Torres, Jacob Manuel (2008-05). Analyzing risk and uncertainty for improving water distribution system security from malevolent water supply contamination events. Master's Thesis. Thesis uri icon

abstract

  • Previous efforts to apply risk analysis for water distribution systems (WDS) have not typically included explicit hydraulic simulations in their methodologies. A risk classification scheme is here employed for identifying vulnerable WDS components subject to an intentional water contamination event. A Monte Carlo simulation is conducted including uncertain stochastic diurnal demand patterns, seasonal demand, initial storage tank levels, time of day of contamination initiation, duration of contamination event, and contaminant quantity. An investigation is conducted on exposure sensitivities to the stochastic inputs and on mitigation measures for contaminant exposure reduction. Mitigation measures include topological modifications to the existing pipe network, valve installation, and an emergency purging system. Findings show that reasonable uncertainties in model inputs produce high variability in exposure levels. It is also shown that exposure level distributions experience noticeable sensitivities to population clusters within the contaminant spread area. The significant uncertainty in exposure patterns leads to greater resources needed for more effective mitigation.
  • Previous efforts to apply risk analysis for water distribution systems (WDS) have
    not typically included explicit hydraulic simulations in their methodologies. A risk
    classification scheme is here employed for identifying vulnerable WDS components
    subject to an intentional water contamination event. A Monte Carlo simulation is
    conducted including uncertain stochastic diurnal demand patterns, seasonal demand,
    initial storage tank levels, time of day of contamination initiation, duration of
    contamination event, and contaminant quantity.
    An investigation is conducted on exposure sensitivities to the stochastic inputs
    and on mitigation measures for contaminant exposure reduction. Mitigation measures
    include topological modifications to the existing pipe network, valve installation, and an
    emergency purging system. Findings show that reasonable uncertainties in model inputs
    produce high variability in exposure levels. It is also shown that exposure level
    distributions experience noticeable sensitivities to population clusters within the
    contaminant spread area. The significant uncertainty in exposure patterns leads to
    greater resources needed for more effective mitigation.

publication date

  • May 2008