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1.
上海市地面沉降泊松旋回长期预测 总被引:8,自引:0,他引:8
本文在上海地面沉降长期预测研究的实际经验基础上,对泊松旋回模型进行了一定的改进,建立了地面沉降泊松旋回预测的数学模型,提出了应用于预测的技术处理方法,适宜于进行地面沉降长期预测。预测的上海部分标点1995 ̄2050年地面沉降量10 ̄37cm,并对这一预测成果进行了一定评估,认为,在现有研究水平上是可信的。把衰减系数引入泊松旋回模型中是本方法的特色之一。 相似文献
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西安地面沉降及地裂缝阶段预测 总被引:4,自引:0,他引:4
地面沉降及地裂缝可视其为复合地质灾害现象。二者性质不同,但就其发展阶段或单旋回过程而言,皆可将其归并于有限系统。本文讨论了西安市小寨地面沉降带的地质背景,建立了泊松旋回预测方程,论证了二者的演化规律及其盛衰阶段。引入指数函数法,进行了沉降阶段的对比研究。根据历史记录,讨论了西安地裂缝兴衰与我国陆块板内地震活动的对应关系。 相似文献
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常州市地面沉降灰色模型预测 总被引:3,自引:0,他引:3
朱兴贤 《水文地质工程地质》1992,19(2):47-48
地面沉降过程可视为有限体系,本文分析了常州市地面沉降动态特征,采用费尔哈斯特(Verhulst)生物繁殖模型,以监测资料为背景予以灰色系统理论处理和进行沉降旋回期或寿命预测。在地下水得到控制开采和回灌补给条件下,常州市地面沉降旋回期为60年,至2030年沉降速率超近于零,为常州市合理开发地下水,控制沉降灾害提供宏观中长期预测信息。 相似文献
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灰色系统在地面沉降分析中的应用 总被引:4,自引:0,他引:4
该文将灰色系统理论引入地面沉降的研究之中。根据上海地面沉降的历史数据建立了上海地面沉降发展的GM(1,1)模型以及地面沉降与地下水位变化的映射GM(1,2)模型,最后运用所建立的模型对地面沉降的发展态势进行了预测。 相似文献
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地面沉降是目前常见的地质灾害之一,其长期的积累给城市带来巨大的经济损失,成为制约城市发展的主要因素。进入20世纪90年代以来,工程环境效应诱发的沉降已经成为上海地面沉降的新趋势,对于外荷载引起的地面沉降过程而言,影响因素较多,既无法用明确的数学关系式表达,又非黑箱那样内部结构、参数和特征一无所知,因此可将灰色预测理论应用于地面沉降的预测。针对监测和观测时间的非等时性,本文应用非等时距灰色理论模型对上海陆家嘴地区某高层建筑的沉降进行预测,并和实际监测沉降量进行了比较;对室内模型试验进行沉降预测,并和实验观测数据以及自适应神经网络系统(ANFIS)预测结果进行了比较。研究发现,对于工程环境效应引起的地面沉降,应用非等时距灰色理论模型进行沉降预测是可行、精确的。 相似文献
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本文对地铁隧道施工中地面沉降模型进行了研究,并且应用这些模型,结合数值分析软件,对具体工程的地面沉降进行了预测。预测结果对于后续施工工艺的选择起到了指导性的作用,取得了良好的经济效益。 相似文献
9.
