Subsidence prediction

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A fusion model used in subsidence prediction in Taiwan

A fusion model used in subsidence prediction in Taiwan

fuse two types of time series for subsidence prediction results in both the spatial and temporal domains and applied to sub- sidence fusion in Jhuoshuei River Alluvial Fan, Taiwan. The fusion method uses a slope criterion and a distance weighting factor to obtain a spatially and temporally connected two- dimensional subsidence distribution by upgrading two one- dimensional models. Wang et al. (2015) adopted this fusion technique to combine the physics-based nonlinear poroelas- tic model (NPM) and the grey-box-based grey system model (GSM) to evaluate the subsidence under the climate change effect in Tainan, Taiwan and got good results. The authors have also applied the fusion technique to predict the subsi- dence in Kaohsiung, Taiwan, which is not yet published.
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Subsidence Prediction and Backfilling Technique Based on Longwall Multi-slice Top Coal Caving in Dighipara Coal Field, Dinajpur, Bangladesh

Subsidence Prediction and Backfilling Technique Based on Longwall Multi-slice Top Coal Caving in Dighipara Coal Field, Dinajpur, Bangladesh

There are very little information is available for subsidence prediction model; particularly the stress-strain behavior of litho-stratigraphy of Bangladesh, and this limited information are not sufficient for detail analysis of subsidence model. For this reason, the empirical Graphical method is used for the prediction of surface subsidence of Dighipara Coal Field. An approximate method for calculation of the subsidence due to underground mining is given in the Subsidence Engineer’s Handbook (NCB, 1975). Considering all of the limitations stated in the manual of the handbook, the NCB method applied in the case of Dighipara Coal Mine conditions with a considerable degree of accuracy. In this research work the calculation of the vertical subsidence, stress and strain behavior of the ground surface and horizontal displacement, the NCB methods are used.
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Multi-seam mining-induced ground surface subsidence, characteristics and prediction

Multi-seam mining-induced ground surface subsidence, characteristics and prediction

ing the basis for developing subsidence prediction methods. It provides in- sights into the mechanisms of strata movements above longwall panels. Phys- ical modelling, at its best, illustrates the physics of the phenomenon, indicates the main principles that cause the most important observations and has the

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Estimating Highway Subsidence due to Longwall Mining

Estimating Highway Subsidence due to Longwall Mining

Longwall mining is a common underground coal extraction technique in Appalachia. The extraction takes the form of panels whose width and length can reach approximately 450 m and 4000 m, with a thickness of about 2.0 m. Typical depth ranges from 180 m to 280 m. Longwall panels were mined underneath highway I-79 in the Cumberland and Emerald mines in southwestern Pennsylvania, causing large subsidence that affects traffic safety and can potentially damage highway structures such as pavements, culverts, and bridge abutments. Mining under the highway prompted the close monitoring by the Pennsylvania Department of Transportation of the impact of mining on the highway sections above the mines. A substantial amount of data was collected that formed the basis of this work. The data included time series of surveying data and inclinometer data in selected points. With the aid of a genetic algorithm, a three dimensional subsidence model was developed. The model gives the spatial and temporal distribution of surface subsidence in terms of the depth of mining, the panel width, the thickness of extraction, and the location relative to the face of the panels. Although the prediction of vertical deformations through the empirical model is feasible, the lateral deformation behavior of highway foundations did not always follow the premises adopted in existing subsidence prediction tools, often based on flat conditions. The complex topography of highway foundations, dominated by embankments with irregular cross sections, a sloped grade, and different orientations with respect to the direction of mining, gives each case a unique character that deems it very difficult to develop comprehensive empirical models to predict the location
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Monitoring and predicting railway subsidence using InSAR and time series prediction techniques

Monitoring and predicting railway subsidence using InSAR and time series prediction techniques

