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HESS | Articles | Volume 24, issue 2
Hydrol. Earth Syst. Sci., 24, 501–513, 2020
https://doi.org/10.5194/hess-24-501-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Hydrol. Earth Syst. Sci., 24, 501–513, 2020
https://doi.org/10.5194/hess-24-501-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 03 Feb 2020

Research article | 03 Feb 2020

Efficient screening of groundwater head monitoring data for anthropogenic effects and measurement errors

Christian Lehr and Gunnar Lischeid

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Cited articles

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Coppola, E., Szidarovszky, F., Poulton, M., and Charles, E.: Artificial Neural Network Approach for Predicting Transient Water Levels in a Multilayered Groundwater System under Variable State, Pumping, and Climate Conditions, J. Hydrol. Eng., 8, 348–360, https://doi.org/10.1061/(ASCE)1084-0699(2003)8:6(348), 2003. 
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A screening method for the fast identification of well-specific peculiarities in hydrographs of groundwater head monitoring networks is suggested and tested. The only information required is a set of time series of groundwater head readings all measured at the same instants of time. The results were used to check the data for measurement errors and to identify wells with possible anthropogenic influence.
A screening method for the fast identification of well-specific peculiarities in hydrographs of...
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