Abstract
Global curve-fitting method (GCFM) is regarded as an effective approach in hydrogeological parameter estimation, as it integrates and uses pumping data and water recovery data of a transient pumping test for parameter estimation. The impacts of pumping duration on hydrogeological parameter estimation by GCFM were investigated in the present study using 2 in situ pumping tests and 24 simulated transient pumping tests. Empirical formulas for determining the optimal pumping duration were derived. The study results suggest that pumping duration will have impacts on the accuracy of hydrogeological parameter estimation. When pumping duration is longer than a certain period, relative errors of hydrogeological parameter estimation keep relatively stable within an acceptable limit. Therefore, it is unnecessary to continue the pumping for a very long time after the groundwater level has become stable. When the change rate of drawdown over time (γ) in an observation well located within a distance of 100 m to the pumping well reaches 0.134, the pumping can be stopped. If there are more than one observation wells in a pumping test, the smallest γ value should be selected to determine the optimal pumping duration. This research is meaningful in the instruction of pumping tests, and will reduce test costs greatly.
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Acknowledgments
This research project was jointly supported by the Doctor Postgraduate Technical Project of Chang’an University (CHD2011ZY025 and CHD2011ZY022), the National Natural Science Foundation of China (41172212 and 51009009), the Special Fund for Basic Scientific Research of Central Colleges (CHD2011ZY020 and CHD2012TD003) and the Open Research Fund of State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin (IWHR-SKL-201109). The editor and anonymous reviewers are also acknowledged for their useful comments.
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Li, P., Qian, H., Wu, J. et al. Determining the optimal pumping duration of transient pumping tests for estimating hydraulic properties of leaky aquifers using global curve-fitting method: a simulation approach. Environ Earth Sci 71, 293–299 (2014). https://doi.org/10.1007/s12665-013-2433-9
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DOI: https://doi.org/10.1007/s12665-013-2433-9