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WATER QUALITY MODEL CALIBRATION: A COMPARISON OF INPUT AND OUTPUT ERROR CRITERIA 1
Author(s) -
Little Keith W.,
Lauria Donald T.
Publication year - 1989
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.1752-1688.1989.tb05390.x
Subject(s) - calibration , estimator , monte carlo method , representation (politics) , errors in variables models , series (stratigraphy) , computer science , least squares function approximation , quality (philosophy) , mathematics , algorithm , mathematical optimization , statistics , paleontology , philosophy , epistemology , politics , political science , law , biology
A common framework for the analysis of water resources systems is the input‐parameter‐output representation. The system, described by its parameters, is driven by inputs and responds with outputs. To calibrate (estimate the parameters) models of these systems requires data on both inputs and outputs, both of which are subject to random errors. When one is uncertain as to whether the predominant source of error is associated with inputs or outputs, uncertainty also exists as to the correct specification of a calibration criterion. This paper develops and analyzes two alternative least squares criteria for calibrating a numerical water quality model. The first criterion assumes that errors are associated with inputs while the second assumes output errors. Statistical properties of the resulting estimators are examined under conditions of pure input or output error and mixed error conditions from a theoretical perspective and then using simulated results from a series of Monte Carlo experiments.