Fault detection for salinity sensors in the Columbia estuary

Cynthia Archer, Antonio Baptista, Todd K. Leen

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Sensors deployed in the Columbia River estuary gather information on physical dynamics and changes in estuary habitat. Of these sensors, conductivity sensors are particularly susceptible to biofouling, which gradually degrades sensor response and corrupts critical data. Several weeks may pass before degradation is visibly detected. Since the onset time of biofouling is unknown, an indeterminate amount of measurement data is corrupted. To speed detection and minimize data loss, we develop automatic biofouling detectors based on machine learning approaches for these conductivity sensors. We demonstrate that our detectors identify biofouling at least as reliably as human experts. In addition, these detectors provide accurate estimates of biofouling onset time. Real-time detectors installed during the summer of 2001 produced no false alarms yet detected all episodes of sensor degradation before the field staff.

Original languageEnglish (US)
Pages (from-to)SWC31-SWC310
JournalWater Resources Research
Issue number3
StatePublished - Mar 2003


  • Biofouling
  • Fault detection
  • Novelty detection
  • Salinity measurement
  • Sensor degradation
  • Sensor failure

ASJC Scopus subject areas

  • Water Science and Technology


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