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基于EWT-Prophet方法的地表沉降预测

针对地表沉降预测研究中单一传统方法预测精度较低、预测过程不稳定等问题,提出一种经验小波变换(EWT)与Prophet预测模型相结合的优化预测方法.以江西省上饶市德兴矿区为例,采用30景哨兵1号影像进行SBAS-InSAR沉降研究,并获取该区域研究时段内的沉降时序数据.首先对原始沉降时序数据进行EWT自适应分解,分解产生...     

上海地区地面沉降原因分析

以上海中心城区为实验区，利用层次分析法对影响地面沉降因素的权重进行了综合分析 ；同时对地下水与地面沉降进行了拟合相关分析，进一步验证了地面沉降量与地下水抽取速度相关。     

Comprehensive analysis and artificial intelligent simulation of land subsidence of Beijing, China

Mechanism and modeling of the land subsidence are complex because of the complicate geological background in Beijing, China. This paper analyzed the spatial relationship between land subsidence and three factors, including the change of groundwater level, the thickness of compressible sediments and the building area by using remote sensing and GIS tools in the upper-middle part of alluvial-proluvial plain fan of the Chaobai River in Beijing. Based on the spatial analysis of the land subsidence and three factors, there exist significant non-linear relationship between the vertical displacement and three factors. The Back Propagation Neural Network (BPN) model combined with Genetic Algorithm (GA) was used to simulate regional distribution of the land subsidence. Results showed that at field scale, the groundwater level and land subsidence showed a significant linear relationship. However, at regional scale, the spatial distribution of groundwater depletion funnel did not overlap with the land subsidence funnel. As to the factor of compressible strata, the places with the biggest compressible strata thickness did not have the largest vertical displacement. The distributions of building area and land subsidence have no obvious spatial relationships. The BPN-GA model simulation results illustrated that the accuracy of the trained model during fifty years is acceptable with an error of 51% of verification data less than 20 mm and the average of the absolute error about 32 mm. The BPN model could be utilized to simulate the general distribution of land subsidence in the study area. Overall, this work contributes to better understand the complex relationship between the land subsidence and three influencing factors. And the distribution of the land subsidence can be simulated by the trained BPN-GA model with the limited available dada and acceptable accuracy.     

山东省黄河北煤炭矿区地表沉陷预测与综合治理研究

黄河北煤炭矿区为鲁西煤炭基地最后一块整装后备资源,阳谷茌平煤田和黄河北煤田其开发建设具有重要的意义。该文采用实际观测资料利用回归分析法获得的岩移参数,对山东省黄河北矿区内上组煤开采后引起的地表沉陷进行了预测,预测结果表明:地表沉陷总面积达到3 724.5 km~2,最大下沉深度为5 455 mm;其中,阳谷茌平煤田最大下沉深度为5 455 mm,地表沉陷面积为1 188.0 km~2;黄河北煤田最大下沉深度为2 976 mm,地表沉陷面积为2 536.5 km~2。地表沉陷预测结果与多年水位观测数据进行对照,煤炭开采会造成1 091.5 km~2季节性积水区和62.3km~2的常年积水区。地表沉陷对地面、地物产生不同的影响和危害,其中对农业的影响最大。地表沉陷形成的塌陷裂缝、不同坡度耕地、大型塌陷坑等可分别采取黄土填堵、大型设备平整、退耕还林、煤矸石充填、修复为鱼塘等治理措施。该文对下一步黄河北矿区开发过程中,相关政府部门采取的规划控制措施提出了建议。     

江苏沿江开发带地下水开采与地面沉降三维数值模拟

根据江苏沿江开发带地下水系统的水文地质机制以及地面沉降机理,在概化出江苏沿江开发带的地下水系统水文地质概念模型和地面沉降模型的基础上,建立了江苏沿江开发带地下水开采与地面沉降三维数值模型。并针对各种开采方案下地面累积沉降量最少的原则,给出了各含水层的最优开采方案。     

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矿区地表沉降监测的一种组合模型预测方法

基于诱导有序加权平均（IOWA）算子,将差分整合移动平均自回归（ARIMA）模型和Holt-Winters指数平滑模型进行组合,采用SBAS-InSAR监测值进行矿区地表沉降预测,并与各单一模型的预测结果进行对比分析。结果表明,基于IOWA算子的组合模型的预测精度较单一模型有明显提升,其中各点均方误差（MSE）平均值为1.458 mm,平均绝对误差（MAE）为2.175 mm,可用于矿山地表沉降监测预测。     

Spatial-temporal characteristics of land subsidence corresponding to dynamic groundwater funnel in Beijing Municipality,China

Due to long-term over-exploitation of groundwater in Beijing Municipality,regional groundwater funnels have formed and land subsidence has been induced.By combining a groundwater monitoring network,GPS monitor-ing network data,radar satellite SAR data,GIS and other new technologies,a coupled process model based on the dy-namic variation of groundwater and the deformation response of land subsidence has been established.The dynamic variation of groundwater funnels and the land subsidence response process were analyzed systematically in Beijing.Study results indicate that current groundwater funnel areas are distributed mainly in the southwest of Shunyi District,the northeast of Chaoyang District and the northwest of Tongzhou District,with an average decline rate of groundwa-ter level of 2.66 m/yr and a maximum of 3.82 m/yr in the center of the funnels.Seasonal and interannual differences exist in the response model of land subsidence to groundwater funnels with uneven spatial and temporal distribution,where the maximum land subsidence rate was about-41.08 mm/yr and the area with a subsidence rate greater than 30 mm/yr was about 1637.29 km2.Although a consistency was revealed to exist between a groundwater funnel and the spatial distribution characteristics of the corresponding land subsidence funnel,this consistency was not perfect.The results showed that the response model of land subsidence to the dynamic variation of groundwater was more revealing when combining conventional technologies with InSAR,GIS,GPS,providing a new strategy for environmental and hydrogeological research and a scientific basis for regional land subsidence control.     

基于InSAR的矿区沉降中心动态变化监测与分析

以安徽省颍上县谢桥煤矿为例,采用InSAR技术探测矿区2007~2011年内各时间段的地表形变结果,利用岩床模型模拟矿区的形变场,分析沉降漏斗的发育状态,为区域地面沉降危险性评估提供重要参考依据。InSAR形变结果显示,开采区域内存在多处沉降漏斗,大体呈东西向分布;随着时间的推移,沉降中心不断推移,沉降范围逐渐扩大。结合遥感影像发现,沉降漏斗与塌陷水域的形成在时间上存在一致性,空间分布也存在高度相关性。     

东营市地面沉降模型的构建与应用

东营市是山东省内重要的沿海经济开发区,近年来地面沉降灾害制约了东营市的经济社会发展。构建三维地面沉降模型可以实现东营市地面沉降监测资料的信息化、可视化。根据东营市地质条件及矿产资源赋存层位,将三维地质结构模型的标准分层分为13层;而后收集了东营地区深钻540个,深度均在2 000 m及以上,其中有82个能够达到4 000~5 000 m甚至更大深度,按照标准分层,对所有钻孔进行标准化处理,并进一步利用Mapgis K9软件建立了三维地质结构模型,首次实现了以矿产资源层位划分为依据的大深度的东营市三维可视化地质结构模型模拟分析。同时,结合东营市19座地面沉降监测站数据,构建了地面沉降模型,首次实现了地面沉降的动态预演及监测,为东营市地面沉降评估与防治提供了科学依据。