野外非饱和土壤水流运动速度的空间变异性及其对溶质运移的影响

根据野外非饱和溶质运移试验资料,分析了港质运移速度的空间变异性,求得了呈对数正态分布的流速分布函数,并依此推导出有效弥散系数α=0.068t.根据流速的随机分布特征,分别用带有随机参数的对流模型、对流一弥散模型和传统的对流-弥散模型,求得了区域平均浓度分布及其方差.计算结果与实测结果拟合良好.通过分析得到,浓度方差与浓度梯度成正比,与孔隙弥散系数成反比,方差最大值分布在浓度锋面附近.     

基于随机理论的地下水环境风险评价

针对确定性模型难以描述含水层非均质空间分布的问题,提出基于随机理论的地下水环境风险评价方法。以矩形场地地下水污染风险评价为例,采用蒙特卡罗法生成大量渗透系数随机场,模拟含水层参数各种可能的非均质空间分布,在此基础上建立场地地下水流模型与溶质运移模型,分别计算污染物在地下水中的迁移转化情况。统计大量随机模拟中污染事故发生的频率,当模拟次数足够多时,污染频率收敛于污染概率,污染风险即通过污染概率体现出来。该方法将模型参数设为满足一定分布特征的随机变量,避免了确定性方法得出的武断的评价结果,可为工厂的选址、水源地的选址等工作提供科学指导。     

机器学习在地下水环境背景值与污染风险评价的应用和展望

地下水资源在世界各国水资源中占有举足轻重的地位,对人类生存发展、维系生态系统健康发挥着重要作用。现阶段地下水污染日益严重,地下水环境背景值研究和污染风险评价对地下水污染防治工作具有重要意义。由于地下水污染影响因素复杂,地下水化学组分空间分布的非均质性、地下水样品采集的小样本问题与大尺度区域的高计算代价,都对传统的污染风险评价方法构成了极大挑战。机器学习作为人工智能的核心,已成为水文地质领域研究的前沿热点,通过智能高效的数据处理和挖掘,在地下水化学组分的分布、变化以及赋存机制等方向已得到探索和尝试。本文全面介绍了近年来在地下水污染研究方面应用的机器学习方法,涵盖了以聚类为主的非监督学习算法,以回归为主的监督学习算法,以提升算法效率为目标的混合算法,以及以神经网络为核心的深度结构算法,展示了不同类型算法在地下水污染研究方面的成果,详细归纳了各种算法的机理,对算法的技术优劣及适用方向进行了探讨;最后对机器学习在地下水污染方面的应用发展趋势进行了展望,建议探索高效集成学习模型,以弥补单一算法的不足,同时发展面向小样本的深度学习建模技术,提高地下水污染评价精度,拓展和丰富新方法新技术在地下水污染研究方面的应用。     

基于多元回归分析的铬污染地下水风险评价方法

土-水分配系数（K_d）是表征重金属污染物在土壤包气带中迁移能力的重要参数,受污染物质量浓度、pH值、有机质质量分数、铁铝氧化物质量分数等多种因素影响。本文通过实验研究了分配系数与各种影响因素之间的关系,基于多元回归分析方法得到了分配系数与影响因素的关系方程;并以分配系数、泄漏量、土壤孔隙度、初始含水率为风险因子建立了地下水污染风险评价方法。以某工厂铬废液的泄露为案例,采用构建的方法进行地下水污染风险评价。结果表明：该处地下水被污染的风险等级为中等。地下水污染风险评价方法的建立为重金属污染地下水的监测管理提供了一种有效方法。     

白于山以北潜水含水层野外弥散试验研究

建立地下水溶质运移模型,对地下水中污染因子的运移扩散情况进行预测,是对地下水进行保护和对地下水污染进行控制的关键。地下水溶质运移模型中弥散参数对模型预测结果的精度和准确性有着至关重要的作用。对陕北白于山以北地区潜水含水层污染水体的运移规律进行分析,采用径向收敛流水动力弥散理论方法进行潜水含水层的弥散试验,计算场地潜水含水层的弥散参数。研究结果表明:计算得到的纵向弥散度(a_L)为0.58 cm,横向弥散度(aT)经验推断值为0.116 cm。研究结果可为该地区进一步建立地下水溶质运移模型和制订有效的地下水污染防治措施提供数据参考。     

弥散试验在罗河铁矿变更建设项目地下水水质污染范围预测中的应用

罗河铁矿变更建设工程在项目建设、生产运行和服务期满后的各个过程中,可能造成地下水水质污染。野外弥散试验用于研究污染物在地下水中运移时其浓度的变化规律,并通过试验获得进行地下水质量定量评价的弥散参数,从而计算出特定时间内地下水水质污染的范围。     

