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Land Subsidence: Monitoring, Prediction and Modeling

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: closed (27 May 2023) | Viewed by 26208

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Prof. Dr. Ryszard Hejmanowski

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Guest Editor

Faculty of Mining Surveying and Environmental Engineering, AGH University of Science and Technology, 30-059 Cracow, Poland
Interests: prediction (modeling) of land subsidence for the hard coal, copper ore, salt, gas and oil deposits; risk assessment and mitigation on transformed terrains; planning of the surveying systems to subsidence monitoring; IT systems developing (GIS-based) for building damage risk assessment and management on human transformed areas; mining seismicity and its influence on the terrain movements
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Dr. Pietro Teatini

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Guest Editor

Department of Civil, Environmental and Architectural Engineering (DICEA), University of Padova, Padova, Italy
Interests: Modelling geomechanical issues related to fluid withdrawal/injection from/into the subsurface. Specifically, land subsidence due to aquifer overexploitation and production of hydrocarbon reservoirs, land uplift caused by fluid injection (aquifer recharge, underground gas storage, CO2 geologic sequestration), stress / strain analyses for safety evaluations (induced seismicity, aseismic earth fissuring accompanying land subsidence). Modelling land subsidence due to peat oxidation and natural consolidation in deltas and wetlands. Use of land subsidence measurements (integrating levelling, GPS, SAR interferometry), together with deformation at depth (borehole extensometers, well-logs) to characterize the geomechanical properties and calibrate the numerical models

Special Issue Information

Dear Colleagues,

Recently, land subsidence has become one of the important risk factors. Taking into consideration global warming and sea-level rise, many regions of the world, large cities, and land users will be affected by the changes. In many of those areas, the land subsides because of water pumping, gas, and oil extraction, soft soils or peat compaction and additional building load. On the other hand, there are terrains where the mining of raw materials is or was lately active. Mining is one the most important factors of subsidence, sinkholes, and other related damage. It can affect buildings and infrastructure, threatening and decreasing quality of life. In any area transformed by human activity, the ground movements should also be considered. New ideas in modeling approach development, rock mechanics, and civil engineering have emerged in many countries. Novel measurement technics, sensors, and expanding availability of remote sensing data pushes the monitoring of land subsidence towards new possibilities.

This Special Issue of Applied Sciences is intended for specialists and an interdisciplinary audience and covers recent advances in the following topics:

Land subsidence innovative monitoring technologies and untypical case studies
Prediction of land subsidence: case studies for different kind of raw materials
Modeling: new and improved approaches, parametrization, accuracy, and reliability

Prof. Ryszard Hejmanowski
Prof. Pietro Teatini
Guest Editors

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Keywords

land subsidence
modeling
uplift
sea-level rise
rock mechanics
monitoring
geodesy
remote sensing
GIS
risk assessment
prediction

Published Papers (10 papers)

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Research

18 pages, 8989 KiB

Open AccessArticle

Deformation Detection and Attribution Analysis of Urban Areas near Dianchi Lake in Kunming Using the Time-Series InSAR Technique

by Junyu Wang, Menghua Li, Mengshi Yang and Bo-Hui Tang

Appl. Sci. 2022, 12(19), 10004; https://doi.org/10.3390/app121910004 - 5 Oct 2022

Cited by 3 | Viewed by 1741

Abstract

The main city of Kunming is located on the north bank of Dianchi Lake. The complex geological environment, large-scale construction, and expansion of the city in recent years have caused uneven land surface subsidence and threatened public safety. In this study, Sentinel-1 ascending and descending orbit datasets were collected for the period of February 2018 to May 2021. The characteristics of surface displacement in the Kunming downtown area were monitored using the time-series interferometric synthetic aperture radar (InSAR) technique, and attribution analysis was performed. It was found that areas with more severe surface settlement were concentrated in the International Exhibition Center area and the large, newly built communities near Dianchi Lake and the Xiaobanqiao Region. The multifactor attribution analysis results demonstrated that the subsidence areas are concentrated in urban villages and engineered, construction-intensive areas in the lakeside sedimentary layer area, with the maximum displacement rate reaching −23.12 mm/a in the line-of-sight direction of the Sentinel-1 ascending dataset. The reliability of the InSAR results was cross-validated with ascending and descending results. This study provides a scientific reference for urban development planning and potential geological disaster detection in Kunming. Full article

(This article belongs to the Special Issue Land Subsidence: Monitoring, Prediction and Modeling)

