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1.
《水文科学杂志》2013,58(6)
Abstract Abstract Characterization of heterogeneity at the field scale generally requires detailed aquifer properties such as transmissivity and hydraulic head. An accurate delineation of these properties is expensive and time consuming, and for many if not most groundwater systems, is not practical. As an alternative approach, stochastic representation of random fields is used and presented in this paper. Specifically, an iterative stochastic conditional simulation approach was applied to a hypothetical and highly heterogeneous pre-designed aquifer system. The approach is similar to the classical co-kriging technique; it uses a linear estimator that depends on the covariance functions of transmissivity (T), and hydraulic head (h), as well as their cross-covariances. A linearized flow equation along with a conditional random field generator constitutes the iterative process of the conditional simulation. One hundred equally likely realizations of transmissivity fields with pre-specified geostatistical parameters were generated, and conditioned to both limited transmissivity and head data. The successful implementation of the approach resulted in conditioned flow paths and travel-time distribution under different degrees of aquifer heterogeneity. This approach worked well for fields exhibiting small variances. However, for random fields exhibiting large variances (greater than 1.0), an iterative procedure was used. The results show that, as the variance of the ln[T] increases, the flow paths tend to diverge, resulting in a wide spectrum of flow conditions, with no direct discernable relationship between the degree of heterogeneity and travel time. The applied approach indicates that high errors may result when estimation of particle travel times in a heterogeneous medium is approximated by an equivalent homogeneous medium. 相似文献
2.
This work evaluated the spatial variability and distribution of heterogeneous hydraulic conductivity (K) in the Choushui River alluvial fan in Taiwan, using ordinary kriging (OK) and mean and individual sequential Gaussian simulations (SGS). A baseline flow model constructed by upscaling parameters was inversely calibrated to determine the pumping and recharge rates. Simulated heads using different K realizations were then compared with historically measured heads. A global/local simulated error between simulated and measured heads was analysed to assess the different spatial variabilities of various estimated K distributions. The results of a MODFLOW simulation indicate that the OK realization had the smallest sum of absolute mean simulation errors (SAMSE) and the SGS realizations preserved the spatial variability of the measured K fields. Moreover, the SAMSE increases as the spatial variability of the K field increases. The OK realization yields small local simulation errors in the measured K field of moderate magnitude, whereas the SGS realizations have small local simulation errors in the measured K fields, with high and low values. The OK realization of K can be applied to perform a deterministic inverse calibration. The mean SGS method is suggested for constructing a K field when the application focuses on extreme values of estimated parameters and small calibration errors, such as in a simulation of contaminant transport in heterogeneous aquifers. The individual SGS realization is useful in stochastically assessing the spatial uncertainty of highly heterogeneous aquifers. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
3.
The groundwater inverse problem of estimating heterogeneous groundwater model parameters (hydraulic conductivity in this case) given measurements of aquifer response (such as hydraulic heads) is known to be an ill-posed problem, with multiple parameter values giving similar fits to the aquifer response measurements. This problem is further exacerbated due to the lack of extensive data, typical of most real-world problems. In such cases, it is desirable to incorporate expert knowledge in the estimation process to generate more reasonable estimates. This work presents a novel interactive framework, called the ‘Interactive Multi-Objective Genetic Algorithm’ (IMOGA), to solve the groundwater inverse problem considering different sources of quantitative data as well as qualitative expert knowledge about the site. The IMOGA is unique in that it looks at groundwater model calibration as a multi-objective problem consisting of quantitative objectives – calibration error and regularization – and a ‘qualitative’ objective based on the preference of the geological expert for different spatial characteristics of the conductivity field. All these objectives are then included within a multi-objective genetic algorithm to find multiple solutions that represent the best combination of all quantitative and qualitative objectives. A hypothetical aquifer case-study (based on the test case presented by Freyberg [Freyberg DL. An exercise in ground-water model calibration and prediction. Ground Water 1988;26(3)], for which the ‘true’ parameter values are known, is used as a test case to demonstrate the applicability of this method. It is shown that using automated calibration techniques without using expert interaction leads to parameter values that are not consistent with site-knowledge. Adding expert interaction is shown to not only improve the plausibility of the estimated conductivity fields but also the predictive accuracy of the calibrated model. 相似文献
4.
