期刊
GROUND WATER
卷 41, 期 1, 页码 66-71出版社
GROUND WATER PUBLISHING CO
DOI: 10.1111/j.1745-6584.2003.tb02569.x
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An algorithm was designed to statistically estimate the areal distribution of water-table altitude. The altitude of the water table was bounded below by the minimum water-table surface and above by the land surface. Using lake elevations and stream stages, and interpolating between lakes and streams, the minimum water-table surface was generated. A multiple linear regression among the minimum water-table altitude, the difference between land-surface and minimum water-table altitudes, and the water-level measurements from surficial aquifer system wells resulted in a consistently high correlation for all groups of physiographic regions in Florida. A simple linear regression between land-surface and water-level measurements resulted in a root-mean-square residual of 4.23 in, with residuals ranging from -8.78 to 41.54 in. A simple linear regression between the minimum water table and the water-level measurements resulted in a root-mean-square residual of 1.45 in, with residuals ranging from -7.39 to 4.10 in. The application of the multiple linear regression presented herein resulted in a root-mean-square residual of 1.05 in, with residuals ranging from -5.24 to 5.63 in. Results from complete and partial F tests rejected the hypothesis of eliminating any of the regressors in the multiple linear regression presented in this study.
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