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8 pages, 257 KiB

Open AccessCommunication

A General Solution for the Errors in Variables (EIV) Model with Equality and Inequality Constraints

by Dengshan Huang, Yulin Tang and Qisheng Wang

Appl. Sci. 2022, 12(19), 9808; https://doi.org/10.3390/app12199808 - 29 Sep 2022

Viewed by 1063

Abstract

Targeting the adjustment of the errors-in-variables (EIV) model with equality and inequality constraints, a general solution that is similar to the classical least square adjustment is proposed based on the penalty function and the weight in measurement. Firstly, we take the equality constraints as inequality constraints that do not satisfy the constraint conditions and construct the penalty functions of equality and inequality constraints, respectively. Thus, the inequality constrained optimization problem is transformed into an unconstrained optimization problem. Then the detailed calculation formula and approximate accuracy evaluation formula of the general solution are deduced. The iteration formula of the general solution is easy regarding comprehension and applicable in implementation. It can not only solve the EIV model with equality and inequality constraints respectively, but also address the EIV model with equality and inequality constraints simultaneously. In addition, it can promote the Gauss–Markov (G-M) model with equality and inequality constraints. Finally, three examples (i.e., equality constraints, inequality constraints and those with equality and inequality constraints) are validated, indicating that the general solution is effective and feasible. The results show that the general solution is effective and feasible. Full article

(This article belongs to the Special Issue Land Subsidence: Monitoring, Prediction and Modeling)

18 pages, 4145 KiB

Open AccessArticle

Extraction of Irregularly Shaped Coal Mining Area Induced Ground Subsidence Prediction Based on Probability Integral Method

by Xianfeng Tan, Bingzhong Song, Huaizhi Bo, Yunwei Li, Meng Wang and Guohong Lu

Appl. Sci. 2020, 10(18), 6623; https://doi.org/10.3390/app10186623 - 22 Sep 2020

Cited by 13 | Viewed by 2647

Abstract

Underground coal mining-induced ground subsidence (or major ground vertical settlement) is a major concern to the mining industry, government and people affected. Based on the probability integral method, this paper presents a new ground subsidence prediction method for predicting irregularly shaped coal mining area extraction-induced ground subsidence. Firstly, the Delaunay triangulation method is used to divide the irregularly shaped mining area into a series of triangular extraction elements. Then, the extraction elements within the calculation area are selected. Finally, the Monte Carlo method is used to calculate extraction element-induced ground subsidence. The proposed method was tested by two experimental data sets: the simulation data set and direct leveling-based subsidence observations. The simulation results show that the prediction error of the proposed method is proportional to mesh size and inversely proportional to the amount of generated random points within the auxiliary domain. In addition, when the mesh size is smaller than 0.5 times the minimum deviation of the inflection point of the mining area, and the amount of random points within an auxiliary domain is greater than 800 times the area of the extraction element, the difference between the proposed method-based subsidence predictions and the traditional probability integral method-based subsidence predictions is marginal. The measurement results show that the root-mean-square error of the proposed method-based subsidence predictions is smaller than 3 cm, the average of absolute deviations of the proposed method-based subsidence predictions is 2.49 cm, and the maximum absolute deviation is 4.05 cm, which is equal to 0.75% of the maximum direct leveling-based subsidence observation. Full article

(This article belongs to the Special Issue Land Subsidence: Monitoring, Prediction and Modeling)

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18 pages, 16968 KiB

Open AccessArticle

Determination of the Long-Term Ground Surface Displacements Using a PSI Technique—Case Study on Wrocław (Poland)

by Piotr Grzempowski, Janusz Badura, Wojciech Milczarek, Jan Blachowski, Tadeusz Głowacki and Marcin Zając

Appl. Sci. 2020, 10(10), 3343; https://doi.org/10.3390/app10103343 - 12 May 2020

Cited by 5 | Viewed by 2303

Abstract

Wrocław is a major city located in the southwestern part of Poland in an aseismic tectonic fault zone. Slow, long-term, vertical displacements have been observed there from the 1930s based on the levelling network measurements with the use of a precise levelling method. Due to the high cost of classic surveys, these were performed at intervals of several decades and the most recent measurement of ground surface displacement was performed in 1999. The main aim of this study is to determine the ground surface displacements on the area of Wrocław in the 1995–2019 period, the spatio-temporal analysis of deformations and the identification of the potential factors causing these deformations. To determine the ground movements, an advanced PSI technique and data from ERS-2, Envisat, and Sentinel-1 sensors were used. Application of SAR technology for the first time in this area, provided new knowledge about the process of deformation in short time intervals over the entire area of the city. The results verify the hypothesis on the linearity of displacements obtained from historical geodetic observations. The obtained results show that the displacements, which continue to occur in the area of Wrocław have a cyclic character with 4–5 year long period of subsidence and 2–3 year long periods of stabilization or uplift. The displacement trends indicate that the area of the city gradually subsides in relation to the reference area located on the Fore-Sudetic Block. Full article