The railway is a long and relatively narrow infrastructure, which subsides continuously over a long time period. As a result, larger image coverage and long time monitoring periods are two key requirements for railway subsidence monitoring. In addition, railway subsidence monitoring should also consider the repeatability, precision and efficiency of the monitoring method, as well as labour costs. The Interferometric Synthetic Aperture Radar (InSAR) technique, which is able to monitor railway subsidence over a large area and long time period, was selected for railway subsidence monitoring by the author. In order to obtain a more reliable railway subsidence measurement result, and extension of InSAR, PS-InSAR (Permanent Scatterer InSAR), was used for the research, since it is capable of supporting a time series analysis of ground deformation. In addition to railway subsidence monitoring, future trends of railway subsidence should also be predicted using subsidence prediction models. Railway deformation records obtained by PS-InSAR can be considered as a discrete time series. As a result, three time series prediction models have been investigated in this thesis for railway subsidence prediction, which are the traditional statistical ARMA model, a neural network model based on artificial intelligence and the grey model.
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Prediction of subsidence due to underground mining by artificial neural networks

Prediction of subsidence due to underground mining by artificial neural networks

Abstract Alternatively to empirical prediction methods, methods based on influential functions and methods based on mechanical model, artificial neural networks can be used for the the surface subsidence prediction. In our case, the multi-layer feed-forward neural network was used. The training and testing of neural network is based on available data. Input variables represent extraction parameters and coordinates of the points of interest, while the output variable represents surface subsidence data. After the neural network has been successfully trained, its performance is tested on a separate testing set. Finally, the surface subsidence trough above the projected excavation is predicted by the trained neural network. The applicability of artificial neural network for the prediction of surface subsidence was verified in different subsidence models and proved on actual excavated levels and in levelled data on surface profile points in the Velenje Coal Mine.
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Compaction and subsidence of the Groningen gas field in the Netherlands

Compaction and subsidence of the Groningen gas field in the Netherlands

The above mentioned compaction models have been used to calculate subsidence at the benchmark locations at the surface. The translation from compaction to subsidence is based on a 1-D model (van Opstal, 1974). In this method, the non-compacting area around the reservoir (side-, over- and underburden) is assumed to be homogeneous and elas- tic. In the case of Groningen, the overburden is highly non- homogeneous as illustrated in the thickness of the Zechstein (Fig. 2). Additionally a rigid basement at a depth of 5 km is assumed, which determines the shape of the subsidence bowl (van Opstal, 1974) at the edges of the reservoir. The differ- ence between measured and modeled subsidence is used to fit the resulting unknown parameters: τ for Time Decay and
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Land Subsidence from Groundwater Use in California

Land Subsidence from Groundwater Use in California

LSCE, BORCHERS AND CARPENTER 25 cost to operate the additional pumping facilities at the San Jose-Santa Clara Sewage Treatment Plant at $200,000 annually in 1970 ($28 million total through 2013 in 2013 dollars). Raising the grades of roads and bridges cost $2.8 million by 1975 ($12 million in 2013 dollars) not including the costs of repairs necessitated by flooding. The estimated cost of constructing bayfront levees was $58 million in 1973 ($305 million in 2013 dollars), and the initial cost of raising stream channel levees was more than $10 million in 1979 ($32.2 million in 2013 dollars). The initial capital outlay to build pumping stations to remove storm drainage was $2.7 million in 1975 ($12 million in 2013 dollars). Annual operation and maintenance costs for the pumping facilities were expected to exceed the total capital outlay for construction of the plants ($283 million in 2013 dollars). Raising a Southern Pacific Railroad bridge to align it to tracks that had to be moved to avoid flooding cost $100,000 in 1970 (0.6 million in 2013 dollars). Roll’s (1967), Viets and others (1979), and Fowler’s (1981) cost estimates translate to more than $756 million in 2013 dollars spent on subsidence remediation in the Santa Clara Valley. These costs did not include replacing destroyed wells or repairing wells at other times than 1960-1965, or the indirect costs of silted up stream channels in flood prone areas. Costs to the Southern Pacific Railroad (and its successors) to raise tracks are not included in these estimated costs, nor are the substantial costs to private industry to raise about 80 km (50 mi) of levees protecting 80 km 2 (30 mi 2 ) of salt evaporation ponds that fringe the bay. The decline in the property values resulting from obstructed views or by flood zone designation has also not been estimated.
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Study on the risk and impacts of land subsidence in Jakarta

