Spatiotemporal analysis of the groundwater head variation caused by natural stimuli using independent component analysis and continuous wavelet transform
Journal
Journal of Hydrology
Journal Volume
590
Date Issued
2020
Author(s)
Hsiao, C.-T.
Abstract
Understanding the contribution of natural stimuli (e.g., rainfall and river stage) to the spatiotemporal head variations of groundwater basins is essential for the management of regional groundwater resources. However, head variations are mixed signals, leading to difficulty in extracting the variations contributed by a single stimulus. To address this issue, a systematic approach that integrates independent component analysis (ICA) and continuous wavelet transform (CWT) is proposed for spatiotemporal analyses, and the effect of the natural stimuli on the spatiotemporal head variations is measured. We found that CWT can better explain the physical meanings of the derived independent components (ICs), which are the features of the stimuli extracted from the spatiotemporal groundwater head observations through ICA. We also found that the head variations are affected not only by the natural stimuli but also by the hydrogeological structures, as the spatial variations of the ICA weightings are consistent with the spatial variations of the hydrogeological structures. Additionally, the features of river stage variations sourced from the deposition in the estuary area are observed. Accordingly, the proposed method can quantify the effect of the natural stimuli on the spatiotemporal head variations, as well as reveal the features of the complicated hydrogeological structure of a groundwater basin. © 2020 Elsevier B.V.
Subjects
Continuous wavelet transform; Hydrogeological structure; Independent component analysis; Signal separation; Spatiotemporal analysis
SDGs
Other Subjects
Groundwater; Groundwater resources; Independent component analysis; Continuous Wavelet Transform; Continuous wavelet transforms; Groundwater basins; Hydrogeological structures; Independent component analysis(ICA); Independent components; Spatial variations; Spatiotemporal analysis; Wavelet transforms; groundwater; groundwater resource; hydraulic head; hydrogeology; spatiotemporal analysis; water management; wavelet analysis
Type
journal article