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COMPARISON OF REGRESSION AND TIME‐SERIES METHODS FOR SYNTHESIZING MISSING STREAMFLOW RECORDS 1
Author(s) -
Beauchamp J.J.,
Downing D.J.,
Railsback S.F.
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.tb05410.x
Subject(s) - streamflow , autocorrelation , regression , series (stratigraphy) , time series , environmental science , hydrology (agriculture) , regression analysis , streams , flow (mathematics) , statistics , meteorology , geography , mathematics , geology , computer science , drainage basin , cartography , geotechnical engineering , paleontology , computer network , geometry
Regression and time‐series techniques have been used to synthesize and predict the stream flow at the Foresta Bridge gage from information at the upstream Pohono Bridge gage on the Merced River near Yosemite National Park. Using the available data from two time periods (calendar year 1979 and water year 1986), we evaluated the two techniques in their ability to model the variation in the observed flows and in their ability to predict stream flow at the Foresta Bridge gage for the 1979 time period with data from the 1986 time period. Both techniques produced reasonably good estimates and forecasts of the flow at the downstream gage. However, the regression model was found to have a significant amount of autocorrelation in the residuals, which the time‐series model was able to eliminate. The time‐series technique presented can be of great assistance in arriving at reasonable estimates of flow in data sets that have large missing portions of data.