共查询到19条相似文献,搜索用时 359 毫秒
1.
水位波动诱发岩溶塌陷的概率分析 总被引:8,自引:8,他引:0
水位波动诱发岩溶塌陷的概率问题可以简化为波动幅度、波动频率和波动时间3个随机变量的极值分布问题。随机变量的极值分布可以通过对水位监测数据进行频谱分析获得。桂林市柘木村水位波动诱发岩溶塌陷概率分析的结果表明: 柘木村2000年水位波动诱发岩溶塌陷的概率为7. 38% , 2001年为1. 47% , 2002年为16. 4%。分析结果与实际情况也比较吻合, 2002年6月柘木村一老塌陷复活,而2000和2001年则未发生塌陷,仅有部分土层发生扰动。因此可以用概率分析来判别某一时段内由水位波动而诱发岩溶塌陷的危险性大小,以便于分时段进行重点防治。 相似文献
2.
3.
岩溶塌陷灾害监测预报技术与方法初步研究--以桂林市柘木村岩溶塌陷监测为例 总被引:5,自引:1,他引:5
我国可溶岩分布面积达365万km2,占国土面积的1/3以上,是世界上岩溶最发育的国家之一.近年来,随着岩溶区城市化建设的飞速发展,岩溶区土地资源、水资源和矿产资源开发的不断增强,由此而引发的岩溶塌陷问题日益突出,已成为岩溶区城市主要地质灾害,严重妨碍城市经济建设与发展.由于岩溶塌陷的产生在时间上具突发性,在空间上具隐蔽性,在机制上具复杂性.因此,被普遍认为难以采取地面常规监测手段,对塌陷进行监测预报.另一方面,试验研究表明,岩溶水气压力变化对塌陷具有触发作用,可以以此作为衡量塌陷发育的临界条件.这就意味着通过对岩溶管道系统的水(气)压力的动态变化进行观测,可以达到对塌陷进行预报的目的.论文以位于广西桂林柘木村的岩溶塌陷监测站为例,详细讨论这一技术方法. 相似文献
4.
5.
受武广客运专线金沙洲隧道施工抽排大量地下水的影响, 2007—2012年广州金沙洲发生了大规模岩溶地面塌陷、地面沉降地质灾害,造成了重大经济损失。为防治地质灾害,采用综合地质调查、地下水位监测、地面沉降监测、物探、钻探和试验等手段勘查和研究,建立了完善的地下水位和地面沉降监测网络。在此基础上,根据地质环境条件、岩溶发育程度和地质灾害分布特征进行岩溶塌陷易发性分区,选择地下水位变化量和地面沉降量这两个与岩溶塌陷最直接、最敏感和最重要的参数,从预警预报参数选择、时间尺度选取、判据分析计算、预警预报方法、模型系统的建立等方面进行研究,选取临界日综合地下水位变化量和临界日综合地面沉降量作为预警预报判据,结合三维地质结构模型建立岩溶塌陷预警预报模型系统。成功地预警预报了两起岩溶地面塌陷,取得较好的预报效果,说明该岩溶地面塌陷预警预报模型系统实用、有效,为金沙洲防灾减灾提供地质科学依据,为当地的社会稳定和经济可持续发展提供技术支撑。 相似文献
6.
7.
基于Verhulst模型的滑坡位移预测研究及其程序化实现 总被引:1,自引:1,他引:0
以甘肃省黄茨滑坡位移时间预测为例,在滑坡工程地质条件、成因、发生与发展过程分析的基础上,结合地面监测桩以及位移计监测的位移时间数据,运用Verhulst预测模型建立了该滑坡位移预测研究的思路.在此基础上,运用Ex-cel内嵌的VBA语言编写了相应的位移时间预测预报程序,解决了笔算困难问题.通过具体实例分析,将Verhulst模型、灰色GM(1,1)模型预测结果与实际监测结果进行对比分析,验证了该模型在滑坡位移时间预测中的适用性以及程序的可靠性.研究结果表明,Verhulst预测模型适宜于滑坡临滑预报,而灰色GM(1,1)预测模型适宜于滑坡中短期预测预报,通过Ver-hulst模型预测黄茨滑坡的临滑时间在1995-01-26至1995-01-27之间,预测结果与滑坡实际滑动时间较为一致,由此说明运用Verhulst预测模型对滑坡进行临滑预报是可行的. 相似文献
8.
