Visualizing uncertainty of one-dimensional land subsidence prediction by preparing various local optimal solutions with a genetic algorithm

2021 ◽  
Author(s):  
Kento Akitaya ◽  
Masaatsu Aichi
Keyword(s):  
Genetic Algorithm ◽  
Land Subsidence ◽  
Groundwater Level ◽  
Physical Property ◽  
Optimal Solutions ◽  
Groundwater Level Fluctuations ◽  
Subsidence Prediction ◽  
Subsidence Monitoring ◽  
Inversion Analysis

<p>This study tried to visualize the predictive uncertainty while predicting future land subsidence caused by the groundwater pumping. Because land subsidence modeling is highly uncertain, it is impossible to determine the distribution of subsurface physical property values uniquely. Therefore, we prepared various local optimal solutions through the inversion analysis with a genetic algorithm in order to visualize land subsidence prediction uncertainty. The inversion analysis was conducted using the long-term land subsidence monitoring data at Kawajima in the Kanto Plain, Japan. In this study site, the seasonal groundwater level fluctuations have caused plastic compaction in summer and elastic expansion in winter every year. Obtained multiple sets of subsurface properties were within the range of typical values in the existing literature and satisfactorily reproduced the observed subsidence, showing that the inversion analysis worked well. In addition, the groundwater level scenario analysis was conducted using obtained property sets. This revealed that the subsidences predicted for a sudden groundwater level drop and rapid recovery scenario are more volatile than the subsidences predicted for the stable scenario. This means that it is important to have multiple sets of subsurface properties to predict future land subsidence caused by unprecedented groundwater level fluctuations.</p>

scholarly journals Is There Deep-Seated Subsidence in the Houston-Galveston Area?

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Jiangbo Yu ◽  
Guoquan Wang ◽  
Timothy J. Kearns ◽  
Linqiang Yang
Keyword(s):  
Land Subsidence ◽  
Groundwater Level ◽  
Land Surface ◽  
The Past ◽  
Subsidence Rate ◽  
Different Depths ◽  
Subsidence Monitoring ◽  
Near Future ◽  
Land Subsidence Rate

Long-term continuous groundwater level and land subsidence monitoring in the Houston-Galveston area indicates that, during the past two decades (1993–2012), the groundwater head has been increasing and the overall land subsidence rate has been decreasing. Assuming that the hydraulic head in the aquifer will reach or exceed the preconsolidation level in the near future, will subsidence in the Houston-Galveston area eventually cease? The key to answer this question is to identify if there is deep-seated subsidence in this area. This study investigated the recent subsidence observed at different depths in the Houston-Galveston area. The subsidence was recorded by using 13 borehole extensometers and 76 GPS antennas. Four of the GPS antennas are mounted on the deep-anchored inner pipes of borehole extensometers. We conclude that recent subsidence (1993–2012) in the Houston-Galveston area was dominated by the compaction of sediments within 600 m below the land surface. Depending on the location of specific sites, the compaction occurred within the Chicot aquifer and part or all of the Evangeline aquifer. No measurable compaction was observed within the Jasper aquifer or within deeper strata. Deep-seated subsidence is not likely occurring in the Houston-Galveston area.

scholarly journals Investigation of Sentinel-1 Derived Land Subsidence Using Wavelet Tools And Triple Exponential Smoothing Algorithm In Lagos, Nigeria

2021 ◽  
Author(s):  
Femi Emmanuel Ikuemonisan ◽  
Vitalis Chidi Ozebo ◽  
Olawale Babatunde Olatinsu
Keyword(s):  
Soil Moisture ◽  
Land Subsidence ◽  
Groundwater Level ◽  
Exponential Smoothing ◽  
Future Trend ◽  
Smoothing Algorithm ◽  
Groundwater Abstraction ◽  
Groundwater Level Fluctuations ◽  
History Of ◽  
Sbas Insar

Abstract Lagos has a history of long-term groundwater abstraction that is often compounded by the rising indiscriminate private borehole and water well proliferation. This has resulted in various forms of environmental degradation, including land subsidence. Prediction of the temporal evolution of land subsidence is central to successful land subsidence management. In this study, a triple exponential smoothing algorithm was applied to predict the future trend of land subsidence in Lagos. Land subsidence time series is computed with SBAS-InSAR technique with Sentinel-1 acquisitions from 2015 to 2019. Besides, Matlab wavelet tool was implemented to investigate the periodicity within land displacement signal components and to understand the relationship between the observed land subsidence, and groundwater level change and that of soil moisture. Results show that land subsidence in the LOS direction varied approximately between –94 and 15 mm/year. According to the wavelet-based analysis result, land subsidence in Lagos is partly influenced by both groundwater level fluctuations and soil moisture variability. Evaluation of the proposed model indicates good accuracy, with the highest residual of approximately 8%. We then used the model to predict land subsidence between the years 2020 and 2023. The result showed that by the end of 2023 the maximum subsidence would reach 958 mm which is approximately 23% increase.

scholarly journals Analysis of long-term observations of the groundwater level In an aseismic region

2019 ◽  
pp. 47-67
Author(s):  
A. A. Lyubushin ◽  
O. S. Kazantseva ◽  
A. B. Manukin
Keyword(s):  
Time Series ◽  
Groundwater Level ◽  
Atmospheric Pressure ◽  
Active Regions ◽  
Sampling Interval ◽  
Pressure Effects ◽  
Adaptive Compensation ◽  
Groundwater Level Fluctuations ◽  
And Cluster Analysis

The results of the analysis of continuous precise time series of atmospheric pressure and groundwater level fluctuations in a well drilled to a depth of 400 m in the territory of Moscow are presented. The observations are remarkable in terms of their duration of more than 22 years (from February 2, 1993 to April 4, 2015) and by the sampling interval of 10 min. These long observations are suitable for exploring the stationarity of the properties of hydrogeological time series in a seismically quiet region, which is important from the methodological standpoint for interpreting the similar observations in seismically active regions aimed at earthquake prediction. Factor and cluster analysis applied to the sequence of multivariate vectors ofthe statistical properties of groundwater level time series in the successive 10-day windows after adaptive compensation for atmospheric pressure effects distinguish five different statistically significant states of the time series with the transitions between them. An attempt to geophysically interpret the revealed states is made. Two significant periods – 46 and 275 days – are established by spectral analysis of the sequence of the transitions times between the clusters.

