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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.)

In recent years, we have witnessed an increase in road subsidence accidents in urban areas, threatening the safety of citizens. Various road facilities, such as water and sewage pipes, and telecommunication facilities are buried under roads, and the aging of these facilities is one of the factors causing road subsidence. In particular, old sewer pipes are a primary cause of road subsidence. However, most maintenance work on such facilities is carried out based on how long ago they were buried underground, without considering the risk of road subsidence caused by them. Therefore, this study aims to present a reliable method to assess road subsidence risk that considers various sewer pipe specifications and the environment surrounding them. To derive the factors influencing subsidence, sewer pipes near the target region, where road subsidence occurs the most, were extracted to analyze the correlation between road subsidence, pipe integrity, and the surrounding environment. An effective analysis method was selected by comparing logistic regression analysis and AHP (Analytic Hierarchy Process) analysis, and a weighted road subsidence risk assessment method was proposed by evaluating the importance of factors affecting ground subsidence. Its applicability was examined by comparing actual road subsidence data and analyzing risk in a pilot study area to validate the reliability of the proposed methodology. The results showed that it was possible to make reliable predictions of road subsidence risk areas. [ABSTRACT FROM AUTHOR]

The rupture of an unpressurized pipeline below the water table can lead to the leakage of groundwater along with soil particles into the pipeline. This not only causes blockages in the pipeline but, more critically, can result in ground subsidence. Understanding the factors influencing this phenomenon is a subject of great interest. To delve into this matter, this study employs the DEM-CFD methodology to synergistically encompass particle dynamics and interactions within the flow domain. It introduces an innovative framework for simulating water and soil erosion subsequent to the rupture of subaqueous unpressurized pipelines. This pioneering approach introduces a novel modeling and simulation paradigm catering to the analysis of intricate phenomena of this nature. Upon validating the flow field, our investigation specifically focused on three key factors: particle friction coefficient, groundwater level, and particle size distribution. We conducted a thorough examination of the process and mechanism of water and soil loss at the pipeline leakage point and the subsequent development of stratum subsidence. Our results indicate that particles with a friction coefficient of 0.6 had a reduced maximum displacement by 8.9%, compared to particles with a friction coefficient of 0.3. Similarly, a groundwater depth of 2 m resulted in a 29.6% decrease in maximum displacement compared to a 4 m depth, with a corresponding 160.9% increase in maximum force chain strength. Discontinuous particle gradation, in contrast to continuous gradation, yielded a notable 40.3% reduction in maximum displacement and a substantial 495.1% increase in maximum force chain strength. This underscores the noteworthy influence of particle friction coefficient, groundwater table elevation, and soil particle diameter on the stability of the overlying soil strata in the vicinity of a compromised unpressurized conduit. [ABSTRACT FROM AUTHOR]

Copyright of Industrial Minerals & Processing / Huagong Kuangwu yu Jiagong is the property of Industrial Minerals & Processing 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.)

Long-term field monitoring finds that serious surface subsidence can still occur even if the high strength cemented fill method is adopted. Combining the results of numerical simulations with global position system (GPS) monitoring, we took a typical filling mining mine with a steeply inclined ore body as an example, and explored its ground subsidence mechanism. The results show that the ground subsidence caused by the mining of steep ore body is characterized by two settlement centers and a significantly uneven spatial distribution, which is visibly different from ground subsidence characteristic of the coal mine. The subsidence on the hanging wall is much larger than that on the footwall, and the settlement center tends to move to the hanging wall with the increase of mining depth. The backfill improves the strength and surrounding rock bearing capacity, which leads to a lag of about 3 years of the subsidence. However, under the actions of continuous and repeated mining disturbances, the supporting effect of the backfill can only reduce the amplitude of the deformation, but it cannot prevent the occurrence of settlement. [ABSTRACT FROM AUTHOR]

Featured Application: Authors are encouraged to provide a concise description of the specific application or a potential application of the work. This section is not mandatory. The main cause of ground subsidence accidents in urban areas is cavities formed by damage to underground utilities. For this reason, the attribute information of underground utilities should be used to prepare against ground subsidence accidents. In this study, attribute information (pipe age, diameter, burial depth, and density) of six types of underground utilities (water, sewer, gas, power, heating, and communication) and history information of ground subsidence were collected. A correlation analysis was conducted using the collected data, and a prediction model of vulnerability to ground subsidence was developed through the ordinary least squares (OLS) method and spatial regression analysis (spatial lag model (SLM) and spatial error model (SEM)). To do this, the target area was divided into a grid of 100 m × 100 m. Datasets were constructed using the attribute information of underground utilities included in the divided grid and the number of ground subsidence occurrences. To analyze the OLS of the constructed data, the variance inflation factor (VIF) of the attribute information of underground utilities was studied. An OLS analysis was conducted using the appropriate factors, and the results show that the spatial data were autocorrelated. Subsequently, SEM and SLM analyses, which were spatial regression analyses, were conducted. As a result, the model using SLM was selected as suitable for analyzing the vulnerability of ground subsidence, and the density of six types of underground utilities was found to be the highest influencing factor. In addition, a vulnerability map of ground subsidence in the target area was prepared using the model. The vulnerability map demonstrates that regions with frequent ground subsidence can be predicted to be highly vulnerable. [ABSTRACT FROM AUTHOR]

In order to realize the monitoring of deformation in the urban area of Hohhot city, this paper uses the permanent scatterer synthetic aperture radar interferometry （PS-InSAR） technique to perform temporal interferometric processing on 25 scenes of Sentinel-1A data from March 2017 to April 2021 in the urban area of Hohhot city to extract the surface subsidence information in the urban area and analyze the causes of subsidence in the main subsidence centers. The results show that there are five obvious centres of subsidence in the urban area of Hohhot, and that the overall average annual surface subsidence rate is 3.65 mm/a, with an average cumulative subsidence of 15.50 mm. The subsidence is mainly due to over-exploitation of groundwater. Given that the free Sentinel-1A data has the advantages of short time baseline and sufficient number of images, it is conducive to InSAR time series analysis, which can meet similar urban surface deformation monitoring work and serve urban safety.

