The evaluation of mine geology disasters based on fuzzy mathematics and grey theory

Mine geology disasters include mine water, mine solid waste, apron and slide, ground collapse sink and underground fracture, etc.. The subject was studied in many ways, and fuzzy mathematics was usually used. It may assure the result and distinguish the dangerous rank of different areas. But it has two defects： The first is the result is not very exact, especially the border; The second is it is short of quantity. Fuzzy mathematics and grey theory were used in order to solve the problem. Firstly, mathematical model was constructed by using grey theory, so as to evaluate and forecast the dangerous rank of mining geology disaster in different areas. Then different areas were analyzed and divided by fuzzy mathematics. By doing these, similitude rules are not only studied but also differences are discriminated. Through the practice it can be known that the result is more accurate than before.

Planning and construction of Xiong’an New Area(city of over 5 million people):Contributions of China’s geologists and urban geology

China established Xiong’an New Area in Hebei Province in 2017,which is planned to accommodate about 5 million people,aiming to relieve Beijing City of the functions non-essential to its role as China’s capital and to expedite the coordinated development of the Beijing-Tianjin-Hebei region.From 2017 to 2021,the China Geological Survey(CGS)took the lead in multi-factor urban geological surveys involving space,resources,environments,and disasters according to the general requirements of“global vision,international standards,distinctive Chinese features,and future-oriented goals”in Xiong’an New Area,identifying the engineering geologic conditions and geologic environmental challenges of this area.The achievements also include a 3D engineering geological structure model for the whole area,along with“one city proper and five clusters”,insights into the ecology and the background endowment of natural resources like land,geothermal resources,groundwater,and wetland of the area before engineering construction,a comprehensive monitoring network of resources and environments in the area,and the“Transparent Xiong’an”geological information platform that is open,shared,dynamically updated,and three-dimensionally visualized.China’s geologists and urban geology have played a significant role in the urban planning and construction of Xiong’an New Area,providing whole-process geological solutions for urban planning,construction,operation and management.The future urban construction of Xiong’an New Area will necessitate the theoretical and technical support of earth system science(ESS)from various aspects,and the purpose is to enhance the resilience of the new type of city and to provide support for the green,low-carbon,and sustainable development of this area.

Deep seabed mining:Frontiers in engineering geology and environment

Ocean mining activities have been ongoing for nearly 70 years,making great contributions to industrialization.Given the increasing demand for energy,along with the restructuring of the energy supply catalyzed by efforts to achieve a low-carbon economy,deep seabed mining will play an important role in addressing energy-and resource-related problems in the future.However,deep seabed mining remains in the exploratory stage,with many challenges presented by the high-pressure,low-temperature,and complex geologic and hydrodynamic environments in deep-sea mining areas,which are inaccessible to human activities.Thus,considerable efforts are required to ensure sustainable,economic,reliable,and safe deep seabed mining.This study reviews the latest advances in marine engineering geology and the environment related to deep-sea min-ing activities,presents a bibliometric analysis of the development of ocean mineral resources since the 1950s,summarizes the development,theory,and issues related to techniques for the three stages of ocean mining(i.e.,exploration,extraction,and closure),and discusses the engineering geology environment,geological disasters,in-situ monitoring techniques,envi-ronmental protection requirements,and environmental effects in detail.Finally,this paper gives some key conclusions and future perspectives to provide insights for subsequent studies and commercial mining operations.

Characteristics and Prevention of Secondary Geological Disasters of Wenchuan Earthquake

In the research, secondary geological disasters of Wenchuan earthquake were defined and the consequences were illustrated based on geological disasters, such as collapse, landslide and debris flow, and threats of barrier lakes. In addition, the characteristics of secondary disasters were analyzed, as follows： Rupture of geological faults lays foundation in terms of geological structure; loose solids provide resources of an earthquake; abundant rainfall and large runoffs are driving forces of an earthquake; rainstorm, flood, and long-term high temperature are major inducing factors. Furthermore, suggestions on prevention of secondary disasters were proposed in terms of prevention before, at and after an earthquake. Finally, the scientific and practical significances of secondary disasters were illustrated.

Comparative study of different machine learning models in landslide susceptibility assessment: A case study of Conghua District, Guangzhou, China

Machine learning is currently one of the research hotspots in the field of landslide prediction.To clarify and evaluate the differences in characteristics and prediction effects of different machine learning models,Conghua District,which is the most prone to landslide disasters in Guangzhou,was selected for landslide susceptibility evaluation.The evaluation factors were selected by using correlation analysis and variance expansion factor method.Applying four machine learning methods namely Logistic Regression(LR),Random Forest(RF),Support Vector Machines(SVM),and Extreme Gradient Boosting(XGB),landslide models were constructed.Comparative analysis and evaluation of the model were conducted through statistical indices and receiver operating characteristic(ROC)curves.The results showed that LR,RF,SVM,and XGB models have good predictive performance for landslide susceptibility,with the area under curve(AUC)values of 0.752,0.965,0.996,and 0.998,respectively.XGB model had the highest predictive ability,followed by RF model,SVM model,and LR model.The frequency ratio(FR)accuracy of LR,RF,SVM,and XGB models was 0.775,0.842,0.759,and 0.822,respectively.RF and XGB models were superior to LR and SVM models,indicating that the integrated algorithm has better predictive ability than a single classification algorithm in regional landslide classification problems.

