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  • 1
    Keywords: Computer science. ; Differential equations. ; Pollution. ; System theory. ; Mathematical models. ; Models of Computation. ; Differential Equations. ; Pollution. ; Complex Systems. ; Mathematical Modeling and Industrial Mathematics.
    Description / Table of Contents: Introduction, objectives -- Overview of uncertainty propagation methods -- Review of Probabilistic versus Fuzzy Approaches to Uncertainty Propagation in Geosciences -- Fuzzy set characterization of uncertainty (fuzzy variables) -- Applications of uncertainty analyses on simplified models -- Applications of uncertainty analysis to 3D subsurface contamination problems -- Discussion and conclusions.
    Abstract: This book highlights several methods and quantitative implementations of both probabilistic and fuzzy-based approaches to uncertainty quantification and uncertainty propagation through environmental subsurface pollution models with uncertain input parameters. The book focuses on methods as well as applications in hydrogeology, soil hydrology, groundwater contamination, and related areas (e.g., corrosion of nuclear waste canisters). The methods are illustrated for a broad spectrum of models, from non-differential I/O models to complex PDE solvers, including a novel 3D quasi-analytical model of contaminant transport, and a site-specific computer model of dissolved contaminant migration from a DNAPL (Dense Non Aqueous Phase Liquid) pollution source.
    Type of Medium: Online Resource
    Pages: IX, 95 p. 31 illus., 27 illus. in color. , online resource.
    Edition: 1st ed. 2023.
    ISBN: 9789819962419
    Series Statement: SpringerBriefs in Applied Sciences and Technology,
    DDC: 004.0151
    Language: English
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  • 2
    ISSN: 1745-6584
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Geosciences
    Notes: Karstic systems are highly heterogeneous geological formations characterized by a multiscale temporal and spatial hydrologic behavior with more or less localized temporal and spatial structures. Classical correlation and spectral analyses cannot take into account these properties. Therefore, it is proposed to introduce a new kind of transformation: the wavelet transform. Here we focus particularly on the use of wavelets to study temporal behavior of local precipitation and watershed runoffs from a part of the karstic system. In the first part of the paper, a brief mathematical overview of the continuous Morlet wavelet transform and of the multiresolution analysis is presented. An analogy with spectral analyses allows the introduction of concepts such as wavelet spectrum and cross-spectrum. In the second part, classical methods (spectral and correlation analyses) and wavelet transforms are applied and compared for daily rainfall rates and runoffs measured on a French karstic watershed (Pyrenees) over a period of 30 years.Different characteristic time scales of the rainfall and runoff processes are determined. These time scales are typically on the order of a few days for floods, but they also include significant half-year and one-year components and multi-annual components. The multiresolution cross-analysis also provides a new interpretation of the impulse response of the system. To conclude, wavelet transforms provide a valuable amount of information, which may be now taken into account in both temporal and spatially distributed karst modeling of precipitation and runoff.
    Type of Medium: Electronic Resource
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  • 3
    ISSN: 1573-8868
    Keywords: tracer transport ; random media ; stratified media ; multilayered media ; macrodispersion ; Lagrangian particle tracking
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract Dispersive mass transport processes in naturally heterogeneous geological formations (porous media) are investigated based on a particle approach to mass transport and on its numerical implementation using LPT3D, a Lagrangian Particle Tracking 3D code. We are currently using this approach for studying microscale and macroscale space–time behavior (advection, diffusion, dispersion) of tracer plumes, solutes, or miscible fluids, in 1,2,3-dimensional heterogeneous and anisotropic subsurface formations (aquifers, petroleum reservoirs). Our analyses are based on a general advection-diffusion model and numerical scheme where concentrations and fluxes are discretized in terms of particles. The advection-diffusion theory is presented in a probabilistic framework, and in particular, a numerical analysis is developed for the case of advective transport and rotational flows (numerical stability of the explicit Euler scheme). The remainder of the paper is devoted to the behavior of concentration, mass flux density, and statistical moments of the transported tracer plume in the case of heterogeneous steady flow fields, where macroscale dispersion occurs due to geologic heterogeneity and stratification. We focus on the case of perfectly stratified or multilayered media, obtained by generating many horizontal layers with a purely random transverse distribution of permeability and horizontal velocity. In this case, we calculate explicitly the exact mass concentration field C(x, t), mass flux density field f(x, t), and moments. This includes spatial moments and dispersion variance σ2 x (t) on a finite domain L, and temporal moments on a finite time scale T, e.g., the “mass variance” of arrival times σ2 T (x). The moments are related to flux concentrations in a way that takes explicitly into account finite space–time scales of analysis (time-dependent tracer mass; spatially variable “flow through” mass). The multilayered model problem is then used in numerical experiments for testing different ways of recovering information on tracer plume migration, dispersion, concentration and flux fields. Our analyses rely on a probabilistic interpretation that emerges naturally from the particle approach; it is based on spatial moments (particle positions), temporal moments (mass weighted arrival times), and probability densities (both concentrations and fluxes). Finally, as an alternative to direct estimations of the flux and concentration fields, we formulate and study the “Moment Inverse Problem.” Solving the MIP yields an indirect method for estimating the space–time distribution of flux concentrations based on observed or estimated moments of the plume. The moments may be estimated from field measurements, or numerically computed by particle tracking as we do here.
