Abstract
For modeling groundwater flow in formationscale fractured
media, no general method exists for scaling the highly
hete
rogeneous hydraulic conductivity data to model
parameters. The
deterministic approach is limited in representing the
heterogeneity
of a medium and the application of fracture network
models has
both conceptual and practical limitations as far as
sitescale
studies are concerned. This study investigates the
applicability of
stochastic continuum modeling at the scale of data
support. No
scaling of the field data is involved, and the original
variability is
preserved throughout the modeling. Contributions of
various
aspects to the total uncertainty in the modeling
prediction can
also be determined with this approach.
Data from five crystalline rock sites in Finland are
analyzed. The
issues considered include stochastic versus deterministic
nature of
the data, statistical similarities and differences
between various
data sets, types of theoretical distributions,
distribution parameters
and their confidence limits, spatial trends and
autocorrelation
structures, role of measuring equipment detection limit
in these
analyses, and needs for ergodicity assumptions. A
stochastic
treatment is applied for data from which significant
fracture
zones are excluded.
With the statistical properties determined, groundwater
flow in
selected regions is modeled by Monte Carlo simulation to
obtain
estimates of uncertainties in the flow computations,
given the
amount and location of hydrological data available. For
each
problem several hundred permeability realizations are
generated,
for which the flow equation is solved. Theoretical
verification
simulations comparing the results with analytically
derived
expressions demonstrate the insignificant role of
numerical
inaccuracies. Simulations describing realistic bedrock
crosssections are carried out both with and without
spatial
correlation. Uncertainty in the head prediction is
higher, and
more widely spread, when autocorrelation is taken into
account.
Predicted flow rates through a twodimensional example
crosssection can vary over three orders of magnitude.
Conditioning with borehole data in the middle of this
section
reduces the uncertainty by one order of magnitude. This
effect is
significant compared to the corresponding reduction
achieved by
increasing the data base with no regard to the location
of this
data. The effect of the formula used for interpreting the
original
well test is also found to be a significant factor in the
total
analysis.
Original language  English 

Qualification  Doctor Degree 
Awarding Institution 

Award date  17 Jun 1994 
Place of Publication  Espoo 
Publisher  
Print ISBNs  9513846229 
Publication status  Published  1994 
MoE publication type  G4 Doctoral dissertation (monograph) 
Keywords
 ground water
 flow
 models
 simulation
 fractures
 mathematical models
 numerical methods
 probability theory
 analyzing
 stochastic processes
 Monte Carlo method
 numerical analysis
 computation
 hydrology
 permeability
 crystalline rocks
 heterogeneity
 radioactive wastes
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Niemi, A. (1994). Modeling flow in fractured medium. Uncertainty analysis with stochastic continuum approach: Dissertation. VTT Technical Research Centre of Finland.