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滑坡变形预测一直是实现滑坡灾害预报与防控的有效手段。岩土体参数是开展滑坡变形计算的关键输入信息,然而目前研究鲜有考虑岩土体参数不确定性对滑坡变形的影响,如何融合有限监测数据实现岩土体参数不确定性定量表征及滑坡变形概率预测仍然是一大难点。以降雨入渗非饱和土坡为例,开展流固耦合分析,基于有限的孔压监测数据,利用DREAM＿zs算法实现对岩土体参数的高效概率反演。根据岩土体参数的先验分布,采用拉丁超立方抽样法生成随机样本,将其导入ABAQUS中计算相应的坡脚变形作为数据集,分别采用多元自适应回归样条曲线（MARS）和Light GBM模型构建基于数理-机制双驱动的边坡坡脚变形预测模型,计算贝叶斯更新后的后验稳态样本对应的边坡坡脚变形值,并对边坡变形值开展统计分析。结果表明：DREAM＿zs算法仅需少量的孔压监测数据,即可完成对岩土体参数的更新,并且计算效率高、收敛速度快。此外,提出的边坡坡脚变形预测模型不仅突破了由孔压等间接监测数据来预测边坡变形的局限,同时还实现了对边坡变形发生概率的预测,为滑坡变形预测提供了新的思路和探索。 相似文献
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降雨入渗滑坡稳定可靠度分析往往仅考虑了土体参数的空间变异性,而忽略土体初始含水率非均匀性空间分布的影响。基于此,推导了不同降雨工况条件下初始含水率任一分布的Green-Ampt入渗模型,利用变步长复化Simpson法求解初始含水率不同空间分布条件下湿润锋深度与降雨历时的函数关系。结合多维正态累计分布函数Mvncdf,计算整个降雨评估基准期滑坡稳定的时变可靠度,并利用某一滑坡实例进行对比验证。计算结果表明,初始含水率空间分布的不同对降雨条件下滑坡稳定时变可靠度的影响十分明显,且相较于初始含水率为均匀和梯形分布;相同降雨条件下,指数分布时滑坡稳定时变可靠度的下降幅度最小。该改进模型适用于土体初始含水率的任意分布,有利于Green-Ampt模型在滑坡稳定性评价的普适性推广应用。 相似文献
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准确可靠的径流预测对于水资源的科学管理与规划具有重要意义,特别是在水资源紧缺的干旱半干旱地区,径流预测对流域内水资源高效利用与水利工程经济运行具有重要现实意义。针对径流预测通常采用单一方法进行建模与预测,难以利用各预测模型优势的问题,本文利用极限学习机（ELM）模型、支持向量机（SVM）模型、多元自适应回归样条（MARS）等机器学习方法建立了疏勒河上游未来1~7日的径流预测模型。在此基础上,运用贝叶斯模型平均（BMA）方法对ELM、SVM、MARS模型的预测结果进行组合,构建了径流组合预测模型,以获取更可靠的预测结果,并采用蒙特卡洛抽样方法获取BMA的95%置信区间,对预测结果进行了不确定性分析。结果表明：ELM、SVM、MARS模型以及BMA组合模型均适用于干旱半干旱地区的中长期日径流预测;BMA的预测精度较单一模型更高,能够提供更准确的预测值;BMA的95%置信区间对实测值覆盖率高,同时能够提供较好的确定性预测和概率预测结果。表明BMA在资料有限的条件下,表现出较单一模型更高的预测性能,可以成为干旱半干旱地区中长期日径流预测的有效方法。 相似文献
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概率反分析是推断不确定土体参数统计特征的重要手段,可以使边坡可靠度评估更接近工程实际。然而目前的概率反分析很少使用多源信息（包括监测数据、观测信息和边坡服役记录）,因为这通常涉及数千个随机变量和高维似然函数的评估。因此融合多源信息对空间变异土体参数进行概率反分析进而预测降雨条件下的边坡可靠度是一项具有挑战性的难题。文章将改进的基于子集模拟的贝叶斯更新（mBUS）方法与自适应条件抽样（aCS）算法相结合,构建了空间变异土体参数概率反分析和边坡可靠度预测的框架,并以某一公路边坡为例验证了该框架的有效性。研究结果表明：通过融合多源信息所获得的土体参数后验统计特征与现场观测结果基本吻合;用更新后的土体参数预测得到2004年9月12日该边坡在暴雨工况下的失效概率为23.1%,符合实际边坡失稳情况,说明在此框架下可以充分利用多源信息解决高维概率反分析问题。 相似文献
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煤炭质量核心指标的估算有利于煤炭质量的管控,并为智能开采、分质开采提供科学依据。将克里金插值法引入到煤质指标估算模型的建立,利用差分进化算法求解其变差函数的模型参数;针对在差分进化过程中因"早熟"现象导致最优解被破坏的问题,在变异过程中设计可动态修正变异方向的缩放因子,提出修正变异方向的自适应差分进化算法(UMDE)来确定变差函数的模型参数,并用该方法对煤矿井下未开采区域的全水分进行克里金插值。通过交叉验证与对比实验,证明基于自适应差分克里金方法(UMDE-Kriging)构建的煤质指标估算模型较其他优化方案在估算精度上有显著提升。 相似文献
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在应用神经网络进行洪水预报时,因洪水系统随着河道上游来流、区间降雨、河床演变等因素的动态变化,其特性并不总是按照基本相同的规律变化,对这类系统的参数辨识,要求算法具有较强的实时跟踪能力,以适应模拟或预测洪水运动变化过程的要求。在BP神经网络模型的基础上,运用最小二乘递推算法,引入时变遗忘因子实时跟踪模型中时变参数的变化,建立了神经网络在非线性系统中动态系统输入、输出数据间的映射关系。计算实例表明:该法对参数的快速时变具有较快的跟踪能力和较高的辨识精度,是一种非常实用的水文实时预报方法。 相似文献
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为了减少洪水对生命和财产造成的危害,构建合适的洪水预报预警体系具有重要的现实意义。本文结合NWP输出的降尺度降雨构建了短期洪水预报体系。所提出的降尺度方法对NWP输出值进行了校正,以便在人工神经网络的校准阶段使用,然后,将降尺度降雨参数作为径流预报的超级水箱模型的输入值。根据预测提前期对模型不确定性进行量化,最终将预测结果整合到现有的洪水预警警报级别中。结果表明,基于神经网络降尺度降雨的洪水预报优于多元线性回归方法。尽管随着预测提前期的增加,模型不确定性呈增加趋势,但仍可以对长达18小时的提前期做出可靠预测。 相似文献
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针对自动送钻控制系统中存在的时变、时滞和非线性条件下难以实现准确控制的情况,提出了一种灰色预测控制算法,该控制算法在建模过程中对原始数据进行累加生成,而这样累加的结果可以大大弱化非线性干扰的影响.利用灰色预测改进模型,实行一步或多步预测,将预测误差与误差变化作为决策机构的输入,送给液压调速系统对绞车的绞车力进行控制,然后控制钻杆的下放速度从而达到恒钻压的目的.该算法自适应强,计算简单,适合于钻压控制系统中.仿真结果表明,该算法是有效的. 相似文献
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A key issue in assessment of rainfall-induced slope failure is a reliable evaluation of pore water pressure distribution and its variations during rainstorm, which in turn requires accurate estimation of soil hydraulic parameters. In this study, the uncertainties of soil hydraulic parameters and their effects on slope stability prediction are evaluated, within the Bayesian framework, using the field measured temporal pore-water pressure data. The probabilistic back analysis and parameter uncertainty estimation is conducted using the Markov Chain Monte Carlo simulation. A case study of a natural terrain site is presented to illustrate the proposed method. The 95% total uncertainty bounds for the calibration period are relatively narrow, indicating an overall good performance of the infiltration model for the calibration period. The posterior uncertainty bounds of slope safety factors are much narrower than the prior ones, implying that the reduction of uncertainty in soil hydraulic parameters significantly reduces the uncertainty of slope stability. 相似文献