《Advances in water resources》1998,22(2):103-116
We consider a one-dimensional model biodegradation system consisting of two reaction–advection equations for nutrient and pollutant concentrations and a rate equation for biomass. The hydrodynamic dispersion is ignored. Under an explicit condition on the decay and growth rates of biomass, the system can be approximated by two component models by setting biomass kinetics to equilibrium. We derive closed form solutions for constant speed traveling fronts for the reduced two component models and compare their profiles in homogeneous media. For a spatially random velocity field, we introduce travel time and study statistics of degradation fronts via representations in terms of the travel time probability density function (pdf) and the traveling front profiles. The travel time pdf does not vary with the nutrient and pollutant concentrations and only depends on the random water velocity. The traveling front profiles are expressed analytically or semi-analytically as functions of the travel time. The problem of nonlinear transport by a random velocity reduces to two subproblems: one being nonlinear transport by a known (unit) velocity, and the other being linear (advective) transport by a random velocity. The approach is illustrated through some examples where the randomness in velocity stems from the spatial variability of porosity. 相似文献
5.
R. Gong C. Lu W.‐M. Wu H. Cheng B. Gu D. Watson P.M. Jardine S.C. Brooks C.S. Criddle P.K. Kitanidis J. Luo 《Ground water》2011,49(2):209-218
A generalized, efficient, and practical approach based on the travel‐time modeling framework is developed to estimate in situ reaction rate coefficients for groundwater remediation in heterogeneous aquifers. The required information for this approach can be obtained by conducting tracer tests with injection of a mixture of conservative and reactive tracers and measurements of both breakthrough curves (BTCs). The conservative BTC is used to infer the travel‐time distribution from the injection point to the observation point. For advection‐dominant reactive transport with well‐mixed reactive species and a constant travel‐time distribution, the reactive BTC is obtained by integrating the solutions to advective‐reactive transport over the entire travel‐time distribution, and then is used in optimization to determine the in situ reaction rate coefficients. By directly working on the conservative and reactive BTCs, this approach avoids costly aquifer characterization and improves the estimation for transport in heterogeneous aquifers which may not be sufficiently described by traditional mechanistic transport models with constant transport parameters. Simplified schemes are proposed for reactive transport with zero‐, first‐, nth‐order, and Michaelis‐Menten reactions. The proposed approach is validated by a reactive transport case in a two‐dimensional synthetic heterogeneous aquifer and a field‐scale bioremediation experiment conducted at Oak Ridge, Tennessee. The field application indicates that ethanol degradation for U(VI)‐bioremediation is better approximated by zero‐order reaction kinetics than first‐order reaction kinetics. 相似文献
6.
We focus on the Bayesian estimation of strongly heterogeneous transmissivity fields conditional on data sampled at a set of locations in an aquifer. Log-transmissivity, Y, is modeled as a stochastic Gaussian process, parameterized through a truncated Karhunen–Loève (KL) expansion. We consider Y fields characterized by a short correlation scale as compared to the size of the observed domain. These systems are associated with a KL decomposition which still requires a high number of parameters, thus hampering the efficiency of the Bayesian estimation of the underlying stochastic field. The distinctive aim of this work is to present an efficient approach for the stochastic inverse modeling of fully saturated groundwater flow in these types of strongly heterogeneous domains. The methodology is grounded on the construction of an optimal sparse KL decomposition which is achieved by retaining only a limited set of modes in the expansion. Mode selection is driven by model selection criteria and is conditional on available data of hydraulic heads and (optionally) Y. Bayesian inversion of the optimal sparse KLE is then inferred using Markov Chain Monte Carlo (MCMC) samplers. As a test bed, we illustrate our approach by way of a suite of computational examples where noisy head and Y values are sampled from a given randomly generated system. Our findings suggest that the proposed methodology yields a globally satisfactory inversion of the stochastic head and Y fields. Comparison of reference values against the corresponding MCMC predictive distributions suggests that observed values are well reproduced in a probabilistic sense. In a few cases, reference values at some unsampled locations (typically far from measurements) are not captured by the posterior probability distributions. In these cases, the quality of the estimation could be improved, e.g., by increasing the number of measurements and/or the threshold for the selection of KL modes. 相似文献
7.
