HR: 1340h
AN: H43E-0413    [Abstracts]
TI: Cross-Sectional And Longitudinal Uncertainty Propagation In Drinking Water Risk Assessment
AU: * Tesfamichael, A A
EM: akliluanges@cc.usu.edu
AF: Civil and Environmental Engineering, Utah State University, 1600 Canyon Road, Logan, UT 84321
AU: Jagath, K J
EM: jkalu@cc.usu.edu
AF: Civil and Environmental Engineering, Utah State University, 1600 Canyon Road, Logan, UT 84321
AB: Pesticide residues in drinking water can vary significantly from day to day. However, drinking water quality monitoring performed under the Safe Drinking Water Act (SDWA) at most community water systems (CWSs) is typically limited to four data points per year over a few years. Due to limited sampling, likely maximum residues may be underestimated in risk assessment. In this work, a statistical methodology is proposed to study the cross-sectional and longitudinal uncertainties in observed samples and their propagated effect in risk estimates. The methodology will be demonstrated using data from 16 CWSs across the US that have three independent databases of atrazine residue to estimate the uncertainty of risk in infants and children. The results showed that in 85% of the CWSs, chronic risks predicted with the proposed approach may be two- to four-folds higher than that predicted with the current approach, while intermediate risks may be two- to three-folds higher in 50% of the CWSs. In 12% of the CWSs, however, the proposed methodology showed a lower intermediate risk. A closed-form solution of propagated uncertainty will be developed to calculate the number of years (seasons) of water quality data and sampling frequency needed to reduce the uncertainty in risk estimates. In general, this methodology provided good insight into the importance of addressing uncertainty of observed water quality data and the need to predict likely maximum residues in risk assessment by considering propagation of uncertainties.
DE: 1803 Anthropogenic effects
DE: 1857 Reservoirs (surface)
DE: 1860 Runoff and streamflow
DE: 1869 Stochastic processes
DE: 1871 Surface water quality
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting