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

Zhang, Liangliang; Cheng, Hua; Yao, Zhishu; Wang, Xiaojian

doi:10.3390/app10093147

Cited by 34 publications

(25 citation statements)

References 24 publications

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“…Land subsidence's spatial extent and value are primarily determined by the depth of exploitation, seam thickness, panel dimensions, overlying rock mass geomechanical conditions, geological defects, surface topography, production methods and post-mining void reclamation method [30,52,53]. Many research papers have been presented in recent years documenting the land subsidence phenomenon caused by mining [47,49,[54][55][56][57][58][59][60][61][62][63]. As a result, one can be stated that the spatial extent of the phenomenon can range from several km 2 [49] to tens of km 2 [15], while its values can range from a few mm/year [64] to several cm/day [65].…”

Section: Introductionmentioning

confidence: 99%

Land Subsidence Estimation for Aquifer Drainage Induced by Underground Mining

Guzy

Witkowski

2021

Energies

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Land subsidence caused by groundwater withdrawal induced by mining is a relatively unknown phenomenon. This is primarily due to the small scale of such movements compared to the land subsidence caused by deposit extraction. Nonetheless, the environmental impact of drainage-related land subsidence remains underestimated. The research was carried out in the “Bogdanka” coal mine in Poland. First, the historical impact of mining on land subsidence and groundwater head changes was investigated. The outcomes of these studies were used to construct the influence method model. With field data, our model was successfully calibrated and validated. Finally, it was used for land subsidence estimation for 2030. As per the findings, the field of mining exploitation has the greatest land subsidence. In 2014, the maximum value of the phenomenon was 0.313 cm. However, this value will reach 0.364 m by 2030. The spatial extent of land subsidence caused by mining-induced drainage extends up to 20 km beyond the mining area’s boundaries. The presented model provided land subsidence patterns without the need for a complex numerical subsidence model. As a result, the method presented can be effectively used for land subsidence regulation plans considering the impact of mining on the aquifer system.

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Section: Introductionmentioning

confidence: 99%

Land Subsidence Estimation for Aquifer Drainage Induced by Underground Mining

Guzy

Witkowski

2021

Energies

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“…However, strain is the most important subsidence parameter for analysing natural and built surface features. While several well-established methods exist for forecasting mine subsidence [15][16][17][18][19][20][21][22][23][24][25][26], predicting horizontal strain is significantly more difficult since the strain is sensitive to variations in surface features and the presence of near-surface landforms [27,28].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Mining-Induced Horizontal Strain Tensor of Land Surface Applying InSAR

et al. 2021

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Horizontal strains related to mining-induced subsidence may endanger infrastructure and surface users’ safety. While directional horizontal strains should be well determined, appropriate solutions for a complete assessment of the terrain surface deformation field are still required. As a result, the presented study examined a new method for calculating horizontal strain tensor based on the decomposition of satellite radar interferometry (InSAR) observations into vertical and azimuth look direction (ALD) displacements. Based on a geometric integral model, we tested our method on experimental data before applying it to an underground copper ore mine in Poland. In the case study, the displacement field was determined using the Multi-Temporal InSAR method on Sentinel-1 data. The model data relative error did not exceed 0.02 at σ = ±0.003. For the case study, land subsidence of up to −167 mm and ALD displacements ranging from −110 mm to +62 mm was obtained, whereas the extreme values of horizontal strains ranged from −0.52 mm/m to +0.36 mm/m at σ = ±0.050 mm/m. Our results demonstrate the high accuracy of the method in determining the horizontal strain tensor. As a result, the approach can broaden the assessment of the environmental impact of land subsidence worldwide.

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“…Ground subsidence due to coal mining is a complicated fourdimensional time-space process [1,2]. This process leads to various forms of damage to subsurface facilities, such as buildings, roads, and water facilities [3]. Moreover, it relates a series of problems including environmental deterioration, land desertification, and economic loss [4].…”

Section: Introductionmentioning

confidence: 99%

An Improved Knothe Time Function Model in the Prediction of Ground Mining Subsidence by Using the Kalman Filter Method

Zhang

2022

Geofluids

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The Knothe time function is a classical method in predicting the ground mining subsidence. Nevertheless, it does not take the observation data into account in the prediction process. The Kalman filter method can solve this issue at large extent. Taking a coal mining work face of Xishan Coalfield as an example, this research compares the performance of the traditional Knothe time function and that of the improved Knothe time function by using the Kalman filter method. The comparison results show that through an improvement by using the Kalman filter method, the RMSE is improved from 133.4 mm to 78.3 mm; ME, from 91.9 mm to 3.1 mm; and the relative error, from 8.1% to 5.7%. Meanwhile, the improved model has good astringency. These verify that the improved model has higher accuracy and reliability. Hence, this research presents an effective method in predicting ground subsidence of mining area by improving the Knothe time function using the Kalman filter method.

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

Cited by 34 publications

References 24 publications

Land Subsidence Estimation for Aquifer Drainage Induced by Underground Mining

Land Subsidence Estimation for Aquifer Drainage Induced by Underground Mining

Estimation of Mining-Induced Horizontal Strain Tensor of Land Surface Applying InSAR

An Improved Knothe Time Function Model in the Prediction of Ground Mining Subsidence by Using the Kalman Filter Method

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