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A simple method is presented for estimating the specific storage of a confined aquifer from an overdamped slug test in a fully penetrating well. This method is based on the quasi-steady flow model developed previously by the authors, simplified to decoupled algebraic equations upon using Hvorslev's estimate of the hydraulic conductivity. The model equations are solved efficiently on a spreadsheet sequentially. The ability of the algebraic method to estimate the specific storage of a confined aquifer is assessed against slug test data from three field cases and against sets of synthetic data generated with the rigorous Cooper-Bredehoeft-Papadopulos method, which is used as reference. The algebraic method estimates the order of magnitude of the specific storage correctly in all three field cases, with two of them arithmetically very close to the Cooper-Bredehoeft-Papadopulos solution, while the hydraulic parameters computed with the numerical quasi-steady solution nearly match the reference values. In the cases of synthetic data, the algebraic method estimates the specific storage reliably when the storage parameter α equals 10−4 and within an order of magnitude when α equals 10−5. [ABSTRACT FROM AUTHOR]

Slug tests offer an efficient method for estimating the hydraulic parameters of an aquifer without water pumping. Two inverse methods are typically used to assess the slug test data and derive parameter estimates of a confined aquifer. The first method provides estimates of both hydraulic conductivity and specific storage, is visual (hence difficult to automate), and is based on the transient-flow analytical solution of Cooperet al.The second method, proposed by Hvorslev, is very straightforward, but provides only hydraulic conductivity estimates. In this study, we are testing the recently proposed quasi-steady method of Koussis and Akylas, which enables the estimation of both hydraulic parameters and, furthermore, can be easily implemented in computer code or an electronic spreadsheet. This quasi-steady method was coupled with the shuffled complex evolution optimization method to fully automate parameter estimation. This coupling is tested using data from field observations, synthetic data produced from the transient-flow analytical solution, and synthetic data with noise. The results show the usefulness and the limitations of the proposed method.Editor Z.W. Kundzewicz [ABSTRACT FROM AUTHOR]