The combination of the analytic element method and a nonlinear parameter estimation technique forges a computationally efficient, information-rich, and cost-effective solution to the inverse ground-water flow problem. The recommended model calibration method uses a nonlinear least-squares objective, as quantified by misfitting the measured and modeled heads, and a modified Levenberg-Marquardt algorithm. As detailed and demonstrated by a steady-state regional aquifer model of Bemidji, Minnesota, automated calibration techniques make ground-water modeling feasible for a wider variety of projects where tight budgets and a lack of tools may have previously made such modeling inappropriate. 相似文献
8.
9.
In this study, we focus on a hydrogeological inverse problem specifically targeting monitoring soil moisture variations using tomographic ground penetrating radar (GPR) travel time data. Technical challenges exist in the inversion of GPR tomographic data for handling non-uniqueness, nonlinearity and high-dimensionality of unknowns. We have developed a new method for estimating soil moisture fields from crosshole GPR data. It uses a pilot-point method to provide a low-dimensional representation of the relative dielectric permittivity field of the soil, which is the primary object of inference: the field can be converted to soil moisture using a petrophysical model. We integrate a multi-chain Markov chain Monte Carlo (MCMC)–Bayesian inversion framework with the pilot point concept, a curved-ray GPR travel time model, and a sequential Gaussian simulation algorithm, for estimating the dielectric permittivity at pilot point locations distributed within the tomogram, as well as the corresponding geostatistical parameters (i.e., spatial correlation range). We infer the dielectric permittivity as a probability density function, thus capturing the uncertainty in the inference. The multi-chain MCMC enables addressing high-dimensional inverse problems as required in the inversion setup. The method is scalable in terms of number of chains and processors, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. The proposed inversion approach can successfully approximate the posterior density distributions of the pilot points, and capture the true values. The computational efficiency, accuracy, and convergence behaviors of the inversion approach were also systematically evaluated, by comparing the inversion results obtained with different levels of noises in the observations, increased observational data, as well as increased number of pilot points. 相似文献
10.
《Advances in water resources》2001,24(8):913-929
In this paper, we face the problem of upscaling transmissivity from the macroscopic to the megascopic scale; here the macroscopic scale is that of the continuous flow equations, whereas the megascopic scale is that of the flow models on a coarse grid. In this paper, we introduce the non-local inverse based scaling (NIBS) and compare it with the simplified renormalization (SR). The latter is a classical technique that we adapt to compute internode transmissivities for a finite differences flow model in a direct way. NIBS is implemented in three steps: in the first step, the macroscopic transmissivity, together with arbitrarily chosen auxiliary boundary conditions and sources, is used to solve forward problems (FPs) at the macroscopic scale; in the second step, the resulting heads are sampled at the megascopic scale; in the third step, the upscaled internode transmissivities are obtained by solving an inverse problem with the differential system method (DS) for which the heads resulting from the second step are used. NIBS is a non-local technique, because the computation of the internode transmissivities relies upon the whole transmissivity field at the macroscopic scale. We test NIBS against SR in the case of synthetic, isotropic, confined aquifers under the assumptions of two-dimensional (2D) and steady-state flow; the aquifers differ for the degree of heterogeneity, which is represented by a normally distributed uncorrelated component of lnT. For the comparison, the reference heads and fluxes at the megascopic scale are computed from the solution of FPs at the macroscopic scale. These reference values are compared with the heads and the fluxes predicted from models at the megascopic scale using the upscaled parameters of SR and NIBS. For the class of aquifers considered in this paper, the results of SR are better than those of NIBS, which hints that non-local effects can be disregarded at the megascopic scale. The two techniques provide comparable results when the heterogeneity increases, when the megascopic scale is large with respect to the heterogeneity length scale, or when the source terms are relevant. 相似文献
11.
