共查询到20条相似文献，搜索用时 15 毫秒
1.
《Advances in water resources》1998,22(4):305-317
The Generalised Likelihood Uncertainty Estimation (GLUE) methodology is used to investigate how distributed water table observations modify simulation and parameter uncertainty for the hydrological model TOPMODEL, applied to the Sæternbekken Minifelt catchment in Norway. Errors in simulating observed flows, continuously-logged borehole water levels and more extensive, spatially distributed water table depths are combined using Bayes' equation within a `likelihood measure' L. It is shown how the distributions of L for the TOPMODEL parameters change as the different types of observed data are considered. These distributions are also used to construct corresponding simulation uncertainty bounds for flows, borehole water levels, and water table depths within the spatially-extensive piezometer network. Qualitatively wide uncertainty bounds for water table simulations are thought to be consistent with the simplified nature of the distributed model. 相似文献
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MODFLOW 2000 head uncertainty,a first-order second moment method 总被引：1，自引：0，他引：1
A computationally efficient method to estimate the variance and covariance in piezometric head results computed through MODFLOW 2000 using a first-order second moment (FOSM) approach is presented. This methodology employs a first-order Taylor series expansion to combine model sensitivity with uncertainty in geologic data. MODFLOW 2000 is used to calculate both the ground water head and the sensitivity of head to changes in input data. From a limited number of samples, geologic data are extrapolated and their associated uncertainties are computed through a conditional probability calculation. Combining the spatially related sensitivity and input uncertainty produces the variance-covariance matrix, the diagonal of which is used to yield the standard deviation in MODFLOW 2000 head. The variance in piezometric head can be used for calibrating the model, estimating confidence intervals, directing exploration, and evaluating the reliability of a design. A case study illustrates the approach, where aquifer transmissivity is the spatially related uncertain geologic input data. The FOSM methodology is shown to be applicable for calculating output uncertainty for (1) spatially related input and output data, and (2) multiple input parameters (transmissivity and recharge). 相似文献
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A. Lourens F. C. van Geer 《Stochastic Environmental Research and Risk Assessment (SERRA)》2016,30(1):237-249
In many fields of study, and certainly in hydrogeology, uncertainty propagation is a recurring subject. Usually, parametrized probability density functions (PDFs) are used to represent data uncertainty, which limits their use to particular distributions. Often, this problem is solved by Monte Carlo simulation, with the disadvantage that one needs a large number of calculations to achieve reliable results. In this paper, a method is proposed based on a piecewise linear approximation of PDFs. The uncertainty propagation with these discretized PDFs is distribution independent. The method is applied to the upscaling of transmissivity data, and carried out in two steps: the vertical upscaling of conductivity values from borehole data to aquifer scale, and the spatial interpolation of the transmissivities. The results of this first step are complete PDFs of the transmissivities at borehole locations reflecting the uncertainties of the conductivities and the layer thicknesses. The second step results in a spatially distributed transmissivity field with a complete PDF at every grid cell. We argue that the proposed method is applicable to a wide range of uncertainty propagation problems. 相似文献
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Assessing hydrological model predictive uncertainty using stochastically generated geological models 
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下载免费PDF全文 In distributed and coupled surface water–groundwater modelling, the uncertainty from the geological structure is unaccounted for if only one deterministic geological model is used. In the present study, the geological structural uncertainty is represented by multiple, stochastically generated geological models, which are used to develop hydrological model ensembles for the Norsminde catchment in Denmark. The geological models have been constructed using two types of field data, airborne geophysical data and borehole well log data. The use of airborne geophysical data in constructing stochastic geological models and followed by the application of such models to assess hydrological simulation uncertainty for both surface water and groundwater have not been previously studied. The results show that the hydrological ensemble based on geophysical data has a lower level of simulation uncertainty, but the ensemble based on borehole data is able to encapsulate more observation points for stream discharge simulation. The groundwater simulations are in general more sensitive to the changes in the geological structure than the stream discharge simulations, and in the deeper groundwater layers, there are larger variations between simulations within an ensemble than in the upper layers. The relationship between hydrological prediction uncertainties measured as the spread within the hydrological ensembles and the spatial aggregation scale of simulation results has been analysed using a representative elementary scale concept. The results show a clear increase of prediction uncertainty as the spatial scale decreases. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
7.
