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Abstract:Theoretical well functions have been derived over the years to predict ground water level behaviour in aquifer systems under stress owing to groundwater extraction. The drawdown data collected during pump tests are typically analysed using graphical curve-matching procedures to estimate aquifer parameters based on these well functions. Difficulty in aquifer characteristic identification and parameter estimation may arise when the field data do not perfectly match the drawdown curves obtained from the well functions. The present study provides a new method for the interpretation of aquifer pump tests which supplements the existing curve-matching procedures in case ideal conditions do not exist; the proposed method provides a greater degree of flexibility in the data analysis for diagnostic tool purposes. The method, referred to as the Incremental Area Method (IAM) is based on integrating the logarithmic-based drawdown curves within a discrete time and matching the results with a corresponding time integral of the Theis (1935) Well Function which governs ideal confined aquifers. The application of the proposed method to synthetically generated data and field data showed that IAM represents a viable method which yields information on potential non-idealness of the aquifer and provides aquifer parameter estimates thus potentially overcoming drawdown data curve-matching difficulties.

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The standard practice for assessing aquifer parameters is to match groundwater drawdown data obtained during pumping tests against theoretical well function curves specific to the aquifer system being tested. The shape of the curve derived from the logarithmic time derivative of the drawdown data is also very frequently used as a diagnostic tool to identify the aquifer system in which the pumping test is being conducted. The present study investigates the incremental area method (IAM) to serve as an alternative diagnostic tool for the aquifer system identification as well as a supplement to the aquifer parameter estimation procedure. The IAM based diagnostic curves for ideal confined, leaky, bounded and unconfined aquifers have been derived as part of this study, and individual features of the plots have been identified. These features were noted to be unique to each aquifer setting, which could be used for rapid evaluation of the aquifer system. The effectiveness of the IAM methodology was investigated by analyzing field data for various aquifer settings including leaky, unconfined, bounded and heterogeneous conditions. The results showed that the proposed approach is a viable method for use as a diagnostic tool to identify the aquifer system characteristics as well as to support the estimation of the hydraulic parameters obtained from standard curve matching procedures.

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