Bayesian Markov chain Monte Carlo Inversion of Time-Lapse Geophysical Data To Characterize the Vadose Zone

TY - ABST

T1 - Bayesian Markov chain Monte Carlo Inversion of Time-Lapse Geophysical Data To Characterize the Vadose Zone

AU - Scholer, Marie

AU - Irving, James

AU - Zibar, Majken Caroline Looms

AU - Nielsen, Lars

AU - Holliger, Klaus

PY - 2011

Y1 - 2011

N2 - Geophysical methods have the potential to provide valuable information on hydrological properties in the unsaturated zone. In particular, time-lapse geophysical data, when coupled with a hydrological model and inverted stochastically, may allow for the effective estimation of subsurface hydraulic parameters and their corresponding uncertainties. In this study, we use a Bayesian Markov-chain-Monte-Carlo (MCMC) inversion approach to investigate how much information regarding vadose zone hydraulic properties can be retrieved from time-lapse crosshole GPR data collected at the Arrenaes field site in Denmark during a forced infiltration experiment.

AB - Geophysical methods have the potential to provide valuable information on hydrological properties in the unsaturated zone. In particular, time-lapse geophysical data, when coupled with a hydrological model and inverted stochastically, may allow for the effective estimation of subsurface hydraulic parameters and their corresponding uncertainties. In this study, we use a Bayesian Markov-chain-Monte-Carlo (MCMC) inversion approach to investigate how much information regarding vadose zone hydraulic properties can be retrieved from time-lapse crosshole GPR data collected at the Arrenaes field site in Denmark during a forced infiltration experiment.

M3 - Conference abstract for conference

T2 - GeoHydro 2011, Quebec, Canada

Y2 - 28 August 2011

ER -