CHROTRAN

Chromium Remediation Plume
a massively parallel numerical simulator for in situ biogeochemical remediation of heavy metals in heterogeneous aquifers

CHROTRAN can simulate sophisticated, multi-scale biogeochemical remediation processes:

  • Groundwater remediation of heavy metals and other contaminants
  • Bioremediation and chemical remediation
  • Multi-dimensional processes from laboratory to field scale
  • Physical and chemical heterogeneity
  • Field pilot studies and long-term deployments

CHROTRAN is based upon the existing PFLOTRAN code framework, utilizing:

  • Fully coupled subsurface flow and reactive transport
  • Highly parallelized computational solvers
  • Large number of unknown variables
  • Complex model domains and highly refined computational grids
  • Existing chemistry capabilities (mineral precipitation/dissolution, aqueous complexation)

CHROTRAN can be coupled to MADS (Model Analysis & Decision Support) for:

  • Model inversion and calibration
  • Sensitivity analysis
  • Uncertainty quantification
  • Decision analysis and support

CHROTRAN has been developed to address groundwater remediation at the LANL (Los Alamos National Laboratory, NM) legacy waste sites and contaminated areas.

Theory & Research

  • Publications
    • Hansen, S.K., Pandey, S., Karra, S., Vesselinov, V.V., CHROTRAN 1.0: A mathematical and computational model for in situ heavy metal remediation in heterogeneous aquifers, Geoscientific. Model Development, 10.5194/gmd-10-4525-2017, 10, 4525–4538, 2017. PDF
    • Pandey, S., S., Karra, S., & Vesselinov, V.V. (In Preparation). A multicomponent reactive transport model of in situ redox manipulation for remediation of chromium contaminated groundwater.
  • Presentations
    • Vesselinov, V V, O'Malley, D., Katzman, D., Decision Analyses for Groundwater Remediation, LA-UR-17-21909, Los Alamos National Laboratory (LANL), 2017. PDF.
  • Reports

Download

CHROTRAN source and example files are available on GitHub

Documentation

Examples how CHROTRAN can be applied are available at GitHub