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Liangshan Prefecture, located at the northeastern edge of the Hengduan Mountain System and within the southern section of the Sichuan-Yunnan tectonic belt in Sichuan Province, China, a region prone to landslides, collapses and debris flows due to its active tectonics, complex topography and significant river erosion. By analysing a dataset of environment factors and geological hazard catalogue, the research uses the Relief algorithm to identify critical influencing factors for each hazard type, selecting 10, 9 and 9 factors for landslides, collapses and debris flows, respectively. Five models are used to assess the vulnerability of these hazards: the Information Value model, the Evidence Weight model, the Logistic Regression model, and both the Evidence Weight-Logistic Regression and the Information Value-Logistic Regression coupled models. The effectiveness of these models is confirmed by confusion matrix and ROC curve analyses, with the combined models showing particularly high accuracy in assessing susceptibility. High risk zones were identified in specific areas and along major fault zones in Liangshan Prefecture. The research provides significant insights into the susceptibility of geological hazards in mountainous and canyon regions, offering a comprehensive approach that goes beyond the limitations of single model applications. This methodology not only provides more accurate and comprehensive results, but also serves as a fundamental reference for geological hazard mitigation and management in Liangshan Prefecture, potentially benefiting similar regions worldwide.

As a kind of natural disasters, geological hazards pose serious threats to the ecological security and socio-economic development of human society. Evaluating the sensitivity of regional geological hazards is essential for making disaster-preventing/mitigating strategies and land use plans. Based on multisource remote sensing data, this study evaluates the geological hazard sensitivity in Liaoning Province by using the method of spatial principal component analysis and spatial autocorrelation finding that such sensitivity is generally moderate, with an average value of 5.25, and is mainly concentrated in three levels: Mild sensitivity, moderate sensitivity and insensitivity, accounting for more than 67% of the total area. Liaodong Mountain Area and Liaoxi Hilly Area are found with the highest sensitivity of geological hazards, showcasing obvious spatial differences and aggregations, mainly because these areas have large terrain fluctuations, poor stability of rock and soil bodies, and strong erosion by precipitation. The main factors affecting the sensitivity of geological hazards include land use mode, elevation, slope, and lithology. Among them, the land use mode has the highest contribution rate to the first principal component, reaching 0.86. This study provides a theoretical reference for the prevention and control over geological hazards and the protection of ecological security in Liaoning Province.

Paleo-channels are one of the geological hazards on the continental shelf. Analyzing the laws of spatial distribution and unearthing the hidden geological significances could provide basis for ocean engineering and disaster prevention and mitigation, and it′s useful to restore the sedimentary processes. After paleo-channels were identified and their spatial distribution laws were studied, three periods were sorted for paleo-channels in the sedimentary layers under the ocean of southwestern Hainan Island, most of which were found under the seabed above which the depth is from 30 m to 80 m, which were speculated to be developed in MIS2, MIS4 and MIS5. The hydrodynamic forces of ancient rivers were weak on the whole, and the spatial distribution of paleo-channels were generally controlled by the spatial distribution of coastlines in Hainan Island. Most of the sedimentary materials were from Hainan Island, Some of which may come from the paleo Red River basin. Although affected by sea level fluctuation, the spatial distribution pattern of river system had strong continuity under the influence of sea level fluctuation.

Currently, in the field of geological disaster monitoring, monitoring and early warning information is mainly released based on the threshold setting of various types of monitoring equipment. However, since the thresholds are established according to empirical values or expert evaluations, there is a lack of pertinence to different types of geological disasters and different environments. Once set, these thresholds remain unchanged for a long time, and even when adjusted, they only slightly float based on experience, lacking scientific data sample analysis. Additionally, monitoring equipment is susceptible to satellite signals and environmental factors, leading to false alarms and false negatives during operation. To address these issues, a method of dynamic adjustment of self-learning and self-correction early warning thresholds is proposed. This method introduces two variable thresholds and a new performance index optimization method for VTAS based on priority and gate and semi-Markov processes. The application of the semi-Markov process allows the method to consider industrial measurements with non-Gaussian distributions. Moreover, an optimization design process based on genetic algorithms is proposed to improve performance indicators by optimizing parameter settings. Three numerical examples are used to illustrate the effectiveness of this approach and compare it with previous studies. When applied at the measured point, the method effectively reduce false alarms and under-alarms compared to the use of fixed thresholds, improving the accuracy of geological disaster early warning and better protecting the safety of people's lives and property.