Due to the overexploitation of water resources, ground subsidence is becoming increasingly problematic in Beijing, China's political, economic, and cultural capital. This article aims to investigate the relationship between ground subsidence and changes in groundwater depth, and water supply from a long-term point of view. Multisource synthetic aperture radar (SAR) data using the interferometric SAR (InSAR) technique were adopted in this research, combined with a set of leveling and ground subsidence data in the Beijing Plain area from 2003 to 2020. The InSAR results demonstrate that ground subsidence in the plain area increased steadily from 2003 to 2015, expanding from sporadic to continuous laminar dispersion and producing five major subsidence centers. The South-to-North Water Diversion Project (SNWDP) that was completed in 2008 and 2015 considerably reduced the demand for groundwater supply in the Beijing Plain area. Since then, the groundwater level depth has continued to increase. However, since 2016, the ground subsidence rate has dramatically slowed down. The obtained results showed that, thanks to the SNWDP, which resulted in a decline in groundwater exploitation and an increase in renewable water recycling, the ground subsidence in Beijing's plain area has been effectively managed.

In this study, a machine learning-based prediction model was developed using the attribute information of underground pipelines and the history information of ground subsidence in order to predict the risk level of ground subsidence in urban areas. The target area was divided into a grid with sizes of 100m $\times 100\text{m}$ , 300m $\times 300\text{m}$ , and 500m $\times 500\text{m}$ , and the attribute information of underground pipelines in the grid and ground subsidence data were utilized to build a dataset. For input data, the pipeline’s diameter, the number of years used, and density were selected based on the pipeline’s length as the basic unit. Additionally, the risk level of ground subsidence was determined as the output data using historical information. A total of 36 datasets were built according to the conditions, and factors with significant correlation were selected through a correlation analysis of the datasets. The developed datasets were divided into training data and evaluation data. The synthetic minority oversampling technique was used to resolve the data imbalance. The model performance evaluation indexes used in this study were F1-score and AUC(Area Under the Curve). The performance of each model was compared, and the comparison results showed that a model that applied a preprocessed dataset with 500m $\times 500\text{m}$ grid size, 10 years in use, 100mm pipeline diameter, and 1–2 ground sinks in Level 1 risk range to the LGBM(Light Gradient Boosting Model) classifier derived the best evaluation indexes(F1-Score:0.750, AUC:0.840). The map was found to be effective for predicting the risk level of ground subsidence in urban areas.

Ground subsidence is a significant safety concern in mining regions, making large-scale subsidence forecasting vital for mine site environmental management. This study proposes a deep learning-based prediction approach to address the challenges posed by the existing prediction methods, such as complicated model parameters or large data requirements. Small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology was utilized to collect spatiotemporal ground subsidence data at the Pingshuo mining area from 2019 to 2022, which was then analyzed using the long-short term memory (LSTM) neural network algorithm. Additionally, an attention mechanism was introduced to incorporate temporal dependencies and improve prediction accuracy, leading to the development of the AT-LSTM model. The results demonstrate that the Pingshuo mine area had subsidence rates ranging from −205.89 to −59.70 mm/yr from 2019 to 2022, with subsidence areas mainly located around Jinggong-1 (JG-1) and the three open-pit mines, strongly linked to mining activities, and the subsidence range continuously expanding. The spatial distribution of the AT-LSTM prediction results is basically consistent with the real situation, and the correlation coefficient is more than 0.97. Compared with the LSTM, the AT-LSTM method better captured the fluctuation changes of the time series for fitting, while the model was more sensitive to the mining method of the mine, and had different expressiveness in open-pit and shaft mines. Furthermore, in comparison to existing time-series forecasting methods, the AT-LSTM is effective and practical. [ABSTRACT FROM AUTHOR]

In this paper, the effect of tunnel excavation and Metro station has been investigated on adjacent bridge foundation with two objectives: investigation of the subsidence by tunneling and the effect of tunnel excavation on the behavior of adjacent bridge foundation by Plaxis 3D finite element software. Therefore, the tunnel of Line 3 of the Tehran Metro near Nobonyad Square, which passes through a pier of the Sadr Bridge to the Nobonyad Metro Station, was selected. To explore the effects of the pile length on settlement, the axial load and bending moments of three scenarios, including piles with a length of 37 m, piles with a length of 47 m, and no piles, were evaluated. It was found that settlement above the station and tunnel reduced near the bridge foundation, suggesting a stiff foundation. To study the effects of the tunnel on adjacent piles, the changes in the axial loads and bending moments of the piles under tunneling and station construction and then in two different models. The post-tunneling axial loads of the pipes showed significant differences from the pre-tunneling values. The results revealed that the axial pile load was slightly higher at a pile length of 47 m than at a pile length of 37 m. As with the axial load, the bending moment increased after tunneling. A comparison of the bending moment between the two models indicated that a 10-m reduction in the pile length would not change the behavior and bending moment of the piles. [ABSTRACT FROM AUTHOR]

Carbonate karst geothermal resources are widely distributed and have large reserves in North China. Currently, the scale of exploitation and utilization of the carbonate karst geothermal resources is gradually increasing. In this work, a geothermal exploitation area where the karst geothermal reservoirs are exploited on a large scale is selected as the study area, and methods including experiment and numerical simulation are used to study the exploitation-induced ground subsidence problems based on the long-term water level monitoring data of the geothermal reservoir. Through analyses of ground subsidence caused by water level changes in the geothermal reservoir, the following conclusions were obtained. The water level drawdown of different types of geothermal reservoirs had different effects on ground subsidence. The maximum ground subsidence of the study area caused by the water level decline of the Jxw carbonate geothermal reservoir was only 0.29 mm/a from 1983 to 2019, which is generally insignificant. In contrast, the same water level change of the Nm sandstone geothermal reservoir was predicted to cause 8.9 mm/a ground subsidence. To slow down or even prevent the ground subsidence, balanced production and reinjection are required. From the result of this work, it can be concluded that the decline of the water level of the Jxw carbonate geothermal reservoir caused by current large-scale geothermal exploitation will not cause serious ground subsidence. [ABSTRACT FROM AUTHOR]

