Karst sinkholes with natural negative landform provide favorable conditions for the pumped storage reservoir construction for less excavation work.However,the construction of the reservoir would plug the natural karst...Karst sinkholes with natural negative landform provide favorable conditions for the pumped storage reservoir construction for less excavation work.However,the construction of the reservoir would plug the natural karst channels for water and air,which would cause remarkable air pressure in karst channels when the groundwater level fluctuates.A large laboratory simulation test was carried out to study the air pressure variation of a reservoir built on the karst sinkhole.The air pressure in the karst channel and inside the model was monitored during the groundwater rising and falling process.Result showed that the variation of air pressure in the karst channel and the surrounding rock exhibited a high degree of similarity.The air pressure increased rapidly at the initial stage of water level rising,followed by a slight decrease,then the air pressure increased sharply when the water level approached the top of the karst cave.The initial peak of air pressure and the final peak of air pressure were defined,and both air pressure peaks were linearly increasing with the water level rising rate.The negative air pressure was also analyzed during the drainage process,which was linearly correlated with the water level falling rate.The causes of air pressure variation in karst channels of a pumped storage reservoir built on the karst sinkhole were discussed.The initial rapid increase,then slight decrease and final sudden increase of air pressure were controlled by the combined effects of air compression in karst channel and air seepage into the surrounding rock.For the drainage process,the instant negative air pressure and gradual recovering of air pressure were controlled by the combined effects of negative air pressure induced by water level falling and air supply from surrounding rock.This work could provide valuable reference for the reservoir construction in karst area.展开更多
Anthropogenic activity-induced sinkholes pose a serious threat to building safety and human life nowadays.Real-time detection and early warning of sinkhole formation are a key and urgent problem in urban areas.This pa...Anthropogenic activity-induced sinkholes pose a serious threat to building safety and human life nowadays.Real-time detection and early warning of sinkhole formation are a key and urgent problem in urban areas.This paper presents an experimental study to evaluate the feasibility of fiber optic strain sensing nerves in sinkhole monitoring.Combining the artificial neural network(ANN)and particle image velocimetry(PIV)techniques,a series of model tests have been performed to explore the relationship between strain measurements and sinkhole development and to establish a conversion model from strain data to ground settlements.It is demonstrated that the failure mechanism of the soil above the sinkhole developed from a triangle failure plane to a vertical failure plane with increasing collapse volume.Meanwhile,the soil-embedded fiber optic strain sensing nerves allowed deformation monitoring of the ground soil in real time.Furthermore,the characteristics of the measured strain profiles indicate the locations of sinkholes and the associated shear bands.Based on the strain data,the ANN model predicts the ground settlement well.Additionally,micro-anchored fiber optic cables have been proven to increase the soil-to-fiber strain transfer efficiency for large deformation monitoring of ground collapse.展开更多
Voids, which have not been liquidated and associated with shallow mining excavations, pose a serious threat of potential formation of sinkholes. This threat is connected with the loss of stability of voids that had be...Voids, which have not been liquidated and associated with shallow mining excavations, pose a serious threat of potential formation of sinkholes. This threat is connected with the loss of stability of voids that had been formed as a result of mining operations in the deeper strata. Taking into account the impact of lower coal seams mining on shallow excavations and based on the example of a region that had been intensely exploited, this paper proposes a methodology for analysing the stability of shallow mine voids in the rock mass. Deformations in the excavation region were calculated by using FLAC2 D computer program and assigning the Coulomb–Mohr model to the rock mass. Based on the numerical analysis, this paper evaluated the stability of the void in the event of a roof support fall. The results indicate the likelihood of void formation. Based on the Budryk–Knothe theory, the deformations of rock mass and sandstone strata in the roof of the void, which had been caused by mining exploitation in consecutive years,were calculated. The results of numerical calculations and analyses were compared with the limit deformations values of sandstone in tension. It is concluded that the exploitations cause the void to break down. The proposed method can forecast the discontinuous deformations threats in the areas that have undergone shallow undermining exploitation and the areas of underground urban.展开更多
The Kinta Valley is an area of karst in the north-western part of Peninsular Malaysia. Over 30 years of uncontrolled land use and development has led to significant changes in topography and geomorphology, such as the...The Kinta Valley is an area of karst in the north-western part of Peninsular Malaysia. Over 30 years of uncontrolled land use and development has led to significant changes in topography and geomorphology, such as the appearance of sinkholes. In this paper, geospatial techniques were utilized to the task of evaluating sinkholes susceptibility map using a spatial multi criteria evaluation approach (SMCE). Sinkhole location and a spatial database were applied to calculate eight inherent causative factors for limestone instability namely: lithology, structure (lineament), soil cover, slope, land use mining, urban area features, ponds and rivers. The preparation of the sinkhole geohazard map involved summing the weighted values for each hazard element, which permits the construction of geohazard model;the results of the analysis were validated using the previous actual sinkholes locations in the study area. The spatial distribution of sinkholes occurrence, urban development, faults distribution and ex-mining ponds are factors that are directly responsible for all sinkholes subsidence hazards. Further, the resulting geo-hazard map shows that 93% of recent sinkholes occur in areas where the model flags as “high” and “very high” potential hazard, located in the urbanized part of the valley, while less-developed areas to the west and southwest suffered less sinkhole development. The results can be used for hazard prevention and land-use planning.展开更多
