Probabilistic Approach to Initial Dilution of Ocean Outfalls

• Published in: Water environment research 1994-09, Vol.66 (6), p.787-793
• Main Authors: Huang, Hening, Proni, John R., Tsai, John J.
• Format: Article
• Language: English
• Subjects: Datasets; Determinism; dilution; effluent; Effluent discharges; Marine; Mathematical models; Modeling; ocean; Ocean currents; Ocean dumping; Oceans; outfall; Probabilities; Q1; Research Papers; Sea water; Statistics; Time series; Waste disposal
• ISSN: 1061-4303; 1554-7531
• DOI: 10.2175/WER.66.6.4

This paper presents a probabilistic approach to develop initial dilution criteria or standards for ocean outfall design and environmental impact assessment of effluent discharges. In contrast to a currently used worst case approach, in which a particular combination of parameters affecting initial dilution is specified and an associated initial dilution is calculated using a deterministic dilution model, the probabilistic approach provides a framework for combining data for the parameters which are often available in the form of time series or described in statistics. The result of the probabilistic approach is a description of initial dilution as a function of cumulative or exceedance probability, from which the exposure risk level for the marine environment can be estimated and criteria or standards can be defined. The proposed methodology basically consists of implementing a probabilistic method with a deterministic initial dilution model. The probabilistic method could be time domain simulation, Monte Carlo simulation, or first-order uncertainty analysis; while the deterministic initial dilution model could be a mathematical model, a physical model, or an empirical equation. A case study is presented of the Miami-Central Outfall on the east coast of South Florida to compare the probabilistic approach with the worst case approach. In this case study, time domain simulation using actual data sets was employed to generate a time series of initial dilution (dilutions were calculated using a semi-empirical equation). Some statistics of initial dilution were then obtained from the simulated dilution time series. For this case study, the worst case dilution is 17.3 (minimum surface or near-surface dilution) and the associated cumulative probability is 5.4%.