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1.
《Advances in water resources》1998,22(3):203-221
Highly resolved simulations of groundwater flow, chemical migration and contaminant recovery processes are used to test the applicability of stochastic models of flow and transport in a typical field setting. A simulation domain encompassing a portion of the upper saturated aquifer materials beneath the Lawrence Livermore National Laboratory was developed to hierarchically represent known hydrostratigraphic units and more detailed stochastic representations of geologic heterogeneity within them. Within each unit, Gaussian random field models were used to represent hydraulic conductivity variation, as parameterized from well test data and geologic interpretation of spatial variability. Groundwater flow, transport and remedial extraction of two hypothetical contaminants were made in six different statistical realizations of the system. The effective flow and transport behavior observed in the simulations compared reasonably with the predictions of stochastic theories based upon the Gaussian models, even though more exacting comparisons were prevented by inherent nonidealities of the geologic model and flow system. More importantly, however, biases and limitations in the hydraulic data appear to have reduced the applicability of the Gaussian representations and clouded the utility of the simulations and effective behavior based upon them. This suggests a need for better and unbiased methods for delineating the spatial distribution and structure of geologic materials and hydraulic properties in field systems. High performance computing can be of critical importance in these endeavors, especially with respect to resolving transport processes within highly variable media.©1998 Elsevier Science Limited. All rights reserved 相似文献
2.
Flach GP 《Ground water》2012,50(2):216-229
Dual-domain solute transport models produce significantly improved agreement to observations compared to single-domain (advection-dispersion) models when used in an a posteriori data fitting mode. However, the use of dual-domain models in a general predictive manner has been a difficult and persistent challenge, particularly at field-scale where characterization of permeability and flow is inherently limited. Numerical experiments were conducted in this study to better understand how single-rate mass transfer parameters vary with aquifer attributes and contaminant exposure. High-resolution reference simulations considered 30 different scenarios involving variations in permeability distribution, flow field, mass transfer timescale, and contaminant exposure time. Optimal dual-domain transport parameters were empirically determined by matching to breakthrough curves from the high-resolution simulations. Numerical results show that mobile porosity increases with lower permeability contrast/variance, smaller spatial correlation length, lower connectivity of high-permeability zones, and flow transverse to strata. A nonzero non-participating porosity improves empirical fitting, and becomes larger for flow aligned with strata, smaller diffusion coefficient, and larger spatial correlation length. The non-dimensional mass transfer coefficient or Damkohler number tends to be close to 1.0 and decrease with contaminant exposure time, in agreement with prior studies. The best empirical fit is generally achieved with a combination of macrodispersion and first-order mass transfer. Quantitative prediction of ensemble-average dual-domain parameters as a function of measurable aquifer attributes proved only marginally successful. 相似文献
3.
A conceptual model of anisotropic and dynamic permeability is developed from hydrogeologic and hydromechanical characterization of a foliated, complexly fractured, crystalline rock aquifer at Gates Pond, Berlin, Massachusetts. Methods of investigation include aquifer‐pumping tests, long‐term hydrologic monitoring, fracture characterization, downhole heat‐pulse flow meter measurements, in situ extensometer testing, and earth tide analysis. A static conceptual model is developed from observations of depth‐dependent and anisotropic permeability that effectively compartmentalizes the aquifer as a function of foliation intensity. Superimposed on the static model is dynamic permeability as a function of hydraulic head in which transient bulk aquifer transmissivity is proportional to changes in hydraulic head due to hydromechanical coupling. The dynamic permeability concept is built on observations that fracture aperture changes as a function of hydraulic head, as measured during in situ extensometer testing of individual fractures, and observed changes in bulk aquifer transmissivity as determined from earth tides during seasonal changes in hydraulic head, with higher transmissivity during periods of high hydraulic head, and lower transmissivity during periods of relatively lower hydraulic head. A final conceptual model is presented that captures both the static and dynamic properties of the aquifer. The workflow presented here demonstrates development of a conceptual framework for building numerical models of complexly fractured, foliated, crystalline rock aquifers that includes both a static model to describe the spatial distribution of permeability as a function of fracture type and foliation intensity and a dynamic model that describes how hydromechanical coupling impacts permeability magnitude as a function of hydraulic head fluctuation. This model captures important geologic controls on permeability magnitude, anisotropy, and transience and therefor offers potentially more reliable history matching and forecasts of different water management strategies, such as resource evaluation, well placement, permeability prediction, and evaluating remediation strategies. 相似文献
4.
