Modeling In Situ Bioremediation of Perchlorate-Contaminated Groundwater

Abstract

Perchlorate-contaminated groundwater is a significant problem for the Department of Defense and the United States Air Force. An innovative technology was recently developed which uses dual-screened treatment wells to mix an electron donor into perchlorate-contaminated groundwater in order to effect in situ bioremediation of the perchlorate by indigenous perchlorate reducing bacteria without the need to extract the contaminated water from the subsurface. In this study, a model that simulates operation of the technology is calibrated and validated using 761 days of observational data obtained from a field-scale technology evaluation project. A genetic algorithm was used with the first 113 days of data to derive a set of best-fit parameters to describe perchlorate reduction kinetics for the electron donor, citrate, utilized in the evaluation study. The calibrated parameter values were then used to predict technology performance from day 114 through day 761. Measurements of goodness-of-fit statistics indicate the model appears to qualitatively reproduce the salient characteristics of the observed data when utilizing the new best-fit parameter values. Therefore, it appears the model may be a useful tool for designing and operating this technology at other perchlorate-contaminated sites.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2007
Accession Number
ADA465182

Entities

People

  • Roland E. Secody

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Bacteria
  • Bioremediation
  • Chemical Synthesis
  • Chemistry
  • Department Of Defense
  • Ecology
  • Environmental Protection
  • Evolutionary Algorithms
  • Genetic Algorithms
  • Groundwater
  • Health Services
  • Microorganisms
  • Public Health
  • Statistics
  • United States

Fields of Study

  • Environmental science

Readers

  • Computational Modeling and Simulation
  • Groundwater Contamination Remediation.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Biotechnology
  • Biotechnology - Bioremediation
  • Microelectronics