The short-time heavy rainfall is sudden and easy to cause disaster， which poses a great threat to people's life and property safety.This paper analyzed the spatial and temporal variation characteristics of short-time heavy rainfall （≥20 mm·h-1） in the Sichuan basin and its relationship with geological hazards.The hourly precipitation observation data from high-density regional automatic stations and national stations （1688 stations） was used from 2011 to 2020.The results showed that： （1） The large values of short-time heavy rainfall frequency and rainfall were mainly concentrated in the transition area between high mountains and basins in the southwest and along the Longmen Mountains in the northwest， with more in the west and less in the east overall.（2） The frequency and rainfall were increasing， but the intensity and intensity extremes were decreasing， so the increase in rainfall was caused by the increase in frequency.In the northwestern part of the basin， the frequency and rainfall was the highest， and the interannual variability was the strongest.（3） The short-time heavy rainfall occurred from March to October， one month earlier than in the early 21st century.The frequency peaked in July and was concentrated from 23:00 to 07:00 next day （Beijing Time）， accounting for 56.5% of the whole day.The basin as a whole exhibited a single-peak night rain structure， but the northwestern， northeastern and central parts were bimodal， and the peak time was delayed from south to north.（4） The correlation and composite analysis revealed that the number of geological hazards was highly correlated with the frequency and rainfall of short-time heavy rainfall in the northwest， with correlation coefficients of 0.87 and 0.89， respectively.For the Sichuan basin as a whole， landslides and debris flows showed significant differences between the more frequent and less frequent short-time heavy rainfall.In the northwestern and southwestern parts of the basin， the short-time heavy rainfall had a large impact on various geological hazards.In the northeast， it had an impact on landslides， debris flows and other geological hazards， while in the south， it had an impact on other types of geological hazards.The northwest and northeast had the highest number of geological hazards， accounting for 40.2% and 31.7% of the total， respectively.But the short-time heavy rainfall was more likely to cause casualties in the northwest， and mainly caused direct economic losses and injuries in the northeast.The number of geological hazards in Sichuan basin was increasing， while the economic loss was decreasing， indicating that the disaster prevention and mitigation capacity has been significantly improved.

Landslide geological disasters, occurring globally, often result in significant loss of life and extensive economic damage. In recent years, the severity of these disasters has increased, likely due to the frequent occurrence of extreme rainstorms associated with global warming. This escalating trend emphasizes the urgent need for a simple and efficient method to identify hidden dangers related to landslide geological disasters. Areas experiencing seasonal heavy rainfall are particularly susceptible to such disasters, posing a serious threat to the lives and property of local residents. In response to the challenging characteristics of landslide geological hazards, such as their strong concealment and the high vegetation coverage in the Liupan Mountain area of the Loess Plateau, this study focuses on the integrated remote sensing identification and research of hidden landslide dangers in Longde County. The methodology combines differential interferometric synthetic aperture radar technology (D-InSAR) and high-resolution optical remote sensing. Surface deformation information of Longde County was obtained by analyzing 85 Sentinel-1A data from 2019 to mid-2020 using Stacking-InSAR, in conjunction with high-resolution optical remote sensing image data from GF-2 in 2019. Furthermore, the study conducted integrated remote sensing identification and field verification of landslide hazards throughout the entire county. This involved interpreting the shape and deformation marks of landslide hazards, identifying the disaster-bearing bodies, and expertly interpreting the environmental factors contributing to the hazards. As a result, 47 suspected landslide hazards and 21 field investigation points were identified, with 16 hazards verified with an accuracy of 76.19%. This outcome directly confirms the applicability and accuracy of the integrated remote sensing identification technology in the study area. The research results presented in this paper provide an effective scientific and theoretical basis for the monitoring and treatment of landslide geological disasters in the future stages. They also play a pivotal role in the prevention of such disasters. [ABSTRACT FROM AUTHOR]

Geological hazard susceptibility assessment (GSCA) is a crucial tool widely utilized by scholars worldwide for predicting the likelihood of geological disasters. The traditional information quantity model in geological disaster susceptibility evaluation, which superimposes the information quantity of each evaluation factor without considering their weights, often negatively impacts susceptibility zoning results. This paper introduces a method employing random forest (RF) empowerment information quantity to address this issue. The method involves calculating objective weights based on a parameter-optimized random forest model, assigning these weights to each evaluation factor, and then conducting a weighted superimposition of the information. Utilizing the natural discontinuity method, the resulting comprehensive information volume map was segmented. The proposed method was applied in Kang County, Gansu Province, and its performance was compared with that of traditional methods in terms of geological disaster susceptibility zoning maps, zoning of statistical disaster point density, and receiver operating characteristic (ROC) curve accuracy. The experimental findings indicate the superior accuracy and reliability of the proposed method over the traditional approach. [ABSTRACT FROM AUTHOR]