The permeability of the Elkhorn fault zone,South Park,Colorado 总被引：5，自引：0，他引：5
The purposes of this study are to use both field and modeling approaches to characterize the permeability of a fault and to assess the role of the fault on regional ground water flow. The study subject is the Elkhorn fault, a low-angle reverse fault that brings Precambrian crystalline rocks over the sediments of Colorado's South Park Basin. The fault is hypothesized to act as a low-permeability barrier to flow, restricting interaction between the crystalline aquifer and the basin sediments. To test this hypothesis and to better predict the permeability structure of the fault, we synthesized geologic data to create a geologic model of the fault, conducted aquifer tests to estimate the hydrogeologic properties of the fault zone, and used ground water modeling to test the influence of a range of hydraulic properties for the fault zone on ground water flow in the region. Our study suggests that the fault is a low-permeability feature. Estimated heads are best matched to observations by modeling the fault as a 10-foot-thick interval of low-permeability fault gouge. Steady-state flow models show that much of the flow in the study area is topographically driven near land surface. Flow rates decrease with depth in the aquifers. In the footwall, ground water moves updip in the Michigan-San Isabel syncline to discharge in the South Park Basin. In the hanging wall, ground water moves east to a regional ground water divide. Sensitivity analyses indicate that hydraulic heads are most sensitive to changes in hydraulic conductivity and recharge. 相似文献
5.
This paper presents a Bayesian Monte Carlo method for evaluating the uncertainty in the delineation of well capture zones and its application to a wellfield in a heterogeneous, multiaquifer system. In the method presented, Bayes' rule is used to update prior distributions for the unknown parameters of the stochastic model for the hydraulic conductivity, and to calculate probability-based weights for parameter realizations using head residuals. These weights are then assigned to the corresponding capture zones obtained using forward particle tracking. Statistical analysis of the set of weighted protection zones results in a probability distribution for the capture zones. The suitability of the Bayesian stochastic method for a multilayered system is investigated, using the wellfield Het Rot at Nieuwrode, Belgium, located in a three-layered aquifer system, as an example. The hydraulic conductivity of the production aquifer is modeled as a spatially correlated random function with uncertain parameters. The aquitard and overlying unconfined aquifer are assigned random, homogeneous conductivities. The stochastic results are compared with deterministic capture zones obtained with a calibrated model for the area. The predictions of the stochastic approach are more conservative and indicate that parameter uncertainty should be taken into account in the delineation of well capture zones. 相似文献
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7.
Two different deterministic and two alternative stochastic (i.e., geostatistical) approaches to modeling the distribution of hydraulic conductivity (K) in a nonuniform (sigma2ln(K)) = 0.29) glacial sand aquifer were used to explore the influence of conceptual model selection on simulations of three-dimensional tracer movement. The deterministic K models employed included a homogeneous effective K and a perfectly stratified 14 layer model. Stochastic K models were constructed using sequential Gaussian simulation and sequential i ndicator simulation conditioned to available K values estimated from measured grain size distributions. Standard simulation software packages MODFLOW, MT3DMS, and MODPATH were used to model three-dimensional ground water flow and transport in a field tracer test, where a pulse of bromide was injected through an array of three fully screened wells and extracted through a single fully screened well approximately 8 m away. Agreement between observed and simulated transport behavior was assessed through direct comparison of breakthrough curves (BTCs) and selected breakthrough metrics at the extraction well and at 26 individual multilevel sample ports distributed irregularly between the injection and extraction wells. Results indicate that conceptual models incorporating formation variability are better able to capture observed breakthrough behavior. Root mean square (RMS) error of the deterministic models bracketed the ensemble mean RMS error of stochastic models for simulated concentration vs. time series, but not for individual BTC characteristic metrics. The spatial variability models evaluated here may be better suited to simulating breakthrough behavior measured in wells screened over large intervals than at arbitrarily distributed observation points within a nonuniform aquifer domain. 相似文献
8.
