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1.
The role of heterogeneity and uncertainty in hydraulic conductivity on hillslope runoff production was evaluated using the fully integrated hydrologic model ParFlow. Simulations were generated using idealized high-resolution hillslopes configured both with a deep water table and a water table equal to the outlet to isolate surface and subsurface flow, respectively. Heterogeneous, correlated random fields were used to create spatial variability in the hydraulic conductivity. Ensembles, generated by multiple realizations of hydraulic conductivity, were used to evaluate how this uncertainty propagates to runoff. Ensemble averages were used to determine the effective runoff for a given hillslope as a function of rainfall rate and degree of subsurface heterogeneity. Cases where the water table is initialized at the outlet show runoff behavior with little sensitivity to variance in hydraulic conductivity. A technique is presented that explicitly interrogates individual realizations at every simulation timestep to partition overland and subsurface flow contributions. This hydrograph separation technique shows that the degree of heterogeneity can play a role in determining proportions of surface and subsurface flow, even when effective hillslope outflow is seen. This method is also used to evaluate current hydrograph separation techniques and demonstrates that recursive filters can accurately proportion overland and base-flow for certain cases. 相似文献
2.
Integration of Tracer Test Data to Refine Geostatistical Hydraulic Conductivity Fields Using Sequential Self-Calibration Method 总被引：3，自引：0，他引：3
On the basis of local measurements of hydraulic conductivity,geostatistical methods have been found to be useful in heterogeneity characterization of a hydraulic conductivity field on a regional scale. However,the methods are not suited to directly integrate dynamic production data,such as,hydraulic head and solute concentration,into the study of conductivity distribution. These data,which record the flow and transport processes in the medium,are closely related to the spatial distribution of hydraulic conductivity. In this study,a three-dimensional gradient-based inverse method-the sequential self-calibration (SSC) method-is developed to calibrate a hydraulic conductivity field,initially generated by a geostatistical simulation method,conditioned on tracer test results. The SSC method can honor both local hydraulic conductivity measurements and tracer test data. The mismatch between the simulated hydraulic conductivity field and the reference true one,measured by its mean square error (MSE),is reduced through the SSC conditional study. In comparison with the unconditional results,the SSC conditional study creates the mean breakthrough curve much closer to the reference true curve,and significantly reduces the prediction uncertainty of the solute transport in the observed locations. Further,the reduction of uncertainty is spatially dependent,which indicates that good locations,geological structure,and boundary conditions will affect the efficiency of the SSC study results. 相似文献
3.
Spatial averaging of hydraulic conductivity in three-dimensional heterogeneous porous media 总被引：4，自引：0，他引：4
A. J. Desbarats 《Mathematical Geology》1992,24(3):249-267
Numerical models of groundwater flow require the assignment of hydraulic conductivities to large grid blocks discretizing the flow domain; however, conductivity data is usually available only at the much smaller scale of core samples. This paper describes a geostatistical model for hydraulic conductivity at both the core or point scale and that of grid blocks. Conductivity at the block scale is obtained empirically as a spatial power-average of point scale values. Assuming a multivariate Gaussian model for point log-conductivity, expressions are derived for the ensemble mean and variance of block conductivity. The expression for the ensemble mean of block scale conductivity is found to be similar to an expression for the ensemble effective conductivity of an infinite field derived analytically by earlier authors. Here, block conductivities obtained by power averaging are compared with effective conductivities obtained from a numerical flow model and are found to be in excellent agreement for a suitably chosen averaging exponent. This agreement deteriorates gradually as the log variance of conductivity increases beyond 2. For arbitrary flow field geometry and anisotropic conductivity covariances, the averaging exponent can be calibrated by recourse to numerical flow experiments. For cubic fields and an isotropic spatial covariance, the averaging exponent is found to be 1/3. In this particular case, it was found that flow field discretization at the block scale through local averaging of point conductivities gave similar results to those obtained directly using a point scale discretization of the flow field. 相似文献
4.
