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 ter.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’

Relationship between land subsidence and hydraulic head Pumping well

Total stress σ Water pressure Effective stress σ’ Δb is the land subsidence. S k 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) Bedrock Sand 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

Water Depth Subsidence 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 AquiferLayer4 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 million cells

Groundwater flow equation K is the component of the hydraulic conductivity W is the volumetric flux per unit volume of sources or sinks of water S s is the specific storage S ’ s is the specific storage of the interbed K v ’ is the vertical hydraulic conductivity of the interbed The unequilibrated heads within the interbeds can be described by the one-dimensional diffusion equation

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 (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 )

Permanent scatterer velocity maps ( ) showing target velocities in mm/yr for the Las Vegas basin (provided by Youquan, Zhang) mm/year BLUE= Uplift RED= 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 subsidence Observed drawdown APE (Adjoint Parameter Estimation) algorithm and UCODE Inversely Calibrate Hydrologic Parameters MODFLOW Automatically identify suitable parameter zonations

Objective function |h simulated -h observed | |sub simulated -sub observed | 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, S ske and S skv 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.

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