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Electrical resistivity imaging data for hydrogeological and geological hazard investigations in Taiwan

This data article presents electrical resistivity imaging (ERI) data and inverted models with the objectives of hydrogeological characterization, land subsidence studies, and geological structural detections in Taiwan. The ERI data for hydrogeological studies includes 5 ERI profiles from Changhua, 3...

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Detalles Bibliográficos
Autores principales: Chang, Ping-Yu, Doyoro, Yonatan Garkebo, Lin, Ding-Jiun, Puntu, Jordi Mahardika, Amania, Haiyina Hasbia, Kassie, Lingerew Nebere
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439298/
https://www.ncbi.nlm.nih.gov/pubmed/37600127
http://dx.doi.org/10.1016/j.dib.2023.109377
Descripción
Sumario:This data article presents electrical resistivity imaging (ERI) data and inverted models with the objectives of hydrogeological characterization, land subsidence studies, and geological structural detections in Taiwan. The ERI data for hydrogeological studies includes 5 ERI profiles from Changhua, 33 from Yunlin, 36 from Yilan, 23 from Taichung, 23 from Chiayi and Tainan, and 23 from Taipei basins. In addition, time-lapse ERI profiles are presented for 10 ERI from Yilan, 10 ERI from Pingtung, 11 ERI from Taichung, and 31 ERI from Minzu basins. Moreover, 10 ERI data were used to detect the Rusui Fault, 12 for the Qishan Fault, 13 for the Yuli Fault, and 25 for the Shanyi Fault. This data article contains 265 ERI profiles with a total survey length of 59,905 m. A single ERI profile contains hundreds to thousands of subsurface apparent resistivity data points. The data was collected between 2010 and 2022 from different regions of Taiwan. The main findings from the ERI data consisted here were reported by Lin et al. [1] for the Pingtung basin, Chang et al. [2] for the Minzu basin, and Jordi et al. [3] for the Taichung basin in order to estimate hydraulic parameters and characterize the aquifer systems. The ERI data presented here can be used for a variety of hydrogeological, geological, engineering, and environmental applications, and it can be further interpreted using machine learning and statistical methods. Therefore, the ERI data will helps in various subsurface applications, academic research, and educational purposes.