Risk assessment of coastal flooding disaster by storm surge based on Elevation-Area method and hydrodynamic models:Taking Bohai Bay as an example

The future inundation by storm surge on coastal areas are currently ill-defined.With increasing global sealevel due to climate change,the coastal flooding by storm surge is more and more frequently,especially in coastal lowland with land subsidence.Therefore,the risk assessment of such inundation for these areas is of great significance for the sustainable socio-economic development.In this paper,the authors use Elevation-Area method and Regional Ocean Model System(ROMS)model to assess the risk of the inundation of Bohai Bay by storm surge.The simulation results of Elevation-Area method show that either a 50-year or 100-year storm surge can inundate coastal areas exceeding 8000 km^(2);the numerical simulation results based on hydrodynamics,considering ground friction and duration of the storm surge high water,show that a 50-year or 100-year storm surge can only inundate an area of over 2000 km^(2),which is far less than 8000 km^(2);while,when taking into account the land subsidence and sea level rise,the very inundation range will rapidly increase by 2050 and 2100.The storm surge will greatly impact the coastal area within about 10-30 km of the Bohai Bay,in where almost all major coastal projects are located.The prompt response to flood disaster due to storm surge is urgently needed,for which five suggestions have been proposed based on the geological background of Bohai Bay.This study may offer insight into the development of the response and adaptive plans for flooding disasters caused by storm surge.

Analysis of the Heavy Rainfall Process in Mangshi City on August 8, 2023

On August 7,2023,Mangshi City,Dehong Prefecture experienced a local heavy rainstorm,and the geological disaster caused by the heavy rainfall caused casualties and property losses.Based on the real-time observation data of automatic stations,Doppler weather radar detection and meteorological risk warning products,the disaster situation,social impact,forecast and early warning service,causes of heavy precipitation and forecast and early warning inspection were summarized and analyzed.The results show that the heavy rainfall was prominent locally,lasted for a long time and accumulated a large amount of rainfall.There were biases in model products,and it was difficult for forecasters to make subjective corrections in complex terrain.The analysis ideas and focus points of heavy rainfall forecast,the improvement ideas and technical schemes of forecast deviation,and the improvement ideas and suggestions of services were summarized.It provides a reference for the forecast and early warning of severe weather in the future.

RS and GIS-based Statistical Analysis of Secondary Geological Disasters after the 2008 Wenchuan Earthquake

Using RS and GIS means, this article analyzes the general geological characteristics and the structural belt distribution features in Wenchuan County, Sichuan province, P.R. China as well as the characteristics of the large-scale landslides, mud-rock flows, earthquake lakes, etc., after the earthquake on May 12, 2008. Based on the above work, comprehensive indoor and outdoor research is launched on disaster distribution characteristics and their relationship with earthquakes, terrains, strata, lithology, and structures. Weights of evidence method is utilized to quantitatively analyze and evaluate the spatial distribution of secondary geological disasters after the earthquake occurred. 3 remedying grades for secondary geological disasters are derived from the results of the weights of Evidence, followed by suggestions given to remedy earthquake secondary disasters.

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.

New Thought of Meteorological Forecasting and Warning Models of Geological Disasters in Loess Plateau of North Shaanxi

The study established daily comprehensive precipitation equations and calculated respective critical daily comprehensive precipitation value of loess-collapse disasters and landslide disasters by dint of the geological disasters and corresponding precipitation data in 47 years.Considering geological disaster risk divisions,precipitation influence coefficient and daily comprehensive precipitation,hourly rolling daily-forecasting and hourly warning fine and no-gap models on the base of high temporal and spatial resolution rainfall data of automatic meteorological station were developed.Through the verifying of combination of dynamical forecasting model and warning model,the results showed that it can improve efficiency of forecast and have good response at the same time.