In earth and environmental sciences applications, uncertainty analysis regarding the outputs of models whose parameters are spatially varying (or spatially distributed) is often performed in a Monte Carlo framework. In this context, alternative realizations of the spatial distribution of model inputs, typically conditioned to reproduce attribute values at locations where measurements are obtained, are generated via geostatistical simulation using simple random (SR) sampling. The environmental model under consideration is then evaluated using each of these realizations as a plausible input, in order to construct a distribution of plausible model outputs for uncertainty analysis purposes. In hydrogeological investigations, for example, conditional simulations of saturated hydraulic conductivity are used as input to physically-based simulators of flow and transport to evaluate the associated uncertainty in the spatial distribution of solute concentration. Realistic uncertainty analysis via SR sampling, however, requires a large number of simulated attribute realizations for the model inputs in order to yield a representative distribution of model outputs; this often hinders the application of uncertainty analysis due to the computational expense of evaluating complex environmental models. Stratified sampling methods, including variants of Latin hypercube sampling, constitute more efficient sampling aternatives, often resulting in a more representative distribution of model outputs (e.g., solute concentration) with fewer model input realizations (e.g., hydraulic conductivity), thus reducing the computational cost of uncertainty analysis. The application of stratified and Latin hypercube sampling in a geostatistical simulation context, however, is not widespread, and, apart from a few exceptions, has been limited to the unconditional simulation case. This paper proposes methodological modifications for adopting existing methods for stratified sampling (including Latin hypercube sampling), employed to date in an unconditional geostatistical simulation context, for the purpose of efficient conditional simulation of Gaussian random fields. The proposed conditional simulation methods are compared to traditional geostatistical simulation, based on SR sampling, in the context of a hydrogeological flow and transport model via a synthetic case study. The results indicate that stratified sampling methods (including Latin hypercube sampling) are more efficient than SR, overall reproducing to a similar extent statistics of the conductivity (and subsequently concentration) fields, yet with smaller sampling variability. These findings suggest that the proposed efficient conditional sampling methods could contribute to the wider application of uncertainty analysis in spatially distributed environmental models using geostatistical simulation. 相似文献
5.
Berenice Zapata-Norberto Eric Morales-Casique Graciela S. Herrera 《Hydrogeology Journal》2018,26(3):755-769
Severe land subsidence due to groundwater extraction may occur in multiaquifer systems where highly compressible aquitards are present. The highly compressible nature of the aquitards leads to nonlinear consolidation where the groundwater flow parameters are stress-dependent. The case is further complicated by the heterogeneity of the hydrogeologic and geotechnical properties of the aquitards. The effect of realistic vertical heterogeneity of hydrogeologic and geotechnical parameters on the consolidation of highly compressible aquitards is investigated by means of one-dimensional Monte Carlo numerical simulations where the lower boundary represents the effect of an instant drop in hydraulic head due to groundwater pumping. Two thousand realizations are generated for each of the following parameters: hydraulic conductivity (K), compression index (C c), void ratio (e) and m (an empirical parameter relating hydraulic conductivity and void ratio). The correlation structure, the mean and the variance for each parameter were obtained from a literature review about field studies in the lacustrine sediments of Mexico City. The results indicate that among the parameters considered, random K has the largest effect on the ensemble average behavior of the system when compared to a nonlinear consolidation model with deterministic initial parameters. The deterministic solution underestimates the ensemble average of total settlement when initial K is random. In addition, random K leads to the largest variance (and therefore largest uncertainty) of total settlement, groundwater flux and time to reach steady-state conditions. 相似文献
6.
To fulfil the need to generate more realistic solutions, stochastic inverse simulations in hydrogeology are now constrained on both piezometric head and hydraulic conductivity data. These inverse techniques, often based on geostatistics, allow modifications of an initial solution conditioned only on hydraulic conductivity data to arrive at a final solution that also matches observed heads. By repeating the process as many times as necessary with different initial solutions, one generates an ensemble of final solutions thereby addressing the uncertainty of the inverse problem. This requires a method able to handle the whole ensemble and to work on its relevant characteristics. From this standpoint, the analysis by Empirical Orthogonal Functions (EOF) appears promising. The method builds an orthogonal decomposition of the covariance matrix, calculated over the whole set of solutions, and the areas in space where the first functions have a greater influence corresponding to locations of maximum uncertainty in the solutions. These locations depend both on the hydraulic characteristics of the flow problem and on the spatial distribution of available data. The EOF analysis is used on a synthetic problem that mimics a possible behavior of the Culebra aquifer of the Waste Isolation Pilot Plant (WIPP, New Mexico). The method also allows new solutions to be generated at lower computational cost by a random composition of the functions obtained by the EOF analysis. These new solutions keep the main characteristics of the initial ensemble and because they can be conditioned, they return very good results when they are used to solve the direct problem. 相似文献
7.