Objectives: To prove the effectiveness of interferometric synthetic aperture radar （InSAR） data in describing the deformation in the local area, the vertical deformation surface information of Shaanxi Province is obtained with Sentinel-1 free data of European Space Agency from 2018 to 2019. Methods: The information is compared with the point and line vertical deformation information from the global navigation satellite system (GNSS) and the level. Results: The results of vertical deformation monitoring show that the uneven subsidence with the maximum velocity of 60 mm/a occurred in the local mining areas of Yulin and Shenmu where the subsidence of surface widely distributed and have obvious characteristics. There are also subsidence with the velocity of 30 mm/a in Changwu and Binxian where the coal has been roughly mined for long time. Uneven subsidence occurs in Xi’an, Weinan of Guanzhong Plain due to excessive groundwater exploitation. The subsidence of local area in Xi’an is the most serious, with the maximum velocity of 60 mm/a. Conclusions: The vertical movement trends of InSAR are consistent with the results of GNSS and level in Shaanxi Province on the whole, however the GNSS monitoring points and the level monitoring points are generally deployed in the stable areas, the subsidence range and subsidence velocity obtained by them are somewhat different from the subsidence results obtained by InSAR. [ABSTRACT FROM AUTHOR]

In this study, a new mechanical model is proposed to compute earth pressure above a pipeline considering pipe-soil interaction and three-dimensional soil arching effects of cohesive fills, based on the Terzaghi vertical sliding surface theory. In this model, the pipeline was mechanically separated into buried and suspended segments, whose stress distribution and deformation were solved according to the boundary conditions and geometric conditions. Comparisons to both the test data and corresponding finite element codes concretely verify the proposed mechanical model. Then a parametric investigation indicated that the mechanical behavior of the pipe is greatly affected by the size of a subsidence area and the flexural rigidity of the pipe. [ABSTRACT FROM AUTHOR]

[Display omitted] • GSREI regarding accumulated subsidence, subsidence rate, and elevation. • VEI from population, GDP, construction land, viaduct and metro density. • Risk assessment model and the GSHI index. Urban ground subsidence (GS) causes ground elevation loss, threatens the safe operation of various facilities, and affects surface runoff and hydrological circulation. Therefore, it is vital to monitor the current status of GS to predict and evaluate potential risks to sustainable urban development. Sentinel SAR images from 2019 to 2020 combined with the data from the 2019–2020 Statistical Yearbook were used as data sources. Based on PS-InSAR and SBAS-InSAR, GIS was integrated with the AHP method. A ground subsidence risk evaluation index (REI) suitable for Shanghai was developed regarding three aspects of the amount of accumulated land subsidence (RS obtained): subsidence rate, and terrain elevation. The vulnerability evaluation index (VEI) was established from five aspects: population density, GDP per unit area, the proportion of construction land, viaduct density, and metro density. We introduced the fuzzy AHP method to complete the risk assessment of ground subsidence in Shanghai and obtained the ground subsidence hazard index (GSHI). We used GIS superimposed remote sensing images to visualize the individual evaluation indicators REI , VEI , and GSHI. Using GIS superimposed remote sensing images, various evaluation indicators and GSHI were visualized. Based on the evaluation results, targeted prevention and control recommendations are provided. The results of this research can provide a basis for scientific decision-making regarding Shanghai's territorial spatial planning and socio-economic development. [ABSTRACT FROM AUTHOR]

As ground subsidence accidents in urban areas that occur due to damage to underground utilities can cause great damage, it is necessary to predict and prepare for such accidents in order to minimize such damage. It has been reported that the main cause of ground subsidence in urban areas is cavities in the ground formed by damage to underground utilities. Thus, in this study, attribute information and historical ground subsidence information of six types of underground utility lines (water supply, sewage, power, gas, heating, and communication) were collected to develop a ground subsidence risk prediction model based on machine learning. To predict the risk of ground subsidence in the target area, it was divided into a grid with a square size of 500 m × 500 m, and attribute information of underground utility lines and historical information of ground subsidence included in the grid were extracted. Six types of underground utility lines were merged into single-type attribute information, and the risk of ground subsidence was categorized into three levels using the number of ground subsidence occurrences to develop a dataset. In addition, 12 datasets, which were developed based on the conditions of certain divided ranges of attribute information and risk levels, and 12 additional datasets, which were developed using the Synthetic Minority Oversampling Technique to resolve the imbalance of data, were built. Then, factors that represented significant correlations between input and output data were singled out and were then applied to the RandomForest, XGBoost, and LightGBM algorithms to select a model that produced the best performance. By classifying the ground subsidence risk levels through the selected model, it was found that density was the most important influencing factor used in the model. A risk map of ground subsidence in the target area was made through the model; the map showed the trend of well-predicted risk levels in the area where ground subsidence was concentrated. [ABSTRACT FROM AUTHOR]

In recent years, the mined-out area resulting in more than 20 goaf collapse disasters in the north Pizhou, Jiangsu Province. The traditional monitoring method of surface soil deformation is difficult to meet the requirement of advance prediction of surface subsidence. In order to solve the lack of monitoring and early warning mechanism of mined-out subsidence in gypsum mining area, a monitoring and early warning system based on fiber sensing technology was developed in this area. According to the results of preliminary investigation, analysis and numerical simulation, the ground collapse mechanism of gypsum mine is deduced, dynamic monitoring of groundwater level, displacement of deep rock and soil mass and microseismic monitoring of bottom aquifer above loose layer were monitored by optical fiber sensor, in the course of monitoring, the alarm will be triggered when the fluctuation of water level and the displacement of rock and soil suddenly exceed the normal fluctuation value or when a strong vibration signal is received, and the effective early warning will be carried out in the early stage of the ground collapse, and can provide adequate lead time for disaster prevention and mitigation efforts. Through the implementation of monitoring and early-warning work, the validity of these monitoring and early-warning means has been verified, which can provide data basis and scientific basis for the monitoring, prediction and prevention of ground subsidence in mining areas, it can also provide reference for prevention, control, monitoring and early warning of ground collapse geological disaster in gypsum mine and other similar conditions.