Remote sensing analysis is an efficient tool for updating geological maps. The regional scale map obtained in this project from compilation of the pre-existing maps and of a number of space images is somewhat more com...Remote sensing analysis is an efficient tool for updating geological maps. The regional scale map obtained in this project from compilation of the pre-existing maps and of a number of space images is somewhat more complete. It takes into account the usual field and laboratory parameters of the rock units, through the previous geologic maps, together with remote sensing parameters such as spectral signatures, textures, roughness, morphology that are observed from optical, microwave and DEM imagery. With more rock characteristics, the old maps are obligatory improved. The Cenozoic faulting in the Al Hamra al Hamadah plateau is largely influenced by the tectonics affecting the Paleozoic oil bearing structures that are hidden by the late Cretaceous-Paleocene layers. The tectonic style is that of reactivation of the Paleozoic faults under effects of the NNE-trending regional tension. Then the faults on the surface of the plateau would indicate location of the hidden Paleozoic faults in depth. A flat plateau, in the arid environment, appears to be a very favorable environment for mapping of gentle folds, faults and tectonic sinkholes. Remote sensing is a fruitful approach in this case study. The gentle anticlines for instance are undetectable in the field, but computer assisted shadowing with a low elevation angle of illumination is the key processing for evidencing these features. Problems of drillings in the area are well known for example to Waha, AGOCO and PB Companies during their exploration activities in the concessions in Ghadames Basin. According to them several incidents of losing drilling Pits have occurred and drilling came into a hole. Because this paper is aimed to know the exact location of sinkholes in the Ghadames basin, I would recommend all the oil companies to review this work and try to trace the sinkholes indicated to minimize the risk of drilling problems.展开更多
The effectiveness of monitoring and early-warning systems for ground deformation phenomena,such as sinkholes,depends on their ability to accurately resolve the ongoing ground displacement and detect the subtle deforma...The effectiveness of monitoring and early-warning systems for ground deformation phenomena,such as sinkholes,depends on their ability to accurately resolve the ongoing ground displacement and detect the subtle deformation preceding catastrophic failures.Sagging sinkholes with a slow subsidence rate and diffuse edges pose a significant challenge for subsidence monitoring due to the low deformation rates and limited lateral strain gradients.In this work,we satisfactorily illustrate the practicality of the Brillouin optical time domain analysis(BOTDA)to measure the spatial-temporal patterns of the vertical displacement in such challenging slow-moving sagging sinkholes.To assess the performance of the approach,we compare the strain recorded by the distributed optical fiber sensor with the vertical displacement measured by high-precision leveling.The results show a good spatial correlation with the ability to identify the maximum subsidence point.There is also a good temporal correlation with the detection of an acceleration phase in the subsidence associated with a flood event.展开更多
This research aims to develop reliable models using machine learning algorithms to precisely predict Total Dissolved Solids (TDS) in wells of the Permian basin, Winkler County, Texas. The data for this contribution wa...This research aims to develop reliable models using machine learning algorithms to precisely predict Total Dissolved Solids (TDS) in wells of the Permian basin, Winkler County, Texas. The data for this contribution was obtained from the Texas Water Development Board website (TWDB). Five hundred and ninety-three samples were obtained from two hundred and ninety-eight wells in the study area. The wells were drilled at different county locations into five aquifers, including Pecos Valley, Dockum, Capitan Reef, Edward Trinity, and Rustler aquifers. A total of fourteen different water quality parameters were used, and they include Potential hydrogen (pH), Sodium, Chloride, Magnesium, Fluoride, TDS, Specific Conductance, Nitrate, Total Hardness, Calcium, Temperature, Well Depth, Sulphate, and Bicarbonates. Four machine learning regression algorithms were developed to get a good model to help predict TDS in this area: Decision Tree regression, Linear regression, Support Vector Regression, and K-nearest neighbor. The study showed that the Decision Tree produced the best model with attributes like the coefficient of determination R2 = 1.00 and 0.96 for the training and testing, respectively. It also produced the lowest score of mean absolute error MAE = 0.00 and 0.04 for training and testing, respectively. This study will reduce the cost of obtaining different water quality parameters in TDS determination by leveraging machine learning to use only the parameters contributing to TDS, thereby helping researchers obtain only the parameters necessary for TDS prediction. It will also help the authorities enact policies that will improve the water quality in areas where drinking water availability is a challenge by providing important information for monitoring and assessing groundwater quality.展开更多
基金support from the National Natural Science Foundation of China(Grant.No.42162027)the Science and technology foundation of Guizhou Province(Grant.No.2022-212,2023-006)are greatly appreciated.