西宁市贵德县河滨公园林场第四系含水层弥散试验研究

地下水污染问题日益严重,研究溶质运移的弥散理论开始应用于实际问题。建立地下水溶质运移模型,对地下水中污染物的运移及发展趋势进行准确预测,是对地下水进行保护、对地下水污染进行控制的基础。而弥散参数的确定则是地下水溶质运移模型建立的关键环节之一,直接影响着模型预测结果的精度和准确性。 对西宁市贵德县地下水污染的水质运移规律进行分析,在贵德县河滨公园林场采用径向收敛流水动力弥散理论方法进行了第四系含水层现场弥散试验,计算了试验场地潜水含水层的弥散度,获得纵向弥散度(a_L)为0.843~0.998 cm,横向弥散度(a_T)经验推断值为0.17~0.20 cm,为进一步建立该地区的地下水溶质运移模型、预测地下水污染的发展趋势和评价该地区地下水环境质量提供了数据参考。     

污染场地六价铬迁移转化机制与数值模拟研究

随着全球工业化迅猛发展,土壤和地下水六价铬污染日益严重。基于某铁合金厂铬渣场地现场调查与采样分析,开展铬渣场地土样吸附、渗透和弥散试验,研究六价铬在粉质黏土土样中的吸附特性和迁移规律,建立考虑对流-弥散-吸附的六价铬迁移三维动力学模型,结合数值软件获取污染源位于场地上、下游时地下水中六价铬迁移分布特征,并揭示弥散度?和分配系数 对六价铬时空分布的影响。试验结果表明,粉质黏土对六价铬吸附符合Langmuir等温吸附模型,最大吸附量为466.6 mg/kg;蒸馏水和160 mg/L 六价铬溶液入渗下粉质黏土渗透系数约为6.5×10–7～6.7×10–7 cm/s,1 000 mg/L六价铬溶液的渗透系数增大至4.4×10–6 cm/s;粉质黏土水动力弥散系数D为1.4×10–4 m2/d,计算得到阻滞因子 为4.2～10。数值模拟结果表明,场地下游受到六价铬污染时,即使不考虑分子扩散作用,上游仍有被污染的风险,污染程度取决于含水层的弥散度;考虑含水层对六价铬吸附时,土体分配系数越大,六价铬污染羽分布范围越小,在预测地下水中六价铬浓度分布时应重点考虑六价铬吸附等转化过程。     

有限单元法地下水水质模型的微型机求解

近几年,我们在山东济宁地区开展了区域的溶质运移问题的试验研究工作。本文根据已建立的济宁地区的二维地下水水质模型,利用有限元法的水质预测的微型机(VICTOR-9000)程序,处理了该区东南角面积为3.7平方公里的计算区的实际资料,选定铬为污染物质,在微型机上模拟计算了地下水铬浓度,计算结果基本达到精度标准,计算的铬浓度分布基本上符合实际铬浓度的变化趋势。并在微机上优选确定了计算区的弥散参数——弥散度,这将为该区地下水污染的预测和控制提供了可靠的依据。     

纵向弥散作用与渗透介质非均质性定量关系的模拟研究

在地下水污染模拟预报中,弥散参数是很难确定的一个模型参数。因实验室小尺度弥散规律一般不能用于大尺度弥散过程,而野外示踪试验却耗资大、周期长,限制了其实用性。文中利用随机数值模拟手段、基于随机理论的蒙特卡罗方法及序贯高斯模拟技术来生成渗透系数随机场,并研究渗透系数对数场的方差、相关长度以及变异函数类型在不同尺度上对纵向弥散度的影响,进而建立纵向弥散度与随机分布渗透系数场的方差和相关长度的统计定量关系,并与Gelhar理论计算结果进行比较。数值模拟结果表明,经过一定迁移距离后纵向弥散度与随机分布渗透系数对数场的方差和相关长度具有良好的线性统计关系,与Gelhar理论公式表达的关系类型类似。但对于较大的方差,纵向弥散度模拟结果明显大于Gelhar理论计算值,而对于较大相关长度在迁移距离不很大时,纵向弥散度模拟结果明显小于Gelhar理论计算值。本研究可为野外大尺度地下水污染预报模型中水动力弥散参数的确定提供方法借鉴。     

An approximate dynamic programming approachto decision making in the presence of uncertainty for surfactant-polymer flooding

