State of the Art and Recent Advancements in the Modelling of Land Subsidence Induced by Groundwater Withdrawal

Guzy, Artur; Malinowska, Agnieszka

doi:10.3390/w12072051

Cited by 77 publications

(48 citation statements)

References 192 publications

(310 reference statements)

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“…In the upcoming decades, population growth and associated economic activities will continue to increase the demand of groundwater and groundwater depletion, and severe LS activities are found in different regions of the world (Famiglietti, 2014). Thus, the most important natural resources, i.e., water levels, are gradually declining due to over-extraction for agricultural, domestic and industrial uses (Abdollahi et al, 2019;Guzy and Malinowska, 2020). Apart from this, climate change and its associated phenomena have a major impact on LS in this region.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of GIS-Based Novel Ensemble Approaches for Land Subsidence Susceptibility Mapping

et al. 2021

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The optimal prediction of land subsidence (LS) is very much difficult because of limitations in proper monitoring techniques, field-base surveys and knowledge related to functioning and behavior of LS. Thus, due to the lack of LS susceptibility maps it is almost impossible to identify LS prone areas and as a result it influences severe economic and human losses. Hence, preparation of LS susceptibility mapping (LSSM) can help to prevent natural and human catastrophes and reduce the economic damages significantly. Machine learning (ML) techniques are becoming increasingly proficient in modeling purpose of such kinds of occurrences and they are increasing used for LSSM. This study compares the performances of single and hybrid ML models to preparation of LSSM for future prediction of performance analysis. In this study, the spatial prediction of LS was assessed using four ML models of maximum entropy (MaxEnt), general linear model (GLM), artificial neural network (ANN) and support vector machine (SVM). Alongside, the possible numbers of novel ensemble models were integrated through the aforementioned four ML models for optimal analysis of LSSM. An inventory LS map was prepared based on the previous occurrences of LS points and the dataset were divvied into 70:30 ratios for training and validating of the modeling process. To identify the robust and best LSSMs, receiver operating characteristic-area under curve (ROC-AUC) curve was employed. The ROC-AUC result indicated that ANN model gives the highest ROC-AUC (0.924) in training accuracy. The highest AUC (0.823) of the LSSMs was determined based on validation datasets identified by SVM followed by ANN-SVM (0.812).

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Section: Introductionmentioning

confidence: 99%

Performance Evaluation of GIS-Based Novel Ensemble Approaches for Land Subsidence Susceptibility Mapping

et al. 2021

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“…Natural Earth factors such as neotectonics [1], volcanic eruptions [2], earthquakes [3] and anthropogenic activities including surface and subsurface urban building [4,5], oil and groundwater extraction [6,7] and mining [8] can all cause land subsidence. This type of phenomenon has been witnessed in various regions around the world for decades [7]. Nonetheless, the growing demand for natural resources is the primary cause of ground subsidence worldwide [9].…”

Section: Introductionmentioning

confidence: 99%

“…The decrease in the groundwater head causes consolidation and compaction of the drained aquifer and the propagation of rock mass deformation to the terrain surface [25,69]. As a result, land subsidence caused by groundwater withdrawal occurs, and, therefore, watercourses and surface reservoirs may be impacted [7,15,25].…”

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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“…The cadastral data are usually referenced to an ellipsoid, and the impact of vertical motions (heights) needs to be considered. Changes of heights, using a geoid as a reference surface, may be caused by: (i) locally by mining [18]; (ii) regionally by Earth crust movements [19]; and (iii) globally by the uplift of the sea level [20]. The last factor has the longest research history, for example, about 250 years for the area of the Baltic Sea [21].…”

Section: Introductionmentioning

confidence: 99%

Crustal Deformation Across and beyond Central Europe and Its Impact on Land Boundaries

et al. 2021

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Land is a critical and limited natural resource. The Land Administration System (LAS) has been developed to resolve and adjudicate over any disputes that might arise concerning the rights and boundaries of land. Land registration and cadastre are types of land recording that need to be established. To secure the property rights, we must be sure of accuracy of the boundary points determining the size of the property. However, in addition to typical factors considered when determining the boundary point positions, such as accuracy of geodetic networks and measurement errors, the global and local crustal deformation, resulting, e.g., from the movement of tectonic plates, should be considered. In this work, the focus is on the movement of points inside the European plate due to tectonic movement, without taking into account local events caused by erosion, landslides, etc. The study area is Europe, and particular attention was paid to Poland, which is located in the centre of the European continent and does not have significant anomalous sub-areas, making it an authoritative research object. In this study, we analysed the velocity of point displacements and the boundary deformation, using GPS observations. For this reason, we used both global (IGS) and regional (ETRF) reference frames, to show differences in point velocities for the studied areas. Overall, for the needs of the real estate cadastre in Poland, information about parcel boundary points must be obtained with an accuracy better than 0.30 m. Within 25 years, the border mark may be shifted by 0.13 m due to tectonic plate movement, which is within the required accuracy. Pursuant to the current legal regulations, the measurements of the boundary points can be performed with any method, ensuring the required accuracy (0.30 m). The most commonly used are direct measurements (GNSS and tacheometry) and photogrammetric measurements. It is recommended that periodic verifications and update of the cadastre data in Poland be carried out at least once every 15 years. In the case of such relatively frequent verification and possible modernisation of data, the potential impact of tectonic plate movement on the relative boundary point displacement can be ignored, particularly in the short term. However, for a long time period it has an influence. We suggest “relatively frequent” cadastral boundary verification to be able to ignore such influence.

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State of the Art and Recent Advancements in the Modelling of Land Subsidence Induced by Groundwater Withdrawal

Cited by 77 publications

References 192 publications

Performance Evaluation of GIS-Based Novel Ensemble Approaches for Land Subsidence Susceptibility Mapping

Performance Evaluation of GIS-Based Novel Ensemble Approaches for Land Subsidence Susceptibility Mapping

Land Subsidence Estimation for Aquifer Drainage Induced by Underground Mining

Crustal Deformation Across and beyond Central Europe and Its Impact on Land Boundaries

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