MARKOV-CHAIN MODEL FOR SEASONAL-WATER QUALITY MANAGEMENT

A nonstationary Markov chain approach to designing seasonal risk-equiv alent water-quality management strategies is presented in this paper. Unlike many existing models for determining seasonal waste load alloca tions, this approach considers a wider range of possible low-flow cond itions than those in the observed historical record. It explicitly inc orporates the probabilistic relationships between low-flow data at adj acent gauging stations. The approach is demonstrated for the managemen t of biochemical oxygen demanding (BOD) waste on the Willamette River in Oregon. The results of this application are compared with those of an existing model for seasonal risk-equivalent waste management. The t reatment strategies derived for the Markov chain approach are similar, but slightly more conservative than those for the alternative program . Moreover, the ability of these treatment strategies to achieve an ac ceptable probability of water-quality violation is potentially less se nsitive to the length of the historical record.