阜阳市地面沉降趋势预测 总被引:2,自引:0,他引:2
阜阳市地面沉降是典型的因抽汲松散岩层地下水引起水位(压)下降而造成的地面沉降。本文采用固结理论、回归分析、灰色理论等三种方法建立地面沉降预测模型,旨在探讨在未建基岩标、分层标的城市如何定量研究地面沉降,同时对该市地面沉降的发展趋势进行预测,提出控制地面沉降的措施。 相似文献
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Application of grey theory-based model to prediction of land subsidence due to engineering environment in Shanghai 总被引:7,自引:0,他引:7
Yi-Qun Tang Zhen-Dong Cui Jian-Xiu Wang Li-Ping Yan Xue-Xin Yan 《Environmental Geology》2008,55(3):583-593
Land subsidence is a common geological hazard. The long-term accumulation of land subsidence in Shanghai has caused economic
loss to the city. Since the 1990s, the engineering structures have become a new cause of land subsidence. Many factors affect
the process of land subsidence. Although such a process cannot be explicitly expressed by a mathematical formula, it is not
a “black box” whose internal structure, parameters, and characteristics are unknown. Therefore, the grey theory can be applied
to the prediction of land subsidence and provides useful information for the control of land subsidence. In this paper, a
grey model (GM) GM (1, 1) with unequal time-intervals was used to predict the subsidence of a high-rise building in the Lujiazui
area of Shanghai, and the results were compared with the monitored data. The prediction of subsidence was also corroborated
by laboratory tests and the results were compared with measured data and the predicted data by the adaptive neuro-fuzzy inference
system (ANFIS). It is found that the GM (1, 1) with unequal time-intervals is accurate and feasible for the prediction of
land subsidence. 相似文献
12.
Jian-Xiu Wang Bo Feng Li-Sheng Hu Yi-Qun Tang Xue-xin Yan Han-mei Wang Jin-bao Liu 《Environmental Earth Sciences》2013,69(1):93-102
The restrictions of the geo-environment are often ignored in urban planning, thereby directly causing a variety of geological hazards, including large areas of land subsidence in soft soil area. Based on the control objective of land subsidence, the geo-environmental capacity of ground buildings (GECGB) is defined. The relationship between floor area ratio (FAR) and land subsidence in Shanghai, China is analyzed. The results illustrate that land subsidence increases as FAR increases, and that the engineering environmental effect of the high-rise building group is the main factor affecting land subsidence in Shanghai, China. Hayashi’s Quantification Theory type I is selected to evaluate the GECGB of four typical areas in Shanghai. The prediction model is established based on existing background materials and the GECGB expressed by allowable FAR of the four typical areas are calculated. The evaluation approach promoted in this paper can be applied in urban planning to control the land subsidence induced by dense high-rise buildings. 相似文献
13.
The state of land subsidence and prediction approaches due to groundwater withdrawal in China 总被引:13,自引:6,他引:7
This article gives a general introduction to land subsidence with the prediction approaches due to withdrawal of groundwater
in three subsided/subsiding regions in China: the deltaic plain of Yangtse River (YRDP), North China Plain (NCP), and Fenwei
Plain (FP). On YRDP, Shanghai is the typical subsided/subsiding city; on NCP Tianjin is the typical subsided/subsiding city,
and on FP Taiyuan is the typical subsided/subsiding city. The subsided area with subsidence over 200 mm on YRDP is about 10,000 km2 and the maximum subsided value reached 2.9 m at Shanghai; on NCP the subsided area reached 60,000 km2 with the maximum subsidence of 3.9 m at Tianjing; on FP the subsided area is relatively smaller than that on the other two
plains and is about 1,135 km2 with maximum subsidence of 3.7 m at Taiyuan city. In order to protect the civil and industrial facilities, it is necessary
to predict the future development of land subsidence based on present state. Many researchers proposed several approaches
to predict the land subsidence due to groundwater withdrawal according to different geological conditions and groundwater
withdrawal practice. This article classifies these approaches into five categories: (i) statistical methods; (ii) 1D numerical
method; (iii) quasi-3D seepage model; (iv) 3D seepage model; (v) fully coupled 3D model. In China, the former four categories
are presently employed in the prediction practice and their merits and demerits are discussed. According to the prediction
practice, 3D seepage model is the best method presently. 相似文献
14.
