a more accurate and powerful tool for managing groundwater resources and predicting land subsidence:...
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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
Figure from Http://www.environment.scotland.gov.uk/our_environment/water/groundwater.aspx
Relationship between land subsidence and hydraulic head
Surface Water
Groundwater
Aquifer System
Relationship between land subsidence and hydraulic head
Total stress σ
Water pressure
Effective stress σ’
' p
Relationship between land subsidence and hydraulic head
Pumping well
Total stress σ
Water pressure
Effective stress σ’
hSb kgdhdpd '
Δb is the land subsidence. Sk is the skeletal storage coefficient , and Δh is the change in hydraulic head
According toTerzaghi's one-dimensional consolidation theory, deformation occurs only in vertical direction
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)
BedrockSand and gravel
Silt and clay interbed
A A’Bedrock
Sand and gravel
Silt and clay interbed
Fault
A
A’
Groundwater has been pumped since 1905; More Than 1.5 m of subsidence has been observed since 1935
Bedrock
Fault
Pumping well Recharge
well
To help mitigate the ongoing occurrence of land subsidence, an artificial recharge program was initiated in 1989
Pumping and Recharging wells
0
20
40
60
210
235
310
285
260
1996 1998 2000 2002 2004 2006
Water DepthSubsidence
Seasonal and long-term subsidence and water level patterns at the Lorenzi site, Las Vegas, Nevada
A significant percentage of the subsidence is delayed relative to the water-level decline
What causes subsidence and delayed drainage?
A significant percentage of the subsidence is delayed from the water-level decline
Subsidence map for Las Vegas Valley from 1992 to 1997 (From Bell, 2002)
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
To better manage groundwater resources and predict future subsidence we have updated and developed a more accurate groundwater management model for Las Vegas Valley
Layer2
Deep-zone Aquifer Layer4
Developed-zone Aquifer
Near-surface Aquifer
Layer3
Layer1
The vertical conceptual model layer distribution (From Yan, 2007)
Faults
50m-Cell
The model incorporates MODFLOW with the SUB (subsidence) and HFB (horizontal flow barrier) packages
Extended simulation period from 1912-2010
1.7 million cells
Groundwater flow equation
z
hSW
z
hK
zy
hK
yx
hK
x szzyyxx
)()()(
K is the component of the hydraulic conductivityW is the volumetric flux per unit volume of sources or sinks of waterSs is the specific storageS’s is the specific storage of the interbedKv’ is the vertical hydraulic conductivity of the interbed
The unequilibrated heads within the interbeds can be described by the one-dimensional diffusion equation
t
h
K
S
z
h
v
s
2
2
Sources of observation data
Groundwater level data can be obtained from the USGS
Groundwater monitoring network
Pumping and Recharging wells
Las Vegas Valley Water District and State Engineer’s Office will provide needed pumping and artificial recharge data for the extended period of record
Subsidence map for the period 1963-1980 (from Bell, 2008) (left)
GPS
Land subsidence data
InSAR and PS-InSAR
Benchmarks established in 1935 and 1963
Currently only one continuous GPS station has been monitored for more than a few years
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
(provided by Youquan, Zhang)
mm
/year
BLUE= UpliftRED= Subsidence
??
?
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
subsidenceObserved drawdown
APE (Adjoint Parameter Estimation) algorithm and
UCODE
Inversely CalibrateHydrologic Parameters
MODFLOW
Automatically identify suitable
parameter zonations
Objective function
|hsimulated-hobserved|
|subsimulated-subobserved|
Minimize
+
h is the groundwater level sub is land subsidence
Estimated Transmissivity Zones after 3 Iterations
True Synthetic Transmissivity Zones
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
Note that the colors in each frame only indicate different zones and the colors (number of zones) change after each iteration
Estimated Specific Storage Zones after 3 Iterations
True Synthetic Specific Storage Zones
The estimated zonations approach the true parameter zonations
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!