Ground subsidence is important during shield construction. How to select reasonable tunnelling parameters is critical to control ground subsidence. However, the selection of shield tunnelling parameters for ground subsidence control usually relies on human experience. It is critical to study how to make judgements of ground subsidence adaptively during shield construction and give recommended values of tunnelling parameters to mitigate subsidence. To meet the above requirements, this paper innovatively proposes a method for analysing the correlation between ground subsidence and tunnelling parameters based on the fusion method of qualitative and quantitative models. First, the a priori algorithm based on MAX–MIN Ant System is adopted to analyse the qualitative relationship between ground subsidence and tunnelling parameters and provides the tunnelling parameters intervals under different ground subsidence intervals. Second, the improved Beetle Antennae Search-Deep Neural Networks is constructed to calculate the occurrence probability of different discrete internals of ground subsidence to correct the rougher results obtained by qualitative analysis. Finally, a qualitative and quantitative model fusion formula is proposed. The occurrence probability is used to modify the discrete interval value range of the tunnelling parameters intervals under different ground subsidence intervals to obtain the optimised values' range of the key tunnelling parameters under different ground subsidence intervals. The proposed model is used in case analysis. The results of the model predict the probability values corresponding to each subsidence interval that occurred. The prediction accuracy of the quantitative model between ground subsidence and tunnelling parameters in different intervals is higher than 96%. Highlights: The maximum-minimum ant system is applied to the Apriori algorithm to construct the qualitative correlation model in the process of qualitative analysis. Deep Neural Networks quantitative model optimizes the initial weight of the Deep Neural Networks. A qualitative and quantitative model fusion formula is creatively proposed. [ABSTRACT FROM AUTHOR]

In order to realize the monitoring of deformation in the urban area of Hohhot city, this paper uses the permanent scatterer synthetic aperture radar interferometry (PS-InSAR) technique to perform temporal interferometric processing on 25 scenes of Sentinel-1A data from March 2017 to April 2021 in the urban area of Hohhot city to extract the surface subsidence information in the urban area and analyze the causes of subsidence in the main subsidence centers. The results show that there are five obvious centres of subsidence in the urban area of Hohhot, and that the overall average annual surface subsidence rate is 3.65 mm/a, with an average cumulative subsidence of 15.50 mm. The subsidence is mainly due to over-exploitation of groundwater. Given that the free Sentinel-1A data has the advantages of short time baseline and sufficient number of images, it is conducive to InSAR time series analysis, which can meet similar urban surface deformation monitoring work and serve urban safety. [ABSTRACT FROM AUTHOR]

Large–scale underground coal mining is bound to cause serious surface subsidence problems. However, conventional filling and mining methods have problems such as high cost and process difficulty. In order to achieve the purpose of high efficiency and low cost, this paper proposes using the technology of CGSG. To achieve the effective control of overburden strata movement and ground surface settlement using cemented gangue strip filling in the goaf (CGSG), this paper studies the design principles and methods of the key parameters of the strip–filling structure including the strength, compressed deformation characteristics, and sizes. Based on the analysis of the structures and movement characteristics of the overburden strata above the coal seam, the mechanical relationship between the strip–filling structure and the overburden strata was established. Formulas for calculating the parameters of the strip–filling structure were derived. Guided by the obtained index parameters, the material ratios and mechanical experiments of the filling body were designed. The research results demonstrated that the strengths of the cemented gangue filling body at different ages should be greater than the compressive load of the strata roof movement on the filling body during the same period; under the compression of the maximum load, the ultimate compressive deformation of the filling body should be less than the ultimate subsidence deflection of the basic roof strata. The width of the strip–filling structure was inversely proportional to its ultimate strength, while the width of the non–filling area was greatly affected by the length of the rock beam formed after the basic roof strata fractured. The research results were applied in the No. 7402 experimental strip–filling workface in Zhaizhen coal mine, China. Reasonable parameters of the cemented gangue strip–filling structure were designed. The field application results demonstrated that, after using the technology of CGSG, there was no obvious pressure appearance when the working face was mined. The maximum sinking value of the ground surface was only 30 mm after the mining of the working face was completed; at the same time, the filling cost was about one–third less than the complete–filling technology in the goaf. [ABSTRACT FROM AUTHOR]

Recently, a number of earthquakes have been detected in Korea and damage has been reported. Actually, ground liquefaction was reported due to the earthquake that occurred in the Pohang. In Korea, the risk of liquefaction in the event of an earthquake is relatively higher as there are many landfill areas such as Busan's coastline, Incheon, and Cheongna International City. In this study, the effect of underground structures when liquefaction occurs is evaluated by dividing it into stages of liquefaction. Moreover, detailed evaluation methods for buried gas pipelines are presented in case of regional liquefaction that can be used in all regions. For the risk assessment of liquefaction, the Standard Penetration Test (SPT) result or Cone Penetration Test (CPT) result of the borehole is used. To evaluate buried gas pipelines, Finite Element (FE) analysis is performed using the subsidence calculation method linked with the borehole data. By defining ground and gas pipe variables, structural analysis is conducted in several cases, and the desired area is evaluated based on this. A Winkler foundation spring-based optimal finite element analysis model is developed to evaluate the structural seismic performance of gas pipelines across areas where liquefaction is expected. [ABSTRACT FROM AUTHOR]

Copyright of Acta Scientiarum Naturalium Universitatis Sunyatseni / Zhongshan Daxue Xuebao is the property of Sun-Yat-Sen University 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.)

The circum-arctic permafrost environment is often disturbed by wildfires but could also show resilience to these disturbances. However, the increased frequency and extent of wildfires, coupled with unprecedented hot weather, have introduced greater uncertainties in the post-fire permafrost dynamics. We need to address emerging questions, e.g. How will permafrost respond to the joint effect of hot anomalies and wildfires? To what extent will post-wildfire deformation evolve? How will permafrost resilience to wildfires vary? Utilizing interferometric synthetic aperture radar time series analysis, we investigated the post-wildfire ground deformation around a 2019 fire scar in the lower Mackenzie Valley, Northwest Territories, Canada, where dramatic heat anomalies and severe wildfires have been recorded in recent years. The resilience of permafrost to wildfires appears to be weakened by the continuous and rapid warming after the fire, as evidenced by the year-on-year acceleration in subsidence rates. Such acceleration was never reported by previous findings that typically observed deceleration in subsidence rates four to five years after wildfires. The deformation along the line of sight (LOS) of the satellite demonstrates significant permafrost degradation induced by wildfires and exacerbated by climate warming, and the cumulative subsidence was detected up to 25 cm in the LOS direction in the upland areas and up to 10 cm in the lowland areas four years after the fire. The difference in deformation magnitude could be attributed to local factors, including ground ice, topography, and vegetation. Our study highlights the increasingly severe threat to circum-arctic permafrost due to the combined effects of wildfires and extreme heat anomalies.

In this paper, GNSS interferometric reflectometry (GNSS-IR) is firstly proposed to estimate ground surface subsidence caused by underground coal mining. Ground subsidence on the main direction of a coal seam is described by using the probability integral model (PIM) with unknown parameters. Based on the laws of reflection in geometric optics, model of GNSS signal-to-noise (SNR) observation for the tilt surface, which results from differential subsidence of ground points, is derived. Semi-cycle SNR observations fitting method is used to determine the phase of the SNR series. Phase variation of the SNR series is used to calculate reflector height of ground specular reflection point. Based on the reflector height and ground tilt angle, an iterative algorithm is proposed to determine coefficients of PIM, and thus subsidence of the ground reflection point. By using the low-cost navigational GNSS receiver and antenna, an experimental campaign was conducted to validate the proposed method. The results show that, when the maximum subsidence is 3076 mm, the maximum relative error of the proposed method-based subsidence estimation is 5.5%. This study also suggests that, based on the proposed method, the navigational GNSS instrument can be treated as a new type of sensor for continuously measuring ground subsidence deformation in a cost-effective way. [ABSTRACT FROM AUTHOR]

Time-series interferometric synthetic aperture radar (TS-InSAR) is often affected by tropospheric artifacts caused by temporal and spatial variability in the atmospheric refractive index. Conventional temporal and spatial filtering cannot effectively distinguish topography-related stratified delays, leading to biased estimates of the deformation phases. Here, we propose a TS-InSAR atmospheric delay correction method based on ERA-5; the robustness and accuracy of ERA-5 data under the influence of different atmospheric delays were explored. Notably, (1) wet delay was the main factor affecting tropospheric delay within the interferogram; the higher spatial and temporal resolution of ERA-5 can capture the wet delay signal better than MERRA-2. (2) The proposed method can mitigate the atmospheric delay component in the interferogram; the average standard deviation (STD) reduction for the Radarsat-2 and Sentinel-1A interferograms were 19.68 and 14.75%, respectively. (3) Compared to the empirical linear model, the correlation between the stratified delays estimated by the two methods reached 0.73. We applied this method for the first time to a ground subsidence study in the Yuxi Basin and successfully detected three subsidence centers. We analyzed and discussed ground deformation causes based on rainfall and fault zones. Finally, we verified the accuracy of the proposed method by using leveling monitoring data. [ABSTRACT FROM AUTHOR]

Mining-induced ground subsidence is a commonly observed geo-hazard that leads to loss of life, property damage, and economic disruption. Monitoring subsidence over time is essential for predicting related geo-risks and mitigating future disasters. Machine-learning algorithms have been applied to develop predictive models to quantify future ground subsidence. However, machine-learning approaches are often difficult to interpret and reproduce, as they are largely used as “black-box” functions. In contrast, stochastic differential equations offer a more reliable and interpretable solution to this problem. In this study, we propose a stochastic differential equation modeling approach to predict short-term subsidence in the temporal domain. Mining-induced time-series data collected from the Global Navigation Satellite System (GNSS) in our case study area were utilized to conduct the analysis. Here, the mining-induced time-series data collected from GNSS system regarding our case study area in Miyi County, Sichuan Province, China between June 2019 and February 2022 has been utilized to conduct the case study. The proposed approach is capable of extracting the time-dependent structure of monitored subsidence data and deriving short-term subsidence forecasts. The predictive outcome and time-path trajectories were obtained by characterizing the parameters within the stochastic differential equations. Comparative analysis against the persistent model, autoregressive model, and other improved autoregressive time-series models is conducted in this study. The computational results validate the effectiveness and accuracy of the proposed approach.

Commensurate with economic globalization, the demand for mineral resources is increasing. With increased mining activity, problems related to ground subsidence and rock movement are becoming increasingly prominent, even affecting mining production activities. However, the physical mechanisms behind the ground subsidence phenomenon have been poorly studied, especially for metal mines with a steep dip. This paper applies the Interferometric Synthetic Aperture Radar (InSAR) technique and the numerical simulation method to deduce the characteristics of rock movement in the Xinli deposit of the steeply inclined Sanshandao gold mine. The InSAR results indicate that more subsidence has occurred in the southern part of the Xinli Village coastline area than in the northern part. This is also supported by the numerical simulation results obtained by the fast Lagrangian analysis of continua in three dimensions (FLAC3D). Notably, the range of ground subsidence obtained by numerical simulation shows an obvious asymmetry. The monitoring data of the No. 55 prospecting profile offer a plausible explanation for this, as the surrounding rock of the fault’s hanging wall has a wider range of rock movements. Furthermore, the sublevels of the No. 55 prospecting profile at different depths show different rock movement characteristics, and a logistic function can be well applied to the right part of the settlement curve; the parameter “a” in the function formula is very close to the maximum subsidence value for each sublevel. We defined the ratio “r” to measure the difference between the maximum subsidence value and the corresponding parameter “a” and found this value to be positively correlated with the fractal dimension value of deeper sublevels (−320 m, −400 m, −480 m, and −600 m) and negatively correlated with the fractal dimension value of lower sublevels (−200 m and −240 m).