根据给定渗透系数、孔隙度以及吸附系数的概率分布,采用顺序高斯模拟生成相关的多参数随机场的实现,作为地下水流和溶质运移模型的输入参数,对污染物浓度进行随机分析。研究结果表明,与仅考虑渗透系数空间变异性相比,考虑相关的多参数空间变异性导致污染羽的扩散程度有显著不同。当孔隙度与渗透系数呈正相关关系时,会减少污染羽的扩散程度,反之,当孔隙度与渗透系数为负相关关系时,会加剧污染羽的扩散程度。吸附系数也是如此。在考虑吸附系数的空间变异性之后,污染羽的分布表现出拖尾现象。同时考虑渗透系数、孔隙度以及吸附系数空间变异性时,孔隙度非均质性对溶质运移的影响较吸附系数非均质性的影响更大。 相似文献
8.
Gregory D. Lazear 《Hydrogeology Journal》2006,14(8):1582-1598
The Tongue Creek watershed lies on the south flank of Grand Mesa in western Colorado, USA and is a site with 1.5 km of topographic relief, heat flow of 100 mW/m2, thermal conductivity of 3.3 W m–1 °C–1, hydraulic conductivity of 10-8 m/s, a water table that closely follows surface topography, and groundwater temperatures 3–15°C above mean surface temperatures. These data suggest that convective heat transport by groundwater flow has modified the thermal regime of the site. Steady state three-dimensional numerical simulations of heat flow, groundwater flow, and convective transport were used to model these thermal and hydrological data. The simulations provided estimates for the scale of hydraulic conductivity and bedrock base flow discharge within the watershed. The numerical models show that (1) complex three-dimensional flow systems develop with a range of scales from tens of meters to tens of kilometers; (2) mapped springs are frequently found at locations where contours of hydraulic head indicate strong vertical flow at the water table, and; (3) the distribution of groundwater temperatures in water wells as a function of surface elevation is predicted by the model. 相似文献
9.
Digital simulation of the scale effect in hydraulic conductivity 总被引：1，自引：1，他引：0
Charles W. Rovey II. 《Hydrogeology Journal》1998,6(2):216-225
Measured hydraulic conductivity increases with the scale of testing, but the reason for this increase is not clear. Possibly,
high-conductivity heterogeneities are more effective in raising hydraulic conductivity over the regional scale than at the
local scale. Alternatively, borehole skin and storage effects, among others, can systematically bias the results of small-scale
tests; thus, the increase may simply be an artifact of the test method.
Radial-flow tests were simulated at various scales in digital models of fractured double-porosity media. The mean hydraulic
conductivity increases until the radius of influence in the test exceeds the fracture spacing. Therefore, under radial flow,
hydraulic conductivity is indeed dependent on measurement scale.
The increase in hydraulic conductivity with scale is a natural consequence of heterogeneity. Over short distances, water converging
toward a borehole must generally flow across heterogeneities. Therefore, small-scale tests tend to measure a weighted harmonic
mean of the hydraulic-conductivity field. Over a large area, however, flow is primarily along high-conductivity heterogeneities.
Therefore, large-scale tests approach a weighted arithmetic mean where high-conductivity heterogeneities have a greater influence.
Received, April 1997 Revised, January 1998 Accepted, December 1997 相似文献
10.
裂隙介质渗透结构表现为高度的非均质性与各项异性。为了科学有效地预测某核工程场地裂隙地下水的流动规律,揭示裂隙岩体地下水的渗流特性,笔者等采用Pilot Point调参方法与null space Monte Carlo方法（NSMC）,开展了裂隙岩体渗透结构的不确定性分析研究,构建了符合实际水文地质条件的多个渗流数值模型集合。结果表明：该方法获得的各个实现地下水位模拟结果能够与实际观测数据较好吻合,可反映工程场地裂隙地下水动力特征与流动趋势;各个实现的参数化渗透结构在空间上存在一定的差异性,但整体变化趋势是保持一致的,渗透参数的不确定性表现为在实测数据分布区域相对较低,钻孔空白区域相对较高;该方法可以弥补单一、确定性模拟结果在表征裂隙介质渗透结构方面的局限性,有效地降低模型参数的不确定性与随机性。此方法对进一步提升裂隙岩体渗流模拟精度与预测能力,深化裂隙地下水迁移规律的认识具有重要的意义。 相似文献
11.
