Runout prediction of potential landslides based on the multi-source data collaboration analysis on historical cases

Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to predict the landslide runout but a fundamental problem remained is how to determine the reliable numerical parameters.This study proposes a framework to predict the runout of potential landslides through multi-source data collaboration and numerical analysis of historical landslide events.Specifically,for the historical landslide cases,the landslide-induced seismic signal,geophysical surveys,and possible in-situ drone/phone videos(multi-source data collaboration)can validate the numerical results in terms of landslide dynamics and deposit features and help calibrate the numerical(rheological)parameters.Subsequently,the calibrated numerical parameters can be used to numerically predict the runout of potential landslides in the region with a similar geological setting to the recorded events.Application of the runout prediction approach to the 2020 Jiashanying landslide in Guizhou,China gives reasonable results in comparison to the field observations.The numerical parameters are determined from the multi-source data collaboration analysis of a historical case in the region(2019 Shuicheng landslide).The proposed framework for landslide runout prediction can be of great utility for landslide risk assessment and disaster reduction in mountainous regions worldwide.

Contamination assessment,source apportionment and associated health risks of PTEs in agricultural soil under five land-use patterns in Sanya,China

To understand the levels of potentially toxic elements(PTEs)contamination in soils and their effects on human health from different agricultural land use in Sanya,China.128 soil samples(64 topsoil samples and corresponding subsoil samples)were collected from the five representative land-use patterns.Inductively coupled plasma mass spectrometry(ICP-MS),Atomic fluorescence spectrometry(AFS),and Inductively coupled plasma optical emission spectrometry(ICP-OES)were used to determine the content of PTEs(As,Cd,Hg,Cu,Cr,Ni,Pb,Zn,Co,Mo,Sb,and V).Correlation analysis and factor analysis were used to determine the source of PTEs.Geo-accumulation index(I_(geo)),hazard quotient(HQ),and total carcinogenic risk index(TR)were used to measure the PTEs contamination and its relative health impacts.Results showed that the average values of 12 PTEs in topsoil were higher than the Hainan soil geochemical baseline,showing different degrees of PTEs accumulation effect.The concentration of PTEs in the topsoil was lower than those in the subsoil except for Cd and Hg.The I_(geo)revealed that the major accumulated element in soils was As followed by Mo.Source apportionment suggested that parent materials and agricultural practices were the dominant factors for PTEs accumulation in the topsoil.Noncarcinogenic risks of soil samples from five land-use patterns presented a trend of paddy field>dry field>woodland>orchard>garden plot.However,the HQ values of 12 PTEs were less than the recommended limit of HQ=1,representing that there are no non-carcinogenic risks of PTEs for children and adults in the study area.The TR values are within 6.95×10^(-6)-1.38×10^(-5),which corresponds to the low level.Therefore the PTEs in the agricultural soil of the study area show little influence on the health status of the local population.

Risk Assessment of Secondary Geological Disasters Induced by the Yushu Earthquake

The Yushu Ms 7.1 earthquake occurred on April 14,2010 in Qinghai Province,China.It induced a mass of secondary geological disasters,such as collapses,landslides,and debris flows.Risk assessment maps are important for geological disaster prevention and mitigation,and also can serve as a guide for post-earthquake reconstruction.Firstly,a hazard assessment index system of secondary geological disasters in the earthquake region was built in this paper,which was based on detailed analysis of environmental and triggering factors closely related to geological disasters in the study area.GIS technology was utilized to extract and analyze the assessment index.Hazard assessment maps of secondary geological disasters were obtained by spatial modeling and overlaying analysis.Secondly,an analysis of the vulnerability of hazard bearing bodies in the area was conducted,important information,such as, population density,percentage of arable land, industrial and agricultural outputs per unit area were regarded as assessment indices to evaluate socioeconomic vulnerability.Thirdly,the risk level of secondary geological disasters of the area was obtained by the formula:Risk=Hazard×Vulnerability. Risk assessment maps were categorized into four levels,including"low","moderate","high"and"very high".These results show that some urban areas are at very high risk,including Jiegu,Chengwen,Xiaxiula and Sahuteng towns.This research can provide some references and suggestions to improve decisionmaking support for emergency relief and post- earthquake reconstruction in the study area.