Data-driven stability prediction of slopes on the basis of survey data plays a vital role in geohazard prevention. A critical issue in data-driven stability prediction is that many factors can affect slope stability and have varied influences. Exploring the influence of different factors on the prediction model is helpful to improve its accuracy. In this paper, we used machine learning methods to predict soil slope stability based on soil slope survey data from four cities in Hunan Province, and evaluated the effects of groundwater and lithology on soil slope stability prediction. First, we analyzed and selected features using machine learning methods, i.e., random forest combined with SHapley Additive exPlanation (SHAP) values. Second, we constructed four machine learning models and compared the performance of the models. Finally, the best machine learning model was selected, and the influence of groundwater and lithology on the prediction of soil slope stability in the study area was explored using the SHAP method. The results show that the prediction accuracy and recall rate of the model decrease when only lithology is considered, while the prediction accuracy cannot be improved when only groundwater is considered. However, when combined with lithology, the prediction performance can be improved, and the accuracy and recall rate of the model are both improved by 0.01, and F-measure is improved by 0.02. The results of this paper can help improve the prediction accuracy of soil slopes in geohazard prevention. [ABSTRACT FROM AUTHOR]

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Strong earthquake geological hazards cause significant social and economic losses. The assessment of post-earthquake socioeconomic development levels is one of the important bases from which to measure the recovery capacity of hazard areas. However, the long-term impact of geological hazards is rarely considered in the assessment of the socioeconomic development level of a mountainous earthquake-stricken area. The purpose of this paper is to study the complex relationship between earthquake geological hazard effects and socioeconomic development in the long-term post-earthquake development and reconstruction of mountainous extremely earthquake-stricken areas, to provide a reference for the study area to achieve regional sustainable development goals and high-quality development. On this basis, using the economic, social, ecological environment and other relevant data from 2008 to 2016, and using unsupervised machine learning algorithms, a socioeconomic development level evaluation model based on spectral clustering was established, and the effects of different kernel function scale parameters on the model were analyzed. The optimal parameters were determined, and the spatiotemporal analysis of the socioeconomic development level of the study area was carried out. The research results show that the performance of the evaluation model is optimal when the output category is 4 and the scale parameter is 0.26, and the scale parameter of the kernel function is an important indicator that affects the accuracy of the model. From 2008 to 2016, the socioeconomic development level of Qingchuan has always been at a very low level, Wenchuan and Beichuan have always been at a low level, Shifang and Mianzhu have always been at a high level, and Pengzhou and Dujiangyan have always been at a very high level. The socioeconomic development level of Anxian, Maoxian and Pingwu fluctuates greatly over time. Another interesting finding is that the socioeconomic development level of the mountainous earthquake-stricken area has a strong correlation with its own industrial structure and landslide hazard effects. The work done in this paper is of great significance for understanding the temporal and spatial effects of hazards and understanding the complexities of regional disaster systems. [ABSTRACT FROM AUTHOR]

This paper mainly summarized a special issue named “Application of Novel High-Tech Methods to Geological Hazard Research”, which includes several aspects of geological hazard prevention and mitigation, such as characteristics and mechanisms, numerical simulations, susceptibility and hazard assessment, monitoring and early warning, prevention and control measures, and geotechnical research of geological hazards. These studies further promoted a deep understanding of the mechanism of geological hazards and the application of high-teches and new methods in geological disaster prevention and reduction.

In order to scientifically and rationally evaluate the susceptibility to landslide hazards in Tekes County, Yili State. This paper takes Tekes County in Xinjiang as an example, on the basis of a comprehensive analysis of the regional geological environment conditions and the distribution pattern and formation conditions of geological disasters, using the data of geological disaster points (landslide center points), and through the correlation matrix calculation of the evaluation factors, the nine evaluation factors with larger absolute values of correlation coefficients were determined to construct the evaluation system of the susceptibility to landslide geological hazards in Tekesi County. Combining the information quantity method and the entropy value method, using the weights determined by the entropy value method, the information quantity method is used to calculate the information quantity value of each factor within the factor, calculate the susceptibility index of landslide geological disasters within the territory of Tekes County, and then carry out the landslide susceptibility evaluation. The susceptibility of landslide disasters was evaluated by ArcGIS. The results show that the landslide disaster susceptibility level in Tekes County can be divided into four levels: high susceptibility, medium susceptibility, low susceptibility, and not susceptible, with areas of 491.3276 km2, 1181.5171 km2, 1674.7609 km2 and 5295.2976 km2 accounting for 5.68%, 13.67%, 19.38% and 61.27% of the total area of Tex County, respectively. The AUC number obtained by the success curve method (ROC) is 0.8736, reflecting the evaluation accuracy of 87.36%, indicating that the model method used in this paper is effective. The results are expected to provide practical data support for landslide disaster control in Tekes County and provide a reference for geological disaster monitoring, early warning and engineering prevention and control deployment in Yili Valley.

