Seasonal Water Quality Management Given Sparse Databy Andrews K. Takyi, Univ of Manitoba, Winnipeg, Canada,
Barbara J. Lence, Univ of Manitoba, Winnipeg, Canada,
Document Type: Proceeding Paper
Part of: Water Management in the '90s: A Time for Innovation
Abstract: An approach for designing robust seasonal water quality management programs for river basins with sparse or short flow records is presented. This approach uses Markov chain modelling and linear regression relationships between low flow records at adjacent gauging stations to calculate transition probabilities for low flow states of the water quality system. The robustness of the solutions derived from the Markov chain approach is demonstrated for a seasonal uniform waste treatment management model for BOD waste discharges on the Willamette River in Oregon. The results of this application show that management decisions based on the Markov chain approach may be more successful at maintaining the acceptable water quality goal than existing seasonal waste management programs, especially for river basins with sparse historical flow records.
Subject Headings: Water quality | Quality control | Waste management | Seasonal variations | Hydrologic models | Water flow | Information management | Rivers and streams | Hydrologic data | Oregon
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