One dimensional numerical modeling of land subsidence caused by seasonal groundwater level fluctuations in Kawajima, Japan

2020 ◽  
Author(s):  
Kento Akitaya ◽  
Masaatsu Aichi
Keyword(s):  
Physical Properties ◽  
Land Subsidence ◽  
Groundwater Level ◽  
Seasonal Fluctuation ◽  
Soil Deformation ◽  
Seasonal Fluctuations ◽  
One Dimensional ◽  
Groundwater Level Fluctuations ◽  
Modified Cam Clay ◽  
Cam Clay

<p>Land subsidence caused by seasonal fluctuation of groundwater level caused by agricultural groundwater use was numerically simulated in this study. In the study area, Kawajima, Saitama prefecture, Japan, the hydraulic head has been gradually increasing over time with seasonal fluctuations and the subsurface formations have repeated expansion and compaction. However, the land subsidence progressed because the compaction included the plastic deformation. In this study, vertically one-dimensional model to numerically simulate coupled groundwater flow and soil deformation in Kawajima was developed with modified cam-clay model. Because of the lack of subsurface information, it was difficult to set the physical properties such that the simulated subsidence and the observed subsidence are satisfactorily close to each other. This study applied a genetic algorithm in order to search the set of underground physical properties. The improved set of underground physical properties succeeded to reproduce the observed land subsidence in Kawajima.</p>

Long-term groundwater level changes and land subsidence in Tianjin, China

2020 ◽  
Author(s):  
Da Ha ◽  
Gang Zheng ◽  
Hugo A. Loáiciga ◽  
Wei Guo ◽  
Haizuo Zhou ◽  
...  
Keyword(s):  
Land Subsidence ◽  
Groundwater Level ◽  
Groundwater Level Changes

scholarly journals LONG-TERM GROUNDWATER REGIME TRENDS IN THE AGRICULTURAL AREAS

2018 ◽  
Author(s):  
Aurelija RUDZIANSKAITĖ
Keyword(s):  
Groundwater Level ◽  
Land Surface ◽  
Sandy Loam ◽  
Peat Soil ◽  
Mineral Soil ◽  
Hydrological Regime ◽  
Kendall Test ◽  
Groundwater Level Fluctuations ◽  
Mineral Soils

Long-term data on hydrological regime change of the groundwater situated in moraine sandy loam and peat in Lithuanian karst zone presented in the article. The aim of the paper was on the basis of long-term groundwater studies to determine the water level trends. Groundwater level fluctuations mainly dependent on the ground type. The nearest land surface groundwater level (61-174 cm) was measured in peat soil (well 1), in mineral soil (well 2) was deeper (309-584 cm). Correlation between data of the annual precipitation and groundwater level in mineral soils (r2 = 0.416, tact .= 3.48>t95%=1.74) was more significant than in peat soils (r2 = 0.185, tact.=1.96 >t95%=1.74). The highest fluctuations of groundwater level was determined in mineral soil (well 2). According to Mann-Kendall test, the groundwater level significantly increased in February, April and December. Due to warmer winters decreased the duration and depth of the frost, frequent thaw, this cause increased feeding of aquifer in winter.

scholarly journals Long-Term Land Subsidence Monitoring of Beijing (China) Using the Small Baseline Subset (SBAS) Technique

2014 ◽  
Vol 6 (5) ◽  
pp. 3648-3661 ◽  
Author(s):  
Bo Hu ◽  
Han-Sheng Wang ◽  
Yong-Ling Sun ◽  
Jian-Guo Hou ◽  
Jun Liang
Keyword(s):  
Land Subsidence ◽  
Small Baseline Subset ◽  
Small Baseline ◽  
Subsidence Monitoring ◽  
Beijing China

scholarly journals Introduction to GPS geodetic infrastructure for land subsidence monitoring in Houston, Texas, USA

2015 ◽  
Vol 372 ◽  
pp. 297-303 ◽  
Author(s):  
G. Wang ◽  
J. Welch ◽  
T. J. Kearns ◽  
L. Yang ◽  
J. Serna Jr.
Keyword(s):  
Reference Frame ◽  
Metropolitan Area ◽  
Land Subsidence ◽  
Groundwater Level ◽  
High Accuracy ◽  
Gps Technology ◽  
The Past ◽  
Software Packages ◽  
Subsidence Monitoring ◽  
Houston Metropolitan Area

Abstract. Houston, Texas is one of the places that first employed high-accuracy GPS technology for land subsidence monitoring beginning in the late 1980s. Currently, there are over 170 permanent GPS stations located in the Houston metropolitan area. This article summarizes the current GPS geodetic infrastructure in the Houston metropolitan area, which is comprised of three components: a dense GPS network with 170 permanent stations, a stable Houston reference frame (SHRF14), and sophisticated software packages for post positioning processing. Average land subsidence and groundwater-level altitude changes during the past 10 years (2005–2014) also are presented in this paper.

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