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Sequential and joint hydrogeophysical inversion using a field-scale groundwater model with ERT and TDEM data

Daan Herckenrath,G. Fiandaca,E. Auken,P. Bauer‐Gottwein

Published 2013 in Hydrology and Earth System Sciences

ABSTRACT

Increasingly, ground-based and airborne geophys- ical data sets are used to inform groundwater models. Re- cent research focuses on establishing coupling relationships between geophysical and groundwater parameters. To fully exploit such information, this paper presents and compares different hydrogeophysical inversion approaches to inform a field-scale groundwater model with time domain electromag- netic (TDEM) and electrical resistivity tomography (ERT) data. In a sequential hydrogeophysical inversion (SHI) a groundwater model is calibrated with geophysical data by coupling groundwater model parameters with the inverted geophysical models. We subsequently compare the SHI with a joint hydrogeophysical inversion (JHI). In the JHI, a geo- physical model is simultaneously inverted with a groundwa- ter model by coupling the groundwater and geophysical pa- rameters to explicitly account for an established petrophysi- cal relationship and its accuracy. Simulations for a synthetic groundwater model and TDEM data showed improved esti- mates for groundwater model parameters that were coupled to relatively well-resolved geophysical parameters when em- ploying a high-quality petrophysical relationship. Compared to a SHI these improvements were insignificant and geophys- ical parameter estimates became slightly worse. When em- ploying a low-quality petrophysical relationship, groundwa- ter model parameters improved less for both the SHI and JHI, where the SHI performed relatively better. When comparing a SHI and JHI for a real-world groundwater model and ERT data, differences in parameter estimates were small. For both

PUBLICATION RECORD

  • Publication year

    2013

  • Venue

    Hydrology and Earth System Sciences

  • Publication date

    2013-10-18

  • Fields of study

    Geology, Engineering, Environmental Science

  • Identifiers
    DOI 10.5194/HESS-17-4043-2013
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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