Study on the risk and impacts of land subsidence in Jakarta

Rapid urban development in Jakarta also contributes to increasing risk of land subsidence occurences in Jakarta (Abidin et al., 2011). In this case, the increases in built-up ar- eas, population, economic and industrial activities, will then increase groundwater extraction and also buildings and in- frastructure loadings; which usually in turn lead to land sub- sidence phenomena. The relatively very rapid urban devel- opment of Jakarta as a megapolitan city is mainly in the sectors of industry, trade, transportation, housing, hotel and apartment, and many others (Firman, 1999, 2004; Hudalah et al., 2013); and they have introduced several negative en- vironmental problems (Firman and Dharmapatni, 1994; Hu-
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Growth Faulting and Subsidence in the Houston, Texas Area:

Growth Faulting and Subsidence in the Houston, Texas Area:

Section 3.7 Better Geodetic Controls and Measurement of Subsidence Houston-area faulting and fault movements have been triggered by oil and gas production, groundwater production, and microseismic activity associated with movements at greater depths, earthquakes and/or injection activities. The development of better geodetic measurements via geopositioning systems (GPS) data has provided the opportunity to more easily discern and study subsidence. For example, GPS data clearly document significant ongoing subsidence of the Jersey Village subsidence depression (shown in Figure 15 by the circular shaded area in dark gray), along with lesser subsidence throughout the region. Horizontal displacements were largely due to the motion of the North American plate during the study interval. Engelkemeir, et al., (2010) conclude that displacement differences among occupied sites may be indicative of the regional motion towards the Gulf of Mexico, possibly related to the movement along active growth faults.
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Section 3.13: LAND SUBSIDENCE AND EXPANSIVE SOILS

Section 3.13: LAND SUBSIDENCE AND EXPANSIVE SOILS

3.13-10 Final Release Date January 4, 2014 Figure 3.13f: Retsof Mine Collapse Study Area An underground room at the southern end of the mine near Cuylerville collapsed on March 12, 1994, and an adjacent room collapsed in early April. Two large circular collapse features that are several hundred feet apart have developed at land surface above the two collapsed mine rooms. The northernmost feature, which is about 700 ft. in diameter, includes a central area about 200 ft. wide that has subsided about 20 to 30 ft. The southernmost feature, which is about 900 ft. in diameter, includes a central area that is about 700 ft. wide that has subsided about 70 ft. The subsidence resulted in the partial collapse of a DOT bridge and forced the closure of a section of State Route 20A.
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Studying Land Subsidence around the City of Shiraz

Studying Land Subsidence around the City of Shiraz

appear when qanat and surface stream dried. It can be concluded that the initial cause of these cracks can be the drop in Groundwater levels and dried qanat and surface streams. Cracks and gaps in this area emerged due to the dierence in subsidence between locations of qanat canals, in which water had already owed, and the surrounding area with no cavity and change in the underlying layers. Comprehensive and complete studies with regard to cracks and ssures created in other places and other qanat series within the studied area and its adjacent areas demonstrated that this consistency was only in a limited number of places; and in some other places, such as Shul village, there were very large cracks which caused many failures, but there were no qanats.
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A Hybrid Clustering-Fusion Methodology for Land Subsidence Estimation

