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Optimal Wastewater Loading under Conflicting Goals and Technology Limitations in a Riverine System
Author(s) -
Rafiee Mojtaba,
Lyon Steve W.,
Zahraie Banafsheh,
Destouni Georgia,
Jaafarzadeh Nemat
Publication year - 2017
Publication title -
water environment research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.356
H-Index - 73
eISSN - 1554-7531
pISSN - 1061-4303
DOI - 10.2175/106143017x14839994523866
Subject(s) - compromise , convergence (economics) , computer science , wastewater , fuzzy logic , function (biology) , risk analysis (engineering) , quality (philosophy) , water quality , environmental science , mathematical optimization , biochemical engineering , environmental economics , management science , environmental engineering , business , engineering , economics , mathematics , social science , philosophy , epistemology , artificial intelligence , sociology , evolutionary biology , biology , economic growth , ecology
This paper investigates a novel simulation‐optimization (S‐O) framework for identifying optimal treatment levels and treatment processes for multiple wastewater dischargers to rivers. A commonly used water quality simulation model, Qual2K, was linked to a Genetic Algorithm optimization model for exploration of relevant fuzzy objective‐function formulations for addressing imprecision and conflicting goals of pollution control agencies and various dischargers. Results showed a dynamic flow dependence of optimal wastewater loading with good convergence to near global optimum. Explicit considerations of real‐world technological limitations, which were developed here in a new S‐O framework, led to better compromise solutions between conflicting goals than those identified within traditional S‐O frameworks. The newly developed framework, in addition to being more technologically realistic, is also less complicated and converges on solutions more rapidly than traditional frameworks. This technique marks a significant step forward for development of holistic, riverscape‐based approaches that balance the conflicting needs of the stakeholders.