地面沉降是加速潮灾、涝灾等自然灾害的风险源.由于上海市市政建设和高层建筑的建设以及周边地区继续抽取地下水的影响,地面沉降趋势仍在继续.这使上海市在未来必将遭受地面沉降灾害所产生的巨大经济损失.分析了上海市未来地面沉降灾害产生经济损失的可能性、损失程度等.通过对影响未来地面沉降灾害经济损失不确定因素的分析,运用统计方法评估了2001-2020年间上海市地面沉降灾害风险的经济损失.经评估,2001-2020年上海区地面沉降灾害风险经济损失总额为245.7亿元. 相似文献
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Shujun Ye Yue Luo Jichun Wu Xuexin Yan Hanmei Wang Xun Jiao Pietro Teatini 《Hydrogeology Journal》2016,24(3):695-709
Shanghai, in China, has experienced two periods of rapid land subsidence mainly caused by groundwater exploitation related to economic and population growth. The first period occurred during 1956–1965 and was characterized by an average land subsidence rate of 83 mm/yr, and the second period occurred during 1990–1998 with an average subsidence rate of 16 mm/yr. Owing to the establishment of monitoring networks for groundwater levels and land subsidence, a valuable dataset has been collected since the 1960s and used to develop regional land subsidence models applied to manage groundwater resources and mitigate land subsidence. The previous geomechanical modeling approaches to simulate land subsidence were based on one-dimensional (1D) vertical stress and deformation. In this study, a numerical model of land subsidence is developed to simulate explicitly coupled three-dimensional (3D) groundwater flow and 3D aquifer-system displacements in downtown Shanghai from 30 December 1979 to 30 December 1995. The model is calibrated using piezometric, geodetic-leveling, and borehole extensometer measurements made during the 16-year simulation period. The 3D model satisfactorily reproduces the measured piezometric and deformation observations. For the first time, the capability exists to provide some preliminary estimations on the horizontal displacement field associated with the well-known land subsidence in Shanghai and for which no measurements are available. The simulated horizontal displacements peak at 11 mm, i.e. less than 10 % of the simulated maximum land subsidence, and seems too small to seriously damage infrastructure such as the subways (metro lines) in the center area of Shanghai. 相似文献
17.
Nguyen Cao Don Nguyen Thi Minh Hang Hiroyuki Araki Hiroyuki Yamanishi Kenichi Koga 《Environmental Geology》2006,49(4):601-609
A sinking of the land surface due to the pumping of groundwater has long been recognized as an environmental issue in the
Shiroishi plain of Saga, Japan. Land subsidence can have several negative economic and social implications such as changes
in groundwater and surface water flow patterns, restrictions on pumping in land subsidence prone areas, localized flooding,
failure of well casings as well as shearing of structures. To minimize such an environmental effect, groundwater management
should be considered in this area. In this study, a new integrated numerical model that integrates a three-dimensional numerical
groundwater flow model coupled with a one-dimensional soil consolidation model and a groundwater optimization model was developed
to simulate groundwater movement, to predict ground settlement and to search for optimal safe yield of groundwater without
violating physical, environmental and socio-economic constraints. It is found that groundwater levels in the aquifers greatly
vary from season to season in response to the varying climatic and pumping conditions. Consequently, land subsidence has occurred
rapidly throughout the area with the Shiroishi plain being the most prone. The predicted optimal safe yield of the pumping
amount is about 5 million m3. The study also suggests that pumping with this optimal amount will minimize the rate of land subsidence over the entire
area.
An erratum to this article can be found at 相似文献
18.
Monitoring land subsidence in Semarang,Indonesia 总被引:1,自引:0,他引:1
Semarang is one of the biggest cities in Indonesia and nowadays suffering from extended land subsidence, which is due to groundwater
withdrawal, to natural consolidation of alluvium soil and to the load of constructions. Land subsidence causes damages to
infrastructure, buildings, and results in tides moving into low-lying areas. Up to the present, there has been no comprehensive
information about the land subsidence and its monitoring in Semarang. This paper examines digital elevation model (DEM) and
benchmark data in Geographic Information System (GIS) raster operation for the monitoring of the land subsidence in Semarang.
This method will predict and quantify the extent of subsidence in future years. The future land subsidence prediction is generated
from the expected future DEM in GIS environment using ILWIS package. The procedure is useful especially in areas with scarce
data. The resulting maps designate the area of land subsidence that increases rapidly and it is predicted that in 2020, an
area of 27.5 ha will be situated 1.5–2.0 m below sea level. This calculation is based on the assumption that the rate of land
subsidence is linear and no action is taken to protect the area from subsidence. 相似文献