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Lulu Zhang Fang Wu Yafei Zheng Lihong Chen Jie Zhang Xu Li 《Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards》2018,12(3):169-182
Multiple types of responses, such as displacements, ground water level, pore water pressures, water contents, etc., are usually measured in comprehensive monitoring programmes for rainfall-induced landslide prevention. In this study, a probabilistic calibration method for coupled hydro-mechanical modelling of slope stability is presented with integration of multiple types of measurements. A numerical example of a soil slope under rainfall infiltration is illustrated to compare the effects of single and multiple types of responses on parameter estimation and model calibration. The results show that the soil parameters can be estimated with less uncertainty and total uncertainty bounds are narrower with multiple types of responses than with a single type of response. Model calibration based on multiple types of responses can compromise different responses and hence the means and standard deviations of model error are the smallest. A feasible correlation coefficient between soil modulus and permeability can be obtained from model calibration with multiple types of responses and single type of response as long as the responses include displacement data. 相似文献
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Parameter estimation of SWAT and quantification of consequent confidence bands of model simulations 总被引：1，自引：0，他引：1
Soil and Water Assessment Tool (SWAT) is a river basin scale model widely used to study the impact of land management practices in large, complex watersheds. Even though model output uncertainties are generally recognized to affect watershed management decisions, those uncertainties are largely ignored in model applications. The uncertainties of SWAT simulations are quantified using various methods, but simultaneous attempt to calibrate a model so as to reduce the uncertainty are seldom done. This study aims to use an uncertainty reduction procedure that helps calibrate the SWAT model. The shuffled complex evolutionary metropolis algorithm for uncertainty analysis is employed for this purpose, and is demonstrated using the data from the St. Joseph River basin, USA. The values of the performance indices, the r2 and the Nash–Sutcliffe efficiency (NSE) for the simulations during calibration period was found to be 0.81 (same for r2 and NSE) and 0.79 for validation period indicating a good simulation by the model. The results also indicate that the algorithm helps reduce the uncertainty (percentage of coverage?=?62% and average width?=?19.2 m3/s), and also identifies the plausible range of parameters that simulate the processes with less uncertainty. The confidence bands of simulations are obtained that can be employed in making uncertainty-based decisions on watershed management practices. 相似文献
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Nuraddeen Muhammad Babangida Muhammad Raza Ul Mustafa Khamaruzaman Wan Yusuf Mohamed Hasnain Isa 《Hydrogeology Journal》2016,24(7):1821-1833
