Environmental management with knowledge of uncertainty: A methylmercury case study



In Oregon's Willamette River Basin, health advisories currently limit consumption of fish that have accumulated methylmercury to levels posing a potential health risk for humans. Under the Clean Water Act, these advisories represent an impairment of the beneficial use of fish consumption and create the requirement for a mercury total maximum daily load. A percent load reduction for total mercury was determined by comparing mercury levels in surface water to a water column guidance value linked to the protection of specified beneficial uses. In this case study, we discuss how probabilistic (Monte Carlo) methods were used to quantify uncertainty in the water column guidance value, how they provided decision makers with knowledge as to the probability of any given water column guidance value affording human health protection for methylmercury, and how this knowledge affected decisions as to a mercury load reduction for the Willamette River Basin. Through consultations with stakeholders, a water column guidance value of 0.92 ng/L (a median for higher trophic level fish) was chosen from among a suite of values of differing probabilities. The selected water column guidance value, when compared with ambient total mercury levels, indicated that a 50% probability of achieving the tissue criterion would require a load reduction of about 26%. Having and working with an explicit knowledge of uncertainty was not easy for many decision makers or stakeholders. However, such knowledge gave them more informed choices, a better understanding of what a specific choice of water column guidance value could mean in terms of achieving protectiveness, and led to a lower load reduction than suggested by a purely deterministic analysis. Nonetheless, more attention must be given to developing management, communication, and regulatory frameworks that can effectively use the greater knowledge of uncertainty afforded by probabilistic methods.