The rupture of an unpressurized pipeline below the water table can lead to the leakage of groundwater along with soil particles into the pipeline. This not only causes blockages in the pipeline but, more critically, can result in ground subsidence. Understanding the factors influencing this phenomenon is a subject of great interest. To delve into this matter, this study employs the DEM-CFD methodology to synergistically encompass particle dynamics and interactions within the flow domain. It introduces an innovative framework for simulating water and soil erosion subsequent to the rupture of subaqueous unpressurized pipelines. This pioneering approach introduces a novel modeling and simulation paradigm catering to the analysis of intricate phenomena of this nature. Upon validating the flow field, our investigation specifically focused on three key factors: particle friction coefficient, groundwater level, and particle size distribution. We conducted a thorough examination of the process and mechanism of water and soil loss at the pipeline leakage point and the subsequent development of stratum subsidence. Our results indicate that particles with a friction coefficient of 0.6 had a reduced maximum displacement by 8.9%, compared to particles with a friction coefficient of 0.3. Similarly, a groundwater depth of 2 m resulted in a 29.6% decrease in maximum displacement compared to a 4 m depth, with a corresponding 160.9% increase in maximum force chain strength. Discontinuous particle gradation, in contrast to continuous gradation, yielded a notable 40.3% reduction in maximum displacement and a substantial 495.1% increase in maximum force chain strength. This underscores the noteworthy influence of particle friction coefficient, groundwater table elevation, and soil particle diameter on the stability of the overlying soil strata in the vicinity of a compromised unpressurized conduit.

In recent years, we have witnessed an increase in road subsidence accidents in urban areas, threatening the safety of citizens. Various road facilities, such as water and sewage pipes, and telecommunication facilities are buried under roads, and the aging of these facilities is one of the factors causing road subsidence. In particular, old sewer pipes are a primary cause of road subsidence. However, most maintenance work on such facilities is carried out based on how long ago they were buried underground, without considering the risk of road subsidence caused by them. Therefore, this study aims to present a reliable method to assess road subsidence risk that considers various sewer pipe specifications and the environment surrounding them. To derive the factors influencing subsidence, sewer pipes near the target region, where road subsidence occurs the most, were extracted to analyze the correlation between road subsidence, pipe integrity, and the surrounding environment. An effective analysis method was selected by comparing logistic regression analysis and AHP (Analytic Hierarchy Process) analysis, and a weighted road subsidence risk assessment method was proposed by evaluating the importance of factors affecting ground subsidence. Its applicability was examined by comparing actual road subsidence data and analyzing risk in a pilot study area to validate the reliability of the proposed methodology. The results showed that it was possible to make reliable predictions of road subsidence risk areas.

Reclamation has allowed rapid land expansions for economic zones, residential areas, airports, industrial parks, and seaports. Meanwhile, the reclaimed lands often pose a risk of ground subsidence, jeopardizing functions of aboveground infrastructures, buildings, and facilities and threatening human lives. Therefore, it is critical to systematically monitor and manage the reclaimed lands after construction and minimize geohazard risks. This paper presents a case study on long-term remote monitoring of ground subsidence in reclaimed land using satellite synthetic aperture radar (SAR) data and the Persistent Scatterer Interferometric SAR (PS-InSAR) technique. The case study explores the excessive and persistent ground subsidence in Busan New Port, South Korea, which occurred since 2007. We employ large stacks of Sentinel-1 data acquired from the ascending and descending tracks for reliable estimation of ground subsidence and utilize the hyperbolic model, providing an updated prediction tool. A benchmarking and media fact-checking approach consistently supports our PS-InSAR analysis results. The time-series results show that the maximum subsidence rate is approximately −85 mm/yr along the radar line-of-sight (LOS). PS-InSAR can assist in saving expensive and laborious mapping and operational field-survey services and offers essential guidance for the next phase of future construction of Busan New Port. [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.)

Ground deformation is a major determinant of delta sustainability. Sentinel-1 Terrain Observation by Progressive Scans (TOPS) data are widely used in interferometric synthetic aperture radar (InSAR) applications to monitor ground subsidence. Due to the unparalleled mapping coverage and considerable data volume requirements, high-performance computing resources including graphics processing units (GPUs) are employed in state-of-the-art methodologies. This paper presents a fast InSAR time-series processing approach targeting Sentinel-1 TOPS images to process massive data with higher efficiency and resolution. We employed a GPU-assisted InSAR processing method to accelerate data processing. Statistically homogeneous pixel selection (SHPS) filtering was used to reduce noise and detect features in scenes with minimal image resolution loss. Compared to the commonly used InSAR processing software, the proposed method significantly improved the Sentinel-1 TOPS data processing efficiency. The feasibility of the method was investigated by mapping the surface deformation over the Yellow River Delta using SAR datasets acquired between January 2021 and February 2022. The findings indicate that several events of significant subsidence have occurred in the study area. Combined with the geological environment, underground brine and hydrocarbon extraction as well as sediment consolidation and compaction contribute to land subsidence in the Yellow River Delta. [ABSTRACT FROM AUTHOR]

Caused by the natural and engineering activities of human being factors, the ground subsidence is the disaster phenomenon of environmental geology with regionally ground level decreasing, which resulted in the compact of soil. Conventional mathematical models are difficult to predict the risk of ground subsidence precisely. In order to analyze the development trend of subsidence of Shanxi Transformation Comprehensive Reform Demonstration Area ⁃ Xiao River Modern Industrial Zone, the work of settlement prediction and hazard zoning were carried out. Based on the In SAR surface subsidence monitoring data from July 2016 to December 2018 in the research area, training samples were constructed, and Elman model was established to predict the subsidence amount for three times from February to March 2019,and then compared with the actual value. At the same time, the annual average settlement in 2020 was predicted according to the established model, then the hazard zoning working was proceeded. The results showed that the predicted value of the subsidence was consistent with the actual value basically based on the Elman model, and the prediction accuracy was higher, the division result was slightly safer than other methods, which can play an early warning role in ground subsidence control of research areas certainly. [ABSTRACT FROM AUTHOR]