The marine economy and submarine landslides represent two critical and seemingly disparate areas of concern within oceanic studies. The marine economy encompasses industries and activities such as fishing, shipping, and tourism that rely on the health and accessibility of marine environments. In contrast, submarine landslides, which are significant geological hazards, can impact marine infrastructure, disrupt economic activities, and pose risks to coastal communities. This article explores the balance between advancing marine economic interests and mitigating the risks associated with submarine landslides. It examines current research, technological advancements, and policy measures aimed at addressing these challenges. Strategies for enhancing economic sustainability while safeguarding against geological hazards are discussed, emphasizing the need for integrated approaches that consider both economic and environmental factors. [ABSTRACT FROM AUTHOR]

The satellite data, include Landsat 7 Enhanced Thematic Mapper (ETM+), Landsat-8 (OLI), Shuttle Radar Topography Mission (SRTM), were processed and interpreted for creating an integrated geospatial map of the geomorphic indices (GI) of Wadi Hagul Basin (WHB). The present study is considered new, useful, and valuable in northwest of Gulf of Suez region to evaluate active tectonics using SRTM resulting drainage network and GI. Where fairly slight studies on active tectonics recognized on GI were prepared in the investigated area. The GI includes; Ratio of valley floor width to valley height (Vf), Transverse topographic symmetry factor (T), Stream length-gradient index (SL), Drainage basin shape (Bs), hypsometric integral (Hi), geomorphological landform and watershed analysis. Also, GI were integrated and combined with the seismic and structural lineaments intensities maps to create an integrated single index map. The morphotectonic geo-spatial distribution hazards map reveals that the high risky area is 82.75% of the total area, the moderate-risk area is 16.51%, and the low risky morph-tectonic area is 0.81%. Based on this map, it is necessary for planners and decision makers to extremely study attractive applicable action concerning the recommended mitigation measurements from this study to avoid any serious future problems in WHB and its surroundings areas. [ABSTRACT FROM AUTHOR]

In order to explore the relationship between land use change and the susceptibility to geological disasters, this study takes Huicheng District, Huizhou City, Guangdong Province, which is developing rapidly, as the research area. Through the combination of object-oriented segmentation and deep neural network model, the land use types of remote sensing images in different periods of the region are classified. The classification results are integrated into the evaluation index system of geological disaster susceptibility as dynamic factors, and in combination with influencing factors such as topography, geological structure, and lithology to construct the susceptibility model to evaluate the susceptibility of regional geological disasters in the two periods. Finally, the influence of land use change on the susceptibility of geological disasters is analyzed. The results show that the building accounted for 55.76% of the areas where the susceptibility level of geological disasters increased significantly and the land use types changed, and 76.35% of the building in this part is from forest and cultivated land, mainly in the eastern part of the region and next to the newly built Guanglong Expressway. In addition, when the proportion of building in the region increased from 17.29% to 20.85%, the susceptibility level of geological disasters in the expanded range accounted for 27.92%, which was 9.27% higher than the proportion of the decline, indicating that human engineering activities played a stronger role in promoting the occurrence of geological disasters. The research results provide a strong scientific basis for urbanization development, disaster prevention and mitigation at the regional scale. [ABSTRACT FROM AUTHOR]

The precursors that appear when geological disasters occur are geotechnical deformations. This paper studies the TDR (Time Domain Reflection) measurement technology for the distributed measurement of geotechnical deformation using parallel spiral wire as a sensor, which is used for monitoring and early warning detection of geological disasters. Based on the mechanism of the electromagnetic field distribution parameters of the parallel spiral sensing wire, the relationship between the stretching amount of the parallel spiral wire and the change in its characteristic impedance is analyzed. When the parallel spiral wire is buried in the soil, the geotechnical deformation causes the parallel spiral wire to be stretched, and according to its characteristic impedance change, the stretching position and the stretching degree can be obtained, thus realizing the distributed measurement of geotechnical deformation. Based on this principle, the TDR measurement system is developed, and a local single-point stretching amount and stretching positioning experiment are designed for the parallel spiral sensing line to verify the effectiveness of the sensing technology and the usability of the measurement system. [ABSTRACT FROM AUTHOR]

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Shuangbai County, located in Yunnan Province, Southwest China, possesses a complex and diverse geological environment and experiences frequent landslide disasters. As a significant area for disaster prevention and control, it is crucial to assess the susceptibility of landslides for effective geological disaster prevention, urban planning, and development. This research focuses on eleven influencing factors, including elevation, slope, slope direction, rainfall, NDVI, and distance from faults, selected as evaluation indexes. The assessment model is constructed using the information quantity method and the information quantity logistic regression coupling method to analyze the landslide susceptibility in Shuangbai County. The entire region's landslide susceptibility is classified into four categories: not likely to occur, low susceptibility, medium susceptibility, and high susceptibility. The accuracy and reasonableness of the models are tested and compared. The results indicate that the coupled information–logistic regression model (80.0% accuracy) outperforms the single information model (74.2% accuracy). Moreover, the density of disaster points in the high-susceptibility area of the coupled model is higher, making it more reasonable. Thus, this model can serve as a valuable tool for evaluating regional landslide susceptibility in Shuangbai County and as a basis for disaster mitigation planning by relevant authorities. [ABSTRACT FROM AUTHOR]

