Abstract

Abstract. Las Vegas Valley has had a long history of surface deformation due to groundwater pumping that began in the early 20th century. After nearly 80 years of pumping, PS-InSAR interferograms have revealed detailed and complex spatial patterns of subsidence in the Las Vegas Valley area that do not coincide with major pumping regions. High spatial and temporal resolution subsidence observations from InSAR and hydraulic head data were used to inversely calibrate transmissivities (T), elastic and inelastic skeletal storage coefficients (Ske and Skv) of the developed-zone aquifer and conductance (CR) of the basin-fill faults for the entire Las Vegas basin. The results indicate that the subsidence observations from PS-InSAR are extremely beneficial for accurately quantifying hydraulic parameters, and the model calibration results are far more accurate than when using only water-levels as observations, and just a few random subsidence observations. Future predictions of land subsidence to year 2030 were made on the basis of existing pumping patterns and rates. Simulation results suggests that subsidence will continue in northwest subsidence bowl area, which is expected to undergo an additional 11.3 cm of subsidence. Even mitigation measures that include artificial recharge and reduced pumping do not significantly reduce the compaction in the northwest subsidence bowl. This is due to the slow draining of thick confining units in the region. However, a small amount of uplift of 0.4 cm is expected in the North and Central bowl areas over the next 20 years.

Highlights

  • Las Vegas Valley (Fig. 1), encompassing an area of 4150 km2 in southern Nevada, has experienced a long history of rapid population growth and consequent growing rates of groundwater pumping that have led to large water-level declines of as much as 90 m (Burbey, 1995) and subsequent extensive and complex subsidence patterns with four regional subsidence bowls, with the Northwest bowl experiencing more than 1.5 m of land subsidence (Bell et al, 2002) in this structural basin filled with more than a thousand meters of unconsolidated to semi-consolidated heterogeneous sediments (Fig. 1b) (Amelung et al, 1999)

  • Final simulated water levels are compared with observed values across the entire Las Vegas Valley in Fig. 4 after the years 1982 and 2006

  • An updated numerical groundwater and subsidence model was created by updating observations of water level and land subsidence through the processing of new InSAR scenes for 2002–2010 and refined discretization

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Summary

Introduction

Las Vegas Valley (Fig. 1), encompassing an area of 4150 km in southern Nevada, has experienced a long history of rapid population growth and consequent growing rates of groundwater pumping that have led to large water-level declines of as much as 90 m (Burbey, 1995) and subsequent extensive and complex subsidence patterns with four regional subsidence bowls, with the Northwest bowl experiencing more than 1.5 m of land subsidence (Bell et al, 2002) in this structural basin filled with more than a thousand meters of unconsolidated to semi-consolidated heterogeneous sediments (Fig. 1b) (Amelung et al, 1999). Yan (2008) has recently included seasonal InSAR data from 1993 to 2002 into the original Las Vegas model (coarse grid) These subsidence data produced a more accurate and robust model, but no efforts were made to reparametrize (new parameter zonations) or rediscretize the model. In this investigation we use newly acquired basin-wide temporal PS-InSAR and water-level data from 2002 to 2010 as observations to inversely estimate aquifer parameters from a more finely discretized groundwater flow model, which extends the previous modeling efforts of Yan (2008) and Yan and Burbey (2008). The goal is to create a robust groundwater management model for the entire Las Vegas basin that accurately reflects the subsidence and recovery patterns observed during the past 100 years of aquifer development

Numerical model for Las Vegas Valley
Initial conditions and observations
Inverse modeling and calibration
Results and predictions
Conclusions

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