Estimation of Hydraulic Conductivity and Its Uncertainty from Grain-Size Data Using GLUE and Artificial Neural Networks 总被引：4，自引：0，他引：4
Bart Rogiers Dirk Mallants Okke Batelaan Matej Gedeon Marijke Huysmans Alain Dassargues 《Mathematical Geosciences》2012,44(6):739-763
Various approaches exist to relate saturated hydraulic conductivity (K s) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods??multiple linear regression and artificial neural networks??that use the entire grain-size distribution data as input for K s prediction. Besides the predictive capacity of the methods, the uncertainty associated with the model predictions is also evaluated, since such information is important for stochastic groundwater flow and contaminant transport modelling. Artificial neural networks (ANNs) are combined with a generalised likelihood uncertainty estimation (GLUE) approach to predict K s from grain-size data. The resulting GLUE-ANN hydraulic conductivity predictions and associated uncertainty estimates are compared with those obtained from the multiple linear regression models by a leave-one-out cross-validation. The GLUE-ANN ensemble prediction proved to be slightly better than multiple linear regression. The prediction uncertainty, however, was reduced by half an order of magnitude on average, and decreased at most by an order of magnitude. This demonstrates that the proposed method outperforms classical data-driven modelling techniques. Moreover, a comparison with methods from the literature demonstrates the importance of site-specific calibration. The data set used for this purpose originates mainly from unconsolidated sandy sediments of the Neogene aquifer, northern Belgium. The proposed predictive models are developed for 173 grain-size K s-pairs. Finally, an application with the optimised models is presented for a borehole lacking K s data. 相似文献
12.
Sellafield in West Cumbria was a potential site for the location of the UK's first underground repository for radioactive, intermediate level waste (ILW). The repository was to lie around 650 m beneath the ground surface within rocks of the Borrowdale volcanic group (BVG), a thick suite of SW dipping, fractured, folded and metamorphosed Ordovician meta-andesites and ignimbrites. These are overlain by an onlapping sequence of Carboniferous and Permo-Triassic sediments. In situ borehole measurements showed that upward trending fluid pressure gradients exist in the area of the potential repository site, and that there are three distinct fluid types in the subsurface; fresh, saline and brine (at depth, to the west of the site). Simulations of fluid flow in the Sellafield region were undertaken with a 2D, steady-state, coupled fluid and heat flow simulation code (OILGEN). In both simplified and geologically complex models, topographically driven flow dominated the regional hydrogeology. Fluids trended persistently upwards through the potential repository site. The dense brine to the west of the site promoted upward deflection of topographically driven groundwaters. The inclusion in hydrogeological models of faults and variably saline sub-surface fluids was essential to the accurate reproduction of regional hydraulic head variations. Sensitivity analyses of geological variables showed that the rate of groundwater flow through the potential repository site was dependent upon the hydraulic conductivity of the BVG, and was unaffected by the hydraulic conductivity of other hydrostratigraphic units. Calibration of the model was achieved by matching simulated subsurface pressures to those measured in situ. Simulations performed with BVG hydraulic conductivity 100 times the base case median value provided the “best-fit” comparison between the calculated equivalent freshwater head and that measured in situ, regardless of the hydraulic conductivity of other hydrostratigraphic units. Transient mass transport simulations utilising the hydraulic conductivities of this “best fit” simulation showed that fluids passing through the potential repository site could reach the surface in 15 000 years. Simple safety case implications drawn from the results of the study showed that the measured BVG hydraulic conductivity must be less than 0.03 m year−1 to be simply declared safe. Recent BVG hydraulic conductivity measurements showed that the maximum BVG hydraulic conductivity is around 1000 times this safety limit. 相似文献
13.
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
14.