《Advances in water resources》1998,22(1):87-95
An iterative co-conditional Monte Carlo simulation (IMCS) approach is developed. This approach derives co-conditional means and variances of transmissivity (T), head (φ), and Darcy's velocity (q), based on sparse measurements of T and φ in heterogeneous, confined aquifers under steady-state conditions. It employs the classical co-conditional Monte Carlo simulation technique (MCS) and a successive linear estimator that takes advantage of our prior knowledge of the covariances of T and φ and their cross-covariance. In each co-conditional simulation, a linear estimate of T is improved by solving the governing steady-state flow equation, and by updating residual covariance functions iteratively. These residual covariance functions consist of the covariance of T and φ and the cross-covariance function between T and φ. As a result, the non-linear relationship between T and φ is incorporated in the co-conditional realizations of T and φ. Once the T and φ fields are generated, a corresponding velocity field is also calculated. The average of the co-conditioned realizations of T, φ, and q yields the co-conditional mean fields. In turn, the co-conditional variances of T, φ, and q, which measure the reduction in uncertainty due to measurements of T and φ, are derived. Results of our numerical experiments show that the co-conditional means from IMCS for T and φ fields have smaller mean square errors (MSE) than those from a non-iterative Monte Carlo simulation (NIMCS). Finally, the co-conditional mean fields from IMCS are compared with the co-conditional effective fields from a direct approach developed by Yeh et al. [Water Resources Research, 32(1), 85–92, 1996]. 相似文献
12.
Previous studies of hyporheic zone focused largely on the net mass transfer of solutes between stream and streambed. Solute transport within the bed has attracted less attention. In this study, we combined flume experiments and numerical simulations to examine solute transport processes in a streambed with periodic bedforms. Solute originating from the stream was subjected to advective transport driven by pore water circulation due to current–bedform interactions as well as hydrodynamic dispersion in the porous bed. The experimental and numerical results showed that advection played a dominant role at the early stage of solute transport, which took place in the hyporheic zone. Downward solute transfer to the deep ambient flow zone was controlled by transverse dispersion at the later stage when the elapsed time exceeded the advective transport characteristic time tc (= L/uc with L being the bedform length and uc the characteristic pore water velocity). The advection-based pumping exchange model was found to predict reasonably well solute transfer between the overlying water and streambed at the early stage but its performance deteriorated at the later stage. With dispersion neglected, the pumping exchange model underestimated the long-term rate and total mass of solute transfer from the overlying water to the bed. Therefore both advective and dispersive transport components are essential for quantification of hyporheic exchange processes. 相似文献
13.
Physical properties of alluvial environments typically feature a high degree of anisotropy and are characterized by dynamic interactions between the surface and the subsurface. Hydrogeological models are often calibrated under the assumptions of isotropic hydraulic conductivity fields and steady-state conditions. We aim at understanding how these simplifications affect predictions of the water table using physically based models and advanced calibration and uncertainty analysis approaches based on singular value decomposition and Bayesian analysis. Specifically, we present an analysis of the information content provided by steady-state hydraulic data compared to transient data with respect to the estimation of aquifer and riverbed hydraulic properties. We show that assuming isotropy or fixed anisotropy may generate biases both in the estimation of aquifer and riverbed parameters as well as in the predictive uncertainty of the water table. We further demonstrate that the information content provided by steady-state hydraulic heads is insufficient to jointly estimate the aquifer anisotropy together with the aquifer and riverbed hydraulic conductivities and that transient data can help to reduce the predictive uncertainty to a greater extent. The outcomes of the synthetic analysis are applied to the calibration of a dynamic and anisotropic alluvial aquifer in Switzerland (The Rhône River). The results of the synthetic and real world modeling and calibration exercises documented herein provide insight on future data acquisition as well as modeling and calibration strategies for these environments. They also provide an incentive for evaluation and estimation of commonly made simplifying assumptions in order to prevent underestimation of the predictive uncertainty. 相似文献
14.