Modern ground water characterization and remediation projects routinely require calibration and inverse analysis of large three-dimensional numerical models of complex hydrogeological systems. Hydrogeologic complexity can be prompted by various aquifer characteristics including complicated spatial hydrostratigraphy and aquifer recharge from infiltration through an unsaturated zone. To keep the numerical models computationally efficient, compromises are frequently made in the model development, particularly, about resolution of the computational grid and numerical representation of the governing flow equation. The compromise is required so that the model can be used in calibration, parameter estimation, performance assessment, and analysis of sensitivity and uncertainty in model predictions. However, grid properties and resolution as well as applied computational schemes can have large effects on forward-model predictions and on inverse parameter estimates. We investigate these effects for a series of one- and two-dimensional synthetic cases representing saturated and variably saturated flow problems. We show that "conformable" grids, despite neglecting terms in the numerical formulation, can lead to accurate solutions of problems with complex hydrostratigraphy. Our analysis also demonstrates that, despite slower computer run times and higher memory requirements for a given problem size, the control volume finite-element method showed an advantage over finite-difference techniques in accuracy of parameter estimation for a given grid resolution for most of the test problems. 相似文献
9.
Prashanth Khambhammettu Philippe Renard John Doherty Jeremy White Marc Killingstad Michael Kladias 《Ground water》2024,62(1):60-74
Categorical parameter distributions consisting of geologic facies with distinct properties, for example, high-permeability channels embedded in a low-permeability matrix, are common at contaminated sites. At these sites, low-permeability facies store solute mass, acting as secondary sources to higher-permeability facies, sustaining concentrations for decades while increasing risk and cleanup costs. Parameter estimation is difficult in such systems because the discontinuities in the parameter space hinder the inverse problem. This paper presents a novel approach based on Traveling Pilot Points (TRIPS) and an iterative ensemble smoother (IES) to solve the categorical inverse problem. Groundwater flow and solute transport in a hypothetical aquifer with a categorical parameter distribution are simulated using MODFLOW 6. Heads and concentrations are recorded at multiple monitoring locations. IES is used to generate posterior ensembles assuming a TRIPS prior and an approximate multi-Gaussian prior. The ensembles are used to predict solute concentrations and mass into the future. The evaluation also includes an assessment of how the number of measurements and the choice of the geological prior determine the characteristics of the posterior ensemble and the resulting predictions. The results indicate that IES was able to efficiently sample the posterior distribution and showed that even with an approximate geological prior, a high degree of parameterization and history matching could lead to parameter ensembles that can be useful for making certain types of predictions (heads, concentrations). However, the approximate geological prior was insufficient for predicting mass. The analysis demonstrates how decision-makers can quantify uncertainty and make informed decisions with an ensemble-based approach. 相似文献
10.
Complexity 总被引：1，自引：0，他引：1
Gómez-Hernández JJ 《Ground water》2006,44(6):782-785
It is difficult to define complexity in modeling. Complexity is often associated with uncertainty since modeling uncertainty is an intrinsically difficult task. However, modeling uncertainty does not require, necessarily, complex models, in the sense of a model requiring an unmanageable number of degrees of freedom to characterize the aquifer. The relationship between complexity, uncertainty, heterogeneity, and stochastic modeling is not simple. Aquifer models should be able to quantify the uncertainty of their predictions, which can be done using stochastic models that produce heterogeneous realizations of aquifer parameters. This is the type of complexity addressed in this article. 相似文献
11.
Since the mid-twentieth century, most cities worldwide have undergone a rapid expansion in urban land use. Along with the expansion, several problems, such as excessive loss of prime agricultural land and increasing traffic congestion have arisen. Thus, understanding and measurements of the expansion scale and its speed are crucial to planners and officials during urban planning and management processes. To measure such geographic phenomena, Shannon first devised entropy theory, and then Batty developed it into spatial entropy. The recently developed spatial entropy model, which was used to measure urban sprawl, introduced area to represent spatial asymmetry. However, most models did not consider spatial discretization, particularly the impact of distance. This study attempted to construct an integrated gravity-spatial entropy model to delineate distance and spatial diffusion impacts on population distribution. Then, we tested the model using Shanghai’s temporal land use and community statistical data. Application results for the new gravity-spatial model show that it is a useful tool for identifying spatial and temporal variations of urban sprawl. 相似文献
12.