A Hybrid Clustering-Fusion Methodology for Land Subsidence Estimation

Metropolitan and agricultural development increase groundwater resources withdrawal, which in turn poses serious environmental challenges. Unregulated and excessive groundwater extraction for agricultural, domestic and industrial use have resulted in severe drop in groundwater table in several basins in Iran (Motagh et al. 2008; Sadegh et al. 2010; Sadegh and Kerachian, 2011). Decline in groundwater level increases the effective stress in the aquifer system that promote compaction in fine-grained sediments (Budhu and Adiyaman 2009; Dehghani et al. 2013), which in turn prompts land subsidence. In addition to groundwater level decline, other geology and hydrogeology factors can affect subsidence rate, including gas, oil and geothermal water extraction (Gambolati et al. 2005), coal mining (Jung et al. 2007) and sudden hydrogeological changes along faults (Burbey 2002). Precise estimation of land subsidence provides helpful information to decision makers in their efforts to control and mitigate the impacts of such a grave hazard. Satellites have provided alternative land subsidence monitoring methods complementing in situe observations based on remote sensing techniques. In the previous decades, several studies have performed monitoring and analyzing land subsidence due to groundwater withdrawal based on observations from satellites and radars such as Environmental Satellite Advanced Synthetic Aperture Radar (ENVISAT ASAR) (Osmanoglu et al. 2011; Yue et al. 2011; Ng et al. 2012; Dehghani et al. 2013; Strozzi et al. 2017; Deng et al. 2017; Lu et al. 2018; Du et al. 2018). Interferometry Synthetic Aperture Radar (InSAR) is one such technique that provides accurate measurements of land subsidence (Amelung et al. 1999; Carnec and Fabriol 1999; Nakagawa et al. 2000; Ding et al. 2004; Dehghani et al. 2009; Yu et al. 2011; Calderhead et al. 2011;Cigna et al. 2012; Teatini et al. 2012; Qu et al. 2014; Strozzi et al. 2017; Lu et al. 2018; Du et al. 2018; Nadiri
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Three dimensional numerical modeling of land subsidence in Shanghai

Three dimensional numerical modeling of land subsidence in Shanghai

In geomechanical investigations at regional scale, uncoupled pressure – displacements solution can be safely used in pre- dicting land subsidence in compacting sedimentary on any time scale of practical interest (Gambolati et al., 2000; Tea- tini et al., 2006, 2010). In this study, an uncoupled approach is thus followed, with the flow field initially computed at each time step and the deformation then calculated using the pore pressure gradient as a known source of strength in the geome- chanical model. The 3-D uncoupled land subsidence model is expressed as (Verruijt, 1969):

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Multiple sensors applied to monitorland subsidence in Central Taiwan

Multiple sensors applied to monitorland subsidence in Central Taiwan

According to the results from the GPS CORSs observed from April 2010 to April 2014, presented in Fig. 6b, the re- gion along the high speed rail runs through the main sub- sidence area in the Yunlin County, especially around the Huwei Township (GFES GPS station located), Tuku Town- ship (TKJS GPS station located), and Yuanchang Township (KTES GPS station located). The rate of subsidence can reach 6 cm per year. The agreement between the results from GPS CORS and Leveling survey can be obtained. Because the advantage of continually observing from GPS CORS, the deformation of land surface caused by the seasonal variation and the change of groundwater in wet/dry season can be de- tected via the Principal Component Analysis (PCA) strategy.
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An integrated assessment framework for land subsidence in delta cities

An integrated assessment framework for land subsidence in delta cities

While subsidence in large urban environments in deltaic regions can usually be associated with groundwater extrac- tion, in the case of the Netherlands, where deep extractions are rare, centuries of drainage of surface water, often from former peat marshes has resulted in the widespread low- ering of the landsurface by several metres. This is exac- erbated by the historic exploitation of peat for fuel, leav- ing large areas below sea level. These areas were reclaimed and converted in fertile clay polders, but require constant drainage of upwelling groundwater from the underlying con- fined aquifers. Although the recent upconing of brackish wa- ter in these polders poses a water management challenge to adapt to these changing environmental and agricultural cir- cumstances, the area where the surficial and shallow peat re- mained poses the greatest problems (Cuenca et al., 2010). Not only does the oxidation of drained peat produce a signif- icant amount of green house gas, the continuing subsidence in these areas leads to larger areas where the volumes of up- welling water become a significant economical cost factor. Here also the risk of upconing of brackish groundwater is looming in the background. The greatest cost factor however has been shown to be the gradual deterioration of foundations and infrastructure.
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The Investigation of Subsidence Effect on Buried Pipes in 3D Space

