boo Hyun Nam;Kyungwon Park;Yong Je Kim
    • Geomechanics and Engineering
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    • v.36 no.5
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    • pp.441-453
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    • 2024
  • Sinkhole subsidence and collapse is a common geohazard often formed in karst areas such as the state of Florida, United States of America. To predict the sinkhole occurrence, we need to understand the formation mechanism of sinkhole and its karst hydrogeology. For this purpose, investigating the factors affecting sinkholes is an essential and important step. The main objectives of the presenting study are (1) the development of a machine learning (ML)-based model, namely C5.0 decision tree (C5.0 DT), for the prediction of sinkhole susceptibility, which accounts for sinkhole/subsidence inventory and sinkhole contributing factors (e.g., geological/hydrogeological) and (2) the construction of a regional-scale sinkhole susceptibility map. The study area is east central Florida (ECF) where a cover-collapse type is commonly reported. The C5.0 DT algorithm was used to account for twelve (12) identified hydrogeological factors. In this study, a total of 1,113 sinkholes in ECF were identified and the dataset was then randomly divided into 70% and 30% subsets for training and testing, respectively. The performance of the sinkhole susceptibility model was evaluated using a receiver operating characteristic (ROC) curve, particularly the area under the curve (AUC). The C5.0 model showed a high prediction accuracy of 83.52%. It is concluded that a decision tree is a promising tool and classifier for spatial prediction of karst sinkholes and subsidence in the ECF area.

Carbonate Breccias of the Middle Cambrian Daegi Formation, Taebaeksan Basin (태백산분지 캠브리아 중기 대기층 내의 탄산염 각력암)

  • Jang, Hwimin;Son, Mira;Ryu, In-Chang
    • Economic and Environmental Geology
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    • v.52 no.5
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    • pp.381-393
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    • 2019
  • Carbonate breccias occur sporadically in the Middle Cambrian Daegi Formation on the southern limb of the Baegunsan Syncline, Taebaeksan Basin. These carbonate breccias have been largely interpreted either as sedimentary breccias or as tectonic, fault-related breccias. Recent study, however, indicates that the majority of these breccias are a solution-collapse breccia which is causally linked to the paleokarstification. Extensive karstification is attributed to prolonged subaerial exposure of the carbonate platform. The exposed surface is a record of interruption in sedimentation on the carbonate platform. In the stratigraphic record, such karst-related post-depositional features are recognized as meteoric diagenetic features, paleosols, and solution-collapse breccias. Solution-collapse breccias are particularly well preserved and most profound in the carbonate rocks below the major unconformities, which also are evidence of prolonged subaerial exposure. The Middle Cambrian Daegi Formation provides an example of solution-collapse breccias. The formation and preservation of the solution-collapse breccias imply that a stratigraphic discontinuity surface (unconformity) can be designated within the Daegi Formation.

Application of Resistivity Technique for Identifying Cavities Near Surface in Karst Area, Muan-gun, South of Korea (무안군 카르스트 지역의 지하공동 탐지를 위한 전기비저항 탐사 기술 적용)

  • Farooq, Muhammad;Park, Sam-Gyu;Song, Young-Soo;Kim, Jung-Ho
    • Geophysics and Geophysical Exploration
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    • v.11 no.4
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    • pp.368-372
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    • 2008
  • This study evaluates the usefulness and capability of surface electrical resistivity technique for identifying the weak zones or subsurface cavities in karst area with limestone formation. Weak zones or cavities near surface can be potentially dangerous and several problems are associated with collapse of roads or buildings accompanied by subsidence phenomena. In this paper, both two and three dimensional resistivity investigation were conducted to investigate subsidence along a road in Yongweol-ri, Muan-gun, South Korea. The results of the resistivity survey using dipole-dipole array provide a clear view of the weathered regolith, the distribution of weak zones or cavities and bedrock. Several low resistivity areas were identified and subsequent drilling led to the discovery of several weak zone or clay-filled underground cavities. The drilling results show excellent correlation with the resistivity images. It is illustrated, the ability of electrical technique to produce high resolution images of subsurface, which are useful for subsidence assessment. Also the results of this study have demonstrated that two and three dimensional electrical resistivity surveys are useful for delineating the subsidence area. Based on resistivity imaging, the map of hazardous zone has been developed.

Analysis of Geological Factors for Risk Assessment in Deep Rock Excavation in South Korea (한국의 대심도 암반 굴착 위험도 산정을 위한 인자 분석)

  • Ihm, Myeong Hyeok;Lee, Hana
    • Tunnel and Underground Space
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    • v.31 no.4
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    • pp.211-220
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    • 2021
  • Tunnel collapse often occurs during deep underground tunneling (> 40 m depth) in South Korea. Natural cavities as well as water supply pipes, sewer pipes, electric power cables, artificial cavities created by subway construction are complexly distributed in the artificial ground in the shallow depths of the urban area. For deep tunnel excavation, it is necessary to understand the properties of the ground which is characterized by porous elements and various geological structures, and their influence on the stability of the ground. This study analyzed geological factors for risk assessment in deep excavation in South Korea based on domestic and overseas case study. As a result, a total of 7 categories and 38 factors were derived. Factors with high weights were fault and fault clay, differential stress, rock type, groundwater and mud inrush, uniaxial compressive strength, cross-sectional area of tunnel, overburden thickness, karst and valley terrain, fold, limestone alternation, fluctuation of groundwater table, tunnel depth, dyke, RQD, joint characteristics, anisotropy, rockburst and so forth.