A methodology is proposed to quantify prediction uncertainty associated with ground water vulnerability models that were developed through an approach that coupled multivariate logistic regression with a geographic information system (GIS). This method uses Latin hypercube sampling (LHS) to illustrate the propagation of input error and estimate uncertainty associated with the logistic regression predictions of ground water vulnerability. Central to the proposed method is the assumption that prediction uncertainty in ground water vulnerability models is a function of input error propagation from uncertainty in the estimated logistic regression model coefficients (model error) and the values of explanatory variables represented in the GIS (data error). Input probability distributions that represent both model and data error sources of uncertainty were simultaneously sampled using a Latin hypercube approach with logistic regression calculations of probability of elevated nonpoint source contaminants in ground water. The resulting probability distribution represents the prediction intervals and associated uncertainty of the ground water vulnerability predictions. The method is illustrated through a ground water vulnerability assessment of the High Plains regional aquifer. Results of the LHS simulations reveal significant prediction uncertainties that vary spatially across the regional aquifer. Additionally, the proposed method enables a spatial deconstruction of the prediction uncertainty that can lead to improved prediction of ground water vulnerability. 相似文献
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John J Onsen Wayne P. Fassbender Patrick Jurcek Laura L. Barreto Larry F. Boyer 《Ground Water Monitoring & Remediation》1999,19(1):110-114
Two active quarries are mining stone from the Silurian dolomite aquifer in Waukesha County in southeastern Wisconsin. The village in which the quarries are located uses local zoning to control the depth of mining and to institute a long-term water level monitoring program and well guarantee/one with the quarry owners. Water levels dropped as much as 40 feet in at least 24 residential wells surrounding the quarries over a period of a few hours to days. The rapid decline in head was caused by a single boring drilled lo a depth of 75 feel he low the floor of one quarry. The borehole penetrated a localized fracture zone under confined artesian head. Water levels recovered to previous static levels within nine days after grouting the borehole. The rapid drawdown event demonstrates the potential impact of mining in fractured aquifers. The apparent complete recovery of the aquifer demonstrates that quick response can sometimes restore an aquifer. However, the potential for blasting into a similar zone illustrates the need for a well-thought-out aquifer monitoring program and emergency response plan. The experience of the village is a good example of managing conflicting uses of a finite resource and collecting baseline data needed to make informed decisions. 相似文献
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The aim of this paper is to compute the ground-motion prediction equation (GMPE)-specific components of epistemic uncertainty, so that they may be better understood and the model standard deviation potentially reduced. The reduced estimate of the model standard deviation may also be more representative of the true aleatory uncertainty in the ground-motion predictions.The epistemic uncertainty due to input variable uncertainty and uncertainty in the estimation of the GMPE coefficients are examined. An enhanced methodology is presented that may be used to analyse their impacts on GMPEs and GMPE predictions. The impacts of accounting for the input variable uncertainty in GMPEs are demonstrated using example values from the literature and by applying the methodology to the GMPE for Arias Intensity. This uncertainty is found to have a significant effect on the estimated coefficients of the model and a small effect on the value of the model standard deviation.The impacts of uncertainty in the GMPE coefficients are demonstrated by quantifying the uncertainty in hazard maps. This paper provides a consistent approach to quantifying the epistemic uncertainty in hazard maps using Monte Carlo simulations and a logic tree framework. The ability to quantify this component of epistemic uncertainty offers significant enhancements over methods currently used in the creation of hazard maps as it is both theoretically consistent and can be used for any magnitude–distance scenario. 相似文献
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This paper develops a new method for decision-making under uncertainty. The method, Bayesian Programming (BP), addresses a class of two-stage decision problems with features that are common in environmental and water resources. BP is applicable to two-stage combinatorial problems characterized by uncertainty in unobservable parameters, only some of which is resolved upon observation of the outcome of the first-stage decision. The framework also naturally accommodates stochastic behavior, which has the effect of impeding uncertainty resolution. With the incorporation of systematic methods for decision search and Monte Carlo methods for Bayesian analysis, BP addresses limitations of other decision-analytic approaches for this class of problems, including conventional decision tree analysis and stochastic programming. The methodology is demonstrated with an illustrative problem of water quality pollution control. Its effectiveness for this problem is compared to alternative approaches, including a single-stage model in which expected costs are minimized and a deterministic model in which uncertain parameters are replaced by their mean values. A new term, the expected value of including uncertainty resolution, or EVIUR, is introduced and evaluated for the illustrative problem. It is a measure of the worth of incorporating the experimental value of decisions into an optimal decision-making framework. For the illustrative problem, the two-stage adaptive management framework extracted up to approximately 50% of the gains of perfect information. The strength and limitations of the method are discussed and conclusions are presented. 相似文献
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Jürgen Pilz Gunter Spöck 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(5):621-632
The spatial prediction methodology that has become known under the heading of kriging is largely based on the assumptions