(This article belongs to the Special Issue Land Subsidence: Monitoring, Prediction and Modeling)

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12 pages, 4265 KiB

Open AccessArticle

Software for Estimation of Stochastic Model Parameters for a Compacting Reservoir

by Wojciech T. Witkowski and Ryszard Hejmanowski

Appl. Sci. 2020, 10(9), 3287; https://doi.org/10.3390/app10093287 - 8 May 2020

Cited by 8 | Viewed by 2341

Abstract

The paper presents a computer program called SubCom v1.0 for determining mathematical model parameters of compaction layers in areas of oil, gas or groundwater extraction. A stochastic model based on the influence function was used to model compaction and subsidence. Estimation of the model parameters was based on solving the inverse problem. Two model parameters were determined: the compaction coefficient C_m of reservoir rocks, and the parameter tgβ, which indirectly describes the mechanical properties of the overburden. The calculations were performed on leveling measurements of land subsidence, as well as on the geometry of the compaction layer and pressure changes in aquifers. The estimation of model parameters allows the prediction of surface deformations due to planned fluid extraction. An algorithm with a graphical user interface was implemented in the Scilab environment. The use of SubCom v1.0 is presented using the case of an underground hard coal mine. Water drainage from rock mass accompanying coal extraction resulted in compaction of the aquifer, which in turn led to additional surface subsidence. As a result, a subsidence trough occurred with a maximum subsidence of 0.56 m. Full article

(This article belongs to the Special Issue Land Subsidence: Monitoring, Prediction and Modeling)

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14 pages, 2873 KiB

Open AccessArticle

Application of the Improved Knothe Time Function Model in the Prediction of Ground Mining Subsidence: A Case Study from Heze City, Shandong Province, China

by Liangliang Zhang, Hua Cheng, Zhishu Yao and Xiaojian Wang

Appl. Sci. 2020, 10(9), 3147; https://doi.org/10.3390/app10093147 - 30 Apr 2020

Cited by 30 | Viewed by 3353

Abstract

Taking into account the inadequacy of the Knothe time function model to predict the dynamic surface subsidence caused by underground mining, a new hypothesis is proposed, and the improved Knothe time function model is established. Theoretical analysis shows the improved model agrees well with surface subsidence dynamic change, velocity change, and acceleration change rules. Combined with field measured data, the probability integral method, dual-medium method, and least square method are adopted to determine the time influence parameter C and the model order n. Based on monitoring data from four monitoring stations in the Guotun coal mine subsidence basin strike main profile from Heze city, Shandong Province, China, the accuracies of the Knothe time function and improved model are compared and analyzed. Results show the improved model can accurately describe the dynamic surface subsidence process and subsidence velocity with mining time. The average relative standard error between the predicted and measured values is only 4.8%—far lower than the Knothe time function model is 23%, verifying the improved model’s accuracy and reliability. Full article

(This article belongs to the Special Issue Land Subsidence: Monitoring, Prediction and Modeling)

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26 pages, 9868 KiB

Open AccessArticle

Law of Movement of Discontinuous Deformation of Strata and Ground with a Thick Loess Layer and Thin Bedrock in Long Wall Mining

by Xugang Lian, Yanjun Zhang, Hongyan Yuan, Chenlong Wang, Junting Guo and Jibo Liu

Appl. Sci. 2020, 10(8), 2874; https://doi.org/10.3390/app10082874 - 21 Apr 2020

Cited by 19 | Viewed by 2405

Abstract

The surface discontinuous deformation caused by coal mining has great damage to the ecological environment and threatens the safety of human lives. Focusing on the problem of discontinuous deformation (ground fissures and collapsed pits) in mining areas with a thick loess and thin bedrock, this paper uses a coal panel in southern Shanxi in China as research background, and uses field investigation, theoretical analysis and the particle flow code 2D (PFC2D) numerical simulation method to study the movement of overburden and discontinuous ground deformation of mining areas with a thick loess layer and a thin bedrock. The results show that with the continual advance of the working face, the failure of the overlying rock, the changing of force chain shape and the development of cracks under this geological and mining condition have their unique rules. This study analyzes the law of movement of overburden in coal seam mining, explains why discontinuous deformation of the surface occurs in case of a thick loess layer and thin bedrock, and provides reference for the prediction of fracture development under the same geological conditions and the application of the PFC2D in coal seam mining in different geological conditions. Full article

(This article belongs to the Special Issue Land Subsidence: Monitoring, Prediction and Modeling)