Modern geostatistical techniques allow the generation of high-resolution heterogeneous models of hydraulic conductivity containing millions to billions of cells. Selective upscaling is a numerical approach for the change of scale of fine-scale hydraulic conductivity models into coarser scale models that are suitable for numerical simulations of groundwater flow and mass transport. Selective upscaling uses an elastic gridding technique to selectively determine the geometry of the coarse grid by an iterative procedure. The geometry of the coarse grid is built so that the variances of flow velocities within the coarse blocks are minimum. Selective upscaling is able to handle complex geological formations and flow patterns, and provides full hydraulic conductivity tensor for each block. Selective upscaling is applied to a cross-bedded formation in which the fine-scale hydraulic conductivities are full tensors with principal directions not parallel to the statistical anisotropy of their spatial distribution. Mass transport results from three coarse-scale models constructed by different upscaling techniques are compared to the fine-scale results for different flow conditions. Selective upscaling provides coarse grids in which mass transport simulation is in good agreement with the fine-scale simulations, and consistently superior to simulations on traditional regular (equal-sized) grids or elastic grids built without accounting for flow velocities. 相似文献
15.
Hugo A. Loáiciga 《Mathematical Geosciences》2008,40(2):199-211
The equation of groundwater flow in marine island aquifers in which there is time-independent, spatially-variable recharge
and pumping is solved in closed form for rectangular, circular, and elliptical island geometries. The solution of the groundwater
flow equation is expressed in terms of the elevation of the phreatic surface within the flow domain. The depth of the seawater-freshwater
interface below mean sea level follows from the Dupuit–Ghyben–Herzberg relation. The method of solution presented in this
work relies on expanding the hydraulic head and forcing function (recharge and groundwater extraction) as Fourier series that
transforms the two-dimensional Poisson-type flow equations into second-order ordinary differential equations solvable using
classical theory. The important case of constant recharge (without groundwater extraction) leads to solutions in which the
hydraulic head is expressible as the product of a flow factor equal to the squared root of the ratio of recharge over hydraulic
conductivity times a geometric factor involving island shape parameters and flow boundary conditions. Estimability conditions
for the hydraulic conductivity are derived for the cases of constant recharge and spatially variable recharge with pumping. 相似文献
16.
Seiyed Mossa Hosseini Najmeh Mahjouri Sajjad Bagheri 《Environmental Earth Sciences》2014,72(9):3531-3548
Analyzing groundwater hydrologic equations related to karstic aquifers and spring hydrograph simulation have become the focus of many researches. Having double or triple porosity structure, mixed flow nature, and varying conduit permeability have made these formations become complex heterogenic systems with great temporal and spatial hydrodynamic variability. In this paper, a conditional sequential gaussian simulation (SGS) is used to simulate monthly flow data of five karstic springs with different hydrogeological properties, located in Zagros Mountain Chain, in western Iran. To evaluate the performance of the SGS algorithm, the results are compared with those of an autoregressive integrated moving average (ARIMA) model. The results demonstrate the efficiency of the SGS model in simulation of monthly flows compared to the ARIMA model. They also show the suitability of this model for handling uncertainty associated with karstic spring flows through generation of several equally probable stochastic realizations. 相似文献
17.
Wang Mingyu The University of Arizona Tucson Arizona USA Department of Water Resources Environmental Engineering China University of Geosciences Beijing Chen Jinsong Wan Li Department of Water Resources Environmental Engineering 《中国地质大学学报(英文版)》2001,12(3)
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18.
This short paper shows that different choices made for control functions of information in hydrodynamic flow problems can have significant implications for interpretations of the system. Using as a simple illustration the case of a steady-state, one-dimensional flow model with no internal sources or sinks and with the hydraulic conductivity depending on a single parameter and the distance from the origin, it is shown that, even when a continuous, error-free head data set is provided, statements about the uniqueness or not of the inverse solution are conditioned on the choice of the control function. Care has to be exercised in obtaining physically meaningful results and, depending on the model assumptions and the data available, there may not be acceptable models. It is also shown that there may be more than one model behavior that is acceptable. The results have implications for the hydrodynamic upscaling problem for flow in permeable media, for ensemble averaging methods, and for parameter determination for deterministic models of permeable flow. 相似文献
19.
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. 相似文献
20.
地下水流数值模拟过程中,水文地质参数的不确定性对模拟结果影响很大。以内蒙古鄂尔多斯市某水源地为例,利用拉丁超立方抽样(LHS)方法获得了含水层渗透参数的随机组合,进行地下水流随机模拟。通过对观测资料与计算水位的绝对值平均(MAE)误差和误差均方根(RMSE)的统计分析,获得了模型较为稳定的随机模拟次数是243次。利用该随机模型对水源地设计开采量进行水位预测,并给出允许降深的风险性分布图。结果表明,预测水位和标准差分布符合实际情况,水位降深大于35 m的风险性最大达到75%。 相似文献