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Approximate Analytical/Numerical Solutions to the Groundwater Flow Problem. CWR 6536 Stochastic Subsurface Hydrology. 3-D Saturated Groundwater Flow. K(x,y,z) random hydraulic conductivity field f (x,y,z) random hydraulic head field No analytic solution exists to this problem - PowerPoint PPT Presentation
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Approximate Analytical/Numerical Solutions to the Groundwater Flow
Problem
CWR 6536
Stochastic Subsurface Hydrology
3-D Saturated Groundwater Flow
• K(x,y,z) random hydraulic conductivity field• (x,y,z) random hydraulic head field• No analytic solution exists to this problem• 3-D Monte Carlo very CPU intensive• Look for approximate analytical/numerical solutions
to the 1st and 2nd ensemble moments of the head field
zK
zyK
yxK
x
0
First-order Perturbation Methods• Bakr et al. Water Resources Research 14(2) p. 263-271,
April 1978• Mizell et al. Water Resources Research 18(4) p. 1053-
1067, August 1982• Gelhar, Stochastic Subsurface Hydrology Ch. 4 Sections
4.1-4.4• McLaughlin and Wood Water Resources Research 24(7)
p. 1037-1060, July 1988• James and Graham, Advances in Water Resources,
22(7),711-728, 1999.
Re-write equation in terms of Ln K
K
zz
K
zyy
K
yxx
K
x
zz
K
Kzyy
K
Kyxx
K
Kx
zz
K
zK
yy
K
yK
xx
K
x
K
ln0
lnlnln0
1110
0
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Small Perturbation Methods• Expand input random variables into the sum of a
potentially spatially variable mean and a small perturbation around this mean, i.e.
• Assume solution of the output random variable can be approximate as a converging power series in the small parameter .
lnK 1)(Var 0)(E )()(
)()()(
xfxfxLnKExF
xfxFxLnK
....)()()()( 22
10 xxxx ii
Small Perturbation Methods
• Insert expansion into governing equation
• Collect terms of similar order
...)()()()()(
...)()()(0
22
10
22
102
xxxxfxF
xxx
)()()()()(0
)()()()()(0
)()()(0
12222
0112
002
xxfxxFx
xxfxxFx
xxFx
Solve Mean Head Distribution• Evaluate mean head distribution to order 2
• Solve equations for E[i(x)]
• Therefore to first order
....)()()()( 22
10 xExExEExE ii
)()()()()(0
)()()()()(0
)()()(0
1222
0112
002
xxfExExFxE
xxfExExFxE
xxFx
)()( 0 xxE
Solve Head Covariance Function
• Evaluate head covariance to order 2
• Need to determine
....)'()(
...)'()'(...)()(
)'(...)'()'()'(
)(...)()()(
)'()'()()()',(
112
22
122
1
022
10
022
10
xxE
xxxx
xxxx
xxxxE
xExxExExxP
)'()( 11 xxE
Solve for Head Covariance
• Post-Multiply equation for (x) by (x’):
• Take (x’) inside derivatives with respect to x:
• Take expected values:
• Need Head-Log Conductivity Crosscovariance
)'()()()()()(0 10112 xxxfxxFx
)()',()',()()',(
)()'()()'()()()'()(0
02
0111112
11111xxxPxxPxFxxP
xxxfExxExFxxE
f
)()'()()'()()()'()(0 0111112 xxxfxxxFxx
)',(1
xxPf
Solve for Head-Log Conductivity Cross-Covariance
• Pre-Multiply equation for (x’) by f(x):
• Take f(x) inside derivatives with respect to x’:
• Take expected values:
• Need log-conductivity auto-covariance
)'()'()'()'()'()(0 0''1''12' xxfxxFxxf xxxxx
)'()',()',()'()',(
)'()'()()'()()'()'()(0
0''''2'
0''1''12'
11xxxPxxPxFxxP
xxfxfExxfExFxxfE
xffxfxxfx
xxxxx
)'()'()()'()()'()'()(0 0''1''12' xxfxfxxfxFxxf xxxxx
)',( xxPff
System of Approximate Moment Eqns
• Use 0(x), as best estimate of (x)
• Use 2=P(x,x) as measure of uncertainty
• Use P(x,x’) and Pf(x,x’) for cokriging to optimally estimate f or based on field observations
)()',()',()()',(0
)'()',()',()'()',(0
)()()(0
02
0''''2'
002
11111
11
xxxPxxPxFxxP
xxxPxxPxFxxP
xxFx
f
xffxfxxfx