that the underlying random field is Gaussian and the covariance function is exactly known. In practical applications, however,
these assumptions will not hold. Beyond Gaussianity of the random field, lognormal kriging, disjunctive kriging, (generalized
linear) model-based kriging and trans-Gaussian kriging have been proposed in the literature. The latter approach makes use
of the Box–Cox-transform of the data. Still, all the alternatives mentioned do not take into account the uncertainty with
respect to the distribution (or transformation) and the estimated covariance function of the data. The Bayesian trans-Gaussian
kriging methodology proposed in the present paper is in the spirit of the “Bayesian bootstrap” idea advocated by Rubin (Ann
Stat 9:130–134, 1981) and avoids the unusual specification of noninformative priors often made in the literature and is entirely based on the
sample distribution of the estimators of the covariance function and of the Box–Cox parameter. After some notes on Bayesian
spatial prediction, noninformative priors and developing our new methodology finally we will present an example illustrating
our pragmatic approach to Bayesian prediction by means of a simulated data set. 相似文献
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Stauffer F 《Ground water》2005,43(6):843-849
A method is proposed to estimate the uncertainty of the location of pathlines in two-dimensional, steady-state confined or unconfined flow in aquifers due to the uncertainty of the spatially variable unconditional hydraulic conductivity or transmissivity field. The method is based on concepts of the semianalytical first-order theory given in Stauffer et al. (2002, 2004), which allows estimates of the lateral second moment (variance) of the location of a moving particle. However, this method is reformulated in order to account for nonuniform recharge and nonuniform aquifer thickness. One prominent application is the uncertainty estimation of the catchment of a pumping well by considering the boundary pathlines starting at a stagnation point. In this method, the advective transport of particles is considered, based on the velocity field. In the case of a well catchment, backtracking is applied by using the reversed velocity field. Spatial variability of hydraulic conductivity or transmissivity is considered by taking into account an isotropic exponential covariance function of log-transformed values with parameters describing the variance and correlation length. The method allows postprocessing of results from ground water models with respect to uncertainty estimation. The code PPPath, which was developed for this purpose, provides a postprocessing of pathline computations under PMWIN, which is based on MODFLOW. In order to test the methodology, it was applied to results from Monte Carlo simulations for catchments of pumping wells. The results correspond well. Practical applications illustrate the use of the method in aquifers. 相似文献
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反射波场分离是井孔地震资料处理中极其重要的一个环节,波场分离的质量直接影响成像结果的精度.不管是VSP还是井间地震资料,其反射波时距曲线都近似直线型,根据这一特征,本文提出一种改进的线性Radon变换方法来进行井孔资料的反射波上下行波场分离.该方法基于频率域线性Radon变换,通过引入一个新的变量λ来消除变换算子对频率的依赖性,避免了求取每一频率分量对应的不同变换算子,显著降低了计算成本;文中在求解该方法对应的最小二乘问题时,引入了发展较为成熟的高分辨率Radon变换技术来进一步提高波场分离的精度.采用本文方法进行井孔地震资料的上下行波场分离可以在保证分离精度的前提下有效地提高计算效率.根据上下行波在λ-f域内分布的特殊性,设计简单的滤波算子就可实现上下行波场的分离.最后通过合成数据试算以及实际资料处理（VSP数据和井间地震数据）验证了该方法的可行性和有效性. 相似文献
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使用德令哈地震台钻孔水位和黑石山水库水位记录数据,与德令哈钻孔应变观测数据进行相关分析;采用集中载荷模型计算水库负载作用对钻孔应变观测的理论干扰值,与实际观测值进行对比。结果显示,水库蓄水对钻孔应变观测造成严重干扰;水库负载作用与渗透作用对钻孔应变观测影响较小,水库水位变化导致周围岩体所受水压作用出现变化,可能是影响钻孔应变观测的主要因素。 相似文献
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At high latitudes, sporadic geomagnetic disturbances associated with geomagnetic storms introduce significant uncertainty in measurements by borehole inclinometers during the directional drilling of deep wells. Variations in the magnetic declination may lead to significant deviations of the actual coordinates of the borehole from the prescribed trajectory. Using the methods for calculating the profile of the actual borehole, we conducted model estimates of the influence of sporadic disturbances in the magnetic declination observed during the magnetic storm of October 28–31, 2003 on the displacement azimuth and intensity of borehole bending at the given locations at the sites of two high-latitude magnetic observatories. It is shown that, unless filtered based on the data of parallel observatory measurements, the geomagnetic disturbances can lead to unacceptably large errors in the borehole inclinometer measurements and cause a borehole deflection exceeding the admissible values. 相似文献
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Alyssa M. Dausman John Doherty Christian D. Langevin Michael C. Sukop 《Ground water》2010,48(5):729-740
The present study demonstrates a methodology for optimization of environmental data acquisition. Based on the premise that the worth of data increases in proportion to its ability to reduce the uncertainty of key model predictions, the methodology can be used to compare the worth of different data types, gathered at different locations within study areas of arbitrary complexity. The method is applied to a hypothetical nonlinear, variable density numerical model of salt and heat transport. The relative utilities of temperature and concentration measurements at different locations within the model domain are assessed in terms of their ability to reduce the uncertainty associated with predictions of movement of the salt water interface in response to a decrease in fresh water recharge. In order to test the sensitivity of the method to nonlinear model behavior, analyses were repeated for multiple realizations of system properties. Rankings of observation worth were similar for all realizations, indicating robust performance of the methodology when employed in conjunction with a highly nonlinear model. The analysis showed that while concentration and temperature measurements can both aid in the prediction of interface movement, concentration measurements, especially when taken in proximity to the interface at locations where the interface is expected to move, are of greater worth than temperature measurements. Nevertheless, it was also demonstrated that pairs of temperature measurements, taken in strategic locations with respect to the interface, can also lead to more precise predictions of interface movement. 相似文献
18.