文摘Karst sinkholes with natural negative landform provide favorable conditions for the pumped storage reservoir construction for less excavation work.However,the construction of the reservoir would plug the natural karst channels for water and air,which would cause remarkable air pressure in karst channels when the groundwater level fluctuates.A large laboratory simulation test was carried out to study the air pressure variation of a reservoir built on the karst sinkhole.The air pressure in the karst channel and inside the model was monitored during the groundwater rising and falling process.Result showed that the variation of air pressure in the karst channel and the surrounding rock exhibited a high degree of similarity.The air pressure increased rapidly at the initial stage of water level rising,followed by a slight decrease,then the air pressure increased sharply when the water level approached the top of the karst cave.The initial peak of air pressure and the final peak of air pressure were defined,and both air pressure peaks were linearly increasing with the water level rising rate.The negative air pressure was also analyzed during the drainage process,which was linearly correlated with the water level falling rate.The causes of air pressure variation in karst channels of a pumped storage reservoir built on the karst sinkhole were discussed.The initial rapid increase,then slight decrease and final sudden increase of air pressure were controlled by the combined effects of air compression in karst channel and air seepage into the surrounding rock.For the drainage process,the instant negative air pressure and gradual recovering of air pressure were controlled by the combined effects of negative air pressure induced by water level falling and air supply from surrounding rock.This work could provide valuable reference for the reservoir construction in karst area.
基金support provided by the National Natural Science Foundation of China(Grant Nos.42225702,and 42077232)the Open Research Project Program of the State Key Laboratory of Internet of Things for Smart City(University of Macao)(Grant No.SKL-IoTSC(UM)-2021-2023/ORP/GA10/2022).
文摘Anthropogenic activity-induced sinkholes pose a serious threat to building safety and human life nowadays.Real-time detection and early warning of sinkhole formation are a key and urgent problem in urban areas.This paper presents an experimental study to evaluate the feasibility of fiber optic strain sensing nerves in sinkhole monitoring.Combining the artificial neural network(ANN)and particle image velocimetry(PIV)techniques,a series of model tests have been performed to explore the relationship between strain measurements and sinkhole development and to establish a conversion model from strain data to ground settlements.It is demonstrated that the failure mechanism of the soil above the sinkhole developed from a triangle failure plane to a vertical failure plane with increasing collapse volume.Meanwhile,the soil-embedded fiber optic strain sensing nerves allowed deformation monitoring of the ground soil in real time.Furthermore,the characteristics of the measured strain profiles indicate the locations of sinkholes and the associated shear bands.Based on the strain data,the ANN model predicts the ground settlement well.Additionally,micro-anchored fiber optic cables have been proven to increase the soil-to-fiber strain transfer efficiency for large deformation monitoring of ground collapse.
文摘Voids, which have not been liquidated and associated with shallow mining excavations, pose a serious threat of potential formation of sinkholes. This threat is connected with the loss of stability of voids that had been formed as a result of mining operations in the deeper strata. Taking into account the impact of lower coal seams mining on shallow excavations and based on the example of a region that had been intensely exploited, this paper proposes a methodology for analysing the stability of shallow mine voids in the rock mass. Deformations in the excavation region were calculated by using FLAC2 D computer program and assigning the Coulomb–Mohr model to the rock mass. Based on the numerical analysis, this paper evaluated the stability of the void in the event of a roof support fall. The results indicate the likelihood of void formation. Based on the Budryk–Knothe theory, the deformations of rock mass and sandstone strata in the roof of the void, which had been caused by mining exploitation in consecutive years,were calculated. The results of numerical calculations and analyses were compared with the limit deformations values of sandstone in tension. It is concluded that the exploitations cause the void to break down. The proposed method can forecast the discontinuous deformations threats in the areas that have undergone shallow undermining exploitation and the areas of underground urban.
文摘The Kinta Valley is an area of karst in the north-western part of Peninsular Malaysia. Over 30 years of uncontrolled land use and development has led to significant changes in topography and geomorphology, such as the appearance of sinkholes. In this paper, geospatial techniques were utilized to the task of evaluating sinkholes susceptibility map using a spatial multi criteria evaluation approach (SMCE). Sinkhole location and a spatial database were applied to calculate eight inherent causative factors for limestone instability namely: lithology, structure (lineament), soil cover, slope, land use mining, urban area features, ponds and rivers. The preparation of the sinkhole geohazard map involved summing the weighted values for each hazard element, which permits the construction of geohazard model;the results of the analysis were validated using the previous actual sinkholes locations in the study area. The spatial distribution of sinkholes occurrence, urban development, faults distribution and ex-mining ponds are factors that are directly responsible for all sinkholes subsidence hazards. Further, the resulting geo-hazard map shows that 93% of recent sinkholes occur in areas where the model flags as “high” and “very high” potential hazard, located in the urbanized part of the valley, while less-developed areas to the west and southwest suffered less sinkhole development. The results can be used for hazard prevention and land-use planning.