The least squares Monte Carlo method is a decision evaluation method that can capture the effect of uncertainty and the value of flexibility of a process. The method is a stochastic approximate dynamic programming approach to decision making. It is based on a forward simulation coupled with a recursive algorithm which produces the near-optimal policy. It relies on the Monte Carlo simulation to produce convergent results. This incurs a significant computational requirement when using this method to evaluate decisions for reservoir engineering problems because this requires running many reservoir simulations. The objective of this study was to enhance the performance of the least squares Monte Carlo method by improving the sampling method used to generate the technical uncertainties used in obtaining the production profiles. The probabilistic collocation method has been proven to be a robust and efficient uncertainty quantification method. By using the sampling methods of the probabilistic collocation method to approximate the sampling of the technical uncertainties, it is possible to significantly reduce the computational requirement of running the decision evaluation method. Thus, we introduce the least squares probabilistic collocation method. The decision evaluation considered a number of technical and economic uncertainties. Three reservoir case studies were used: a simple homogeneous model, the PUNQ-S3 model, and a modified portion of the SPE10 model. The results show that using the sampling techniques of the probabilistic collocation method produced relatively accurate responses compared with the original method. Different possible enhancements were discussed in order to practically adapt the least squares probabilistic collocation method to more realistic and complex reservoir models. Furthermore, it is desired to perform the method to evaluate high-dimensional decision scenarios for different chemical enhanced oil recovery processes using real reservoir data.     

Stochastic seismic slope stability assessment using polynomial chaos expansions combined with relevance vector machine

This paper presents probabilistic assessment of seismically-induced slope displacements considering uncertainties of seismic ground motions and soil properties.A stochastic ground motion model representing both the temporal and spectral non-stationarity of earthquake shakings and a three-dimensional rotational failure mechanism are integrated to assess Newmark-type slope displacements.A new probabilistic approach that incorporates machine learning in metamodeling technique is proposed,by combining relevance vector machine with polynomial chaos expansions(RVM-PCE).Compared with other PCE methods,the proposed RVM-PCE is shown to be more effective in estimating failure probabilities.The sensitivity and relative influence of each random input parameter to the slope displacements are discussed.Finally,the fragility curves for slope displacements are established for sitespecific soil conditions and earthquake hazard levels.The results indicate that the slope displacement is more sensitive to the intensities and strong shaking durations of seismic ground motions than the frequency contents,and a critical Arias intensity that leads to the maximum annual failure probabilities can be identified by the proposed approach.     

地质条件不确定性下TBM管片结构失事概率计算

不良地质条件是影响TBM施工隧洞管片结构安全的重要因素。综合考虑围岩地质条件和衬砌结构的不确定性,提出了一种定量分析TBM管片结构失事概率的新方法。在基于Markov过程估计隧洞沿程地质岩性变化概率的基础上,建立了隧洞任意位置处管片选型不匹配的概率模型;考虑围岩和管片参数的不确定性,采用随机有限元方法计算某一类型管片在不同围岩下的失事概率;由此,采用全概率公式,可计算隧洞沿程任意位置处管片结构的失事概率。结合实际工程,针对施工期工况,确定了该隧洞管片沿程的失事概率、最大失事概率及其所对应的位置等,为管片选型、优化设计及TBM施工期的风险防范提供了依据。     

Stochastic response surface method for reliability analysis of rock slopes involving correlated non-normal variables

This paper proposes a stochastic response surface method for reliability analysis involving correlated non-normal random variables, in which the Nataf transformation is adopted to effectively transform the correlated non-normal variables into independent standard normal variables. Transformations of random variables that are often used in reliability analyses in terms of standard normal variables are summarized. The closed-form expressions for fourth to sixth order Hermite polynomial chaos expansions involving any number of random variables are formulated. The proposed method will substantially extend the application of stochastic response surface method for reliability problems. An example of reliability analysis of rock slope stability with plane failure is presented to demonstrate the validity and capability of the proposed stochastic response surface method. The results indicate that the proposed stochastic response surface method can evaluate the reliability of rock slope stability involving correlated non-normal variables accurately and efficiently. Its accuracy is shown to be higher than that for the first-order reliability method, and it is much more efficient than direct Monte-Carlo simulation. The results also show that the number of collocation points selected should ensure that the Hermite polynomial matrix has a full rank so that different order SRSMs can produce a robust estimation of probability of failure for a specified performance function. Generally, the accuracy of SRSM increases as the order of SRSM increases.     