Geological disasters refer to adverse geological phenomena that occur under the influence of natural or human factors and cause damage to human life and property. Establishing prevention and control zones based on geological disaster risk assessment results in land planning and management is crucial for ensuring safe regional development. In recent years, there has been an increase in extreme rainfall events, so it is necessary to conduct effective geological hazard and risk assessments for different extreme rainfall conditions. Based on the first national geological disaster risk survey results, this paper uses the analytic hierarchy process (AHP) combined with the information method (IM) to construct four extreme rainfall conditions, namely, 10-year, 20-year, 50-year, and 100-year return periods. The susceptibility, hazard, vulnerability, and risk of geological disasters in the Laoshan District in eastern China are evaluated, and prevention and control zones are established based on the evaluation results. The results show that: (1) There are 121 collapse geological disasters in Laoshan District, generally at a low susceptibility level. (2) A positive correlation exists between extreme rainfall and hazards/risks. With the rainfall condition changing from a 10-year return period to a 100-year return period, the proportion of high-hazard zones increased from 20% to 41%, and high-risk zones increased from 31% to 51%, respectively. The Receiver operating characteristic (ROC) proved that the assessment accuracy was acceptable. (3) Key, sub-key, and general prevention zones have been established, and corresponding prevention and control suggestions have been proposed, providing a reference for geological disaster prevention and early warning in other regions. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Geological Hazard & Control is the property of China Institute of Geological Environmental Monitoring (CIGEM) Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Plateau Meteorology is the property of Plateau Meteorology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As a natural disaster prone to occur in mountainous areas, geological hazards cause serious economic losses to China every year. In order to reveal the factors influencing of geological hazards susceptibility in typical mountain valley, this paper takes Changdu City as the study area.Firstly, we analyze the spatial distribution of geological hazards, and then divides it into three major watersheds based on the differences of disaster-inducing environments in the study area, selects 10 indicators such as elevation, slope and terrain relief to build a evaluation index system of geological hazard susceptibility , and the weights of index determined based on the Random Forest. The spatial distribution of geological hazards in each watershed of Changdu City is obtained by overlaying with GIS, and it is found that: (1) The types of geological hazards in Changdu City are mainly small disasters, while the distribution of large disasters is relatively small but the hazards are huge and the danger level is high. (2) In general, the factors influencing geological hazards are more or less the same in each basin, but there are still some differences, with the factor of medium altitude and road being more prominent in the Jinsha River basin, the factor of density of settlements being more prominent in the Lancang River basin, and the factor of road being more prominent in the Nujiang River basin.(3) The Jinsha River basin has the largest area of low susceptibility, and the Lancang and Nujiang River basins have the largest area of medium susceptibility; all three basins have the smallest area of high susceptibility, but they are distributed in the whole basin, and mainly in areas with strong human activities and soft lithology.

Glacial debris flow is a common natural disaster, and its frequency has been increasing in recent years due to the continuous retreat of glaciers caused by global warming. To reduce the damage caused by glacial debris flows to human and physical properties, glacier susceptibility assessment analysis is needed. Most research efforts consider the effect of existing glacier area and ignore the effect of glacier ablation volume change. In this paper, we consider the impact of glacier ablation volume change to investigate the susceptibility of glacial debris flow. The susceptibility to mudslide was evaluated by taking the glacial mudslide-prone ditch of G318 Linzhi section of Sichuan-Tibet Highway as the research object. First, by using a simple band ratio method with manual correction, we produced a glacial mudslide remote sensing image dataset, and second, we proposed a deep-learning-based approach using a weight-optimized glacial mudslide semantic segmentation model for accurately and automatically mapping the boundaries of complex glacial mudslide-covered remote sensing images. Then, we calculated the ablation volume by the change in glacier elevation and ablation area from 2015 to 2020. Finally, glacial debris flow susceptibility was evaluated based on the entropy weight method and Topsis method with glacial melt volume in different watersheds as the main factor. The research results of this paper show that most of the evaluation indices of the model are above 90%, indicating that the model is reasonable for glacier boundary extraction, and remote sensing images and deep learning techniques can effectively assess the glacial debris flow susceptibility and provide support for future glacial debris flow disaster prevention. [ABSTRACT FROM AUTHOR]

The purpose of this study was to construct a geological hazard susceptibility evaluation and analysis model using three types of machine learning models, namely, random forest (RF), support vector machine (SVM), and naive Bayes (NB), and to evaluate the susceptibility to landslides, using the Puge section of the Zemu River valley in the Liangshan Yi Autonomous Prefecture as the study area. First, 89 shallow landslide and debris flow locations were recognized through field surveys and remote sensing interpretation. A total of eight hazard-causing factors, namely, slope, aspect, rock group, land cover, distance to road, distance to river, distance to fault, and normalized difference vegetation index (NDVI), were selected to evaluate the spatial relationship with landslide occurrence. As a result of the analysis, the results of the weighting of the hazard-causing factors indicate that the two elements of rock group and distance to river contribute most to the creation of geological hazards. After comparing all the indices of the three models, the random forest model had a higher correct area under the ROC curve (AUC) value of 0.87, root mean squared error (RMSE) of 0.118, and mean absolute error (MAE) of 0.045. The SVM model had the highest sensitivity to geological hazards. The results of geological hazard prediction susceptibility analysis matched the actual situation in the study area, and the prediction effects were good. The results of the hazard susceptibility assessment of the three models are able to provide support and help for the prevention and control of geological hazards in the same type of areas. [ABSTRACT FROM AUTHOR]