矿区岩溶地表塌陷神经网络预测研究 总被引:3,自引:0,他引:3
针对近年来某矿岩溶地表塌陷频繁发生的现象,分析确定了影响地表塌陷的主要因素,构建了矿区岩溶地表塌陷预测BP神经网络模型,以训练后的BP网络模型对矿山帷幕注浆三期工程完成后可能形成的地表塌陷区的空间分布进行预测。并针对矿山现实塌陷情况,结合各区预测塌陷危险分级结果,提出了相应的岩溶地表塌陷灾害防治措施。实践表明,所建模型的预测结果与矿区地表塌陷实际情况相符,可为矿山后续帷幕注浆工程的设计与施工提供有益借鉴,为岩溶矿区地表塌陷灾害提供预警支持。 相似文献
9.
为了研究岩溶地区的岩溶塌陷预测问题,根据大量岩溶塌陷实例确定6项岩溶地区典型的影响因子(岩性系数(RQC)、岩体结构系数(RMSC)、地下水系数(GWC)、覆盖层系数(SSC)、地形地貌系数(LPC)、环境条件系数(ECC)),采用熵权法计算各项影响因子的权重并结合云理论建立熵权正态云模型。通过模型对桂林西城区岩溶塌陷进行预测且结合实际塌陷情况进行比较分析,结果证明建立的熵权正态云模型的预测结果与实际结果比较接近。表明该模型对于岩溶塌陷的预测分析方面具有良好的适用性和可靠性,且能够为岩溶发育地区岩溶塌陷的非线性、复杂性预测判断提供一种新的思路和方法。 相似文献
10.
山东泰安岩溶地面塌陷前兆及其预测预报 总被引:16,自引:0,他引:16
1 引言。2003年5月31日凌晨4时,山东省泰安市泰山区东羊娄村东北800m处,产生巨大的岩溶地面塌陷:在即将成熟的麦田中出现一椭圆型塌陷坑,长轴近东西向,长35m;短轴近南北向,长27m,深23m(由地面到岩溶水面)(图1)。塌陷发生时出现惊雷般的轰鸣声。作者6月4日下午6时在现场目睹了塌陷四壁仍在坍塌,并发出雷鸣般的声音。本文试图通过一些现象,总结进行岩溶地面塌陷预测预报的原理及基本方法。 相似文献
11.
New grey prediction model and its application in forecasting land subsidence in coal mine 总被引:2,自引:1,他引:1
Mining subsidence destroys environment seriously and is difficult to forecast because the parameters in prediction model are difficult to obtain. As there are many uncertainties in mining subsidence, we forecast it by grey prediction model. Traditional GM (1,1) model predict for a time series. In this paper, the panel data are studied and are viewed as a sequence in which elements are matrix based on cross-sectional data, and the mean sequence of row vector GM (1,1) model, mean sequence of column vector GM (1,1) model and the cell volume sequence GM (1,1) model are established, respectively. Combining these grey models, we build prediction model of cross-sectional data matrix sequence. Thus, the scope of grey prediction has been expanded, and grey forecasting theory has been enriched. Using the newly built predictive models, we study the land deformation due to mining of Pingdingshan coal mine in Henan Province. Practical verification and model accuracy test show that the grey model can make accurate predictions, with a good agreement between the predictive value and actual value. It can provide effective and accurate information and also can provide an important reference for the reclamation planning of surface environment. 相似文献
12.
为了建立一个适合于三峡库区的塌岸预测方法体系,采用具有处理非线性关系功能的人工神经网络方法对水库塌岸问题进行研究。通过训练、学习和仿真,获得预测正确率为97.2%的具有7-32-14网络结构的BP神经网络模型,采用该模型对蓄水位为175 m时丰都县各岸段进行塌岸预测,并将预测结果与传统经验公式计算法所得结果及实际监测数据进行对比。结果表明:基于人工神经网络的塌岸预测宽度与实际监测数据很接近,偏差在5 m以内;公式法计算结果与监测值平均偏差为15.9 m,而且对于部分坡段,公式法计算结果比实际监测值小8~11 m,没能预测出塌岸的真正范围。采用神经网络模型对丰都县水库进行塌岸预测,预测结果与实际监测数据平均偏差约3.8%,表明其预测结果可靠。 相似文献
13.