In this work, the concept of entropy based on probability is applied in modeling the vertical distribution of velocity in open channel turbulent flow. Using the principle of maximum entropy, one-dimensional velocity distribution is derived by maximizing the Renyi entropy subject to some constraints by assuming dimensionless velocity as a random variable. The Renyi entropy-based equation is capable of modeling the velocity distribution from the channel bed to the water surface. The derived velocity distribution is tested with field and laboratory observations and is also compared with existing entropy-based velocity distributions. The present model has shown good agreement with observed data and its prediction accuracy is superior than the other existing models. 相似文献
13.
A covariance-based model-fitting approach is often considered valid to represent field spatial variability of hydraulic properties. This study examines the representation of geologic heterogeneity in two types of geostatistical models under the same mean and spatial covariance structure, and subsequently its effect on the hydraulic response to a pumping test based on 3D high-resolution numerical simulation and field data. Two geostatistical simulation methods, sequential Gaussian simulation (SGS) and transition probability indicator simulation (TPROGS) were applied to create conditional realizations of alluvial fan aquifer systems in the Lawrence Livermore National Laboratory (LLNL) area. The simulated K fields were then used in a numerical groundwater flow model to simulate a pumping test performed at the LLNL site. Spatial connectivity measures of high-K materials (channel facies) captured connectivity characteristics of each geostatistical model and revealed that the TPROGS model created an aquifer (channel) network having greater lateral connectivity. SGS realizations neglected important geologic structures associated with channel and overbank (levee) facies, even though the covariance model used to create these realizations provided excellent fits to sample covariances computed from exhaustive samplings of TPROGS realizations. Observed drawdown response in monitoring wells during a pumping test and its numerical simulation shows that in an aquifer system with strongly connected network of high-K materials, the Gaussian approach could not reproduce a similar behavior in simulated drawdown response found in TPROGS case. Overall, the simulated drawdown responses demonstrate significant disagreement between TPROGS and SGS realizations. This study showed that important geologic characteristics may not be captured by a spatial covariance model, even if that model is exhaustively determined and closely fits the exponential function. 相似文献
14.
Derivation of different suspension equations in sediment-laden flow from Shannon entropy 总被引：1，自引：0，他引：1
In this study the well-known Rouse equation and Barenblatt equation for suspension concentration distribution in a sediment-laden flow is derived using Shannon entropy. Considering dimensionless suspended sediment concentration as a random variable and using principle of maximum entropy, probability density function of suspension concentration is obtained. A new and general cumulative distribution function for the flow domain is proposed which can describe specific previous forms reported in the literature. The cumulative distribution function is tested with a variety sets of experimental data and also compared with previous models. The test results ensure the superiority of the new cumulative distribution function. Further a modified form of the cumulative distribution function is discussed and used to derive the suspension model of Greimann et al. The model parameters are expressed in terms of the Rouse number to show the effectiveness of this study using entropy based approach. Finally a non-linear equation in the Rouse number has been suggested to compute it from the experimental data. 相似文献
15.
Stochastic rainfall-runoff forecasting: parameter estimation,multi-step prediction,and evaluation of overflow risk 总被引：2，自引：2，他引：0
Roland Löwe Peter Steen Mikkelsen Henrik Madsen 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(3):505-516
Probabilistic runoff forecasts generated by stochastic greybox models can be notably useful for the improvement of the decision-making process in real-time control setups for urban drainage systems because the prediction risk relationships in these systems are often highly nonlinear. To date, research has primarily focused on one-step-ahead flow predictions for identifying, estimating, and evaluating greybox models. For control purposes, however, stochastic predictions are required for longer forecast horizons and for the prediction of runoff volumes, rather than flows. This article therefore analyzes the quality of multistep ahead forecasts of runoff volume and considers new estimation methods based on scoring rules for k-step-ahead predictions. The study shows that the score-based methods are, in principle, suitable for the estimation of model parameters and can therefore help the identification of models for cases with noisy in-sewer observations. For the prediction of the overflow risk, no improvement was demonstrated through the application of stochastic forecasts instead of point predictions, although this result is thought to be caused by the notably simplified setup used in this analysis. In conclusion, further research must focus on the development of model structures that allow the proper separation of dry and wet weather uncertainties and simulate runoff uncertainties depending on the rainfall input. 相似文献
16.
