A More Accurate and Powerful
Tool for Managing
Groundwater Resources and
Predicting Land Subsidence: an
application to Las Vegas Valley
Zhang, Meijing
Dept. of Geosciences, Virginia Tech
Advisor: T.J. Burbey
Relationship between land subsidence and hydraulic
head
Surface Water
Aquifer System
Groundwater
Figure from
Http://www.environment.scotland.gov.uk/our_environment/water/groundwa
ter.aspx
Relationship between land subsidence and hydraulic
head
  p  '
Total stress σ
Water
pressure
Effective
stress σ’
Relationship between land subsidence and hydraulic
head
Pumping well
According toTerzaghi's one-dimensional consolidation
theory, deformation occurs only in vertical direction
d '  dp   gdh
b  Sk h
Total stress σ
Water
pressure
Effective
stress σ’
Δb is the land subsidence. Sk is the skeletal storage
coefficient , and Δh is the change in hydraulic head
Sand and
gravel
Bedrock
Sand and
A gravel
Silt and clay
interbed
A
A’
Silt and
clay
interbed
A’
Bedrock
Fault
Generalized surficial
geologic map of Las
Vegas Valley
Geologic cross-section (A-A’)
illustrates the stratigraphic and
fault relations interpreted from
well log data. (From Bell, 2008)
Groundwater has been
pumped since 1905; More
Than 1.5 m of subsidence
has been observed since
1935
Pumping and
Recharging
wells
To help mitigate the
ongoing occurrence of
land subsidence, an
artificial recharge
program was initiated in
1989
Pumping
well
Recharge
well
Bedrock
Fault
A significant percentage of the subsidence is delayed
relative to the water-level decline
210
0
Water Depth
Subsidence
235
20
260
40
285
60
310
1996
1998
2000
2002 2004
2006
Seasonal and long-term subsidence and water level
patterns at the Lorenzi site, Las Vegas, Nevada
A significant percentage of the subsidence is delayed
from the water-level decline
What causes subsidence and delayed drainage?
Subsidence bowls are offset from the major pumping center.
Over time, the valley has yielded a very complex subsidence
pattern, much more so than the water-level distribution
Subsidence map for Las Vegas Valley from 1992 to 1997 (From
Bell, 2002)
To better manage groundwater resources and predict future
subsidence we have updated and developed a more accurate
groundwater management model for Las Vegas Valley
Near-surface
Aquifer
Developed-zone Aquifer
Deep-zone Aquifer
Layer1
Layer2
Layer3
Layer4
The vertical conceptual model layer distribution
(From Yan, 2007)
The model incorporates MODFLOW with the SUB
(subsidence) and HFB (horizontal flow barrier) packages
50m-Cell
1.7 million cells
Faults
Extended simulation period from 1912-2010
Groundwater flow equation

h 
h 
h
h
( K xx )  ( K yy )  ( K zz )  W  S s
x
x y
y z
z
z
The unequilibrated heads within the interbeds can be described
by the one-dimensional diffusion equation
 2h Ss h

2
z
Kv t
K is the component of the hydraulic conductivity
W is the volumetric flux per unit volume of sources
or sinks of water
Ss is the specific storage
S’s is the specific storage of the interbed
Kv’ is the vertical hydraulic conductivity of the interbed
Sources of observation data
Groundwater
monitoring network
Pumping and
Recharging
wells
Groundwater level data Las Vegas Valley Water District and
can be obtained from
State Engineer’s Office will provide
the USGS
needed pumping and artificial recharge
data for the extended period of record
Land subsidence data
Benchmarks established
in 1935 and 1963
GPS
Currently only
one continuous
GPS station has
been monitored
for more than a
few years
Subsidence map for
the period 1963-1980
(from Bell, 2008) (left)
InSAR and
PS-InSAR
Provides
surface
deformations
from
interferometric
synthetic
aperture radar
(data available
from 1992-2010)
Permanent scatterer velocity maps (2002-2010) showing target
velocities in mm/yr for the Las Vegas basin
BLUE= Uplift
RED= Subsidence
mm/year
(provided by Youquan, Zhang)
Limitation of the traditional inverse
method
How to
specify the
number of
zones ???
Where
each zone
is for each
parameter
???
?
??
The objective of this investigation
Observed land
subsidence
MODFLOW
APE (Adjoint Parameter
Estimation) algorithm and
UCODE
Automatically
identify suitable
parameter zonations
Inversely Calibrate
Hydrologic Parameters
Observed
drawdown
Objective function
Minimize
|hsimulated-hobserved|
+
|subsimulated-subobserved|


h is the groundwater level
sub is land subsidence
To verify the validity of the algorithm, a MODFLOW 2000
hypothetical model is developed, and the APE algorithm
is executed to create approximate spatial zonations of T,
Sske and Sskv
Estimated
Transmissivity
Zones after 3
Iterations
True Synthetic
Transmissivity
Zones
Note that the colors in each frame only indicate different zones and
the colors (number of zones) change after each iteration
The estimated zonations approach the true
parameter zonations
Estimated Specific
Storage Zones
after 3 Iterations
True Synthetic
Specific Storage
Zones
Observed vs. simulated
(a) final drawdown, and
(b) final subsidence.
Where do we go from here?



Our next goal is to apply the APE algorithm to
Las Vegas Valley to build a complete
management model for water purveyors
If necessary, global methods will be
employed
A parallel method will be incorporated
Conclusions



An updated groundwater management model
for Las Vegas Valley model is being developed.
We have outlined an automated parameter
estimation process that can greatly aid the
calibration of ground water flow models like
those of LVV.
Accurate parameterization will provide a far
more accurate and precise groundwater model
that can be used to more accurately predict
future trends on the basis of future pumping
patterns.
Thanks!