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The methodology of comprehensive risk assessment for natural disasters has been the subject of recent research. The risk assessment process is thoroughly explained and applied to geological hazards (such as landslides, earthquakes, and tsunamis) that have a potential for calamity. Obtaining a complicated risk level for a few geophysical and geological risks in northeast Bulgaria is the major goal. It has been done to clearly identify the many dangers, their effects, the elements at risk, exposure, and vulnerability, as well as to analyze the secondary events that were generated. For the first time in practice, a thorough risk assessment approach is used, and it incorporates the idea of risk perception. The methodology's adaptability enables the presentation of the results as either a risk matrix or a risk profile. It depends on the tasks, challenges, and scientific puzzles that need to be solved as well as expert judgment. The outcome showed strong practical applicability and sustainability. [ABSTRACT FROM AUTHOR]

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Copyright of Journal of Engineering Geology / Gongcheng Dizhi Xuebao is the property of Journal of Engineering Geology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Nonferrous Metals (Mining Section) is the property of Beijing Research Institute of Mining & Metallurgy Technology Group and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Geological hazard susceptibility assessment is an important basis for territorial space planning and geological hazard prevention and mitigation. In order to explore the evaluation method suitable for the geological hazard susceptibility of low hills and gullies in Yunnan plateau, Wuhua District of Kunming, Yunnan Province, China was selected as a typical study area. Eight factors including the engineering geology groups, distance from faults, elevation, slope, direction, curvature, distance from roads and land use covers were selected, and the weight evidence method based on Bayesian theory was applied to evaluate the susceptibility of geological hazards. After performing the Student-T test of the comprehensive evidence weight of each factor, the classification scheme of factors were optimized. The results of vulnerability zoning based on the evaluation of the model established in this paper showed that 89.9% and 9.1% of the geological hazard points fall into high and medium susceptibility areas. The comparative analysis showed that the modeling results are highly consistent with the geological hazards distribution, which better reveals the characteristics of geological hazards susceptibility in the study area. It can provide reference for the planning of geological hazards prevention in Wuhua District and other low hills and gullies areas of Yunnan plateau.

Introduction: As our understanding of the ocean and its uses continues to advance, countries worldwide with ocean access are implementing new marine strategies. For example, understanding marine geological disasters can help develop the use of ocean resources and oceanic engineering.Methods: Therefore, this study used recent data from the Oujiang Estuary, a nearshore area in China, to determine its geological hazards.Results: The geological hazards were classified as active or restricted based on topography, geomorphology, shallow seismic profile, single-channel seismic profile, and geological drilling data. Active geological hazards primarily include shallow gas and active sand waves, whereas restrictive geological hazards include irregularly buried bedrock, erosion channels, steep submarine slopes, and buried paleochannels. We also evaluated the distribution characteristics and scope, such as the vertical distribution of shallow gas based on the seismic profiles, drilling rock facies, methane, and carbon dioxide contents in the top air, and the isotope values. We found that shallow gas was vertically distributed among multiple layers. The main gas-bearing layers were the clayey silt and sandy (silt) clay layers of the early Holocene and late Pleistocene strata. The shallow gas content was relatively low in the coarse sediment layer at the bottom of the late Pleistocene succession. Generally, the Holocene and late Pleistocene deposits do not contain gas, and the gas content in the middle and late Pleistocene strata (at greater depths) is relatively low.Discussion: The combined effects of the regional geological structure, sea level changes, modern hydrodynamics, and human activities have formed the geological environment of the Oujiang Estuary.

Landslide disasters occur frequently in southern Shaanxi. Effective landslide susceptibility evaluation in this area is of great significance for disaster prevention and reduction. Based on the data of 257 landslide disaster points in Danfeng County, Shangluo City, Shaanxi Province, 10 influencing factors such as elevation, slope angle, slope aspect, profile curvature, plan curvature, TWI, NDVI, distance to roads, distance to faults and average annual rainfall were selected for evaluation. Through the evaluation and analysis of relevant attributes, the most closely related to the occurrence of landslide in the study area are elevation, TWI and distance to roads. Based on GIS, 70% of the grid data were randomly extracted as samples, and the Stacking model was used to integrate RA, DECORATE and RS models. They were trained respectively in WEKA software to verify the remaining 30% of the grid data, and the AUC value was used to compare the model performance. Finally, the landslide susceptibility maps of each separate classifier and stacked were generated respectively. The results showed that the AUC values of the four models are greater than 0.7 and the training accuracy and verification prediction rate are high. Four models are suitable for the evaluation of landslide susceptibility in the study area. Among them, the Stacking model has the highest prediction ability, indicating that the combination of different base classifiers improves the fitting ability of the Stacking model and enhances the identification of landslide susceptibility. [ABSTRACT FROM AUTHOR]

