Estimating the Average Magnitude of Pumping Surrounding Monitoring Wells Using Signal Processing
Publication: Journal of Hydrologic Engineering
Volume 28, Issue 4
Abstract
The groundwater level observed from a monitoring well is a mixed signal resulting from different stimulations. It is challenging to obtain a specific component from this mixed signal. This is the case for obtaining the pumping component from a monitoring well in an area with many pumping wells. This study developed a signal processing method to extract the average magnitude of pumping (AMP) from the observed groundwater signals. AMP represents the variation over time in the groundwater level caused by pumping surrounding a monitored well. It is obtained from a digital filtering procedure. The use of a Gaussian high-pass filter removes the long-term trends from the groundwater signal and reveals a high-frequency signal that is usually hidden. After applying frequency analysis and verifying it by fast Fourier transformation (FFT), the pumping frequency was identified. The pumping frequency is set as the center frequency for a band-pass filter to obtain AMP. To validate and understand the factor influencing AMP, a three-dimensional (3D) numerical model was constructed to simulate artificial groundwater fluctuations. The synthetic case study showed that the pumping rate and the distance between the pumping wells and the monitoring well are factors that control AMP. We further applied this methodology to evaluate AMP for three monitoring wells in Tuku Township, located in the Chou-Shui Chi alluvial fan in central Taiwan. The results showed a negative correlation between the AMP variation and rainfall events, describing long-term trends for pumping and the influence of pumping on the groundwater level variation with time. Furthermore, the results revealed the scale of the AMP at each monitoring well, and the area with a higher AMP had a higher drawdown magnitude daily. Finally, the average pumping rate of a region can be estimated using AMP.
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Data Availability Statement
Some data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request. Some data, models, or code used during the study were provided by a third party; direct requests for these materials may be made to the provider as indicated in the acknowledgments.
Acknowledgments
The authors would like to thank the Water Resources Agency, MOEA, Taiwan and ROC Central Weather Bureau, Taiwan for making the data available. Technical support from the AnCAD Company in New Taipei City is also appreciated.
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Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 28 • Issue 4 • April 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Feb 24, 2022
Accepted: Dec 29, 2022
Published online: Feb 10, 2023
Published in print: Apr 1, 2023
Discussion open until: Jul 10, 2023
ASCE Technical Topics:
- Analysis (by type)
- Engineering fundamentals
- Environmental engineering
- Equipment and machinery
- Filters
- Filtration
- Gaussian process
- Groundwater
- Groundwater depletion
- Mathematics
- Models (by type)
- Probability
- Pumps
- Signal processing
- Stochastic processes
- Three-dimensional models
- Water (by type)
- Water and water resources
- Water level
- Water management
- Water supply
- Water treatment
- Wells (water)
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