Dylan R. Harp Velimir V. Vesselinov 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(7):1023-1042
An approach is presented for identifying statistical characteristics of stratigraphies from borehole and hydraulic data. The
approach employs a Markov-chain based geostatistical framework in a stochastic inversion. Borehole data provide information
on the stratigraphy while pressure and flux data provide information on the hydraulic performance of the medium. The use of
Markov-chain geostatistics as opposed to covariance-based geostatistics can provide a more easily interpreted model geologically
and geometrically. The approach hinges on the use of mean facies lengths (negative inverse auto-transition rates) and mean
transition lengths (inverse cross-transition rates) as adjustable parameters in the stochastic inversion. Along with an unconstrained
Markov-chain model, simplifying constraints to the Markov-chain model, including (1) proportionally-random and (2) symmetric
spatial correlations, are evaluated in the stochastic inversion. Sensitivity analyses indicate that the simplifying constraints
can facilitate the inversion at the cost of spatial correlation model generality. Inverse analyses demonstrate the feasibility
of this approach, indicating that despite some low parameter sensitivities, all adjustable parameters do converge for a sufficient
number of ensemble realizations towards their “true” values. This paper extends the approach presented in Harp et al. (doi:, 2008) to (1) statistically characterize the hydraulic response of a geostatistical model, thereby incorporating an uncertainty
analysis directly in the inverse method, (2) demonstrate that a gradient-based optimization strategy is sufficient, thereby
providing relative computational efficiency compared to global optimization strategies, (3) demonstrate that the approach
can be extended to a 3-D analysis, and (4) introduce the use of mean facies lengths and mean transition lengths as adjustable
parameters in a geostatistical inversion, thereby allowing the approach to be extended to greater than two category Markov-chain
models. 相似文献
19.
Verifying optimality of rainfed agriculture using a stochastic model for drought occurrence 总被引：1，自引：1，他引：0
Erfaneh Sharifi Koichi Unami Macarius Yangyuoru Masayuki Fujihara 《Stochastic Environmental Research and Risk Assessment (SERRA)》2016,30(5):1503-1514
It may be paradoxical but subsistence rainfed agriculture is the predominant source of food in Sub-Saharan Africa where the production uncertainty is associated with the stochastic nature of rainfall. This paper attempts to comprehend the rationale of this situation by a mathematical approach. Considering the level of drought severity as the zero-reverting Ornstein–Uhlenbeck process, optimality of rainfed agriculture is investigated in the context of stochastic control theory. Occurrence of drought terminating growth of crops is modelled with the concept of first exit time. A stochastic control problem allowing for virtual cost of irrigation, water stress to crops, and benefits of farming is formulated with irrigation effort as the control variable. The Hamilton–Jacobi–Bellman equation governing the optimal control is studied to identify the set of cost functions optimizing rainfed agriculture in an inverse problem approach. Data and information were collected in the coastal savanna agro-ecological zone of Ghana, to identify model parameters, formulate the stochastic control problem, solve the inverse problem, and then verify optimality of rainfed agriculture. The results indicated that rainfed agriculture is not optimal when the crop is more tolerant to water stress. 相似文献
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研究各种地层和井眼环境因素对碳氧比C/O测井长、短源距探测器的影响规律，可以为C/O测井仪器的刻度方法提供指导，为解释模型的建立和数据处理提供依据.本文用Monte Carlo方法，计算了C/O值随井眼直径、水泥环厚度、套管直径、孔隙度、含油饱和度、地层岩性和油密度的变化规律.从中看出，当井内流体为油时，井径或套管直径增大，C/O值增大，井眼影响增大；当井内流体为水时，井径或套管直径的增大，C/O值减小；水泥环厚度增加时C/O值减小；当井眼条件不变时，地层孔隙度越大，含油饱和度越大，C/O值越大，对测井越有利；反之，地层孔隙度越小，含油饱和度越小，C/O值越小，对测井不利；地层岩性对C/O值的影响显著，相同条件下，碳酸盐岩比砂岩的C/O值高；油密度越大，C/O值越大.文中还提出了一种消除这些因素影响的数据处理方法 相似文献