Inverse modeling using PS-InSAR for improved calibration of hydraulic parameters and prediction of future subsidence for Las Vegas Valley, USA

被引:10
|
作者
Burbey, T. J. [1 ]
Zhang, M. [2 ]
机构
[1] Virginia Tech, Blacksburg, VA 24061 USA
[2] Duke Univ, Durham, NC USA
关键词
LAND SUBSIDENCE; NEVADA;
D O I
10.5194/piahs-372-411-2015
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
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 (S-ke and S-kv) 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.
引用
收藏
页码:411 / 416
页数:6
相关论文
共 4 条
  • [1] Inverse modelling using PS-InSAR data for improved land subsidence simulation in Las Vegas Valley, Nevada
    Zhang, Meijing
    Burbey, Thomas J.
    HYDROLOGICAL PROCESSES, 2016, 30 (24) : 4494 - 4516
  • [2] Land subsidence prediction in Beijing based on PS-InSAR technique and improved Grey-Markov model
    Deng, Zeng
    Ke, Yinghai
    Gong, Huili
    Li, Xiaojuan
    Li, Zhenhong
    GISCIENCE & REMOTE SENSING, 2017, 54 (06) : 797 - 818
  • [3] Spatiotemporal modeling of land subsidence using a geographically weighted deep learning method based on PS-InSAR
    Li, Huijun
    Zhu, Lin
    Dai, Zhenxue
    Gong, Huili
    Guo, Tao
    Guo, Gaoxuan
    Wang, Jingbo
    Teatini, Pietro
    SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 799
  • [4] Inverse modeling of interbed storage parameters using land subsidence observations, Antelope Valley, California
    Hoffmann, J
    Galloway, DL
    Zebker, HA
    WATER RESOURCES RESEARCH, 2003, 39 (02)