R.W. Readman 《Physics of the Earth and Planetary Interiors》1978,16(3):196-199
Magnetisation measurements on ulvöspinel have shown that there is a transition from the weakly ferromagnetic state to an essentially antiferromagnetic one at T ～ 60–100 K when moderate measuring fields (24 kOe) are used. Cooling from above 100 K in the presence of a magnetic field of several kilooersteds produces a reversed remanence for and the resulting thermomagnetic curve is Néel N-type. Magnetisation in 80 kOe produces a spontaneous moment extrapolated to 0 K of 0.015 μB, although this may not be completely saturated. An explanation for the magnetic transition is suggested in terms of an increased anisotropy possibly associated with a crystal transition. 相似文献
15.
Coupled inverse modelling of groundwater flow and mass transport and the worth of concentration data 总被引：1，自引：0，他引：1
Harrie-Jan Hendricks Franssen Jaime Gómez-Hernández Andrés Sahuquillo 《Journal of Hydrology》2003,281(4):281-295
This paper presents the extension of the self-calibrating method to the coupled inverse modelling of groundwater flow and mass transport. The method generates equally likely solutions to the inverse problem that display the variability as observed in the field and are not affected by a linearisation of the state equations. Conditioning to the state variables is measured by an objective function including, among others, the mismatch between the simulated and measured concentrations. Conditioning is achieved by minimising the objective function by gradient-based methods. The gradient contains the partial derivatives of the objective function with respect to: log conductivities, log storativities, prescribed heads at boundaries, retardation coefficients and mass sources. The derivatives of the objective function with respect to log conductivity are the most cumbersome and need the most CPU-time to be evaluated. For this reason, to compute this derivative only advective transport is considered. The gradient is calculated by the adjoint-state method. The method is demonstrated in a controlled, synthetic study, in which the worth of concentration data is analysed. It is shown that concentration data are essential to improve transport predictions and also help to improve aquifer characterisation and flow predictions, especially in the upstream part of the aquifer, even in the case that a considerable amount of other experimental data like conductivities and heads are available. Besides, conditioning to concentration data reduces the ensemble variances of estimated transmissivity, hydraulic head and concentration. 相似文献
16.
A calibration method to solve the groundwater inverse problem under steady- and transient-state conditions is presented. The method compares kriged and numerical head field gradients to modify hydraulic conductivity without the use of non-linear optimization techniques. The process is repeated iteratively until a close match with piezometric data is reached. The approach includes a damping factor to avoid divergence and oscillation of the solution in areas of low hydraulic gradient and a weighting factor to account for temporal head variation in transient simulations. The efficiency of the method in terms of computing time and calibration results is demonstrated with a synthetic field. It is shown that the proposed method provides parameter fields that reproduce both hydraulic conductivity and piezometric data in few forward model solutions. Stochastic numerical experiments are conducted to evaluate the sensitivity of the method to the damping function and to the head field estimation errors. 相似文献
17.
Doherty J 《Ground water》2003,41(2):170-177
Use of nonlinear parameter estimation techniques is now commonplace in ground water model calibration. However, there is still ample room for further development of these techniques in order to enable them to extract more information from calibration datasets, to more thoroughly explore the uncertainty associated with model predictions, and to make them easier to implement in various modeling contexts. This paper describes the use of "pilot points" as a methodology for spatial hydraulic property characterization. When used in conjunction with nonlinear parameter estimation software that incorporates advanced regularization functionality (such as PEST), use of pilot points can add a great deal of flexibility to the calibration process at the same time as it makes this process easier to implement. Pilot points can be used either as a substitute for zones of piecewise parameter uniformity, or in conjunction with such zones. In either case, they allow the disposition of areas of high and low hydraulic property value to be inferred through the calibration process, without the need for the modeler to guess the geometry of such areas prior to estimating the parameters that pertain to them. Pilot points and regularization can also be used as an adjunct to geostatistically based stochastic parameterization methods. Using the techniques described herein, a series of hydraulic property fields can be generated, all of which recognize the stochastic characterization of an area at the same time that they satisfy the constraints imposed on hydraulic property values by the need to ensure that model outputs match field measurements. Model predictions can then be made using all of these fields as a mechanism for exploring predictive uncertainty. 相似文献
18.
