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This study utilized electrical resistivity imaging (ERI) to investigate subsurface characteristics near Nicolaus Copernicus University Polar Station on the western Spitsbergen-Kaffiøyra Plain island in the Svalbard archipelago. Surveys along two lines, LN (148 m) collected in 2022 and 2023, and ST (40 m) collected in 2023, were conducted to assess resistivity and its correlation with ground temperatures. The LN line revealed a 1- to 2-m-thick resistive unsaturated outwash sediment layer, potentially indicative of permafrost. Comparing the LN resistivity result between 2022 and 2023, a 600 Ohm.m decrease in the unsaturated active layer in 2023 was observed, attributed to a 5.8 °C temperature increase, suggesting a link to global warming. ERI along the ST line depicted resistivity, reaching its minimum at approximately 1.6 m, rising to over 200 Ohm.m at 4 m, and slightly decreasing to around 150 Ohm.m at 7 m. Temperature measurements from the ST line's monitoring strongly confirmed that the active layer extends to around 1.6 m, with permafrost located at greater depths. Additionally, water content distribution in the ST line was estimated after temperature correction, revealing a groundwater depth of approximately 1.06 m, consistent with measurements from the S4 borehole on the ST line. This study provides valuable insights into Arctic subsurface dynamics, emphasizing the sensitivity of resistivity patterns to climate change and offering a comprehensive understanding of permafrost behavior in the region. [ABSTRACT FROM AUTHOR]

We used transient electromagnetic (TEM) to map the hydrogeological structures in the Choushui River Alluvial Fan in Yunlin County of central Taiwan. A total of 63 TEM measurements were collected using the FASTSNAP system with 50 × 50 m in-loop configurations in the middle and distal fan. The 1D model, based on prior information, was constructed from the inverted soundings. Results showed a thin, resistive shallow layer and a 40 m low-resistive (6–42 ohm-m) zone beneath it. High-resistive zones (50–170 ohm-m) were found from 50–120 m depth, and low-resistive zones were revealed below 120 m in some areas. Results were consistent with resistivity and lithology logs from nearby wells. The inverted TEM models provide reliable subsurface information when prior informations of vertical electrical sounding and TEM were considered. We interpolated resistivity at 10 m, 50 m, 100 m, and 160 m depth from the 1D model results to produce a slice map of the area, which indicated variations, trends, and depths of the sediment deposits. The TEM method successfully identified the hydrogeological structures, showing that the upper 40 m of sediment acts as a confining layer for the aquifer structure from 50 m to 120 m depth. [ABSTRACT FROM AUTHOR]

This study aims to apply geophysical methods to determine the Specific Yield (Sy) and Groundwater Level (GWL) in an unconfined aquifer of the Pingtung Plain in South Taiwan. Sy is an important hydraulic parameter for assessing groundwater potential. Obtaining specific yield for a large area is impractical due to the limited coverage and the high cost of the pumping test, which limits the potential evaluation of regional groundwater. Therefore, we used time-lapse Electrical Resistivity Imaging (ERI) to determine the Sy and GWL. Seasonal variations were considered when measuring time-lapse resistivity for five different months in 2019. We calculated the Sy and GWL from inverted resistivity data using empirical formulas and the soil–water characteristic curve (SWCC). We first used Archie's law to calculate the relative saturation change with depth for each ERI profile, and then we used the Van Genuchten (VG) and Brooks–Corey (BC) empirical equations to estimate Sy and GWL. Finally, we compared the obtained GWL to the existing observation well to verify the findings of our study. The results showed that the VG and BC are able to predict Sy and GWL; however, the BC result is less consistent with the observation well result. In the study area, the dry season GWL ranged from 24.5 m to 35.2 m for the VG results and from 25.7 m to 35.5 m for the BC results. The wet season GWL ranged from 26.5 m to 38.9 m for the VG and from 26.4 m to 38.2 m for the BC results. The spatial distribution of the GWL shows a high gradient of GWL in the northeastern region, induced by significant proximal fan recharge. The determined spatial distribution of Sy varies from 0.15 to 0.21 for the VG and 0.14 to 0.20 for the BC results, indicating the study area has significant potential for groundwater resources. Therefore, nondestructive resistivity imaging can be used to aid in the determination of hydraulic parameters. [ABSTRACT FROM AUTHOR]