水利工程风险分析研究现状综述

将水利工程风险分析分为单一和综合两种情况进行归纳分析。总结了风险分析在水利工程中应用的各种分析方法,并就各种方法在研究应用中的适用条件、相关关系和优缺点进行评述。指出单一风险在水利工程中的应用主要以数理统计方法为主,分析水利工程的随机不确定性。综合风险能够考虑水利工程的随机、模糊和灰色等不确定性,但存在着相关性、一致性、行为因素影响分析等技术难点。给出了正确选择评价方法、结合失事后果进行分析等一些建议。     

岩溶地区地下水污染风险评价方法探究——以地苏地下河系流域为例

岩溶地下水污染风险评价对岩溶地下水的保护、管理和合理利用具有重要意义。文章总结了近年来国内外地下水污染风险评价方面的研究进展,针对目前评价体系存在的不足,构建了适合岩溶区地下水污染风险评价体系。该方法基于欧洲模式,实现地下水防污性能评价;污染负荷评价则考虑污染物在覆盖层中的衰减过程,利用折减系数实现污染负荷量化;最后,基于GIS空间叠加分析耦合防污性能与污染负荷评价,实现区域地下水污染风险评价。文章以地苏地下河系流域为例,开展岩溶区域地下水污染风险评价,结果表明:区域整体地下水污染风险偏低,地下水中等及以上污染风险区域面积424.41 km2,占研究区总面积的39.03%,主要分布在研究区中东部地苏乡、东庙乡、六也乡局部等人类活动频繁与地苏地下河干流中下游段。地下水污染风险空间分布特征不仅显示了岩性、坡度、岩溶网络发育等自然条件对评价结果的影响,同时也反映了人类活动的影响。地势平缓,岩溶发育程度强烈,加之人类活动频繁是导致区域地下水污染风险较高的原因所在。      

A stochastic collocation based Kalman filter for data assimilation

In this paper, a stochastic collocation-based Kalman filter (SCKF) is developed to estimate the hydraulic conductivity from direct and indirect measurements. It combines the advantages of the ensemble Kalman filter (EnKF) for dynamic data assimilation and the polynomial chaos expansion (PCE) for efficient uncertainty quantification. In this approach, the random log hydraulic conductivity field is first parameterized by the Karhunen–Loeve (KL) expansion and the hydraulic pressure is expressed by the PCE. The coefficients of PCE are solved with a collocation technique. Realizations are constructed by choosing collocation point sets in the random space. The stochastic collocation method is non-intrusive in that such realizations are solved forward in time via an existing deterministic solver independently as in the Monte Carlo method. The needed entries of the state covariance matrix are approximated with the coefficients of PCE, which can be recovered from the collocation results. The system states are updated by updating the PCE coefficients. A 2D heterogeneous flow example is used to demonstrate the applicability of the SCKF with respect to different factors, such as initial guess, variance, correlation length, and the number of observations. The results are compared with those from the EnKF method. It is shown that the SCKF is computationally more efficient than the EnKF under certain conditions. Each approach has its own advantages and limitations. The performance of the SCKF decreases with larger variance, smaller correlation ratio, and fewer observations. Hence, the choice between the two methods is problem dependent. As a non-intrusive method, the SCKF can be easily extended to multiphase flow problems.     

Uncertainty assessment in quantitative rockfall risk assessment

This study shows a quantitative rockfall risk assessment (QRA) for a slope of the Feifeng Mountain (China), including an explicit assessment of the uncertainties. For rockfall risk analysis, the annual probability of occurrence, reach probability, temporal–spatial probability and vulnerability of tourists were calculated for both dry and rainy day conditions. The resulting individual risk for exposed people visiting the historical site can be considered as acceptable for all scenarios, whereas the overall societal risk lies within the as low as reasonably practicable (ALARP) zone and therefore requires some mitigation actions. For the explicit assessment of uncertainty, an error propagation technique (first-order second moment (FOSM)) was adopted, starting from expert knowledge heuristic estimations of the coefficient of variation for each component of the risk analysis procedure. As a result, coefficients of variation of the calculated risk were obtained, ranging from 48 to 132 %, thus demonstrating the importance of accounting for uncertainty in rockfall risk modelling. A multi-criteria methodology is also proposed for the assessment of the standard deviation of the parameters adopted for the stochastic rockfall run-out model.     

梯级施工导流系统整体风险分析

进行流域梯级水电站开发,对相邻两座同期建设的水电工程组成的梯级施工导流系统进行整体风险分析意义重大。基于风险分析理论,考虑梯级施工导流系统水文和水力的不确定性,建立了系统整体风险数学模型。在此基础上构建了不同洪水组合情况下的风险计算模型,并利用Monte-Carlo方法耦合主要风险因素进行模型求解。同时,针对洪水过程遭遇情况下的风险模型,通过引入起始时间差随机因素来计算下游导流系统施工洪水过程。工程实例分析证明,风险分析模型和方法是可靠、有效的,为流域梯级开发条件下施工导流标准选取及导流方案优选提供重要依据。