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Environmental Engineering Research 2009;14(4): 200-210. DOI: https://doi.org/10.4491/eer.2009.14.4.200
Development of Water Quality Modeling in the United States
Robert B. Ambrose, Jr.1, Tim A. Wool2, and Thomas O. Barnwell, Jr.1
1U.S. Environmental Protection Agency (retired)
2U.S. Environmental Protection Agency, Region 4 Water Management Division
Corresponding Author: Robert B. Ambrose, Jr. ,Tel: +01-706-296-5228, Email: rambrose@alum.mit.edu
Received: November 1, 2009;  Accepted: November 17, 2009.
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ABSTRACT
The modern era of water quality modeling in the United States began in the 1960s. Pushed by advances in computer technology as well as environmental sciences, water quality modeling evolved through five broad periods: (1) initial model development with mainframe computers (1960s – mid 1970s), (2) model refinement and generalization with minicomputers (mid 1970s – mid 1980s), (3) model standardization and support with microcomputers (mid 1980s – mid 1990s), (4) better model access and performance with faster desktop computers running Windows and local area networks linked to the Internet (mid 1990s – early 2000s), and (5) model integration and widespread use of the Internet (early 2000s – present). Improved computer technology continues to drive improvements in water quality models, including more detailed environmental analysis (spatially and temporally), better user interfaces and geographic information system software, more accessibility to environmental data from on-line repositories, and more robust modeling frameworks linking hydrodynamics, water quality, watershed and atmospheric models. Driven by regulatory needs and advancing technology, water quality modeling will continue to improve to better address more complicated water bodies and pollutant types, and more complicated management questions. This manuscript describes historical trends in water quality model development in the United States, reviews current efforts, and projects promising future directions.
Keywords: Water quality models | Computing trends | Model development | Model integration
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