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20 pages, 5025 KiB

Open AccessArticle

Simulation of Mining-Induced Ground Damage Using Orthogonal Experiments to Determine Key Parameters of Super-Large Coalface: A Case Study in Shendong Coalfield in China

by Yinfei Cai, Xiaojing Li, Wu Xiao and Wenkai Zhang

Appl. Sci. 2020, 10(7), 2258; https://doi.org/10.3390/app10072258 - 26 Mar 2020

Cited by 11 | Viewed by 2208

Abstract

High-strength mining of super-large coalfaces in the Shendong coalfield causes significant damage to the ground surface. To study the key parameters of undermined coalfaces that affect ground damage, 25 numerical simulation models were designed using an orthogonal experimental method based on the geological and mining conditions of the Bulianta Mine. In the orthogonal design, four factors (the lengths in both the dip and strike directions, the thickness and the mining speed of the coalface) were considered, with five levels designed for each factor. The subsidence displacements and deformations caused by the excavation were then simulated and verified using field surveying data. A damage extent index (DEI) was introduced and used to assess the extent of global ground damage caused by each simulative excavation. Analysis of variance (ANOVA) method was then employed to determine the key parameters of the coalface that significantly influence the ground damage. It was found that the coalface dip length and thickness and the coalface thickness can be regarded as the key parameters for ground objects of building and timberland, respectively. This research provides theoretical and technical support for the coordinated exploitation of resources and environments in Shendong and other similar, ecologically fragile coalfields. Full article

(This article belongs to the Special Issue Land Subsidence: Monitoring, Prediction and Modeling)

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20 pages, 9180 KiB

Open AccessArticle

Application of Artificial Neural Networks in Assessing Mining Subsidence Risk

by Yangkyun Kim and Sean S. Lee

Appl. Sci. 2020, 10(4), 1302; https://doi.org/10.3390/app10041302 - 14 Feb 2020

Cited by 15 | Viewed by 3647

Abstract

Subsidence at abandoned mines sometimes causes destruction of local areas and casualties. This paper proposes a mine subsidence risk index and establishes a subsidence risk grade based on two separate analyses of A and B to predict the occurrence of subsidence at an abandoned mine. For the analyses, 227 locations were ultimately selected at 15 abandoned coal mines and 22 abandoned mines of other types (i.e., gold, silver, and metal mines). Analysis A predicts whether subsidence is likely using an artificial neural network. Analysis B assesses a mine subsidence risk index that indicates the extent of risk of subsidence. Results of both analyses are utilized to assign a subsidence risk grade to each ground location investigated. To check the model’s reliability, a new dataset of 22 locations was selected from five other abandoned mines; the subsidence risk grade results were compared with those of the actual ground conditions. The resulting correct prediction percentage for 13 subsidence locations of the abandoned mines was 83–86%. To improve reliability of the subsidence risk, much more subsidence data with greater variations in ground conditions is required, and various types of analyses by numerical and empirical approaches, etc. need to be combined. Full article

(This article belongs to the Special Issue Land Subsidence: Monitoring, Prediction and Modeling)

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32 pages, 11602 KiB

Open AccessArticle

Numerical Parametric Study of Countermeasures to Alleviate the Tunnel Excavation Effects on an Existing Tunnel in a Shallow-Buried Environment near a Slope

by Ziyong He, Chao Li, Qiao He, Yang Liu and Jiangong Chen

Appl. Sci. 2020, 10(2), 608; https://doi.org/10.3390/app10020608 - 15 Jan 2020

Cited by 8 | Viewed by 2530

Abstract

This paper studies the influence law of existing tunnels on the construction of intersecting new tunnels in a shallow slope burial context through 3D numerical analysis. The emphasis is on exploring the effect of new tunnels constructed in 54 conditions, including three ratios of overburden to tunnel height (C/H), three ratios of slope distance to tunnel span (D/W), two backfilling conditions of the existing tunnel (“hty” and “htn” conditions), and three magnitudes of surface loads (10 kPa, 20 kPa, and 30 kPa), on the deformation of lateral slopes and the overlying road. As the results show, the rigidly separated area between the existing and newly built tunnels in parallel to the excavation direction was precisely the sensitive area affected by the existing tunnel backfilling condition. The road settlement simulations perpendicular to the excavation direction revealed that various C/H and D/W ratio combinations controlled the shape and size differences of the settlement trough curve. This was because the C/H ratio primarily controlled the effective span and height transition of the newly built tunnel, whereas the D/W ratio mainly controlled the intersection position of the tunnels. Next, model A-A (“hty” condition) was identified as the only feasible construction model among all models in accordance with the engineering safety control criteria. Lastly, comparison of monitoring data with simulations found a slight difference in the distribution pattern between the two. Nevertheless, the final maximum settlement fully satisfied the construction control requirements overall. Aside from proving the correctness of simulation results, the present study also sets an excellent referential example for similar projects. Full article

(This article belongs to the Special Issue Land Subsidence: Monitoring, Prediction and Modeling)

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