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dc.contributor.authorZhang, Meijingen_US
dc.date.accessioned2014-11-12T09:00:34Z
dc.date.available2014-11-12T09:00:34Z
dc.date.issued2014-11-10en_US
dc.identifier.othervt_gsexam:3840en_US
dc.identifier.urihttp://hdl.handle.net/10919/50833
dc.description.abstractThe 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.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.rightsThis Item is protected by copyright and/or related rights. Some uses of this Item may be deemed fair and permitted by law even without permission from the rights holder(s), or the rights holder(s) may have licensed the work for use under certain conditions. For other uses you need to obtain permission from the rights holder(s).en_US
dc.subjectParameter estimationen_US
dc.subjectadaptive multi-scale methoden_US
dc.subjectDREAMen_US
dc.subjecttransmissivityen_US
dc.subjectspecific storage coefficienten_US
dc.subjectland subsidenceen_US
dc.subjectInSARen_US
dc.subjectLas Vegas Valleyen_US
dc.titleQuantifying high-resolution hydrologic parameters at the basin scale using InSAR and inverse modeling, Las Vegas Valley, NVen_US
dc.typeDissertationen_US
dc.contributor.departmentGeosciencesen_US
dc.description.degreePHDen_US
thesis.degree.namePHDen_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineGeosciencesen_US
dc.contributor.committeechairBurbey, Thomas Jen_US
dc.contributor.committeememberHole, John Andrewen_US
dc.contributor.committeememberSchreiber, Madeline Een_US
dc.contributor.committeememberWiddowson, Mark Aen_US
dc.contributor.committeememberBorggaard, Jeffrey Ten_US


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