Browsing by Author "Zhang, Meijing"

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    Quantifying high-resolution hydrologic parameters at the basin scale using InSAR and inverse modeling, Las Vegas Valley, NV
    Zhang, Meijing (Virginia Tech, 2014-11-10)
    The overall goal of this dissertation is to determine and develop optimal strategies for inversely calibrating 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, and to investigate future trends of land subsidence in Las Vegas Valley. This dissertation consists of three separate stand-alone chapters. Chapter 2 presents a discrete adjoint parameter estimation (APE) algorithm for automatically identifying suitable hydraulic parameter zonations from hydraulic head and subsidence measurements. Chapter 3 compares three different inversion strategies to determine the most accurate and computationally efficient method for estimating T and Ske and Skv at the basin scale: the zonation method (ZM), the adaptive multi-scale method and the Differential Evolution Adaptive Metropolis Markov chain Monte Carlo scheme (DREAM MCMC). Chapter 4 outlines a fine-scale numerical model capable of capturing far more hydrologic detail than any previously developed model of Las Vegas Valley The new model is calibrated using high-resolution InSAR data and hydraulic head data from 1912 to 2010. The calibrated model is used to investigate the influence of faults and their potential role on influencing clay thicknesses and land subsidence distributions, and to investigate future trends of land subsidence in Las Vegas Valley.