Factor analysis of earthquake-induced geological disasters of the M7.0 Lushan earthquake in China

The seismic intensities, lithologic characteristics and terrain features from a 3000 km2-region near the epicenter of the Lushan earthquake are used to analyze earthquake-induced geological disaster. The preliminary results indicate that secondary effects of the earthquake will affect specific areas, including those with glutenite and carbonate bedrock, a seismic intensity of IX, slopes between 40° and 50°, elevations of less than 2500 m, slope change rates between 20° and 30°, slope curvatures from - 1 to -0.5 and 0. 5 to 1, and relief between 50 and 100 m. Regions with susceptibility indices greater than 0.71 are prone to landslides and collapses. The secondary features are mainly distributed on both sides of the ridges that extend from Baosheng to Shuangshi and from Baosheng to Longxing. Other features are scattered on both sides of the ridges that extend from Qishuping to Baosheng and from Masangping to Lingguan. The distribution of the earthquake-related features trends in the NE direction, and the area that was most affected by the Lushan earthquake covers approximately 52.4 km^2.

Construction of Forecast and Early Warning System of Meteorological and Geological Disasters in Qinghai Province

Based on the meteorological and geological disaster data, ground observation data set, CLDAS grid point data set, and EC, BJ and other model product data during 2008-2020, the temporal and spatial distribution characteristics of meteorological and geological disasters and precipitation were analyzed, and the causes of the occurrence of meteorological geological disasters and the deviation of model precipitation forecast were revealed. Besides, an objective precipitation forecast system and a forecast and early warning system of meteorological and geological disasters were established. The results show that meteorological and geological disasters and precipitation were mainly concentrated from May to October, of which continuous precipitation appeared frequently in June and September, and convective precipitation was mainly distributed in July-August;the occurrence frequency of meteorological and geological disasters was basically consistent with the distribution of accumulated precipitation and short-term heavy precipitation, and they were mainly concentrated in the southern and eastern parts of Qinghai. Meteorological and geological disasters were basically caused by heavy rain and above, and meteorological and geological disasters were divided into three types: continuous precipitation(type I), short-term heavy precipitation(type II) and mixed precipitation(type III). For type I, the early warning conditions of meteorological and geological disasters in Qinghai are as follows: if the soil volumetric water content difference between 0-10 and 10-40 cm is ≤0.03 mm^(3)/mm^(3), or the soil volumetric water content at one of the depths is ≥0.25 mm^(3)/mm^(3), the future effective precipitation reaches 8.4 mm in 1 h, 10.2 mm in 2 h, 11.5 mm in 3 h, 14.2 mm in 6 h, 17.7 mm in 12 h, and 18.2 mm in 24 h, and such warning conditions are mainly used in Yushu, Guoluo, southern Hainan, southern Huangnan and other places. For type II, when the future effective precipitation is up to 11.5 mm in 1 h, 14.9 mm in 2 h, 16.2 mm in 3 h, 19.9 mm in 6 h, 25.3 mm in 12 h, and 26.3 mm in 24 h, such precipitation thresholds are mainly used in Hainan, Huangnan, and eastern Guoluo;as it is up to 13.3 mm in 1 h, 15.5 mm in 2 h, 16.6 mm in 3 h, 19.9 mm in 6 h, 31.1 mm in 12 h, and 34.0 mm in 24 h, such precipitation thresholds are mainly used in Hehuang valley. The precipitation thresholds of type III are between type I and type II, and closer to that of type II;such precipitation thresholds are mainly used in Hainan, Huangnan, and northern Guoluo. The forecasting ability of global models for heavy rain and above was not as good as that of mesoscale numerical prediction model, and global models had a wet bias for small-scale precipitation and a dry bias for large-scale precipitation;meso-scale models had a significantly larger precipitation bias. The forecast ability of precipitation objective forecast system constructed by frequency matching and multi-model integration has improved. At the same time, the constructed grid forecast and early warning system of meteorological and geological disasters is more precise and accurate, and is of instructive significance for the forecast and early warning of meteorological and geological disasters.

Application of Electronic Sand Table System in Geological Disasters Meteorological Service Based on GIS

With complex terrain and developed economy, Zhejiang Province has suffered a lot from the frequent geological disasters, which have done great damages to the construction and development of the whole province. Therefore, it is particularly important to improve the geological disasters meteorological service. Electronic sand table system, a high-tech product of three-dimensional visualization, can provide the geological disaster meteorological service with the intuitive and visual application environment. In this study, we developed electronic sand table system based on GIS and established the geological disasters meteorological service database. In addition, we also analyzed and discussed the applications of meteorological service in online weather forecast, meteorological warning message, and multimedia meteorological electronic display. The application of electronic sand table system in geological disaster meteorological services for disaster prevention and mitigation is of great importance that it provides intuitive terrain analysis data for the forecast of geological disasters warning, which greatly enhances the ability of geological disasters meteorological service.

Analysis on the Relationship between Geological Disasters and Precipitation in Zhuanghe Region

To improve relevance and timeliness of forecasting and early warning for precipitation-type geological disasters in Zhuanghe City, by using case information of geological disasters and corresponding precipitation data in Zhuanghe City during 2009 -2011, the relationship between geological disasters and precipitation was analyzed. Results showed that precipitation-type geological disasters in Zhuanghe City had close relationships with precipitation intensity in prior period and rainfall on the day. The research had important actual significance for prevention of geological disasters.