14.
15.
A new model has been developed for track prediction of Indian Ocean cyclones. The model utilizes environmental steering flow using the forecasts from a high-resolution global model and the effect due to earth??s rotation (the beta-effect) to determine the future movement of cyclone. A new approach based on vertical profile of potential vorticity is used to determine weights for different vertical levels for computation of mean steering current. Despite the fact that the model is based on the dynamical framework, the operational cost and time for running the model is only a fraction of what is needed by a normal numerical weather prediction model. This new approach will enhance flexibility in defining the initial position of the cyclone in the model, and also, it is possible to create a large ensemble of predicted tracks to assess the impact of the uncertainty of initial cyclone position on the predicted tracks. The performance of the model for ten cyclones, viz. GONU (02?C08 Jun, 2007), SIDR (11?C16 November, 2007), NARGIS (27 Apr?C04 May, 2008), RASHMI (25?C27 October, 2008) KHAI-MUK (14?C16 November, 2008), NISHA (25?C27 November, 2008), SEVEN (04?C08 December, 2008), BIJLI (14?C18 April, 2009), AILA (23?C26 May, 2009), and PHYAN (09?C11 November, 2009), have been tested in the present study. The forecast errors of the present model have been computed with respect to the Joint Typhoon Warning Center best track analysis positions. The forecast skill improvement (mean of ten cyclones) of the model with respect to the Climatology and Persistence (CLIPER) statistical model varies from 7 to 67?% between 12 and 72?h. 相似文献
16.
17.
T. S. V. Vijaya Kumar J. Sanjay B. K. Basu A. K. Mitra D. V. Bhaskar Rao O. P. Sharma P. K. Pal T. N. Krishnamurti 《Natural Hazards》2007,41(3):471-485
This study entails the implementation of an experimental real time forecast capability for tropical cyclones over the Bay
of Bengal basin of North Indian Ocean. This work is being built on the experience gained from a number of recent studies using
the concept of superensemble developed at the Florida State University (FSU). Real time hurricane forecasts are one of the
major components of superensemble modeling at FSU. The superensemble approach of training followed by real time forecasts
produces the best forecasts for tracks and intensity (up to 5 days) of Atlantic hurricanes and Pacific typhoons. Improvements
in track forecasts of about 25–35% compared to current operational forecast models has been noted over the Atlantic Ocean
basin. The intensity forecasts for hurricanes are only marginally better than the best models. In this paper, we address tropical
cyclone forecasts over the Bay of Bengal for the years 1996–2000. The main result from this study is that the position and
intensity errors for tropical cyclone forecasts over the Bay of Bengal from the multimodel superensemble are generally less
than those of all of the participating models during 1- to 3-day forecasts. Some of the major tropical cyclones, such as the
November 1996 Andhra Pradesh cyclone and October 1999 Orissa super cyclone were well handled by this superensemble approach.
A conclusion from this study is that the proposed approach may be a viable way to construct improved forecasts of Bay of Bengal
tropical cyclone positions and intensity. 相似文献
18.
基于无偏灰色马尔可夫链的吉林省降水量预测 总被引:1,自引:0,他引:1
为了更准确地对吉林省降水量进行预测,分析其时空变化特征,应用无偏灰色马尔可夫链模型对8个具有代表性的雨量站进行降水量预测,并根据预报结果讨论历史数据波动性与预报精度的关系。其中:83%以上预测结果合格,白城、乾安、长春、蛟河、四平、通化6个地区降水量多年呈递减趋势,减幅分别为0.23%、0.09%、0.24%、1.01%、0.51%、0.54%;延吉、靖宇2个地区降水量多年呈递增趋势,增幅分别为2.60%、0.54%。结果表明:无偏灰色马尔可夫链模型预测精度较高,说明该方法适用于吉林省的降水量预测;吉林省中西部地区降水量呈递减趋势,东部地区呈递增趋势,但变幅不大;在波动性与预报精度的关系方面,时间序列的波动性越大预测所产生的误差越大。 相似文献