We examine multi-year conductivity-temperature-depth (CTD) data to better understand temperature and salinity variability over the central Bering Sea shelf. Particular consideration is given to observations made annually from 2002 to 2007 between August and October, although other seasons and years are also considered. Vertical and horizontal correlation maps show that near-surface and near-bottom salinity anomalies tend to fluctuate in phase across the central shelf, but that temperature anomalies are vertically coherent only in the weakly or unstratified inner-shelf waters. We formulate heat content (HC) and freshwater content (FWC) budgets based on the CTD observations, direct estimates of external fluxes (surface heat fluxes, ice melt, precipitation (P), evaporation (E) and river discharge), and indirect estimates of advective contributions. Ice melt, P−E, river discharge, and along-isobath advection are sufficient to account for the mean spring-to-fall increase in FWC, while summer surface heat fluxes are primarily responsible for the mean seasonal increase in HC, although interannual variability in the HC at the end of summer appears related to variability in the along-isobath advection during the summer months. On the other hand, FWC anomalies at the end of summer are significantly correlated with the mean wind direction and cross-isobath Ekman transport averaged over the previous winter. Consistent with the latter finding, salinities exhibit a weak but significant inverse correlation between the coastal and mid-shelf waters. The cross-shelf transport likely has significant effect on nutrient fluxes and other processes important to the functioning of the shelf ecosystem. Both the summer and winter advection fields appear to result from the seasonal mean position and strength of the Aleutian Low. We find that interannual thermal and haline variability over the central Bering Sea shelf are largely uncoupled. 相似文献
19.
N. I. Berezina V. I. Dmitriev N. A. Merschikova 《Izvestiya Physics of the Solid Earth》2013,49(3):350-355
We consider the iterative numerical method for solving two-dimensional (2D) inverse problems of magnetotelluric sounding, which significantly reduces the computational burden of the inverse problem solution in the class of quasi-layered models. The idea of the method is to replace the operator of the direct 2D problem of calculating the low-frequency electromagnetic field in a quasi-layered medium by a quasi-one dimensional operator at each observation point. The method is applicable for solving the inverse problems of magnetotellurics with either the E- and H-polarized fields and in the case when the inverse problem is simultaneously solved using the impedance values for the fields with both polarizations. We describe the numerical method and present the examples of its application to the numerical solution of a number of model inverse problems of magnetotelluric sounding. 相似文献
20.
Evaporation from three water bodies of different sizes and climates: Measurements and scaling analysis 总被引：3，自引：0，他引：3
S. Assouline S.W. Tyler J. Tanny S. Cohen E. Bou-Zeid M.B. Parlange G.G. Katul 《Advances in water resources》2008
Evaporation from small reservoirs, wetlands, and lakes continues to be a theoretical and practical problem in surface hydrology and micrometeorology because atmospheric flows above such systems can rarely be approximated as stationary and planar-homogeneous with no mean subsidence (hereafter referred to as idealized flow state). Here, the turbulence statistics of temperature (T) and water vapor (q) most pertinent to lake evaporation measurements over three water bodies differing in climate, thermal inertia and degree of advective conditions are explored. The three systems included Lac Léman in Switzerland (high thermal inertia, near homogeneous conditions with no appreciable advection due to long upwind fetch), Eshkol reservoir in Israel (intermediate thermal inertia, frequent strong advective conditions) and Tilopozo wetland in Chile (low thermal inertia, frequent but moderate advection). The data analysis focused on how similarity constants for the flux-variance approach, CT/Cq, and relative transport efficiencies RwT/Rwq, are perturbed from unity with increased advection or the active role of temperature. When advection is small and thermal inertia is large, CT/Cq < 1 (or RwT/Rwq > 1) primarily due to the active role of temperature, which is consistent with a large number of studies conducted over bare soil and vegetated surfaces. However, when advection is significantly large, then CT/Cq > 1 (orRwT/Rwq < 1). When advection is moderate and thermal inertia is low, then CT/Cq ∼ 1. This latter equality, while consistent with Monin–Obukhov similarity theory (MOST), is due to the fact that advection tends to increase CT/Cq above unity while the active role of temperature tends to decrease CT/Cq below unity. A simplified scaling analysis derived from the scalar variance budget equation, explained qualitatively how advection could perturb MOST scaling (assumed to represent the idealized flow state). 相似文献