scispace - formally typeset
Journal ArticleDOI

A Stochastic-Conceptual Analysis of One-Dimensional Groundwater Flow in Nonuniform Homogeneous Media

R. Allan Freeze
- 01 Oct 1975 - 
- Vol. 11, Iss: 5, pp 725-741
Reads0
Chats0
TLDR
In this paper, the effects of stochastic parameter distributions on predicted hydraulic heads are analyzed with the aid of a set of Monte Carlo solutions to the pertinent boundary value problems, and the results show that the standard deviations of the input hydrogeologic parameters, particularly σy and σc, are important index properties; changes in their values lead to different responses for even when the means μy, μc, and μn are fixed.
Abstract
The most realistic representation of a naturally occurring porous medium is a stochastic set of macroscopic elements in which the values of the three basic hydrogeologic parameters (hydraulic conductivity K, compressibility α, and porosity n) are defined by frequency distributions. A homogeneous formation under this representation is one in which the frequency distributions do not change through space. All soils and geologic formations, even the ones that are homogeneous, show random variations in the values of the hydrogeological parameters through space; that is, they are nonuniform, and a measure of the nonuniformity is provided by the standard deviation of the frequency distributions. If K and α are log normally distributed and n is normally distributed, and if we define Y = log K and C = log α, then the parameters Y, C, and n can be generated from a multivariate normal density function with means μy, μc, and μn, standard deviations σy, σc, and σn, and correlation coefficients ρyc, ρyn, and ρcn The analysis of groundwater flow in nonuniform media requires a stochastic-conceptual approach in which the effects of stochastic parameter distributions on predicted hydraulic heads are analyzed with the aid of a set of Monte Carlo solutions to the pertinent boundary value problems. In this study, two one-dimensional saturated flow problems are analyzed: steady state flow between two specified heads and transient consolidation of a clay layer. The primary output is the statistical distribution of hydraulic head ϕ, through space and time, as indicated by the mean values and their standard deviations Sϕ¯(x, t) Results show that the standard deviations of the input hydrogeologic parameters, particularly σy and σc, are important index properties; changes in their values lead to different responses for even when the means μy, μc, and μn are fixed. The degree of uncertainty associated with hydraulic head predictions increases as the degree of nonuniformity of the porous medium increases. For large values of σy and σc it becomes virtually impossible to obtain meaningful hydraulic head predictions. For transient flow the output distribution of hydraulic head values is almost never normal; in some cases it approaches a uniform distribution. The results of this study throw into question the validity of the hidden assumption that underlies all deterministic groundwater modeling; namely, that it is possible to select a single value for each flow parameter in a homogeneous but nonuniform medium that is somehow representative and hence define an ‘equivalent’ uniform porous medium. For transient flow there may be no way to define an equivalent medium. The fact that nine index parameters rather than three are required to describe a nonuniform geologic formation, the large uncertainties in predicted hydraulic heads for relatively simple flow problems in nonuniform soils, and the contention that there may be no simple way to define an equivalent uniform porous medium all have important implications in the development of groundwater flow theory and in its most fundamental applications.

read more

Citations
More filters
Journal ArticleDOI

Large-Scale Modeling of Unsaturated Flow by a Stochastic Perturbation Approach

TL;DR: In this article, a large-scale unsaturated flow model was derived in which the saturated hydraulic conductivity (K s) is assumed to be a random field, and the corresponding effective parameters (i.e., the largescale relative diffusivity and the large scale relative conductivity) can be evaluated by the mean parameters and correction terms, the latter are affected by variability of the dimensionless form of K s and the flow process.
Journal ArticleDOI

Locating new production wells using a probabilistic-based groundwater model

TL;DR: In this paper, uncertainty analysis techniques within the groundwater modeling environment are used to predict regions within a groundwater basin that have a low probability of excessive drawdown and groundwater contamination, based on quantification of a basinwide water-balance, generation of a spatial distribution of lithology, locating a nearby total dissolved solids (TDS) plume and construction of an accurate groundwater flow model.
Journal ArticleDOI

Effect of spatial variation in hydraulic conductivity on groundwater flow by alternate solution techniques

TL;DR: In this article, the behavior of an aquifer in which there is spatial variation in hydraulic conductivity is simulated by means of a Monte Carlo procedure and the lognormal function is used to model the distribution of conductivities.
ReportDOI

Recent Developments in Modeling Groundwater Systems

TL;DR: Presented at the IBM Seminar on Regional Groundwater Hydrology and Modeling, Venice, Italy, May 25-26, 1976.

Stochastic Analysis for Water Quality

TL;DR: In this article, the feasibility of applying stochastic techniques to linear water quality models was demonstrated using a long term phosphorus model of Lake Washington, and the effect of uncertainty of the phosphorus loading term on simulated phosphorus levels was analyzed.
References
More filters
Book

Dynamics of fluids in porous media

Jacob Bear
TL;DR: In this paper, the Milieux poreux Reference Record was created on 2004-09-07, modified on 2016-08-08 and the reference record was updated in 2016.
Journal ArticleDOI

Statistical Continuum Theories

Journal ArticleDOI

Stochastic dynamic prediction

TL;DR: Stochastic dynamic prediction as mentioned in this paper assumes the laws governing atmospheric behavior are entirely deterministic, but seeks solutions corresponding to probabilistic statements of the initial conditions, thus recognizing the impossibility of exact or sufficiently dense observations.