• A distributed pressure sensor (DPS) is proposed for groundwater pressure monitoring. • The feasibility of the DPS was verified. • The DPS was used for pumping test and compared with traditional pressure sensor. • The DPS provides an innovative means for groundwater pressure monitoring. Groundwater pressure is a key parameter in the analysis of ground subsidence laws and disaster-causing factors. However, existing sensors make it difficult to achieve distributed and accurate measurements of groundwater pressure. This paper presents a new distributed pressure sensor (DPS) based on optical frequency domain reflectometer (OFDR) for groundwater pressure accurate measurement. The comprehensive temperature influence coefficient was proposed to eliminate the influence of temperature. Tests were conducted to verify the performance of the DPS and analyze the influencing factors. Finally, the proposed method was applied to on-site monitoring of groundwater pressure in Ningbo, China. The test results show that a smaller helically wound pitch length of the fiber optic and a larger diameter piezoresistive element are conducive to improving the sensitivity of the sensor. The on-site monitoring results indicate that the DPS has obvious advantages over traditional pressure sensors and is an innovative means for groundwater pressure measurement. [ABSTRACT FROM AUTHOR]

The city of Wałbrzych represents a geomorphic landscape, heavily modified by nearly three centuries of industrial activity, related mainly to coal mining. The key landforms due to human impact include spoil tips of various types, extensive levelled terrains, waste ponds, and railway embankments and cuts. Ground subsidence due to mining and water pumping have affected large areas. The map shows the distribution of anthropogenic landforms due to industrial activity, mainly coal mining, over an area of 85 km2. The thematic symbol set for the main map contains 22 classes of objects which show 13 distinctive types of landform modification due to construction, excavation, levelling and complex features. The Main Map is accompanied by inset maps showing generalized geology of the area, extent and magnitude of ground subsidence, as well as relief visualization.

The main cause of ground subsidence accidents in urban areas is cavities formed by damage to underground utilities. For this reason, the attribute information of underground utilities should be used to prepare against ground subsidence accidents. In this study, attribute information (pipe age, diameter, burial depth, and density) of six types of underground utilities (water, sewer, gas, power, heating, and communication) and history information of ground subsidence were collected. A correlation analysis was conducted using the collected data, and a prediction model of vulnerability to ground subsidence was developed through the ordinary least squares (OLS) method and spatial regression analysis (spatial lag model (SLM) and spatial error model (SEM)). To do this, the target area was divided into a grid of 100 m × 100 m. Datasets were constructed using the attribute information of underground utilities included in the divided grid and the number of ground subsidence occurrences. To analyze the OLS of the constructed data, the variance inflation factor (VIF) of the attribute information of underground utilities was studied. An OLS analysis was conducted using the appropriate factors, and the results show that the spatial data were autocorrelated. Subsequently, SEM and SLM analyses, which were spatial regression analyses, were conducted. As a result, the model using SLM was selected as suitable for analyzing the vulnerability of ground subsidence, and the density of six types of underground utilities was found to be the highest influencing factor. In addition, a vulnerability map of ground subsidence in the target area was prepared using the model. The vulnerability map demonstrates that regions with frequent ground subsidence can be predicted to be highly vulnerable.

Geothermal reservoir operations can lead to seismic activity, for instance, due to increased pore pressure, but some observations are difficult to explain by pressure changes alone. Such observations include unexpected, induced events after injection well shut-in when pore pressures are thought to decrease. Here, we analyze induced seismicity up to M L 1.5 and surface deformation in Blue Mountain, Nevada using seismic, geodetic, and hydraulic data between 2016 and 2020. This period is characterized by long-term surface subsidence of up to 1 cm/yr above the reservoir. The long-term deformation is associated with modest seismic activity but also short-lived seismicity spikes during rapid maintenance shutdowns in 2017 and 2018. The seismicity is concentrated within the geothermal reservoir at 0.5 - 2.5 km depth, similar to injection operations. We present a numerical model of abrupt seismicity rate changes during the two shutdowns that explains the observation through short-term poroelastic effects leading to increased Coulomb stressing rates. In contrast, the long-term surface subsidence can be modeled statically by superimposing localized fault slip, and thermal contraction of the reservoir. Our findings demonstrate that poroelastic coupling drives the abrupt increase in seismic activity following well shutdown, while aseismic fault slip and thermal contraction dictate the long-term static deformation. [ABSTRACT FROM AUTHOR]

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 Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. 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 Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. 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.)

Coal is one of the fundamental fossil energy supporting the world's economy. The synergistic development between efficient coal mining and ecological environment protection is the inevitable requirement for the preservation of global harmony. As the world's largest coal producer, China has conducted a strategic shift from east to west in terms of the exploitation of its energy resources, posing a serious threat to the fragile ecological environment of the western region. In particular, the surface subsidence caused by coal mining is the root of the ecological deteriotation and the destruction of ground structures. However, it is difficult to reveal the law of large-scale surface subsidence in western mining areas merely by conventional measurement methods such as leveling, on account of the high intensity of coal seam mining, the weakness of the lithology of overlying rock and the large thickness of wind-blown sand strata. In view of this, small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology was used in this study to obtain the time series of surface vertical displacement during the whole mining process of the 2401 working face in the Yingpanhao coal mine, Inner Mongolia. Based on the deformation data, the dynamic evolution characteristics of surface subsidence under high intensity mining in the western mining area were analyzed exhaustively. It was found that the surface subsidence is characterized by an extensive coverage range (48.52 km2) with minimal ground settlement (250 mm) in the study area. Meanwhile, the boundary shape of the subsidence basin followed a "circular-parallelogram-trapezoid" changeable process and the coverage area of the basin experienced three stages: a linear increasing period, a temporary stagnation period, and a re-expansion period. Furthermore, there existed an abnormal uplift phenomenon on the east side of the open-off cut in the 2401 working face. Combined with the structure of overlying strata, this paper carried out a preliminary analysis on the reasons of the abovementioned phenomenon. The research results are of vital realistic significance for ground buildings and ecological environmental protection in the aeolian sand mining area in Western China. [ABSTRACT FROM AUTHOR]

