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A STATISTICALLY BASED MATHEMATICAL WATER QUALITY MODEL FOR A NON‐ESTUARINE RIVER SYSTEM 1
Author(s) -
Tirabassi Michael A.
Publication year - 1971
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.1752-1688.1971.tb05058.x
Subject(s) - black box , computer science , quality (philosophy) , water quality , mathematical model , data collection , variable (mathematics) , statistics , hydrology (agriculture) , mathematics , artificial intelligence , engineering , ecology , mathematical analysis , philosophy , geotechnical engineering , epistemology , biology
A mathematical model has been formulated, solely through the use of the mathematical statistics, for the purpose of predicting river water quality without reference to the causal chemical, biological and physical relationships. In a sense, this is a “black box” approach wherein with a known input, one may reliably predict the output. The use of a main force statistical method for predicting river‐water quality can provide accurate predictive information with a minimum of time and money expended if a sufficiently large data base is available for the river system in question. What has been lacking in the past is a model which is not only statistically significant but contains only those water quality parameters which contribute significantly to the estimation of the dependent variable. The model which is herein described discusses the formulation procedure, data collection requirements, model hypothesis testing and significance procedures, and finally validation methods employed in verifying the final model equations. A description of how the simulated results are employed in the forecasting procedure is also developed.