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The warning accuracy, false alarm rate and timeliness of regional geological hazard early warning models (GHEWMs) have an important impact on significantly reducing the damage caused by geological hazards. Most of the existing regional GHEWMs are based on forecast rainfall. Due to the influence of rainfall forecast accuracy and other factors, its early warning accuracy, false alarm rate and timeliness are still difficult to meet the needs of engineering applications such as disaster avoidance, mitigation and prevention of geological hazards. Therefore, this paper proposes a regional GHEWM based on the hourly rainfall series (HRS) of real-time automatic rainfall stations. Based on the data of 689 geological hazards that have occurred in Huangshan City from 2018 to 2021 and the corresponding rainfall data of automatic rainfall stations, the model uses the dynamic time warping (DTW) algorithm on the Spark big data platform to extract the historical HRS of each geological hazard and calculates the highest similarity between it and the current HRS in parallel. By coupling the probability of occurrence of geological hazards and the highest similarity of the above-mentioned HRS, a regional GHEWM based on real-time rainfall big data is finally constructed. The research results show that the model's early warning accuracy reaches 85%, and the false alarm rate is only 15%, which can predict the possibility of geological hazards after the next 3 h. [ABSTRACT FROM AUTHOR]

On December 26, 2018 (2:19 UTC), during a volcanic eruption on the Mt. Etna eastern flank (Sicily, southern Italy), the largest instrumental earthquake ever recorded in the volcano ruptured the Fiandaca Fault, with epicenter between Fleri and Pennisi villages (hypocenter at ca. 300 m a. s. l., Mw 4.9). This was the mainshock of an earthquake swarm and it was accompanied by widespread surface faulting and extensive damage along a narrow belt near the fault trace. Few hours after the mainshock, an episodic aseismic creep event occurred along the Aci Platani Fault, a SE extension of the Fiandaca Fault, which caused several damages in the Aci Platani village. We surveyed and mapped the coseismic and aseismic ground ruptures, and collected structural data on their geometry, displacement, and fault zone fabric. We compared the mapped surface ruptures with topography, lithology, and morphology of the buried top of the sedimentary basement. We conclude that the geometry of the volcanic pile influenced the surface expression of faulting during the December 26, 2018 event. The top surface of the marly clay basement should be considered as a detachment surface for shallow sliding blocks. The earthquake occurred on top of a depression of the sedimentary basement forcing the sliding eastward, causing at surface the re-arrangement of the fault strand pattern and deformation style, switching from shear faulting to a tensile failure. The Fleri earthquake therefore provides an unprecedented dataset for 1) understanding active faulting in the European largest onshore volcano, 2) modeling its complex dynamics, and 3) contributing to a more refined surface faulting hazard assessment at Mt. Etna. Results from this investigation might be useful for characterizing capable faulting in similar volcano-tectonic settings worldwide. [ABSTRACT FROM AUTHOR]

This research studied the risk assessment of geological hazards, such as landslides and debris flow, under the time series and trend characteristics of extreme precipitation events in the last 60 years in nine typical regions of the lower Jinshajiang River Basin. Nine indicators, including slope, engineering geological rock group, slope structure type, distance to road, topographic relief, distance to fault, distance to the water system, vegetation cover and profile curvature, were selected as the index factors for landslide susceptibility evaluation, and the information quantity method was used to obtain the landslide susceptibility evaluation of the study area. Based on the susceptibility evaluation, the spatial analysis function of GIS was used to derive the geological hazard zoning under the extreme rainfall trend. The results showed that the areas with high extreme rainfall trends have higher densities of geological hazard development and they are concentrated, while areas with low extreme rainfall trends have relatively less geological hazard development, and what development exists is scattered. [ABSTRACT FROM AUTHOR]

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Abstract The landslide surge is a common secondary disaster of reservoir bank landslides, which can cause more serious damage than the landslide itself in many cases. With the development of large-scale scientific and engineering computing, many new techniques have been applied to the study of hydrodynamic problems to make up for the shortcomings of traditional methods. In this paper, we use the physics-informed neural network (PINN) to simulate the propagation process of surges caused by landslides. We study different characteristics of landslide surges by changing water depth and particle density. We find that: (1) the landslide surge propagation process simulation method based on the physics-informed neural network has good applicability, and the stages of landslide surge propagation can be well presented; (2) the depth of water influences the landslide surge propagation as the amplitude of the surge increases with deeper water; (3) the particle density of water influences the landslide surge propagation as the fluctuation of the surge is more obvious with larger particle density. Our study is helpful to understand the propagation process of landslide surges more clearly and provides new ideas for the follow-up study of this kind of complex fluid–structure interaction problem.