Assessment of prospective hazards resulting from the 2017 earthquake at the world heritage site Jiuzhaigou Valley, Sichuan, China

On August 8, 2017, a Ms = 7.0 magnitude earthquake occurred in the Jiuzhaigou Valley, in Sichuan Province, China(N: 33.20°, E: 103.82°). Jiuzhaigou Valley is an area recognized and listed as a world heritage site by UNESCO in 1992. Data analysis and field survey were conducted on the landslide, collapse, and debris flow gully, to assess the coseismic geological hazards generated by the earthquake using an unmanned aerial vehicle(UAV), remote-sensing imaging, laser range finders, geological radars, and cameras. The results highlighted the occurrence of 13 landslides, 70 collapses, and 25 potential debris flow gullies following the earthquake. The hazards were classified on the basis of their size and the potential property loss attributable to them. Consequently, 14 large-scale hazards, 30 medium-sized hazards, and 64 small hazards accounting for 13%, 28%, and 59% of the total hazards, respectively, were identified. Based on the variation tendency of the geological hazards that ensued in areas affected by the Kanto earthquake(Japan), Chi-chi earthquake(Taiwan China), and Wenchuan earthquake(Sichuan China), the study predicts that, depending on the rain intensity cycle, the duration of geological hazard activities in the Jiuzhaigou Valley may last over ten years and will gradually decrease for the following five to ten yearsbefore returning to pre-earthquake levels. Thus,necessary monitoring and early warning systems must be implemented to ensure the safety of residents,workers and tourists during the construction of engineering projects and reopening of scenic sites to the public.

Forecast of Geological Gas Hazards for “Three-Soft” Coal Seams in Gliding Structural Areas

Gas outbursts from "three-soft" coal seams (soft roof,soft floor and soft coal) constitute a very serious prob-lem in the Ludian gliding structure area in western Henan. By means of theories and methods of gas geology,structural geology,coal petrology and rock tests,we have discussed the effect of control of several physical properties of soft roof on gas preservation and proposed a new method of forecasting gas geological hazards under open structural conditions. The result shows that the areas with type Ⅲ or Ⅳ soft roofs are the most dangerous areas where gas outburst most likely can take place. Therefore,countermeasures should be taken in these areas to prevent gas outbursts.

Short-term displacement prediction for newly established monitoring slopes based on transfer learning

This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.

Deformation,structure and potential hazard of a landslide based on InSAR in Banbar county,Xizang(Tibet)

The Tibetan Plateau is characterized by complex geological conditions and a relatively fragile ecological environment.In recent years,there has been continuous development and increased human activity in the Tibetan Plateau region,leading to a rising risk of landslides.The landslide in Banbar County,Xizang(Tibet),have been perturbed by ongoing disturbances from human engineering activities,making it susceptible to instability and displaying distinct features.In this study,small baseline subset synthetic aperture radar interferometry(SBAS-InSAR)technology is used to obtain the Line of Sight(LOS)deformation velocity field in the study area,and then the slope-orientation deformation field of the landslide is obtained according to the spatial geometric relationship between the satellite’s LOS direction and the landslide.Subsequently,the landslide thickness is inverted by applying the mass conservation criterion.The results show that the movement area of the landslide is about 6.57×10^(4)m^(2),and the landslide volume is about 1.45×10^(6)m^(3).The maximum estimated thickness and average thickness of the landslide are 39 m and 22 m,respectively.The thickness estimation results align with the findings from on-site investigation,indicating the applicability of this method to large-scale earth slides.The deformation rate of the landslide exhibits a notable correlation with temperature variations,with rainfall playing a supportive role in the deformation process and displaying a certain lag.Human activities exert the most substantial influence on the spatial heterogeneity of landslide deformation,leading to the direct impact of several prominent deformation areas due to human interventions.Simultaneously,utilizing the long short-term memory(LSTM)model to predict landslide displacement,and the forecast results demonstrate the effectiveness of the LSTM model in predicting landslides that are in a continuous development and movement phase.The landslide is still active,and based on the spatial heterogeneity of landslide deformation,new recommendations have been proposed for the future management of the landslide in order to mitigate potential hazards associated with landslide instability.