Nonlinear complex behavior of pore-water pressure responses to rainfall was modelled using support vector regression (SVR). Pore-water pressure can rise to disturbing levels that may result in slope failure during or after rainfall. Traditionally, monitoring slope pore-water pressure responses to rainfall is tedious and expensive, in that the slope must be instrumented with necessary monitors. Data on rainfall and corresponding responses of pore-water pressure were collected from such a monitoring program at a slope site in Malaysia and used to develop SVR models to predict pore-water pressure fluctuations. Three models, based on their different input configurations, were developed. SVR optimum meta-parameters were obtained using k-fold cross validation and a grid search. Model type 3 was adjudged the best among the models and was used to predict three other points on the slope. For each point, lag intervals of 30 min, 1 h and 2 h were used to make the predictions. The SVR model predictions were compared with predictions made by an artificial neural network model; overall, the SVR model showed slightly better results. Uncertainty quantification analysis was also performed for further model assessment. The uncertainty components were found to be low and tolerable, with d-factor of 0.14 and 74 % of observed data falling within the 95 % confidence bound. The study demonstrated that the SVR model is effective in providing an accurate and quick means of obtaining pore-water pressure response, which may be vital in systems where response information is urgently needed. 相似文献
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为了开展寒旱山区典型流域融雪径流过程的研究,提高融雪径流模型（SRM）在山区融雪地区的水文过程模拟精度,本文选取新疆提孜那甫河流域作为典型研究区,在SRM径流计算基础上,加入合适的基流数据并进行不确定性分析。考虑4种常见的基流分割方法（数字滤波法、加里宁法、BFI法（滑动最小值法）和HYSEP（hydrograph separation program）法）,基于贝叶斯理论,采用马尔科夫链蒙特卡洛（MCMC）模拟进行参数不确定性分析,对使用不同基流数据SRM的融雪径流模拟表现进行综合评价。分析结果表明,基于加里宁基流分割方法的模型（SRMK）能够最佳地模拟研究区融雪径流过程（纳什系数NSE在识别期和验证期分别为0.866和0.721,大于其他对比模型）。MCMC模拟能够较好地识别SRM参数,获得可靠的参数后验概率分布。当实测降水资料缺乏或其代表性较差时,TRMM（tropical rainfall measuring mission）卫星数据能够描述研究区的降水过程特征。 相似文献
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E.C. Gaucher C. Tournassat F.J. Pearson C. Crouzet S. Altmann 《Geochimica et cosmochimica acta》2009,73(21):6470-6487
The chemistry of pore water is an important property of clayrocks being considered as host rocks for long-term storage of radioactive waste. It may be difficult, if not impossible, to obtain water samples for chemical analysis from such rocks because of their low hydraulic conductivity. This paper presents an approach for calculating the pore-water compositions of clayrocks from laboratory-measured properties of core samples, including their leachable Cl and SO4 concentrations and analysed exchangeable cations, and from mineral and cation exchange equilibria based on the formation mineralogy. New core sampling and analysis procedures are presented that reduce or quantify side reactions such as sample oxidation (e.g. pyrite) and soluble mineral dissolution (celestite, SrSO4) that affect measured SO4 concentrations and exchangeable cation distributions. The model considers phase equilibria only with minerals that are observed in the formation including the principal clay phases. The model has been used to calculate the composition of mobile pore water in the Callovo-Oxfordian clayrock and validated against measurements of water chemistry made in an underground research laboratory in that formation. The model reproduces the measured, in situ pore-water composition without any estimated parameters. All required parameters can be obtained from core sample analysis. We highlight the need to consider only those mineral phases which can be shown to be in equilibrium with contacting pore water. The consequence of this is that some conceptual models available in the literature appear not to be appropriate for modelling clayrocks, particularly those considering high temperature and/or high pressure detrital phases as chemical buffers of pore water. The robustness of our model with respect to uncertainties in the log K values of clay phases is also demonstrated. Large uncertainties in log K values for clay minerals have relatively small effects on modelled pore-water compositions. 相似文献
