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STOCHASTIC WATER QUALITY CONTROL BY SIMULATION 1
Author(s) -
Shih Chia Shun
Publication year - 1975
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.1975.tb00678.x
Subject(s) - probabilistic logic , reliability (semiconductor) , computer science , sensitivity (control systems) , water quality , environmental science , continuous simulation , water resources , quality (philosophy) , surface runoff , reliability engineering , operations research , hydrology (agriculture) , simulation , engineering , ecology , power (physics) , philosophy , physics , geotechnical engineering , epistemology , quantum mechanics , artificial intelligence , electronic engineering , biology
In order to handle the probabilistic nature of treated waste effluent characteristics, the reliability associated with a basin‐wide quality management goal has been included in the modeling process. Meanwhile, the quantitative and qualitative variations of the irrigation return flows and the urban runoff also exhibit a probabilistic nature in terms of both temporal and spatial measurements. Computer simulation has been utilized in analyzing the reliability and sensitivity of a river basin quality management. In this paper, a simulation‐optimization scheme for the determination of policies in regional water quality management was developed subject to specific water quality standards. Stochastic quadratic programming techniques have been used in the optimization analysis. A series of simulation models describing the statistical water quality control phenomena was developed. Meanwhile, a simulation analysis for the description of probabilistic nature of the stream quality was developed for the control strategies of the return flows in the regional management system. As an illustration of the applicability of this water quality control approach, the major wastewater treatment facilities in the San Antonio River Basin were analyzed. The sensitivity analysis was conducted to assess the most satisfying strategies for a regional water quality management system subject to probabilistic standards.