Predicting geological hazards during tunnel construction

The complicated geological conditions and geological hazards are challenging problems during tunnel construction,which will cause great losses of life and property.Therefore,reliable prediction of geological defective features,such as faults,karst caves and groundwater,has important practical significances and theoretical values.In this paper,we presented the criteria for detecting typical geological anomalies using the tunnel seismic prediction（TSP） method.The ground penetrating radar（GPR） signal response to water-bearing structures was used for theoretical derivations.And the 3D tomography of the transient electromagnetic method（TEM） was used to develop an equivalent conductance method.Based on the improvement of a single prediction technique,we developed a technical system for reliable prediction of geological defective features by analyzing the advantages and disadvantages of all prediction methods.The procedure of the application of this system was introduced in detail.For prediction,the selection of prediction methods is an important and challenging work.The analytic hierarchy process（AHP） was developed for prediction optimization.We applied the newly developed prediction system to several important projects in China,including Hurongxi highway,Jinping II hydropower station,and Kiaochow Bay subsea tunnel.The case studies show that the geological defective features can be successfully detected with good precision and efficiency,and the prediction system is proved to be an effective means to minimize the risks of geological hazards during tunnel construction.

The Scanning Characteristics of Spatial and Temporal Dynamic Pictures of the Seismicity in the South Yellow Sea and Its Coast Region

On the basis of the viewpoint of preparation of strong earthquakes in group, the spatial andtemporal scanning characteristics of the seismicity in the South Yellow Sea and its coast regionare studied, and some problems regarding the prediction of seismic hazard are also discussed.The results show that the seismic activity of M=4. 0 earthquakes has overall presented arelative stable state, but the partially concentrated area wbich evolves and migrates and theanomalous low b-value area have appeared in different periods, and the moderately strongearthquakes with M=5. 0～6. 0 have taken place on the edge of the anomalous area. Theaccumulative frequency of M=4. 0 earthquakes in the anomalous area presents non-linearindex acceleration and the moderately strong earthquakes have appeared in the late period ofthe non-linear index acceleration of M=4. 0 earthquakes or in the later anomalous tranquilperiotl. The spatial and temporal uneven Phenomenon of seismicity has some stability andreproducibility, and has

Chinese public participation monitoring and warning system for geological hazards

In China,many geological hazards occurred in remote mountainous regions,and it was time-consuming to disseminate disaster information for the responsible parties to make timely judgements.Besides,only relying on professionals to monitor and manage disasters was demanding and costly.The Chinese government created a system to engage residents in the process of disaster risk management,namely’Public Participation Monitoring and Warning’(PPMW),to disseminate timely disaster information and bring down management costs.The objective of this system was to reduce casualties with minimum cost by organizing residents to evacuate from disasters in advance.This paper introduced the PPMW system,including its structure,operation mechanism by reviewing government documents and research articles,and its implementation by a case study of a landslide at Boli village(E 101°01’,N 27°29’),Yanyuan County,Sichuan Province,China on July 19th 2018.Further,this paper analyzed the strengths and limitations of the system and discussed its future development.It had the potential to become an affordable disaster risk management tool for other countries facing similar situations to China.

基于无人机倾斜摄影测量三维建模的区域黄土滑坡识别及特征分析

【研究目的】黄土滑坡是黄土地区人居与城镇建设安全的重大隐患。滑坡识别是滑坡灾害及其他研究工作的基础,因此基于无人机倾斜摄影测量三维建模从不同维度、不同视角直观快速地识别黄土滑坡并进行特征参数提取,能够为黄土滑坡风险识别及风险管理精细化研究提供技术支撑。【研究方法】以宁夏回族自治区固原市彭阳县红河镇西南部的黑牛沟村为研究区,采用无人机倾斜摄影测量数据获取、三维建模、现场验证结合地统计学分析,开展了区域黄土滑坡识别及其特征参数提取和分析。【研究结果】基于三维实景模型确定并分析研究区沟谷沿线地貌凹陷区是否存在陡壁及其周界形态,结合色调、纹理和微地貌等标志实现了黄土滑坡识别,共圈定了23个滑坡,结合现场验证移除2个非滑坡点,最终确定了21个滑坡;滑坡密集分布在主沟和支沟沟口,多呈对滑的形式出现在沟谷两侧且具有群发性;大型及特大型滑坡占比达到57.14%,滑坡的滑动方向主要以西南(阳坡)、东南(半阳坡)为主,相对高差集中在80~120 m,滑坡体坡形多呈凹形坡,滑坡体坡度主要集中在20°~30°;滑坡体土地利用类型主要为植被,其次为裸地,也有一部分为农田,道路和河流占比极少。【结论】基于无人机倾斜摄影测量构建的三维实景模型可从多维度、多视角精确快速地识别区域黄土滑坡,并分析其相关特征参数,能够弥补当前二维平面遥感影像存在的不足;还能够为滑坡易发性、危险性、易损性及风险评估等相关研究提供数据支撑。

