Browsing by Author "Chang, Ping-Yu"

Now showing 1 - 5 of 5

Applying FDEM, ERT and GPR at a site with soil contamination: A case study
(2015-10-01)
Wang, Tzu-Pin
;
Chen, Chien-Chih
;
Tong, Lun-Tao
;
Chang, Ping-Yu
;
Chen, Yi-Chieh
This study employed the combination of three methods, namely the Frequency Domain Electromagnetic (FDEM), Electrical Resistivity Tomography (ERT) and Ground Penetrating Radar (GPR) to evaluate a heavy-metal contaminated site for both pre- and post-remediation investigations. The main goals were to verify the position and the integrity of the underground storage tanks (UST), and to determine the effectiveness of remediation to ensure no contaminants remained at the site. In general, the GPR survey was effective at locating shallowly buried objects. However, due to the highly conductive nature of the heavy-metal laden sludge, the GPR signals were attenuated severely. Thus, the first attempt to use GPR in the pre-remediation investigation did not achieve the desired results and other methods were deployed. The existence of the UST and the sludge within were confirmed by ERT and the UST shape was mapped by FDEM. The principal remediation scheme was soil replacement by replacing the contaminated soil with clean silt Based on the distinctive property differences of the contaminated soil and the clean silt, the completion of the remediation was confirmed by the differences between pre-remediation and post-remediation in GPR, ERT and FDEM results. (C) 2015 Elsevier B.V. All rights reserved.
Constructing the Apparent Geological Model by Fusing Surface Resistivity Survey and Borehole Records
(2019-07-01)
Tsai, Jui-Pin
;
Chang, Ping-Yu
;
Yeh, Tian-Chyi J.
;
Chang, Liang-Cheng
;
Hsiao, Chin-Tsai
We constructed an apparent geological model with resistivity data from surface resistivity surveys. We developed a data fusion approach by integrating dense electrical resistivity measurements collected with Schlumberger arrays and wellbore logs. This approach includes an optimization algorithm and a geostatistic interpolation method. We first generated an apparent formation factor model from the surface resistivity measurements and groundwater resistivity records with an inverse distance method. We then converted the model into a geology model with the optimized judgment criteria from the algorithms relating the apparent formation factors to the borehole geology. We also employed a non-parametric bootstrap method to analyze the uncertainty of the predicted sediment types, and the predictive uncertainties of clay, gravel, and sand were less than 5%. Overall, our model is capable of capturing the spatial features of the sediment types. More importantly, this approach can be arranged in a self-updated sequence to enable adjustments to the model to accommodate newly collected core records or geophysical data. This approach yields a more detailed apparent geological model for use in future groundwater simulations, which is of benefit to multi-discipline studies.
Estimating Hydraulic Conductivity Fields in Composite Fan Delta Using Vertical Electrical Sounding
(2018-11-01)
Chen, You-Cheng
;
Tsai, Jui-Pin
;
Chang, Liang-Cheng
;
Chang, Ping-Yu
;
Lin, Helen
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.
Spatial-temporal pattern recognition of groundwater head variations for recharge zone identification
(2017-06-01)
Tsai, Jui-Pin
;
Chang, Liang-Cheng
;
Chang, Ping-Yu
;
Lin, Yuan-Chien
;
Chen, You-Cheng
The delineation of groundwater recharge zones is crucial for the conservation of groundwater quality and quantity. To objectively estimate groundwater recharge zones, many field surveys are required that are costly in both time and money. To facilitate the assessment of recharge zones with high efficiency and low expense, this study proposes a 'fast-filter' approach based on empirical orthogonal function analysis and applies it in a synthetic case study and to Taiwan's Yilan Plain. In the synthetic case study, we demonstrate that the proposed method can effectively identify the recharge area by considering the head variations driven by rainfall recharge. For the case of Yilan Plain application, the field investigations (i.e., collected wellbore logs and electrical resistivity tomography [ERT] surveys) and a groundwater simulation model support the recharge zones estimated by the proposed method. The study results show that within the estimated recharge zone, all of the collected wellbore logs consist of coarse grains, and thick and continuous high resistivity zones were shown in the ERT profile images. Moreover, the groundwater model indicates that the recharge within the estimated recharge zone is 57.6% of the total recharge despite that the area of the estimated zone is only 26.8% of the study area. Therefore, the proposed method is shown to delineate recharge zones at low cost. (C) 2017 Elsevier B.V. All rights reserved.
Using the Resistivity Imaging Method to Monitor the Dynamic Effects on the Vadose Zone During Pumping Tests at the Pengtsuo Site in Pingtung, Taiwan
(2016-02)
Chang, Ping-Yu
;
Hsu, Shao-Yiu
;
Chang, Liang-Cheng
;
Chen, Wen-Fu
;
Chen, Yu-Wen
We conducted a time-lapse monitoring study during a well-pumping test at the Pengtsuo site in Pingtung, Taiwan. Water-level gauges were installed in four wells (P1, W1, O1, and O2) at the Pengtsuo site with different screen depths for the observation. We designed the pumping test to be executed in three phases: the background, the stepwise-pumping, and the continuous-pumping phases. The survey line crossed the four wells so that a comparison would be possible between the resistivity measurements and the water-level records. The resistivity differences relative to the pre-pumping background show that electrical resistivity imaging (ERI) can resolve changes due to dewatering from pumping activity. The time-lapse resistivity images reveal that the maximum resistivity increase took place at the locations in the vadose zone instead of at the ground-water surface. The variation in the resistivity differences in the vadose zone correlated to the change in groundwater level in the stepwise phase. On the other hand, the resistivity-difference change was not fully consistent with the groundwater-level change in the continuous-pumping phase. We attribute the abnormal ERI signals to the dynamic non-equilibrium of the water movement in the vadose zone. The findings suggest that pumping designs can affect the changing resistivity differences and water-content distribution patterns. We show the potential of the ER method to reveal both the water flow and water-content changes in the vadose zone with different transient boundary conditions.