文摘Remote sensing analysis is an efficient tool for updating geological maps. The regional scale map obtained in this project from compilation of the pre-existing maps and of a number of space images is somewhat more complete. It takes into account the usual field and laboratory parameters of the rock units, through the previous geologic maps, together with remote sensing parameters such as spectral signatures, textures, roughness, morphology that are observed from optical, microwave and DEM imagery. With more rock characteristics, the old maps are obligatory improved. The Cenozoic faulting in the Al Hamra al Hamadah plateau is largely influenced by the tectonics affecting the Paleozoic oil bearing structures that are hidden by the late Cretaceous-Paleocene layers. The tectonic style is that of reactivation of the Paleozoic faults under effects of the NNE-trending regional tension. Then the faults on the surface of the plateau would indicate location of the hidden Paleozoic faults in depth. A flat plateau, in the arid environment, appears to be a very favorable environment for mapping of gentle folds, faults and tectonic sinkholes. Remote sensing is a fruitful approach in this case study. The gentle anticlines for instance are undetectable in the field, but computer assisted shadowing with a low elevation angle of illumination is the key processing for evidencing these features. Problems of drillings in the area are well known for example to Waha, AGOCO and PB Companies during their exploration activities in the concessions in Ghadames Basin. According to them several incidents of losing drilling Pits have occurred and drilling came into a hole. Because this paper is aimed to know the exact location of sinkholes in the Ghadames basin, I would recommend all the oil companies to review this work and try to trace the sinkholes indicated to minimize the risk of drilling problems.
基金This work has been supported by Ministerio de Ciencia e Innovacion,Gobierno de Espana(Grant Nos.CGL2017-85045-P,PID2021-123189NB-I00,DI-17-09169)Government of Aragon(Grant No.Reference Group T20_23R)Jorge Sevil has a predoctoral contract(Grant No.PRE2018-084240)co-financed by the Spanish Government and the European Social Fund(ESF).
文摘The effectiveness of monitoring and early-warning systems for ground deformation phenomena,such as sinkholes,depends on their ability to accurately resolve the ongoing ground displacement and detect the subtle deformation preceding catastrophic failures.Sagging sinkholes with a slow subsidence rate and diffuse edges pose a significant challenge for subsidence monitoring due to the low deformation rates and limited lateral strain gradients.In this work,we satisfactorily illustrate the practicality of the Brillouin optical time domain analysis(BOTDA)to measure the spatial-temporal patterns of the vertical displacement in such challenging slow-moving sagging sinkholes.To assess the performance of the approach,we compare the strain recorded by the distributed optical fiber sensor with the vertical displacement measured by high-precision leveling.The results show a good spatial correlation with the ability to identify the maximum subsidence point.There is also a good temporal correlation with the detection of an acceleration phase in the subsidence associated with a flood event.
文摘This research aims to develop reliable models using machine learning algorithms to precisely predict Total Dissolved Solids (TDS) in wells of the Permian basin, Winkler County, Texas. The data for this contribution was obtained from the Texas Water Development Board website (TWDB). Five hundred and ninety-three samples were obtained from two hundred and ninety-eight wells in the study area. The wells were drilled at different county locations into five aquifers, including Pecos Valley, Dockum, Capitan Reef, Edward Trinity, and Rustler aquifers. A total of fourteen different water quality parameters were used, and they include Potential hydrogen (pH), Sodium, Chloride, Magnesium, Fluoride, TDS, Specific Conductance, Nitrate, Total Hardness, Calcium, Temperature, Well Depth, Sulphate, and Bicarbonates. Four machine learning regression algorithms were developed to get a good model to help predict TDS in this area: Decision Tree regression, Linear regression, Support Vector Regression, and K-nearest neighbor. The study showed that the Decision Tree produced the best model with attributes like the coefficient of determination R2 = 1.00 and 0.96 for the training and testing, respectively. It also produced the lowest score of mean absolute error MAE = 0.00 and 0.04 for training and testing, respectively. This study will reduce the cost of obtaining different water quality parameters in TDS determination by leveraging machine learning to use only the parameters contributing to TDS, thereby helping researchers obtain only the parameters necessary for TDS prediction. It will also help the authorities enact policies that will improve the water quality in areas where drinking water availability is a challenge by providing important information for monitoring and assessing groundwater quality.