We examined the uncertainty of the two-dimensional (2D) resistivity method using conceptual cavity models. The experimental cavity study was conducted to validate numerical model results. Spatial resolution and sensitivity to resistivity perturbations were also assessed using checkerboard tests. Conceptual models were simulated to generate synthetic resistivity data for dipole-dipole (DD), pole-dipole (PD), Wenner–Schlumberger (WS), and pole-pole (PP) arrays. The synthetically measured resistivity data were inverted to obtain the geoelectric models. The highest anomaly effect (1.46) and variance (24,400 Ω·m) in resistivity data were recovered by the DD array, whereas the PP array obtained the lowest anomaly effect (0.60) and variance (2401 Ω·m) for the shallowest target cavity set at 2.2 m depth. The anomaly effect and variance showed direct dependency on the quality of the inverted models. The DD array provided the highest model resolution that shows relatively distinct anomaly geometries. In contrast, the PD and WS arrays recovered good resolutions, but it is challenging to determine the correct anomaly geometries with them. The PP array reproduced the lowest resolution with less precise anomaly geometries. Moreover, all the tested arrays showed high sensitivity to the resistivity contrasts at shallow depth. The DD and WS arrays displayed the higher sensitivity to the resistivity perturbations compared to the PD and PP arrays. The inverted models showed a reduction in sensitivity, model resolution, and accuracy at deeper depths, creating ambiguity in resistivity model interpretations. Despite these uncertainties, our modeling specified that two-dimensional resistivity imaging is a potential technique to study subsurface cavities. We inferred that the DD array is the most appropriate for cavity surveys. The PD and WS arrays are adequate, while the PP array is the least suitable for cavity studies. [ABSTRACT FROM AUTHOR]

In this study, we attempt to establish an alternative method for estimating the groundwater levels and the specific yields of an unconfined aquifer for the evaluation of potential groundwater reservoirs. We first converted the inverted resistivity into the normalized water content. Then, we inverted the parameters of the Brooks-Corey model from the vertical profiles of the water content by assuming that the suction head was in proportion to the elevation regarding a predefined base level. Lastly, we estimated the groundwater level, the theoretical specific yield, and the specific yield capacity from the Brooks-Corey parameters at every survey site in the study area. The contour maps of the time-lapse groundwater levels show that the groundwater flows downstream, with a higher hydraulic gradient near the river channel than in the area away from the main channel. We conclude that the estimated maximum specific yield capacities are consistent with that derived from the pumping tests in the nearby observation well. Additionally, the specific yield capacities are only three quarters to two thirds of the theoretical specific yields derived from the difference between the residual and saturated water contents in the Brooks-Corey model. We conclude that the distribution pattern of the specific yields had been subjected to the distribution of natural river sediments in the Minzu Basin, since the modern channel was artificially modified. Although we had to make some simple assumptions for the estimations, the results show that the surface resistivity surveys provide reasonable estimations of the hydraulic parameters for a preliminary assessment in an area with few available wells. [ABSTRACT FROM AUTHOR]

We aim to develop a comprehensive tunnel lining detection method and clustering technique for semi-automatic rebar identification in order to investigate the ten tunnels along the South-link Line Railway of Taiwan (SLRT). We used the Ground Penetrating Radar (GPR) instrument with a 1000 MHz antenna frequency, which was placed on a versatile antenna holder that is flexible to the tunnel's condition. We called it a Vehicle-mounted Ground Penetrating Radar (VMGPR) system. We detected the tunnel lining boundary according to the Fresnel Reflection Coefficient (FRC) in both A-scan and B-scan data, then estimated the thinning lining of the tunnels. By applying the Hilbert Transform (HT), we extracted the envelope to see the overview of the energy distribution in our data. Once we obtained the filtered radargram, we used it to estimate the Two-dimensional Forward Modeling (TDFM) simulation parameters. Specifically, we produced the TDFM model with different random noise (0–30%) for the rebar model. The rebar model and the field data were identified with the Hierarchical Agglomerative Clustering (HAC) in machine learning and evaluated using the Silhouette Index (SI). Taken together, these results suggest three boundaries of the tunnel lining i.e., the air–second lining boundary, the second–first lining boundary, and the first–wall rock boundary. Among the tunnels that we scanned, the Fangye 1 tunnel is the only one in category B, with the highest percentage of the thinning lining, i.e., 13.39%, whereas the other tunnels are in category A, with a percentage of the thinning lining of 0–1.71%. Based on the clustered radargram, the TDFM model for rebar identification is consistent with the field data, where k = 2 is the best choice to represent our data set. It is interesting to observe in the clustered radargram that the TDFM model can mimic the field data. The most striking result is that the TDFM model with 30% random noise seems to describe our data well, where the rebar response is rough due to the high noise level on the radargram. [ABSTRACT FROM AUTHOR]

Hydraulic conductivity (K) is crucial for groundwater studies and is conventionally obtained through pumping tests, which are costly due to well installation, resulting in a limited amount of data. Recent studies have addressed this limitation by estimating K through the integration of a pumping-test K and electrical resistivity measurements. While this approach is suitable for local areas, it cannot readily be applied to determine K fields for the composite fan delta. This study proposes and demonstrates an advanced method to estimate the K's spatial distribution of a composite fan delta. The proposed method included data classification, linear regression, and kriging interpolation. Data classification was conducted using a physical-based zonation method. The K and formation factor (F) data pairs were classified into several groups. Linear regression was used to develop K-F mapping for each group. The regression results showed a good correlation between K and F in each group. These K-F mappings were verified by additional pumping tests. These results indicate that estimation errors were between 7 m/day and 58 m/day, and the correlation coefficient of each data group was greater than 0.8. Based on these regression equations and ordinary kriging method, the detailed K spatial distribution of the study area was derived. According to these results, the proposed method is efficient and economical to delineate K's spatial features for regional groundwater systems and can benefit groundwater-related studies. [ABSTRACT FROM AUTHOR]