    Type of Medium: Electronic Resource
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  • 4
    ISSN: 1573-1634
    Keywords: Flow in random media ; effective conductivity ; finite differences ; iterative methods ; large-scale simulations ; groundwater flow ; stochastic hydrology ; random functions
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Technology
    Notes: Abstract This paper presents a numerical method for simulating flow fields in a stochastic porous medium that satisfies locally the Darcy equation, and has each of its hydraulic parameters represented as one realization of a three-dimensional random field. These are generated by using the Turning Bands method. Our ultimate objective is to obtain statistically meaningful solutions in order to check and extend a series of approximate analytical results previously obtained by a spectral perturbation method (L. W. Gelhar and co-workers). We investigate the computational aspects of the problem in relation with stochastic concepts. The difficulty of the numerical problem arises from the random nature of the hydraulic conductivities, which implies that a very large discretized algebraic system must be solved. Indeed, a preliminary evaluation with the aid of scale analysis suggests that, in order to solve meaningful flow problems, the total number of nodes must be of the order of 106. This is due to the requirement that Δx i ≪ gl i ≪ L i , where Δx i is the mesh size, λ i is a typical correlation scale of the inputs, and L i is the size of the flow domain (i = 1, 2, 3). The optimum strategy for the solution of such a problem is discussed in relation with supercomputer capabilities. Briefly, the proposed discretization method is the seven-point finite differences scheme, and the proposed solution method is iterative, based on prior approximate factorization of the large coefficient matrix. Preliminary results obtained with grids on the order of one hundred thousand nodes are discussed for the case of steady saturated flow with highly variable, random conductivities.
    Type of Medium: Electronic Resource
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  • 5
    ISSN: 1573-8868
    Keywords: kriging ; condition number ; random fields ; conditional simulation ; covariance matrices ; state-space estimation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Mathematics
    Notes: Abstract The numerical stability of linear systems arising in kriging, estimation, and simulation of random fields, is studied analytically and numerically. In the state-space formulation of kriging, as developed here, the stability of the kriging system depends on the condition number of the prior, stationary covariance matrix. The same is true for conditional random field generation by the superposition method, which is based on kriging, and the multivariate Gaussian method, which requires factoring a covariance matrix. A large condition number corresponds to an ill-conditioned, numerically unstable system. In the case of stationary covariance matrices and uniform grids, as occurs in kriging of uniformly sampled data, the degree of ill-conditioning generally increases indefinitely with sampling density and, to a limit, with domain size. The precise behavior is, however, highly sensitive to the underlying covariance model. Detailed analytical and numerical results are given for five one-dimensional covariance models: (1) hole-exponential, (2) exponential, (3) linear-exponential, (4) hole-Gaussian, and (5) Gaussian. This list reflects an approximate ranking of the models, from “best” to “worst” conditioned. The methods developed in this work can be used to analyze other covariance models. Examples of such representative analyses, conducted in this work, include the spherical and periodic hole-effect (hole-sinusoidal) covariance models. The effect of small-scale variability (nugget) is addressed and extensions to irregular sampling schemes and higher dimensional spaces are discussed.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Transport in porous media 18 (1995), S. 199-201 
    ISSN: 1573-1634
    Source: Springer Online Journal Archives 1860-2000
    Topics: Geosciences , Technology
    Type of Medium: Electronic Resource
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  • 7
    Publication Date: 2001-07-01
    Print ISSN: 0017-467X
    Electronic ISSN: 1745-6584
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Geosciences
    Published by Wiley
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  • 8
    Publication Date: 2018-07-02
    Print ISSN: 0169-3913
    Electronic ISSN: 1573-1634
    Topics: Geosciences , Technology
    Published by Springer
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  • 9
    Publication Date: 2019-02-08
    Print ISSN: 1874-8961
    Electronic ISSN: 1874-8953
    Topics: Geosciences , Mathematics
    Published by Springer
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  • 10
    Publication Date: 1994-01-01
    Print ISSN: 1874-8961
    Electronic ISSN: 1874-8953
    Topics: Geosciences , Mathematics
    Published by Springer
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