Aquifer Parameter Estimation Using Kalman Filters

by Subhash Chander, Prof. in Civ. Engrg.; Indian Inst. of Tech., Delhi, Hauz Khas, New Delhi, 110029, India,
Sushil K. Goyal, Research Scholar in Civ. Engrg.; Indian Inst. of Tech., Delhi, Hauz Khas, New Delhi, 110029, India,
Prakash N. Kapoor, Asst. Prof. in Civ. Engrg.; Indian Inst. of Tech., Delhi, Hauz Khas, New Delhi, 110029, India,


Serial Information: Journal of the Irrigation and Drainage Division, 1981, Vol. 107, Issue 1, Pg. 25-33


Document Type: Journal Paper

Abstract: An iterated extended Kalman filter (IEKF) has been used for the estimation of aquifer parameters in the presence of uncertainties in the system and noise in the measurements. The technique is sequential and each additional observation reduces the error covariance of the parameter estimates. The method is computationally efficient and gives the confidence limits of the parameter estimates. Only a few observations are sufficient to provide a reasonable estimate of the aquifer parameters. Actual aquifer test data for confined nonleaky and leaky aquifers have been analyzed and the results compared with those obtained using the known technique. The IEKF method gives less residual square error and eliminates the subjectivity involved in the conventional curve matching techniques.

Subject Headings: Aquifers | Parameters (statistics) | Kalman filters | Filters | Uncertainty principles | Errors (statistics) | Computing in civil engineering | Confidence intervals

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