The Investigation of Subsidence Effect on Buried Pipes in 3D Space

Kang et al. [3] showed that the surface pressure exerted on the pipes implemented in deep depth is always influenced by the subsidence of soil mass above and around the pipe. They also found that pressure on the pipe decreases if the top layer of the pipe is replaced by lighter materials with higher compressibility. Evidently, cast iron pipes are more appropriate options in this situation since their rigidity is higher than that of steel pipes. Ozkan and Mohareb [4] performed some experiments on the pipes and found that due to the plasticity condition of the pipe and loads in the given problem, among all investigated parameters only axial force is capable of moment distribution. They also concluded that the induced axial tension is effective in reaching a plastic condition resistance in the pipe.
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Subsidence at the “Trébol” of Quito, Ecuador: an indicator for future disasters?

Subsidence at the “Trébol” of Quito, Ecuador: an indicator for future disasters?

ing which leads the river Machangara for a distance of some 20 m. Fortunately, no victims where reported. The result of this subsidence has been a traffic collapse and the declara- tion of the state of emergency of the Municipality of Quito. This event forced the authorities of Quito first to find out the causes of this subsidence and afterwards to search for fur- ther areas with similar problems and vulnerabilities in order to avoid future disasters where potentially people could be involved.

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Behaviour of buildings due to tunnel induced subsidence

Behaviour of buildings due to tunnel induced subsidence

greenfield surface settlement prediction, while on the other hand it yields a more conservative estimate of the modification factors. This trend is further demonstrated when plotting the deflection ratios versus relative bending stiffness ρ ∗ . Figure 4.6 shows this plot for the results of the 70m wide mesh. The data points obtained by Potts & Addenbrooke (1997) are also given for comparative purposes. For the DR sag results it can be seen that the data points for a global K 0 lie above their counterparts for a K 0 -reduced zone. For the 3 and the 5 storey building the reduced K 0 points of this study coincide well with the results by Potts & Addenbrooke (1997). For the 1-storey building (lowest ρ ∗ ) there is some scatter which can be explained by the different ap- proaches adopted to determine the point of inflection and thus the deflection ratio (explained in Section 3.4.5): In this thesis a spread sheet calculation has been used while a graphical approach was chosen by Potts & Addenbrooke (1997). The modification factors M DR hog are low and therefore all data points lie close together when plotted on a scale that enables the design curves to be included.
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Subsidence Hazard Zoning of Jiroft Plain, Southeast Iran

Subsidence Hazard Zoning of Jiroft Plain, Southeast Iran

Abstract:- This paper deals with subsidence hazard zoning in Jiroft plain which lies at 28º 15´ to 28º 50´ northern latitude and 57º 40´ to 58º 00´eastern longitude in SE Iran. In order to evaluate this hazard, firstly, geological, geomorphological as well as hydrogeological conditions of the plain were studied and, secondly, location and causes of subsided sites were investigated and, lastly, hazard assessment and zoning was undertaken. In this region, clay dehydration as a result of over-exploitation and groundwater-level decline is considered as the cause of subsidence which has inflicted damages to structures, roads and cultivation fields. Subsidence is manifested as open and wide fissures. The main criteria for zoning include the presence or absence of fissures, the extent of water-table drop, the kind of deposits (presence, absence and purity of clays) and the original depth of water table. In general, four zones were separated and mapped which include high, medium and low-hazard zones as well as a hazard-free zone. In the end, land-use recommendations are offered for each zone.
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