Stochastic partial differential equations in groundwater hydrology
 T. E. Unny
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Many problems in hydraulics and hydrology are described by linear, time dependent partial differential equations, linearity being, of course, an assumption based on necessity.
Solutions to such equations have been obtained in the past based purely on deterministic consideration. The derivation of such a solution requires that the initial conditions, the boundary conditions, and the parameters contained within the equations be stipulated in exact terms. It is obvious that the solution so derived is a function of these specified, values.
There are at least four ways in which randomness enters the problem. i) the random initial value problem; ii) the random boundary value problem; iii) the random forcing problem when the nonhomogeneous part becomes random and iv) the random parameter problem.
Such randomness is inherent in the environment surrounding the system, the environment being endowed with a large number of degrees of freedom.
This paper considers the problem of groundwater flow in a phreatic aquifer fed by rainfall. The goveming equations are linear second order partial differential equations. Explicit form solutions to this randomly forced equation have been derived in well defined regular boundaries. The paper also provides a derivation of low order moment equations. It contains a discussion on the parameter estimation problem for stochastic partial differential equations.
 Title
 Stochastic partial differential equations in groundwater hydrology
 Journal

Stochastic Hydrology and Hydraulics
Volume 3, Issue 2 , pp 135153
 Cover Date
 198906
 DOI
 10.1007/BF01544077
 Print ISSN
 09311955
 Online ISSN
 1435151X
 Publisher
 SpringerVerlag
 Additional Links
 Topics

 Math. Applications in Geosciences
 Probability Theory and Stochastic Processes
 Statistics for Engineering, Physics, Computer Science, Chemistry & Geosciences
 Numerical and Computational Methods in Engineering
 Math. Appl. in Environmental Science
 Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution
 Keywords

 Stochastic partial differential equations
 maximum likelihood estimation
 parameter estimation
 moment equations
 stodhastic contaminant transport
 Industry Sectors
 Authors

 T. E. Unny ^{(1)}
 Author Affiliations

 1. Dept. of System Design Engineering, University of Waterloo, N2L 3G1, Waterloo, Ontario, Canada