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Abderraouf El Ouazzani Taibi Amro Elfeki Guoping Zhang 《Arabian Journal of Geosciences》2011,4(5-6):1005-1018
The research presented in this paper focuses on the application of a newly developed physically based watershed modeling approach, which is called representative elementary watershed approach. The study stressed the effects of uncertainty of input parameters on the watershed responses (i.e., simulated discharges). The approach was applied to the Zwalm catchment, which is an agriculture-dominated watershed with a drainage area of 114 km2 located in East Flanders, Belgium. Uncertainty analysis of the model parameters is limited to the saturated hydraulic conductivity because of its high influence on the watershed hydrologic behavior and availability of the data. The assessment of output uncertainty is performed using the Monte Carlo method. The ensemble statistical watershed responses and their uncertainties are calculated and compared with measurements. The results show that the measured discharges fall within the 95% confidence interval of the modeled discharge. This provides the uncertainty bounds of the discharges that account for the uncertainty in saturated hydraulic conductivity. The methodology can be extended to address other uncertain parameters as far as the probability density function of the parameter is defined. 相似文献
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尾矿料的动力特性试验研究 总被引：10，自引：0，他引：10
通过对某铜矿的尾矿料进行动三轴和共振柱试验,研究了尾矿材料动力变形特性,提出了简单实用的孔隙水压力模型,给出了能更加准确地预测尾矿材料的动孔隙水压力的公式,并将其与Seed提出的预测公式进行了比较。在不同密度尾矿料的动三轴试验基础上,分析了相对密度对液化特性的影响,得出了相对密度小于70 %时抗液化强度随相对密度的增加而明显增加的结论。在不同围压下进行动三轴试验,结果表明：在相同的液化振次条件下,围压越高,动剪应力比越低。由共振柱试验可知,尾矿料的阻尼比随着动剪应变幅的增大而增大,而动剪模量随动剪应变幅的增大而减小,动剪模量和阻尼比与动剪应变幅的关系受围压影响不太敏感。 相似文献
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Xiaoli Li Zhiqiang Li Jiansi Yang Yaohui Liu Bo Fu Wenhua Qi Xiwei Fan 《Natural Hazards》2018,90(2):843-861
The present study analyzes the runoff response during extreme rain events over the basin of Subarnarekha River in India using soil and water assessment tool (SWAT). The SWAT model is configured for the Subarnarekha River basin with 32 sub-basins. Three gauging stations in the basin (viz., Adityapur, Jamshedpur and Ghatshila) were selected to assess the model performance. Daily stream flow data are taken from Central Water Commission, India—Water Resources Information System. Calibration and validation of the model were performed using the soil and water assessment tool-calibration uncertainty programs (SWAT-CUPs) with sequential uncertainty fitting (SUFI-2) algorithm. The model was run for the period from 1982 to 2011 with a calibration period from 1982 to 1997 and a validation period from 1998 to 2011. The sensitivity of basin parameters has been analyzed in order to improve the runoff simulation efficiency of the model. The study concluded that the model performed well in Ghatshila gauging station with a Nash–Sutcliffe efficiency (NSE) of 0.68 during calibration and 0.62 during validation at daily scale. The model, thus calibrated and validated, was then applied to evaluate the extreme monsoon rain events in recent years. Five extreme events were identified in Jamshedpur and Ghatshila sub-basins of Subarnarekha River basin. The simulation results were found to be good for the extreme events with the NSE of 0.89 at Jamshedpur and 0.96 at Ghatshila gauging stations. The findings of this study can be useful in runoff simulation and flood forecasting for extreme rainfall events in Subarnarekha River basin. 相似文献
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以淮河小柳巷水文站以上各支流组成的流域为研究对象,应用ESSI分布式水文模型对流域出口的年、月、日径流以及流域水文空间过程进行模拟以验证模型的适用性和模拟精度。选取合理的模型运行方案组合,以2001~2004年作为模型校准期,率定出模型参数,并用2006~2009年的实测水文数据进行模型验证。结果表明ESSI模型率定得到的参数在研究区具有一定的代表性,较为准确地概化描述了研究区的水文过程,在淮河流域中上游具有良好的适用性;此外,模拟的水文空间过程与淮河流域的客观规律相近,表明ESSI模型对各水文过程具有合理的描述和表达,为水资源的时空动态变化规律研究提供良好的模拟平台。 相似文献