The large and diverse body of subsurface characterization data generated at a field research site near Oyster, Virginia, provides a unique opportunity to test the impact of conditioning data of various types on predictions of flow and transport. Bromide breakthrough curves (BTCs) were measured during a forced-gradient local-scale injection experiment conducted in 1999. Observed BTCs are available at 140 sampling points in a three-dimensional array within the transport domain. A detailed three-dimensional numerical model is used to simulate breakthrough curves at the same locations as the observed BTCs under varying assumptions regarding the character of hydraulic conductivity spatial distributions, and variable amounts and types of conditioning data. We present comparative results of six cases ranging from simple (deterministic homogeneous models) to complex (stochastic indicator simulation conditioned to cross-borehole geophysical observations). Quantitative measures of model goodness-of-fit are presented. The results show that conditioning to a large number of small-scale measurements does not significantly improve model predictions, and may lead to biased or overly confident predictions. However, conditioning to geophysical interpretations with larger spatial support significantly improves the accuracy and precision of model predictions. In all cases, the effects of model error appear to be significant in relation to parameter uncertainty. 相似文献
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18.
基于最大熵原理,得到地震时间间隔和地震震级的概率分布函数。根据时间间隔分布,得到地震发震概率,当概率上升达到警界值时,可对云南5级以上中强地震做出预测。6个月以内中短期预测对应率为91％;3个月以内,短临期预测对应率为73％。根据震级分布,得到用最大熵原理求出的地震理论发生次数,理论发震次数与实际较为接近。用最大熵原理求出了云南不同地区不同震级档次5级以上中强地震的复发周期。分析认为,云南7级以上大震危险性在逐步逼近,西部危险性高于东部。 相似文献
19.
Flow from some springs in former glacial lakebeds of the Upper Midwest is extremely steady throughout the year and does not increase significantly after precipitation events or seasonal recharge. Analytical and simplified numerical models of spring systems were used to determine whether preferential ground water flow through high-permeability features in shallow sandstone aquifers could produce typical values of spring discharge and the unusually steady rates of spring flow. The analytical model is based on a one-dimensional solution for periodic ground water flow. Solutions to this model suggest that it is unlikely that a periodic forcing due to seasonal variations in areal recharge would propagate to springs in a setting where high-permeability features exist. The analytical model shows that the effective length of the aquifer, or the length of flowpaths to a spring, and the total transmissivity of the aquifer have the greatest potential to impact the nature of spring flow in this setting. The numerical models show that high-permeability features can influence the magnitude of spring flow and the results demonstrate that the lengths of ground water flowpaths increase when high-permeability features are explicitly modeled, thus decreasing the likelihood for temporal variations in spring flow. 相似文献
20.
Hillslope scale runoff is generated as a result of interacting factors that include water influx rate, surface and subsurface properties, and antecedent saturation. Heterogeneity of these factors affects the existence and characteristics of runoff. This heterogeneity becomes an increasingly relevant consideration as hydrologic models are extended and employed to capture greater detail in runoff generating processes. We investigate the impact of one type of heterogeneity – subsurface permeability – on runoff using the integrated hydrologic model ParFlow. Specifically, we examine the sensitivity of runoff to variation in three-dimensional subsurface permeability fields for scenarios dominated by either Hortonian or Dunnian runoff mechanisms. Ten thousand statistically consistent subsurface permeability fields are parameterized using a truncated Karhunen–Loéve (KL) series and used as inputs to 48-h simulations of integrated surface-subsurface flow in an idealized ‘tilted-v’ domain. Coefficients of the spatial modes of the KL permeability fields provide the parameter space for analysis using the active subspace method. The analysis shows that for Dunnian-dominated runoff conditions the cumulative runoff volume is sensitive primarily to the first spatial mode, corresponding to permeability values in the center of the three-dimensional model domain. In the Hortonian case, runoff volume is sensitive to multiple smaller-scale spatial modes and the locus of that sensitivity is in the near-surface zone upslope from the domain outlet. Variation in runoff volume resulting from random heterogeneity configurations can be expressed as an approximately univariate function of the active variable, a weighted combination of spatial parameterization coefficients computed through the active subspace method. However, this relationship between the active variable and runoff volume is more well-defined for Dunnian runoff than for the Hortonian scenario. 相似文献