Proposed Correlation Model for Groundwater Level Prediction Based on River Stage Considering Changes in Hydrological and Geological Conditions
Publication: Journal of Hydrologic Engineering
Volume 24, Issue 10
Abstract
The groundwater level (GWL) is an important subsoil condition that affects water resource management, soil contamination analysis, and infrastructure design. In this study, the spatial and time-dependent variation of the GWL was analyzed and a GWL prediction model based on river stage (RS) is proposed. A series of finite-element analyses were performed for the various geological and hydrological conditions. The results were used to quantify the response of the GWL to the RS for various permeability and RS conditions. A correlation model of the GWL and RS was established and the model parameters were evaluated to yield design equations. Implementation steps for the method were derived, including an adjustment procedure for cases with multiple RS fluctuations. Two case studies were used to verify the validity of the method by comparing its predictions with both the measured values and results from an artificial neural network (ANN). The correlation model produced well-predicted results in both the shape and values compared with the measured GWL.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available in a repository online in accordance with funder data retention policies (https://drive.google.com/open?id=1DI0q_KOo69zVh0-Xzoz2ePRVmdELOo_0).
Acknowledgments
This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), the Korea Institute of Energy Technology Evaluation and Planning (KETEP), and the Ministry of Trade, Industry and Energy (MOTIE), with grants funded by the government of Korea (2016R1D1A1A09919098 and 20174030201480).
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Journal of Hydrologic Engineering
Volume 24 • Issue 10 • October 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: Nov 18, 2018
Accepted: Jun 11, 2019
Published online: Aug 7, 2019
Published in print: Oct 1, 2019
Discussion open until: Jan 7, 2020
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