中外地质灾害风险评价研究文献综述

中外学者对地质灾害风险评价研究成果颇丰,有必要进行阶段性整理。搜集1992—2020年CNKI数据库的2308篇和WOS数据库的884篇文章,运用文献计量和传统文献研究方法,全面梳理了包括热点、主题、主要研究团队与机构、历程、对象演变、内涵发展以及评价方法等方面当前已有的研究成果。明确了研究的阶段性划分并发现研究具有主题明确化、维度综合化和方法科学化等趋势,给出几点思考供同侪研究者参考。

甘肃临夏积石山县6.2级地震地质灾害发育特征及危险性评价

2023年12月18日23时59分,甘肃省临夏州积石山县发生Ms6.2级地震,诱发了大量崩滑地质灾害,严重威胁人民生命财产安全。基于震区现场实地调查成果,开展地震诱发加剧地质灾害的发育特征、危险性评价研究,提出防灾减灾措施建议。根据实地调查统计,此次地震后新增地质灾害隐患点64处,加剧的地质灾害隐患点有63处。新增和变形加剧的隐患点以崩塌为主,滑坡次之;规模等级以小型为主,中型次之。崩滑地质灾害主要集中在黄土丘陵区,以黄土陡坎地带切坡建房、切坡修路为主。利用GIS技术的加权信息量法评价积石山县域地质灾害易发性。结果显示,高易发区、中易发区、低易发区、非易发区占比分别为5.45%、9.83%、32.70%和52.02%,其中高易发区主要分布在积石山东部黄土丘陵区的山梁地带。基于区域地质灾害易发性评价,开展地震活动断裂、地震动分布以及不同降雨工况条件(10年、20年、50年、100年一遇)下积石山县域地质灾害危险性评价。结果显示:100年一遇极高危险区较10年一遇极高危险区的增幅最大为18.26%,说明未来区内遭遇极端降雨会显著提高区内地质灾害危险程度。研究认为,积石山地震地质灾害后效应将增强,未来崩塌、滑坡发生频次升高,地质灾害易在降水、冻融条件下形成,需针对性地采取防控措施,有效降低其威胁程度。

基于PS-InSAR技术的晋城矿区地表形变监测及地质灾害风险预警

地表形变是一种严重的地质灾害现象,不仅严重影响灾害区居民的日常生活,而且会造成巨大的社会经济危害,尤其在采煤区。针对传统地表沉陷监测方法费时费力、无法获取地表沉降面状信息、难以进行地表沉陷灾害评估的不足,基于高分辨率SAR卫星影像,利用永久散射体合成孔径雷达干涉测量(PS-InSAR)技术对山西省晋城市晋城矿区2018年1月至2018年12月期间地表沉陷进行监测,分析获取了该地区地表连续形变情况,并利用该技术获取的海量PS点建立支持向量机(SVM)地质灾害风险评估预警模型,对晋城矿区周边居民点地质灾害风险进行了识别和预测。结果表明:晋城矿区10个煤矿及其周边区域存在较大的地表形变;晋城矿区平均LOS向年平均地表形变速率范围为-37~30.3 mm/a;PS-InSAR技术在晋城矿区地表形变监测中具有可行性,且可以实现矿区地质灾害风险综合识别和预警。