Taking Zemuhe fault zone (Puge section) as the study area, the control effect and development law of geological disasters in the study area are analyzed; Seven evaluation factors such as elevation, aspect and slope from fault are selected to construct the evaluation index system. The weighted information model coupled with deterministic coefficient model and information model is used to evaluate the susceptibility of geological disasters through ArcGIS. The results show that the development of geological hazards in the study area has fault distance effect, elevation and slope micro geomorphic effect and stratigraphic effect;The areas of extremely high, high, medium and low prone areas are 46.75 km2, 123.78 km2, 215.73 km2 and 285.34 km2 respectively, accounting for 6.96%, 18.43%, 32.12% and 42.49% respectively. The research results have important practical significance for guiding the land spatial planning and geological disaster prevention in Zemuhe fault zone and similar regions.

[Objective] The susceptibility zoning and meteorological forecast model of highway geological hazards were studied in order to provide a theoretical basis for implementing the meteorological forecast of geological hazards along the highways in Linzhi City, Tebit Autonomous Region. [Methods] Firstly, eight zoning factors, including fault density, soil type, slope, valley density, annual precipitation, land use, bare rock ratio and distance from rivers, were selected in the 15 km buffer zone along the highway in Linzhi City. The coefficients of each zoning factor were determined by the information and logistic regression method, and the zoning model of geological hazard susceptibility was obtained. Secondly, based on the daily precipitation data of the rainfall occurrence day, the first day, the second and and the third day before the landslide hazards, a meteorological forecast model of geological hazards was established by using logistic regression method. [Results] The susceptibility of most areas in the 15 km buffer zone along the highway in Linzhi City was less than 0.4, and the closer to the road, the greater probability of geological hazard susceptibility. The accuracy rate of the model was 85.71%, and the failure rate was 14.29%. [Conclusion] Affected by topography, geomorphology and precipitation data, the prediction results of the established model may deviate from the actual situation, but it can reflect the basic trend.

Wubao County is located in the northeastern part of the loess plateau in northern Shaanxi, geological disasters are developing in the area, which seriously threatens the life and property safety of local residents. On the basis of fully analyzing the geological disaster survey data in Wubao County, the evaluation indicators such as slope, slope aspect, and surface curvature were selected for the whole county scale, and the risk assessment was carried out based on the 25 m×25 m grid unit based on the information model based on the GIS platform. The evaluation results are divided into: extremely high risk area, high risk area, medium risk area and low risk area, accounting for 0.63%, 12.58%, 24.40% and 62.39% of the total area respectively. According to the scale of key areas, the factors of slope and slope height are selected, and the analytic hierarchy process model is used to carry out risk assessment of slope units divided by hydrological method based on GIS platform, including 19 extremely high-risk slopes, 69 high-risk slopes, 145 medium-risk slopes, 359 low-risk slopes. The same area (area A) under the two scales was selected to conduct variance analysis on the risk assessment results. It shows that at different scales and the same geographical location, the evaluation results of risk level may be inconsistent. At the county-wide scale, various mathematical statistical models with predictive functions should be used, but at the smaller key area scale, due to the insufficient number of samples used for training, it is not appropriate to use mathematical statistical models. Correspondingly, the grid unit based on GIS tools can be used as the evaluation unit at the county scale; the actual slope body can be used as the evaluation unit at the key area scale.

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The presence of geological hazards on the Sakhalin shelf creates difficulties in the design, construction, and maintenance of offshore oil and gas facilities. Identification and assessment of geological hazards in the coastal area of the northeastern shelf of Sakhalin Island will allow avoiding environmental disasters, minimizing the risks of accidents, and developing recommendations for ensuring safety in the development of oil and gas fields. The paper presents the results of an analysis of data from expeditionary surveys carried out at two sites using geophysical surveys and bathymetric surveys. The zones of ice gouging in the coastal part of site no. 1 caused by gouging of the seabed by stamukhas have been identified. Gas zones and paleo-incisions were found and mapped in the bottom part of the section at site no. 2. [ABSTRACT FROM AUTHOR]

At a time, when the five riparian countries have renewed consultation with each other about the future of the Caspian Sea, it is appropriate to propose a state of the art of the potential natural threats to the regional environment. We present a critical review of geological, meteorological–climatological and hydrological hazards and disasters illustrated by many examples from within the Caspian drainage basin. Our work is set in the frame of an analysis of the factors contributing to the scale of the disasters. A brief overview of the mitigation measures in place and their future development is also included underlining the current limited warning systems (especially transboundary) despite improvements. While analysing past disasters is an essential source of information on which to base new mitigation, current and future conditions have poor or even no analogue in the past. Even though it clearly turns out that earthquakes are certainly the most deadly hazard, Caspian Sea level changes are by far causing the largest economical impact and affect the largest area and thus population. This review has also highlighted the need to create a Caspian database of natural hazards and disasters. [ABSTRACT FROM AUTHOR]