Mining cities in China have long faced pressures such as the occupation of urban land by waste discharge from mining areas, the harsh ecological environment, and the surge in unemployment. After years of exploration, the development of urban underground space is the best way to solve the above problems. Based on the geological condition and urban planning condition of Tangshan City, this paper put forward the concept of underground space development, and chose underground space waste storage and utilization methods according to local conditions. It analyzed the distribution of underground space in Tangshan City and its corresponding surface conditions, and calculated the volume of underground space as 9.1 × 107m3; proposed the concept of utilization efficiency of underground space, established the deformation model of underground space surrounding rock, and calculated the reasonable width of waste storage space. The width is about 60 m, and the space utilization efficiency should reach 82%; based on the field practice of the waste storage project, the measured space utilization efficiency is 73%, which is slightly less than the theoretical calculation value; Through the urban surface deformation and air monitoring, the underground waste storage project in Tangshan City is successful. The negative effect of urban ground is relatively small, and it is the best method suitable for the utilization of underground space in China's mining cities, and provides a theoretical basis for the development of urban underground space in China. [ABSTRACT FROM AUTHOR]

Coastal regions are becoming increasingly vulnerable to flooding because of accelerating sea-level-rise (SLR), local ground subsidence, and the changes in topography and morphology. Moreover, coastal areas are usually highly urbanized and increased human activities have an effect on the stability and preservation of the environment. For instance, the growing demand for new lands to accommodate the population and the industrial facilities in China has required the design and the deployment of land-reclamation projects from the ocean, with a marked impact on fragile coastal eco-systems. Specifically, the Yangtze River and Pearl River Estuary, two major estuaries of the world, have long been subject to intensive human activities over the past decades. Long-term ground subsidence evolution, topographic changes, and morphological variation of the coastal regions have drawn great attention. This paper provides an overview of well-established Earth Observation (EO) remote sensing (RS) technologies that are employed to continuously monitor the changes of urbanized regions. The combined use of EO-based DInSAR analyses along with the knowledge of the geomorphology of the coastal regions allows a more precise picture of the SLR risk in the investigated coastal regions. In this paper, we will concentrate on remote sensing technologies that allow the gathering of heterogeneous information, such as those based on the use of synthetic aperture radar (SAR), satellite altimeters and tide gauge data. We will underline how human activities trigger changes in the living environment of coastal zones and the associated risks for the population. Observed coastline changes, coastal regions terrain subsidence, and offshore bathymetry have a pronounced effect on the increasing risk of flooding. Accordingly, we also present insights into some inundation model projections employed for evaluating the potential flooding risk in coastal regions.

As an earthquake occurred in Iburi subprefecture, Japan on September 2018, Sapporo has also been damaged by ground subsidence. Ground subsidence can occur in various area, especially in urban areas causing considerable damage to human lives and properties. Currently, ground subsidence is one of the most important problems all over the world. However, quantitative research about ground subsidence due to earthquake that particularly occurred in urban area was not well studied. To prevent and minimize critical damage caused by subsidence, this study aims to construct hazard map to predict susceptible subsidence place in East area of Sapporo, using geographic information system (GIS) and frequency ratio (FR) model. To determine major factors related to ground subsidence, spatial databases were constructed from geological map, slope data, land use map, borehole data, precipitation data, railroad and subway line data and earthquake information data. Weight of each factors were estimated by FR model to analyze degree of subsidence hazard and construct subsidence hazard map. Constructed subsidence susceptibility map was compared with reported actual ground subsidence area for verification and showed prediction accuracy of 85.17%. This result showed sufficient possibility for reliable susceptibility mapping of ground subsidence using GIS and FR model.

Due to the cyclic dynamic load, the underground cavity will gradually develop into road subsidence. In view of this problem, this paper establishes model tests to simulate the whole developing process of road subsidence. The results show that as the cyclic dynamic load decreases, the limited cyclic loading times causing road subsidence increases exponentially. However, if there is a certain size of underground cavity, small cyclic dynamic load can also lead to road subsidence after sufficient cyclic loading times. The soil with larger maximum particle size and higher uneven coefficient has larger ultimate static strength and smaller ultimate dynamic strength. On the contrary, soil with smaller maximum particle size and smaller uneven coefficient has smaller ultimate static strength and larger ultimate dynamic strength. Larger thickness of the soil overlying the underground cavity will lead to larger ultimate static and dynamic strength. At the same time, the development of the road subsidence curve and the soil cracks under the cyclic dynamic load undergo three stages. Stage 1 is the initial consolidation settlement stage with short duration. In this stage, the soil is compacted by vibration and the ground surface has overall settlement with no obvious development of the observed soil cracks. Stage 2 is the uniform development stage with long duration and uniform development in settlement and soil cracks. The soil is subjected to the effect of shear vibrating. Stage 3 is the accelerated development stage with the shortest duration. The soil is subjected to vibration failure. The settlement and soil cracks develop rapidly until road subsidence occurs.

The probability integral method (PIM) is the main method for mining subsidence prediction in China. Parameter errors and model errors are the main sources of error in the application of the probability integral method. There are many surface subsidence problems caused by coal mining. In order to improve the accuracy and operating efficiency of the genetic algorithm (GA) in calculating the parameters of the PIM, this paper proposes an improved genetic algorithm (IGA) by adding the dynamic crossover and mutation rate to the traditional GA. Made improvements to the shortcomings of random crossover and mutation rate of all individuals in the population in the original algorithm.Through simulation experiments, it is confirmed that the IGA improves the calculation efficiency and accuracy of the traditional GA under the same conditions.The IGA has higher accuracy, reliability, resistance to gross interference and resistance to missing observation points. This method is obviously superior to direct inversion and conventional optimization inversion algorithms, and effectively avoids the dependence on the initial value of the probabilistic integral method parameter.

Taking Weiqiang Coal Mine 1313 working face as an example, through the analysis of mine geological, hydrogeological conditions, the main water-filled source and water-filled channel of working face mining are determined, and the surface collapse caused by stoping of 1313 working face is predicted by using probability integral method in combination with the measured results of surface movement deformation in advance, so as to judge the damage degree of surface reservoir dam body. The results show that the sandstone aquifer of the fourth member of Jurassic Yan’an Formation and Zhilao Formation of No.3 coal seam is the main water-filling source in the mining of 1313 working face, and the overlying rock water-guiding fault zone is the main water-filling channel, and the atmospheric precipitation and surface reservoir water will not be communicated into the underground; However, the surface collapse and deformation after stoping will cause grade IV damage to the dam body of the reservoir, which is very likely to cause the overflow of water body of the reservoir and the risk of irrigation into the downstream farmland.