Impulsion discharge technique and its application in geology casulty control

Impulsion discharge technique is a new technology to prevent geological disasters, such an approach is in a liquid medium into the borehole electrode to gain access ,o high-voltage, forme discharge, and mechanical wave energy into electrical energy, produce a shockwave and in the same time compact the surrounding soil. Building on the existing foundation of the Act has been applied to engineering and water conservancy projects, the results were very good.

Study on Quantitative Assessment for the Social Risk of Major Geological Disasters

Based on the analysis of social risk of geological disasters,the index system of social risk evaluation was established. To assess the social risk quantitatively,a quantitative evaluation model of the social risk was established based on AHP,and the social risk of geological disasters was graded. Finally,the evaluation model was applied in a case.

Imbalance Between Scientific Technology and Human Rights and Measures to Rectify the Imbalance——Taking Geological Disasters as an Example

I. Increase in Human Activity and Occurrence of Geological Disasters ＂A geological disaster is a natural disaster that happens in a geo- logical environment. It is a geological effect （phenomenon） caused or in- fluenced by Nature and （or） human factors that leads to losses to human life, property and the environment.TM Based on their cause, geological disasters can be divided into natural geological and artificial geological disasters. Natural geological disas- ters include those caused by natural effects. These include typhoons, rain- fall, melting snow and earthquakes,

Landslide susceptibility assessment in Western Henan Province based on a comparison of conventional and ensemble machine learning

Landslide is a serious natural disaster next only to earthquake and flood,which will cause a great threat to people’s lives and property safety.The traditional research of landslide disaster based on experience-driven or statistical model and its assessment results are subjective,difficult to quantify,and no pertinence.As a new research method for landslide susceptibility assessment,machine learning can greatly improve the landslide susceptibility model’s accuracy by constructing statistical models.Taking Western Henan for example,the study selected 16 landslide influencing factors such as topography,geological environment,hydrological conditions,and human activities,and 11 landslide factors with the most significant influence on the landslide were selected by the recursive feature elimination(RFE)method.Five machine learning methods[Support Vector Machines(SVM),Logistic Regression(LR),Random Forest(RF),Extreme Gradient Boosting(XGBoost),and Linear Discriminant Analysis(LDA)]were used to construct the spatial distribution model of landslide susceptibility.The models were evaluated by the receiver operating characteristic curve and statistical index.After analysis and comparison,the XGBoost model(AUC 0.8759)performed the best and was suitable for dealing with regression problems.The model had a high adaptability to landslide data.According to the landslide susceptibility map of the five models,the overall distribution can be observed.The extremely high and high susceptibility areas are distributed in the Funiu Mountain range in the southwest,the Xiaoshan Mountain range in the west,and the Yellow River Basin in the north.These areas have large terrain fluctuations,complicated geological structural environments and frequent human engineering activities.The extremely high and highly prone areas were 12043.3 km^(2)and 3087.45 km^(2),accounting for 47.61%and 12.20%of the total area of the study area,respectively.Our study reflects the distribution of landslide susceptibility in western Henan Province,which provides a scientific basis for regional disaster warning,prediction,and resource protection.The study has important practical significance for subsequent landslide disaster management.

Progress and Prospects of the Natural Restoration of Damaged Vegetation after the Earthquake

Vegetation plays an important role in soil and water conservation, water conservation and carbon sequestration of an ecosystem. The restoration of damaged vegetation is of great significance to the maintenance of species diversity and the restoration of the regional ecological environment. It is also one of the most effective measures to improve the fragile ecosystem. This paper summarizes the research results from decades of damaged vegetation recovery in the process of vegetation recovery, the main driving factor and the restoration mode.

Remote Sensing Landslide Monitoring Based on Machine Learning Method

The susceptibility evaluation of landslides has become one of the key environmental issues that people are concerned about. This study took the land-slides in Xishuangbanna, Yunnan Province as the study object, and selected 10 evaluation factors such as digital elevation model (DEM), slope aspect, precipitation, land use, water system, roads, population density, lithology, faults, and NDVI. Different machine learning methods were compared and studied, and the ROC (receiver operating characteristics) curve verification revealed that the accuracy of the random forest evaluation model was high. In the prediction and evaluation of the susceptibility of landslides, five risk levels were divided. After the superimposed analysis, 87.26% of the disaster points fell in the first and second susceptibility areas. The spot analysis found that the distribution of hot spots is consistent with the distribution of disaster spots. In a word, the results of this study can provide better technical support for the evaluation and early warning of landslides in Southwest China.