郑州市西部山地丘陵区地质灾害发育特征及危险性评价

郑州市西部山地丘陵区地质环境条件复杂,崩塌、滑坡及泥石流等地质灾害频发,尤其是2021年“7·20”特大暴雨引发了大量地质灾害。地质灾害危险性评价主要采用单一方法进行,存在评价准确性略低等问题。通过对研究区地质环境背景、地质灾害分布特征的分析研究,选取坡度、地貌、工程地质岩组、高程、距断裂距离、距河流距离、24小时最大降雨量和人类工程活动强度8个评价因子,采用加权信息量法,对研究区进行地质灾害危险性评价。结果表明:低、中、高危险区面积分别为1387.14 km^(2)、1803.18 km^(2)、1066.47 km^(2),分别占总面积的32.59%、42.36%、25.05%,地质灾害点的空间分布与地质灾害危险性评价结果基本一致,利用受试者工作特征(ROC)曲线检验评价结果合理,研究结论可为郑州市西部山地丘陵区地质灾害防治提供准确的依据。

安徽省阜南县地质灾害风险调查评价研究

为深入探究并科学评价安徽省阜南县地质灾害高风险区域,确保当地居民生命财产安全,本文通过1∶5万比例尺地质灾害风险调查工作,对该县潜在的地质灾害类型、形成机制以及对人类社会构成的威胁进行了系统分析。基于调查数据和科学的风险评估方法,本文不仅提出了针对性的地质灾害风险管控策略,还全面总结了阜南县地质灾害的发育分布规律。这一研究不仅为阜南县地质灾害的防控提供了科学依据,也为类似地区的地质灾害风险管理提供了参考。

不同降雨工况条件下的崩滑地质灾害危险性评价

为针对性地采取预防、避让、治理等地质灾害防治与管控提供依据,完善在地质灾害危险性评价中将降雨作为单一诱发因子参与评价体系的弊端,在大雨、暴雨、大暴雨和特大暴雨4种不同降雨工况条件下进行了研究区崩滑地质灾害危险性评价。以云南省元阳县作为研究区域,以栅格单元作为评价单元,选取地貌类型、高程、坡度、坡向、曲率、工程地质岩组、土地利用类型、断层距离和河流距离9个评价因子,采用主观的层次分析法与客观的信息量模型相结合的加权信息量模型对元阳县崩塌、滑坡进行了地质灾害易发性评价。研究结果表明:基于自然间断点法元阳县域可分为低、中、高、极高4类易发区,4类易发区面积分别占元阳县面积的21.55%,35.46%,25.53%和17.16%。利用ROC曲线得出区划结果精度AUC值为0.812,表明区划结果很好。在易发性评价基础上,以年平均最大日降雨量为诱发因素,分别对大雨、暴雨、大暴雨和特大暴雨4种工况条件下的研究区进行了崩塌、滑坡地质灾害危险性评价,得到了大雨([25,50) mm)工况、暴雨([50,100) mm)工况、大暴雨([100,250]mm)工况和特大暴雨(>250 mm)工况4种条件下基于极值假设的研究区崩滑地质灾害危险性评价结果,并对不同降雨工况条件下的地质灾害危险性评价结果进行了对比分析,确定了地质灾害危险性评价结果在不同降雨条件下的空间合理性。通过与实际调查结果的对比表明,4种不同降雨工况条件下的崩滑地质灾害危险性评价结果与实际高度吻合,说明评价结果具有较高的可靠性与合理性。

甘肃省白龙江流域不同岩性滑坡降雨阈值研究

降雨引发斜坡破坏的阈值是地质灾害预警的基础。文章以2004—2019年白龙江流域甘肃段5个县区内因长期强降雨引发的滑坡作为研究对象,采用频数法研究不同岩性特征的滑坡降雨预警阈值。构建了不同概率等级下,引发滑坡的事件降雨量(event rainfall)与降雨历时(duration of rainfall)之间的关系模型,并给出了下限临界累计降雨阈值。通过2020年陇南武都区暴洪灾害引发的滑坡特征及降雨数据验证,滑坡前雨量计监测获得的累计降雨量与模型给出的临界累计降雨阈值基本相符,对持续强降雨引发的滑坡灾害的预警具有指导意义。

水合物开采及海洋环境诱发地质灾害机理和风险评估研究现状与展望

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