• Title of article

    A multi-species reactive transport model to estimate biogeochemical rates based on single-well push–pull test data

  • Author/Authors

    Phanikumar، نويسنده , , Mantha S. and McGuire، نويسنده , , Jennifer T.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2010
  • Pages
    8
  • From page
    997
  • To page
    1004
  • Abstract
    Push–pull tests are a popular technique to investigate various aquifer properties and microbial reaction kinetics in situ. Most previous studies have interpreted push–pull test data using approximate analytical solutions to estimate (generally first-order) reaction rate coefficients. Though useful, these analytical solutions may not be able to describe important complexities in rate data. This paper reports the development of a multi-species, radial coordinate numerical model (PPTEST) that includes the effects of sorption, reaction lag time and arbitrary reaction order kinetics to estimate rates in the presence of mixing interfaces such as those created between injected “push” water and native aquifer water. The model has the ability to describe an arbitrary number of species and user-defined reaction rate expressions including Monod/Michelis–Menten kinetics. The FORTRAN code uses a finite-difference numerical model based on the advection-dispersion-reaction equation and was developed to describe the radial flow and transport during a push–pull test. The accuracy of the numerical solutions was assessed by comparing numerical results with analytical solutions and field data available in the literature. The model described the observed breakthrough data for tracers (chloride and iodide-131) and reactive components (sulfate and strontium-85) well and was found to be useful for testing hypotheses related to the complex set of processes operating near mixing interfaces.
  • Keywords
    Sorption , dispersion , Inverse modeling , reaction , Mobile–immobile , Pump test , Microbial processes , Push–pull test , In situ rate estimation , PPTEST
  • Journal title
    Computers & Geosciences
  • Serial Year
    2010
  • Journal title
    Computers & Geosciences
  • Record number

    2287789