EXH AR024681: Sensitivity Analysis Mixing Zone Parameters (cont.) — Stormwater Mgmt

A 1999 technical memorandum from Parametrix, Inc. analyzes whether stormwater discharged near Des Moines Creek meets Washington State dissolved copper water quality criteria, using a Monte Carlo simulation model. The analysis finds that copper levels in the stormwater effluent consistently exceed water quality standards regardless of background ambient concentrations, with dilution factors generally less than 2. The study evaluates several potential remedies, including increased onsite detention, expanded mixing zones, and water effect ratio adjustments, finding that the Water Effect Ratio (WER) is the most influential factor in achieving compliance.

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Memorandum dated September 7, 1999 from Jim Dexter of Parametrix, Inc. to Paul Fendt and Linda Logan (cc: Ken Ludwa), Project No. 55-2912-61-01, Port of Seattle Stormwater Management. Analyzes sensitivity of mixing zone parameters for dissolved copper water quality criteria (WQC) compliance at Des Moines Creek point of compliance (NW Ponds outlet), using SDS-3 outfall effluent. Uses Monte Carlo simulation (@RISK spreadsheet) and TOPRANK sensitivity analysis per EPA Technical Support Document For Water Quality Based Toxics Control (1991). Addresses five questions: ambient copper concentration effect on WQC compliance, sensitivity of WQC calculations to parameters, water effect ratio (WER) testing outcomes, stormwater release rate control, and hardness effects. Key parameters analyzed include ambient receiving water flow, effluent stormwater flow, ambient and effluent pollutant concentrations, dissolved copper WQC, allowable mixing volume (vol_factor), WER (range 1–6), and onsite detention/flow control (0–10 cfs). TOPRANK results rank WER (#1), vol_factor (#2), and onsite detention (#3) by sensitivity. Expected WQC exceedence values range from approximately -2.691 to 18.354 µg/L depending on inputs; copper WQC baseline calculated at 4.21 µg/L. HSPF model output used for flow probability distributions.

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